gitlab debug

Ok/gitlab webhook

See merge request codiumai/pr-agent!1

.dockerignore

@@ -1,5 +1,3 @@
 venv/
 pr_agent/settings/.secrets.toml
-pics/
-pr_agent.egg-info/
-build/
+pics/

.github/workflows/build-and-test.yaml

@@ -1,39 +0,0 @@
-name: Build-and-test
-
-on:
-  push:
-    branches:
-      - main
-  pull_request:
-    branches:
-      - main
-
-jobs:
-  build-and-test:
-    runs-on: ubuntu-latest
-
-    steps:
-      - id: checkout
-        uses: actions/checkout@v2
-
-      - id: dockerx
-        name: Setup Docker Buildx
-        uses: docker/setup-buildx-action@v2
-
-      - id: build
-        name: Build dev docker
-        uses: docker/build-push-action@v2
-        with:
-          context: .
-          file: ./docker/Dockerfile
-          push: false
-          load: true
-          tags: codiumai/pr-agent:test
-          cache-from: type=gha,scope=dev
-          cache-to: type=gha,mode=max,scope=dev
-          target: test
-
-      - id: test
-        name: Test dev docker
-        run: |
-          docker run --rm codiumai/pr-agent:test pytest -v tests/unittest

.github/workflows/code_coverage.yaml

@@ -1,54 +0,0 @@
-name: Code-coverage
-
-on:
-  workflow_dispatch:
-  # push:
-  #   branches:
-  #     - main
-  pull_request:
-    branches:
-      - main
-
-jobs:
-  build-and-test:
-    runs-on: ubuntu-latest
-
-    steps:
-      - id: checkout
-        uses: actions/checkout@v2
-
-      - id: dockerx
-        name: Setup Docker Buildx
-        uses: docker/setup-buildx-action@v2
-
-      - id: build
-        name: Build dev docker
-        uses: docker/build-push-action@v2
-        with:
-          context: .
-          file: ./docker/Dockerfile
-          push: false
-          load: true
-          tags: codiumai/pr-agent:test
-          cache-from: type=gha,scope=dev
-          cache-to: type=gha,mode=max,scope=dev
-          target: test
-
-      - id: code_cov
-        name: Test dev docker
-        run: |
-          docker run --name test_container codiumai/pr-agent:test  pytest  tests/unittest --cov=pr_agent --cov-report term --cov-report xml:coverage.xml
-          docker cp test_container:/app/coverage.xml coverage.xml
-          docker rm test_container
-
-
-      - name: Validate coverage report
-        run: |
-          if [ ! -f coverage.xml ]; then
-            echo "Coverage report not found"
-            exit 1
-          fi
-      - name: Upload coverage to Codecov
-        uses: codecov/codecov-action@v4.0.1
-        with:
-          token: ${{ secrets.CODECOV_TOKEN }}

.github/workflows/docs-ci.yaml

@@ -1,33 +0,0 @@
-name: docs-ci
-on:
-  push:
-    branches:
-      - main
-      - add-docs-portal
-    paths:
-      - docs/**
-permissions:
-  contents: write
-jobs:
-  deploy:
-    runs-on: ubuntu-latest
-    steps:
-      - uses: actions/checkout@v4
-      - name: Configure Git Credentials
-        run: |
-          git config user.name github-actions[bot]
-          git config user.email 41898282+github-actions[bot]@users.noreply.github.com
-      - uses: actions/setup-python@v5
-        with:
-          python-version: 3.x
-      - run: echo "cache_id=$(date --utc '+%V')" >> $GITHUB_ENV
-      - uses: actions/cache@v4
-        with:
-          key: mkdocs-material-${{ env.cache_id }}
-          path: .cache
-          restore-keys: |
-            mkdocs-material-
-      - run: pip install mkdocs-material
-      - run: pip install "mkdocs-material[imaging]"
-      - run: pip install mkdocs-glightbox
-      - run: mkdocs gh-deploy -f docs/mkdocs.yml --force

.github/workflows/e2e_tests.yaml

@@ -1,46 +0,0 @@
-name: PR-Agent E2E tests
-
-on:
-  workflow_dispatch:
-#  schedule:
-#    - cron: '0 0 * * *' # This cron expression runs the workflow every night at midnight UTC
-
-jobs:
-  pr_agent_job:
-    runs-on: ubuntu-latest
-    name: PR-Agent E2E GitHub App Test
-    steps:
-      - name: Checkout repository
-        uses: actions/checkout@v2
-
-      - name: Setup Docker Buildx
-        uses: docker/setup-buildx-action@v2
-
-      - id: build
-        name: Build dev docker
-        uses: docker/build-push-action@v2
-        with:
-          context: .
-          file: ./docker/Dockerfile
-          push: false
-          load: true
-          tags: codiumai/pr-agent:test
-          cache-from: type=gha,scope=dev
-          cache-to: type=gha,mode=max,scope=dev
-          target: test
-
-      - id: test1
-        name: E2E test github app
-        run: |
-           docker run -e GITHUB.USER_TOKEN=${{ secrets.TOKEN_GITHUB }} --rm codiumai/pr-agent:test pytest -v tests/e2e_tests/test_github_app.py
-
-      - id: test2
-        name: E2E gitlab webhook
-        run: |
-          docker run -e gitlab.PERSONAL_ACCESS_TOKEN=${{ secrets.TOKEN_GITLAB }} --rm codiumai/pr-agent:test pytest -v tests/e2e_tests/test_gitlab_webhook.py
-
-
-      - id: test3
-        name: E2E bitbucket app
-        run: |
-          docker run -e BITBUCKET.USERNAME=${{ secrets.BITBUCKET_USERNAME }}  -e BITBUCKET.PASSWORD=${{ secrets.BITBUCKET_PASSWORD }} --rm codiumai/pr-agent:test pytest -v tests/e2e_tests/test_bitbucket_app.py

.github/workflows/pr-agent-review.yaml

@@ -1,32 +0,0 @@
-# This workflow enables developers to call PR-Agents `/[actions]` in PR's comments and upon PR creation.
-# Learn more at https://www.codium.ai/pr-agent/
-# This is v0.2 of this workflow file
-
-name: PR-Agent
-
-on:
-# pull_request:
-# issue_comment:
-  workflow_dispatch:
-
-permissions:
-  issues: write
-  pull-requests: write
-
-jobs:
-  pr_agent_job:
-    runs-on: ubuntu-latest
-    name: Run pr agent on every pull request
-    steps:
-      - name: PR Agent action step
-        id: pragent
-        uses: Codium-ai/pr-agent@main
-        env:
-          OPENAI_KEY: ${{ secrets.OPENAI_KEY }}
-          OPENAI_ORG: ${{ secrets.OPENAI_ORG }} # optional
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-          PINECONE.API_KEY: ${{ secrets.PINECONE_API_KEY }}
-          PINECONE.ENVIRONMENT: ${{ secrets.PINECONE_ENVIRONMENT }}
-          GITHUB_ACTION_CONFIG.AUTO_DESCRIBE: true
-          GITHUB_ACTION_CONFIG.AUTO_REVIEW: true
-          GITHUB_ACTION_CONFIG.AUTO_IMPROVE: true

.github/workflows/pre-commit.yml

@@ -1,17 +0,0 @@
-# disabled. We might run it manually if needed.
-name: pre-commit
-
-on:
-  workflow_dispatch:
-#  pull_request:
-#  push:
-#    branches: [main]
-
-jobs:
-  pre-commit:
-    runs-on: ubuntu-latest
-    steps:
-      - uses: actions/checkout@v3
-      - uses: actions/setup-python@v5
-      # SEE https://github.com/pre-commit/action
-      - uses: pre-commit/action@v3.0.1

.github/workflows/review.yaml

@@ -0,0 +1,16 @@
+on:
+  pull_request:
+  issue_comment:
+jobs:
+  pr_agent_job:
+    runs-on: ubuntu-latest
+    name: Run pr agent on every pull request
+    steps:
+      - name: PR Agent action step
+        id: pragent
+        uses: Codium-ai/pr-agent@main
+        env:
+          OPENAI_KEY: ${{ secrets.OPENAI_KEY }}
+          OPENAI_ORG: ${{ secrets.OPENAI_ORG }} # optional
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+

.gitignore

@@ -1,11 +1,4 @@
 .idea/
-.lsp/
-.vscode/
 venv/
 pr_agent/settings/.secrets.toml
-__pycache__
-dist/
-*.egg-info/
-build/
-.DS_Store
-docs/.cache/
+__pycache__

.gitlab-ci.yml

@@ -0,0 +1,11 @@
+bot-review:
+  stage: test
+  variables:
+    MR_URL: ${CI_MERGE_REQUEST_PROJECT_URL}/-/merge_requests/${CI_MERGE_REQUEST_IID}
+  image: docker:latest
+  services:
+    - docker:19-dind
+  script:
+    - docker run --rm -e OPENAI.KEY=${OPEN_API_KEY} -e OPENAI.ORG=${OPEN_API_ORG} -e GITLAB.PERSONAL_ACCESS_TOKEN=${GITLAB_PAT} -e CONFIG.GIT_PROVIDER=gitlab codiumai/pr-agent --pr_url ${MR_URL} describe
+  rules:
+    - if: $CI_COMMIT_BRANCH != $CI_DEFAULT_BRANCH

.pr_agent.toml

@@ -1,3 +0,0 @@
-[pr_reviewer]
-enable_review_labels_effort = true
-enable_auto_approval = true

.pre-commit-config.yaml

@@ -1,46 +0,0 @@
-# See https://pre-commit.com for more information
-# See https://pre-commit.com/hooks.html for more hooks
-
-default_language_version:
-  python: python3
-
-repos:
-  - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v5.0.0
-    hooks:
-      - id: check-added-large-files
-      - id: check-toml
-      - id: check-yaml
-      - id: end-of-file-fixer
-      - id: trailing-whitespace
-  # - repo: https://github.com/rhysd/actionlint
-  #   rev: v1.7.3
-  #   hooks:
-  #     - id: actionlint
-  - repo: https://github.com/pycqa/isort
-    # rev must match what's in dev-requirements.txt
-    rev: 5.13.2
-    hooks:
-      - id: isort
-  # - repo: https://github.com/PyCQA/bandit
-  #   rev: 1.7.10
-  #   hooks:
-  #     - id: bandit
-  #       args: [
-  #         "-c", "pyproject.toml",
-  #       ]
-  # - repo: https://github.com/astral-sh/ruff-pre-commit
-  #   rev: v0.7.1
-  #   hooks:
-  #     - id: ruff
-  #       args:
-  #         - --fix
-  #     - id: ruff-format
-  # -   repo: https://github.com/PyCQA/autoflake
-  #     rev: v2.3.1
-  #     hooks:
-  #     -   id: autoflake
-  #         args:
-  #           - --in-place
-  #           - --remove-all-unused-imports
-  #           - --remove-unused-variables

CHANGELOG.md

@@ -1,45 +0,0 @@
-## 2023-08-03
-
-### Optimized
-- Optimized PR diff processing by introducing caching for diff files, reducing the number of API calls.
-- Refactored `load_large_diff` function to generate a patch only when necessary.
-- Fixed a bug in the GitLab provider where the new file was not retrieved correctly.
-
-## 2023-08-02
-
-### Enhanced
-- Updated several tools in the `pr_agent` package to use commit messages in their functionality.
-- Commit messages are now retrieved and stored in the `vars` dictionary for each tool.
-- Added a section to display the commit messages in the prompts of various tools.
-
-## 2023-08-01
-
-### Enhanced
-- Introduced the ability to retrieve commit messages from pull requests across different git providers.
-- Implemented commit messages retrieval for GitHub and GitLab providers.
-- Updated the PR description template to include a section for commit messages if they exist.
-- Added support for repository-specific configuration files (.pr_agent.yaml) for the PR Agent.
-- Implemented this feature for both GitHub and GitLab providers.
-- Added a new configuration option 'use_repo_settings_file' to enable or disable the use of a repo-specific settings file.
-
-
-## 2023-07-30
-
-### Enhanced
-- Added the ability to modify any configuration parameter from 'configuration.toml' on-the-fly.
-- Updated the command line interface and bot commands to accept configuration changes as arguments.
-- Improved the PR agent to handle additional arguments for each action.
-
-## 2023-07-28
-
-### Improved
-- Enhanced error handling and logging in the GitLab provider.
-- Improved handling of inline comments and code suggestions in GitLab.
-- Fixed a bug where an additional unneeded line was added to code suggestions in GitLab.
-
-## 2023-07-26
-
-### Added
-- New feature for updating the CHANGELOG.md based on the contents of a PR.
-- Added support for this feature for the Github provider.
-- New configuration settings and prompts for the changelog update feature.

CONFIGURATION.md

@@ -0,0 +1,19 @@
+## Configuration
+
+The different tools and sub-tools used by CodiumAI pr-agent are easily configurable via the configuration file: `/pr-agent/settings/configuration.toml`.
+##### Git Provider:
+You can select your git_provider with the flag `git_provider` in the `config` section
+
+##### PR Reviewer:
+
+You can enable/disable the different PR Reviewer abilities with the following flags (`pr_reviewer` section):
+```
+require_focused_review=true
+require_score_review=true
+require_tests_review=true
+require_security_review=true
+```
+You can contol the number of suggestions returned by the PR Reviewer with the following flag:
+```inline_code_comments=3```
+And enable/disable the inline code suggestions with the following flag:
+```inline_code_comments=true```

Dockerfile.github_action

@@ -1,11 +1,9 @@
-FROM python:3.12 as base
+FROM python:3.10 as base
 
 WORKDIR /app
-ADD pyproject.toml .
 ADD requirements.txt .
-RUN pip install . && rm pyproject.toml requirements.txt
+RUN pip install -r requirements.txt && rm requirements.txt
 ENV PYTHONPATH=/app
-ADD docs docs
 ADD pr_agent pr_agent
 ADD github_action/entrypoint.sh /
 RUN chmod +x /entrypoint.sh

INSTALL.md

@@ -0,0 +1,218 @@
+
+## Installation
+
+---
+
+#### Method 1: Use Docker image (no installation required)
+
+To request a review for a PR, or ask a question about a PR, you can run directly from the Docker image. Here's how:
+
+1. To request a review for a PR, run the following command:
+
+```
+docker run --rm -it -e OPENAI.KEY=<your key> -e GITHUB.USER_TOKEN=<your token> codiumai/pr-agent --pr_url <pr_url> review
+```
+
+2. To ask a question about a PR, run the following command:
+
+```
+docker run --rm -it -e OPENAI.KEY=<your key> -e GITHUB.USER_TOKEN=<your token> codiumai/pr-agent --pr_url <pr_url> ask "<your question>"
+```
+
+Possible questions you can ask include:
+
+- What is the main theme of this PR?
+- Is the PR ready for merge?
+- What are the main changes in this PR?
+- Should this PR be split into smaller parts?
+- Can you compose a rhymed song about this PR?
+
+---
+
+#### Method 2: Run as a GitHub Action
+
+You can use our pre-built Github Action Docker image to run PR-Agent as a Github Action. 
+
+1. Add the following file to your repository under `.github/workflows/pr_agent.yml`:
+
+```yaml
+on:
+  pull_request:
+  issue_comment:
+jobs:
+  pr_agent_job:
+    runs-on: ubuntu-latest
+    name: Run pr agent on every pull request, respond to user comments
+    steps:
+      - name: PR Agent action step
+        id: pragent
+        uses: Codium-ai/pr-agent@main
+        env:
+          OPENAI_KEY: ${{ secrets.OPENAI_KEY }}
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+```
+
+2. Add the following secret to your repository under `Settings > Secrets`:
+
+```
+OPENAI_KEY: <your key>
+```
+
+The GITHUB_TOKEN secret is automatically created by GitHub.
+
+3. Merge this change to your main branch. 
+When you open your next PR, you should see a comment from `github-actions` bot with a review of your PR, and instructions on how to use the rest of the tools.
+
+4. You may configure PR-Agent by adding environment variables under the env section corresponding to any configurable property in the [configuration](./CONFIGURATION.md) file. Some examples:
+```yaml
+      env:
+        # ... previous environment values
+        OPENAI.ORG: "<Your organization name under your OpenAI account>"
+        PR_REVIEWER.REQUIRE_TESTS_REVIEW: "false" # Disable tests review
+        PR_CODE_SUGGESTIONS.NUM_CODE_SUGGESTIONS: 6 # Increase number of code suggestions
+```
+
+---
+
+#### Method 3: Run from source
+
+1. Clone this repository:
+
+```
+git clone https://github.com/Codium-ai/pr-agent.git
+```
+
+2. Install the requirements in your favorite virtual environment:
+
+```
+pip install -r requirements.txt
+```
+
+3. Copy the secrets template file and fill in your OpenAI key and your GitHub user token:
+
+```
+cp pr_agent/settings/.secrets_template.toml pr_agent/settings/.secrets.toml
+# Edit .secrets.toml file
+```
+
+4. Add the pr_agent folder to your PYTHONPATH, then run the cli.py script:
+
+```
+export PYTHONPATH=[$PYTHONPATH:]<PATH to pr_agent folder>
+python pr_agent/cli.py --pr_url <pr_url> review
+python pr_agent/cli.py --pr_url <pr_url> ask <your question>
+python pr_agent/cli.py --pr_url <pr_url> describe
+python pr_agent/cli.py --pr_url <pr_url> improve
+```
+
+---
+
+#### Method 4: Run as a polling server
+Request reviews by tagging your Github user on a PR
+
+Follow steps 1-3 of method 2.
+Run the following command to start the server:
+
+```
+python pr_agent/servers/github_polling.py
+```
+
+---
+
+#### Method 5: Run as a GitHub App
+Allowing you to automate the review process on your private or public repositories.
+
+1. Create a GitHub App from the [Github Developer Portal](https://docs.github.com/en/developers/apps/creating-a-github-app).
+
+   - Set the following permissions:
+     - Pull requests: Read & write
+     - Issue comment: Read & write
+     - Metadata: Read-only
+   - Set the following events:
+     - Issue comment
+     - Pull request
+
+2. Generate a random secret for your app, and save it for later. For example, you can use:
+
+```
+WEBHOOK_SECRET=$(python -c "import secrets; print(secrets.token_hex(10))")
+```
+
+3. Acquire the following pieces of information from your app's settings page:
+
+   - App private key (click "Generate a private key" and save the file)
+   - App ID
+
+4. Clone this repository:
+
+```
+git clone https://github.com/Codium-ai/pr-agent.git
+```
+
+5. Copy the secrets template file and fill in the following:
+    ```
+    cp pr_agent/settings/.secrets_template.toml pr_agent/settings/.secrets.toml
+    # Edit .secrets.toml file
+    ```
+   - Your OpenAI key.
+   - Copy your app's private key to the private_key field.
+   - Copy your app's ID to the app_id field.
+   - Copy your app's webhook secret to the webhook_secret field.
+   - Set deployment_type to 'app' in [configuration.toml](./pr_agent/settings/configuration.toml)
+
+> The .secrets.toml file is not copied to the Docker image by default, and is only used for local development. 
+> If you want to use the .secrets.toml file in your Docker image, you can add remove it from the .dockerignore file.
+> In most production environments, you would inject the secrets file as environment variables or as mounted volumes. 
+> For example, in order to inject a secrets file as a volume in a Kubernetes environment you can update your pod spec to include the following,
+> assuming you have a secret named `pr-agent-settings` with a key named `.secrets.toml`:
+``` 
+       volumes:
+        - name: settings-volume
+          secret:
+            secretName: pr-agent-settings
+// ...
+       containers:
+// ...
+          volumeMounts:
+            - mountPath: /app/pr_agent/settings_prod
+              name: settings-volume
+```
+
+> Another option is to set the secrets as environment variables in your deployment environment, for example `OPENAI.KEY` and `GITHUB.USER_TOKEN`.
+
+6. Build a Docker image for the app and optionally push it to a Docker repository. We'll use Dockerhub as an example:
+
+```
+docker build . -t codiumai/pr-agent:github_app --target github_app -f docker/Dockerfile
+docker push codiumai/pr-agent:github_app  # Push to your Docker repository
+```
+
+7. Host the app using a server, serverless function, or container environment. Alternatively, for development and
+   debugging, you may use tools like smee.io to forward webhooks to your local machine.
+    You can check [Deploy as a Lambda Function](#deploy-as-a-lambda-function)
+
+8. Go back to your app's settings, and set the following:
+
+   - Webhook URL: The URL of your app's server or the URL of the smee.io channel.
+   - Webhook secret: The secret you generated earlier.
+
+9. Install the app by navigating to the "Install App" tab and selecting your desired repositories.
+
+---
+
+####  Deploy as a Lambda Function
+
+1. Follow steps 1-5 of [Method 5](#method-5-run-as-a-github-app).
+2. Build a docker image that can be used as a lambda function
+    ```shell
+    docker buildx build --platform=linux/amd64 . -t codiumai/pr-agent:serverless -f docker/Dockerfile.lambda
+   ```
+3. Push image to ECR
+    ```shell
+	docker tag codiumai/pr-agent:serverless <AWS_ACCOUNT>.dkr.ecr.<AWS_REGION>.amazonaws.com/codiumai/pr-agent:serverless
+	docker push <AWS_ACCOUNT>.dkr.ecr.<AWS_REGION>.amazonaws.com/codiumai/pr-agent:serverless
+    ```
+4. Create a lambda function that uses the uploaded image. Set the lambda timeout to be at least 3m.
+5. Configure the lambda function to have a Function URL.
+6. Go back to steps 8-9 of [Method 5](#method-5-run-as-a-github-app) with the function url as your Webhook URL.
+    The Webhook URL would look like `https://<LAMBDA_FUNCTION_URL>/api/v1/github_webhooks`

LICENSE

@@ -199,4 +199,4 @@
    distributed under the License is distributed on an "AS IS" BASIS,
    WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    See the License for the specific language governing permissions and
-   limitations under the License.
+   limitations under the License.

MANIFEST.in

@@ -1,2 +0,0 @@
-recursive-include pr_agent *.toml
-recursive-exclude pr_agent *.secrets.toml

PR_COMPRESSION.md

@@ -1,47 +1,42 @@
-
-## Overview - PR Compression Strategy
+# Git Patch Logic
 There are two scenarios:
-
 1. The PR is small enough to fit in a single prompt (including system and user prompt)
 2. The PR is too large to fit in a single prompt (including system and user prompt)
 
 For both scenarios, we first use the following strategy
-
 #### Repo language prioritization strategy
-We prioritize the languages of the repo based on the following criteria:
 
+We prioritize the languages of the repo based on the following criteria:
 1. Exclude binary files and non code files (e.g. images, pdfs, etc)
 2. Given the main languages used in the repo
-3. We sort the PR files by the most common languages in the repo (in descending order):
+2. We sort the PR files by the most common languages in the repo (in descending order): 
    * ```[[file.py, file2.py],[file3.js, file4.jsx],[readme.md]]```
+   
 
-
-### Small PR
+## Small PR
 In this case, we can fit the entire PR in a single prompt:
 1. Exclude binary files and non code files (e.g. images, pdfs, etc)
-2. We Expand the surrounding context of each patch to 3 lines above and below the patch
+2. We Expand the surrounding context of each patch to 6 lines above and below the patch
+## Large PR
 
-### Large PR
-
-#### Motivation
+### Motivation
 Pull Requests can be very long and contain a lot of information with varying degree of relevance to the pr-agent.
 We want to be able to pack as much information as possible in a single LMM prompt, while keeping the information relevant to the pr-agent.
 
-#### Compression strategy
+
+
+#### PR compression strategy
 We prioritize additions over deletions:
  - Combine all deleted files into a single list (`deleted files`)
  - File patches are a list of hunks, remove all hunks of type deletion-only from the hunks in the file patch
-
 ####  Adaptive and token-aware file patch fitting
 We use [tiktoken](https://github.com/openai/tiktoken) to tokenize the patches after the modifications described above, and we use the following strategy to fit the patches into the prompt:
-
-1. Within each language we sort the files by the number of tokens in the file (in descending order):
-    - ```[[file2.py, file.py],[file4.jsx, file3.js],[readme.md]]```
+1. Withing each language we sort the files by the number of tokens in the file (in descending order):
+   * ```[[file2.py, file.py],[file4.jsx, file3.js],[readme.md]]```
 2. Iterate through the patches in the order described above
-3. Add the patches to the prompt until the prompt reaches a certain buffer from the max token length
-4. If there are still patches left, add the remaining patches as a list called `other modified files` to the prompt until the prompt reaches the max token length (hard stop), skip the rest of the patches.
-5. If we haven't reached the max token length, add the `deleted files` to the prompt until the prompt reaches the max token length (hard stop), skip the rest of the patches.
+2. Add the patches to the prompt until the prompt reaches a certain buffer from the max token length
+3. If there are still patches left, add the remaining patches as a list called `other modified files` to the prompt until the prompt reaches the max token length (hard stop), skip the rest of the patches.
+4. If we haven't reached the max token length, add the `deleted files` to the prompt until the prompt reaches the max token length (hard stop), skip the rest of the patches.
 
-#### Example
-
-![Core Abilities](https://codium.ai/images/git_patch_logic.png){width=768}
+### Example
+![](https://codium.ai/images/git_patch_logic.png)

README.md

@@ -2,304 +2,169 @@
 
 <div align="center">
 
-
-<picture>
-  <source media="(prefers-color-scheme: dark)" srcset="https://codium.ai/images/pr_agent/logo-dark.png" width="330">
-  <source media="(prefers-color-scheme: light)" srcset="https://codium.ai/images/pr_agent/logo-light.png" width="330">
-  <img src="https://codium.ai/images/pr_agent/logo-light.png" alt="logo" width="330">
-
-</picture>
-<br/>
-Qode Merge PR-Agent aims to help efficiently review and handle pull requests, by providing AI feedback and suggestions
+<img src="./pics/logo-dark.png#gh-dark-mode-only" width="330"/>
+<img src="./pics/logo-light.png#gh-light-mode-only" width="330"/><br/>
+Making pull requests less painful with an AI agent
 </div>
 
-[![Static Badge](https://img.shields.io/badge/Chrome-Extension-violet)](https://chromewebstore.google.com/detail/pr-agent-chrome-extension/ephlnjeghhogofkifjloamocljapahnl)
-[![Static Badge](https://img.shields.io/badge/Pro-App-blue)](https://github.com/apps/qodo-merge-pro/)
-[![Static Badge](https://img.shields.io/badge/OpenSource-App-red)](https://github.com/apps/qodo-merge-pro-for-open-source/)
+[![GitHub license](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://github.com/Codium-ai/pr-agent/blob/main/LICENSE)
 [![Discord](https://badgen.net/badge/icon/discord?icon=discord&label&color=purple)](https://discord.com/channels/1057273017547378788/1126104260430528613)
-<a href="https://github.com/Codium-ai/pr-agent/commits/main">
-<img alt="GitHub" src="https://img.shields.io/github/last-commit/Codium-ai/pr-agent/main?style=for-the-badge" height="20">
-</a>
+    <a href="https://github.com/Codium-ai/pr-agent/commits/main">
+    <img alt="GitHub" src="https://img.shields.io/github/last-commit/Codium-ai/pr-agent/main?style=for-the-badge" height="20">
+    </a>
 </div>
-
-### [Documentation](https://pr-agent-docs.codium.ai/)
-- See the [Installation Guide](https://qodo-merge-docs.qodo.ai/installation/) for instructions on installing Qode Merge PR-Agent on different platforms.
-
-- See the [Usage Guide](https://qodo-merge-docs.qodo.ai/usage-guide/) for instructions on running Qode Merge PR-Agent tools via different interfaces, such as CLI, PR Comments, or by automatically triggering them when a new PR is opened.
-
-- See the [Tools Guide](https://qodo-merge-docs.qodo.ai/tools/) for a detailed description of the different tools, and the available configurations for each tool.
-
-
-## Table of Contents
-- [News and Updates](#news-and-updates)
-- [Overview](#overview)
-- [Example results](#example-results)
-- [Try it now](#try-it-now)
-- [PR-Agent Pro 💎](https://pr-agent-docs.codium.ai/overview/pr_agent_pro/)
-- [How it works](#how-it-works)
-- [Why use PR-Agent?](#why-use-pr-agent)
-
-## News and Updates
-
-### December 2, 2024
-
-Open-source repositories can now freely use Qodo Merge Pro, and enjoy easy one-click installation using a marketplace [app](https://github.com/apps/qodo-merge-pro-for-open-source).
-
-<kbd><img src="https://github.com/user-attachments/assets/b0838724-87b9-43b0-ab62-73739a3a855c" width="512"></kbd>
-
-See [here](https://qodo-merge-docs.qodo.ai/installation/pr_agent_pro/) for more details about installing Qodo Merge Pro for private repositories.
-
-
-### November 18, 2024
-
-A new mode was enabled by default for code suggestions - `--pr_code_suggestions.focus_only_on_problems=true`:
-
-- This option reduces the number of code suggestions received
-- The suggestions will focus more on identifying and fixing code problems, rather than style considerations like best practices, maintainability, or readability.
-- The suggestions will be categorized into just two groups: "Possible Issues" and "General".
-
-Still, if you prefer the previous mode, you can set `--pr_code_suggestions.focus_only_on_problems=false` in the [configuration file](https://qodo-merge-docs.qodo.ai/usage-guide/configuration_options/).
-
-**Example results:**
-
-Original mode
-
-<kbd><img src="https://qodo.ai/images/pr_agent/code_suggestions_original_mode.png" width="512"></kbd>
-
-Focused mode
-
-<kbd><img src="https://qodo.ai/images/pr_agent/code_suggestions_focused_mode.png" width="512"></kbd>
-
-
-### November 4, 2024
-
-Qodo Merge PR Agent will now leverage context from Jira or GitHub tickets to enhance the PR Feedback. Read more about this feature
-[here](https://qodo-merge-docs.qodo.ai/core-abilities/fetching_ticket_context/)
-
-
-## Overview
 <div style="text-align:left;">
 
-Supported commands per platform:
+CodiumAI `PR-Agent` is an open-source tool aiming to help developers review pull requests faster and more efficiently. It automatically analyzes the pull request and can provide several types of feedback:
 
-|       |                                                                                                         | GitHub             | GitLab             | Bitbucket          | Azure DevOps |
-|-------|---------------------------------------------------------------------------------------------------------|:--------------------:|:--------------------:|:--------------------:|:------------:|
-| TOOLS | [Review](https://qodo-merge-docs.qodo.ai/tools/review/)                                                                                                  | ✅ | ✅ | ✅ |      ✅       |
-|       | [Describe](https://qodo-merge-docs.qodo.ai/tools/describe/)                                                                                                | ✅ | ✅ | ✅ |      ✅       |
-|       | [Improve](https://qodo-merge-docs.qodo.ai/tools/improve/)                                                                                                 | ✅ | ✅ | ✅ |      ✅       |
-|       | [Ask](https://qodo-merge-docs.qodo.ai/tools/ask/)                                                                                                     | ✅ | ✅ | ✅ |      ✅       |
-|       | ⮑ [Ask on code lines](https://pr-agent-docs.codium.ai/tools/ask#ask-lines)                              | ✅ | ✅ |                    |              |
-|       | [Update CHANGELOG](https://qodo-merge-docs.qodo.ai/tools/update_changelog/)                                                                                     | ✅ | ✅ | ✅ |      ✅       |
-|       | [Ticket Context](https://qodo-merge-docs.qodo.ai/core-abilities/fetching_ticket_context/) 💎  | ✅ | ✅ |  ✅                  |   |
-|       | [Utilizing Best Practices](https://qodo-merge-docs.qodo.ai/tools/improve/#best-practices) 💎  | ✅ | ✅ |  ✅                  |   |
-|       | [PR Chat](https://qodo-merge-docs.qodo.ai/chrome-extension/features/#pr-chat) 💎  | ✅ |  |                    |   |
-|       | [Suggestion Tracking](https://qodo-merge-docs.qodo.ai/tools/improve/#suggestion-tracking) 💎  | ✅ | ✅ |                    |   |
-|       | [CI Feedback](https://pr-agent-docs.codium.ai/tools/ci_feedback/) 💎                                    | ✅ |                    |                    |              |
-|       | [PR Documentation](https://pr-agent-docs.codium.ai/tools/documentation/) 💎                         | ✅ | ✅ |                   |              |
-|       | [Custom Labels](https://pr-agent-docs.codium.ai/tools/custom_labels/) 💎                                | ✅ | ✅ |                    |              |
-|       | [Analyze](https://pr-agent-docs.codium.ai/tools/analyze/) 💎                                            | ✅ | ✅ |                    |              |
-|       | [Similar Code](https://pr-agent-docs.codium.ai/tools/similar_code/) 💎                                  | ✅ |                    |                    |              |
-|       | [Custom Prompt](https://pr-agent-docs.codium.ai/tools/custom_prompt/) 💎                                | ✅ | ✅ | ✅ |              |
-|       | [Test](https://pr-agent-docs.codium.ai/tools/test/) 💎                                                  | ✅ | ✅ |                    |              |
-|       |                                                                                                         |                    |                    |                    |              |
-| USAGE | [CLI](https://qodo-merge-docs.qodo.ai/usage-guide/automations_and_usage/#local-repo-cli)                                                                                                     | ✅ | ✅ | ✅ |      ✅       |
-|       | [App / webhook](https://qodo-merge-docs.qodo.ai/usage-guide/automations_and_usage/#github-app)                                                                                           | ✅ | ✅ | ✅ |      ✅       |
-|       | [Tagging bot](https://github.com/Codium-ai/pr-agent#try-it-now)                                                                                             | ✅ |                    |                    |              |
-|       | [Actions](https://qodo-merge-docs.qodo.ai/installation/github/#run-as-a-github-action)                                                                                                 | ✅ |✅| ✅ |✅|
-|       |                                                                                                         |                    |                    |                    |              |
-| CORE  | [PR compression](https://qodo-merge-docs.qodo.ai/core-abilities/compression_strategy/)                                                                  | ✅ | ✅ | ✅ |      ✅       |
-|       | Adaptive and token-aware file patch fitting                                                             | ✅ | ✅ | ✅ |      ✅       |
-|       | [Multiple models support](https://qodo-merge-docs.qodo.ai/usage-guide/changing_a_model/)                                                                                 | ✅ | ✅ | ✅ |      ✅       |
-|       | [Local and global metadata](https://qodo-merge-docs.qodo.ai/core-abilities/metadata/)          | ✅ | ✅ | ✅ | ✅             |
-|       | [Dynamic context](https://qodo-merge-docs.qodo.ai/core-abilities/dynamic_context/)          | ✅ | ✅ | ✅ | ✅             |
-|       | [Self reflection](https://qodo-merge-docs.qodo.ai/core-abilities/self_reflection/)          | ✅ | ✅ | ✅ | ✅             |
-|       | [Static code analysis](https://qodo-merge-docs.qodo.ai/core-abilities/static_code_analysis/) 💎         | ✅ | ✅ | ✅ |              |
-|       | [Global and wiki configurations](https://pr-agent-docs.codium.ai/usage-guide/configuration_options/) 💎 | ✅ | ✅ | ✅ |              |
-|       | [PR interactive actions](https://www.codium.ai/images/pr_agent/pr-actions.mp4) 💎                       | ✅ |        ✅           |                    |              |
-|       | [Impact Evaluation](https://qodo-merge-docs.qodo.ai/core-abilities/impact_evaluation/) 💎  | ✅ | ✅ |                    |   |
-- 💎 means this feature is available only in [PR-Agent Pro](https://www.codium.ai/pricing/)
+**Auto-Description**: Automatically generating PR description - title, type, summary, code walkthrough and PR labels.
+\
+**PR Review**: Adjustable feedback about the PR main theme, type, relevant tests, security issues, focus, score, and various suggestions for the PR content.
+\
+**Question Answering**: Answering free-text questions about the PR.
+\
+**Code Suggestion**: Committable code suggestions for improving the PR.
 
-[//]: # (- Support for additional git providers is described in [here]&#40;./docs/Full_environments.md&#41;)
-___
-
-‣ **Auto Description ([`/describe`](https://pr-agent-docs.codium.ai/tools/describe/))**: Automatically generating PR description - title, type, summary, code walkthrough and labels.
-\
-‣ **Auto Review ([`/review`](https://pr-agent-docs.codium.ai/tools/review/))**: Adjustable feedback about the PR, possible issues, security concerns, review effort and more.
-\
-‣ **Code Suggestions ([`/improve`](https://pr-agent-docs.codium.ai/tools/improve/))**: Code suggestions for improving the PR.
-\
-‣ **Question Answering ([`/ask ...`](https://pr-agent-docs.codium.ai/tools/ask/))**: Answering free-text questions about the PR.
-\
-‣ **Update Changelog ([`/update_changelog`](https://pr-agent-docs.codium.ai/tools/update_changelog/))**: Automatically updating the CHANGELOG.md file with the PR changes.
-\
-‣ **Find Similar Issue ([`/similar_issue`](https://pr-agent-docs.codium.ai/tools/similar_issues/))**: Automatically retrieves and presents similar issues.
-\
-‣ **Add Documentation 💎  ([`/add_docs`](https://pr-agent-docs.codium.ai/tools/documentation/))**: Generates documentation to methods/functions/classes that changed in the PR.
-\
-‣ **Generate Custom Labels 💎 ([`/generate_labels`](https://pr-agent-docs.codium.ai/tools/custom_labels/))**: Generates custom labels for the PR, based on specific guidelines defined by the user.
-\
-‣ **Analyze 💎 ([`/analyze`](https://pr-agent-docs.codium.ai/tools/analyze/))**: Identify code components that changed in the PR, and enables to interactively generate tests, docs, and code suggestions for each component.
-\
-‣ **Custom Prompt 💎 ([`/custom_prompt`](https://pr-agent-docs.codium.ai/tools/custom_prompt/))**: Automatically generates custom suggestions for improving the PR code, based on specific guidelines defined by the user.
-\
-‣ **Generate Tests 💎 ([`/test component_name`](https://pr-agent-docs.codium.ai/tools/test/))**: Generates unit tests for a selected component, based on the PR code changes.
-\
-‣ **CI Feedback 💎 ([`/checks ci_job`](https://pr-agent-docs.codium.ai/tools/ci_feedback/))**: Automatically generates feedback and analysis for a failed CI job.
-\
-‣ **Similar Code 💎 ([`/find_similar_component`](https://pr-agent-docs.codium.ai/tools/similar_code/))**: Retrieves the most similar code components from inside the organization's codebase, or from open-source code.
-___
-
-## Example results
+<h3>Example results:</h2>
 </div>
-<h4><a href="https://github.com/Codium-ai/pr-agent/pull/530">/describe</a></h4>
+<h4>/describe:</h4>
 <div align="center">
 <p float="center">
-<img src="https://www.codium.ai/images/pr_agent/describe_new_short_main.png" width="512">
+<img src="https://www.codium.ai/images/describe-2.gif" width="800">
 </p>
 </div>
-<hr>
-
-<h4><a href="https://github.com/Codium-ai/pr-agent/pull/732#issuecomment-1975099151">/review</a></h4>
+<h4>/review:</h4>
 <div align="center">
 <p float="center">
-<kbd>
-<img src="https://www.codium.ai/images/pr_agent/review_new_short_main.png" width="512">
-</kbd>
+<img src="https://www.codium.ai/images/review-2.gif" width="800">
 </p>
 </div>
-<hr>
-
-<h4><a href="https://github.com/Codium-ai/pr-agent/pull/732#issuecomment-1975099159">/improve</a></h4>
+<h4>/reflect_and_review:</h4>
 <div align="center">
 <p float="center">
-<kbd>
-<img src="https://www.codium.ai/images/pr_agent/improve_new_short_main.png" width="512">
-</kbd>
+<img src="https://www.codium.ai/images/reflect_and_review.gif" width="800">
+</p>
+</div>
+<h4>/ask:</h4>
+<div align="center">
+<p float="center">
+<img src="https://www.codium.ai/images/ask-2.gif" width="800">
+</p>
+</div>
+<h4>/improve:</h4>
+<div align="center">
+<p float="center">
+<img src="https://www.codium.ai/images/improve-2.gif" width="800">
 </p>
 </div>
-
-
-
-
-[//]: # (<h4><a href="https://github.com/Codium-ai/pr-agent/pull/78#issuecomment-1639739496">/reflect_and_review:</a></h4>)
-
-[//]: # (<div align="center">)
-
-[//]: # (<p float="center">)
-
-[//]: # (<img src="https://www.codium.ai/images/reflect_and_review.gif" width="800">)
-
-[//]: # (</p>)
-
-[//]: # (</div>)
-
-[//]: # (<h4><a href="https://github.com/Codium-ai/pr-agent/pull/229#issuecomment-1695020538">/ask:</a></h4>)
-
-[//]: # (<div align="center">)
-
-[//]: # (<p float="center">)
-
-[//]: # (<img src="https://www.codium.ai/images/ask-2.gif" width="800">)
-
-[//]: # (</p>)
-
-[//]: # (</div>)
-
-[//]: # (<h4><a href="https://github.com/Codium-ai/pr-agent/pull/229#issuecomment-1695024952">/improve:</a></h4>)
-
-[//]: # (<div align="center">)
-
-[//]: # (<p float="center">)
-
-[//]: # (<img src="https://www.codium.ai/images/improve-2.gif" width="800">)
-
-[//]: # (</p>)
-
-[//]: # (</div>)
 <div align="left">
 
 
+- [Overview](#overview)
+- [Try it now](#try-it-now)
+- [Installation](#installation)
+- [Usage and tools](#usage-and-tools)
+- [Configuration](./CONFIGURATION.md)
+- [How it works](#how-it-works)
+- [Roadmap](#roadmap)
+- [Similar projects](#similar-projects)
 </div>
-<hr>
 
 
+## Overview
+`PR-Agent` offers extensive pull request functionalities across various git providers:
+|       |                                             | GitHub | Gitlab | Bitbucket |
+|-------|---------------------------------------------|:------:|:------:|:---------:|
+| TOOLS | Review                                      |   :white_check_mark:    |   :white_check_mark:    |   :white_check_mark:       |
+|       | ⮑ Inline review                             |   :white_check_mark:    |   :white_check_mark:    |           |
+|       | Ask                                         |   :white_check_mark:    |   :white_check_mark:    |           |
+|       | Auto-Description                            |   :white_check_mark:    |  :white_check_mark:      |           |
+|       | Improve Code                                |   :white_check_mark:    |   :white_check_mark:    |           |
+|       | Reflect and Review                          |   :white_check_mark:    |                         |           |
+|       |                                             |        |        |           |
+| USAGE | CLI                                         |   :white_check_mark:    |   :white_check_mark:    |   :white_check_mark:       |
+|       | Tagging bot                                 |   :white_check_mark:    |        |           |
+|       | Actions                                     |   :white_check_mark:    |        |           |
+|       |                                             |        |        |           |
+| CORE  | PR compression                              |   :white_check_mark:    |   :white_check_mark:    |   :white_check_mark:       |
+|       | Repo language prioritization                |   :white_check_mark:    |   :white_check_mark:    |   :white_check_mark:       |
+|       | Adaptive and token-aware<br />file patch fitting |   :white_check_mark:    |   :white_check_mark:    |   :white_check_mark:       |
+|       | Incremental PR Review |   :white_check_mark:    |      |         |
+
+Examples for invoking the different tools via the CLI:
+- **Review**:       python cli.py --pr-url=<pr_url>  review
+- **Describe**:     python cli.py --pr-url=<pr_url>  describe
+- **Improve**:      python cli.py --pr-url=<pr_url>  improve
+- **Ask**:          python cli.py --pr-url=<pr_url>  ask "Write me a poem about this PR"
+- **Reflect**:      python cli.py --pr-url=<pr_url>  reflect
+
+"<pr_url>" is the url of the relevant PR (for example: https://github.com/Codium-ai/pr-agent/pull/50).
+
+In the [configuration](./CONFIGURATION.md) file you can select your git provider (GitHub, Gitlab, Bitbucket), and further configure the different tools.
+
 ## Try it now
 
-Try the GPT-4 powered PR-Agent instantly on _your public GitHub repository_. Just mention `@CodiumAI-Agent` and add the desired command in any PR comment. The agent will generate a response based on your command.
-For example, add a comment to any pull request with the following text:
-```
-@CodiumAI-Agent /review
-```
-and the agent will respond with a review of your PR.
-
-Note that this is a promotional bot, suitable only for initial experimentation.
-It does not have 'edit' access to your repo, for example, so it cannot update the PR description or add labels (`@CodiumAI-Agent /describe` will publish PR description as a comment). In addition, the bot cannot be used on private repositories, as it does not have access to the files there.
-
+Try GPT-4 powered PR-Agent on your public GitHub repository for free. Just mention `@CodiumAI-Agent` and add the desired command in any PR comment! The agent will generate a response based on your command.
 
 ![Review generation process](https://www.codium.ai/images/demo-2.gif)
 
-
-To set up your own PR-Agent, see the [Installation](https://pr-agent-docs.codium.ai/installation/) section below.
-Note that when you set your own PR-Agent or use CodiumAI hosted PR-Agent, there is no need to mention `@CodiumAI-Agent ...`. Instead, directly start with the command, e.g., `/ask ...`.
+To set up your own PR-Agent, see the [Installation](#installation) section
 
 ---
 
+## Installation
 
-## PR-Agent Pro 💎
-[PR-Agent Pro](https://www.codium.ai/pricing/) is a hosted version of PR-Agent, provided by CodiumAI. It is available for a monthly fee, and provides the following benefits:
-1. **Fully managed** - We take care of everything for you - hosting, models, regular updates, and more. Installation is as simple as signing up and adding the PR-Agent app to your GitHub\GitLab\BitBucket repo.
-2. **Improved privacy** - No data will be stored or used to train models. PR-Agent Pro will employ zero data retention, and will use an OpenAI account with zero data retention.
-3. **Improved support** - PR-Agent Pro users will receive priority support, and will be able to request new features and capabilities.
-4. **Extra features** -In addition to the benefits listed above, PR-Agent Pro will emphasize more customization, and the usage of static code analysis, in addition to LLM logic, to improve results.
-See [here](https://qodo-merge-docs.qodo.ai/overview/pr_agent_pro/) for a list of features available in PR-Agent Pro.
+To get started with PR-Agent quickly, you first need to acquire two tokens:
 
+1. An OpenAI key from [here](https://platform.openai.com/), with access to GPT-4.
+2. A GitHub personal access token (classic) with the repo scope.
 
+There are several ways to use PR-Agent:
+
+- [Method 1: Use Docker image (no installation required)](INSTALL.md#method-1-use-docker-image-no-installation-required)
+- [Method 2: Run as a GitHub Action](INSTALL.md#method-2-run-as-a-github-action)
+- [Method 3: Run from source](INSTALL.md#method-3-run-from-source)
+- [Method 4: Run as a polling server](INSTALL.md#method-4-run-as-a-polling-server)
+  - Request reviews by tagging your GitHub user on a PR
+- [Method 5: Run as a GitHub App](INSTALL.md#method-5-run-as-a-github-app)
+  - Allowing you to automate the review process on your private or public repositories
+
+## Usage and Tools
+
+**PR-Agent** provides five types of interactions ("tools"): `"PR Reviewer"`, `"PR Q&A"`, `"PR Description"`, `"PR Code Sueggestions"` and `"PR Reflect and Review"`.
+
+- The "PR Reviewer" tool automatically analyzes PRs, and provides various types of feedback.
+- The "PR Q&A" tool answers free-text questions about the PR.
+- The "PR Description" tool automatically sets the PR Title and body.
+- The "PR Code Suggestion" tool provide inline code suggestions for the PR that can be applied and committed.
+- The "PR Reflect and Review" tool initiates a dialog with the user, asks them to reflect on the PR, and then provides a more focused review.
 
 ## How it works
 
-The following diagram illustrates PR-Agent tools and their flow:
+![PR-Agent Tools](https://www.codium.ai/wp-content/uploads/2023/07/codiumai-diagram-v4.jpg)
 
-![PR-Agent Tools](https://codium.ai/images/pr_agent/diagram-v0.9.png)
+Check out the [PR Compression strategy](./PR_COMPRESSION.md) page for more details on how we convert a code diff to a manageable LLM prompt
 
-Check out the [PR Compression strategy](https://pr-agent-docs.codium.ai/core-abilities/#pr-compression-strategy) page for more details on how we convert a code diff to a manageable LLM prompt
+## Roadmap
 
-## Why use PR-Agent?
+- [ ] Support open-source models, as a replacement for OpenAI models. (Note - a minimal requirement for each open-source model is to have 8k+ context, and good support for generating JSON as an output)
+- [x] Support other Git providers, such as Gitlab and Bitbucket.
+- [ ] Develop additional logic for handling large PRs, and compressing git patches
+- [ ] Add additional context to the prompt. For example, repo (or relevant files) summarization, with tools such a [ctags](https://github.com/universal-ctags/ctags)
+- [ ] Adding more tools. Possible directions:
+  - [x] PR description
+  - [x] Inline code suggestions
+  - [x] Reflect and review
+  - [ ] Enforcing CONTRIBUTING.md guidelines
+  - [ ] Performance (are there any performance issues)
+  - [ ] Documentation (is the PR properly documented)
+  - [ ] Rank the PR importance
+  - [ ] ...
 
-A reasonable question that can be asked is: `"Why use PR-Agent? What makes it stand out from existing tools?"`
+## Similar Projects
 
-Here are some advantages of PR-Agent:
-
-- We emphasize **real-life practical usage**. Each tool (review, improve, ask, ...) has a single GPT-4 call, no more. We feel that this is critical for realistic team usage - obtaining an answer quickly (~30 seconds) and affordably.
-- Our [PR Compression strategy](https://pr-agent-docs.codium.ai/core-abilities/#pr-compression-strategy)  is a core ability that enables to effectively tackle both short and long PRs.
-- Our JSON prompting strategy enables to have **modular, customizable tools**. For example, the '/review' tool categories can be controlled via the [configuration](pr_agent/settings/configuration.toml) file. Adding additional categories is easy and accessible.
-- We support **multiple git providers** (GitHub, Gitlab, Bitbucket), **multiple ways** to use the tool (CLI, GitHub Action, GitHub App, Docker, ...), and **multiple models** (GPT-4, GPT-3.5, Anthropic, Cohere, Llama2).
-
-
-## Data privacy
-
-### Self-hosted PR-Agent
-
-- If you host PR-Agent with your OpenAI API key, it is between you and OpenAI. You can read their API data privacy policy here:
-https://openai.com/enterprise-privacy
-
-### CodiumAI-hosted PR-Agent Pro 💎
-
-- When using PR-Agent Pro 💎, hosted by CodiumAI, we will not store any of your data, nor will we use it for training. You will also benefit from an OpenAI account with zero data retention.
-
-- For certain clients, CodiumAI-hosted PR-Agent Pro will use CodiumAI’s proprietary models — if this is the case, you will be notified.
-
-- No passive collection of Code and Pull Requests’ data — PR-Agent will be active only when you invoke it, and it will then extract and analyze only data relevant to the executed command and queried pull request.
-
-### PR-Agent Chrome extension
-
-- The [PR-Agent Chrome extension](https://chromewebstore.google.com/detail/pr-agent-chrome-extension/ephlnjeghhogofkifjloamocljapahnl) serves solely to modify the visual appearance of a GitHub PR screen. It does not transmit any user's repo or pull request code. Code is only sent for processing when a user submits a GitHub comment that activates a PR-Agent tool, in accordance with the standard privacy policy of PR-Agent.
-
-## Links
-
-[![Join our Discord community](https://raw.githubusercontent.com/Codium-ai/codiumai-vscode-release/main/media/docs/Joincommunity.png)](https://discord.gg/kG35uSHDBc)
-
-- Discord community: https://discord.gg/kG35uSHDBc
-- CodiumAI site: https://codium.ai
-- Blog: https://www.codium.ai/blog/
-- Troubleshooting: https://www.codium.ai/blog/technical-faq-and-troubleshooting/
-- Support: support@codium.ai
+- [CodiumAI - Meaningful tests for busy devs](https://github.com/Codium-ai/codiumai-vscode-release)
+- [Aider - GPT powered coding in your terminal](https://github.com/paul-gauthier/aider)
+- [openai-pr-reviewer](https://github.com/coderabbitai/openai-pr-reviewer)
+- [CodeReview BOT](https://github.com/anc95/ChatGPT-CodeReview)
+- [AI-Maintainer](https://github.com/merwanehamadi/AI-Maintainer)

RELEASE_NOTES.md

@@ -1,103 +0,0 @@
-## [Version 0.11] - 2023-12-07
-- codiumai/pr-agent:0.11
-- codiumai/pr-agent:0.11-github_app
-- codiumai/pr-agent:0.11-bitbucket-app
-- codiumai/pr-agent:0.11-gitlab_webhook
-- codiumai/pr-agent:0.11-github_polling
-- codiumai/pr-agent:0.11-github_action
-
-### Added::Algo
-- New section in `/describe` tool - [PR changes walkthrough](https://github.com/Codium-ai/pr-agent/pull/509)
-- Improving PR Agent [prompts](https://github.com/Codium-ai/pr-agent/pull/501)
-- Persistent tools (`/review`, `/describe`) now send an [update message](https://github.com/Codium-ai/pr-agent/pull/499) after finishing
-- Add Amazon Bedrock [support](https://github.com/Codium-ai/pr-agent/pull/483)
-
-### Fixed
-- Update [dependencies](https://github.com/Codium-ai/pr-agent/pull/503) in requirements.txt for Python 3.12
-
-
-## [Version 0.10] - 2023-11-15
-- codiumai/pr-agent:0.10
-- codiumai/pr-agent:0.10-github_app
-- codiumai/pr-agent:0.10-bitbucket-app
-- codiumai/pr-agent:0.10-gitlab_webhook
-- codiumai/pr-agent:0.10-github_polling
-- codiumai/pr-agent:0.10-github_action
-
-### Added::Algo
-- Review tool now works with [persistent comments](https://github.com/Codium-ai/pr-agent/pull/451) by default
-- Bitbucket now publishes review suggestions with [code links](https://github.com/Codium-ai/pr-agent/pull/428)
-- Enabling to limit [max number of tokens](https://github.com/Codium-ai/pr-agent/pull/437/files)
-- Support ['gpt-4-1106-preview'](https://github.com/Codium-ai/pr-agent/pull/437/files) model
-- Support for Google's [Vertex AI](https://github.com/Codium-ai/pr-agent/pull/436)
-- Implementing [thresholds](https://github.com/Codium-ai/pr-agent/pull/423) for incremental PR reviews
-- Decoupled custom labels from [PR type](https://github.com/Codium-ai/pr-agent/pull/431)
-
-### Fixed
-- Fixed bug in [parsing quotes](https://github.com/Codium-ai/pr-agent/pull/446) in CLI
-- Preserve [user-added labels](https://github.com/Codium-ai/pr-agent/pull/433) in pull requests
-- Bug fixes in GitLab and BitBucket
-
-## [Version 0.9] - 2023-10-29
-- codiumai/pr-agent:0.9
-- codiumai/pr-agent:0.9-github_app
-- codiumai/pr-agent:0.9-bitbucket-app
-- codiumai/pr-agent:0.9-gitlab_webhook
-- codiumai/pr-agent:0.9-github_polling
-- codiumai/pr-agent:0.9-github_action
-
-### Added::Algo
-- New tool - [generate_labels](https://github.com/Codium-ai/pr-agent/blob/main/docs/GENERATE_CUSTOM_LABELS.md)
-- New ability to use [customize labels](https://github.com/Codium-ai/pr-agent/blob/main/docs/GENERATE_CUSTOM_LABELS.md#how-to-enable-custom-labels) on the `review` and `describe` tools.
-- New tool - [add_docs](https://github.com/Codium-ai/pr-agent/blob/main/docs/ADD_DOCUMENTATION.md)
-- GitHub Action: Can now use a `.pr_agent.toml` file to control configuration parameters (see [Usage Guide](./Usage.md#working-with-github-action)).
-- GitHub App: Added ability to trigger tools on [push events](https://github.com/Codium-ai/pr-agent/blob/main/Usage.md#github-app-automatic-tools-for-new-code-pr-push)
-- Support custom domain URLs for Azure devops integration (see [link](https://github.com/Codium-ai/pr-agent/pull/381)).
-- PR Description default mode is now in [bullet points](https://github.com/Codium-ai/pr-agent/blob/main/pr_agent/settings/configuration.toml#L35).
-
-### Added::Documentation
-Significant documentation updates (see [Installation Guide](https://github.com/Codium-ai/pr-agent/blob/main/INSTALL.md), [Usage Guide](https://github.com/Codium-ai/pr-agent/blob/main/Usage.md), and [Tools Guide](https://github.com/Codium-ai/pr-agent/blob/main/docs/TOOLS_GUIDE.md))
-
-### Fixed
-- Fixed support for BitBucket pipeline (see [link](https://github.com/Codium-ai/pr-agent/pull/386))
-- Fixed a bug in `review -i` tool
-- Added blacklist for specific file extensions in `add_docs` tool (see [link](https://github.com/Codium-ai/pr-agent/pull/385/))
-
-## [Version 0.8] - 2023-09-27
-- codiumai/pr-agent:0.8
-- codiumai/pr-agent:0.8-github_app
-- codiumai/pr-agent:0.8-bitbucket-app
-- codiumai/pr-agent:0.8-gitlab_webhook
-- codiumai/pr-agent:0.8-github_polling
-- codiumai/pr-agent:0.8-github_action
-
-### Added::Algo
-- GitHub Action: Can control which tools will run automatically when a new PR is created. (see usage guide: https://github.com/Codium-ai/pr-agent/blob/main/Usage.md#working-with-github-action)
-- Code suggestion tool: Will try to avoid an 'add comments' suggestion  (see https://github.com/Codium-ai/pr-agent/pull/327)
-
-### Fixed
-- Gitlab: Fixed a bug of improper usage of pr_id
-
-
-## [Version 0.7] - 2023-09-20
-
-### Docker Tags
-- codiumai/pr-agent:0.7
-- codiumai/pr-agent:0.7-github_app
-- codiumai/pr-agent:0.7-bitbucket-app
-- codiumai/pr-agent:0.7-gitlab_webhook
-- codiumai/pr-agent:0.7-github_polling
-- codiumai/pr-agent:0.7-github_action
-
-### Added::Algo
-- New tool /similar_issue - Currently on GitHub app and CLI: indexes the issues in the repo, find the most similar issues to the target issue.
-- Describe markers: Empower the /describe tool with a templating capability (see more details in https://github.com/Codium-ai/pr-agent/pull/273).
-- New feature in the /review tool - added an estimated effort estimation to the review (https://github.com/Codium-ai/pr-agent/pull/306).
-
-### Added::Infrastructure
-- Implementation of a GitLab webhook.
-- Implementation of a BitBucket app.
-
-### Fixed
-- Protection against no code suggestions generated.
-- Resilience to repositories where the languages cannot be automatically detected.

codecov.yml

@@ -1,5 +0,0 @@
-comment: false
-coverage:
-  status:
-    patch: false
-    project: false

docker/Dockerfile

@@ -1,42 +1,20 @@
-FROM python:3.12.3 AS base
+FROM python:3.10 as base
 
 WORKDIR /app
-ADD pyproject.toml .
 ADD requirements.txt .
-ADD docs docs
-RUN pip install . && rm pyproject.toml requirements.txt
+RUN pip install -r requirements.txt && rm requirements.txt
 ENV PYTHONPATH=/app
-
-FROM base AS github_app
 ADD pr_agent pr_agent
-CMD ["python", "-m", "gunicorn", "-k", "uvicorn.workers.UvicornWorker", "-c", "pr_agent/servers/gunicorn_config.py", "--forwarded-allow-ips", "*", "pr_agent.servers.github_app:app"]
 
-FROM base AS bitbucket_app
-ADD pr_agent pr_agent
-CMD ["python", "pr_agent/servers/bitbucket_app.py"]
+FROM base as github_app
+CMD ["python", "pr_agent/servers/github_app.py"]
 
-FROM base AS bitbucket_server_webhook
-ADD pr_agent pr_agent
-CMD ["python", "pr_agent/servers/bitbucket_server_webhook.py"]
-
-FROM base AS github_polling
-ADD pr_agent pr_agent
+FROM base as github_polling
 CMD ["python", "pr_agent/servers/github_polling.py"]
 
-FROM base AS gitlab_webhook
-ADD pr_agent pr_agent
-CMD ["python", "pr_agent/servers/gitlab_webhook.py"]
-
-FROM base AS azure_devops_webhook
-ADD pr_agent pr_agent
-CMD ["python", "pr_agent/servers/azuredevops_server_webhook.py"]
-
-FROM base AS test
+FROM base as test
 ADD requirements-dev.txt .
 RUN pip install -r requirements-dev.txt && rm requirements-dev.txt
-ADD pr_agent pr_agent
-ADD tests tests
 
-FROM base AS cli
-ADD pr_agent pr_agent
+FROM base as cli
 ENTRYPOINT ["python", "pr_agent/cli.py"]

docker/Dockerfile.lambda

@@ -1,12 +1,12 @@
 FROM public.ecr.aws/lambda/python:3.10
 
 RUN yum update -y && \
-    yum install -y gcc python3-devel git && \
+    yum install -y gcc python3-devel && \
     yum clean all
 
-ADD pyproject.toml requirements.txt .
-RUN pip install . && rm pyproject.toml
-RUN pip install mangum==0.17.0
+ADD requirements.txt .
+RUN pip install -r requirements.txt && rm requirements.txt
+RUN pip install mangum==16.0.0
 COPY pr_agent/ ${LAMBDA_TASK_ROOT}/pr_agent/
 
 CMD ["pr_agent.servers.serverless.serverless"]

docs/README.md

@@ -1 +0,0 @@
-# [Visit Our Docs Portal](https://qodo-merge-docs.qodo.ai/)

docs/docs/CNAME

@@ -1 +0,0 @@
-qodo-merge-docs.qodo.ai

docs/docs/assets/logo.svg

@@ -1 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?><svg id="Layer_1" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 109.77 81.94"><defs><style>.cls-1{fill:#7968fa;}.cls-1,.cls-2{stroke-width:0px;}.cls-2{fill:#5ae3ae;}</style></defs><path class="cls-2" d="m109.77,40.98c0,22.62-7.11,40.96-15.89,40.96-3.6,0-6.89-3.09-9.58-8.31,6.82-7.46,11.22-19.3,11.22-32.64s-4.4-25.21-11.22-32.67C86.99,3.09,90.29,0,93.89,0c8.78,0,15.89,18.33,15.89,40.97"/><path class="cls-1" d="m95.53,40.99c0,13.35-4.4,25.19-11.23,32.64-3.81-7.46-6.28-19.3-6.28-32.64s2.47-25.21,6.28-32.67c6.83,7.46,11.23,19.32,11.23,32.67"/><path class="cls-2" d="m55.38,78.15c-4.99,2.42-10.52,3.79-16.38,3.79C17.46,81.93,0,63.6,0,40.98S17.46,0,39,0C44.86,0,50.39,1.37,55.38,3.79c-9.69,6.47-16.43,20.69-16.43,37.19s6.73,30.7,16.43,37.17"/><path class="cls-1" d="m78.02,40.99c0,16.48-9.27,30.7-22.65,37.17-9.69-6.47-16.43-20.69-16.43-37.17S45.68,10.28,55.38,3.81c13.37,6.49,22.65,20.69,22.65,37.19"/><path class="cls-2" d="m84.31,73.63c-4.73,5.22-10.64,8.31-17.06,8.31-4.24,0-8.27-1.35-11.87-3.79,13.37-6.48,22.65-20.7,22.65-37.17,0,13.35,2.47,25.19,6.28,32.64"/><path class="cls-2" d="m84.31,8.31c-3.81,7.46-6.28,19.32-6.28,32.67,0-16.5-9.27-30.7-22.65-37.19,3.6-2.45,7.63-3.8,11.87-3.8,6.43,0,12.33,3.09,17.06,8.31"/></svg>

docs/docs/chrome-extension/data_privacy.md

@@ -1,4 +0,0 @@
-We take your code's security and privacy seriously:
-
-- The Chrome extension will not send your code to any external servers.
-- For private repositories, we will first validate the user's identity and permissions. After authentication, we generate responses using the existing Qodo Merge Pro integration.

docs/docs/chrome-extension/features.md

@@ -1,51 +0,0 @@
-
-### PR chat
-
-The PR-Chat feature allows to freely chat with your PR code, within your GitHub environment.
-It will seamlessly use the PR as context to your chat session, and provide AI-powered feedback.
-
-To enable private chat, simply install the Qodo Merge Chrome extension. After installation, each PR's file-changed tab will include a chat box, where you may ask questions about your code.
-This chat session is **private**, and won't be visible to other users.
-
-All open-source repositories are supported.
-For private repositories, you will also need to install Qodo Merge Pro, After installation, make sure to open at least one new PR to fully register your organization. Once done, you can chat with both new and existing PRs across all installed repositories.
-
-#### Context-aware PR chat
-
-Qodo Merge constructs a comprehensive context for each pull request, incorporating the PR description, commit messages, and code changes with extended dynamic context. This contextual information, along with additional PR-related data, forms the foundation for an AI-powered chat session. The agent then leverages this rich context to provide intelligent, tailored responses to user inquiries about the pull request.
-
-<img src="https://codium.ai/images/pr_agent/pr_chat_1.png" width="768">
-<img src="https://codium.ai/images/pr_agent/pr_chat_2.png" width="768">
-
-
-### Toolbar extension
-With Qodo Merge Chrome extension, it's [easier than ever](https://www.youtube.com/watch?v=gT5tli7X4H4) to interactively configure and experiment with the different tools and configuration options.
-
-For private repositories, after you found the setup that works for you, you can also easily export it as a persistent configuration file, and use it for automatic commands.
-
-<img src="https://codium.ai/images/pr_agent/toolbar1.png" width="512">
-
-<img src="https://codium.ai/images/pr_agent/toolbar2.png" width="512">
-
-### Qodo Merge filters
-
-Qodo Merge filters is a sidepanel option. that allows you to filter different message in the conversation tab.
-
-For example, you can choose to present only message from Qodo Merge, or filter those messages, focusing only on user's comments.
-
-<img src="https://codium.ai/images/pr_agent/pr_agent_filters1.png" width="256">
-
-<img src="https://codium.ai/images/pr_agent/pr_agent_filters2.png" width="256">
-
-
-### Enhanced code suggestions
-
-Qodo Merge Chrome extension adds the following capabilities to code suggestions tool's comments:
-
-- Auto-expand the table when you are viewing a code block, to avoid clipping.
-- Adding a "quote-and-reply" button, that enables to address and comment on a specific suggestion (for example, asking the author to fix the issue)
-
-
-<img src="https://codium.ai/images/pr_agent/chrome_extension_code_suggestion1.png" width="512">
-
-<img src="https://codium.ai/images/pr_agent/chrome_extension_code_suggestion2.png" width="512">

docs/docs/chrome-extension/index.md

@@ -1,14 +0,0 @@
-[Qodo Merge Chrome extension](https://chromewebstore.google.com/detail/pr-agent-chrome-extension/ephlnjeghhogofkifjloamocljapahnl) is a collection of tools that integrates seamlessly with your GitHub environment, aiming to enhance your Git usage experience, and providing AI-powered capabilities to your PRs.
-
-With a single-click installation you will gain access to a context-aware chat on your pull requests code, a toolbar extension with multiple AI feedbacks, Qodo Merge filters, and additional abilities.
-
-The extension is powered by top code models like Claude 3.5 Sonnet and GPT4. All the extension's features are free to use on public repositories.
-
-For private repositories, you will need to install [Qodo Merge Pro](https://github.com/apps/qodo-merge-pro) in addition to the extension  (Quick GitHub app setup with a 14-day free trial. No credit card needed).
-For a demonstration of how to install Qodo Merge Pro and use it with the Chrome extension, please refer to the tutorial video at the provided [link](https://codium.ai/images/pr_agent/private_repos.mp4).
-
-<img src="https://codium.ai/images/pr_agent/PR-AgentChat.gif" width="768">
-
-### Supported browsers
-
-The extension is supported on all Chromium-based browsers, including Google Chrome, Arc, Opera, Brave, and Microsoft Edge.

docs/docs/core-abilities/code_oriented_yaml.md

@@ -1,2 +0,0 @@
-## Overview
-TBD

docs/docs/core-abilities/dynamic_context.md

@@ -1,72 +0,0 @@
-## TL;DR
-
-Qodo Merge uses an **asymmetric and dynamic context strategy** to improve AI analysis of code changes in pull requests.
-It provides more context before changes than after, and dynamically adjusts the context based on code structure (e.g., enclosing functions or classes).
-This approach balances providing sufficient context for accurate analysis, while avoiding needle-in-the-haystack information overload that could degrade AI performance or exceed token limits.
-
-## Introduction
-
-Pull request code changes are retrieved in a unified diff format, showing three lines of context before and after each modified section, with additions marked by '+' and deletions by '-'.
-```
-@@ -12,5 +12,5 @@ def func1():
- code line that already existed in the file...
- code line that already existed in the file...
- code line that already existed in the file....
--code line that was removed in the PR
-+new code line added in the PR
- code line that already existed in the file...
- code line that already existed in the file...
- code line that already existed in the file...
-
-@@ -26,2 +26,4 @@ def func2():
-...
-```
-
-This unified diff format can be challenging for AI models to interpret accurately, as it provides limited context for understanding the full scope of code changes.
-The presentation of code using '+', '-', and ' ' symbols to indicate additions, deletions, and unchanged lines respectively also differs from the standard code formatting typically used to train AI models.
-
-
-## Challenges of expanding the context window
-
-While expanding the context window is technically feasible, it presents a more fundamental trade-off:
-
-Pros:
-
-- Enhanced context allows the model to better comprehend and localize the code changes, results (potentially) in more precise analysis and suggestions. Without enough context, the model may struggle to understand the code changes and provide relevant feedback.
-
-Cons:
-
-- Excessive context may overwhelm the model with extraneous information, creating a "needle in a haystack" scenario where focusing on the relevant details (the code that actually changed) becomes challenging.
-LLM quality is known to degrade when the context gets larger.
-Pull requests often encompass multiple changes across many files, potentially spanning hundreds of lines of modified code. This complexity presents a genuine risk of overwhelming the model with excessive context.
-
-- Increased context expands the token count, increasing processing time and cost, and may prevent the model from processing the entire pull request in a single pass.
-
-## Asymmetric and dynamic context
-To address these challenges, Qodo Merge employs an **asymmetric** and **dynamic** context strategy, providing the model with more focused and relevant context information for each code change.
-
-**Asymmetric:**
-
-We start by recognizing that the context preceding a code change is typically more crucial for understanding the modification than the context following it.
-Consequently, Qodo Merge implements an asymmetric context policy, decoupling the context window into two distinct segments: one for the code before the change and another for the code after.
-
-By independently adjusting each context window, Qodo Merge can supply the model with a more tailored and pertinent context for individual code changes.
-
-**Dynamic:**
-
-We also employ a "dynamic" context strategy.
-We start by recognizing that the optimal context for a code change often corresponds to its enclosing code component (e.g., function, class), rather than a fixed number of lines.
-Consequently, we dynamically adjust the context window based on the code's structure, ensuring the model receives the most pertinent information for each modification.
-
-To prevent overwhelming the model with excessive context, we impose a limit on the number of lines searched when identifying the enclosing component.
-This balance allows for comprehensive understanding while maintaining efficiency and limiting context token usage.
-
-## Appendix - relevant configuration options
-```
-[config]
-patch_extension_skip_types =[".md",".txt"]  # Skip files with these extensions when trying to extend the context
-allow_dynamic_context=true                  # Allow dynamic context extension
-max_extra_lines_before_dynamic_context = 8  # will try to include up to X extra lines before the hunk in the patch, until we reach an enclosing function or class
-patch_extra_lines_before = 3                # Number of extra lines (+3 default ones) to include before each hunk in the patch
-patch_extra_lines_after = 1                 # Number of extra lines (+3 default ones) to include after each hunk in the patch
-```

docs/docs/core-abilities/fetching_ticket_context.md

@@ -1,134 +0,0 @@
-# Fetching Ticket Context for PRs
-`Supported Git Platforms : GitHub, GitLab, Bitbucket`
-
-## Overview
-Qodo Merge PR Agent streamlines code review workflows by seamlessly connecting with multiple ticket management systems.
-This integration enriches the review process by automatically surfacing relevant ticket information and context alongside code changes.
-
-## Ticket systems supported
-- GitHub
-- Jira (💎)
-
-Ticket data fetched:
-
-1. Ticket Title
-2. Ticket Description
-3. Custom Fields (Acceptance criteria)
-4. Subtasks (linked tasks)
-5. Labels
-6. Attached Images/Screenshots
-
-## Affected Tools
-
-Ticket Recognition Requirements:
-
-- The PR description should contain a link to the ticket or if the branch name starts with the ticket id / number.
-- For Jira tickets, you should follow the instructions in [Jira Integration](https://qodo-merge-docs.qodo.ai/core-abilities/fetching_ticket_context/#jira-integration) in order to authenticate with Jira.
-
-### Describe tool
-Qodo Merge PR Agent will recognize the ticket and use the ticket content (title, description, labels) to provide additional context for the code changes.
-By understanding the reasoning and intent behind modifications, the LLM can offer more insightful and relevant code analysis.
-
-### Review tool
-Similarly to the `describe` tool, the `review` tool will use the ticket content to provide additional context for the code changes.
-
-In addition, this feature will evaluate how well a Pull Request (PR) adheres to its original purpose/intent as defined by the associated ticket or issue mentioned in the PR description.
-Each ticket will be assigned a label (Compliance/Alignment level), Indicates the degree to which the PR fulfills its original purpose, Options: Fully compliant, Partially compliant or Not compliant.
-
-
-![Ticket Compliance](https://www.qodo.ai/images/pr_agent/ticket_compliance_review.png){width=768}
-
-By default, the tool will automatically validate if the PR complies with the referenced ticket.
-If you want to disable this feedback, add the following line to your configuration file:
-
-```toml
-[pr_reviewer]
-require_ticket_analysis_review=false
-```
-
-## Providers
-
-### Github Issues Integration
-
-Qodo Merge PR Agent will automatically recognize Github issues mentioned in the PR description and fetch the issue content.
-Examples of valid GitHub issue references:
-
-- `https://github.com/<ORG_NAME>/<REPO_NAME>/issues/<ISSUE_NUMBER>`
-- `#<ISSUE_NUMBER>`
-- `<ORG_NAME>/<REPO_NAME>#<ISSUE_NUMBER>`
-
-Since Qodo Merge PR Agent is integrated with GitHub, it doesn't require any additional configuration to fetch GitHub issues.
-
-### Jira Integration 💎
-
-We support both Jira Cloud and Jira Server/Data Center.
-To integrate with Jira, you can link your PR to a ticket using either of these methods:
-
-**Method 1: Description Reference:**
-
-Include a ticket reference in your PR description using either the complete URL format https://<JIRA_ORG>.atlassian.net/browse/ISSUE-123 or the shortened ticket ID ISSUE-123.
-
-**Method 2: Branch Name Detection:**
-
-Name your branch with the ticket ID as a prefix (e.g., `ISSUE-123-feature-description` or `ISSUE-123/feature-description`).
-
-!!! note "Jira Base URL"
-    For shortened ticket IDs or branch detection (method 2), you must configure the Jira base URL in your configuration file under the [jira] section:
-
-    ```toml
-    [jira]
-    jira_base_url = "https://<JIRA_ORG>.atlassian.net"
-    ```
-
-#### Jira Cloud 💎
-There are two ways to authenticate with Jira Cloud:
-
-**1) Jira App Authentication**
-
-The recommended way to authenticate with Jira Cloud is to install the Qodo Merge app in your Jira Cloud instance. This will allow Qodo Merge to access Jira data on your behalf.
-
-Installation steps:
-
-1. Click [here](https://auth.atlassian.com/authorize?audience=api.atlassian.com&client_id=8krKmA4gMD8mM8z24aRCgPCSepZNP1xf&scope=read%3Ajira-work%20offline_access&redirect_uri=https%3A%2F%2Fregister.jira.pr-agent.codium.ai&state=qodomerge&response_type=code&prompt=consent) to install the Qodo Merge app in your Jira Cloud instance, click the `accept` button.<br>
-![Jira Cloud App Installation](https://www.qodo.ai/images/pr_agent/jira_app_installation1.png){width=384}
-
-2. After installing the app, you will be redirected to the Qodo Merge registration page. and you will see a success message.<br>
-![Jira Cloud App success message](https://www.qodo.ai/images/pr_agent/jira_app_success.png){width=384}
-
-3. Now you can use the Jira integration in Qodo Merge PR Agent.
-
-**2) Email/Token Authentication**
-
-You can create an API token from your Atlassian account:
-
-1. Log in to https://id.atlassian.com/manage-profile/security/api-tokens.
-
-2. Click Create API token.
-
-3. From the dialog that appears, enter a name for your new token and click Create.
-
-4. Click Copy to clipboard.
-
-![Jira Cloud API Token](https://images.ctfassets.net/zsv3d0ugroxu/1RYvh9lqgeZjjNe5S3Hbfb/155e846a1cb38f30bf17512b6dfd2229/screenshot_NewAPIToken){width=384}
-
-5. In your [configuration file](https://qodo-merge-docs.qodo.ai/usage-guide/configuration_options/) add the following lines:
-
-```toml
-[jira]
-jira_api_token = "YOUR_API_TOKEN"
-jira_api_email = "YOUR_EMAIL"
-```
-
-
-#### Jira Server/Data Center 💎
-
-Currently, we only support the Personal Access Token (PAT) Authentication method.
-
-1. Create a [Personal Access Token (PAT)](https://confluence.atlassian.com/enterprise/using-personal-access-tokens-1026032365.html) in your Jira account
-2. In your Configuration file/Environment variables/Secrets file, add the following lines:
-
-```toml
-[jira]
-jira_base_url = "YOUR_JIRA_BASE_URL" # e.g. https://jira.example.com
-jira_api_token = "YOUR_API_TOKEN"
-```

docs/docs/core-abilities/impact_evaluation.md

@@ -1,44 +0,0 @@
-# Overview - Impact Evaluation 💎
-
-Demonstrating the return on investment (ROI) of AI-powered initiatives is crucial for modern organizations.
-To address this need, Qodo Merge has developed an AI impact measurement tools and metrics, providing advanced analytics to help businesses quantify the tangible benefits of AI adoption in their PR review process.
-
-
-## Auto Impact Validator - Real-Time Tracking of Implemented Qodo Merge Suggestions
-
-### How It Works
-When a user pushes a new commit to the pull request, Qodo Merge automatically compares the updated code against the previous suggestions, marking them as implemented if the changes address these recommendations, whether directly or indirectly:
-
-1. **Direct Implementation:** The user directly addresses the suggestion as-is in the PR, either by clicking on the "apply code suggestion" checkbox or by making the changes manually.
-2. **Indirect Implementation:** Qodo Merge recognizes when a suggestion's intent is fulfilled, even if the exact code changes differ from the original recommendation. It marks these suggestions as implemented, acknowledging that users may achieve the same goal through alternative solutions.
-
-### Real-Time Visual Feedback
-Upon confirming that a suggestion was implemented, Qodo Merge automatically adds a ✅ (check mark) to the relevant suggestion, enabling transparent tracking of Qodo Merge's impact analysis.
-Qodo Merge will also add, inside the relevant suggestions, an explanation of how the new code was impacted by each suggestion.
-
-![Suggestion_checkmark](https://codium.ai/images/pr_agent/auto_suggestion_checkmark.png){width=512}
-
-### Dashboard Metrics
-The dashboard provides macro-level insights into the overall impact of Qodo Merge on the pull-request process with key productivity metrics.
-
-By offering clear, data-driven evidence of Qodo Merge's impact, it empowers leadership teams to make informed decisions about the tool's effectiveness and ROI.
-
-Here are key metrics that the dashboard tracks:
-
-#### Qodo Merge Impacts per 1K Lines
-![Dashboard](https://codium.ai/images/pr_agent/impacts_per_1k_llines.png){width=512}
-> Explanation: for every 1K lines of code (additions/edits), Qodo Merge had on average ~X suggestions implemented.
-
-**Why This Metric Matters:**
-
-1. **Standardized and Comparable Measurement:** By measuring impacts per 1K lines of code additions, you create a standardized metric that can be compared across different projects, teams, customers, and time periods. This standardization is crucial for meaningful analysis, benchmarking, and identifying where Qodo Merge is most effective.
-2. **Accounts for PR Variability and Incentivizes Quality:** This metric addresses the fact that "Not all PRs are created equal." By normalizing against lines of code rather than PR count, you account for the variability in PR sizes and focus on the quality and impact of suggestions rather than just the number of PRs affected.
-3. **Quantifies Value and ROI:** The metric directly correlates with the value Qodo Merge is providing, showing how frequently it offers improvements relative to the amount of new code being written. This provides a clear, quantifiable way to demonstrate Qodo Merge's return on investment to stakeholders.
-
-#### Suggestion Effectiveness Across Categories
-![Impacted_Suggestion_Score](https://codium.ai/images/pr_agent/impact_by_category.png){width=512}
-> Explanation: This chart illustrates the distribution of implemented suggestions across different categories, enabling teams to better understand Qodo Merge's impact on various aspects of code quality and development practices.
-
-#### Suggestion Score Distribution
-![Impacted_Suggestion_Score](https://codium.ai/images/pr_agent/impacted_score_dist.png){width=512}
-> Explanation: The distribution of the suggestion score for the implemented suggestions, ensuring that higher-scored suggestions truly represent more significant improvements.

docs/docs/core-abilities/index.md

@@ -1,29 +0,0 @@
-# Core Abilities
-Qodo Merge utilizes a variety of core abilities to provide a comprehensive and efficient code review experience. These abilities include:
-
-- [Fetching ticket context](https://qodo-merge-docs.qodo.ai/core-abilities/fetching_ticket_context/)
-- [Local and global metadata](https://qodo-merge-docs.qodo.ai/core-abilities/metadata/)
-- [Dynamic context](https://qodo-merge-docs.qodo.ai/core-abilities/dynamic_context/)
-- [Self-reflection](https://qodo-merge-docs.qodo.ai/core-abilities/self_reflection/)
-- [Impact evaluation](https://qodo-merge-docs.qodo.ai/core-abilities/impact_evaluation/)
-- [Interactivity](https://qodo-merge-docs.qodo.ai/core-abilities/interactivity/)
-- [Compression strategy](https://qodo-merge-docs.qodo.ai/core-abilities/compression_strategy/)
-- [Code-oriented YAML](https://qodo-merge-docs.qodo.ai/core-abilities/code_oriented_yaml/)
-- [Static code analysis](https://qodo-merge-docs.qodo.ai/core-abilities/static_code_analysis/)
-- [Code fine-tuning benchmark](https://qodo-merge-docs.qodo.ai/finetuning_benchmark/)
-
-## Blogs
-
-Here are some additional technical blogs from Qodo, that delve deeper into the core capabilities and features of Large Language Models (LLMs) when applied to coding tasks.
-These resources provide more comprehensive insights into leveraging LLMs for software development.
-
-### Code Generation and LLMs
-- [State-of-the-art Code Generation with AlphaCodium – From Prompt Engineering to Flow Engineering](https://www.qodo.ai/blog/qodoflow-state-of-the-art-code-generation-for-code-contests/)
-- [RAG for a Codebase with 10k Repos](https://www.qodo.ai/blog/rag-for-large-scale-code-repos/)
-
-### Development Processes
-- [Understanding the Challenges and Pain Points of the Pull Request Cycle](https://www.qodo.ai/blog/understanding-the-challenges-and-pain-points-of-the-pull-request-cycle/)
-- [Introduction to Code Coverage Testing](https://www.qodo.ai/blog/introduction-to-code-coverage-testing/)
-
-### Cost Optimization
-- [Reduce Your Costs by 30% When Using GPT for Python Code](https://www.qodo.ai/blog/reduce-your-costs-by-30-when-using-gpt-3-for-python-code/)

docs/docs/core-abilities/interactivity.md

@@ -1,2 +0,0 @@
-## Interactive invocation 💎
-TBD

docs/docs/core-abilities/metadata.md

@@ -1,56 +0,0 @@
-## Local and global metadata injection with multi-stage analysis
-(1)
-Qodo Merge initially retrieves for each PR the following data:
-
-- PR title and branch name
-- PR original description
-- Commit messages history
-- PR diff patches, in [hunk diff](https://loicpefferkorn.net/2014/02/diff-files-what-are-hunks-and-how-to-extract-them/) format
-- The entire content of the files that were modified in the PR
-
-!!! tip "Tip: Organization-level metadata"
-    In addition to the inputs above, Qodo Merge can incorporate supplementary preferences provided by the user, like [`extra_instructions` and `organization best practices`](https://qodo-merge-docs.qodo.ai/tools/improve/#extra-instructions-and-best-practices). This information can be used to enhance the PR analysis.
-
-(2)
-By default, the first command that Qodo Merge executes is [`describe`](https://qodo-merge-docs.qodo.ai/tools/describe/), which generates three types of outputs:
-
-- PR Type (e.g. bug fix, feature, refactor, etc)
-- PR Description - a bullet point summary of the PR
-- Changes walkthrough - for each modified file, provide a one-line summary followed by a detailed bullet point list of the changes.
-
-These AI-generated outputs are now considered as part of the PR metadata, and can be used in subsequent commands like `review` and `improve`.
-This effectively enables multi-stage chain-of-thought analysis, without doing any additional API calls which will cost time and money.
-
-For example, when generating code suggestions for different files, Qodo Merge can inject the AI-generated ["Changes walkthrough"](https://github.com/Codium-ai/pr-agent/pull/1202#issue-2511546839) file summary in the prompt:
-
-```
-## File: 'src/file1.py'
-### AI-generated file summary:
-- edited function `func1` that does X
-- Removed function `func2` that was not used
-- ....
-
-@@ ... @@ def func1():
-__new hunk__
-11  unchanged code line0 in the PR
-12  unchanged code line1 in the PR
-13 +new code line2 added in the PR
-14  unchanged code line3 in the PR
-__old hunk__
- unchanged code line0
- unchanged code line1
--old code line2 removed in the PR
- unchanged code line3
-
-@@ ... @@ def func2():
-__new hunk__
-...
-__old hunk__
-...
-```
-
-(3) The entire PR files that were retrieved are also used to expand and enhance the PR context (see [Dynamic Context](https://qodo-merge-docs.qodo.ai/core-abilities/dynamic_context/)).
-
-
-(4) All the metadata described above represents several level of cumulative analysis - ranging from hunk level, to file level, to PR level, to organization level.
-This comprehensive approach enables Qodo Merge AI models to generate more precise and contextually relevant suggestions and feedback.

docs/docs/core-abilities/self_reflection.md

@@ -1,50 +0,0 @@
-## TL;DR
-
-Qodo Merge implements a **self-reflection** process where the AI model reflects, scores, and re-ranks its own suggestions, eliminating irrelevant or incorrect ones.
-This approach improves the quality and relevance of suggestions, saving users time and enhancing their experience.
-Configuration options allow users to set a score threshold for further filtering out suggestions.
-
-## Introduction - Efficient Review with Hierarchical Presentation
-
-
-Given that not all generated code suggestions will be relevant, it is crucial to enable users to review them in a fast and efficient way, allowing quick identification and filtering of non-applicable ones.
-
-To achieve this goal, Qodo Merge offers a dedicated hierarchical structure when presenting suggestions to users:
-
-- A "category" section groups suggestions by their category, allowing users to quickly dismiss irrelevant suggestions.
-- Each suggestion is first described by a one-line summary, which can be expanded to a full description by clicking on a collapsible.
-- Upon expanding a suggestion, the user receives a more comprehensive description, and a code snippet demonstrating the recommendation.
-
-!!! note "Fast Review"
-    This hierarchical structure is designed to facilitate rapid review of each suggestion, with users spending an average of ~5-10 seconds per item.
-
-## Self-reflection and Re-ranking
-
-The AI model is initially tasked with generating suggestions, and outputting them in order of importance.
-However, in practice we observe that models often struggle to simultaneously generate high-quality code suggestions and rank them well in a single pass.
-Furthermore, the initial set of generated suggestions sometimes contains easily identifiable errors.
-
-To address these issues, we implemented a "self-reflection" process that refines suggestion ranking and eliminates irrelevant or incorrect proposals.
-This process consists of the following steps:
-
-1. Presenting the generated suggestions to the model in a follow-up call.
-2. Instructing the model to score each suggestion on a scale of 0-10 and provide a rationale for the assigned score.
-3. Utilizing these scores to re-rank the suggestions and filter out incorrect ones (with a score of 0).
-4. Optionally, filtering out all suggestions below a user-defined score threshold.
-
-Note that presenting all generated suggestions simultaneously provides the model with a comprehensive context, enabling it to make more informed decisions compared to evaluating each suggestion individually.
-
-To conclude, the self-reflection process enables Qodo Merge to prioritize suggestions based on their importance, eliminate inaccurate or irrelevant proposals, and optionally exclude suggestions that fall below a specified threshold of significance.
-This results in a more refined and valuable set of suggestions for the user, saving time and improving the overall experience.
-
-## Example Results
-
-![self_reflection](https://codium.ai/images/pr_agent/self_reflection1.png){width=768}
-![self_reflection](https://codium.ai/images/pr_agent/self_reflection2.png){width=768}
-
-
-## Appendix - Relevant Configuration Options
-```
-[pr_code_suggestions]
-suggestions_score_threshold	= 0 # Filter out suggestions with a score below this threshold (0-10)
-```

docs/docs/core-abilities/static_code_analysis.md

@@ -1,70 +0,0 @@
-## Overview - Static Code Analysis 💎
-
-By combining static code analysis with LLM capabilities, Qodo Merge can provide a comprehensive analysis of the PR code changes on a component level.
-
-It scans the PR code changes, finds all the code components (methods, functions, classes) that changed, and enables to interactively generate tests, docs, code suggestions and similar code search for each component.
-
-!!! note "Language that are currently supported:"
-    Python, Java, C++, JavaScript, TypeScript, C#.
-
-
-## Capabilities
-
-### Analyze PR
-
-
-The [`analyze`](https://qodo-merge-docs.qodo.ai/tools/analyze/) tool enables to interactively generate tests, docs, code suggestions and similar code search for each component that changed in the PR.
-It can be invoked manually by commenting on any PR:
-```
-/analyze
-```
-
-An example result:
-
-![Analyze 1](https://codium.ai/images/pr_agent/analyze_1.png){width=768}
-
-Clicking on each checkbox will trigger the relevant tool for the selected component.
-
-### Generate Tests
-
-The [`test`](https://qodo-merge-docs.qodo.ai/tools/test/) tool  generate tests for a selected component, based on the PR code changes.
-It can be invoked manually by commenting on any PR:
-```
-/test component_name
-```
-where 'component_name' is the name of a specific component in the PR,  Or be triggered interactively by using the `analyze` tool.
-
-![test1](https://codium.ai/images/pr_agent/test1.png){width=768}
-
-### Generate Docs for a Component
-
-The [`add_docs`](https://qodo-merge-docs.qodo.ai/tools/documentation/) tool scans the PR code changes, and automatically generate docstrings for any code components that changed in the PR.
-It can be invoked manually by commenting on any PR:
-```
-/add_docs component_name
-```
-
-Or be triggered interactively by using the `analyze` tool.
-
-![Docs single component](https://codium.ai/images/pr_agent/docs_single_component.png){width=768}
-
-### Generate Code Suggestions for a Component
-The [`improve_component`](https://qodo-merge-docs.qodo.ai/tools/improve_component/) tool generates code suggestions for a specific code component that changed in the PR.
-It can be invoked manually by commenting on any PR:
-```
-/improve_component component_name
-```
-
-Or be triggered interactively by using the `analyze` tool.
-
-![improve_component2](https://codium.ai/images/pr_agent/improve_component2.png){width=768}
-
-### Find Similar Code
-
-The [`similar code`](https://qodo-merge-docs.qodo.ai/tools/similar_code/) tool retrieves the most similar code components from inside the organization's codebase or from open-source code, including details about the license associated with each repository.
-
-For example:
-
-`Global Search` for a method called `chat_completion`:
-
-![similar code global](https://codium.ai/images/pr_agent/similar_code_global2.png){width=768}

docs/docs/css/custom.css

@@ -1,49 +0,0 @@
-
-
-:root {
-    --md-primary-fg-color: #765bfa;
-    --md-accent-fg-color: #AEA1F1;
-  }
-
-.md-nav--primary {
-    .md-nav__link {
-    font-size: 18px; /* Change the font size as per your preference */
-    }
-}
-
-.md-nav--primary {
-    position: relative; /* Ensure the element is positioned */
-}
-
-.md-nav--primary::before {
-    content: "";
-    position: absolute;
-    top: 0;
-    right: 10px; /* Move the border 10 pixels to the right */
-    width: 2px;
-    height: 100%;
-    background-color: #f5f5f5; /* Match the border color */
-}
-/*.md-nav__title, .md-nav__link  {*/
-/*    font-size: 18px;*/
-/*    margin-top: 14px; !* Adjust the space as needed *!*/
-/*    margin-bottom: 14px; !* Adjust the space as needed *!*/
-/*}*/
-
-.md-tabs__link  {
-    font-size: 18px;
-}
-
-.md-header__title {
-    font-size: 20px;
-    margin-left: 0px !important;
-}
-
-.md-content img {
-    border-width: 1px;
-    border-style: solid;
-    border-color: black;
-    outline-width: 1px;
-    outline-style: solid;
-    outline-color: darkgray;
-  }

docs/docs/faq/index.md

@@ -1,67 +0,0 @@
-# FAQ
-
-??? note "Question: Can Qodo Merge serve as a substitute for a human reviewer?"
-    #### Answer:<span style="display:none;">1</span>
-
-    Qodo Merge is designed to assist, not replace, human reviewers.
-
-    Reviewing PRs is a tedious and time-consuming task often seen as a "chore". In addition, the longer the PR – the shorter the relative feedback, since long PRs can overwhelm reviewers, both in terms of technical difficulty, and the actual review time.
-    Qodo Merge aims to address these pain points, and to assist and empower both the PR author and reviewer.
-
-    However, Qodo Merge has built-in safeguards to ensure the developer remains in the driver's seat. For example:
-
-    1. Preserves user's original PR header
-    2. Places user's description above the AI-generated PR description
-    3. Cannot approve PRs; approval remains reviewer's responsibility
-    4. The code suggestions are optional, and aim to:
-        - Encourage self-review and self-reflection
-        - Highlight potential bugs or oversights
-        - Enhance code quality and promote best practices
-
-    Read more about this issue in our [blog](https://www.codium.ai/blog/understanding-the-challenges-and-pain-points-of-the-pull-request-cycle/)
-
-___
-
-??? note "Question: I received an incorrect or irrelevant suggestion. Why?"
-
-    #### Answer:<span style="display:none;">2</span>
-
-    - Modern AI models, like Claude 3.5 Sonnet and GPT-4, are improving rapidly but remain imperfect. Users should critically evaluate all suggestions rather than accepting them automatically.
-    - AI errors are rare, but possible. A main value from reviewing the code suggestions lies in their high probability of catching **mistakes or bugs made by the PR author**. We believe it's worth spending 30-60 seconds reviewing suggestions, even if some aren't relevant, as this practice can enhances code quality and prevent bugs in production.
-
-
-    - The hierarchical structure of the suggestions is designed to help the user to _quickly_ understand them, and to decide which ones are relevant and which are not:
-
-        - Only if the `Category` header is relevant, the user should move to the summarized suggestion description.
-        - Only if the summarized suggestion description is relevant, the user should click on the collapsible, to read the full suggestion description with a code preview example.
-
-    - In addition, we recommend to use the [`extra_instructions`](https://qodo-merge-docs.qodo.ai/tools/improve/#extra-instructions-and-best-practices) field to guide the model to suggestions that are more relevant to the specific needs of the project.
-    - The interactive [PR chat](https://qodo-merge-docs.qodo.ai/chrome-extension/) also provides an easy way to get more tailored suggestions and feedback from the AI model.
-
-___
-
-??? note "Question: How can I get more tailored suggestions?"
-    #### Answer:<span style="display:none;">3</span>
-
-    See [here](https://qodo-merge-docs.qodo.ai/tools/improve/#extra-instructions-and-best-practices) for more information on how to use the `extra_instructions` and `best_practices` configuration options, to guide the model to more tailored suggestions.
-
-___
-
-??? note "Question: Will you store my code ? Are you using my code to train models?"
-    #### Answer:<span style="display:none;">4</span>
-
-    No. Qodo Merge strict privacy policy ensures that your code is not stored or used for training purposes.
-
-    For a detailed overview of our data privacy policy, please refer to [this link](https://qodo-merge-docs.qodo.ai/overview/data_privacy/)
-
-___
-
-??? note "Question: Can I use my own LLM keys with Qodo Merge?"
-    #### Answer:<span style="display:none;">5</span>
-
-    When you self-host, you use your own keys.
-
-    Qodo Merge Pro with SaaS deployment is a hosted version of Qodo Merge, where Qodo manages the infrastructure and the keys.
-    For enterprise customers, on-prem deployment is also available. [Contact us](https://www.codium.ai/contact/#pricing) for more information.
-
-___

docs/docs/finetuning_benchmark/index.md

@@ -1,93 +0,0 @@
-# Qodo Merge Code Fine-tuning Benchmark
-
-On coding tasks, the gap between open-source models and top closed-source models such as GPT4 is significant.
-<br>
-In practice, open-source models are unsuitable for most real-world code tasks, and require further fine-tuning to produce acceptable results.
-
-_Qodo Merge fine-tuning benchmark_ aims to benchmark open-source models on their ability to be fine-tuned for a coding task.
-Specifically, we chose to fine-tune open-source models on the task of analyzing a pull request, and providing useful feedback and code suggestions.
-
-Here are the results:
-<br>
-<br>
-
-**Model performance:**
-
-| Model name                  | Model size [B] | Better than gpt-4 rate, after fine-tuning [%] |
-|-----------------------------|----------------|----------------------------------------------|
-| **DeepSeek 34B-instruct**   | **34**         | **40.7**                                     |
-| DeepSeek 34B-base           | 34             | 38.2                                         |
-| Phind-34b                   | 34             | 38                                           |
-| Granite-34B                 | 34             | 37.6                                         |
-| Codestral-22B-v0.1          | 22             | 32.7                                         |
-| QWEN-1.5-32B                | 32             | 29                                           |
-|                             |                |                                              |
-| **CodeQwen1.5-7B**          | **7**          | **35.4**                                     |
-| Llama-3.1-8B-Instruct       | 8              | 35.2                                         |
-| Granite-8b-code-instruct    | 8              | 34.2                                         |
-| CodeLlama-7b-hf             | 7              | 31.8                                         |
-| Gemma-7B                    | 7              | 27.2                                         |
-| DeepSeek coder-7b-instruct  | 7              | 26.8                                         |
-| Llama-3-8B-Instruct         | 8              | 26.8                                         |
-| Mistral-7B-v0.1             | 7              | 16.1                                         |
-
-<br>
-
-**Fine-tuning impact:**
-
-| Model name                | Model size [B] | Fine-tuned | Better than gpt-4 rate [%] |
-|---------------------------|----------------|------------|----------------------------|
-| DeepSeek 34B-instruct     | 34             | yes        | 40.7                       |
-| DeepSeek 34B-instruct     | 34             | no         | 3.6                        |
-
-## Results analysis
-
-- **Fine-tuning is a must** - without fine-tuning, open-source models provide poor results on most real-world code tasks, which include complicated prompt and lengthy context. We clearly see that without fine-tuning, deepseek model was 96.4% of the time inferior to GPT-4, while after fine-tuning, it is better 40.7% of the time.
-- **Always start from a code-dedicated model** — When fine-tuning, always start from a code-dedicated model, and not from a general-usage model. The gaps in downstream results are very big.
-- **Don't believe the hype** —newer models, or models from big-tech companies (Llama3, Gemma, Mistral), are not always better for fine-tuning.
-- **The best large model** - For large 34B code-dedicated models, the gaps when doing proper fine-tuning are small. The current top model is **DeepSeek 34B-instruct**
-- **The best small model** - For small 7B code-dedicated models, the gaps when fine-tuning are much larger. **CodeQWEN 1.5-7B** is by far the best model for fine-tuning.
-- **Base vs. instruct** - For the top model (deepseek), we saw small advantage when starting from the instruct version. However, we recommend testing both versions on each specific task, as the base model is generally considered more suitable for fine-tuning.
-
-## The dataset
-
-### Training dataset
-
-Our training dataset comprises 25,000 pull requests, aggregated from permissive license repos. For each pull request, we generated responses for the three main tools of Qodo Merge:
-[Describe](https://qodo-merge-docs.qodo.ai/tools/describe/), [Review](https://qodo-merge-docs.qodo.ai/tools/improve/) and [Improve](https://qodo-merge-docs.qodo.ai/tools/improve/).
-
-On the raw data collected, we employed various automatic and manual cleaning techniques to ensure the outputs were of the highest quality, and suitable for instruct-tuning.
-
-Here are the prompts, and example outputs, used as input-output pairs to fine-tune the models:
-
-| Tool     | Prompt                                                                                                     | Example output |
-|----------|------------------------------------------------------------------------------------------------------------|----------------|
-| Describe | [link](https://github.com/Codium-ai/pr-agent/blob/main/pr_agent/settings/pr_description_prompts.toml) | [link](https://github.com/Codium-ai/pr-agent/pull/910#issue-2303989601)           |
-| Review   | [link](https://github.com/Codium-ai/pr-agent/blob/main/pr_agent/settings/pr_reviewer_prompts.toml) | [link](https://github.com/Codium-ai/pr-agent/pull/910#issuecomment-2118761219)           |
-| Improve  | [link](https://github.com/Codium-ai/pr-agent/blob/main/pr_agent/settings/pr_code_suggestions_prompts.toml) | [link](https://github.com/Codium-ai/pr-agent/pull/910#issuecomment-2118761309)           |
-
-### Evaluation dataset
-
-- For each tool, we aggregated 100 additional examples to be used for evaluation. These examples were not used in the training dataset, and were manually selected to represent diverse real-world use-cases.
-- For each test example, we generated two responses: one from the fine-tuned model, and one from the best code model in the world, `gpt-4-turbo-2024-04-09`.
-
-- We used a third LLM to judge which response better answers the prompt, and will likely be perceived by a human as better response.
-<br>
-
-We experimented with three model as judges: `gpt-4-turbo-2024-04-09`, `gpt-4o`, and `claude-3-opus-20240229`. All three produced similar results, with the same ranking order. This strengthens the validity of our testing protocol.
-The evaluation prompt can be found [here](https://github.com/Codium-ai/pr-agent/blob/main/pr_agent/settings/pr_evaluate_prompt_response.toml)
-
-Here is an example of a judge model feedback:
-
-```
-command: improve
-model1_score: 9,
-model2_score: 6,
-why: |
-  Response 1 is better because it provides more actionable and specific suggestions that directly
-  enhance the code's maintainability, performance, and best practices. For example, it suggests
-  using a variable for reusable widget instances and using named routes for navigation, which
-  are practical improvements. In contrast, Response 2 focuses more on general advice and less
-  actionable suggestions, such as changing variable names and adding comments, which are less
-  critical for immediate code improvement."
-```

docs/docs/index.md

@@ -1,100 +0,0 @@
-# Overview
-
-Qodo Merge is an open-source tool to help efficiently review and handle pull requests.
-
-- See the [Installation Guide](./installation/index.md) for instructions on installing and running the tool on different git platforms.
-
-- See the [Usage Guide](./usage-guide/index.md) for instructions on running the Qodo Merge commands via different interfaces, including _CLI_, _online usage_, or by _automatically triggering_ them when a new PR is opened.
-
-- See the [Tools Guide](./tools/index.md) for a detailed description of the different tools.
-
-
-## Qodo Merge Docs Smart Search
-
-To search the documentation site using natural language:
-
-1) Comment `/help "your question"` in either:
-
-   - A pull request where Qodo Merge is installed
-   - A [PR Chat](https://qodo-merge-docs.qodo.ai/chrome-extension/features/#pr-chat)
-
-2) Qodo Merge will respond with an [answer](https://github.com/Codium-ai/pr-agent/pull/1241#issuecomment-2365259334) that includes relevant documentation links.
-
-
-## Qodo Merge Features
-
-Qodo Merge offers extensive pull request functionalities across various git providers.
-
-|       |                                                                                                         | GitHub             | GitLab             | Bitbucket          | Azure DevOps |
-|-------|---------------------------------------------------------------------------------------------------------|:--------------------:|:--------------------:|:--------------------:|:------------:|
-| TOOLS | [Review](https://qodo-merge-docs.qodo.ai/tools/review/)                                                                                                  | ✅ | ✅ | ✅ |      ✅       |
-|       | [Describe](https://qodo-merge-docs.qodo.ai/tools/describe/)                                                                                                | ✅ | ✅ | ✅ |      ✅       |
-|       | [Improve](https://qodo-merge-docs.qodo.ai/tools/improve/)                                                                                                 | ✅ | ✅ | ✅ |      ✅       |
-|       | [Ask](https://qodo-merge-docs.qodo.ai/tools/ask/)                                                                                                     | ✅ | ✅ | ✅ |      ✅       |
-|       | ⮑ [Ask on code lines](https://pr-agent-docs.codium.ai/tools/ask#ask-lines)                              | ✅ | ✅ |                    |              |
-|       | [Update CHANGELOG](https://qodo-merge-docs.qodo.ai/tools/update_changelog/)                                                                                     | ✅ | ✅ | ✅ |      ✅       |
-|       | [Ticket Context](https://qodo-merge-docs.qodo.ai/core-abilities/fetching_ticket_context/) 💎  | ✅ | ✅ |  ✅                  |   |
-|       | [Utilizing Best Practices](https://qodo-merge-docs.qodo.ai/tools/improve/#best-practices) 💎  | ✅ | ✅ |  ✅                  |   |
-|       | [PR Chat](https://qodo-merge-docs.qodo.ai/chrome-extension/features/#pr-chat) 💎  | ✅ |  |                    |   |
-|       | [Suggestion Tracking](https://qodo-merge-docs.qodo.ai/tools/improve/#suggestion-tracking) 💎  | ✅ | ✅ |                    |   |
-|       | [CI Feedback](https://pr-agent-docs.codium.ai/tools/ci_feedback/) 💎                                    | ✅ |                    |                    |              |
-|       | [PR Documentation](https://pr-agent-docs.codium.ai/tools/documentation/) 💎                         | ✅ | ✅ |                   |              |
-|       | [Custom Labels](https://pr-agent-docs.codium.ai/tools/custom_labels/) 💎                                | ✅ | ✅ |                    |              |
-|       | [Analyze](https://pr-agent-docs.codium.ai/tools/analyze/) 💎                                            | ✅ | ✅ |                    |              |
-|       | [Similar Code](https://pr-agent-docs.codium.ai/tools/similar_code/) 💎                                  | ✅ |                    |                    |              |
-|       | [Custom Prompt](https://pr-agent-docs.codium.ai/tools/custom_prompt/) 💎                                | ✅ | ✅ | ✅ |              |
-|       | [Test](https://pr-agent-docs.codium.ai/tools/test/) 💎                                                  | ✅ | ✅ |                    |              |
-|       |                                                                                                         |                    |                    |                    |              |
-| USAGE | [CLI](https://qodo-merge-docs.qodo.ai/usage-guide/automations_and_usage/#local-repo-cli)                                                                                                     | ✅ | ✅ | ✅ |      ✅       |
-|       | [App / webhook](https://qodo-merge-docs.qodo.ai/usage-guide/automations_and_usage/#github-app)                                                                                           | ✅ | ✅ | ✅ |      ✅       |
-|       | [Tagging bot](https://github.com/Codium-ai/pr-agent#try-it-now)                                                                                             | ✅ |                    |                    |              |
-|       | [Actions](https://qodo-merge-docs.qodo.ai/installation/github/#run-as-a-github-action)                                                                                                 | ✅ |✅| ✅ |✅|
-|       |                                                                                                         |                    |                    |                    |              |
-| CORE  | [PR compression](https://qodo-merge-docs.qodo.ai/core-abilities/compression_strategy/)                                                                  | ✅ | ✅ | ✅ |      ✅       |
-|       | Adaptive and token-aware file patch fitting                                                             | ✅ | ✅ | ✅ |      ✅       |
-|       | [Multiple models support](https://qodo-merge-docs.qodo.ai/usage-guide/changing_a_model/)                                                                                 | ✅ | ✅ | ✅ |      ✅       |
-|       | [Local and global metadata](https://qodo-merge-docs.qodo.ai/core-abilities/metadata/)          | ✅ | ✅ | ✅ | ✅             |
-|       | [Dynamic context](https://qodo-merge-docs.qodo.ai/core-abilities/dynamic_context/)          | ✅ | ✅ | ✅ | ✅             |
-|       | [Self reflection](https://qodo-merge-docs.qodo.ai/core-abilities/self_reflection/)          | ✅ | ✅ | ✅ | ✅             |
-|       | [Static code analysis](https://qodo-merge-docs.qodo.ai/core-abilities/static_code_analysis/) 💎         | ✅ | ✅ | ✅ |              |
-|       | [Global and wiki configurations](https://pr-agent-docs.codium.ai/usage-guide/configuration_options/) 💎 | ✅ | ✅ | ✅ |              |
-|       | [PR interactive actions](https://www.codium.ai/images/pr_agent/pr-actions.mp4) 💎                       | ✅ |        ✅           |                    |              |
-|       | [Impact Evaluation](https://qodo-merge-docs.qodo.ai/core-abilities/impact_evaluation/) 💎  | ✅ | ✅ |                    |   |
-
-💎 marks a feature available only in [Qodo Merge Pro](https://www.qodo.ai/pricing/){:target="_blank"}
-
-
-## Example Results
-<hr>
-
-#### [/describe](https://github.com/Codium-ai/pr-agent/pull/530)
-<figure markdown="1">
-![/describe](https://www.codium.ai/images/pr_agent/describe_new_short_main.png){width=512}
-</figure>
-<hr>
-
-#### [/review](https://github.com/Codium-ai/pr-agent/pull/732#issuecomment-1975099151)
-<figure markdown="1">
-![/review](https://www.codium.ai/images/pr_agent/review_new_short_main.png){width=512}
-</figure>
-<hr>
-
-#### [/improve](https://github.com/Codium-ai/pr-agent/pull/732#issuecomment-1975099159)
-<figure markdown="1">
-![/improve](https://www.codium.ai/images/pr_agent/improve_new_short_main.png){width=512}
-</figure>
-<hr>
-
-#### [/generate_labels](https://github.com/Codium-ai/pr-agent/pull/530)
-<figure markdown="1">
-![/generate_labels](https://www.codium.ai/images/pr_agent/geneare_custom_labels_main_short.png){width=300}
-</figure>
-<hr>
-
-## How it Works
-
-The following diagram illustrates Qodo Merge tools and their flow:
-
-![Qodo Merge Tools](https://codium.ai/images/pr_agent/diagram-v0.9.png)
-
-Check out the [core abilities](core-abilities/index.md) page for a comprehensive overview of the variety of core abilities used by Qodo Merge.

docs/docs/installation/azure.md

@@ -1,95 +0,0 @@
-## Azure DevOps Pipeline
-You can use a pre-built Action Docker image to run Qodo Merge as an Azure devops pipeline.
-add the following file to your repository under `azure-pipelines.yml`:
-```yaml
-# Opt out of CI triggers
-trigger: none
-
-# Configure PR trigger
-pr:
-  branches:
-    include:
-    - '*'
-  autoCancel: true
-  drafts: false
-
-stages:
-- stage: pr_agent
-  displayName: 'PR Agent Stage'
-  jobs:
-  - job: pr_agent_job
-    displayName: 'PR Agent Job'
-    pool:
-      vmImage: 'ubuntu-latest'
-    container:
-      image: codiumai/pr-agent:latest
-      options: --entrypoint ""
-    variables:
-      - group: pr_agent
-    steps:
-    - script: |
-        echo "Running PR Agent action step"
-
-        # Construct PR_URL
-        PR_URL="${SYSTEM_COLLECTIONURI}${SYSTEM_TEAMPROJECT}/_git/${BUILD_REPOSITORY_NAME}/pullrequest/${SYSTEM_PULLREQUEST_PULLREQUESTID}"
-        echo "PR_URL=$PR_URL"
-
-        # Extract organization URL from System.CollectionUri
-        ORG_URL=$(echo "$(System.CollectionUri)" | sed 's/\/$//') # Remove trailing slash if present
-        echo "Organization URL: $ORG_URL"
-
-        export azure_devops__org="$ORG_URL"
-        export config__git_provider="azure"
-
-        pr-agent --pr_url="$PR_URL" describe
-        pr-agent --pr_url="$PR_URL" review
-        pr-agent --pr_url="$PR_URL" improve
-      env:
-        azure_devops__pat: $(azure_devops_pat)
-        openai__key: $(OPENAI_KEY)
-      displayName: 'Run Qodo Merge'
-```
-This script will run Qodo Merge on every new merge request, with the `improve`, `review`, and `describe` commands.
-Note that you need to export the `azure_devops__pat` and `OPENAI_KEY` variables in the Azure DevOps pipeline settings (Pipelines -> Library -> + Variable group):
-
-![Qodo Merge Pro](https://codium.ai/images/pr_agent/azure_devops_pipeline_secrets.png){width=468}
-
-Make sure to give pipeline permissions to the `pr_agent` variable group.
-
-> Note that Azure Pipelines lacks support for triggering workflows from PR comments. If you find a viable solution, please contribute it to our [issue tracker](https://github.com/Codium-ai/pr-agent/issues)
-
-## Azure DevOps from CLI
-
-To use Azure DevOps provider use the following settings in configuration.toml:
-```
-[config]
-git_provider="azure"
-```
-
-Azure DevOps provider supports [PAT token](https://learn.microsoft.com/en-us/azure/devops/organizations/accounts/use-personal-access-tokens-to-authenticate?view=azure-devops&tabs=Windows) or [DefaultAzureCredential](https://learn.microsoft.com/en-us/azure/developer/python/sdk/authentication-overview#authentication-in-server-environments) authentication.
-PAT is faster to create, but has build in expiration date, and will use the user identity for API calls.
-Using DefaultAzureCredential you can use managed identity or Service principle, which are more secure and will create separate ADO user identity (via AAD) to the agent.
-
-If PAT was chosen, you can assign the value in .secrets.toml.
-If DefaultAzureCredential was chosen, you can assigned the additional env vars like AZURE_CLIENT_SECRET directly,
-or use managed identity/az cli (for local development) without any additional configuration.
-in any case, 'org' value must be assigned in .secrets.toml:
-```
-[azure_devops]
-org = "https://dev.azure.com/YOUR_ORGANIZATION/"
-# pat = "YOUR_PAT_TOKEN" needed only if using PAT for authentication
-```
-
-### Azure DevOps Webhook
-
-To trigger from an Azure webhook, you need to manually [add a webhook](https://learn.microsoft.com/en-us/azure/devops/service-hooks/services/webhooks?view=azure-devops).
-Use the "Pull request created" type to trigger a review, or "Pull request commented on" to trigger any supported comment with /<command> <args> comment on the relevant PR. Note that for the "Pull request commented on" trigger, only API v2.0 is supported.
-
-
-For webhook security, create a sporadic username/password pair and configure the webhook username and password on both the server and Azure DevOps webhook. These will be sent as basic Auth data by the webhook with each request:
-```
-[azure_devops_server]
-webhook_username = "<basic auth user>"
-webhook_password = "<basic auth password>"
-```
-> :warning: **Ensure that the webhook endpoint is only accessible over HTTPS** to mitigate the risk of credential interception when using basic authentication.

docs/docs/installation/bitbucket.md

@@ -1,70 +0,0 @@
-## Run as a Bitbucket Pipeline
-
-
-You can use the Bitbucket Pipeline system to run Qodo Merge on every pull request open or update.
-
-1. Add the following file in your repository bitbucket-pipelines.yml
-
-```yaml
-pipelines:
-    pull-requests:
-      '**':
-        - step:
-            name: PR Agent Review
-            image: python:3.10
-            services:
-              - docker
-            script:
-              - docker run -e CONFIG.GIT_PROVIDER=bitbucket -e OPENAI.KEY=$OPENAI_API_KEY -e BITBUCKET.BEARER_TOKEN=$BITBUCKET_BEARER_TOKEN codiumai/pr-agent:latest --pr_url=https://bitbucket.org/$BITBUCKET_WORKSPACE/$BITBUCKET_REPO_SLUG/pull-requests/$BITBUCKET_PR_ID review
-```
-
-2. Add the following secure variables to your repository under Repository settings > Pipelines > Repository variables.
-OPENAI_API_KEY: `<your key>`
-BITBUCKET_BEARER_TOKEN: `<your token>`
-
-You can get a Bitbucket token for your repository by following Repository Settings -> Security -> Access Tokens.
-
-Note that comments on a PR are not supported in Bitbucket Pipeline.
-
-
-## Run using CodiumAI-hosted Bitbucket app 💎
-
-Please contact visit [Qodo Merge Pro](https://www.codium.ai/pricing/) if you're interested in a hosted BitBucket app solution that provides full functionality including PR reviews and comment handling. It's based on the [bitbucket_app.py](https://github.com/Codium-ai/pr-agent/blob/main/pr_agent/git_providers/bitbucket_provider.py) implementation.
-
-
-## Bitbucket Server and Data Center
-
-Login into your on-prem instance of Bitbucket with your service account username and password.
-Navigate to `Manage account`, `HTTP Access tokens`, `Create Token`.
-Generate the token and add it to .secret.toml under `bitbucket_server` section
-
-```toml
-[bitbucket_server]
-bearer_token = "<your key>"
-```
-
-### Run it as CLI
-
-Modify `configuration.toml`:
-
-```toml
-git_provider="bitbucket_server"
-```
-
-and pass the Pull request URL:
-```shell
-python cli.py --pr_url https://git.onpreminstanceofbitbucket.com/projects/PROJECT/repos/REPO/pull-requests/1 review
-```
-
-### Run it as service
-
-To run Qodo Merge as webhook, build the docker image:
-```
-docker build . -t codiumai/pr-agent:bitbucket_server_webhook --target bitbucket_server_webhook -f docker/Dockerfile
-docker push codiumai/pr-agent:bitbucket_server_webhook  # Push to your Docker repository
-```
-
-Navigate to `Projects` or `Repositories`, `Settings`, `Webhooks`, `Create Webhook`.
-Fill the name and URL, Authentication None select the Pull Request Opened checkbox to receive that event as webhook.
-
-The URL should end with `/webhook`, for example: https://domain.com/webhook

docs/docs/installation/github.md

@@ -1,268 +0,0 @@
-## Run as a GitHub Action
-
-You can use our pre-built Github Action Docker image to run Qodo Merge as a Github Action.
-
-1) Add the following file to your repository under `.github/workflows/pr_agent.yml`:
-
-```yaml
-on:
-  pull_request:
-    types: [opened, reopened, ready_for_review]
-  issue_comment:
-jobs:
-  pr_agent_job:
-    if: ${{ github.event.sender.type != 'Bot' }}
-    runs-on: ubuntu-latest
-    permissions:
-      issues: write
-      pull-requests: write
-      contents: write
-    name: Run pr agent on every pull request, respond to user comments
-    steps:
-      - name: PR Agent action step
-        id: pragent
-        uses: Codium-ai/pr-agent@main
-        env:
-          OPENAI_KEY: ${{ secrets.OPENAI_KEY }}
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-```
-
-2) Add the following secret to your repository under `Settings > Secrets and variables > Actions > New repository secret > Add secret`:
-
-```
-Name = OPENAI_KEY
-Secret = <your key>
-```
-
-The GITHUB_TOKEN secret is automatically created by GitHub.
-
-3) Merge this change to your main branch.
-When you open your next PR, you should see a comment from `github-actions` bot with a review of your PR, and instructions on how to use the rest of the tools.
-
-4) You may configure Qodo Merge by adding environment variables under the env section corresponding to any configurable property in the [configuration](https://github.com/Codium-ai/pr-agent/blob/main/pr_agent/settings/configuration.toml) file. Some examples:
-```yaml
-      env:
-        # ... previous environment values
-        OPENAI.ORG: "<Your organization name under your OpenAI account>"
-        PR_REVIEWER.REQUIRE_TESTS_REVIEW: "false" # Disable tests review
-        PR_CODE_SUGGESTIONS.NUM_CODE_SUGGESTIONS: 6 # Increase number of code suggestions
-```
-See detailed usage instructions in the [USAGE GUIDE](https://qodo-merge-docs.qodo.ai/usage-guide/automations_and_usage/#github-action)
-
-### Using a specific release
-!!! tip ""
-    if you want to pin your action to a specific release (v0.23 for example) for stability reasons, use:
-    ```yaml
-    ...
-        steps:
-          - name: PR Agent action step
-            id: pragent
-            uses: docker://codiumai/pr-agent:0.23-github_action
-    ...
-    ```
-
-    For enhanced security, you can also specify the Docker image by its [digest](https://hub.docker.com/repository/docker/codiumai/pr-agent/tags):
-    ```yaml
-    ...
-        steps:
-          - name: PR Agent action step
-            id: pragent
-            uses: docker://codiumai/pr-agent@sha256:14165e525678ace7d9b51cda8652c2d74abb4e1d76b57c4a6ccaeba84663cc64
-    ...
-    ```
-
-### Action for GitHub enterprise server
-!!! tip ""
-    To use the action with a GitHub enterprise server, add an environment variable `GITHUB.BASE_URL` with the API URL of your GitHub server.
-
-    For example, if your GitHub server is at `https://github.mycompany.com`, add the following to your workflow file:
-    ```yaml
-          env:
-            # ... previous environment values
-            GITHUB.BASE_URL: "https://github.mycompany.com/api/v3"
-    ```
-
-
----
-
-## Run as a GitHub App
-Allowing you to automate the review process on your private or public repositories.
-
-1) Create a GitHub App from the [Github Developer Portal](https://docs.github.com/en/developers/apps/creating-a-github-app).
-
-   - Set the following permissions:
-     - Pull requests: Read & write
-     - Issue comment: Read & write
-     - Metadata: Read-only
-     - Contents: Read-only
-   - Set the following events:
-     - Issue comment
-     - Pull request
-     - Push (if you need to enable triggering on PR update)
-
-2) Generate a random secret for your app, and save it for later. For example, you can use:
-
-```
-WEBHOOK_SECRET=$(python -c "import secrets; print(secrets.token_hex(10))")
-```
-
-3) Acquire the following pieces of information from your app's settings page:
-
-   - App private key (click "Generate a private key" and save the file)
-   - App ID
-
-4) Clone this repository:
-
-```
-git clone https://github.com/Codium-ai/pr-agent.git
-```
-
-5) Copy the secrets template file and fill in the following:
-
-```
-cp pr_agent/settings/.secrets_template.toml pr_agent/settings/.secrets.toml
-# Edit .secrets.toml file
-```
-
-   - Your OpenAI key.
-   - Copy your app's private key to the private_key field.
-   - Copy your app's ID to the app_id field.
-   - Copy your app's webhook secret to the webhook_secret field.
-   - Set deployment_type to 'app' in [configuration.toml](https://github.com/Codium-ai/pr-agent/blob/main/pr_agent/settings/configuration.toml)
-
-    > The .secrets.toml file is not copied to the Docker image by default, and is only used for local development.
-    > If you want to use the .secrets.toml file in your Docker image, you can add remove it from the .dockerignore file.
-    > In most production environments, you would inject the secrets file as environment variables or as mounted volumes.
-    > For example, in order to inject a secrets file as a volume in a Kubernetes environment you can update your pod spec to include the following,
-    > assuming you have a secret named `pr-agent-settings` with a key named `.secrets.toml`:
-    ```
-           volumes:
-            - name: settings-volume
-              secret:
-                secretName: pr-agent-settings
-    // ...
-           containers:
-    // ...
-              volumeMounts:
-                - mountPath: /app/pr_agent/settings_prod
-                  name: settings-volume
-    ```
-
-    > Another option is to set the secrets as environment variables in your deployment environment, for example `OPENAI.KEY` and `GITHUB.USER_TOKEN`.
-
-6) Build a Docker image for the app and optionally push it to a Docker repository. We'll use Dockerhub as an example:
-
-    ```
-    docker build . -t codiumai/pr-agent:github_app --target github_app -f docker/Dockerfile
-    docker push codiumai/pr-agent:github_app  # Push to your Docker repository
-    ```
-
-7. Host the app using a server, serverless function, or container environment. Alternatively, for development and
-   debugging, you may use tools like smee.io to forward webhooks to your local machine.
-    You can check [Deploy as a Lambda Function](#deploy-as-a-lambda-function)
-
-8. Go back to your app's settings, and set the following:
-
-   - Webhook URL: The URL of your app's server or the URL of the smee.io channel.
-   - Webhook secret: The secret you generated earlier.
-
-9. Install the app by navigating to the "Install App" tab and selecting your desired repositories.
-
-> **Note:** When running Qodo Merge from GitHub app, the default configuration file (configuration.toml) will be loaded.
-> However, you can override the default tool parameters by uploading a local configuration file `.pr_agent.toml`
-> For more information please check out the [USAGE GUIDE](../usage-guide/automations_and_usage.md#github-app)
----
-
-## Deploy as a Lambda Function
-
-Note that since AWS Lambda env vars cannot have "." in the name, you can replace each "." in an env variable with "__".<br>
-For example: `GITHUB.WEBHOOK_SECRET` --> `GITHUB__WEBHOOK_SECRET`
-
-1. Follow steps 1-5 from [here](#run-as-a-github-app).
-2. Build a docker image that can be used as a lambda function
-    ```shell
-    docker buildx build --platform=linux/amd64 . -t codiumai/pr-agent:serverless -f docker/Dockerfile.lambda
-   ```
-3. Push image to ECR
-    ```shell
-	docker tag codiumai/pr-agent:serverless <AWS_ACCOUNT>.dkr.ecr.<AWS_REGION>.amazonaws.com/codiumai/pr-agent:serverless
-	docker push <AWS_ACCOUNT>.dkr.ecr.<AWS_REGION>.amazonaws.com/codiumai/pr-agent:serverless
-    ```
-4. Create a lambda function that uses the uploaded image. Set the lambda timeout to be at least 3m.
-5. Configure the lambda function to have a Function URL.
-6. In the environment variables of the Lambda function, specify `AZURE_DEVOPS_CACHE_DIR` to a writable location such as /tmp. (see [link](https://github.com/Codium-ai/pr-agent/pull/450#issuecomment-1840242269))
-7. Go back to steps 8-9 of [Method 5](#run-as-a-github-app) with the function url as your Webhook URL.
-    The Webhook URL would look like `https://<LAMBDA_FUNCTION_URL>/api/v1/github_webhooks`
-
----
-
-## AWS CodeCommit Setup
-
-Not all features have been added to CodeCommit yet.  As of right now, CodeCommit has been implemented to run the Qodo Merge CLI on the command line, using AWS credentials stored in environment variables.  (More features will be added in the future.)  The following is a set of instructions to have Qodo Merge do a review of your CodeCommit pull request from the command line:
-
-1. Create an IAM user that you will use to read CodeCommit pull requests and post comments
-    * Note: That user should have CLI access only, not Console access
-2. Add IAM permissions to that user, to allow access to CodeCommit (see IAM Role example below)
-3. Generate an Access Key for your IAM user
-4. Set the Access Key and Secret using environment variables (see Access Key example below)
-5. Set the `git_provider` value to `codecommit` in the `pr_agent/settings/configuration.toml` settings file
-6. Set the `PYTHONPATH` to include your `pr-agent` project directory
-    * Option A: Add `PYTHONPATH="/PATH/TO/PROJECTS/pr-agent` to your `.env` file
-    * Option B: Set `PYTHONPATH` and run the CLI in one command, for example:
-        * `PYTHONPATH="/PATH/TO/PROJECTS/pr-agent python pr_agent/cli.py [--ARGS]`
-
----
-
-
-#### AWS CodeCommit IAM Role Example
-
-Example IAM permissions to that user to allow access to CodeCommit:
-
-* Note: The following is a working example of IAM permissions that has read access to the repositories and write access to allow posting comments
-* Note: If you only want pr-agent to review your pull requests, you can tighten the IAM permissions further, however this IAM example will work, and allow the pr-agent to post comments to the PR
-* Note: You may want to replace the `"Resource": "*"` with your list of repos, to limit access to only those repos
-
-```
-{
-    "Version": "2012-10-17",
-    "Statement": [
-        {
-            "Effect": "Allow",
-            "Action": [
-                "codecommit:BatchDescribe*",
-                "codecommit:BatchGet*",
-                "codecommit:Describe*",
-                "codecommit:EvaluatePullRequestApprovalRules",
-                "codecommit:Get*",
-                "codecommit:List*",
-                "codecommit:PostComment*",
-                "codecommit:PutCommentReaction",
-                "codecommit:UpdatePullRequestDescription",
-                "codecommit:UpdatePullRequestTitle"
-            ],
-            "Resource": "*"
-        }
-    ]
-}
-```
-
-#### AWS CodeCommit Access Key and Secret
-
-Example setting the Access Key and Secret using environment variables
-
-```sh
-export AWS_ACCESS_KEY_ID="XXXXXXXXXXXXXXXX"
-export AWS_SECRET_ACCESS_KEY="XXXXXXXXXXXXXXXX"
-export AWS_DEFAULT_REGION="us-east-1"
-```
-
-#### AWS CodeCommit CLI Example
-
-After you set up AWS CodeCommit using the instructions above, here is an example CLI run that tells pr-agent to **review** a given pull request.
-(Replace your specific PYTHONPATH and PR URL in the example)
-
-```sh
-PYTHONPATH="/PATH/TO/PROJECTS/pr-agent" python pr_agent/cli.py \
-  --pr_url https://us-east-1.console.aws.amazon.com/codesuite/codecommit/repositories/MY_REPO_NAME/pull-requests/321 \
-  review
-```

docs/docs/installation/gitlab.md

@@ -1,78 +0,0 @@
-## Run as a GitLab Pipeline
-You can use a pre-built Action Docker image to run Qodo Merge as a GitLab pipeline. This is a simple way to get started with Qodo Merge without setting up your own server.
-
-(1) Add the following file to your repository under `.gitlab-ci.yml`:
-```yaml
-stages:
-  - pr_agent
-
-pr_agent_job:
-  stage: pr_agent
-  image:
-    name: codiumai/pr-agent:latest
-    entrypoint: [""]
-  script:
-    - cd /app
-    - echo "Running PR Agent action step"
-    - export MR_URL="$CI_MERGE_REQUEST_PROJECT_URL/merge_requests/$CI_MERGE_REQUEST_IID"
-    - echo "MR_URL=$MR_URL"
-    - export gitlab__url=$CI_SERVER_PROTOCOL://$CI_SERVER_FQDN
-    - export gitlab__PERSONAL_ACCESS_TOKEN=$GITLAB_PERSONAL_ACCESS_TOKEN
-    - export config__git_provider="gitlab"
-    - export openai__key=$OPENAI_KEY
-    - python -m pr_agent.cli --pr_url="$MR_URL" describe
-    - python -m pr_agent.cli --pr_url="$MR_URL" review
-    - python -m pr_agent.cli --pr_url="$MR_URL" improve
-  rules:
-    - if: '$CI_PIPELINE_SOURCE == "merge_request_event"'
-```
-This script will run Qodo Merge on every new merge request. You can modify the `rules` section to run Qodo Merge on different events.
-You can also modify the `script` section to run different Qodo Merge commands, or with different parameters by exporting different environment variables.
-
-
-(2) Add the following masked variables to your GitLab repository (CI/CD -> Variables):
-
-- `GITLAB_PERSONAL_ACCESS_TOKEN`: Your GitLab personal access token.
-
-- `OPENAI_KEY`: Your OpenAI key.
-
-Note that if your base branches are not protected, don't set the variables as `protected`, since the pipeline will not have access to them.
-
-> **Note**: The `$CI_SERVER_FQDN` variable is available starting from GitLab version 16.10. If you're using an earlier version, this variable will not be available. However, you can combine `$CI_SERVER_HOST` and `$CI_SERVER_PORT` to achieve the same result. Please ensure you're using a compatible version or adjust your configuration.
-
-
-## Run a GitLab webhook server
-
-1. From the GitLab workspace or group, create an access token with "Reporter" role ("Developer" if using Pro version of the agent) and "api" scope.
-
-2. Generate a random secret for your app, and save it for later. For example, you can use:
-
-```
-WEBHOOK_SECRET=$(python -c "import secrets; print(secrets.token_hex(10))")
-```
-
-3. Clone this repository:
-
-```
-git clone https://github.com/Codium-ai/pr-agent.git
-```
-
-4. Prepare variables and secrets. Skip this step if you plan on settings these as environment variables when running the agent:
-  1. In the configuration file/variables:
-    - Set `deployment_type` to "gitlab"
-
-  2. In the secrets file/variables:
-    - Set your AI model key in the respective section
-    - In the [gitlab] section, set `personal_access_token` (with token from step 1) and `shared_secret` (with secret from step 2)
-
-
-5. Build a Docker image for the app and optionally push it to a Docker repository. We'll use Dockerhub as an example:
-```
-docker build . -t gitlab_pr_agent --target gitlab_webhook -f docker/Dockerfile
-docker push codiumai/pr-agent:gitlab_webhook  # Push to your Docker repository
-```
-
-6. Create a webhook in GitLab. Set the URL to ```http[s]://<PR_AGENT_HOSTNAME>/webhook```, the secret token to the generated secret from step 2, and enable the triggers `push`, `comments` and `merge request events`.
-
-7. Test your installation by opening a merge request or commenting on a merge request using one of CodiumAI's commands.
-boxes

docs/docs/installation/index.md

@@ -1,21 +0,0 @@
-# Installation
-
-## Self-hosted Qodo Merge
-If you choose to host your own Qodo Merge, you first need to acquire two tokens:
-
-1. An OpenAI key from [here](https://platform.openai.com/api-keys), with access to GPT-4 (or a key for other [language models](https://qodo-merge-docs.qodo.ai/usage-guide/changing_a_model/), if you prefer).
-2. A GitHub\GitLab\BitBucket personal access token (classic), with the repo scope. [GitHub from [here](https://github.com/settings/tokens)]
-
-There are several ways to use self-hosted Qodo Merge:
-
-- [Locally](./locally.md)
-- [GitHub](./github.md)
-- [GitLab](./gitlab.md)
-- [BitBucket](./bitbucket.md)
-- [Azure DevOps](./azure.md)
-
-## Qodo Merge Pro 💎
-Qodo Merge Pro, an app hosted by CodiumAI for GitHub\GitLab\BitBucket, is also available.
-<br>
-With Qodo Merge Pro, installation is as simple as signing up and adding the Qodo Merge app to your relevant repo.
-See [here](https://qodo-merge-docs.qodo.ai/installation/pr_agent_pro/) for more details.

docs/docs/installation/locally.md

@@ -1,113 +0,0 @@
-## Using pip package
-
-Install the package:
-
-```
-pip install pr-agent
-```
-
-Then run the relevant tool with the script below.
-<br>
-Make sure to fill in the required parameters (`user_token`, `openai_key`, `pr_url`, `command`):
-
-```python
-from pr_agent import cli
-from pr_agent.config_loader import get_settings
-
-def main():
-    # Fill in the following values
-    provider = "github" # github/gitlab/bitbucket/azure_devops
-    user_token = "..."  #  user token
-    openai_key = "..."  # OpenAI key
-    pr_url = "..."      # PR URL, for example 'https://github.com/Codium-ai/pr-agent/pull/809'
-    command = "/review" # Command to run (e.g. '/review', '/describe', '/ask="What is the purpose of this PR?"', ...)
-
-    # Setting the configurations
-    get_settings().set("CONFIG.git_provider", provider)
-    get_settings().set("openai.key", openai_key)
-    get_settings().set("github.user_token", user_token)
-
-    # Run the command. Feedback will appear in GitHub PR comments
-    cli.run_command(pr_url, command)
-
-
-if __name__ == '__main__':
-    main()
-```
-
-## Using Docker image
-
-A list of the relevant tools can be found in the [tools guide](../tools/ask.md).
-
-To invoke a tool (for example `review`), you can run directly from the Docker image. Here's how:
-
-- For GitHub:
-    ```
-    docker run --rm -it -e OPENAI.KEY=<your key> -e GITHUB.USER_TOKEN=<your token> codiumai/pr-agent:latest --pr_url <pr_url> review
-    ```
-    If you are using GitHub enterprise server, you need to specify the custom url as variable.
-    For example, if your GitHub server is at `https://github.mycompany.com`, add the following to the command:
-    ```
-    -e GITHUB.BASE_URL=https://github.mycompany.com/api/v3
-    ```
-
-- For GitLab:
-    ```
-    docker run --rm -it -e OPENAI.KEY=<your key> -e CONFIG.GIT_PROVIDER=gitlab -e GITLAB.PERSONAL_ACCESS_TOKEN=<your token> codiumai/pr-agent:latest --pr_url <pr_url> review
-    ```
-
-    If you have a dedicated GitLab instance, you need to specify the custom url as variable:
-    ```
-    -e GITLAB.URL=<your gitlab instance url>
-    ```
-
-- For BitBucket:
-    ```
-    docker run --rm -it -e CONFIG.GIT_PROVIDER=bitbucket -e OPENAI.KEY=$OPENAI_API_KEY -e BITBUCKET.BEARER_TOKEN=$BITBUCKET_BEARER_TOKEN codiumai/pr-agent:latest --pr_url=<pr_url> review
-    ```
-
-For other git providers, update CONFIG.GIT_PROVIDER accordingly, and check the `pr_agent/settings/.secrets_template.toml` file for the environment variables expected names and values.
-
----
-
-## Run from source
-
-1. Clone this repository:
-
-```
-git clone https://github.com/Codium-ai/pr-agent.git
-```
-
-2. Navigate to the `/pr-agent` folder and install the requirements in your favorite virtual environment:
-
-```
-pip install -e .
-```
-
-*Note: If you get an error related to Rust in the dependency installation then make sure Rust is installed and in your `PATH`, instructions: https://rustup.rs*
-
-3. Copy the secrets template file and fill in your OpenAI key and your GitHub user token:
-
-```
-cp pr_agent/settings/.secrets_template.toml pr_agent/settings/.secrets.toml
-chmod 600 pr_agent/settings/.secrets.toml
-# Edit .secrets.toml file
-```
-
-4. Run the cli.py script:
-
-```
-python3 -m pr_agent.cli --pr_url <pr_url> review
-python3 -m pr_agent.cli --pr_url <pr_url> ask <your question>
-python3 -m pr_agent.cli --pr_url <pr_url> describe
-python3 -m pr_agent.cli --pr_url <pr_url> improve
-python3 -m pr_agent.cli --pr_url <pr_url> add_docs
-python3 -m pr_agent.cli --pr_url <pr_url> generate_labels
-python3 -m pr_agent.cli --issue_url <issue_url> similar_issue
-...
-```
-
-[Optional] Add the pr_agent folder to your PYTHONPATH
-```
-export PYTHONPATH=$PYTHONPATH:<PATH to pr_agent folder>
-```

docs/docs/installation/pr_agent_pro.md

@@ -1,81 +0,0 @@
-Qodo Merge Pro is a versatile application compatible with GitHub, GitLab, and BitBucket, hosted by QodoAI.
-See [here](https://qodo-merge-docs.qodo.ai/overview/pr_agent_pro/) for more details about the benefits of using Qodo Merge Pro.
-
-A complimentary two-week trial is provided to all new users. Following the trial period, user licenses (seats) are required for continued access.
-To purchase user licenses, please visit our [pricing page](https://www.qodo.ai/pricing/).
-Once subscribed, users can seamlessly deploy the application across any of their code repositories.
-
-## Install Qodo Merge Pro for GitHub
-
-### GitHub Cloud
-
-Qodo Merge Pro for GitHub cloud is available for installation through the [GitHub Marketplace](https://github.com/apps/qodo-merge-pro).
-
-![Qodo Merge Pro](https://codium.ai/images/pr_agent/pr_agent_pro_install.png){width=468}
-
-### GitHub Enterprise Server
-
-To use Qodo Merge Pro application on your private GitHub Enterprise Server, you will need to contact us for starting an [Enterprise](https://www.codium.ai/pricing/) trial.
-
-### GitHub Open Source Projects
-
-For open-source projects, Qodo Merge Pro is available for free usage. To install Qodo Merge Pro for your open-source repositories, use the following marketplace [link](https://github.com/apps/qodo-merge-pro-for-open-source).
-
-## Install Qodo Merge Pro for Bitbucket
-
-###  Bitbucket Cloud
-
-Qodo Merge Pro for Bitbucket Cloud is available for installation through the following [link](https://bitbucket.org/site/addons/authorize?addon_key=d6df813252c37258)
-
-![Qodo Merge Pro](https://qodo.ai/images/pr_agent/pr_agent_pro_bitbucket_install.png){width=468}
-
-### Bitbucket Server
-
-To use Qodo Merge Pro application on your private Bitbucket Server, you will need to contact us for starting an [Enterprise](https://www.codium.ai/pricing/) trial.
-
-
-## Install Qodo Merge Pro for GitLab (Teams & Enterprise)
-
-Since GitLab platform does not support apps, installing Qodo Merge Pro for GitLab is a bit more involved, and requires the following steps:
-
-#### Step 1
-
-Acquire a personal, project or group level access token. Enable the “api” scope in order to allow Qodo Merge to read pull requests, comment and respond to requests.
-
-<figure markdown="1">
-![Step 1](https://www.codium.ai/images/pr_agent/gitlab_pro_pat.png){width=750}
-</figure>
-
-Store the token in a safe place, you won’t be able to access it again after it was generated.
-
-#### Step 2
-
-Generate a shared secret and link it to the access token. Browse to [https://register.gitlab.pr-agent.codium.ai](https://register.gitlab.pr-agent.codium.ai).
-Fill in your generated GitLab token and your company or personal name in the appropriate fields and click "Submit".
-
-You should see "Success!" displayed above the Submit button, and a shared secret will be generated. Store it in a safe place, you won’t be able to access it again after it was generated.
-
-#### Step 3
-
-Install a webhook for your repository or groups, by clicking “webhooks” on the settings menu. Click the “Add new webhook” button.
-
-<figure markdown="1">
-![Step 3.1](https://www.codium.ai/images/pr_agent/gitlab_pro_add_webhook.png)
-</figure>
-
-In the webhook definition form, fill in the following fields:
-URL: https://pro.gitlab.pr-agent.codium.ai/webhook
-
-Secret token: Your QodoAI key
-Trigger: Check the ‘comments’ and ‘merge request events’ boxes.
-Enable SSL verification: Check the box.
-
-<figure markdown="1">
-![Step 3.2](https://www.codium.ai/images/pr_agent/gitlab_pro_webhooks.png){width=750}
-</figure>
-
-#### Step 4
-
-You’re all set!
-
-Open a new merge request or add a MR comment with one of Qodo Merge’s commands such as /review, /describe or /improve.

docs/docs/overview/data_privacy.md

@@ -1,16 +0,0 @@
-## Self-hosted Qodo Merge
-
-- If you self-host Qodo Merge with your OpenAI (or other LLM provider) API key, it is between you and the provider. We don't send your code data to Qodo Merge servers.
-
-## Qodo Merge Pro 💎
-
-- When using Qodo Merge Pro 💎, hosted by CodiumAI, we will not store any of your data, nor will we use it for training. You will also benefit from an OpenAI account with zero data retention.
-
-- For certain clients, CodiumAI-hosted Qodo Merge Pro will use CodiumAI’s proprietary models. If this is the case, you will be notified.
-
-- No passive collection of Code and Pull Requests’ data — Qodo Merge will be active only when you invoke it, and it will then extract and analyze only data relevant to the executed command and queried pull request.
-
-
-## Qodo Merge Chrome extension
-
-- The [Qodo Merge Chrome extension](https://chromewebstore.google.com/detail/pr-agent-chrome-extension/ephlnjeghhogofkifjloamocljapahnl) will not send your code to any external servers.

docs/docs/overview/index.md

@@ -1,93 +0,0 @@
-# Overview
-
-Qodo Merge is an open-source tool to help efficiently review and handle pull requests.
-
-- See the [Installation Guide](./installation/index.md) for instructions on installing and running the tool on different git platforms.
-
-- See the [Usage Guide](./usage-guide/index.md) for instructions on running the Qodo Merge commands via different interfaces, including _CLI_, _online usage_, or by _automatically triggering_ them when a new PR is opened.
-
-- See the [Tools Guide](./tools/index.md) for a detailed description of the different tools.
-
-
-## Qodo Merge Docs Smart Search
-
-To search the documentation site using natural language:
-
-1) Comment `/help "your question"` in either:
-
-   - A pull request where Qodo Merge is installed
-   - A [PR Chat](https://qodo-merge-docs.qodo.ai/chrome-extension/features/#pr-chat)
-
-2) Qodo Merge will respond with an [answer](https://github.com/Codium-ai/pr-agent/pull/1241#issuecomment-2365259334) that includes relevant documentation links.
-
-
-## Qodo Merge Features
-
-Qodo Merge offers extensive pull request functionalities across various git providers.
-
-|       |                                                                                                                       | GitHub | Gitlab | Bitbucket | Azure DevOps |
-|-------|-----------------------------------------------------------------------------------------------------------------------|:------:|:------:|:---------:|:------------:|
-| TOOLS | Review                                                                                                                |   ✅    |   ✅    |   ✅       |      ✅      |
-|       | ⮑ Incremental                                                                                                         |   ✅    |        |            |              |
-|       | Ask                                                                                                                   |   ✅    |   ✅    |   ✅        |      ✅      |
-|       | Describe                                                                                                              |   ✅    |   ✅    |   ✅        |      ✅      |
-|       | ⮑ [Inline file summary](https://qodo-merge-docs.qodo.ai/tools/describe/#inline-file-summary){:target="_blank"} 💎     |   ✅    |   ✅    |           |      ✅      |
-|       | Improve                                                                                                               |   ✅    |   ✅    |   ✅        |      ✅      |
-|       | ⮑ Extended                                                                                                            |   ✅    |   ✅    |   ✅        |      ✅      |
-|       | [Custom Prompt](./tools/custom_prompt.md){:target="_blank"} 💎                                                        |   ✅    |   ✅    |   ✅        |      ✅      |
-|       | Reflect and Review                                                                                                    |   ✅    |   ✅    |   ✅        |      ✅      |
-|       | Update CHANGELOG.md                                                                                                   |   ✅    |   ✅    |   ✅        |      ️       |
-|       | Find Similar Issue                                                                                                    |   ✅    |        |             |      ️       |
-|       | [Add PR Documentation](./tools/documentation.md){:target="_blank"} 💎                                                 |   ✅    |   ✅    |          |      ✅      |
-|       | [Generate Custom Labels](./tools/describe.md#handle-custom-labels-from-the-repos-labels-page-💎){:target="_blank"} 💎 |   ✅    |   ✅    |            |      ✅      |
-|       | [Analyze PR Components](./tools/analyze.md){:target="_blank"} 💎                                                      |   ✅    |   ✅    |       |      ✅      |
-|       |                                                                                                                       |        |        |            |      ️       |
-| USAGE | CLI                                                                                                                   |   ✅    |   ✅    |   ✅       |      ✅      |
-|       | App / webhook                                                                                                         |   ✅    |   ✅    |    ✅        |      ✅      |
-|       | Actions                                                                                                               |   ✅    |        |            |      ️       |
-|       |                                                                                                                       |        |        |            |
-| CORE  | PR compression                                                                                                        |   ✅    |   ✅    |   ✅       |   ✅        |
-|       | Repo language prioritization                                                                                          |   ✅    |   ✅    |   ✅       |   ✅        |
-|       | Adaptive and token-aware file patch fitting                                                                           |   ✅    |   ✅    |   ✅     |   ✅        |
-|       | Multiple models support                                                                                               |   ✅    |   ✅    |   ✅       |   ✅        |
-|       | Incremental PR review                                                                                                 |   ✅    |        |            |           |
-|       | [Static code analysis](./tools/analyze.md/){:target="_blank"} 💎                                                      |   ✅    |   ✅     |    ✅    |   ✅        |
-|       | [Multiple configuration options](./usage-guide/configuration_options.md){:target="_blank"} 💎                         |   ✅    |   ✅     |    ✅    |   ✅        |
-
-💎 marks a feature available only in [Qodo Merge Pro](https://www.codium.ai/pricing/){:target="_blank"}
-
-
-## Example Results
-<hr>
-
-#### [/describe](https://github.com/Codium-ai/pr-agent/pull/530)
-<figure markdown="1">
-![/describe](https://www.codium.ai/images/pr_agent/describe_new_short_main.png){width=512}
-</figure>
-<hr>
-
-#### [/review](https://github.com/Codium-ai/pr-agent/pull/732#issuecomment-1975099151)
-<figure markdown="1">
-![/review](https://www.codium.ai/images/pr_agent/review_new_short_main.png){width=512}
-</figure>
-<hr>
-
-#### [/improve](https://github.com/Codium-ai/pr-agent/pull/732#issuecomment-1975099159)
-<figure markdown="1">
-![/improve](https://www.codium.ai/images/pr_agent/improve_new_short_main.png){width=512}
-</figure>
-<hr>
-
-#### [/generate_labels](https://github.com/Codium-ai/pr-agent/pull/530)
-<figure markdown="1">
-![/generate_labels](https://www.codium.ai/images/pr_agent/geneare_custom_labels_main_short.png){width=300}
-</figure>
-<hr>
-
-## How it Works
-
-The following diagram illustrates Qodo Merge tools and their flow:
-
-![Qodo Merge Tools](https://codium.ai/images/pr_agent/diagram-v0.9.png)
-
-Check out the [PR Compression strategy](core-abilities/index.md) page for more details on how we convert a code diff to a manageable LLM prompt

docs/docs/overview/pr_agent_pro.md

@@ -1,51 +0,0 @@
-### Overview
-
-[Qodo Merge Pro](https://www.codium.ai/pricing/) is a hosted version of open-source [Qodo Merge (PR-Agent)](https://github.com/Codium-ai/pr-agent). A complimentary two-week trial is offered, followed by a monthly subscription fee.
-Qodo Merge Pro is designed for companies and teams that require additional features and capabilities. It provides the following benefits:
-
-1. **Fully managed** - We take care of everything for you - hosting, models, regular updates, and more. Installation is as simple as signing up and adding the Qodo Merge app to your GitHub\GitLab\BitBucket repo.
-
-2. **Improved privacy** - No data will be stored or used to train models. Qodo Merge Pro will employ zero data retention, and will use an OpenAI and Claude accounts with zero data retention.
-
-3. **Improved support** - Qodo Merge Pro users will receive priority support, and will be able to request new features and capabilities.
-
-4. **Supporting self-hosted git servers** - Qodo Merge Pro can be installed on GitHub Enterprise Server, GitLab, and BitBucket. For more information, see the [installation guide](https://qodo-merge-docs.qodo.ai/installation/pr_agent_pro/).
-
-5. **PR Chat** - Qodo Merge Pro allows you to engage in [private chat](https://qodo-merge-docs.qodo.ai/chrome-extension/features/#pr-chat) about your pull requests on private repositories.
-
-### Additional features
-
-Here are some of the additional features and capabilities that Qodo Merge Pro offers:
-
-| Feature                                                                                                              | Description                                                                                                                                                      |
-|----------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-| [**Model selection**](https://qodo-merge-docs.qodo.ai/usage-guide/PR_agent_pro_models/)          | Choose the model that best fits your needs, among top models like `GPT4` and `Claude-Sonnet-3.5`
-| [**Global and wiki configuration**](https://qodo-merge-docs.qodo.ai/usage-guide/configuration_options/)              | Control configurations for many repositories from a single location; <br>Edit configuration of a single repo without committing code                              |
-| [**Apply suggestions**](https://qodo-merge-docs.qodo.ai/tools/improve/#overview)                                     | Generate committable code from the relevant suggestions interactively by clicking on a checkbox                                                                   |
-| [**Suggestions impact**](https://qodo-merge-docs.qodo.ai/tools/improve/#assessing-impact)                         | Automatically mark suggestions that were implemented by the user (either directly in GitHub, or indirectly in the IDE) to enable tracking of the impact of the suggestions |
-| [**CI feedback**](https://qodo-merge-docs.qodo.ai/tools/ci_feedback/) | Automatically analyze failed CI checks on GitHub and provide actionable feedback in the PR conversation, helping to resolve issues quickly |
-| [**Advanced usage statistics**](https://www.codium.ai/contact/#/)                                                    | Qodo Merge Pro offers detailed statistics at user, repository, and company levels, including metrics about Qodo Merge usage, and also general statistics and insights |
-| [**Incorporating companies' best practices**](https://qodo-merge-docs.qodo.ai/tools/improve/#best-practices)         | Use the companies' best practices as reference to increase the effectiveness and the relevance of the code suggestions                                           |
-| [**Interactive triggering**](https://qodo-merge-docs.qodo.ai/tools/analyze/#example-usage)                           | Interactively apply different tools via the `analyze` command                                                                                                    |
-| [**Custom labels**](https://qodo-merge-docs.qodo.ai/tools/describe/#handle-custom-labels-from-the-repos-labels-page) | Define custom labels for Qodo Merge to assign to the PR                                                                                                            |
-
-### Additional tools
-
-Here are additional tools that are available only for Qodo Merge Pro users:
-
-| Feature | Description |
-|---------|-------------|
-| [**Custom Prompt Suggestions**](https://qodo-merge-docs.qodo.ai/tools/custom_prompt/) | Generate code suggestions based on custom prompts from the user |
-| [**Analyze PR components**](https://qodo-merge-docs.qodo.ai/tools/analyze/) | Identify the components that changed in the PR, and enable to interactively apply different tools to them |
-| [**Tests**](https://qodo-merge-docs.qodo.ai/tools/test/) | Generate tests for code components that changed in the PR |
-| [**PR documentation**](https://qodo-merge-docs.qodo.ai/tools/documentation/) | Generate docstring for code components that changed in the PR |
-| [**Improve Component**](https://qodo-merge-docs.qodo.ai/tools/improve_component/) | Generate code suggestions for code components that changed in the PR |
-| [**Similar code search**](https://qodo-merge-docs.qodo.ai/tools/similar_code/) | Search for similar code in the repository, organization, or entire GitHub |
-
-
-### Supported languages
-
-Qodo Merge Pro leverages the world's leading code models - Claude 3.5 Sonnet and GPT-4.
-As a result, its primary tools such as `describe`, `review`, and `improve`, as well as the PR-chat feature, support virtually all programming languages.
-
-For specialized commands that require static code analysis, Qodo Merge Pro offers support for specific languages. For more details about features that require static code analysis, please refer to the [documentation](https://qodo-merge-docs.qodo.ai/tools/analyze/#overview).

docs/docs/tools/analyze.md

@@ -1,19 +0,0 @@
-## Overview
-The `analyze` tool combines advanced static code analysis with LLM capabilities to provide a comprehensive analysis of the PR code changes.
-
-The tool scans the PR code changes, finds the code components (methods, functions, classes) that changed, and enables to interactively generate tests, docs, code suggestions and similar code search for each component.
-
-It can be invoked manually by commenting on any PR:
-```
-/analyze
-```
-
-## Example usage
-
-An example result:
-
-![Analyze 1](https://codium.ai/images/pr_agent/analyze_1.png){width=750}
-
-**Notes**
-
-- Language that are currently supported: Python, Java, C++, JavaScript, TypeScript, C#.

docs/docs/tools/ask.md

@@ -1,59 +0,0 @@
-## Overview
-
-The `ask` tool answers questions about the PR, based on the PR code changes. Make sure to be specific and clear in your questions.
-It can be invoked manually by commenting on any PR:
-```
-/ask "..."
-```
-
-## Example usage
-
-![Ask Comment](https://codium.ai/images/pr_agent/ask_comment.png){width=512}
-
-![Ask](https://codium.ai/images/pr_agent/ask.png){width=512}
-
-## Ask lines
-
-You can run `/ask` on specific lines of code in the PR from the PR's diff view. The tool will answer questions based on the code changes in the selected lines.
-- Click on the '+' sign next to the line number to select the line.
-- To select multiple lines, click on the '+' sign of the first line and then hold and drag to select the rest of the lines.
-- write `/ask "..."` in the comment box and press `Add single comment` button.
-
-![Ask Line](https://codium.ai/images/pr_agent/Ask_line.png){width=512}
-
-Note that the tool does not have "memory" of previous questions, and answers each question independently.
-
-## Ask on images
-
-You can also ask questions about images that appear in the comment, where the entire PR code will be used as context.
-<br>
-The basic syntax is:
-```
-/ask "..."
-
-[Image](https://real_link_to_image)
-```
-where `https://real_link_to_image` is the direct link to the image.
-
-Note that GitHub has a built-in mechanism of pasting images in comments. However, pasted image does not provide a direct link.
-To get a direct link to an image, we recommend using the following scheme:
-
-1) First, post a comment that contains **only** the image:
-
-![Ask image1](https://codium.ai/images/pr_agent/ask_images1.png){width=512}
-
-2) Quote reply to that comment:
-
-![Ask image2](https://codium.ai/images/pr_agent/ask_images2.png){width=512}
-
-3) In the screen opened, type the question below the image:
-
-![Ask image3](https://codium.ai/images/pr_agent/ask_images3.png){width=512}
-![Ask image4](https://codium.ai/images/pr_agent/ask_images4.png){width=512}
-
-4) Post the comment, and receive the answer:
-
-![Ask image5](https://codium.ai/images/pr_agent/ask_images5.png){width=512}
-
-
-See a full video tutorial [here](https://codium.ai/images/pr_agent/ask_image_video.mov)

docs/docs/tools/ci_feedback.md

@@ -1,39 +0,0 @@
-## Overview
-
-The CI feedback tool (`/checks)` automatically triggers when a PR has a failed check.
-The tool analyzes the failed checks and provides several feedbacks:
-
-- Failed stage
-- Failed test name
-- Failure summary
-- Relevant error logs
-
-## Example usage
-
-![Failed Check 1](https://www.codium.ai/images/pr_agent/failed_check1.png){width=768}
-
-→
-![Failed Check 2](https://www.codium.ai/images/pr_agent/failed_check2.png){width=768}
-
-___
-
-In addition to being automatically triggered, the tool can also be invoked manually by commenting on a PR:
-```
-/checks "https://github.com/{repo_name}/actions/runs/{run_number}/job/{job_number}"
-```
-where `{repo_name}` is the name of the repository, `{run_number}` is the run number of the failed check, and `{job_number}` is the job number of the failed check.
-
-## Disabling the tool from running automatically
-
-If you wish to disable the tool from running automatically, you can do so by adding the following configuration to the configuration file:
-```
-[checks]
-enable_auto_checks_feedback = false
-```
-
-## Configuration options
-- `enable_auto_checks_feedback` - if set to true, the tool will automatically provide feedback when a check is failed. Default is true.
-- `excluded_checks_list` - a list of checks to exclude from the feedback, for example: ["check1", "check2"]. Default is an empty list.
-- `persistent_comment` - if set to true, the tool will overwrite a previous checks comment with the new feedback. Default is true.
-- `enable_help_text=true` - if set to true, the tool will provide a help message when a user comments "/checks" on a PR. Default is true.
-- `final_update_message` - if `persistent_comment` is true and updating a previous checks message, the tool will also create a new message: "Persistent checks updated to latest commit". Default is true.

docs/docs/tools/custom_labels.md

@@ -1,60 +0,0 @@
-## Overview
-The `generate_labels` tool scans the PR code changes, and given a list of labels and their descriptions, it automatically suggests labels that match the PR code changes.
-
-It can be invoked manually by commenting on any PR:
-```
-/generate_labels
-```
-
-## Example usage
-
-If we wish to add detect changes to SQL queries in a given PR, we can add the following custom label along with its description:
-
-![Custom labels list](https://codium.ai/images/pr_agent/custom_labels_list.png){width=768}
-
-When running the `generate_labels` tool on a PR that includes changes in SQL queries, it will automatically suggest the custom label:
-
-![Custom labels published](https://codium.ai/images/pr_agent/custom_label_published.png){width=768}
-
-Note that in addition to the dedicated tool `generate_labels`, the custom labels will also be used by the `describe` tool.
-
-### How to enable custom labels
-There are 3 ways to enable custom labels:
-
-#### 1. CLI (local configuration file)
-When working from CLI, you need to apply the [configuration changes](#configuration-options) to the [custom_labels file](https://github.com/Codium-ai/pr-agent/blob/main/pr_agent/settings/custom_labels.toml):
-
-#### 2. Repo configuration file
-To enable custom labels, you need to apply the [configuration changes](#configuration-options) to the local `.pr_agent.toml` file in your repository.
-
-#### 3. Handle custom labels from the Repo's labels page 💎
-> This feature is available only in Qodo Merge Pro
-
-* GitHub : `https://github.com/{owner}/{repo}/labels`, or click on the "Labels" tab in the issues or PRs page.
-* GitLab : `https://gitlab.com/{owner}/{repo}/-/labels`, or click on "Manage" -> "Labels" on the left menu.
-
-b. Add/edit the custom labels. It should be formatted as follows:
-* Label name: The name of the custom label.
-* Description: Start the description of with prefix `pr_agent:`, for example: `pr_agent: Description of when AI should suggest this label`.<br>
-The description should be comprehensive and detailed, indicating when to add the desired label.
-
-![Add native custom labels](https://codium.ai/images/pr_agent/add_native_custom_labels.png){width=880}
-
-c. Now the custom labels will be included in the `generate_labels` tool.
-
-> This feature is supported in GitHub and GitLab.
-
-## Configuration options
- - Change `enable_custom_labels` to True: This will turn off the default labels and enable the custom labels provided in the custom_labels.toml file.
- - Add the custom labels. It should be formatted as follows:
-
-```
-[config]
-enable_custom_labels=true
-
-[custom_labels."Custom Label Name"]
-description = "Description of when AI should suggest this label"
-
-[custom_labels."Custom Label 2"]
-description = "Description of when AI should suggest this label 2"
-```

docs/docs/tools/custom_prompt.md

@@ -1,58 +0,0 @@
-## Overview
-The `custom_prompt` tool scans the PR code changes, and automatically generates suggestions for improving the PR code.
-It shares similarities with the `improve` tool, but with one main difference: the `custom_prompt` tool will **only propose suggestions that follow specific guidelines defined by the prompt** in: `pr_custom_prompt.prompt` configuration.
-
-The tool can be triggered [automatically](../usage-guide/automations_and_usage.md#github-app-automatic-tools-when-a-new-pr-is-opened) every time a new PR is opened, or can be invoked manually by commenting on a PR.
-
-When commenting, use the following template:
-
-```
-/custom_prompt --pr_custom_prompt.prompt="
-The code suggestions should focus only on the following:
-- ...
-- ...
-
-"
-```
-
-With a [configuration file](../usage-guide/automations_and_usage.md#github-app), use the following template:
-
-```
-[pr_custom_prompt]
-prompt="""\
-The suggestions should focus only on the following:
--...
--...
-
-"""
-```
-
-Remember - with this tool, you are the prompter. Be specific, clear, and concise in the instructions. Specify relevant aspects that you want the model to focus on. \
-You might benefit from several trial-and-error iterations, until you get the correct prompt for your use case.
-
-## Example usage
-
-Here is an example of a possible prompt, defined in the configuration file:
-```
-[pr_custom_prompt]
-prompt="""\
-The code suggestions should focus only on the following:
-- look for edge cases when implementing a new function
-- make sure every variable has a meaningful name
-- make sure the code is efficient
-"""
-```
-
-(The instructions above are just an example. We want to emphasize that the prompt should be specific and clear, and be tailored to the needs of your project)
-
-Results obtained with the prompt above:
-
-![Custom prompt results](https://codium.ai/images/pr_agent/custom_suggestions_result.png){width=768}
-
-## Configuration options
-
-`prompt`: the prompt for the tool. It should be a multi-line string.
-
-`num_code_suggestions`: number of code suggestions provided by the 'custom_prompt' tool. Default is 4.
-
-`enable_help_text`: if set to true, the tool will display a help text in the comment. Default is true.

docs/docs/tools/describe.md

@@ -1,224 +0,0 @@
-## Overview
-The `describe` tool scans the PR code changes, and generates a description for the PR - title, type, summary, walkthrough and labels.
-
-The tool can be triggered automatically every time a new PR is [opened](../usage-guide/automations_and_usage.md#github-app-automatic-tools-when-a-new-pr-is-opened), or it can be invoked manually by commenting on any PR:
-```
-/describe
-```
-
-## Example usage
-
-### Manual triggering
-
-Invoke the tool manually by commenting `/describe` on any PR:
-
-![Describe comment](https://codium.ai/images/pr_agent/describe_comment.png){width=512}
-
-After ~30 seconds, the tool will generate a description for the PR:
-
-![Describe New](https://codium.ai/images/pr_agent/describe_new.png){width=512}
-
-If you want to edit [configurations](#configuration-options), add the relevant ones to the command:
-```
-/describe --pr_description.some_config1=... --pr_description.some_config2=...
-```
-
-### Automatic triggering
-
-To run the `describe` automatically when a PR is opened, define in a [configuration file](https://qodo-merge-docs.qodo.ai/usage-guide/configuration_options/#wiki-configuration-file):
-```
-[github_app]
-pr_commands = [
-    "/describe",
-    ...
-]
-
-[pr_description]
-publish_labels = true
-...
-```
-
-- The `pr_commands` lists commands that will be executed automatically when a PR is opened.
-- The `[pr_description]` section contains the configurations for the `describe` tool you want to edit (if any).
-
-
-## Configuration options
-
-!!! example "Possible configurations"
-
-<table>
-  <tr>
-    <td><b>publish_labels</b></td>
-    <td>If set to true, the tool will publish labels to the PR. Default is false.</td>
-  </tr>
-  <tr>
-    <td><b>publish_description_as_comment</b></td>
-    <td>If set to true, the tool will publish the description as a comment to the PR. If false, it will overwrite the original description. Default is false.</td>
-  </tr>
-  <tr>
-    <td><b>publish_description_as_comment_persistent</b></td>
-    <td>If set to true and `publish_description_as_comment` is true, the tool will publish the description as a persistent comment to the PR. Default is true.</td>
-  </tr>
-  <tr>
-    <td><b>add_original_user_description</b></td>
-    <td>If set to true, the tool will add the original user description to the generated description. Default is true.</td>
-  </tr>
-  <tr>
-    <td><b>generate_ai_title</b></td>
-    <td>If set to true, the tool will also generate an AI title for the PR. Default is false.</td>
-  </tr>
-  <tr>
-    <td><b>extra_instructions</b></td>
-    <td>Optional extra instructions to the tool. For example: "focus on the changes in the file X. Ignore change in ..."</td>
-  </tr>
-  <tr>
-    <td><b>enable_pr_type</b></td>
-    <td>If set to false, it will not show the `PR type` as a text value in the description content. Default is true.</td>
-  </tr>
-  <tr>
-    <td><b>final_update_message</b></td>
-    <td>If set to true, it will add a comment message [`PR Description updated to latest commit...`](https://github.com/Codium-ai/pr-agent/pull/499#issuecomment-1837412176) after finishing calling `/describe`. Default is false.</td>
-  </tr>
-  <tr>
-    <td><b>enable_semantic_files_types</b></td>
-    <td>If set to true, "Changes walkthrough" section will be generated. Default is true.</td>
-  </tr>
-  <tr>
-    <td><b>collapsible_file_list</b></td>
-    <td>If set to true, the file list in the "Changes walkthrough" section will be collapsible. If set to "adaptive", the file list will be collapsible only if there are more than 8 files. Default is "adaptive".</td>
-  </tr>
-  <tr>
-    <td><b>enable_large_pr_handling</b></td>
-    <td>Pro feature. If set to true, in case of a large PR the tool will make several calls to the AI and combine them to be able to cover more files. Default is true.</td>
-  </tr>
-  <tr>
-    <td><b>enable_help_text</b></td>
-    <td>If set to true, the tool will display a help text in the comment. Default is false.</td>
-  </tr>
-</table>
-
-
-## Inline file summary 💎
-
-This feature enables you to copy the `changes walkthrough` table to the "Files changed" tab, so you can quickly understand the changes in each file while reviewing the code changes (diff view).
-
-To copy the `changes walkthrough` table to the "Files changed" tab, you can click on the checkbox that appears PR Description status message below the main PR Description:
-
-![Add table checkbox](https://codium.ai/images/pr_agent/add_table_checkbox.png){width=512}
-
-If you prefer to have the file summaries appear in the "Files changed" tab on every PR, change the `pr_description.inline_file_summary` parameter in the configuration file, possible values are:
-
-- `'table'`: File changes walkthrough table will be displayed on the top of the "Files changed" tab, in addition to the "Conversation" tab.
-
-![Diffview table](https://codium.ai/images/pr_agent/diffview-table.png){width=512}
-
-- `true`: A collapsible file comment with changes title and a changes summary for each file in the PR.
-
-![Diffview changes](https://codium.ai/images/pr_agent/diffview_changes.png){width=512}
-
-- `false` (`default`): File changes walkthrough will be added only to the "Conversation" tab.
-
-**Note**: that this feature is currently available only for GitHub.
-
-
-## Markers template
-
-To enable markers, set `pr_description.use_description_markers=true`.
-Markers enable to easily integrate user's content and auto-generated content, with a template-like mechanism.
-
-For example, if the PR original description was:
-```
-User content...
-
-## PR Type:
-pr_agent:type
-
-## PR Description:
-pr_agent:summary
-
-## PR Walkthrough:
-pr_agent:walkthrough
-```
-The marker `pr_agent:type` will be replaced with the PR type, `pr_agent:summary` will be replaced with the PR summary, and `pr_agent:walkthrough` will be replaced with the PR walkthrough.
-
-![Describe markers before](https://codium.ai/images/pr_agent/describe_markers_before.png){width=512}
-
-&rarr;
-
-![Describe markers after](https://codium.ai/images/pr_agent/describe_markers_after.png){width=512}
-
-
-**Configuration params**:
-
-- `use_description_markers`: if set to true, the tool will use markers template. It replaces every marker of the form `pr_agent:marker_name` with the relevant content. Default is false.
-- `include_generated_by_header`: if set to true, the tool will add a dedicated header: 'Generated by PR Agent at ...' to any automatic content. Default is true.
-
-## Custom labels
-The default labels of the describe tool are quite generic, since they are meant to be used in any repo: [`Bug fix`, `Tests`, `Enhancement`, `Documentation`, `Other`].
-
-You can define custom labels that are relevant for your repo and use cases.
-Custom labels can be defined in a [configuration file](https://qodo-merge-docs.qodo.ai/tools/custom_labels/#configuration-options), or directly in the repo's [labels page](#handle-custom-labels-from-the-repos-labels-page).
-
-Make sure to provide proper title, and a detailed and well-phrased description for each label, so the tool will know when to suggest it.
-Each label description should be a **conditional statement**, that indicates if to add the label to the PR or not, according to the PR content.
-
-### Handle custom labels from a configuration file
-Example for a custom labels configuration setup in a configuration file:
-```
-[config]
-enable_custom_labels=true
-
-
-[custom_labels."sql_changes"]
-description = "Use when a PR contains changes to SQL queries"
-
-[custom_labels."test"]
-description = "use when a PR primarily contains new tests"
-
-...
-```
-
-### Handle custom labels from the Repo's labels page 💎
-
-You can also control the custom labels that will be suggested by the `describe` tool from the repo's labels page:
-
-* GitHub : go to `https://github.com/{owner}/{repo}/labels` (or click on the "Labels" tab in the issues or PRs page)
-* GitLab : go to `https://gitlab.com/{owner}/{repo}/-/labels` (or click on "Manage" -> "Labels" on the left menu)
-
-Now add/edit the custom labels. they should be formatted as follows:
-
-* Label name: The name of the custom label.
-* Description: Start the description of with prefix `pr_agent:`, for example: `pr_agent: Description of when AI should suggest this label`.<br>
-
-Examples for custom labels:
-
-  - `Main topic:performance` -  pr_agent:The main topic of this PR is performance
-  - `New endpoint` -  pr_agent:A new endpoint was added in this PR
-  - `SQL query` -  pr_agent:A new SQL query was added in this PR
-  - `Dockerfile changes` - pr_agent:The PR contains changes in the Dockerfile
-  - ...
-
-The description should be comprehensive and detailed, indicating when to add the desired label. For example:
-![Add native custom labels](https://codium.ai/images/pr_agent/add_native_custom_labels.png){width=768}
-
-
-## Usage Tips
-
-!!! tip "Automation"
-    - When you first install Qodo Merge app, the [default mode](../usage-guide/automations_and_usage.md#github-app) for the describe tool is:
-    ```
-    pr_commands = ["/describe", ...]
-    ```
-    meaning the `describe` tool will run automatically on every PR, with the default configurations.
-
-
-   - Markers are an alternative way to control the generated description, to give maximal control to the user. If you set:
-   ```
-   pr_commands = ["/describe --pr_description.use_description_markers=true", ...]
-   ```
-   the tool will replace every marker of the form `pr_agent:marker_name` in the PR description with the relevant content, where `marker_name` is one of the following:
-         * `type`: the PR type.
-         * `summary`: the PR summary.
-         * `walkthrough`: the PR walkthrough.
-
-   - Note that when markers are enabled, if the original PR description does not contain any markers, the tool will not alter the description at all.

docs/docs/tools/documentation.md

@@ -1,33 +0,0 @@
-## Overview
-The `add_docs` tool scans the PR code changes, and automatically suggests documentation for any code components that changed in the PR (functions, classes, etc.).
-
-It can be invoked manually by commenting on any PR:
-```
-/add_docs
-```
-
-## Example usage
-
-Invoke the tool manually by commenting `/add_docs` on any PR:
-
-![Docs command](https://codium.ai/images/pr_agent/docs_command.png){width=768}
-
-The tool will generate documentation for all the components that changed in the PR:
-
-![Docs component](https://codium.ai/images/pr_agent/docs_components.png){width=768}
-
-![Docs single component](https://codium.ai/images/pr_agent/docs_single_component.png){width=768}
-
-You can state a name of a specific component in the PR to get documentation only for that component:
-```
-/add_docs component_name
-```
-
-## Configuration options
- - `docs_style`: The exact style of the documentation (for python docstring). you can choose between: `google`, `numpy`, `sphinx`, `restructuredtext`, `plain`. Default is `sphinx`.
- - `extra_instructions`: Optional extra instructions to the tool. For example: "focus on the changes in the file X. Ignore change in ...".
-
-**Notes**
-
-- Language that are currently fully supported: Python, Java, C++, JavaScript, TypeScript, C#.
-- This tool can also be triggered interactively by using the [`analyze`](./analyze.md) tool.

docs/docs/tools/help.md

@@ -1,17 +0,0 @@
-## Overview
-The `help` tool provides a list of all the available tools and their descriptions.
-For Qodo Merge Pro users, it also enables to trigger each tool by checking the relevant box.
-
-It can be invoked manually by commenting on any PR:
-```
-/help
-```
-
-## Example usage
-An example [result](https://github.com/Codium-ai/pr-agent/pull/546#issuecomment-1868524805):
-
-![Help 1](https://codium.ai/images/pr_agent/help1.png){width=750}
-
-→
-
-![Analyze 2](https://codium.ai/images/pr_agent/help2.png){width=750}

docs/docs/tools/improve.md

@@ -1,378 +0,0 @@
-## Overview
-The `improve` tool scans the PR code changes, and automatically generates [meaningful](https://github.com/Codium-ai/pr-agent/blob/main/pr_agent/settings/pr_code_suggestions_prompts.toml#L41) suggestions for improving the PR code.
-The tool can be triggered automatically every time a new PR is [opened](../usage-guide/automations_and_usage.md#github-app-automatic-tools-when-a-new-pr-is-opened), or it can be invoked manually by commenting on any PR:
-```toml
-/improve
-```
-
-![code_suggestions_as_comment_closed.png](https://codium.ai/images/pr_agent/code_suggestions_as_comment_closed.png){width=512}
-
-![code_suggestions_as_comment_open.png](https://codium.ai/images/pr_agent/code_suggestions_as_comment_open.png){width=512}
-
-Note that the `Apply this suggestion` checkbox, which interactively converts a suggestion into a commitable code comment, is available only for Qodo Merge Pro 💎 users.
-
-
-## Example usage
-
-### Manual triggering
-
-Invoke the tool manually by commenting `/improve` on any PR. The code suggestions by default are presented as a single comment:
-
-To edit [configurations](#configuration-options) related to the improve tool, use the following template:
-```toml
-/improve --pr_code_suggestions.some_config1=... --pr_code_suggestions.some_config2=...
-```
-
-For example, you can choose to present all the suggestions as commitable code comments, by running the following command:
-```toml
-/improve --pr_code_suggestions.commitable_code_suggestions=true
-```
-
-![improve](https://codium.ai/images/pr_agent/improve.png){width=512}
-
-
-As can be seen, a single table comment has a significantly smaller PR footprint. We recommend this mode for most cases.
-Also note that collapsible are not supported in _Bitbucket_. Hence, the suggestions can only be presented in Bitbucket as code comments.
-
-### Automatic triggering
-
-To run the `improve` automatically when a PR is opened, define in a [configuration file](https://qodo-merge-docs.qodo.ai/usage-guide/configuration_options/#wiki-configuration-file):
-```toml
-[github_app]
-pr_commands = [
-    "/improve",
-    ...
-]
-
-[pr_code_suggestions]
-num_code_suggestions_per_chunk = ...
-...
-```
-
-- The `pr_commands` lists commands that will be executed automatically when a PR is opened.
-- The `[pr_code_suggestions]` section contains the configurations for the `improve` tool you want to edit (if any)
-
-### Assessing Impact 💎
-
-Note that Qodo Merge pro tracks two types of implementations:
-
-- Direct implementation - when the user directly applies the suggestion by clicking the `Apply` checkbox.
-- Indirect implementation - when the user implements the suggestion in their IDE environment. In this case, Qodo Merge will utilize, after each commit, a dedicated logic to identify if a suggestion was implemented, and will mark it as implemented.
-
-![code_suggestions_asses_impact](https://codium.ai/images/pr_agent/code_suggestions_asses_impact.png){width=512}
-
-In post-process, Qodo Merge counts the number of suggestions that were implemented, and provides general statistics and insights about the suggestions' impact on the PR process.
-
-![code_suggestions_asses_impact_stats_1](https://codium.ai/images/pr_agent/code_suggestions_asses_impact_stats_1.png){width=512}
-
-![code_suggestions_asses_impact_stats_2](https://codium.ai/images/pr_agent/code_suggestions_asses_impact_stats_2.png){width=512}
-
-## Suggestion tracking 💎
-`Platforms supported: GitHub, GitLab`
-
-Qodo Merge employs an novel detection system to automatically [identify](https://qodo-merge-docs.qodo.ai/core-abilities/impact_evaluation/) AI code suggestions that PR authors have accepted and implemented.
-
-Accepted suggestions are also automatically documented in a dedicated wiki page called `.pr_agent_accepted_suggestions`, allowing users to track historical changes, assess the tool's effectiveness, and learn from previously implemented recommendations in the repository.
-An example [result](https://github.com/Codium-ai/pr-agent/wiki/.pr_agent_accepted_suggestions):
-
-[![pr_agent_accepted_suggestions1.png](https://qodo.ai/images/pr_agent/pr_agent_accepted_suggestions1.png){width=768}](https://github.com/Codium-ai/pr-agent/wiki/.pr_agent_accepted_suggestions)
-
-This dedicated wiki page will also serve as a foundation for future AI model improvements, allowing it to learn from historically implemented suggestions and generate more targeted, contextually relevant recommendations.
-
-This feature is controlled by a boolean configuration parameter: `pr_code_suggestions.wiki_page_accepted_suggestions` (default is true).
-
-!!! note "Wiki must be enabled"
-    While the aggregation process is automatic, GitHub repositories require a one-time manual wiki setup.
-
-    To initialize the wiki: navigate to `Wiki`, select `Create the first page`, then click `Save page`.
-
-    ![pr_agent_accepted_suggestions_create_first_page.png](https://qodo.ai/images/pr_agent/pr_agent_accepted_suggestions_create_first_page.png){width=768}
-
-    Once a wiki repo is created, the tool will automatically use this wiki for tracking suggestions.
-
-!!! note "Why a wiki page?"
-    Your code belongs to you, and we respect your privacy. Hence, we won't store any code suggestions in an external database.
-
-    Instead, we leverage a dedicated private page, within your repository wiki, to track suggestions. This approach offers convenient secure suggestion tracking while avoiding pull requests or any noise to the main repository.
-
-## `Extra instructions` and `best practices`
-
-The `improve` tool can be further customized by providing additional instructions and best practices to the AI model.
-
-### Extra instructions
-
->`Platforms supported: GitHub, GitLab, Bitbucket, Azure DevOps`
-
-You can use the `extra_instructions` configuration option to give the AI model additional instructions for the `improve` tool.
-Be specific, clear, and concise in the instructions. With extra instructions, you are the prompter.
-
-Examples for possible instructions:
-```toml
-[pr_code_suggestions]
-extra_instructions="""\
-(1) Answer in japanese
-(2) Don't suggest to add try-except block
-(3) Ignore changes in toml files
-...
-"""
-```
-Use triple quotes to write multi-line instructions. Use bullet points or numbers to make the instructions more readable.
-
-### Best practices 💎
-
->`Platforms supported: GitHub, GitLab, Bitbucket`
-
-Another option to give additional guidance to the AI model is by creating a dedicated [**wiki page**](https://github.com/Codium-ai/pr-agent/wiki) called `best_practices.md`.
-This page can contain a list of best practices, coding standards, and guidelines that are specific to your repo/organization.
-
-The AI model will use this wiki page as a reference, and in case the PR code violates any of the guidelines, it will create additional suggestions, with a dedicated label: `Organization
-best practice`.
-
-Example for a python `best_practices.md` content:
-```markdown
-## Project best practices
-- Make sure that I/O operations are encapsulated in a try-except block
-- Use the `logging` module for logging instead of `print` statements
-- Use `is` and `is not` to compare with `None`
-- Use `if __name__ == '__main__':` to run the code only when the script is executed
-- Use `with` statement to open files
-...
-```
-
-Tips for writing an effective `best_practices.md` file:
-
-- Write clearly and concisely
-- Include brief code examples when helpful
-- Focus on project-specific guidelines, that will result in relevant suggestions you actually want to get
-- Keep the file relatively short, under 800 lines, since:
-    - AI models may not process effectively very long documents
-    - Long files tend to contain generic guidelines already known to AI
-
-#### Local and global best practices
-By default, Qodo Merge will look for a local `best_practices.md` wiki file in the root of the relevant local repo.
-
-If you want to enable also a global `best_practices.md` wiki file, set first in the global configuration file:
-
-```toml
-[best_practices]
-enable_global_best_practices = true
-```
-
-Then, create a `best_practices.md` wiki file in the root of [global](https://qodo-merge-docs.qodo.ai/usage-guide/configuration_options/#global-configuration-file) configuration repository,  `pr-agent-settings`.
-
-#### Best practices for multiple languages
-For a git organization working with multiple programming languages, you can maintain a centralized global `best_practices.md` file containing language-specific guidelines. 
-When reviewing pull requests, Qodo Merge automatically identifies the programming language and applies the relevant best practices from this file.
-
-To do this, structure your `best_practices.md` file using the following format:
-
-```
-# [Python]
-...
-# [Java]
-...
-# [JavaScript]
-...
-```
-
-#### Dedicated label for best practices suggestions
-Best practice suggestions are labeled as `Organization best practice` by default. 
-To customize this label, modify it in your configuration file:
-
-```toml
-[best_practices]
-organization_name = "..."
-```
-
-And the label will be: `{organization_name} best practice`.
-
-
-#### Example results
-
-![best_practice](https://codium.ai/images/pr_agent/org_best_practice.png){width=512}
-
-
-### How to combine `extra instructions` and `best practices`
-
-The `extra instructions` configuration is more related to the `improve` tool prompt. It can be used, for example, to avoid specific suggestions ("Don't suggest to add try-except block", "Ignore changes in toml files", ...) or to emphasize specific aspects or formats ("Answer in Japanese", "Give only short suggestions", ...)
-
-In contrast, the `best_practices.md` file is a general guideline for the way code should be written in the repo.
-
-Using a combination of both can help the AI model to provide relevant and tailored suggestions.
-
-
-## Usage Tips
-
-### Implementing the proposed code suggestions
-Each generated suggestion consists of three key elements:
-
-1. A single-line summary of the proposed change
-2. An expandable section containing a comprehensive description of the suggestion
-3. A diff snippet showing the recommended code modification (before and after)
-
-We advise users to apply critical analysis and judgment when implementing the proposed suggestions.
-In addition to mistakes (which may happen, but are rare), sometimes the presented code modification may serve more as an _illustrative example_ than a direct applicable solution.
-In such cases, we recommend prioritizing the suggestion's detailed description, using the diff snippet primarily as a supporting reference.
-
-### Dual publishing mode
-Our recommended approach for presenting code suggestions is through a [table](https://qodo-merge-docs.qodo.ai/tools/improve/#overview) (`--pr_code_suggestions.commitable_code_suggestions=false`).
-This method significantly reduces the PR footprint and allows for quick and easy digestion of multiple suggestions.
-
-We also offer a complementary **dual publishing mode**. When enabled, suggestions exceeding a certain score threshold are not only displayed in the table, but also presented as commitable PR comments.
-This mode helps highlight suggestions deemed more critical.
-
-To activate dual publishing mode, use the following setting:
-
-```toml
-[pr_code_suggestions]
-dual_publishing_score_threshold = x
-```
-
-Where x represents the minimum score threshold (>=) for suggestions to be presented as commitable PR comments in addition to the table. Default is -1 (disabled).
-
-### Self-review
-If you set in a configuration file:
-```toml
-[pr_code_suggestions]
-demand_code_suggestions_self_review = true
-```
-
-The `improve` tool will add a checkbox below the suggestions, prompting user to acknowledge that they have reviewed the suggestions.
-You can set the content of the checkbox text via:
-```toml
-[pr_code_suggestions]
-code_suggestions_self_review_text = "... (your text here) ..."
-```
-
-![self_review_1](https://codium.ai/images/pr_agent/self_review_1.png){width=512}
-
-
-!!! tip "Tip - Reducing visual footprint after self-review 💎"
-
-    The configuration parameter `pr_code_suggestions.fold_suggestions_on_self_review` (default is True)
-    can be used to automatically fold the suggestions after the user clicks the self-review checkbox.
-
-    This reduces the visual footprint of the suggestions, and also indicates to the PR reviewer that the suggestions have been reviewed by the PR author, and don't require further attention.
-
-
-
-!!! tip "Tip - Demanding self-review from the PR author 💎"
-
-    By setting:
-    ```toml
-    [pr_code_suggestions]
-    approve_pr_on_self_review = true
-    ```
-    the tool can automatically add an approval when the PR author clicks the self-review checkbox.
-
-
-    - If you set the number of required reviewers for a PR to 2, this effectively means that the PR author must click the self-review checkbox before the PR can be merged (in addition to a human reviewer).
-
-    ![self_review_2](https://codium.ai/images/pr_agent/self_review_2.png){width=512}
-
-    - If you keep the number of required reviewers for a PR to 1 and enable this configuration, this effectively means that the PR author can approve the PR by actively clicking the self-review checkbox.
-
-        To prevent unauthorized approvals, this configuration defaults to false, and cannot be altered through online comments; enabling requires a direct update to the configuration file and a commit to the repository. This ensures that utilizing the feature demands a deliberate documented decision by the repository owner.
-
-
-### How many code suggestions are generated?
-Qodo Merge uses a dynamic strategy to generate code suggestions based on the size of the pull request (PR). Here's how it works:
-
-1) Chunking large PRs:
-
-- Qodo Merge divides large PRs into 'chunks'.
-- Each chunk contains up to `pr_code_suggestions.max_context_tokens` tokens (default: 14,000).
-
-
-2) Generating suggestions:
-
-- For each chunk, Qodo Merge generates up to `pr_code_suggestions.num_code_suggestions_per_chunk` suggestions (default: 4).
-
-
-This approach has two main benefits:
-
-- Scalability: The number of suggestions scales with the PR size, rather than being fixed.
-- Quality: By processing smaller chunks, the AI can maintain higher quality suggestions, as larger contexts tend to decrease AI performance.
-
-Note: Chunking is primarily relevant for large PRs. For most PRs (up to 500 lines of code), Qodo Merge will be able to process the entire code in a single call.
-
-
-## Configuration options
-
-??? example "General options"
-
-    <table>
-      <tr>
-        <td><b>extra_instructions</b></td>
-        <td>Optional extra instructions to the tool. For example: "focus on the changes in the file X. Ignore change in ...".</td>
-      </tr>
-      <tr>
-        <td><b>commitable_code_suggestions</b></td>
-        <td>If set to true, the tool will display the suggestions as commitable code comments. Default is false.</td>
-      </tr>
-      <tr>
-        <td><b>dual_publishing_score_threshold</b></td>
-        <td>Minimum score threshold for suggestions to be presented as commitable PR comments in addition to the table. Default is -1 (disabled).</td>
-      </tr>
-      <tr>
-        <td><b>focus_only_on_problems</b></td>
-        <td>If set to true, suggestions will focus primarily on identifying and fixing code problems, and less on style considerations like best practices, maintainability, or readability. Default is true.</td> 
-      </tr>
-      <tr>
-        <td><b>persistent_comment</b></td>
-        <td>If set to true, the improve comment will be persistent, meaning that every new improve request will edit the previous one. Default is false.</td>
-      </tr>
-      <tr>
-        <td><b>suggestions_score_threshold</b></td>
-        <td> Any suggestion with importance score less than this threshold will be removed. Default is 0. Highly recommend not to set this value above 7-8, since above it may clip relevant suggestions that can be useful. </td>
-      </tr>
-      <tr>
-        <td><b>apply_suggestions_checkbox</b></td>
-        <td> Enable the checkbox to create a committable suggestion. Default is true.</td>
-      </tr>
-      <tr>
-        <td><b>enable_help_text</b></td>
-        <td>If set to true, the tool will display a help text in the comment. Default is true.</td>
-      </tr>
-      <tr>
-        <td><b>enable_chat_text</b></td>
-        <td>If set to true, the tool will display a reference to the PR chat in the comment. Default is true.</td>
-      </tr>
-      <tr>
-        <td><b>wiki_page_accepted_suggestions</b></td>
-        <td>If set to true, the tool will automatically track accepted suggestions in a dedicated wiki page called `.pr_agent_accepted_suggestions`. Default is true.</td>
-      </tr>
-      <tr>
-        <td><b>allow_thumbs_up_down</b></td>
-        <td>If set to true, all code suggestions will have thumbs up and thumbs down buttons, to encourage users to provide feedback on the suggestions. Default is false.</td>
-      </tr>
-    </table>
-
-??? example "Params for number of suggestions and AI calls"
-
-    <table>
-      <tr>
-        <td><b>auto_extended_mode</b></td>
-        <td>Enable chunking the PR code and running the tool on each chunk. Default is true.</td>
-      </tr>
-      <tr>
-        <td><b>num_code_suggestions_per_chunk</b></td>
-        <td>Number of code suggestions provided by the 'improve' tool, per chunk. Default is 4.</td>
-      </tr>
-      <tr>
-        <td><b>max_number_of_calls</b></td>
-        <td>Maximum number of chunks. Default is 3.</td>
-      </tr>
-    </table>
-
-## A note on code suggestions quality
-
-- AI models for code are getting better and better (Sonnet-3.5 and GPT-4), but they are not flawless. Not all the suggestions will be perfect, and a user should not accept all of them automatically. Critical reading and judgment are required.
-- While mistakes of the AI are rare but can happen, a real benefit from the suggestions of the `improve` (and [`review`](https://qodo-merge-docs.qodo.ai/tools/review/)) tool is to catch, with high probability, **mistakes or bugs done by the PR author**, when they happen. So, it's a good practice to spend the needed ~30-60 seconds to review the suggestions, even if not all of them are always relevant.
-- The hierarchical structure of the suggestions is designed to help the user to _quickly_ understand them, and to decide which ones are relevant and which are not:
-
-    - Only if the `Category` header is relevant, the user should move to the summarized suggestion description
-    - Only if the summarized suggestion description is relevant, the user should click on the collapsible, to read the full suggestion description with a code preview example.
-
-- In addition, we recommend to use the [`extra_instructions`](https://qodo-merge-docs.qodo.ai/tools/improve/#extra-instructions-and-best-practices) field to guide the model to suggestions that are more relevant to the specific needs of the project.
-- The interactive [PR chat](https://qodo-merge-docs.qodo.ai/chrome-extension/) also provides an easy way to get more tailored suggestions and feedback from the AI model.

docs/docs/tools/improve_component.md

@@ -1,29 +0,0 @@
-## Overview
-The `improve_component` tool generates code suggestions for a specific code component that changed in the PR.
-it can be invoked manually by commenting on any PR:
-```
-/improve_component component_name
-```
-
-To get a list of the components that changed in the PR and choose the relevant component interactively, use the [`analyze`](./analyze.md) tool.
-
-
-## Example usage
-
-Invoke the tool manually by commenting `/improve_component` on any PR:
-
-![improve_component1](https://codium.ai/images/pr_agent/improve_component1.png){width=768}
-
-The tool will generate code suggestions for the selected component (if no component is stated, it will generate code suggestions for the largest component):
-
-![improve_component2](https://codium.ai/images/pr_agent/improve_component2.png){width=768}
-
-**Notes**
-- Language that are currently supported by the tool: Python, Java, C++, JavaScript, TypeScript, C#.
-- This tool can also be triggered interactively by using the [`analyze`](./analyze.md) tool.
-
-## Configuration options
-- `num_code_suggestions`: number of code suggestions to provide. Default is 4
-- `extra_instructions`: Optional extra instructions to the tool. For example: "focus on ...".
-- `file`: in case there are several components with the same name, you can specify the relevant file.
-- `class_name`: in case there are several methods with the same name in the same file, you can specify the relevant class name.

docs/docs/tools/index.md

@@ -1,22 +0,0 @@
-# Tools
-
-Here is a list of Qodo Merge tools, each with a dedicated page that explains how to use it:
-
-| Tool                                                                                     | Description                                                                                                                                 |
-|------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------|
-| **[PR Description (`/describe`](./describe.md))**                                        | Automatically generating PR description - title, type, summary, code walkthrough and labels                                                 |
-| **[PR Review (`/review`](./review.md))**                                                 | Adjustable feedback about the PR, possible issues, security concerns, review effort and more                                                |
-| **[Code Suggestions (`/improve`](./improve.md))**                                        | Code suggestions for improving the PR                                                                                                       |
-| **[Question Answering (`/ask ...`](./ask.md))**                                          | Answering free-text questions about the PR, or on specific code lines                                                                       |
-| **[Update Changelog (`/update_changelog`](./update_changelog.md))**                      | Automatically updating the CHANGELOG.md file with the PR changes                                                                            |
-| **[Find Similar Issue (`/similar_issue`](./similar_issues.md))**                         | Automatically retrieves and presents similar issues                                                                                         |
-| **[Help (`/help`](./help.md))**                                                          | Provides a list of all the available tools. Also enables to trigger them interactively (💎)                                                 |
-| **💎 [Add Documentation (`/add_docs`](./documentation.md))**                             | Generates documentation to methods/functions/classes that changed in the PR                                                                 |
-| **💎 [Generate Custom Labels (`/generate_labels`](./custom_labels.md))**                 | Generates custom labels for the PR, based on specific guidelines defined by the user                                                        |
-| **💎 [Analyze (`/analyze`](./analyze.md))**                                              | Identify code components that changed in the PR, and enables to interactively generate tests, docs, and code suggestions for each component |
-| **💎 [Custom Prompt (`/custom_prompt`](./custom_prompt.md))**                            | Automatically generates custom suggestions for improving the PR code, based on specific guidelines defined by the user                      |
-| **💎 [Generate Tests (`/test component_name`](./test.md))**                              | Automatically generates unit tests for a selected component, based on the PR code changes                                                   |
-| **💎 [Improve Component (`/improve_component component_name`](./improve_component.md))** | Generates code suggestions for a specific code component that changed in the PR                                                             |
-| **💎 [CI Feedback (`/checks ci_job`](./ci_feedback.md))**                                | Automatically generates feedback and analysis for a failed CI job                                                                           |
-
-Note that the tools marked with 💎 are available only for Qodo Merge Pro users.

docs/docs/tools/review.md

@@ -1,260 +0,0 @@
-## Overview
-The `review` tool scans the PR code changes, and generates a list of feedbacks about the PR, aiming to aid the reviewing process.
-<br>
-The tool can be triggered automatically every time a new PR is [opened](../usage-guide/automations_and_usage.md#github-app-automatic-tools-when-a-new-pr-is-opened), or can be invoked manually by commenting on any PR:
-```
-/review
-```
-
-Note that the main purpose of the `review` tool is to provide the **PR reviewer** with useful feedbacks and insights. The PR author, in contrast, may prefer to save time and focus on the output of the [improve](./improve.md) tool, which provides actionable code suggestions.
-
-(Read more about the different personas in the PR process and how Qodo Merge aims to assist them in our [blog](https://www.codium.ai/blog/understanding-the-challenges-and-pain-points-of-the-pull-request-cycle/))
-
-
-## Example usage
-
-### Manual triggering
-
-Invoke the tool manually by commenting `/review` on any PR:
-
-![review comment](https://codium.ai/images/pr_agent/review_comment.png){width=512}
-
-After ~30 seconds, the tool will generate a review for the PR:
-
-![review](https://codium.ai/images/pr_agent/review3.png){width=512}
-
-If you want to edit [configurations](#configuration-options), add the relevant ones to the command:
-```
-/review --pr_reviewer.some_config1=... --pr_reviewer.some_config2=...
-```
-
-### Automatic triggering
-
-To run the `review` automatically when a PR is opened, define in a [configuration file](https://qodo-merge-docs.qodo.ai/usage-guide/configuration_options/#wiki-configuration-file):
-```
-[github_app]
-pr_commands = [
-    "/review",
-    ...
-]
-
-[pr_reviewer]
-extra_instructions = "..."
-...
-```
-
-- The `pr_commands` lists commands that will be executed automatically when a PR is opened.
-- The `[pr_reviewer]` section contains the configurations for the `review` tool you want to edit (if any).
-
-[//]: # ()
-[//]: # (### Incremental Mode)
-
-[//]: # (Incremental review only considers changes since the last Qodo Merge review. This can be useful when working on the PR in an iterative manner, and you want to focus on the changes since the last review instead of reviewing the entire PR again.)
-
-[//]: # (For invoking the incremental mode, the following command can be used:)
-
-[//]: # (```)
-
-[//]: # (/review -i)
-
-[//]: # (```)
-
-[//]: # (Note that the incremental mode is only available for GitHub.)
-
-[//]: # ()
-[//]: # (![incremental review]&#40;https://codium.ai/images/pr_agent/incremental_review_2.png&#41;{width=512})
-
-[//]: # (### PR Reflection)
-
-[//]: # ()
-[//]: # (By invoking:)
-
-[//]: # (```)
-
-[//]: # (/reflect_and_review)
-
-[//]: # (```)
-
-[//]: # (The tool will first ask the author questions about the PR, and will guide the review based on their answers.)
-
-[//]: # ()
-[//]: # (![reflection questions]&#40;https://codium.ai/images/pr_agent/reflection_questions.png&#41;{width=512})
-
-[//]: # ()
-[//]: # (![reflection answers]&#40;https://codium.ai/images/pr_agent/reflection_answers.png&#41;{width=512})
-
-[//]: # ()
-[//]: # (![reflection insights]&#40;https://codium.ai/images/pr_agent/reflection_insights.png&#41;{width=512})
-
-
-
-## Configuration options
-
-!!! example "General options"
-
-<table>
-  <tr>
-    <td><b>num_code_suggestions</b></td>
-    <td>Number of code suggestions provided by the 'review' tool. Default is 0, meaning no code suggestions will be provided by the `review` tool. Note that this is a legacy feature, that will be removed in future releases. Use the `improve` tool instead for code suggestions</td>
-  </tr>
-  <tr>
-    <td><b>inline_code_comments</b></td>
-    <td>If set to true, the tool will publish the code suggestions as comments on the code diff. Default is false. Note that you need to set `num_code_suggestions`>0 to get code suggestions </td>
-  </tr>
-  <tr>
-    <td><b>persistent_comment</b></td>
-    <td>If set to true, the review comment will be persistent, meaning that every new review request will edit the previous one. Default is true.</td>
-  </tr>
-  <tr>
-    <td><b>extra_instructions</b></td>
-    <td>Optional extra instructions to the tool. For example: "focus on the changes in the file X. Ignore change in ...".</td>
-  </tr>
-  <tr>
-    <td><b>enable_help_text</b></td>
-    <td>If set to true, the tool will display a help text in the comment. Default is true.</td>
-  </tr>
-</table>
-
-!!! example "Enable\\disable specific sub-sections"
-
-<table>
-  <tr>
-    <td><b>require_score_review</b></td>
-    <td>If set to true, the tool will add a section that scores the PR. Default is false.</td>
-  </tr>
-  <tr>
-    <td><b>require_tests_review</b></td>
-    <td>If set to true, the tool will add a section that checks if the PR contains tests. Default is true.</td>
-  </tr>
-  <tr>
-    <td><b>require_estimate_effort_to_review</b></td>
-    <td>If set to true, the tool will add a section that estimates the effort needed to review the PR. Default is true.</td>
-  </tr>
-  <tr>
-    <td><b>require_can_be_split_review</b></td>
-    <td>If set to true, the tool will add a section that checks if the PR contains several themes, and can be split into smaller PRs. Default is false.</td>
-  </tr>
-  <tr>
-    <td><b>require_security_review</b></td>
-    <td>If set to true, the tool will add a section that checks if the PR contains a possible security or vulnerability issue. Default is true.</td>
-  </tr>
-  <tr>
-    <td><b>require_ticket_analysis_review</b></td>
-    <td>If set to true, and the PR contains a GitHub or Jira ticket link, the tool will add a section that checks if the PR in fact fulfilled the ticket requirements. Default is true.</td>
-  </tr>
-</table>
-
-!!! example "Adding PR labels"
-
-You can enable\disable the `review` tool to add specific labels to the PR:
-
-<table>
-  <tr>
-    <td><b>enable_review_labels_security</b></td>
-    <td>If set to true, the tool will publish a 'possible security issue' label if it detects a security issue. Default is true.</td>
-  </tr>
-  <tr>
-    <td><b>enable_review_labels_effort</b></td>
-    <td>If set to true, the tool will publish a 'Review effort [1-5]: x' label. Default is true.</td>
-  </tr>
-</table>
-
-!!! example "Auto-approval"
-
-If enabled, the `review` tool can approve a PR when a specific comment, `/review auto_approve`, is invoked.
-
-<table>
-  <tr>
-    <td><b>enable_auto_approval</b></td>
-    <td>If set to true, the tool will approve the PR when invoked with the 'auto_approve' command. Default is false. This flag can be changed only from a configuration file.</td>
-  </tr>
-  <tr>
-    <td><b>maximal_review_effort</b></td>
-    <td>Maximal effort level for auto-approval. If the PR's estimated review effort is above this threshold, the auto-approval will not run. Default is 5.</td>
-  </tr>
-</table>
-
-## Usage Tips
-
-!!! tip "General guidelines"
-
-    The `review` tool provides a collection of configurable feedbacks about a PR.
-    It is recommended to review the [Configuration options](#configuration-options) section, and choose the relevant options for your use case.
-
-    Some of the features that are disabled by default are quite useful, and should be considered for enabling. For example:
-    `require_score_review`, and more.
-
-    On the other hand, if you find one of the enabled features to be irrelevant for your use case, disable it. No default configuration can fit all use cases.
-
-!!! tip "Automation"
-    When you first install Qodo Merge app, the [default mode](../usage-guide/automations_and_usage.md#github-app-automatic-tools-when-a-new-pr-is-opened) for the `review` tool is:
-    ```
-    pr_commands = ["/review --pr_reviewer.num_code_suggestions=0", ...]
-    ```
-    Meaning the `review` tool will run automatically on every PR, without providing code suggestions.
-    Edit this field to enable/disable the tool, or to change the configurations used.
-
-!!! tip "Possible labels from the review tool"
-
-    The `review` tool can auto-generate two specific types of labels for a PR:
-
-    - a `possible security issue` label that detects if a possible [security issue](https://github.com/Codium-ai/pr-agent/blob/tr/user_description/pr_agent/settings/pr_reviewer_prompts.toml#L136) exists in the PR code (`enable_review_labels_security` flag)
-    - a `Review effort [1-5]: x` label, where x is the estimated effort to review the PR (`enable_review_labels_effort` flag)
-
-    Both modes are useful, and we recommended to enable them.
-
-!!! tip "Extra instructions"
-
-    Extra instructions are important.
-    The `review` tool can be configured with extra instructions, which can be used to guide the model to a feedback tailored to the needs of your project.
-
-    Be specific, clear, and concise in the instructions. With extra instructions, you are the prompter. Specify the relevant sub-tool, and the relevant aspects of the PR that you want to emphasize.
-
-    Examples of extra instructions:
-    ```
-    [pr_reviewer]
-    extra_instructions="""\
-    In the code feedback section, emphasize the following:
-    - Does the code logic cover relevant edge cases?
-    - Is the code logic clear and easy to understand?
-    - Is the code logic efficient?
-    ...
-    """
-    ```
-    Use triple quotes to write multi-line instructions. Use bullet points to make the instructions more readable.
-
-
-!!! tip "Auto-approval"
-
-    Qodo Merge can approve a PR when a specific comment is invoked.
-
-    To ensure safety, the auto-approval feature is disabled by default. To enable auto-approval, you need to actively set in a pre-defined configuration file the following:
-    ```
-    [pr_reviewer]
-    enable_auto_approval = true
-    ```
-    (this specific flag cannot be set with a command line argument, only in the configuration file, committed to the repository)
-
-
-    After enabling, by commenting on a PR:
-    ```
-    /review auto_approve
-    ```
-    Qodo Merge will automatically approve the PR, and add a comment with the approval.
-
-
-    You can also enable auto-approval only if the PR meets certain requirements, such as that the `estimated_review_effort` label is equal or below a certain threshold, by adjusting the flag:
-    ```
-    [pr_reviewer]
-    maximal_review_effort = 5
-    ```
-
-[//]: # (!!! tip  "Code suggestions")
-
-[//]: # ()
-[//]: # (    If you set `num_code_suggestions`>0 , the `review` tool will also provide code suggestions.)
-
-[//]: # (    )
-[//]: # (    Notice If you are interested **only** in the code suggestions, it is recommended to use the [`improve`]&#40;./improve.md&#41; feature instead, since it is a dedicated only to code suggestions, and usually gives better results.)
-
-[//]: # (    Use the `review` tool if you want to get more comprehensive feedback, which includes code suggestions as well.)

docs/docs/tools/similar_code.md

@@ -1,64 +0,0 @@
-## Overview
-The similar code tool retrieves the most similar code components from inside the organization's codebase, or from open-source code.
-
-For example:
-
-`Global Search` for a method called `chat_completion`:
-
-![similar code global](https://codium.ai/images/pr_agent/similar_code_global2.png){width=768}
-
-
-Qodo Merge will examine the code component and will extract the most relevant keywords to search for similar code:
-
-- `extracted keywords`: the keywords that were extracted from the code by Qodo Merge. the link will open a search page with the extracted keywords, to allow the user to modify the search if needed.
-- `search context`: the context in which the search will be performed, organization's codebase or open-source code (Global).
-- `similar code`: the most similar code components found. the link will open the code component in the relevant file.
-- `relevant repositories`: the open-source repositories in which that are relevant to the searched code component and it's keywords.
-
-Search result link example:
-
-![code search result single](https://codium.ai/images/pr_agent/code_search_result_single.png){width=768}
-
-
-`Organization Search`:
-
-![similar code org](https://codium.ai/images/pr_agent/similar_code_org.png){width=768}
-
-
-## How to use
-### Manually
-To invoke the `similar code` tool manually, comment on the PR:
-```
-/find_similar_component COMPONENT_NAME
-```
-Where `COMPONENT_NAME` should be the name of a code component in the PR (class, method, function).
-
-If there is a name ambiguity, there are two configurations that will help the tool to find the correct component:
-
-- `--pr_find_similar_component.file`: in case there are several components with the same name, you can specify the relevant file.
-- `--pr_find_similar_component.class_name`: in case there are several methods with the same name in the same file, you can specify the relevant class name.
-
-example:
-```
-/find_similar_component COMPONENT_NAME --pr_find_similar_component.file=FILE_NAME
-```
-
-### Automatically (via Analyze table)
-It can be invoked automatically from the analyze table, can be accessed by:
-```
-/analyze
-```
-Choose the components you want to find similar code for, and click on the `similar` checkbox.
-
-![analyze similar](https://codium.ai/images/pr_agent/analyze_similar.png){width=768}
-
-You can search for similar code either within the organization's codebase or globally, which includes open-source repositories. Each result will include the relevant code components along with their associated license details.
-
-![similar code global](https://codium.ai/images/pr_agent/similar_code_global.png){width=768}
-
-
-## Configuration options
-
-- `search_from_org`: if set to true, the tool will search for similar code in the organization's codebase. Default is false.
-- `number_of_keywords`: number of keywords to use for the search. Default is 5.
-- `number_of_results`: the maximum number of results to present. Default is 5.

docs/docs/tools/similar_issues.md

@@ -1,43 +0,0 @@
-## Overview
-The similar issue tool retrieves the most similar issues to the current issue.
-It can be invoked manually by commenting on any PR:
-```
-/similar_issue
-```
-
-
-## Example usage
-
-![similar_issue_original_issue](https://codium.ai/images/pr_agent/similar_issue_original_issue.png){width=768}
-
-![similar_issue_comment](https://codium.ai/images/pr_agent/similar_issue_comment.png){width=768}
-
-![similar_issue](https://codium.ai/images/pr_agent/similar_issue.png){width=768}
-
-Note that to perform retrieval, the `similar_issue` tool indexes all the repo previous issues (once).
-
-
-**Select VectorDBs** by changing `pr_similar_issue` parameter in `configuration.toml` file
-
-2 VectorDBs are available to switch in
-1. LanceDB
-2. Pinecone
-
-To enable usage of the '**similar issue**' tool for Pinecone, you need to set the following keys in `.secrets.toml` (or in the relevant environment variables):
-
-```
-[pinecone]
-api_key = "..."
-environment = "..."
-```
-These parameters can be obtained by registering to [Pinecone](https://app.pinecone.io/?sessionType=signup/).
-
-
-## How to use
-- To invoke the 'similar issue' tool from **CLI**, run:
-`python3 cli.py --issue_url=... similar_issue`
-
-- To invoke the 'similar' issue tool via online usage, [comment](https://github.com/Codium-ai/pr-agent/issues/178#issuecomment-1716934893) on a PR:
-`/similar_issue`
-
-- You can also enable the 'similar issue' tool to run automatically when a new issue is opened, by adding it to the [pr_commands list in the github_app section](https://github.com/Codium-ai/pr-agent/blob/main/pr_agent/settings/configuration.toml#L66)

docs/docs/tools/test.md

@@ -1,32 +0,0 @@
-## Overview
-By combining LLM abilities with static code analysis, the `test` tool  generate tests for a selected component, based on the PR code changes.
-It can be invoked manually by commenting on any PR:
-```
-/test component_name
-```
-where 'component_name' is the name of a specific component in the PR.
-To get a list of the components that changed in the PR and choose the relevant component interactively, use the [`analyze`](./analyze.md) tool.
-
-## Example usage
-
-Invoke the tool manually by commenting `/test` on any PR:
-The tool will generate tests for the selected component (if no component is stated, it will generate tests for largest component):
-
-![test1](https://codium.ai/images/pr_agent/test1.png){width=768}
-
-
-(Example taken from [here](https://github.com/Codium-ai/pr-agent/pull/598#issuecomment-1913679429)):
-
-**Notes**
-- Language that are currently supported by the tool: Python, Java, C++, JavaScript, TypeScript, C#.
-- This tool can also be triggered interactively by using the [`analyze`](./analyze.md) tool.
-
-
-## Configuration options
-- `num_tests`: number of tests to generate. Default is 3.
-- `testing_framework`: the testing framework to use. If not set, for Python it will use `pytest`, for Java it will use `JUnit`, for C++ it will use `Catch2`, and for JavaScript and TypeScript it will use `jest`.
-- `avoid_mocks`: if set to true, the tool will try to avoid using mocks in the generated tests. Note that even if this option is set to true, the tool might still use mocks if it cannot generate a test without them. Default is true.
-- `extra_instructions`: Optional extra instructions to the tool. For example: "use the following mock injection scheme: ...".
-- `file`: in case there are several components with the same name, you can specify the relevant file.
-- `class_name`: in case there are several methods with the same name in the same file, you can specify the relevant class name.
-- `enable_help_text`: if set to true, the tool will add a help text to the PR comment. Default is true.

docs/docs/tools/update_changelog.md

@@ -1,19 +0,0 @@
-## Overview
-The `update_changelog` tool automatically updates the CHANGELOG.md file with the PR changes.
-It can be invoked manually by commenting on any PR:
-```
-/update_changelog
-```
-
-## Example usage
-
-![update_changelog_comment](https://codium.ai/images/pr_agent/update_changelog_comment.png){width=768}
-
-![update_changelog](https://codium.ai/images/pr_agent/update_changelog.png){width=768}
-
-## Configuration options
-
-Under the section `pr_update_changelog`, the [configuration file](https://github.com/Codium-ai/pr-agent/blob/main/pr_agent/settings/configuration.toml#L50) contains options to customize the 'update changelog' tool:
-
-- `push_changelog_changes`: whether to push the changes to CHANGELOG.md, or just print them. Default is false (print only).
-- `extra_instructions`: Optional extra instructions to the tool. For example: "focus on the changes in the file X. Ignore change in ...

docs/docs/usage-guide/EXAMPLE_BEST_PRACTICE.md

@@ -1,189 +0,0 @@
-## Recommend Python Best Practices
-This document outlines a series of recommended best practices for Python development. These guidelines aim to improve code quality, maintainability, and readability.
-
-###  Imports
-
-Use  `import`  statements for packages and modules only, not for individual types, classes, or functions.
-
-#### Definition
-
-Reusability mechanism for sharing code from one module to another.
-
-####  Decision
-
--   Use  `import x`  for importing packages and modules.
--   Use  `from x import y`  where  `x`  is the package prefix and  `y`  is the module name with no prefix.
--   Use  `from x import y as z`  in any of the following circumstances:
-    -   Two modules named  `y`  are to be imported.
-    -   `y`  conflicts with a top-level name defined in the current module.
-    -   `y`  conflicts with a common parameter name that is part of the public API (e.g.,  `features`).
-    -   `y`  is an inconveniently long name, or too generic in the context of your code
--   Use  `import y as z`  only when  `z`  is a standard abbreviation (e.g.,  `import numpy as np`).
-
-For example the module  `sound.effects.echo`  may be imported as follows:
-
-```
-from sound.effects import echo
-...
-echo.EchoFilter(input, output, delay=0.7, atten=4)
-
-```
-
-Do not use relative names in imports. Even if the module is in the same package, use the full package name. This helps prevent unintentionally importing a package twice.
-
-##### Exemptions
-
-Exemptions from this rule:
-
--   Symbols from the following modules are used to support static analysis and type checking:
-    -   [`typing`  module](https://google.github.io/styleguide/pyguide.html#typing-imports)
-    -   [`collections.abc`  module](https://google.github.io/styleguide/pyguide.html#typing-imports)
-    -   [`typing_extensions`  module](https://github.com/python/typing_extensions/blob/main/README.md)
--   Redirects from the  [six.moves module](https://six.readthedocs.io/#module-six.moves).
-
-###  Packages
-
-Import each module using the full pathname location of the module.
-
-#### Decision
-
-All new code should import each module by its full package name.
-
-Imports should be as follows:
-
-```
-Yes:
-  # Reference absl.flags in code with the complete name (verbose).
-  import absl.flags
-  from doctor.who import jodie
-
-  _FOO = absl.flags.DEFINE_string(...)
-
-```
-
-```
-Yes:
-  # Reference flags in code with just the module name (common).
-  from absl import flags
-  from doctor.who import jodie
-
-  _FOO = flags.DEFINE_string(...)
-
-```
-
-_(assume this file lives in  `doctor/who/`  where  `jodie.py`  also exists)_
-
-```
-No:
-  # Unclear what module the author wanted and what will be imported.  The actual
-  # import behavior depends on external factors controlling sys.path.
-  # Which possible jodie module did the author intend to import?
-  import jodie
-
-```
-
-The directory the main binary is located in should not be assumed to be in  `sys.path`  despite that happening in some environments. This being the case, code should assume that  `import jodie`  refers to a third-party or top-level package named  `jodie`, not a local  `jodie.py`.
-
-### Default Iterators and Operators
-Use default iterators and operators for types that support them, like lists, dictionaries, and files.
-
-#### Definition
-
-Container types, like dictionaries and lists, define default iterators and membership test operators (“in” and “not in”).
-
-#### Decision
-
-Use default iterators and operators for types that support them, like lists, dictionaries, and files. The built-in types define iterator methods, too. Prefer these methods to methods that return lists, except that you should not mutate a container while iterating over it.
-
-```
-Yes:  for key in adict: ...
-      if obj in alist: ...
-      for line in afile: ...
-      for k, v in adict.items(): ...
-```
-
-```
-No:   for key in adict.keys(): ...
-      for line in afile.readlines(): ...
-```
-
-### Lambda Functions
-
-Okay for one-liners. Prefer generator expressions over  `map()`  or  `filter()`  with a  `lambda`.
-
-#### Decision
-
-Lambdas are allowed. If the code inside the lambda function spans multiple lines or is longer than 60-80 chars, it might be better to define it as a regular  [nested function](https://google.github.io/styleguide/pyguide.html#lexical-scoping).
-
-For common operations like multiplication, use the functions from the  `operator`  module instead of lambda functions. For example, prefer  `operator.mul`  to  `lambda x, y: x * y`.
-
-### Default Argument Values
-
-Okay in most cases.
-
-#### Definition
-
-You can specify values for variables at the end of a function’s parameter list, e.g.,  `def foo(a, b=0):`. If  `foo`  is called with only one argument,  `b`  is set to 0. If it is called with two arguments,  `b`  has the value of the second argument.
-
-####  Decision
-
-Okay to use with the following caveat:
-
-Do not use mutable objects as default values in the function or method definition.
-
-```
-Yes: def foo(a, b=None):
-         if b is None:
-             b = []
-Yes: def foo(a, b: Sequence | None = None):
-         if b is None:
-             b = []
-Yes: def foo(a, b: Sequence = ()):  # Empty tuple OK since tuples are immutable.
-         ...
-```
-
-```
-from absl import flags
-_FOO = flags.DEFINE_string(...)
-
-No:  def foo(a, b=[]):
-         ...
-No:  def foo(a, b=time.time()):  # Is `b` supposed to represent when this module was loaded?
-         ...
-No:  def foo(a, b=_FOO.value):  # sys.argv has not yet been parsed...
-         ...
-No:  def foo(a, b: Mapping = {}):  # Could still get passed to unchecked code.
-         ...
-```
-
-### True/False Evaluations
-
-
-Use the “implicit” false if possible, e.g.,  `if foo:`  rather than  `if foo != []:`
-
-### Lexical Scoping
-
-Okay to use.
-
-An example of the use of this feature is:
-
-```
-def get_adder(summand1: float) -> Callable[[float], float]:
-    """Returns a function that adds numbers to a given number."""
-    def adder(summand2: float) -> float:
-        return summand1 + summand2
-
-    return adder
-```
-#### Decision
-
-Okay to use.
-
-
-### Threading
-
-Do not rely on the atomicity of built-in types.
-
-While Python’s built-in data types such as dictionaries appear to have atomic operations, there are corner cases where they aren’t atomic (e.g. if  `__hash__`  or  `__eq__`  are implemented as Python methods) and their atomicity should not be relied upon. Neither should you rely on atomic variable assignment (since this in turn depends on dictionaries).
-
-Use the  `queue`  module’s  `Queue`  data type as the preferred way to communicate data between threads. Otherwise, use the  `threading`  module and its locking primitives. Prefer condition variables and  `threading.Condition`  instead of using lower-level locks.

docs/docs/usage-guide/PR_agent_pro_models.md

@@ -1,18 +0,0 @@
-## Qodo Merge Pro Models
-
-The default models used by Qodo Merge Pro are a combination of Claude-3.5-sonnet and  OpenAI's GPT-4 models.
-
-Users can configure Qodo Merge Pro to use solely a specific model by editing the [configuration](https://qodo-merge-docs.qodo.ai/usage-guide/configuration_options/) file.
-
-For example, to restrict Qodo Merge Pro to using only `Claude-3.5-sonnet`, add this setting:
-
-```
-[config]
-model="claude-3-5-sonnet"
-```
-
-Or to restrict Qodo Merge Pro to using only `GPT-4o`, add this setting:
-```
-[config]
-model="gpt-4o"
-```

docs/docs/usage-guide/additional_configurations.md

@@ -1,172 +0,0 @@
-## Show possible configurations
-The possible configurations of Qodo Merge are stored in [here](https://github.com/Codium-ai/pr-agent/blob/main/pr_agent/settings/configuration.toml).
-In the [tools](https://qodo-merge-docs.qodo.ai/tools/) page you can find explanations on how to use these configurations for each tool.
-
-To print all the available configurations as a comment on your PR, you can use the following command:
-```
-/config
-```
-
-![possible_config1](https://codium.ai/images/pr_agent/possible_config1.png){width=512}
-
-
-To view the **actual** configurations used for a specific tool, after all the user settings are applied, you can add for each tool a `--config.output_relevant_configurations=true` suffix.
-For example:
-```
-/improve --config.output_relevant_configurations=true
-```
-Will output an additional field showing the actual configurations used for the `improve` tool.
-
-![possible_config2](https://codium.ai/images/pr_agent/possible_config2.png){width=512}
-
-
-## Ignoring files from analysis
-
-In some cases, you may want to exclude specific files or directories from the analysis performed by Qodo Merge. This can be useful, for example, when you have files that are generated automatically or files that shouldn't be reviewed, like vendor code.
-
-You can ignore files or folders using the following methods:
- - `IGNORE.GLOB`
- - `IGNORE.REGEX`
-
-which you can edit to ignore files or folders based on glob or regex patterns.
-
-### Example usage
-
-Let's look at an example where we want to ignore all files with `.py` extension from the analysis.
-
-To ignore Python files in a PR with online usage, comment on a PR:
-`/review --ignore.glob="['*.py']"`
-
-
-To ignore Python files in all PRs using `glob` pattern, set in a configuration file:
-```
-[ignore]
-glob = ['*.py']
-```
-
-And to ignore Python files in all PRs using `regex` pattern, set in a configuration file:
-```
-[regex]
-regex = ['.*\.py$']
-```
-
-## Extra instructions
-
-All Qodo Merge tools have a parameter called `extra_instructions`, that enables to add free-text extra instructions. Example usage:
-```
-/update_changelog --pr_update_changelog.extra_instructions="Make sure to update also the version ..."
-```
-
-## Working with large PRs
-
-The default mode of CodiumAI is to have a single call per tool, using GPT-4, which has a token limit of 8000 tokens.
-This mode provides a very good speed-quality-cost tradeoff, and can handle most PRs successfully.
-When the PR is above the token limit, it employs a [PR Compression strategy](../core-abilities/index.md).
-
-However, for very large PRs, or in case you want to emphasize quality over speed and cost, there are two possible solutions:
-1) [Use a model](https://qodo-merge-docs.qodo.ai/usage-guide/changing_a_model/) with larger context, like GPT-32K, or claude-100K. This solution will be applicable for all the tools.
-2) For the `/improve` tool, there is an ['extended' mode](https://qodo-merge-docs.qodo.ai/tools/improve/) (`/improve --extended`),
-which divides the PR into chunks, and processes each chunk separately. With this mode, regardless of the model, no compression will be done (but for large PRs, multiple model calls may occur)
-
-
-
-## Patch Extra Lines
-
-By default, around any change in your PR, git patch provides three lines of context above and below the change.
-```
-@@ -12,5 +12,5 @@ def func1():
- code line that already existed in the file...
- code line that already existed in the file...
- code line that already existed in the file....
--code line that was removed in the PR
-+new code line added in the PR
- code line that already existed in the file...
- code line that already existed in the file...
- code line that already existed in the file...
-```
-
-Qodo Merge will try to increase the number of lines of context, via the parameter:
-```
-[config]
-patch_extra_lines_before=3
-patch_extra_lines_after=1
-```
-
-Increasing this number provides more context to the model, but will also increase the token budget, and may overwhelm the model with too much information, unrelated to the actual PR code changes.
-
-If the PR is too large (see [PR Compression strategy](https://github.com/Codium-ai/pr-agent/blob/main/PR_COMPRESSION.md)), Qodo Merge may automatically set this number to 0, and will use the original git patch.
-
-
-## Editing the prompts
-
-The prompts for the various Qodo Merge tools are defined in the `pr_agent/settings` folder.
-In practice, the prompts are loaded and stored as a standard setting object.
-Hence, editing them is similar to editing any other configuration value - just place the relevant key in `.pr_agent.toml`file, and override the default value.
-
-For example, if you want to edit the prompts of the [describe](https://github.com/Codium-ai/pr-agent/blob/main/pr_agent/settings/pr_description_prompts.toml) tool, you can add the following to your `.pr_agent.toml` file:
-```
-[pr_description_prompt]
-system="""
-...
-"""
-user="""
-...
-"""
-```
-Note that the new prompt will need to generate an output compatible with the relevant [post-process function](https://github.com/Codium-ai/pr-agent/blob/main/pr_agent/tools/pr_description.py#L137).
-
-## Integrating with Logging Observability Platforms
-
-Various logging observability tools can be used out-of-the box when using the default LiteLLM AI Handler. Simply configure the LiteLLM callback settings in `configuration.toml` and set environment variables according to the LiteLLM [documentation](https://docs.litellm.ai/docs/).
-
-For example, to use [LangSmith](https://www.langchain.com/langsmith) you can add the following to your `configuration.toml` file:
-```
-[litellm]
-enable_callbacks = true
-success_callback = ["langsmith"]
-failure_callback = ["langsmith"]
-service_callback = []
-```
-
-Then set the following environment variables:
-
-```
-LANGSMITH_API_KEY=<api_key>
-LANGSMITH_PROJECT=<project>
-LANGSMITH_BASE_URL=<url>
-```
-
-## Ignoring automatic commands in PRs
-
-In some cases, you may want to automatically ignore specific PRs . Qodo Merge enables you to ignore PR with a specific title, or from/to specific branches (regex matching).
-
-To ignore PRs with a specific title such as "[Bump]: ...", you can add the following to your `configuration.toml` file:
-
-```
-[config]
-ignore_pr_title = ["\\[Bump\\]"]
-```
-
-Where the `ignore_pr_title` is a list of regex patterns to match the PR title you want to ignore. Default is `ignore_pr_title = ["^\\[Auto\\]", "^Auto"]`.
-
-
-To ignore PRs from specific source or target branches, you can add the following to your `configuration.toml` file:
-
-```
-[config]
-ignore_pr_source_branches = ['develop', 'main', 'master', 'stage']
-ignore_pr_target_branches = ["qa"]
-```
-
-Where the `ignore_pr_source_branches` and `ignore_pr_target_branches` are lists of regex patterns to match the source and target branches you want to ignore.
-They are not mutually exclusive, you can use them together or separately.
-
-
-To allow only specific folders (often needed in large monorepos), set:
-
-```
-[config]
-allow_only_specific_folders=['folder1','folder2']
-```
-
-For the configuration above, automatic feedback will only be triggered when the PR changes include files from 'folder1' or 'folder2'

docs/docs/usage-guide/automations_and_usage.md

@@ -1,291 +0,0 @@
-## Local repo (CLI)
-
-When running from your locally cloned Qodo Merge repo (CLI), your local configuration file will be used.
-Examples of invoking the different tools via the CLI:
-
-- **Review**:       `python -m pr_agent.cli --pr_url=<pr_url>  review`
-- **Describe**:     `python -m pr_agent.cli --pr_url=<pr_url>  describe`
-- **Improve**:      `python -m pr_agent.cli --pr_url=<pr_url>  improve`
-- **Ask**:          `python -m pr_agent.cli --pr_url=<pr_url>  ask "Write me a poem about this PR"`
-- **Reflect**:      `python -m pr_agent.cli --pr_url=<pr_url>  reflect`
-- **Update Changelog**:      `python -m pr_agent.cli --pr_url=<pr_url>  update_changelog`
-
-`<pr_url>` is the url of the relevant PR (for example: [#50](https://github.com/Codium-ai/pr-agent/pull/50)).
-
-**Notes:**
-
-(1) in addition to editing your local configuration file, you can also change any configuration value by adding it to the command line:
-```
-python -m pr_agent.cli --pr_url=<pr_url>  /review --pr_reviewer.extra_instructions="focus on the file: ..."
-```
-
-(2) You can print results locally, without publishing them, by setting in `configuration.toml`:
-```
-[config]
-publish_output=false
-verbosity_level=2
-```
-This is useful for debugging or experimenting with different tools.
-
-(3)
-
-**git provider**: The [git_provider](https://github.com/Codium-ai/pr-agent/blob/main/pr_agent/settings/configuration.toml#L5) field in a configuration file determines the GIT provider that will be used by Qodo Merge. Currently, the following providers are supported:
-`
-"github", "gitlab", "bitbucket", "azure", "codecommit", "local", "gerrit"
-`
-
-Default is "github".
-
-### CLI Health Check
-To verify that Qodo Merge has been configured correctly, you can run this health check command from the repository root:
-
-```bash
-python -m tests.health_test.main
-```
-
-If the health check passes, you will see the following output:
-
-```
-========
-Health test passed successfully
-========
-```
-
-At the end of the run.
-
-Before running the health check, ensure you have:
-
-- Configured your [LLM provider](https://qodo-merge-docs.qodo.ai/usage-guide/changing_a_model/)
-- Added a valid GitHub token to your configuration file
-
-## Online usage
-
-Online usage means invoking Qodo Merge tools by [comments](https://github.com/Codium-ai/pr-agent/pull/229#issuecomment-1695021901) on a PR.
-Commands for invoking the different tools via comments:
-
-- **Review**:       `/review`
-- **Describe**:     `/describe`
-- **Improve**:      `/improve`  (or `/improve_code` for bitbucket, since `/improve` is sometimes reserved)
-- **Ask**:          `/ask "..."`
-- **Reflect**:      `/reflect`
-- **Update Changelog**:      `/update_changelog`
-
-
-To edit a specific configuration value, just add `--config_path=<value>` to any command.
-For example, if you want to edit the `review` tool configurations, you can run:
-```
-/review --pr_reviewer.extra_instructions="..." --pr_reviewer.require_score_review=false
-```
-Any configuration value in [configuration file](https://github.com/Codium-ai/pr-agent/blob/main/pr_agent/settings/configuration.toml) file can be similarly edited. Comment `/config` to see the list of available configurations.
-
-
-## Qodo Merge Automatic Feedback
-
-
-### Disabling all automatic feedback
-
-To easily disable all automatic feedback from Qodo Merge (GitHub App, GitLab Webhook, BitBucket App, Azure DevOps Webhook), set in a configuration file:
-
-```toml
-[config]
-disable_auto_feedback = true
-```
-
-When this parameter is set to `true`, Qodo Merge will not run any automatic tools (like `describe`, `review`, `improve`) when a new PR is opened, or when new code is pushed to an open PR.
-
-### GitHub App
-
-!!! note "Configurations for Qodo Merge Pro"
-    Qodo Merge Pro for GitHub is an App, hosted by CodiumAI. So all the instructions below are relevant also for Qodo Merge Pro users.
-    Same goes for [GitLab webhook](#gitlab-webhook) and [BitBucket App](#bitbucket-app) sections.
-
-#### GitHub app automatic tools when a new PR is opened
-
-The [github_app](https://github.com/Codium-ai/pr-agent/blob/main/pr_agent/settings/configuration.toml#L220) section defines GitHub app specific configurations.
-
-The configuration parameter `pr_commands` defines the list of tools that will be **run automatically** when a new PR is opened:
-```toml
-[github_app]
-pr_commands = [
-    "/describe",
-    "/review",
-    "/improve",
-]
-```
-
-This means that when a new PR is opened/reopened or marked as ready for review, Qodo Merge will run the `describe`, `review` and `improve` tools.  
-
-You can override the default tool parameters by using one the three options for a [configuration file](https://qodo-merge-docs.qodo.ai/usage-guide/configuration_options/): **wiki**, **local**, or **global**.
-For example, if your configuration file contains:
-
-```toml
-[pr_description]
-generate_ai_title = true
-```
-
-Every time you run the `describe` tool (including automatic runs) the PR title will be generated by the AI.
-
-You can customize configurations specifically for automated runs by using the `--config_path=<value>` parameter.
-For instance, to modify the `review` tool settings only for newly opened PRs, use:
-```toml
-[github_app]
-pr_commands = [
-    "/describe",
-    "/review --pr_reviewer.extra_instructions='focus on the file: ...'",
-    "/improve",
-]
-```
-
-#### GitHub app automatic tools for push actions (commits to an open PR)
-
-In addition to running automatic tools when a PR is opened, the GitHub app can also respond to new code that is pushed to an open PR.
-
-The configuration toggle `handle_push_trigger` can be used to enable this feature.
-The configuration parameter `push_commands` defines the list of tools that will be **run automatically** when new code is pushed to the PR.
-```toml
-[github_app]
-handle_push_trigger = true
-push_commands = [
-    "/describe",
-    "/review",
-]
-```
-This means that when new code is pushed to the PR, the Qodo Merge will run the `describe` and `review` tools, with the specified parameters.
-
-### GitHub Action
-`GitHub Action` is a different way to trigger Qodo Merge tools, and uses a different configuration mechanism than `GitHub App`.<br>
-You can configure settings for `GitHub Action` by adding environment variables under the env section in `.github/workflows/pr_agent.yml` file.
-Specifically, start by setting the following environment variables:
-```yaml
-      env:
-        OPENAI_KEY: ${{ secrets.OPENAI_KEY }} # Make sure to add your OpenAI key to your repo secrets
-        GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} # Make sure to add your GitHub token to your repo secrets
-        github_action_config.auto_review: "true" # enable\disable auto review
-        github_action_config.auto_describe: "true" # enable\disable auto describe
-        github_action_config.auto_improve: "true" # enable\disable auto improve
-        github_action_config.pr_actions: '["opened", "reopened", "ready_for_review", "review_requested"]'
-```
-`github_action_config.auto_review`, `github_action_config.auto_describe` and `github_action_config.auto_improve` are used to enable/disable automatic tools that run when a new PR is opened.
-If not set, the default configuration is for all three tools to run automatically when a new PR is opened.
-
-`github_action_config.pr_actions` is used to configure which `pull_requests` events will trigger the enabled auto flags
-If not set, the default configuration is `["opened", "reopened", "ready_for_review", "review_requested"]`
-
-`github_action_config.enable_output` are used to enable/disable github actions [output parameter](https://docs.github.com/en/actions/creating-actions/metadata-syntax-for-github-actions#outputs-for-docker-container-and-javascript-actions) (default is `true`).
-Review result is output as JSON to `steps.{step-id}.outputs.review` property.
-The JSON structure is equivalent to the yaml data structure defined in [pr_reviewer_prompts.toml](https://github.com/idubnori/pr-agent/blob/main/pr_agent/settings/pr_reviewer_prompts.toml).
-
-Note that you can give additional config parameters by adding environment variables to `.github/workflows/pr_agent.yml`, or by using a `.pr_agent.toml` [configuration file](https://qodo-merge-docs.qodo.ai/usage-guide/configuration_options/#global-configuration-file) in the root of your repo
-
-For example, you can set an environment variable: `pr_description.publish_labels=false`, or add a `.pr_agent.toml` file with the following content:
-
-```toml
-[pr_description]
-publish_labels = false
-```
-
-to prevent Qodo Merge from publishing labels when running the `describe` tool.
-
-### GitLab Webhook
-After setting up a GitLab webhook, to control which commands will run automatically when a new MR is opened, you can set the `pr_commands` parameter in the configuration file, similar to the GitHub App:
-
-```toml
-[gitlab]
-pr_commands = [
-    "/describe",
-    "/review",
-    "/improve",
-]
-```
-
-the GitLab webhook can also respond to new code that is pushed to an open MR.
-The configuration toggle `handle_push_trigger` can be used to enable this feature.
-The configuration parameter `push_commands` defines the list of tools that will be **run automatically** when new code is pushed to the MR.
-```toml
-[gitlab]
-handle_push_trigger = true
-push_commands = [
-    "/describe",
-    "/review",
-]
-```
-
-Note that to use the 'handle_push_trigger' feature, you need to give the gitlab webhook also the "Push events" scope.
-
-### BitBucket App
-Similar to GitHub app, when running Qodo Merge from BitBucket App, the default [configuration file](https://github.com/Codium-ai/pr-agent/blob/main/pr_agent/settings/configuration.toml) from a pre-built docker will be initially loaded.
-
-By uploading a local `.pr_agent.toml` file to the root of the repo's main branch, you can edit and customize any configuration parameter. Note that you need to upload `.pr_agent.toml` prior to creating a PR, in order for the configuration to take effect.
-
-For example, if your local `.pr_agent.toml` file contains:
-```toml
-[pr_reviewer]
-extra_instructions = "Answer in japanese"
-```
-
-Each time you invoke a `/review` tool, it will use the extra instructions you set in the local configuration file.
-
-
-Note that among other limitations, BitBucket provides relatively low rate-limits for applications (up to 1000 requests per hour), and does not provide an API to track the actual rate-limit usage.
-If you experience a lack of responses from Qodo Merge, you might want to set: `bitbucket_app.avoid_full_files=true` in your configuration file.
-This will prevent Qodo Merge from acquiring the full file content, and will only use the diff content. This will reduce the number of requests made to BitBucket, at the cost of small decrease in accuracy, as dynamic context will not be applicable.
-
-
-#### BitBucket Self-Hosted App automatic tools
-
-To control which commands will run automatically when a new PR is opened, you can set the `pr_commands` parameter in the configuration file:
-Specifically, set the following values:
-
-```toml
-[bitbucket_app]
-pr_commands = [
-    "/review",
-    "/improve --pr_code_suggestions.commitable_code_suggestions=true --pr_code_suggestions.suggestions_score_threshold=7",
-]
-```
-Note that we set specifically for bitbucket, we recommend using: `--pr_code_suggestions.suggestions_score_threshold=7` and that is the default value we set for bitbucket.
-Since this platform only supports inline code suggestions, we want to limit the number of suggestions, and only present a limited number.
-
-To enable BitBucket app to respond to each **push** to the PR, set (for example):
-```toml
-[bitbucket_app]
-handle_push_trigger = true
-push_commands = [
-    "/describe",
-    "/review",
-]
-```
-
-### Azure DevOps provider
-
-To use Azure DevOps provider use the following settings in configuration.toml:
-```toml
-[config]
-git_provider="azure"
-```
-
-Azure DevOps provider supports [PAT token](https://learn.microsoft.com/en-us/azure/devops/organizations/accounts/use-personal-access-tokens-to-authenticate?view=azure-devops&tabs=Windows) or [DefaultAzureCredential](https://learn.microsoft.com/en-us/azure/developer/python/sdk/authentication-overview#authentication-in-server-environments) authentication.
-PAT is faster to create, but has build in expiration date, and will use the user identity for API calls.
-Using DefaultAzureCredential you can use managed identity or Service principle, which are more secure and will create separate ADO user identity (via AAD) to the agent.
-
-If PAT was chosen, you can assign the value in .secrets.toml.
-If DefaultAzureCredential was chosen, you can assigned the additional env vars like AZURE_CLIENT_SECRET directly,
-or use managed identity/az cli (for local development) without any additional configuration.
-in any case, 'org' value must be assigned in .secrets.toml:
-```
-[azure_devops]
-org = "https://dev.azure.com/YOUR_ORGANIZATION/"
-# pat = "YOUR_PAT_TOKEN" needed only if using PAT for authentication
-```
-
-#### Azure DevOps Webhook
-
-To control which commands will run automatically when a new PR is opened, you can set the `pr_commands` parameter in the configuration file, similar to the GitHub App:
-```toml
-[azure_devops_server]
-pr_commands = [
-    "/describe",
-    "/review --pr_reviewer.num_code_suggestions=0",
-    "/improve",
-]
-```

docs/docs/usage-guide/changing_a_model.md

@@ -1,195 +0,0 @@
-## Changing a model
-
-See [here](https://github.com/Codium-ai/pr-agent/blob/main/pr_agent/algo/__init__.py) for a list of available models.
-To use a different model than the default (GPT-4), you need to edit in the [configuration file](https://github.com/Codium-ai/pr-agent/blob/main/pr_agent/settings/configuration.toml#L2) the fields:
-```
-[config]
-model = "..."
-fallback_models = ["..."]
-```
-
-For models and environments not from OpenAI, you might need to provide additional keys and other parameters.
-You can give parameters via a configuration file (see below for instructions), or from environment variables. See [litellm documentation](https://litellm.vercel.app/docs/proxy/quick_start#supported-llms) for the environment variables relevant per model.
-
-### Azure
-
-To use Azure, set in your `.secrets.toml` (working from CLI), or in the GitHub `Settings > Secrets and variables` (working from GitHub App or GitHub Action):
-```
-[openai]
-key = "" # your azure api key
-api_type = "azure"
-api_version = '2023-05-15'  # Check Azure documentation for the current API version
-api_base = ""  # The base URL for your Azure OpenAI resource. e.g. "https://<your resource name>.openai.azure.com"
-deployment_id = ""  # The deployment name you chose when you deployed the engine
-```
-
-and set in your configuration file:
-```
-[config]
-model="" # the OpenAI model you've deployed on Azure (e.g. gpt-4o)
-fallback_models=["..."]
-```
-
-### Hugging Face
-
-**Local**
-You can run Hugging Face models locally through either [VLLM](https://docs.litellm.ai/docs/providers/vllm) or [Ollama](https://docs.litellm.ai/docs/providers/ollama)
-
-E.g. to use a new Hugging Face model locally via Ollama, set:
-```
-[__init__.py]
-MAX_TOKENS = {
-    "model-name-on-ollama": <max_tokens>
-}
-e.g.
-MAX_TOKENS={
-    ...,
-    "ollama/llama2": 4096
-}
-
-
-[config] # in configuration.toml
-model = "ollama/llama2"
-fallback_models=["ollama/llama2"]
-
-[ollama] # in .secrets.toml
-api_base = ... # the base url for your Hugging Face inference endpoint
-# e.g. if running Ollama locally, you may use:
-api_base = "http://localhost:11434/"
-```
-
-### Inference Endpoints
-
-To use a new model with Hugging Face Inference Endpoints, for example, set:
-```
-[__init__.py]
-MAX_TOKENS = {
-    "model-name-on-huggingface": <max_tokens>
-}
-e.g.
-MAX_TOKENS={
-    ...,
-    "meta-llama/Llama-2-7b-chat-hf": 4096
-}
-[config] # in configuration.toml
-model = "huggingface/meta-llama/Llama-2-7b-chat-hf"
-fallback_models=["huggingface/meta-llama/Llama-2-7b-chat-hf"]
-
-[huggingface] # in .secrets.toml
-key = ... # your Hugging Face api key
-api_base = ... # the base url for your Hugging Face inference endpoint
-```
-(you can obtain a Llama2 key from [here](https://replicate.com/replicate/llama-2-70b-chat/api))
-
-### Replicate
-
-To use Llama2 model with Replicate, for example, set:
-```
-[config] # in configuration.toml
-model = "replicate/llama-2-70b-chat:2c1608e18606fad2812020dc541930f2d0495ce32eee50074220b87300bc16e1"
-fallback_models=["replicate/llama-2-70b-chat:2c1608e18606fad2812020dc541930f2d0495ce32eee50074220b87300bc16e1"]
-[replicate] # in .secrets.toml
-key = ...
-```
-(you can obtain a Llama2 key from [here](https://replicate.com/replicate/llama-2-70b-chat/api))
-
-
-Also, review the [AiHandler](https://github.com/Codium-ai/pr-agent/blob/main/pr_agent/algo/ai_handler.py) file for instructions on how to set keys for other models.
-
-### Groq
-
-To use Llama3 model with Groq, for example, set:
-```
-[config] # in configuration.toml
-model = "llama3-70b-8192"
-fallback_models = ["groq/llama3-70b-8192"]
-[groq] # in .secrets.toml
-key = ... # your Groq api key
-```
-(you can obtain a Groq key from [here](https://console.groq.com/keys))
-
-### Vertex AI
-
-To use Google's Vertex AI platform and its associated models (chat-bison/codechat-bison) set:
-
-```
-[config] # in configuration.toml
-model = "vertex_ai/codechat-bison"
-fallback_models="vertex_ai/codechat-bison"
-
-[vertexai] # in .secrets.toml
-vertex_project = "my-google-cloud-project"
-vertex_location = ""
-```
-
-Your [application default credentials](https://cloud.google.com/docs/authentication/application-default-credentials) will be used for authentication so there is no need to set explicit credentials in most environments.
-
-If you do want to set explicit credentials, then you can use the `GOOGLE_APPLICATION_CREDENTIALS` environment variable set to a path to a json credentials file.
-
-### Google AI Studio
-
-To use [Google AI Studio](https://aistudio.google.com/) models, set the relevant models in the configuration section of the configuration file:
-
-```toml
-[config] # in configuration.toml
-model="google_ai_studio/gemini-1.5-flash"
-fallback_models=["google_ai_studio/gemini-1.5-flash"]
-
-[google_ai_studio] # in .secrets.toml
-gemini_api_key = "..."
-```
-
-If you don't want to set the API key in the .secrets.toml file, you can set the `GOOGLE_AI_STUDIO.GEMINI_API_KEY` environment variable.
-
-### Anthropic
-
-To use Anthropic models, set the relevant models in the configuration section of the configuration file:
-
-```
-[config]
-model="anthropic/claude-3-opus-20240229"
-fallback_models=["anthropic/claude-3-opus-20240229"]
-```
-
-And also set the api key in the .secrets.toml file:
-```
-[anthropic]
-KEY = "..."
-```
-
-### Amazon Bedrock
-
-To use Amazon Bedrock and its foundational models, add the below configuration:
-
-```
-[config] # in configuration.toml
-model="bedrock/anthropic.claude-3-sonnet-20240229-v1:0"
-fallback_models=["bedrock/anthropic.claude-v2:1"]
-```
-
-Note that you have to add access to foundational models before using them. Please refer to [this document](https://docs.aws.amazon.com/bedrock/latest/userguide/setting-up.html) for more details.
-
-If you are using the claude-3 model, please configure the following settings as there are parameters incompatible with claude-3.
-```
-[litellm]
-drop_params = true
-```
-
-AWS session is automatically authenticated from your environment, but you can also explicitly set `AWS_ACCESS_KEY_ID`, `AWS_SECRET_ACCESS_KEY` and `AWS_REGION_NAME` environment variables. Please refer to [this document](https://litellm.vercel.app/docs/providers/bedrock) for more details.
-
-### Custom models
-
-If the relevant model doesn't appear [here](https://github.com/Codium-ai/pr-agent/blob/main/pr_agent/algo/__init__.py), you can still use it as a custom model:
-
-(1) Set the model name in the configuration file:
-```
-[config]
-model="custom_model_name"
-fallback_models=["custom_model_name"]
-```
-(2) Set the maximal tokens for the model:
-```
-[config]
-custom_model_max_tokens= ...
-```
-(3) Go to [litellm documentation](https://litellm.vercel.app/docs/proxy/quick_start#supported-llms), find the model you want to use, and set the relevant environment variables.

docs/docs/usage-guide/configuration_options.md

@@ -1,71 +0,0 @@
-The different tools and sub-tools used by Qodo Merge are adjustable via the **[configuration file](https://github.com/Codium-ai/pr-agent/blob/main/pr_agent/settings/configuration.toml)**.
-
-In addition to general configuration options, each tool has its own configurations. For example, the `review` tool will use parameters from the [pr_reviewer](https://github.com/Codium-ai/pr-agent/blob/main/pr_agent/settings/configuration.toml#L16) section in the configuration file.
-See the [Tools Guide](https://qodo-merge-docs.qodo.ai/tools/) for a detailed description of the different tools and their configurations.
-
-There are three ways to set persistent configurations:
-
-1. Wiki configuration page 💎
-2. Local configuration file
-3. Global configuration file 💎
-
-In terms of precedence, wiki configurations will override local configurations, and local configurations will override global configurations.
-
-!!! tip "Tip1: edit only what you need"
-    Your configuration file should be minimal, and edit only the relevant values. Don't copy the entire configuration options, since it can lead to legacy problems when something changes.
-!!! tip "Tip2: show relevant configurations"
-    If you set `config.output_relevant_configurations=true`, each tool will also output in a collapsible section its relevant configurations. This can be useful for debugging, or getting to know the configurations better.
-
-## Wiki configuration file 💎
-
-`Platforms supported: GitHub, GitLab, Bitbucket`
-
-With Qodo Merge Pro, you can set configurations by creating a page called `.pr_agent.toml` in the [wiki](https://github.com/Codium-ai/pr-agent/wiki/pr_agent.toml) of the repo.
-The advantage of this method is that it allows to set configurations without needing to commit new content to the repo - just edit the wiki page and **save**.
-
-
-![wiki_configuration](https://codium.ai/images/pr_agent/wiki_configuration.png){width=512}
-
-Click [here](https://codium.ai/images/pr_agent/wiki_configuration_pr_agent.mp4) to see a short instructional video. We recommend surrounding the configuration content with triple-quotes (or \`\`\`toml), to allow better presentation when displayed in the wiki as markdown.
-An example content:
-
-```toml
-[pr_description]
-generate_ai_title=true
-```
-
-Qodo Merge will know to remove the surrounding quotes when reading the configuration content.
-
-## Local configuration file
-
-`Platforms supported: GitHub, GitLab, Bitbucket, Azure DevOps`
-
-
-By uploading a local `.pr_agent.toml` file to the root of the repo's main branch, you can edit and customize any configuration parameter. Note that you need to upload `.pr_agent.toml` prior to creating a PR, in order for the configuration to take effect.
-
-For example, if you set in `.pr_agent.toml`:
-
-```
-[pr_reviewer]
-extra_instructions="""\
-- instruction a
-- instruction b
-...
-"""
-```
-
-Then you can give a list of extra instructions to the `review` tool.
-
-
-## Global configuration file 💎
-
-`Platforms supported: GitHub, GitLab, Bitbucket`
-
-If you create a repo called `pr-agent-settings` in your **organization**, it's configuration file `.pr_agent.toml` will be used as a global configuration file for any other repo that belongs to the same organization.
-Parameters from a local `.pr_agent.toml` file, in a specific repo, will override the global configuration parameters.
-
-For example, in the GitHub organization `Codium-ai`:
-
-- The file [`https://github.com/Codium-ai/pr-agent-settings/.pr_agent.toml`](https://github.com/Codium-ai/pr-agent-settings/blob/main/.pr_agent.toml)  serves as a global configuration file for all the repos in the GitHub organization `Codium-ai`.
-
-- The repo [`https://github.com/Codium-ai/pr-agent`](https://github.com/Codium-ai/pr-agent/blob/main/.pr_agent.toml) inherits the global configuration file from `pr-agent-settings`.

docs/docs/usage-guide/index.md

@@ -1,26 +0,0 @@
-# Usage guide
-
-This page provides a detailed guide on how to use Qodo Merge.
-It includes information on how to adjust Qodo Merge configurations, define which tools will run automatically, and other advanced configurations.
-
-
-- [Introduction](./introduction.md)
-- [Configuration File](./configuration_options.md)
-- [Usage and Automation](./automations_and_usage.md)
-    - [Local Repo (CLI)](./automations_and_usage.md#local-repo-cli)
-    - [Online Usage](./automations_and_usage.md#online-usage)
-    - [GitHub App](./automations_and_usage.md#github-app)
-    - [GitHub Action](./automations_and_usage.md#github-action)
-    - [GitLab Webhook](./automations_and_usage.md#gitlab-webhook)
-    - [BitBucket App](./automations_and_usage.md#bitbucket-app)
-    - [Azure DevOps Provider](./automations_and_usage.md#azure-devops-provider)
-- [Managing Mail Notifications](./mail_notifications.md)
-- [Changing a Model](./changing_a_model.md)
-- [Additional Configurations Walkthrough](./additional_configurations.md)
-    - [Ignoring files from analysis](./additional_configurations.md#ignoring-files-from-analysis)
-    - [Extra instructions](./additional_configurations.md#extra-instructions)
-    - [Working with large PRs](./additional_configurations.md#working-with-large-prs)
-    - [Changing a model](./additional_configurations.md#changing-a-model)
-    - [Patch Extra Lines](./additional_configurations.md#patch-extra-lines)
-    - [Editing the prompts](./additional_configurations.md#editing-the-prompts)
-- [Qodo Merge Pro Models](./PR_agent_pro_models.md)

docs/docs/usage-guide/introduction.md

@@ -1,12 +0,0 @@
-
-After [installation](https://qodo-merge-docs.qodo.ai/installation/), there are three basic ways to invoke Qodo Merge:
-
-1. Locally running a CLI command
-2. Online usage - by [commenting](https://github.com/Codium-ai/pr-agent/pull/229#issuecomment-1695021901) on a PR
-3. Enabling Qodo Merge tools to run automatically when a new PR is opened
-
-
-Specifically, CLI commands can be issued by invoking a pre-built [docker image](https://qodo-merge-docs.qodo.ai/installation/locally/#using-docker-image), or by invoking a [locally cloned repo](https://qodo-merge-docs.qodo.ai/installation/locally/#run-from-source).
-
-For online usage, you will need to setup either a [GitHub App](https://qodo-merge-docs.qodo.ai/installation/github/#run-as-a-github-app) or a [GitHub Action](https://qodo-merge-docs.qodo.ai/installation/github/#run-as-a-github-action) (GitHub), a [GitLab webhook](https://qodo-merge-docs.qodo.ai/installation/gitlab/#run-a-gitlab-webhook-server) (GitLab), or a [BitBucket App](https://qodo-merge-docs.qodo.ai/installation/bitbucket/#run-using-codiumai-hosted-bitbucket-app) (BitBucket).
-These platforms also enable to run Qodo Merge specific tools automatically when a new PR is opened, or on each push to a branch.

docs/docs/usage-guide/mail_notifications.md

@@ -1,18 +0,0 @@
-
-Unfortunately, it is not possible in GitHub to disable mail notifications from a specific user.
-If you are subscribed to notifications for a repo with Qodo Merge, we recommend turning off notifications for PR comments, to avoid lengthy emails:
-
-![notifications](https://codium.ai/images/pr_agent/notifications.png){width=512}
-
-As an alternative, you can filter in your mail provider the notifications specifically from the Qodo Merge bot, [see how](https://www.quora.com/How-can-you-filter-emails-for-specific-people-in-Gmail#:~:text=On%20the%20Filters%20and%20Blocked,the%20body%20of%20the%20email).
-
-![filter_mail_notifications](https://codium.ai/images/pr_agent/filter_mail_notifications.png){width=512}
-
-
-Another option to reduce the mail overload, yet still receive notifications on Qodo Merge tools, is to disable the help collapsible section in Qodo Merge bot comments.
-This can done by setting `enable_help_text=false` for the relevant tool in the configuration file.
-For example, to disable the help text for the `pr_reviewer` tool, set:
-```
-[pr_reviewer]
-enable_help_text = false
-```

docs/mkdocs.yml

@@ -1,157 +0,0 @@
-site_name: Qodo Merge (formerly known as PR-Agent)
-repo_url: https://github.com/Codium-ai/pr-agent
-repo_name: Codium-ai/pr-agent
-
-nav:
-  - Overview:
-    - 'index.md'
-    - 💎 Qodo Merge Pro: 'overview/pr_agent_pro.md'
-    - Data Privacy: 'overview/data_privacy.md'
-  - Installation:
-    - 'installation/index.md'
-    - Locally: 'installation/locally.md'
-    - GitHub: 'installation/github.md'
-    - GitLab: 'installation/gitlab.md'
-    - BitBucket: 'installation/bitbucket.md'
-    - Azure DevOps: 'installation/azure.md'
-    - 💎 Qodo Merge Pro: 'installation/pr_agent_pro.md'
-  - Usage Guide:
-    - 'usage-guide/index.md'
-    - Introduction: 'usage-guide/introduction.md'
-    - Configuration File: 'usage-guide/configuration_options.md'
-    - Usage and Automation: 'usage-guide/automations_and_usage.md'
-    - Managing Mail Notifications: 'usage-guide/mail_notifications.md'
-    - Changing a Model: 'usage-guide/changing_a_model.md'
-    - Additional Configurations: 'usage-guide/additional_configurations.md'
-    - 💎 Qodo Merge Pro Models: 'usage-guide/PR_agent_pro_models'
-  - Tools:
-    - 'tools/index.md'
-    - Describe: 'tools/describe.md'
-    - Review: 'tools/review.md'
-    - Improve: 'tools/improve.md'
-    - Ask: 'tools/ask.md'
-    - Update Changelog: 'tools/update_changelog.md'
-    - Similar Issues: 'tools/similar_issues.md'
-    - Help: 'tools/help.md'
-    - 💎 Analyze: 'tools/analyze.md'
-    - 💎 Test: 'tools/test.md'
-    - 💎 Improve Component: 'tools/improve_component.md'
-    - 💎 Documentation: 'tools/documentation.md'
-    - 💎 Custom Labels: 'tools/custom_labels.md'
-    - 💎 Custom Prompt: 'tools/custom_prompt.md'
-    - 💎 CI Feedback: 'tools/ci_feedback.md'
-    - 💎 Similar Code: 'tools/similar_code.md'
-  - Core Abilities:
-      - 'core-abilities/index.md'
-      - Fetching ticket context: 'core-abilities/fetching_ticket_context.md'
-      - Local and global metadata: 'core-abilities/metadata.md'
-      - Dynamic context: 'core-abilities/dynamic_context.md'
-      - Self-reflection: 'core-abilities/self_reflection.md'
-      - Impact evaluation: 'core-abilities/impact_evaluation.md'
-      - Interactivity: 'core-abilities/interactivity.md'
-      - Compression strategy: 'core-abilities/compression_strategy.md'
-      - Code-oriented YAML: 'core-abilities/code_oriented_yaml.md'
-      - Static code analysis: 'core-abilities/static_code_analysis.md'
-      - Code Fine-tuning Benchmark: 'finetuning_benchmark/index.md'
-  - Chrome Extension:
-      - Qodo Merge Chrome Extension: 'chrome-extension/index.md'
-      - Features: 'chrome-extension/features.md'
-      - Data Privacy: 'chrome-extension/data_privacy.md'
-  - FAQ:
-      - FAQ: 'faq/index.md'
-#  - Code Fine-tuning Benchmark: 'finetuning_benchmark/index.md'
-
-theme:
-  logo: assets/logo.svg
-  favicon: assets/favicon.ico
-  name: material
-  icon:
-    repo: fontawesome/brands/github
-  features:
-    - navigation.tabs
-    - navigation.expand
-    - navigation.path
-    - navigation.top
-    - navigation.tracking
-    - navigation.indexes
-    - search.suggest
-    - search.highlight
-    - content.tabs.link
-    - content.code.annotation
-    - content.code.copy
-    - content.tabs.link
-  language: en
-  custom_dir: overrides
-
-  palette:
-    - media: "(prefers-color-scheme)"
-      toggle:
-        icon: material/brightness-auto
-        name: Switch to light mode
-    - media: "(prefers-color-scheme: light)"
-      scheme: default
-      toggle:
-        icon: material/toggle-switch-off-outline
-        name: Switch to dark mode
-      primary: custom
-      accent: custom
-    - media: "(prefers-color-scheme: dark)"
-      scheme: slate
-      toggle:
-        icon: material/toggle-switch
-        name: Switch to light mode
-      primary: custom
-      accent: custom
-
-plugins:
-  - social
-  - search
-  - glightbox
-
-extra:
-  generator: false
-  social:
-    - icon: fontawesome/brands/github
-      link: https://github.com/Codium-ai
-    - icon: fontawesome/brands/discord
-      link: https://discord.com/invite/SgSxuQ65GF
-    - icon: fontawesome/brands/youtube
-      link: https://www.youtube.com/@Codium-AI
-    - icon: fontawesome/brands/linkedin
-      link: https://www.linkedin.com/company/codiumai
-    - icon: fontawesome/brands/twitter
-      link: https://twitter.com/CodiumAI
-    - icon: fontawesome/brands/instagram
-      link: https://www.instagram.com/codiumai/
-  analytics:
-    provider: custom
-    property: ${{ secrets.GOOGLE_ANALYTICS_ID }}
-
-extra_css:
-  - css/custom.css
-
-markdown_extensions:
-  - pymdownx.highlight:
-      anchor_linenums: true
-  - pymdownx.inlinehilite
-  - pymdownx.snippets
-  - admonition
-  - pymdownx.arithmatex:
-      generic: true
-  - footnotes
-  - pymdownx.details
-  - pymdownx.superfences
-  - pymdownx.mark
-  - md_in_html
-  - attr_list
-  - pymdownx.emoji:
-      emoji_index: !!python/name:material.extensions.emoji.twemoji
-      emoji_generator: !!python/name:material.extensions.emoji.to_svg
-  - toc:
-      title: On this page
-      toc_depth: 3
-      permalink: true
-
-
-copyright: |
-  &copy; 2024 <a href="https://www.codium.ai/"  target="_blank" rel="noopener">CodiumAI</a>

docs/overrides/main.html

@@ -1,10 +0,0 @@
-{% extends "base.html" %}
-
-{% block scripts %}
-  {{ super() }}
-
-    <!-- Google Tag Manager (noscript) -->
-    <noscript><iframe src="https://www.googletagmanager.com/ns.html?id=GTM-5C9KZBM3"
-    height="0" width="0" style="display:none;visibility:hidden"></iframe></noscript>
-    <!-- End Google Tag Manager (noscript) -->
-{% endblock %}

docs/overrides/partials/footer.html

@@ -1,115 +0,0 @@
-<!DOCTYPE html>
-<html lang="en">
-<head>
-<meta charset="UTF-8">
-<meta name="viewport" content="width=device-width, initial-scale=1.0">
-<title>Footer</title>
-<style>
-  body {
-    margin: 0;
-    padding: 0;
-    font-family: Arial, sans-serif;
-    font-size: 16px;
-  }
-
-  .wrapper {
-    background-color: #171518;
-  }
-
-  .container {
-    display: flex;
-    flex-direction: row;
-    align-items: center;
-    justify-content: space-between;
-    color: white;
-    padding: 20px;
-    max-width: 61rem;
-    margin-left: auto;
-    margin-right: auto;
-  }
-
-  .footer-links, .social-icons {
-    padding: 0;
-    list-style-type: none;
-    display: flex;
-    justify-content: center;
-    gap: 20px;
-    align-items: center;
-  }
-
-  .footer-links a:hover, .social-icons a:hover {
-    color: #AEA1F1;
-  }
-
-  .social-icons svg {
-    width: 24px;
-    height: auto;
-    fill: white;
-  }
-
-  .footer-text {
-    width: 240px;
-  }
-
-  @media (max-width: 768px) {
-    .container {
-      flex-direction: column;
-      align-items: center;
-      text-align: center;
-    }
-
-    .footer-links, .social-icons, .footer-text {
-      width: 100%;
-      justify-content: center;
-      margin: 10px 0;
-    }
-
-    .footer-links {
-      order: 1;
-    }
-
-    .social-icons {
-      order: 2;
-    }
-
-    .footer-text {
-      order: 3;
-    }
-  }
-</style>
-</head>
-<body>
-
-<footer class="wrapper">
-  <div class="container">
-    <p class="footer-text">© 2024 <a href="https://www.qodo.ai/" target="_blank" rel="noopener">Qodo</a></p>
-    <div class="footer-links">
-      <a href="https://qodo-gen-docs.qodo.ai/">Qodo Gen</a>
-      <p>|</p>
-      <a href="https://qodo-flow-docs.qodo.ai/">AlphaCodium</a>
-    </div>
-    <div class="social-icons">
-      <a href="https://github.com/Codium-ai" target="_blank" rel="noopener" title="github.com" class="social-link">
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-      </a>
-    </div>
-  </div>
-</footer>
-
-</body>
-</html>

docs/overrides/partials/integrations/analytics/custom.html

@@ -1,7 +0,0 @@
-<!-- Google Tag Manager -->
-<script>(function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':
-    new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],
-    j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src=
-    'https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);
-    })(window,document,'script','dataLayer','GTM-M6PJSFV');</script>
-    <!-- End Google Tag Manager -->

pr_agent/__init__.py

@@ -0,0 +1 @@
+

pr_agent/agent/pr_agent.py

@@ -1,98 +1,33 @@
-import shlex
-from functools import partial
+import re
 
-from pr_agent.algo.ai_handlers.base_ai_handler import BaseAiHandler
-from pr_agent.algo.ai_handlers.litellm_ai_handler import LiteLLMAIHandler
-from pr_agent.algo.utils import update_settings_from_args
-from pr_agent.config_loader import get_settings
-from pr_agent.git_providers.utils import apply_repo_settings
-from pr_agent.log import get_logger
-from pr_agent.tools.pr_add_docs import PRAddDocs
+from pr_agent.config_loader import settings
 from pr_agent.tools.pr_code_suggestions import PRCodeSuggestions
-from pr_agent.tools.pr_config import PRConfig
 from pr_agent.tools.pr_description import PRDescription
-from pr_agent.tools.pr_generate_labels import PRGenerateLabels
-from pr_agent.tools.pr_help_message import PRHelpMessage
 from pr_agent.tools.pr_information_from_user import PRInformationFromUser
-from pr_agent.tools.pr_line_questions import PR_LineQuestions
 from pr_agent.tools.pr_questions import PRQuestions
 from pr_agent.tools.pr_reviewer import PRReviewer
-from pr_agent.tools.pr_similar_issue import PRSimilarIssue
-from pr_agent.tools.pr_update_changelog import PRUpdateChangelog
-
-command2class = {
-    "auto_review": PRReviewer,
-    "answer": PRReviewer,
-    "review": PRReviewer,
-    "review_pr": PRReviewer,
-    "reflect": PRInformationFromUser,
-    "reflect_and_review": PRInformationFromUser,
-    "describe": PRDescription,
-    "describe_pr": PRDescription,
-    "improve": PRCodeSuggestions,
-    "improve_code": PRCodeSuggestions,
-    "ask": PRQuestions,
-    "ask_question": PRQuestions,
-    "ask_line": PR_LineQuestions,
-    "update_changelog": PRUpdateChangelog,
-    "config": PRConfig,
-    "settings": PRConfig,
-    "help": PRHelpMessage,
-    "similar_issue": PRSimilarIssue,
-    "add_docs": PRAddDocs,
-    "generate_labels": PRGenerateLabels,
-}
-
-commands = list(command2class.keys())
 
 
 class PRAgent:
-    def __init__(self, ai_handler: partial[BaseAiHandler,] = LiteLLMAIHandler):
-        self.ai_handler = ai_handler  # will be initialized in run_action
-        self.forbidden_cli_args = ['enable_auto_approval']
+    def __init__(self):
+        pass
 
-    async def handle_request(self, pr_url, request, notify=None) -> bool:
-        # First, apply repo specific settings if exists
-        apply_repo_settings(pr_url)
-
-        # Then, apply user specific settings if exists
-        if isinstance(request, str):
-            request = request.replace("'", "\\'")
-            lexer = shlex.shlex(request, posix=True)
-            lexer.whitespace_split = True
-            action, *args = list(lexer)
-        else:
-            action, *args = request
-
-        if args:
-            for forbidden_arg in self.forbidden_cli_args:
-                for arg in args:
-                    if forbidden_arg in arg:
-                        get_logger().error(
-                            f"CLI argument for param '{forbidden_arg}' is forbidden. Use instead a configuration file."
-                        )
-                        return False
-        args = update_settings_from_args(args)
-
-        action = action.lstrip("/").lower()
-        if action not in command2class:
-            get_logger().debug(f"Unknown command: {action}")
-            return False
-        with get_logger().contextualize(command=action, pr_url=pr_url):
-            get_logger().info("PR-Agent request handler started", analytics=True)
-            if action == "reflect_and_review":
-                get_settings().pr_reviewer.ask_and_reflect = True
-            if action == "answer":
-                if notify:
-                    notify()
-                await PRReviewer(pr_url, is_answer=True, args=args, ai_handler=self.ai_handler).run()
-            elif action == "auto_review":
-                await PRReviewer(pr_url, is_auto=True, args=args, ai_handler=self.ai_handler).run()
-            elif action in command2class:
-                if notify:
-                    notify()
-
-                await command2class[action](pr_url, ai_handler=self.ai_handler, args=args).run()
+    async def handle_request(self, pr_url, request) -> bool:
+        action, *args = request.strip().split()
+        if any(cmd == action for cmd in ["/answer"]):
+            await PRReviewer(pr_url, is_answer=True).review()
+        elif any(cmd == action for cmd in ["/review", "/review_pr", "/reflect_and_review"]):
+            if settings.pr_reviewer.ask_and_reflect or "/reflect_and_review" in request:
+                await PRInformationFromUser(pr_url).generate_questions()
             else:
-                return False
-            return True
+                await PRReviewer(pr_url, args=args).review()
+        elif any(cmd == action for cmd in ["/describe", "/describe_pr"]):
+            await PRDescription(pr_url).describe()
+        elif any(cmd == action for cmd in ["/improve", "/improve_code"]):
+            await PRCodeSuggestions(pr_url).suggest()
+        elif any(cmd == action for cmd in ["/ask", "/ask_question"]):
+            await PRQuestions(pr_url, args).answer()
+        else:
+            return False
+
+        return True

pr_agent/algo/__init__.py

@@ -1,79 +1,10 @@
 MAX_TOKENS = {
-    'text-embedding-ada-002': 8000,
-    'gpt-3.5-turbo': 16000,
-    'gpt-3.5-turbo-0125': 16000,
+    'gpt-3.5-turbo': 4000,
     'gpt-3.5-turbo-0613': 4000,
-    'gpt-3.5-turbo-1106': 16000,
+    'gpt-3.5-turbo-0301': 4000,
     'gpt-3.5-turbo-16k': 16000,
     'gpt-3.5-turbo-16k-0613': 16000,
     'gpt-4': 8000,
     'gpt-4-0613': 8000,
     'gpt-4-32k': 32000,
-    'gpt-4-1106-preview': 128000,  # 128K, but may be limited by config.max_model_tokens
-    'gpt-4-0125-preview': 128000,  # 128K, but may be limited by config.max_model_tokens
-    'gpt-4o': 128000,  # 128K, but may be limited by config.max_model_tokens
-    'gpt-4o-2024-05-13': 128000,  # 128K, but may be limited by config.max_model_tokens
-    'gpt-4-turbo-preview': 128000,  # 128K, but may be limited by config.max_model_tokens
-    'gpt-4-turbo-2024-04-09': 128000,  # 128K, but may be limited by config.max_model_tokens
-    'gpt-4-turbo': 128000,  # 128K, but may be limited by config.max_model_tokens
-    'gpt-4o-mini': 128000,  # 128K, but may be limited by config.max_model_tokens
-    'gpt-4o-mini-2024-07-18': 128000,  # 128K, but may be limited by config.max_model_tokens
-    'gpt-4o-2024-08-06': 128000,  # 128K, but may be limited by config.max_model_tokens
-    'gpt-4o-2024-11-20': 128000,  # 128K, but may be limited by config.max_model_tokens
-    'o1-mini': 128000,  # 128K, but may be limited by config.max_model_tokens
-    'o1-mini-2024-09-12': 128000,  # 128K, but may be limited by config.max_model_tokens
-    'o1-preview': 128000,  # 128K, but may be limited by config.max_model_tokens
-    'o1-preview-2024-09-12': 128000,  # 128K, but may be limited by config.max_model_tokens
-    'o1-2024-12-17': 204800,  # 200K, but may be limited by config.max_model_tokens
-    'o1': 204800,  # 200K, but may be limited by config.max_model_tokens
-    'claude-instant-1': 100000,
-    'claude-2': 100000,
-    'command-nightly': 4096,
-    'replicate/llama-2-70b-chat:2c1608e18606fad2812020dc541930f2d0495ce32eee50074220b87300bc16e1': 4096,
-    'meta-llama/Llama-2-7b-chat-hf': 4096,
-    'vertex_ai/codechat-bison': 6144,
-    'vertex_ai/codechat-bison-32k': 32000,
-    'vertex_ai/claude-3-haiku@20240307': 100000,
-    'vertex_ai/claude-3-5-haiku@20241022': 100000,
-    'vertex_ai/claude-3-sonnet@20240229': 100000,
-    'vertex_ai/claude-3-opus@20240229': 100000,
-    'vertex_ai/claude-3-5-sonnet@20240620': 100000,
-    'vertex_ai/claude-3-5-sonnet-v2@20241022': 100000,
-    'vertex_ai/gemini-1.5-pro': 1048576,
-    'vertex_ai/gemini-1.5-flash': 1048576,
-    'vertex_ai/gemma2': 8200,
-    'gemini/gemini-1.5-pro': 1048576,
-    'gemini/gemini-1.5-flash': 1048576,
-    'gemini/gemini-2.0-flash-exp': 1048576,
-    'codechat-bison': 6144,
-    'codechat-bison-32k': 32000,
-    'anthropic.claude-instant-v1': 100000,
-    'anthropic.claude-v1': 100000,
-    'anthropic.claude-v2': 100000,
-    'anthropic/claude-3-opus-20240229': 100000,
-    'anthropic/claude-3-5-sonnet-20240620': 100000,
-    'anthropic/claude-3-5-sonnet-20241022': 100000,
-    'anthropic/claude-3-5-haiku-20241022': 100000,
-    'bedrock/anthropic.claude-instant-v1': 100000,
-    'bedrock/anthropic.claude-v2': 100000,
-    'bedrock/anthropic.claude-v2:1': 100000,
-    'bedrock/anthropic.claude-3-sonnet-20240229-v1:0': 100000,
-    'bedrock/anthropic.claude-3-haiku-20240307-v1:0': 100000,
-    'bedrock/anthropic.claude-3-5-haiku-20241022-v1:0': 100000,
-    'bedrock/anthropic.claude-3-5-sonnet-20240620-v1:0': 100000,
-    'bedrock/anthropic.claude-3-5-sonnet-20241022-v2:0': 100000,
-    'claude-3-5-sonnet': 100000,
-    'groq/llama3-8b-8192': 8192,
-    'groq/llama3-70b-8192': 8192,
-    'groq/mixtral-8x7b-32768': 32768,
-    'groq/llama-3.1-8b-instant': 131072,
-    'groq/llama-3.1-70b-versatile': 131072,
-    'groq/llama-3.1-405b-reasoning': 131072,
-    'ollama/llama3': 4096,
-    'watsonx/meta-llama/llama-3-8b-instruct': 4096,
-    "watsonx/meta-llama/llama-3-70b-instruct": 4096,
-    "watsonx/meta-llama/llama-3-405b-instruct": 16384,
-    "watsonx/ibm/granite-13b-chat-v2": 8191,
-    "watsonx/ibm/granite-34b-code-instruct": 8191,
-    "watsonx/mistralai/mistral-large": 32768,
 }

pr_agent/algo/ai_handler.py

@@ -0,0 +1,82 @@
+import logging
+
+import openai
+from openai.error import APIError, Timeout, TryAgain, RateLimitError
+from retry import retry
+
+from pr_agent.config_loader import settings
+
+OPENAI_RETRIES=5
+
+class AiHandler:
+    """
+    This class handles interactions with the OpenAI API for chat completions.
+    It initializes the API key and other settings from a configuration file,
+    and provides a method for performing chat completions using the OpenAI ChatCompletion API.
+    """
+
+    def __init__(self):
+        """
+        Initializes the OpenAI API key and other settings from a configuration file.
+        Raises a ValueError if the OpenAI key is missing.
+        """
+        try:
+            openai.api_key = settings.openai.key
+            if settings.get("OPENAI.ORG", None):
+                openai.organization = settings.openai.org
+            self.deployment_id = settings.get("OPENAI.DEPLOYMENT_ID", None)
+            if settings.get("OPENAI.API_TYPE", None):
+                openai.api_type = settings.openai.api_type
+            if settings.get("OPENAI.API_VERSION", None):
+                openai.api_version = settings.openai.api_version
+            if settings.get("OPENAI.API_BASE", None):
+                openai.api_base = settings.openai.api_base
+        except AttributeError as e:
+            raise ValueError("OpenAI key is required") from e
+
+    @retry(exceptions=(APIError, Timeout, TryAgain, AttributeError, RateLimitError),
+           tries=OPENAI_RETRIES, delay=2, backoff=2, jitter=(1, 3))
+    async def chat_completion(self, model: str, temperature: float, system: str, user: str):
+        """
+        Performs a chat completion using the OpenAI ChatCompletion API.
+        Retries in case of API errors or timeouts.
+        
+        Args:
+            model (str): The model to use for chat completion.
+            temperature (float): The temperature parameter for chat completion.
+            system (str): The system message for chat completion.
+            user (str): The user message for chat completion.
+        
+        Returns:
+            tuple: A tuple containing the response and finish reason from the API.
+        
+        Raises:
+            TryAgain: If the API response is empty or there are no choices in the response.
+            APIError: If there is an error during OpenAI inference.
+            Timeout: If there is a timeout during OpenAI inference.
+            TryAgain: If there is an attribute error during OpenAI inference.
+        """
+        try:
+            response = await openai.ChatCompletion.acreate(
+                            model=model,
+                            deployment_id=self.deployment_id,
+                            messages=[
+                                {"role": "system", "content": system},
+                                {"role": "user", "content": user}
+                            ],
+                            temperature=temperature,
+                        )
+        except (APIError, Timeout, TryAgain) as e:
+            logging.error("Error during OpenAI inference: ", e)
+            raise
+        except (RateLimitError) as e:
+            logging.error("Rate limit error during OpenAI inference: ", e)
+            raise
+        except (Exception) as e:
+            logging.error("Unknown error during OpenAI inference: ", e)
+            raise TryAgain from e
+        if response is None or len(response.choices) == 0:
+            raise TryAgain
+        resp = response.choices[0]['message']['content']
+        finish_reason = response.choices[0].finish_reason
+        return resp, finish_reason

pr_agent/algo/ai_handlers/base_ai_handler.py

@@ -1,28 +0,0 @@
-from abc import ABC, abstractmethod
-
-
-class BaseAiHandler(ABC):
-    """
-    This class defines the interface for an AI handler to be used by the PR Agents.
-    """
-
-    @abstractmethod
-    def __init__(self):
-        pass
-
-    @property
-    @abstractmethod
-    def deployment_id(self):
-        pass
-
-    @abstractmethod
-    async def chat_completion(self, model: str, system: str, user: str, temperature: float = 0.2, img_path: str = None):
-        """
-        This method should be implemented to return a chat completion from the AI model.
-        Args:
-            model (str): the name of the model to use for the chat completion
-            system (str): the system message string to use for the chat completion
-            user (str): the user message string to use for the chat completion
-            temperature (float): the temperature to use for the chat completion
-        """
-        pass

pr_agent/algo/ai_handlers/langchain_ai_handler.py

@@ -1,76 +0,0 @@
-try:
-    from langchain_core.messages import HumanMessage, SystemMessage
-    from langchain_openai import AzureChatOpenAI, ChatOpenAI
-except:  # we don't enforce langchain as a dependency, so if it's not installed, just move on
-    pass
-
-import functools
-
-from openai import APIError, RateLimitError, Timeout
-from retry import retry
-
-from pr_agent.algo.ai_handlers.base_ai_handler import BaseAiHandler
-from pr_agent.config_loader import get_settings
-from pr_agent.log import get_logger
-
-OPENAI_RETRIES = 5
-
-
-class LangChainOpenAIHandler(BaseAiHandler):
-    def __init__(self):
-        # Initialize OpenAIHandler specific attributes here
-        super().__init__()
-        self.azure = get_settings().get("OPENAI.API_TYPE", "").lower() == "azure"
-
-        # Create a default unused chat object to trigger early validation
-        self._create_chat(self.deployment_id)
-
-    def chat(self, messages: list, model: str, temperature: float):
-        chat = self._create_chat(self.deployment_id)
-        return chat.invoke(input=messages, model=model, temperature=temperature)
-
-    @property
-    def deployment_id(self):
-        """
-        Returns the deployment ID for the OpenAI API.
-        """
-        return get_settings().get("OPENAI.DEPLOYMENT_ID", None)
-
-    @retry(exceptions=(APIError, Timeout, AttributeError, RateLimitError),
-           tries=OPENAI_RETRIES, delay=2, backoff=2, jitter=(1, 3))
-    async def chat_completion(self, model: str, system: str, user: str, temperature: float = 0.2):
-        try:
-            messages = [SystemMessage(content=system), HumanMessage(content=user)]
-
-            # get a chat completion from the formatted messages
-            resp = self.chat(messages, model=model, temperature=temperature)
-            finish_reason = "completed"
-            return resp.content, finish_reason
-
-        except (Exception) as e:
-            get_logger().error("Unknown error during OpenAI inference: ", e)
-            raise e
-
-    def _create_chat(self, deployment_id=None):
-        try:
-            if self.azure:
-                # using a partial function so we can set the deployment_id later to support fallback_deployments
-                # but still need to access the other settings now so we can raise a proper exception if they're missing
-                return AzureChatOpenAI(
-                    openai_api_key=get_settings().openai.key,
-                    openai_api_version=get_settings().openai.api_version,
-                    azure_deployment=deployment_id,
-                    azure_endpoint=get_settings().openai.api_base,
-                )
-            else:
-                # for llms that compatible with openai, should use custom api base
-                openai_api_base = get_settings().get("OPENAI.API_BASE", None)
-                if openai_api_base is None or len(openai_api_base) == 0:
-                    return ChatOpenAI(openai_api_key=get_settings().openai.key)
-                else:
-                    return ChatOpenAI(openai_api_key=get_settings().openai.key, openai_api_base=openai_api_base)
-        except AttributeError as e:
-            if getattr(e, "name"):
-                raise ValueError(f"OpenAI {e.name} is required") from e
-            else:
-                raise e

pr_agent/algo/ai_handlers/litellm_ai_handler.py

@@ -1,265 +0,0 @@
-import os
-
-import litellm
-import openai
-import requests
-from litellm import acompletion
-from tenacity import retry, retry_if_exception_type, stop_after_attempt
-
-from pr_agent.algo.ai_handlers.base_ai_handler import BaseAiHandler
-from pr_agent.algo.utils import get_version
-from pr_agent.config_loader import get_settings
-from pr_agent.log import get_logger
-
-OPENAI_RETRIES = 5
-
-
-class LiteLLMAIHandler(BaseAiHandler):
-    """
-    This class handles interactions with the OpenAI API for chat completions.
-    It initializes the API key and other settings from a configuration file,
-    and provides a method for performing chat completions using the OpenAI ChatCompletion API.
-    """
-
-    def __init__(self):
-        """
-        Initializes the OpenAI API key and other settings from a configuration file.
-        Raises a ValueError if the OpenAI key is missing.
-        """
-        self.azure = False
-        self.api_base = None
-        self.repetition_penalty = None
-        if get_settings().get("OPENAI.KEY", None):
-            openai.api_key = get_settings().openai.key
-            litellm.openai_key = get_settings().openai.key
-        elif 'OPENAI_API_KEY' not in os.environ:
-            litellm.api_key = "dummy_key"
-        if get_settings().get("aws.AWS_ACCESS_KEY_ID"):
-            assert get_settings().aws.AWS_SECRET_ACCESS_KEY and get_settings().aws.AWS_REGION_NAME, "AWS credentials are incomplete"
-            os.environ["AWS_ACCESS_KEY_ID"] = get_settings().aws.AWS_ACCESS_KEY_ID
-            os.environ["AWS_SECRET_ACCESS_KEY"] = get_settings().aws.AWS_SECRET_ACCESS_KEY
-            os.environ["AWS_REGION_NAME"] = get_settings().aws.AWS_REGION_NAME
-        if get_settings().get("litellm.use_client"):
-            litellm_token = get_settings().get("litellm.LITELLM_TOKEN")
-            assert litellm_token, "LITELLM_TOKEN is required"
-            os.environ["LITELLM_TOKEN"] = litellm_token
-            litellm.use_client = True
-        if get_settings().get("LITELLM.DROP_PARAMS", None):
-            litellm.drop_params = get_settings().litellm.drop_params
-        if get_settings().get("LITELLM.SUCCESS_CALLBACK", None):
-            litellm.success_callback = get_settings().litellm.success_callback
-        if get_settings().get("LITELLM.FAILURE_CALLBACK", None):
-            litellm.failure_callback = get_settings().litellm.failure_callback
-        if get_settings().get("LITELLM.SERVICE_CALLBACK", None):
-            litellm.service_callback = get_settings().litellm.service_callback
-        if get_settings().get("OPENAI.ORG", None):
-            litellm.organization = get_settings().openai.org
-        if get_settings().get("OPENAI.API_TYPE", None):
-            if get_settings().openai.api_type == "azure":
-                self.azure = True
-                litellm.azure_key = get_settings().openai.key
-        if get_settings().get("OPENAI.API_VERSION", None):
-            litellm.api_version = get_settings().openai.api_version
-        if get_settings().get("OPENAI.API_BASE", None):
-            litellm.api_base = get_settings().openai.api_base
-        if get_settings().get("ANTHROPIC.KEY", None):
-            litellm.anthropic_key = get_settings().anthropic.key
-        if get_settings().get("COHERE.KEY", None):
-            litellm.cohere_key = get_settings().cohere.key
-        if get_settings().get("GROQ.KEY", None):
-            litellm.api_key = get_settings().groq.key
-        if get_settings().get("REPLICATE.KEY", None):
-            litellm.replicate_key = get_settings().replicate.key
-        if get_settings().get("HUGGINGFACE.KEY", None):
-            litellm.huggingface_key = get_settings().huggingface.key
-        if get_settings().get("HUGGINGFACE.API_BASE", None) and 'huggingface' in get_settings().config.model:
-            litellm.api_base = get_settings().huggingface.api_base
-            self.api_base = get_settings().huggingface.api_base
-        if get_settings().get("OLLAMA.API_BASE", None):
-            litellm.api_base = get_settings().ollama.api_base
-            self.api_base = get_settings().ollama.api_base
-        if get_settings().get("HUGGINGFACE.REPETITION_PENALTY", None):
-            self.repetition_penalty = float(get_settings().huggingface.repetition_penalty)
-        if get_settings().get("VERTEXAI.VERTEX_PROJECT", None):
-            litellm.vertex_project = get_settings().vertexai.vertex_project
-            litellm.vertex_location = get_settings().get(
-                "VERTEXAI.VERTEX_LOCATION", None
-            )
-        # Google AI Studio
-        # SEE https://docs.litellm.ai/docs/providers/gemini
-        if get_settings().get("GOOGLE_AI_STUDIO.GEMINI_API_KEY", None):
-          os.environ["GEMINI_API_KEY"] = get_settings().google_ai_studio.gemini_api_key
-
-    def prepare_logs(self, response, system, user, resp, finish_reason):
-        response_log = response.dict().copy()
-        response_log['system'] = system
-        response_log['user'] = user
-        response_log['output'] = resp
-        response_log['finish_reason'] = finish_reason
-        if hasattr(self, 'main_pr_language'):
-            response_log['main_pr_language'] = self.main_pr_language
-        else:
-            response_log['main_pr_language'] = 'unknown'
-        return response_log
-
-    def add_litellm_callbacks(selfs, kwargs) -> dict:
-        captured_extra = []
-
-        def capture_logs(message):
-            # Parsing the log message and context
-            record = message.record
-            log_entry = {}
-            if record.get('extra', None).get('command', None) is not None:
-                log_entry.update({"command": record['extra']["command"]})
-            if record.get('extra', {}).get('pr_url', None) is not None:
-                log_entry.update({"pr_url": record['extra']["pr_url"]})
-
-            # Append the log entry to the captured_logs list
-            captured_extra.append(log_entry)
-
-        # Adding the custom sink to Loguru
-        handler_id = get_logger().add(capture_logs)
-        get_logger().debug("Capturing logs for litellm callbacks")
-        get_logger().remove(handler_id)
-
-        context = captured_extra[0] if len(captured_extra) > 0 else None
-
-        command = context.get("command", "unknown")
-        pr_url = context.get("pr_url", "unknown")
-        git_provider = get_settings().config.git_provider
-
-        metadata = dict()
-        callbacks = litellm.success_callback + litellm.failure_callback + litellm.service_callback
-        if "langfuse" in callbacks:
-            metadata.update({
-                "trace_name": command,
-                "tags": [git_provider, command, f'version:{get_version()}'],
-                "trace_metadata": {
-                    "command": command,
-                    "pr_url": pr_url,
-                },
-            })
-        if "langsmith" in callbacks:
-            metadata.update({
-                "run_name": command,
-                "tags": [git_provider, command, f'version:{get_version()}'],
-                "extra": {
-                    "metadata": {
-                        "command": command,
-                        "pr_url": pr_url,
-                    }
-                },
-            })
-
-        # Adding the captured logs to the kwargs
-        kwargs["metadata"] = metadata
-
-        return kwargs
-
-    @property
-    def deployment_id(self):
-        """
-        Returns the deployment ID for the OpenAI API.
-        """
-        return get_settings().get("OPENAI.DEPLOYMENT_ID", None)
-
-    @retry(
-        retry=retry_if_exception_type((openai.APIError, openai.APIConnectionError, openai.APITimeoutError)), # No retry on RateLimitError
-        stop=stop_after_attempt(OPENAI_RETRIES)
-    )
-    async def chat_completion(self, model: str, system: str, user: str, temperature: float = 0.2, img_path: str = None):
-        try:
-            resp, finish_reason = None, None
-            deployment_id = self.deployment_id
-            if self.azure:
-                model = 'azure/' + model
-            if 'claude' in model and not system:
-                system = "No system prompt provided"
-                get_logger().warning(
-                    "Empty system prompt for claude model. Adding a newline character to prevent OpenAI API error.")
-            messages = [{"role": "system", "content": system}, {"role": "user", "content": user}]
-
-            if img_path:
-                try:
-                    # check if the image link is alive
-                    r = requests.head(img_path, allow_redirects=True)
-                    if r.status_code == 404:
-                        error_msg = f"The image link is not [alive](img_path).\nPlease repost the original image as a comment, and send the question again with 'quote reply' (see [instructions](https://pr-agent-docs.codium.ai/tools/ask/#ask-on-images-using-the-pr-code-as-context))."
-                        get_logger().error(error_msg)
-                        return f"{error_msg}", "error"
-                except Exception as e:
-                    get_logger().error(f"Error fetching image: {img_path}", e)
-                    return f"Error fetching image: {img_path}", "error"
-                messages[1]["content"] = [{"type": "text", "text": messages[1]["content"]},
-                                          {"type": "image_url", "image_url": {"url": img_path}}]
-
-            # Currently, model OpenAI o1 series does not support a separate system and user prompts
-            O1_MODEL_PREFIX = 'o1'
-            model_type = model.split('/')[-1] if '/' in model else model
-            if model_type.startswith(O1_MODEL_PREFIX):
-                user = f"{system}\n\n\n{user}"
-                system = ""
-                get_logger().info(f"Using O1 model, combining system and user prompts")
-                messages = [{"role": "user", "content": user}]
-                kwargs = {
-                    "model": model,
-                    "deployment_id": deployment_id,
-                    "messages": messages,
-                    "timeout": get_settings().config.ai_timeout,
-                    "api_base": self.api_base,
-                }
-            else:
-                kwargs = {
-                    "model": model,
-                    "deployment_id": deployment_id,
-                    "messages": messages,
-                    "temperature": temperature,
-                    "timeout": get_settings().config.ai_timeout,
-                    "api_base": self.api_base,
-                }
-
-            if get_settings().litellm.get("enable_callbacks", False):
-                kwargs = self.add_litellm_callbacks(kwargs)
-
-            seed = get_settings().config.get("seed", -1)
-            if temperature > 0 and seed >= 0:
-                raise ValueError(f"Seed ({seed}) is not supported with temperature ({temperature}) > 0")
-            elif seed >= 0:
-                get_logger().info(f"Using fixed seed of {seed}")
-                kwargs["seed"] = seed
-
-            if self.repetition_penalty:
-                kwargs["repetition_penalty"] = self.repetition_penalty
-
-            get_logger().debug("Prompts", artifact={"system": system, "user": user})
-
-            if get_settings().config.verbosity_level >= 2:
-                get_logger().info(f"\nSystem prompt:\n{system}")
-                get_logger().info(f"\nUser prompt:\n{user}")
-
-            response = await acompletion(**kwargs)
-        except (openai.APIError, openai.APITimeoutError) as e:
-            get_logger().warning(f"Error during LLM inference: {e}")
-            raise
-        except (openai.RateLimitError) as e:
-            get_logger().error(f"Rate limit error during LLM inference: {e}")
-            raise
-        except (Exception) as e:
-            get_logger().warning(f"Unknown error during LLM inference: {e}")
-            raise openai.APIError from e
-        if response is None or len(response["choices"]) == 0:
-            raise openai.APIError
-        else:
-            resp = response["choices"][0]['message']['content']
-            finish_reason = response["choices"][0]["finish_reason"]
-            get_logger().debug(f"\nAI response:\n{resp}")
-
-            # log the full response for debugging
-            response_log = self.prepare_logs(response, system, user, resp, finish_reason)
-            get_logger().debug("Full_response", artifact=response_log)
-
-            # for CLI debugging
-            if get_settings().config.verbosity_level >= 2:
-                get_logger().info(f"\nAI response:\n{resp}")
-
-        return resp, finish_reason

pr_agent/algo/ai_handlers/openai_ai_handler.py

@@ -1,68 +0,0 @@
-from os import environ
-from pr_agent.algo.ai_handlers.base_ai_handler import BaseAiHandler
-import openai
-from openai import APIError, AsyncOpenAI, RateLimitError, Timeout
-from retry import retry
-
-from pr_agent.algo.ai_handlers.base_ai_handler import BaseAiHandler
-from pr_agent.config_loader import get_settings
-from pr_agent.log import get_logger
-
-OPENAI_RETRIES = 5
-
-
-class OpenAIHandler(BaseAiHandler):
-    def __init__(self):
-        # Initialize OpenAIHandler specific attributes here
-        try:
-            super().__init__()
-            environ["OPENAI_API_KEY"] = get_settings().openai.key
-            if get_settings().get("OPENAI.ORG", None):
-                openai.organization = get_settings().openai.org
-            if get_settings().get("OPENAI.API_TYPE", None):
-                if get_settings().openai.api_type == "azure":
-                    self.azure = True
-                    openai.azure_key = get_settings().openai.key
-            if get_settings().get("OPENAI.API_VERSION", None):
-                openai.api_version = get_settings().openai.api_version
-            if get_settings().get("OPENAI.API_BASE", None):
-                environ["OPENAI_BASE_URL"] = get_settings().openai.api_base
-
-        except AttributeError as e:
-            raise ValueError("OpenAI key is required") from e
-
-    @property
-    def deployment_id(self):
-        """
-        Returns the deployment ID for the OpenAI API.
-        """
-        return get_settings().get("OPENAI.DEPLOYMENT_ID", None)
-
-    @retry(exceptions=(APIError, Timeout, AttributeError, RateLimitError),
-           tries=OPENAI_RETRIES, delay=2, backoff=2, jitter=(1, 3))
-    async def chat_completion(self, model: str, system: str, user: str, temperature: float = 0.2):
-        try:
-            get_logger().info("System: ", system)
-            get_logger().info("User: ", user)
-            messages = [{"role": "system", "content": system}, {"role": "user", "content": user}]
-            client = AsyncOpenAI()
-            chat_completion = await client.chat.completions.create(
-                model=model,
-                messages=messages,
-                temperature=temperature,
-            )
-            resp = chat_completion.choices[0].message.content
-            finish_reason = chat_completion.choices[0].finish_reason
-            usage = chat_completion.usage
-            get_logger().info("AI response", response=resp, messages=messages, finish_reason=finish_reason,
-                              model=model, usage=usage)
-            return resp, finish_reason
-        except (APIError, Timeout) as e:
-            get_logger().error("Error during OpenAI inference: ", e)
-            raise
-        except (RateLimitError) as e:
-            get_logger().error("Rate limit error during OpenAI inference: ", e)
-            raise
-        except (Exception) as e:
-            get_logger().error("Unknown error during OpenAI inference: ", e)
-            raise

pr_agent/algo/file_filter.py

@@ -1,65 +0,0 @@
-import fnmatch
-import re
-
-from pr_agent.config_loader import get_settings
-
-
-def filter_ignored(files, platform = 'github'):
-    """
-    Filter out files that match the ignore patterns.
-    """
-
-    try:
-        # load regex patterns, and translate glob patterns to regex
-        patterns = get_settings().ignore.regex
-        if isinstance(patterns, str):
-            patterns = [patterns]
-        glob_setting = get_settings().ignore.glob
-        if isinstance(glob_setting, str):  # --ignore.glob=[.*utils.py], --ignore.glob=.*utils.py
-            glob_setting = glob_setting.strip('[]').split(",")
-        patterns += [fnmatch.translate(glob) for glob in glob_setting]
-
-        # compile all valid patterns
-        compiled_patterns = []
-        for r in patterns:
-            try:
-                compiled_patterns.append(re.compile(r))
-            except re.error:
-                pass
-
-        # keep filenames that _don't_ match the ignore regex
-        if files and isinstance(files, list):
-            for r in compiled_patterns:
-                if platform == 'github':
-                    files = [f for f in files if (f.filename and not r.match(f.filename))]
-                elif platform == 'bitbucket':
-                    # files = [f for f in files if (f.new.path and not r.match(f.new.path))]
-                    files_o = []
-                    for f in files:
-                        if hasattr(f, 'new'):
-                            if f.new and f.new.path and not r.match(f.new.path):
-                                files_o.append(f)
-                                continue
-                        if hasattr(f, 'old'):
-                            if f.old and f.old.path and not r.match(f.old.path):
-                                files_o.append(f)
-                                continue
-                    files = files_o
-                elif platform == 'gitlab':
-                    # files = [f for f in files if (f['new_path'] and not r.match(f['new_path']))]
-                    files_o = []
-                    for f in files:
-                        if 'new_path' in f and f['new_path'] and not r.match(f['new_path']):
-                            files_o.append(f)
-                            continue
-                        if 'old_path' in f and f['old_path'] and not r.match(f['old_path']):
-                            files_o.append(f)
-                            continue
-                    files = files_o
-                elif platform == 'azure':
-                    files = [f for f in files if not r.match(f)]
-
-    except Exception as e:
-        print(f"Could not filter file list: {e}")
-
-    return files

pr_agent/algo/git_patch_processing.py

@@ -1,187 +1,73 @@
 from __future__ import annotations
 
+import logging
 import re
-import traceback
 
-from pr_agent.algo.types import EDIT_TYPE, FilePatchInfo
-from pr_agent.config_loader import get_settings
-from pr_agent.log import get_logger
+from pr_agent.config_loader import settings
 
 
-def extend_patch(original_file_str, patch_str, patch_extra_lines_before=0,
-                 patch_extra_lines_after=0, filename: str = "") -> str:
-    if not patch_str or (patch_extra_lines_before == 0 and patch_extra_lines_after == 0) or not original_file_str:
+def extend_patch(original_file_str, patch_str, num_lines) -> str:
+    """
+    Extends the given patch to include a specified number of surrounding lines.
+    
+    Args:
+        original_file_str (str): The original file to which the patch will be applied.
+        patch_str (str): The patch to be applied to the original file.
+        num_lines (int): The number of surrounding lines to include in the extended patch.
+        
+    Returns:
+        str: The extended patch string.
+    """
+    if not patch_str or num_lines == 0:
         return patch_str
 
-    original_file_str = decode_if_bytes(original_file_str)
-    if not original_file_str:
-        return patch_str
-
-    if should_skip_patch(filename):
-        return patch_str
-
-    try:
-        extended_patch_str = process_patch_lines(patch_str, original_file_str,
-                                                 patch_extra_lines_before, patch_extra_lines_after)
-    except Exception as e:
-        get_logger().warning(f"Failed to extend patch: {e}", artifact={"traceback": traceback.format_exc()})
-        return patch_str
-
-    return extended_patch_str
-
-
-def decode_if_bytes(original_file_str):
-    if isinstance(original_file_str, (bytes, bytearray)):
-        try:
-            return original_file_str.decode('utf-8')
-        except UnicodeDecodeError:
-            encodings_to_try = ['iso-8859-1', 'latin-1', 'ascii', 'utf-16']
-            for encoding in encodings_to_try:
-                try:
-                    return original_file_str.decode(encoding)
-                except UnicodeDecodeError:
-                    continue
-            return ""
-    return original_file_str
-
-
-def should_skip_patch(filename):
-    patch_extension_skip_types = get_settings().config.patch_extension_skip_types
-    if patch_extension_skip_types and filename:
-        return any(filename.endswith(skip_type) for skip_type in patch_extension_skip_types)
-    return False
-
-
-def process_patch_lines(patch_str, original_file_str, patch_extra_lines_before, patch_extra_lines_after):
-    allow_dynamic_context = get_settings().config.allow_dynamic_context
-    patch_extra_lines_before_dynamic = get_settings().config.max_extra_lines_before_dynamic_context
+    if type(original_file_str) == bytes:
+        original_file_str = original_file_str.decode('utf-8')
 
     original_lines = original_file_str.splitlines()
-    len_original_lines = len(original_lines)
     patch_lines = patch_str.splitlines()
     extended_patch_lines = []
 
-    is_valid_hunk = True
     start1, size1, start2, size2 = -1, -1, -1, -1
     RE_HUNK_HEADER = re.compile(
         r"^@@ -(\d+)(?:,(\d+))? \+(\d+)(?:,(\d+))? @@[ ]?(.*)")
     try:
-        for i,line in enumerate(patch_lines):
+        for line in patch_lines:
             if line.startswith('@@'):
                 match = RE_HUNK_HEADER.match(line)
-                # identify hunk header
                 if match:
-                    # finish processing previous hunk
-                    if is_valid_hunk and (start1 != -1 and patch_extra_lines_after > 0):
-                        delta_lines = [f' {line}' for line in original_lines[start1 + size1 - 1:start1 + size1 - 1 + patch_extra_lines_after]]
-                        extended_patch_lines.extend(delta_lines)
+                    # finish previous hunk
+                    if start1 != -1:
+                        extended_patch_lines.extend(
+                            original_lines[start1 + size1 - 1:start1 + size1 - 1 + num_lines])
 
-                    section_header, size1, size2, start1, start2 = extract_hunk_headers(match)
-
-                    is_valid_hunk = check_if_hunk_lines_matches_to_file(i, original_lines, patch_lines, start1)
-
-                    if is_valid_hunk and (patch_extra_lines_before > 0 or patch_extra_lines_after > 0):
-                        def _calc_context_limits(patch_lines_before):
-                            extended_start1 = max(1, start1 - patch_lines_before)
-                            extended_size1 = size1 + (start1 - extended_start1) + patch_extra_lines_after
-                            extended_start2 = max(1, start2 - patch_lines_before)
-                            extended_size2 = size2 + (start2 - extended_start2) + patch_extra_lines_after
-                            if extended_start1 - 1 + extended_size1 > len_original_lines:
-                                # we cannot extend beyond the original file
-                                delta_cap = extended_start1 - 1 + extended_size1 - len_original_lines
-                                extended_size1 = max(extended_size1 - delta_cap, size1)
-                                extended_size2 = max(extended_size2 - delta_cap, size2)
-                            return extended_start1, extended_size1, extended_start2, extended_size2
-
-                        if allow_dynamic_context:
-                            extended_start1, extended_size1, extended_start2, extended_size2 = \
-                                _calc_context_limits(patch_extra_lines_before_dynamic)
-                            lines_before = original_lines[extended_start1 - 1:start1 - 1]
-                            found_header = False
-                            for i, line, in enumerate(lines_before):
-                                if section_header in line:
-                                    found_header = True
-                                    # Update start and size in one line each
-                                    extended_start1, extended_start2 = extended_start1 + i, extended_start2 + i
-                                    extended_size1, extended_size2 = extended_size1 - i, extended_size2 - i
-                                    # get_logger().debug(f"Found section header in line {i} before the hunk")
-                                    section_header = ''
-                                    break
-                            if not found_header:
-                                # get_logger().debug(f"Section header not found in the extra lines before the hunk")
-                                extended_start1, extended_size1, extended_start2, extended_size2 = \
-                                    _calc_context_limits(patch_extra_lines_before)
-                        else:
-                            extended_start1, extended_size1, extended_start2, extended_size2 = \
-                                _calc_context_limits(patch_extra_lines_before)
-
-                        delta_lines = [f' {line}' for line in original_lines[extended_start1 - 1:start1 - 1]]
-
-                        #  logic to remove section header if its in the extra delta lines (in dynamic context, this is also done)
-                        if section_header and not allow_dynamic_context:
-                            for line in delta_lines:
-                                if section_header in line:
-                                    section_header = ''  # remove section header if it is in the extra delta lines
-                                    break
-                    else:
-                        extended_start1 = start1
-                        extended_size1 = size1
-                        extended_start2 = start2
-                        extended_size2 = size2
-                        delta_lines = []
-                    extended_patch_lines.append('')
+                    start1, size1, start2, size2 = map(int, match.groups()[:4])
+                    section_header = match.groups()[4]
+                    extended_start1 = max(1, start1 - num_lines)
+                    extended_size1 = size1 + (start1 - extended_start1) + num_lines
+                    extended_start2 = max(1, start2 - num_lines)
+                    extended_size2 = size2 + (start2 - extended_start2) + num_lines
                     extended_patch_lines.append(
                         f'@@ -{extended_start1},{extended_size1} '
                         f'+{extended_start2},{extended_size2} @@ {section_header}')
-                    extended_patch_lines.extend(delta_lines)  # one to zero based
+                    extended_patch_lines.extend(
+                        original_lines[extended_start1 - 1:start1 - 1])  # one to zero based
                     continue
             extended_patch_lines.append(line)
     except Exception as e:
-        get_logger().warning(f"Failed to extend patch: {e}", artifact={"traceback": traceback.format_exc()})
+        if settings.config.verbosity_level >= 2:
+            logging.error(f"Failed to extend patch: {e}")
         return patch_str
 
-    # finish processing last hunk
-    if start1 != -1 and patch_extra_lines_after > 0 and is_valid_hunk:
-        delta_lines = original_lines[start1 + size1 - 1:start1 + size1 - 1 + patch_extra_lines_after]
-        # add space at the beginning of each extra line
-        delta_lines = [f' {line}' for line in delta_lines]
-        extended_patch_lines.extend(delta_lines)
+    # finish previous hunk
+    if start1 != -1:
+        extended_patch_lines.extend(
+            original_lines[start1 + size1 - 1:start1 + size1 - 1 + num_lines])
 
     extended_patch_str = '\n'.join(extended_patch_lines)
     return extended_patch_str
 
 
-def check_if_hunk_lines_matches_to_file(i, original_lines, patch_lines, start1):
-    """
-    Check if the hunk lines match the original file content. We saw cases where the hunk header line doesn't match the original file content, and then
-    extending the hunk with extra lines before the hunk header can cause the hunk to be invalid.
-    """
-    is_valid_hunk = True
-    try:
-        if i + 1 < len(patch_lines) and patch_lines[i + 1][0] == ' ': # an existing line in the file
-            if patch_lines[i + 1].strip() != original_lines[start1 - 1].strip():
-                is_valid_hunk = False
-                get_logger().error(
-                    f"Invalid hunk in PR, line {start1} in hunk header doesn't match the original file content")
-    except:
-        pass
-    return is_valid_hunk
-
-
-def extract_hunk_headers(match):
-    res = list(match.groups())
-    for i in range(len(res)):
-        if res[i] is None:
-            res[i] = 0
-    try:
-        start1, size1, start2, size2 = map(int, res[:4])
-    except:  # '@@ -0,0 +1 @@' case
-        start1, size1, size2 = map(int, res[:3])
-        start2 = 0
-    section_header = res[4]
-    return section_header, size1, size2, start1, start2
-
-
 def omit_deletion_hunks(patch_lines) -> str:
     """
     Omit deletion hunks from the patch and return the modified patch.
@@ -211,10 +97,9 @@ def omit_deletion_hunks(patch_lines) -> str:
                 inside_hunk = True
         else:
             temp_hunk.append(line)
-            if line:
-                edit_type = line[0]
-                if edit_type == '+':
-                    add_hunk = True
+            edit_type = line[0]
+            if edit_type == '+':
+                add_hunk = True
     if inside_hunk and add_hunk:
         added_patched.extend(temp_hunk)
 
@@ -222,7 +107,7 @@ def omit_deletion_hunks(patch_lines) -> str:
 
 
 def handle_patch_deletions(patch: str, original_file_content_str: str,
-                           new_file_content_str: str, file_name: str, edit_type: EDIT_TYPE = EDIT_TYPE.UNKNOWN) -> str:
+                           new_file_content_str: str, file_name: str) -> str:
     """
     Handle entire file or deletion patches.
 
@@ -239,25 +124,24 @@ def handle_patch_deletions(patch: str, original_file_content_str: str,
         str: The modified patch with deletion hunks omitted.
 
     """
-    if not new_file_content_str and (edit_type == EDIT_TYPE.DELETED or edit_type == EDIT_TYPE.UNKNOWN):
+    if not new_file_content_str:
         # logic for handling deleted files - don't show patch, just show that the file was deleted
-        if get_settings().config.verbosity_level > 0:
-            get_logger().info(f"Processing file: {file_name}, minimizing deletion file")
+        if settings.config.verbosity_level > 0:
+            logging.info(f"Processing file: {file_name}, minimizing deletion file")
         patch = None # file was deleted
     else:
         patch_lines = patch.splitlines()
         patch_new = omit_deletion_hunks(patch_lines)
         if patch != patch_new:
-            if get_settings().config.verbosity_level > 0:
-                get_logger().info(f"Processing file: {file_name}, hunks were deleted")
+            if settings.config.verbosity_level > 0:
+                logging.info(f"Processing file: {file_name}, hunks were deleted")
             patch = patch_new
     return patch
 
 
 def convert_to_hunks_with_lines_numbers(patch: str, file) -> str:
     """
-    Convert a given patch string into a string with line numbers for each hunk, indicating the new and old content of
-    the file.
+    Convert a given patch string into a string with line numbers for each hunk, indicating the new and old content of the file.
 
     Args:
         patch (str): The patch string to be converted.
@@ -268,7 +152,7 @@ def convert_to_hunks_with_lines_numbers(patch: str, file) -> str:
 
     example output:
 ## src/file.ts
-__new hunk__
+--new hunk--
 881        line1
 882        line2
 883        line3
@@ -277,7 +161,7 @@ __new hunk__
 889        line6
 890        line7
 ...
-__old hunk__
+--old hunk--
         line1
         line2
 -       line3
@@ -286,11 +170,9 @@ __old hunk__
         line6
            ...
     """
-    # if the file was deleted, return a message indicating that the file was deleted
-    if hasattr(file, 'edit_type') and file.edit_type == EDIT_TYPE.DELETED:
-        return f"\n\n## file '{file.filename.strip()}' was deleted\n"
-
-    patch_with_lines_str = f"\n\n## File: '{file.filename.strip()}'\n"
+    
+    patch_with_lines_str = f"## {file.filename}\n"
+    import re
     patch_lines = patch.splitlines()
     RE_HUNK_HEADER = re.compile(
         r"^@@ -(\d+)(?:,(\d+))? \+(\d+)(?:,(\d+))? @@[ ]?(.*)")
@@ -298,114 +180,41 @@ __old hunk__
     old_content_lines = []
     match = None
     start1, size1, start2, size2 = -1, -1, -1, -1
-    prev_header_line = []
-    header_line = []
-    for line_i, line in enumerate(patch_lines):
-        if 'no newline at end of file' in line.lower():
-            continue
-
-        if line.startswith('@@'):
-            header_line = line
-            match = RE_HUNK_HEADER.match(line)
-            if match and (new_content_lines or old_content_lines):  # found a new hunk, split the previous lines
-                if prev_header_line:
-                    patch_with_lines_str += f'\n{prev_header_line}\n'
-                is_plus_lines = is_minus_lines = False
-                if new_content_lines:
-                    is_plus_lines = any([line.startswith('+') for line in new_content_lines])
-                if old_content_lines:
-                    is_minus_lines = any([line.startswith('-') for line in old_content_lines])
-                if is_plus_lines or is_minus_lines: # notice 'True' here - we always present __new hunk__ for section, otherwise LLM gets confused
-                    patch_with_lines_str = patch_with_lines_str.rstrip() + '\n__new hunk__\n'
-                    for i, line_new in enumerate(new_content_lines):
-                        patch_with_lines_str += f"{start2 + i} {line_new}\n"
-                if is_minus_lines:
-                    patch_with_lines_str = patch_with_lines_str.rstrip() + '\n__old hunk__\n'
-                    for line_old in old_content_lines:
-                        patch_with_lines_str += f"{line_old}\n"
-                new_content_lines = []
-                old_content_lines = []
-            if match:
-                prev_header_line = header_line
-
-            section_header, size1, size2, start1, start2 = extract_hunk_headers(match)
-
-        elif line.startswith('+'):
-            new_content_lines.append(line)
-        elif line.startswith('-'):
-            old_content_lines.append(line)
-        else:
-            if not line and line_i: # if this line is empty and the next line is a hunk header, skip it
-                if line_i + 1 < len(patch_lines) and patch_lines[line_i + 1].startswith('@@'):
-                    continue
-                elif line_i + 1 == len(patch_lines):
-                    continue
-            new_content_lines.append(line)
-            old_content_lines.append(line)
-
-    # finishing last hunk
-    if match and new_content_lines:
-        patch_with_lines_str += f'\n{header_line}\n'
-        is_plus_lines = is_minus_lines = False
-        if new_content_lines:
-            is_plus_lines = any([line.startswith('+') for line in new_content_lines])
-        if old_content_lines:
-            is_minus_lines = any([line.startswith('-') for line in old_content_lines])
-        if is_plus_lines or is_minus_lines:  # notice 'True' here - we always present __new hunk__ for section, otherwise LLM gets confused
-            patch_with_lines_str = patch_with_lines_str.rstrip() + '\n__new hunk__\n'
-            for i, line_new in enumerate(new_content_lines):
-                patch_with_lines_str += f"{start2 + i} {line_new}\n"
-        if is_minus_lines:
-            patch_with_lines_str = patch_with_lines_str.rstrip() + '\n__old hunk__\n'
-            for line_old in old_content_lines:
-                patch_with_lines_str += f"{line_old}\n"
-
-    return patch_with_lines_str.rstrip()
-
-
-def extract_hunk_lines_from_patch(patch: str, file_name, line_start, line_end, side) -> tuple[str, str]:
-
-    patch_with_lines_str = f"\n\n## File: '{file_name.strip()}'\n\n"
-    selected_lines = ""
-    patch_lines = patch.splitlines()
-    RE_HUNK_HEADER = re.compile(
-        r"^@@ -(\d+)(?:,(\d+))? \+(\d+)(?:,(\d+))? @@[ ]?(.*)")
-    match = None
-    start1, size1, start2, size2 = -1, -1, -1, -1
-    skip_hunk = False
-    selected_lines_num = 0
     for line in patch_lines:
         if 'no newline at end of file' in line.lower():
             continue
 
         if line.startswith('@@'):
-            skip_hunk = False
-            selected_lines_num = 0
-            header_line = line
-
             match = RE_HUNK_HEADER.match(line)
+            if match and new_content_lines:  # found a new hunk, split the previous lines
+                if new_content_lines:
+                    patch_with_lines_str += '\n--new hunk--\n'
+                    for i, line_new in enumerate(new_content_lines):
+                        patch_with_lines_str += f"{start2 + i} {line_new}\n"
+                if old_content_lines:
+                    patch_with_lines_str += '--old hunk--\n'
+                    for line_old in old_content_lines:
+                        patch_with_lines_str += f"{line_old}\n"
+                new_content_lines = []
+                old_content_lines = []
+            start1, size1, start2, size2 = map(int, match.groups()[:4])
+        elif line.startswith('+'):
+            new_content_lines.append(line)
+        elif line.startswith('-'):
+            old_content_lines.append(line)
+        else:
+            new_content_lines.append(line)
+            old_content_lines.append(line)
 
-            section_header, size1, size2, start1, start2 = extract_hunk_headers(match)
+    # finishing last hunk
+    if match and new_content_lines:
+        if new_content_lines:
+            patch_with_lines_str += '\n--new hunk--\n'
+            for i, line_new in enumerate(new_content_lines):
+                patch_with_lines_str += f"{start2 + i} {line_new}\n"
+        if old_content_lines:
+            patch_with_lines_str += '\n--old hunk--\n'
+            for line_old in old_content_lines:
+                patch_with_lines_str += f"{line_old}\n"
 
-            # check if line range is in this hunk
-            if side.lower() == 'left':
-                # check if line range is in this hunk
-                if not (start1 <= line_start <= start1 + size1):
-                    skip_hunk = True
-                    continue
-            elif side.lower() == 'right':
-                if not (start2 <= line_start <= start2 + size2):
-                    skip_hunk = True
-                    continue
-            patch_with_lines_str += f'\n{header_line}\n'
-
-        elif not skip_hunk:
-            if side.lower() == 'right' and line_start <= start2 + selected_lines_num <= line_end:
-                selected_lines += line + '\n'
-            if side.lower() == 'left' and start1 <= selected_lines_num + start1 <= line_end:
-                selected_lines += line + '\n'
-            patch_with_lines_str += line + '\n'
-            if not line.startswith('-'): # currently we don't support /ask line for deleted lines
-                selected_lines_num += 1
-
-    return patch_with_lines_str.rstrip(), selected_lines.rstrip()
+    return patch_with_lines_str.strip()

pr_agent/algo/language_handler.py

@@ -1,24 +1,22 @@
 # Language Selection, source: https://github.com/bigcode-project/bigcode-dataset/blob/main/language_selection/programming-languages-to-file-extensions.json  # noqa E501
 from typing import Dict
 
-from pr_agent.config_loader import get_settings
+from pr_agent.config_loader import settings
+
+language_extension_map_org = settings.language_extension_map_org
+language_extension_map = {k.lower(): v for k, v in language_extension_map_org.items()}
+
+# Bad Extensions, source: https://github.com/EleutherAI/github-downloader/blob/345e7c4cbb9e0dc8a0615fd995a08bf9d73b3fe6/download_repo_text.py  # noqa: E501
+bad_extensions = settings.bad_extensions.default
+if settings.config.use_extra_bad_extensions:
+    bad_extensions += settings.bad_extensions.extra
 
 
 def filter_bad_extensions(files):
-    # Bad Extensions, source: https://github.com/EleutherAI/github-downloader/blob/345e7c4cbb9e0dc8a0615fd995a08bf9d73b3fe6/download_repo_text.py  # noqa: E501
-    bad_extensions = get_settings().bad_extensions.default
-    if get_settings().config.use_extra_bad_extensions:
-        bad_extensions += get_settings().bad_extensions.extra
-    return [f for f in files if f.filename is not None and is_valid_file(f.filename, bad_extensions)]
+    return [f for f in files if is_valid_file(f.filename)]
 
 
-def is_valid_file(filename:str, bad_extensions=None) -> bool:
-    if not filename:
-        return False
-    if not bad_extensions:
-        bad_extensions = get_settings().bad_extensions.default
-        if get_settings().config.use_extra_bad_extensions:
-            bad_extensions += get_settings().bad_extensions.extra
+def is_valid_file(filename):
     return filename.split('.')[-1] not in bad_extensions
 
 
@@ -31,8 +29,6 @@ def sort_files_by_main_languages(languages: Dict, files: list):
     # languages_sorted = sorted(languages, key=lambda x: x[1], reverse=True)
     # get all extensions for the languages
     main_extensions = []
-    language_extension_map_org = get_settings().language_extension_map_org
-    language_extension_map = {k.lower(): v for k, v in language_extension_map_org.items()}
     for language in languages_sorted_list:
         if language.lower() in language_extension_map:
             main_extensions.append(language_extension_map[language.lower()])
@@ -46,11 +42,6 @@ def sort_files_by_main_languages(languages: Dict, files: list):
     files_sorted = []
     rest_files = {}
 
-    # if no languages detected, put all files in the "Other" category
-    if not languages:
-        files_sorted = [({"language": "Other", "files": list(files_filtered)})]
-        return files_sorted
-
     main_extensions_flat = []
     for ext in main_extensions:
         main_extensions_flat.extend(ext)

pr_agent/algo/pr_processing.py

@@ -1,549 +1,212 @@
 from __future__ import annotations
 
-import traceback
-from typing import Callable, List, Tuple
+import logging
+from typing import Tuple, Union, Callable, List
 
-from github import RateLimitExceededException
-
-from pr_agent.algo.file_filter import filter_ignored
-from pr_agent.algo.git_patch_processing import (
-    convert_to_hunks_with_lines_numbers, extend_patch, handle_patch_deletions)
+from pr_agent.algo import MAX_TOKENS
+from pr_agent.algo.git_patch_processing import convert_to_hunks_with_lines_numbers, extend_patch, handle_patch_deletions
 from pr_agent.algo.language_handler import sort_files_by_main_languages
 from pr_agent.algo.token_handler import TokenHandler
-from pr_agent.algo.types import EDIT_TYPE, FilePatchInfo
-from pr_agent.algo.utils import ModelType, clip_tokens, get_max_tokens, get_weak_model
-from pr_agent.config_loader import get_settings
+from pr_agent.algo.utils import load_large_diff
+from pr_agent.config_loader import settings
 from pr_agent.git_providers.git_provider import GitProvider
-from pr_agent.log import get_logger
 
 DELETED_FILES_ = "Deleted files:\n"
 
-MORE_MODIFIED_FILES_ = "Additional modified files (insufficient token budget to process):\n"
+MORE_MODIFIED_FILES_ = "More modified files:\n"
 
-ADDED_FILES_ = "Additional added files (insufficient token budget to process):\n"
-
-OUTPUT_BUFFER_TOKENS_SOFT_THRESHOLD = 1500
-OUTPUT_BUFFER_TOKENS_HARD_THRESHOLD = 1000
-MAX_EXTRA_LINES = 10
+OUTPUT_BUFFER_TOKENS_SOFT_THRESHOLD = 1000
+OUTPUT_BUFFER_TOKENS_HARD_THRESHOLD = 600
+PATCH_EXTRA_LINES = 3
 
 
-def cap_and_log_extra_lines(value, direction) -> int:
-    if value > MAX_EXTRA_LINES:
-        get_logger().warning(f"patch_extra_lines_{direction} was {value}, capping to {MAX_EXTRA_LINES}")
-        return MAX_EXTRA_LINES
-    return value
+def get_pr_diff(git_provider: GitProvider, token_handler: TokenHandler, model: str,
+                add_line_numbers_to_hunks: bool = False, disable_extra_lines: bool = False) -> str:
+    """
+    Returns a string with the diff of the pull request, applying diff minimization techniques if needed.
 
+    Args:
+        git_provider (GitProvider): An object of the GitProvider class representing the Git provider used for the pull request.
+        token_handler (TokenHandler): An object of the TokenHandler class used for handling tokens in the context of the pull request.
+        model (str): The name of the model used for tokenization.
+        add_line_numbers_to_hunks (bool, optional): A boolean indicating whether to add line numbers to the hunks in the diff. Defaults to False.
+        disable_extra_lines (bool, optional): A boolean indicating whether to disable the extension of each patch with extra lines of context. Defaults to False.
+
+    Returns:
+        str: A string with the diff of the pull request, applying diff minimization techniques if needed.
+    """
 
-def get_pr_diff(git_provider: GitProvider, token_handler: TokenHandler,
-                model: str,
-                add_line_numbers_to_hunks: bool = False,
-                disable_extra_lines: bool = False,
-                large_pr_handling=False,
-                return_remaining_files=False):
     if disable_extra_lines:
-        PATCH_EXTRA_LINES_BEFORE = 0
-        PATCH_EXTRA_LINES_AFTER = 0
-    else:
-        PATCH_EXTRA_LINES_BEFORE = get_settings().config.patch_extra_lines_before
-        PATCH_EXTRA_LINES_AFTER = get_settings().config.patch_extra_lines_after
-        PATCH_EXTRA_LINES_BEFORE = cap_and_log_extra_lines(PATCH_EXTRA_LINES_BEFORE, "before")
-        PATCH_EXTRA_LINES_AFTER = cap_and_log_extra_lines(PATCH_EXTRA_LINES_AFTER, "after")
-
-    try:
-        diff_files_original = git_provider.get_diff_files()
-    except RateLimitExceededException as e:
-        get_logger().error(f"Rate limit exceeded for git provider API. original message {e}")
-        raise
-
-    diff_files = filter_ignored(diff_files_original)
-    if diff_files != diff_files_original:
-        try:
-            get_logger().info(f"Filtered out {len(diff_files_original) - len(diff_files)} files")
-            new_names = set([a.filename for a in diff_files])
-            orig_names = set([a.filename for a in diff_files_original])
-            get_logger().info(f"Filtered out files: {orig_names - new_names}")
-        except Exception as e:
-            pass
+        global PATCH_EXTRA_LINES
+        PATCH_EXTRA_LINES = 0
 
+    diff_files = list(git_provider.get_diff_files())
 
     # get pr languages
     pr_languages = sort_files_by_main_languages(git_provider.get_languages(), diff_files)
-    if pr_languages:
-        try:
-            get_logger().info(f"PR main language: {pr_languages[0]['language']}")
-        except Exception as e:
-            pass
 
     # generate a standard diff string, with patch extension
-    patches_extended, total_tokens, patches_extended_tokens = pr_generate_extended_diff(
-        pr_languages, token_handler, add_line_numbers_to_hunks,
-        patch_extra_lines_before=PATCH_EXTRA_LINES_BEFORE, patch_extra_lines_after=PATCH_EXTRA_LINES_AFTER)
+    patches_extended, total_tokens = pr_generate_extended_diff(pr_languages, token_handler,
+                                                               add_line_numbers_to_hunks)
 
     # if we are under the limit, return the full diff
-    if total_tokens + OUTPUT_BUFFER_TOKENS_SOFT_THRESHOLD < get_max_tokens(model):
-        get_logger().info(f"Tokens: {total_tokens}, total tokens under limit: {get_max_tokens(model)}, "
-                          f"returning full diff.")
+    if total_tokens + OUTPUT_BUFFER_TOKENS_SOFT_THRESHOLD < MAX_TOKENS[model]:
         return "\n".join(patches_extended)
 
-    # if we are over the limit, start pruning (If we got here, we will not extend the patches with extra lines)
-    get_logger().info(f"Tokens: {total_tokens}, total tokens over limit: {get_max_tokens(model)}, "
-                      f"pruning diff.")
-    patches_compressed_list, total_tokens_list, deleted_files_list, remaining_files_list, file_dict, files_in_patches_list = \
-        pr_generate_compressed_diff(pr_languages, token_handler, model, add_line_numbers_to_hunks, large_pr_handling)
+    # if we are over the limit, start pruning
+    patches_compressed, modified_file_names, deleted_file_names = \
+        pr_generate_compressed_diff(pr_languages, token_handler, add_line_numbers_to_hunks)
 
-    if large_pr_handling and len(patches_compressed_list) > 1:
-        get_logger().info(f"Large PR handling mode, and found {len(patches_compressed_list)} patches with original diff.")
-        return "" # return empty string, as we want to generate multiple patches with a different prompt
-
-    # return the first patch
-    patches_compressed = patches_compressed_list[0]
-    total_tokens_new = total_tokens_list[0]
-    files_in_patch = files_in_patches_list[0]
-
-    # Insert additional information about added, modified, and deleted files if there is enough space
-    max_tokens = get_max_tokens(model) - OUTPUT_BUFFER_TOKENS_HARD_THRESHOLD
-    curr_token = total_tokens_new  # == token_handler.count_tokens(final_diff)+token_handler.prompt_tokens
     final_diff = "\n".join(patches_compressed)
-    delta_tokens = 10
-    added_list_str = modified_list_str = deleted_list_str = ""
-    unprocessed_files = []
-    # generate the added, modified, and deleted files lists
-    if (max_tokens - curr_token) > delta_tokens:
-        for filename, file_values in file_dict.items():
-            if filename in files_in_patch:
-                continue
-            if file_values['edit_type'] == EDIT_TYPE.ADDED:
-                unprocessed_files.append(filename)
-                if not added_list_str:
-                    added_list_str = ADDED_FILES_ + f"\n{filename}"
-                else:
-                    added_list_str = added_list_str + f"\n{filename}"
-            elif file_values['edit_type'] in [EDIT_TYPE.MODIFIED, EDIT_TYPE.RENAMED]:
-                unprocessed_files.append(filename)
-                if not modified_list_str:
-                    modified_list_str = MORE_MODIFIED_FILES_ + f"\n{filename}"
-                else:
-                    modified_list_str = modified_list_str + f"\n{filename}"
-            elif file_values['edit_type'] == EDIT_TYPE.DELETED:
-                # unprocessed_files.append(filename) # not needed here, because the file was deleted, so no need to process it
-                if not deleted_list_str:
-                    deleted_list_str = DELETED_FILES_ + f"\n{filename}"
-                else:
-                    deleted_list_str = deleted_list_str + f"\n{filename}"
-
-    # prune the added, modified, and deleted files lists, and add them to the final diff
-    added_list_str = clip_tokens(added_list_str, max_tokens - curr_token)
-    if added_list_str:
-        final_diff = final_diff + "\n\n" + added_list_str
-        curr_token += token_handler.count_tokens(added_list_str) + 2
-    modified_list_str = clip_tokens(modified_list_str, max_tokens - curr_token)
-    if modified_list_str:
+    if modified_file_names:
+        modified_list_str = MORE_MODIFIED_FILES_ + "\n".join(modified_file_names)
         final_diff = final_diff + "\n\n" + modified_list_str
-        curr_token += token_handler.count_tokens(modified_list_str) + 2
-    deleted_list_str = clip_tokens(deleted_list_str, max_tokens - curr_token)
-    if deleted_list_str:
+    if deleted_file_names:
+        deleted_list_str = DELETED_FILES_ + "\n".join(deleted_file_names)
         final_diff = final_diff + "\n\n" + deleted_list_str
-
-    get_logger().debug(f"After pruning, added_list_str: {added_list_str}, modified_list_str: {modified_list_str}, "
-                       f"deleted_list_str: {deleted_list_str}")
-    if not return_remaining_files:
-        return final_diff
-    else:
-        return final_diff, remaining_files_list
+    return final_diff
 
 
-def get_pr_diff_multiple_patchs(git_provider: GitProvider, token_handler: TokenHandler, model: str,
-                add_line_numbers_to_hunks: bool = False, disable_extra_lines: bool = False):
-    try:
-        diff_files_original = git_provider.get_diff_files()
-    except RateLimitExceededException as e:
-        get_logger().error(f"Rate limit exceeded for git provider API. original message {e}")
-        raise
+def pr_generate_extended_diff(pr_languages: list, token_handler: TokenHandler,
+                              add_line_numbers_to_hunks: bool) -> \
+        Tuple[list, int]:
+    """
+    Generate a standard diff string with patch extension, while counting the number of tokens used and applying diff minimization techniques if needed.
 
-    diff_files = filter_ignored(diff_files_original)
-    if diff_files != diff_files_original:
-        try:
-            get_logger().info(f"Filtered out {len(diff_files_original) - len(diff_files)} files")
-            new_names = set([a.filename for a in diff_files])
-            orig_names = set([a.filename for a in diff_files_original])
-            get_logger().info(f"Filtered out files: {orig_names - new_names}")
-        except Exception as e:
-            pass
+    Args:
+    - pr_languages: A list of dictionaries representing the languages used in the pull request and their corresponding files.
+    - token_handler: An object of the TokenHandler class used for handling tokens in the context of the pull request.
+    - add_line_numbers_to_hunks: A boolean indicating whether to add line numbers to the hunks in the diff.
 
-    # get pr languages
-    pr_languages = sort_files_by_main_languages(git_provider.get_languages(), diff_files)
-    if pr_languages:
-        try:
-            get_logger().info(f"PR main language: {pr_languages[0]['language']}")
-        except Exception as e:
-            pass
-
-    patches_compressed_list, total_tokens_list, deleted_files_list, remaining_files_list, file_dict, files_in_patches_list = \
-        pr_generate_compressed_diff(pr_languages, token_handler, model, add_line_numbers_to_hunks, large_pr_handling=True)
-
-    return patches_compressed_list, total_tokens_list, deleted_files_list, remaining_files_list, file_dict, files_in_patches_list
-
-
-def pr_generate_extended_diff(pr_languages: list,
-                              token_handler: TokenHandler,
-                              add_line_numbers_to_hunks: bool,
-                              patch_extra_lines_before: int = 0,
-                              patch_extra_lines_after: int = 0) -> Tuple[list, int, list]:
+    Returns:
+    - patches_extended: A list of extended patches for each file in the pull request.
+    - total_tokens: The total number of tokens used in the extended patches.
+    """
     total_tokens = token_handler.prompt_tokens  # initial tokens
     patches_extended = []
-    patches_extended_tokens = []
     for lang in pr_languages:
         for file in lang['files']:
             original_file_content_str = file.base_file
+            new_file_content_str = file.head_file
             patch = file.patch
+
+            # handle the case of large patch, that initially was not loaded
+            patch = load_large_diff(file, new_file_content_str, original_file_content_str, patch)
+
             if not patch:
                 continue
 
             # extend each patch with extra lines of context
-            extended_patch = extend_patch(original_file_content_str, patch,
-                                          patch_extra_lines_before, patch_extra_lines_after, file.filename)
-            if not extended_patch:
-                get_logger().warning(f"Failed to extend patch for file: {file.filename}")
-                continue
-            full_extended_patch = f"\n\n## {file.filename}\n{extended_patch.rstrip()}\n"
+            extended_patch = extend_patch(original_file_content_str, patch, num_lines=PATCH_EXTRA_LINES)
+            full_extended_patch = f"## {file.filename}\n\n{extended_patch}\n"
 
             if add_line_numbers_to_hunks:
                 full_extended_patch = convert_to_hunks_with_lines_numbers(extended_patch, file)
 
-            # add AI-summary metadata to the patch
-            if file.ai_file_summary and  get_settings().get("config.enable_ai_metadata", False):
-                full_extended_patch = add_ai_summary_top_patch(file, full_extended_patch)
-
             patch_tokens = token_handler.count_tokens(full_extended_patch)
             file.tokens = patch_tokens
             total_tokens += patch_tokens
-            patches_extended_tokens.append(patch_tokens)
             patches_extended.append(full_extended_patch)
 
-    return patches_extended, total_tokens, patches_extended_tokens
+    return patches_extended, total_tokens
 
 
 def pr_generate_compressed_diff(top_langs: list, token_handler: TokenHandler, model: str,
-                                convert_hunks_to_line_numbers: bool,
-                                large_pr_handling: bool) -> Tuple[list, list, list, list, dict, list]:
-    deleted_files_list = []
+                                convert_hunks_to_line_numbers: bool) -> Tuple[list, list, list]:
+    """
+    Generate a compressed diff string for a pull request, using diff minimization techniques to reduce the number of tokens used.
+    Args:
+        top_langs (list): A list of dictionaries representing the languages used in the pull request and their corresponding files.
+        token_handler (TokenHandler): An object of the TokenHandler class used for handling tokens in the context of the pull request.
+        model (str): The model used for tokenization.
+        convert_hunks_to_line_numbers (bool): A boolean indicating whether to convert hunks to line numbers in the diff.
+    Returns:
+        Tuple[list, list, list]: A tuple containing the following lists:
+            - patches: A list of compressed diff patches for each file in the pull request.
+            - modified_files_list: A list of file names that were skipped due to large patch size.
+            - deleted_files_list: A list of file names that were deleted in the pull request.
 
+    Minimization techniques to reduce the number of tokens:
+    0. Start from the largest diff patch to smaller ones
+    1. Don't use extend context lines around diff
+    2. Minimize deleted files
+    3. Minimize deleted hunks
+    4. Minimize all remaining files when you reach token limit
+    """
+
+    patches = []
+    modified_files_list = []
+    deleted_files_list = []
     # sort each one of the languages in top_langs by the number of tokens in the diff
     sorted_files = []
     for lang in top_langs:
         sorted_files.extend(sorted(lang['files'], key=lambda x: x.tokens, reverse=True))
 
-    # generate patches for each file, and count tokens
-    file_dict = {}
+    total_tokens = token_handler.prompt_tokens
     for file in sorted_files:
         original_file_content_str = file.base_file
         new_file_content_str = file.head_file
         patch = file.patch
+        patch = load_large_diff(file, new_file_content_str, original_file_content_str, patch)
         if not patch:
             continue
 
         # removing delete-only hunks
         patch = handle_patch_deletions(patch, original_file_content_str,
-                                       new_file_content_str, file.filename, file.edit_type)
+                                       new_file_content_str, file.filename)
         if patch is None:
-            if file.filename not in deleted_files_list:
-                deleted_files_list.append(file.filename)
+            if not deleted_files_list:
+                total_tokens += token_handler.count_tokens(DELETED_FILES_)
+            deleted_files_list.append(file.filename)
+            total_tokens += token_handler.count_tokens(file.filename) + 1
             continue
 
         if convert_hunks_to_line_numbers:
             patch = convert_to_hunks_with_lines_numbers(patch, file)
 
-        ## add AI-summary metadata to the patch (disabled, since we are in the compressed diff)
-        # if file.ai_file_summary and get_settings().config.get('config.is_auto_command', False):
-        #     patch = add_ai_summary_top_patch(file, patch)
-
         new_patch_tokens = token_handler.count_tokens(patch)
-        file_dict[file.filename] = {'patch': patch, 'tokens': new_patch_tokens, 'edit_type': file.edit_type}
-
-    max_tokens_model = get_max_tokens(model)
-
-    # first iteration
-    files_in_patches_list = []
-    remaining_files_list =  [file.filename for file in sorted_files]
-    patches_list =[]
-    total_tokens_list = []
-    total_tokens, patches, remaining_files_list, files_in_patch_list = generate_full_patch(convert_hunks_to_line_numbers, file_dict,
-                                       max_tokens_model, remaining_files_list, token_handler)
-    patches_list.append(patches)
-    total_tokens_list.append(total_tokens)
-    files_in_patches_list.append(files_in_patch_list)
-
-    # additional iterations (if needed)
-    if large_pr_handling:
-        NUMBER_OF_ALLOWED_ITERATIONS = get_settings().pr_description.max_ai_calls - 1 # one more call is to summarize
-        for i in range(NUMBER_OF_ALLOWED_ITERATIONS-1):
-            if remaining_files_list:
-                total_tokens, patches, remaining_files_list, files_in_patch_list = generate_full_patch(convert_hunks_to_line_numbers,
-                                                                                 file_dict,
-                                                                                  max_tokens_model,
-                                                                                  remaining_files_list, token_handler)
-                if patches:
-                    patches_list.append(patches)
-                    total_tokens_list.append(total_tokens)
-                    files_in_patches_list.append(files_in_patch_list)
-            else:
-                break
-
-    return patches_list, total_tokens_list, deleted_files_list, remaining_files_list, file_dict, files_in_patches_list
-
-
-def generate_full_patch(convert_hunks_to_line_numbers, file_dict, max_tokens_model,remaining_files_list_prev, token_handler):
-    total_tokens = token_handler.prompt_tokens # initial tokens
-    patches = []
-    remaining_files_list_new = []
-    files_in_patch_list = []
-    for filename, data in file_dict.items():
-        if filename not in remaining_files_list_prev:
-            continue
-
-        patch = data['patch']
-        new_patch_tokens = data['tokens']
-        edit_type = data['edit_type']
 
         # Hard Stop, no more tokens
-        if total_tokens > max_tokens_model - OUTPUT_BUFFER_TOKENS_HARD_THRESHOLD:
-            get_logger().warning(f"File was fully skipped, no more tokens: {filename}.")
+        if total_tokens > MAX_TOKENS[model] - OUTPUT_BUFFER_TOKENS_HARD_THRESHOLD:
+            logging.warning(f"File was fully skipped, no more tokens: {file.filename}.")
             continue
 
         # If the patch is too large, just show the file name
-        if total_tokens + new_patch_tokens > max_tokens_model - OUTPUT_BUFFER_TOKENS_SOFT_THRESHOLD:
+        if total_tokens + new_patch_tokens > MAX_TOKENS[model] - OUTPUT_BUFFER_TOKENS_SOFT_THRESHOLD:
             # Current logic is to skip the patch if it's too large
             # TODO: Option for alternative logic to remove hunks from the patch to reduce the number of tokens
             #  until we meet the requirements
-            if get_settings().config.verbosity_level >= 2:
-                get_logger().warning(f"Patch too large, skipping it, {filename}")
-            remaining_files_list_new.append(filename)
+            if settings.config.verbosity_level >= 2:
+                logging.warning(f"Patch too large, minimizing it, {file.filename}")
+            if not modified_files_list:
+                total_tokens += token_handler.count_tokens(MORE_MODIFIED_FILES_)
+            modified_files_list.append(file.filename)
+            total_tokens += token_handler.count_tokens(file.filename) + 1
             continue
 
         if patch:
             if not convert_hunks_to_line_numbers:
-                patch_final = f"\n\n## File: '{filename.strip()}\n\n{patch.strip()}\n'"
+                patch_final = f"## {file.filename}\n\n{patch}\n"
             else:
-                patch_final = "\n\n" + patch.strip()
+                patch_final = patch
             patches.append(patch_final)
             total_tokens += token_handler.count_tokens(patch_final)
-            files_in_patch_list.append(filename)
-            if get_settings().config.verbosity_level >= 2:
-                get_logger().info(f"Tokens: {total_tokens}, last filename: {filename}")
-    return total_tokens, patches, remaining_files_list_new, files_in_patch_list
+            if settings.config.verbosity_level >= 2:
+                logging.info(f"Tokens: {total_tokens}, last filename: {file.filename}")
+
+    return patches, modified_files_list, deleted_files_list
 
 
-async def retry_with_fallback_models(f: Callable, model_type: ModelType = ModelType.REGULAR):
-    all_models = _get_all_models(model_type)
-    all_deployments = _get_all_deployments(all_models)
-    # try each (model, deployment_id) pair until one is successful, otherwise raise exception
-    for i, (model, deployment_id) in enumerate(zip(all_models, all_deployments)):
-        try:
-            get_logger().debug(
-                f"Generating prediction with {model}"
-                f"{(' from deployment ' + deployment_id) if deployment_id else ''}"
-            )
-            get_settings().set("openai.deployment_id", deployment_id)
-            return await f(model)
-        except:
-            get_logger().warning(
-                f"Failed to generate prediction with {model}"
-            )
-            if i == len(all_models) - 1:  # If it's the last iteration
-                raise Exception(f"Failed to generate prediction with any model of {all_models}")
-
-
-def _get_all_models(model_type: ModelType = ModelType.REGULAR) -> List[str]:
-    if model_type == ModelType.WEAK:
-        model = get_weak_model()
-    else:
-        model = get_settings().config.model
-    fallback_models = get_settings().config.fallback_models
+async def retry_with_fallback_models(f: Callable):
+    model = settings.config.model
+    fallback_models = settings.config.fallback_models
     if not isinstance(fallback_models, list):
-        fallback_models = [m.strip() for m in fallback_models.split(",")]
+        fallback_models = [fallback_models]
     all_models = [model] + fallback_models
-    return all_models
-
-
-def _get_all_deployments(all_models: List[str]) -> List[str]:
-    deployment_id = get_settings().get("openai.deployment_id", None)
-    fallback_deployments = get_settings().get("openai.fallback_deployments", [])
-    if not isinstance(fallback_deployments, list) and fallback_deployments:
-        fallback_deployments = [d.strip() for d in fallback_deployments.split(",")]
-    if fallback_deployments:
-        all_deployments = [deployment_id] + fallback_deployments
-        if len(all_deployments) < len(all_models):
-            raise ValueError(f"The number of deployments ({len(all_deployments)}) "
-                             f"is less than the number of models ({len(all_models)})")
-    else:
-        all_deployments = [deployment_id] * len(all_models)
-    return all_deployments
-
-
-def get_pr_multi_diffs(git_provider: GitProvider,
-                       token_handler: TokenHandler,
-                       model: str,
-                       max_calls: int = 5) -> List[str]:
-    """
-    Retrieves the diff files from a Git provider, sorts them by main language, and generates patches for each file.
-    The patches are split into multiple groups based on the maximum number of tokens allowed for the given model.
-
-    Args:
-        git_provider (GitProvider): An object that provides access to Git provider APIs.
-        token_handler (TokenHandler): An object that handles tokens in the context of a pull request.
-        model (str): The name of the model.
-        max_calls (int, optional): The maximum number of calls to retrieve diff files. Defaults to 5.
-
-    Returns:
-        List[str]: A list of final diff strings, split into multiple groups based on the maximum number of tokens allowed for the given model.
-
-    Raises:
-        RateLimitExceededException: If the rate limit for the Git provider API is exceeded.
-    """
-    try:
-        diff_files = git_provider.get_diff_files()
-    except RateLimitExceededException as e:
-        get_logger().error(f"Rate limit exceeded for git provider API. original message {e}")
-        raise
-
-    diff_files = filter_ignored(diff_files)
-
-    # Sort files by main language
-    pr_languages = sort_files_by_main_languages(git_provider.get_languages(), diff_files)
-
-    # Sort files within each language group by tokens in descending order
-    sorted_files = []
-    for lang in pr_languages:
-        sorted_files.extend(sorted(lang['files'], key=lambda x: x.tokens, reverse=True))
-
-    # Get the maximum number of extra lines before and after the patch
-    PATCH_EXTRA_LINES_BEFORE = get_settings().config.patch_extra_lines_before
-    PATCH_EXTRA_LINES_AFTER = get_settings().config.patch_extra_lines_after
-    PATCH_EXTRA_LINES_BEFORE = cap_and_log_extra_lines(PATCH_EXTRA_LINES_BEFORE, "before")
-    PATCH_EXTRA_LINES_AFTER = cap_and_log_extra_lines(PATCH_EXTRA_LINES_AFTER, "after")
-
-    # try first a single run with standard diff string, with patch extension, and no deletions
-    patches_extended, total_tokens, patches_extended_tokens = pr_generate_extended_diff(
-        pr_languages, token_handler, add_line_numbers_to_hunks=True,
-        patch_extra_lines_before=PATCH_EXTRA_LINES_BEFORE,
-        patch_extra_lines_after=PATCH_EXTRA_LINES_AFTER)
-
-    # if we are under the limit, return the full diff
-    if total_tokens + OUTPUT_BUFFER_TOKENS_SOFT_THRESHOLD < get_max_tokens(model):
-        return ["\n".join(patches_extended)] if patches_extended else []
-
-    patches = []
-    final_diff_list = []
-    total_tokens = token_handler.prompt_tokens
-    call_number = 1
-    for file in sorted_files:
-        if call_number > max_calls:
-            if get_settings().config.verbosity_level >= 2:
-                get_logger().info(f"Reached max calls ({max_calls})")
-            break
-
-        original_file_content_str = file.base_file
-        new_file_content_str = file.head_file
-        patch = file.patch
-        if not patch:
-            continue
-
-        # Remove delete-only hunks
-        patch = handle_patch_deletions(patch, original_file_content_str, new_file_content_str, file.filename, file.edit_type)
-        if patch is None:
-            continue
-
-        patch = convert_to_hunks_with_lines_numbers(patch, file)
-        # add AI-summary metadata to the patch
-        if file.ai_file_summary and get_settings().get("config.enable_ai_metadata", False):
-            patch = add_ai_summary_top_patch(file, patch)
-        new_patch_tokens = token_handler.count_tokens(patch)
-
-        if patch and (token_handler.prompt_tokens + new_patch_tokens) > get_max_tokens(
-                model) - OUTPUT_BUFFER_TOKENS_SOFT_THRESHOLD:
-            if get_settings().config.get('large_patch_policy', 'skip') == 'skip':
-                get_logger().warning(f"Patch too large, skipping: {file.filename}")
-                continue
-            elif get_settings().config.get('large_patch_policy') == 'clip':
-                delta_tokens = get_max_tokens(model) - OUTPUT_BUFFER_TOKENS_SOFT_THRESHOLD - token_handler.prompt_tokens
-                patch_clipped = clip_tokens(patch, delta_tokens, delete_last_line=True, num_input_tokens=new_patch_tokens)
-                new_patch_tokens = token_handler.count_tokens(patch_clipped)
-                if patch_clipped and (token_handler.prompt_tokens + new_patch_tokens) > get_max_tokens(
-                        model) - OUTPUT_BUFFER_TOKENS_SOFT_THRESHOLD:
-                    get_logger().warning(f"Patch too large, skipping: {file.filename}")
-                    continue
-                else:
-                    get_logger().info(f"Clipped large patch for file: {file.filename}")
-                    patch = patch_clipped
-            else:
-                get_logger().warning(f"Patch too large, skipping: {file.filename}")
-                continue
-
-        if patch and (total_tokens + new_patch_tokens > get_max_tokens(model) - OUTPUT_BUFFER_TOKENS_SOFT_THRESHOLD):
-            final_diff = "\n".join(patches)
-            final_diff_list.append(final_diff)
-            patches = []
-            total_tokens = token_handler.prompt_tokens
-            call_number += 1
-            if call_number > max_calls: # avoid creating new patches
-                if get_settings().config.verbosity_level >= 2:
-                    get_logger().info(f"Reached max calls ({max_calls})")
-                break
-            if get_settings().config.verbosity_level >= 2:
-                get_logger().info(f"Call number: {call_number}")
-
-        if patch:
-            patches.append(patch)
-            total_tokens += new_patch_tokens
-            if get_settings().config.verbosity_level >= 2:
-                get_logger().info(f"Tokens: {total_tokens}, last filename: {file.filename}")
-
-    # Add the last chunk
-    if patches:
-        final_diff = "\n".join(patches)
-        final_diff_list.append(final_diff)
-
-    return final_diff_list
-
-
-def add_ai_metadata_to_diff_files(git_provider, pr_description_files):
-    """
-    Adds AI metadata to the diff files based on the PR description files (FilePatchInfo.ai_file_summary).
-    """
-    try:
-        if not pr_description_files:
-            get_logger().warning(f"PR description files are empty.")
-            return
-        available_files = {pr_file['full_file_name'].strip(): pr_file for pr_file in pr_description_files}
-        diff_files = git_provider.get_diff_files()
-        found_any_match = False
-        for file in diff_files:
-            filename = file.filename.strip()
-            if filename in available_files:
-                file.ai_file_summary = available_files[filename]
-                found_any_match = True
-        if not found_any_match:
-            get_logger().error(f"Failed to find any matching files between PR description and diff files.",
-                               artifact={"pr_description_files": pr_description_files})
-    except Exception as e:
-        get_logger().error(f"Failed to add AI metadata to diff files: {e}",
-                           artifact={"traceback": traceback.format_exc()})
-
-
-def add_ai_summary_top_patch(file, full_extended_patch):
-    try:
-        # below every instance of '## File: ...' in the patch, add the ai-summary metadata
-        full_extended_patch_lines = full_extended_patch.split("\n")
-        for i, line in enumerate(full_extended_patch_lines):
-            if line.startswith("## File:") or line.startswith("## file:"):
-                full_extended_patch_lines.insert(i + 1,
-                                                 f"### AI-generated changes summary:\n{file.ai_file_summary['long_summary']}")
-                full_extended_patch = "\n".join(full_extended_patch_lines)
-                return full_extended_patch
-
-        # if no '## File: ...' was found
-        return full_extended_patch
-    except Exception as e:
-        get_logger().error(f"Failed to add AI summary to the top of the patch: {e}",
-                           artifact={"traceback": traceback.format_exc()})
-        return full_extended_patch
+    for i, model in enumerate(all_models):
+        try:
+            return await f(model)
+        except Exception as e:
+            logging.warning(f"Failed to generate prediction with {model}: {e}")
+            if i == len(all_models) - 1:  # If it's the last iteration
+                raise  # Re-raise the last exception

pr_agent/algo/token_handler.py

@@ -1,27 +1,8 @@
-from threading import Lock
-
 from jinja2 import Environment, StrictUndefined
-from tiktoken import encoding_for_model, get_encoding
+from tiktoken import encoding_for_model
 
-from pr_agent.config_loader import get_settings
-from pr_agent.log import get_logger
-
-
-class TokenEncoder:
-    _encoder_instance = None
-    _model = None
-    _lock = Lock()  # Create a lock object
-
-    @classmethod
-    def get_token_encoder(cls):
-        model = get_settings().config.model
-        if cls._encoder_instance is None or model != cls._model:  # Check without acquiring the lock for performance
-            with cls._lock:  # Lock acquisition to ensure thread safety
-                if cls._encoder_instance is None or model != cls._model:
-                    cls._model = model
-                    cls._encoder_instance = encoding_for_model(cls._model) if "gpt" in cls._model else get_encoding(
-                        "cl100k_base")
-        return cls._encoder_instance
+from pr_agent.algo import MAX_TOKENS
+from pr_agent.config_loader import settings
 
 
 class TokenHandler:
@@ -29,15 +10,12 @@ class TokenHandler:
     A class for handling tokens in the context of a pull request.
 
     Attributes:
-    - encoder: An object of the encoding_for_model class from the tiktoken module. Used to encode strings and count the
-      number of tokens in them.
-    - limit: The maximum number of tokens allowed for the given model, as defined in the MAX_TOKENS dictionary in the
-      pr_agent.algo module.
-    - prompt_tokens: The number of tokens in the system and user strings, as calculated by the _get_system_user_tokens
-      method.
+    - encoder: An object of the encoding_for_model class from the tiktoken module. Used to encode strings and count the number of tokens in them.
+    - limit: The maximum number of tokens allowed for the given model, as defined in the MAX_TOKENS dictionary in the pr_agent.algo module.
+    - prompt_tokens: The number of tokens in the system and user strings, as calculated by the _get_system_user_tokens method.
     """
 
-    def __init__(self, pr=None, vars: dict = {}, system="", user=""):
+    def __init__(self, pr, vars: dict, system, user):
         """
         Initializes the TokenHandler object.
 
@@ -47,9 +25,8 @@ class TokenHandler:
         - system: The system string.
         - user: The user string.
         """
-        self.encoder = TokenEncoder.get_token_encoder()
-        if pr is not None:
-            self.prompt_tokens = self._get_system_user_tokens(pr, self.encoder, vars, system, user)
+        self.encoder = encoding_for_model(settings.config.model)
+        self.prompt_tokens = self._get_system_user_tokens(pr, self.encoder, vars, system, user)
 
     def _get_system_user_tokens(self, pr, encoder, vars: dict, system, user):
         """
@@ -65,16 +42,13 @@ class TokenHandler:
         Returns:
         The sum of the number of tokens in the system and user strings.
         """
-        try:
-            environment = Environment(undefined=StrictUndefined)
-            system_prompt = environment.from_string(system).render(vars)
-            user_prompt = environment.from_string(user).render(vars)
-            system_prompt_tokens = len(encoder.encode(system_prompt))
-            user_prompt_tokens = len(encoder.encode(user_prompt))
-            return system_prompt_tokens + user_prompt_tokens
-        except Exception as e:
-            get_logger().error(f"Error in _get_system_user_tokens: {e}")
-            return 0
+        environment = Environment(undefined=StrictUndefined)
+        system_prompt = environment.from_string(system).render(vars)
+        user_prompt = environment.from_string(user).render(vars)
+
+        system_prompt_tokens = len(encoder.encode(system_prompt))
+        user_prompt_tokens = len(encoder.encode(user_prompt))
+        return system_prompt_tokens + user_prompt_tokens
 
     def count_tokens(self, patch: str) -> int:
         """
@@ -86,4 +60,4 @@ class TokenHandler:
         Returns:
         The number of tokens in the patch string.
         """
-        return len(self.encoder.encode(patch, disallowed_special=()))
+        return len(self.encoder.encode(patch, disallowed_special=()))