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32
README.md
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@ -43,6 +43,38 @@ Qode Merge PR-Agent aims to help efficiently review and handle pull requests, by
## News and Updates
### November 7, 2024
Added new option: `--pr_code_suggestions.focus_only_on_problems=true`
When enabled, this option reduces the number of code suggestions and categorizes them into just two groups: "Possible Issues" and "General". The suggestions will focus primarily on identifying and fixing code problems, rather than style considerations like best practices, maintainability, or readability.
This mode is ideal for developers who want to concentrate specifically on finding and fixing potential bugs in their pull request code.
**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/)
### November 3, 2024
Meaningful improvement to the quality of code suggestions by separating the code suggestion generation from [line number detection](https://github.com/Codium-ai/pr-agent/pull/1338)
<kbd>![image](https://github.com/user-attachments/assets/093c185c-31ca-47a1-a4fe-be7d9335ea66)</kbd>
### October 27, 2024
Qodo Merge PR Agent will now automatically document accepted code suggestions in a dedicated wiki page (`.pr_agent_accepted_suggestions`), enabling users to track historical changes, assess the tool's effectiveness, and learn from previously implemented recommendations in the repository.

115
docs/docs/core-abilities/fetching_ticket_context.md Normal file
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@ -0,0 +1,115 @@
# Fetching Ticket Context for PRs
## 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.
## Affected Tools
Ticket Recognition Requirements:
1. The PR description should contain a link to the ticket.
2. 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, The PR Description should contain a link to the Jira ticket.
For Jira integration, 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`.
!!! note "Jira Base URL"
If using the shortened format, ensure your configuration file contains the Jira base URL under the [jira] section like this:
```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"
```

1
docs/docs/core-abilities/index.md
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@ -1,6 +1,7 @@
# 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/)

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docs/docs/core-abilities/self_reflection.md
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@ -46,6 +46,5 @@ This results in a more refined and valuable set of suggestions for the user, sav
## Appendix - Relevant Configuration Options
```
[pr_code_suggestions]
self_reflect_on_suggestions = true # Enable self-reflection on code suggestions
suggestions_score_threshold = 0 # Filter out suggestions with a score below this threshold (0-10)
```

2
docs/docs/installation/bitbucket.md
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@ -3,7 +3,7 @@
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
1. Add the following file in your repository bitbucket-pipelines.yml
```yaml
pipelines:

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docs/docs/tools/improve.md
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@ -276,12 +276,12 @@ Using a combination of both can help the AI model to provide relevant and tailor
<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>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>
<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 false.</td>
</tr>
<tr>
<td><b>self_reflect_on_suggestions</b></td>
<td>If set to true, the improve tool will calculate an importance score for each suggestion [1-10], and sort the suggestion labels group based on this score. Default is true.</td>
<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>

2
docs/docs/tools/review.md
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@ -140,7 +140,7 @@ num_code_suggestions = ...
</tr>
<tr>
<td><b>require_ticket_analysis_review</b></td>
<td>If set to true, and the PR contains a GitHub ticket number, the tool will add a section that checks if the PR in fact fulfilled the ticket requirements. Default is true.</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>

10
docs/docs/usage-guide/additional_configurations.md
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@ -160,3 +160,13 @@ 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'

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docs/docs/usage-guide/automations_and_usage.md
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@ -72,13 +72,14 @@ The configuration parameter `pr_commands` defines the list of tools that will be
```
[github_app]
pr_commands = [
"/describe --pr_description.final_update_message=false",
"/review --pr_reviewer.num_code_suggestions=0",
"/improve",
"/describe",
"/review",
"/improve --pr_code_suggestions.suggestions_score_threshold=5",
]
```
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.
For the `review` tool, for example, the `num_code_suggestions` parameter will be set to 0.
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.
For the `improve` tool, for example, the `suggestions_score_threshold` parameter will be set to 5 (suggestions below a score of 5 won't be presented)
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 local `.pr_agent.toml` file contains:
@ -105,7 +106,7 @@ The configuration parameter `push_commands` defines the list of tools that will
handle_push_trigger = true
push_commands = [
"/describe",
"/review --pr_reviewer.num_code_suggestions=0 --pr_reviewer.final_update_message=false",
"/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.
@ -148,7 +149,7 @@ After setting up a GitLab webhook, to control which commands will run automatica
[gitlab]
pr_commands = [
"/describe",
"/review --pr_reviewer.num_code_suggestions=0",
"/review",
"/improve",
]
```
@ -161,7 +162,7 @@ The configuration parameter `push_commands` defines the list of tools that will
handle_push_trigger = true
push_commands = [
"/describe",
"/review --pr_reviewer.num_code_suggestions=0 --pr_reviewer.final_update_message=false",
"/review",
]
```
@ -182,7 +183,7 @@ Each time you invoke a `/review` tool, it will use the extra instructions you se
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 lack of responses from Qodo Merge, you might want to set: `bitbucket_app.avoid_full_files=true` in your configuration file.
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.
@ -194,13 +195,23 @@ Specifically, set the following values:
```
[bitbucket_app]
pr_commands = [
"/review --pr_reviewer.num_code_suggestions=0",
"/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):
```
[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:

1
docs/mkdocs.yml
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@ -43,6 +43,7 @@ nav:
- 💎 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'

3
pr_agent/algo/__init__.py
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@ -31,6 +31,7 @@ MAX_TOKENS = {
'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,
@ -48,11 +49,13 @@ MAX_TOKENS = {
'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,

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pr_agent/algo/ai_handlers/openai_ai_handler.py
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@ -1,5 +1,7 @@
from os import environ
from pr_agent.algo.ai_handlers.base_ai_handler import BaseAiHandler
import openai
from openai.error import APIError, RateLimitError, Timeout, TryAgain
from openai import APIError, AsyncOpenAI, RateLimitError, Timeout
from retry import retry
from pr_agent.algo.ai_handlers.base_ai_handler import BaseAiHandler
@ -14,7 +16,7 @@ class OpenAIHandler(BaseAiHandler):
# Initialize OpenAIHandler specific attributes here
try:
super().__init__()
openai.api_key = get_settings().openai.key
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):
@ -24,7 +26,7 @@ class OpenAIHandler(BaseAiHandler):
if get_settings().get("OPENAI.API_VERSION", None):
openai.api_version = get_settings().openai.api_version
if get_settings().get("OPENAI.API_BASE", None):
openai.api_base = get_settings().openai.api_base
environ["OPENAI_BASE_URL"] = get_settings().openai.api_base
except AttributeError as e:
raise ValueError("OpenAI key is required") from e
@ -36,28 +38,26 @@ class OpenAIHandler(BaseAiHandler):
"""
return get_settings().get("OPENAI.DEPLOYMENT_ID", None)
@retry(exceptions=(APIError, Timeout, TryAgain, AttributeError, RateLimitError),
@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:
deployment_id = self.deployment_id
get_logger().info("System: ", system)
get_logger().info("User: ", user)
messages = [{"role": "system", "content": system}, {"role": "user", "content": user}]
chat_completion = await openai.ChatCompletion.acreate(
client = AsyncOpenAI()
chat_completion = await client.chat.completions.create(
model=model,
deployment_id=deployment_id,
messages=messages,
temperature=temperature,
)
resp = chat_completion["choices"][0]['message']['content']
finish_reason = chat_completion["choices"][0]["finish_reason"]
usage = chat_completion.get("usage")
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, TryAgain) as e:
except (APIError, Timeout) as e:
get_logger().error("Error during OpenAI inference: ", e)
raise
except (RateLimitError) as e:
@ -65,4 +65,4 @@ class OpenAIHandler(BaseAiHandler):
raise
except (Exception) as e:
get_logger().error("Unknown error during OpenAI inference: ", e)
raise TryAgain from e
raise

2
pr_agent/algo/utils.py
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@ -1028,7 +1028,7 @@ def process_description(description_full: str) -> Tuple[str, List]:
if not description_full:
return "", []
description_split = description_full.split(PRDescriptionHeader.CHANGES_WALKTHROUGH)
description_split = description_full.split(PRDescriptionHeader.CHANGES_WALKTHROUGH.value)
base_description_str = description_split[0]
changes_walkthrough_str = ""
files = []

2
pr_agent/git_providers/azuredevops_provider.py
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@ -404,7 +404,7 @@ class AzureDevopsProvider(GitProvider):
pr_body = pr_body[:ind]
if len(pr_body) > MAX_PR_DESCRIPTION_AZURE_LENGTH:
changes_walkthrough_text = PRDescriptionHeader.CHANGES_WALKTHROUGH
changes_walkthrough_text = PRDescriptionHeader.CHANGES_WALKTHROUGH.value
ind = pr_body.find(changes_walkthrough_text)
if ind != -1:
pr_body = pr_body[:ind]

5
pr_agent/settings/configuration.toml
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@ -7,6 +7,7 @@ fallback_models=["gpt-4o-2024-05-13"]
git_provider="github"
publish_output=true
publish_output_progress=true
publish_output_no_suggestions=true
verbosity_level=0 # 0,1,2
use_extra_bad_extensions=false
# Configurations
@ -106,10 +107,11 @@ enable_help_text=false
[pr_code_suggestions] # /improve #
max_context_tokens=14000
max_context_tokens=16000
#
commitable_code_suggestions = false
dual_publishing_score_threshold=-1 # -1 to disable, [0-10] to set the threshold (>=) for publishing a code suggestion both in a table and as commitable
focus_only_on_problems=false
#
extra_instructions = ""
rank_suggestions = false
@ -121,7 +123,6 @@ max_history_len=4
# enable to apply suggestion 💎
apply_suggestions_checkbox=true
# suggestions scoring
self_reflect_on_suggestions=true
suggestions_score_threshold=0 # [0-10]| recommend not to set this value above 8, since above it may clip highly relevant suggestions
# params for '/improve --extended' mode
auto_extended_mode=true

40
pr_agent/settings/pr_code_suggestions_prompts.toml
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@ -1,7 +1,10 @@
[pr_code_suggestions_prompt]
system="""You are PR-Reviewer, an AI specializing in Pull Request (PR) code analysis and suggestions.
Your task is to examine the provided code diff, focusing on new code (lines prefixed with '+'), and offer concise, actionable suggestions to fix possible bugs and problems, and enhance code quality, readability, and performance.
{%- if not focus_only_on_problems %}
Your task is to examine the provided code diff, focusing on new code (lines prefixed with '+'), and offer concise, actionable suggestions to fix possible bugs and problems, and enhance code quality and performance.
{%- else %}
Your task is to examine the provided code diff, focusing on new code (lines prefixed with '+'), and offer concise, actionable suggestions to fix critical bugs and problems.
{%- endif %}
The PR code diff will be in the following structured format:
======
@ -14,10 +17,10 @@ The PR code diff will be in the following structured format:
@@ ... @@ 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
unchanged code line0 in the PR
unchanged code line1 in the PR
+new code line2 added in the PR
unchanged code line3 in the PR
__old hunk__
unchanged code line0
unchanged code line1
@ -35,7 +38,6 @@ __new hunk__
======
- In the format above, the diff is organized into separate '__new hunk__' and '__old hunk__' sections for each code chunk. '__new hunk__' contains the updated code, while '__old hunk__' shows the removed code. If no code was removed in a specific chunk, the __old hunk__ section will be omitted.
- Line numbers were added for the '__new hunk__' sections to help referencing specific lines in the code suggestions. These numbers are for reference only and are not part of the actual code.
- Code lines are prefixed with symbols: '+' for new code added in the PR, '-' for code removed, and ' ' for unchanged code.
{%- if is_ai_metadata %}
- When available, an AI-generated summary will precede each file's diff, with a high-level overview of the changes. Note that this summary may not be fully accurate or complete.
@ -43,9 +45,17 @@ __new hunk__
Specific guidelines for generating code suggestions:
{%- if not focus_only_on_problems %}
- Provide up to {{ num_code_suggestions }} distinct and insightful code suggestions.
- Focus solely on enhancing new code introduced in the PR, identified by '+' prefixes in '__new hunk__' sections (after the line numbers).
{%- else %}
- Provide up to {{ num_code_suggestions }} distinct and insightful code suggestions. Return less suggestions if no pertinent ones are applicable.
{%- endif %}
- Focus solely on enhancing new code introduced in the PR, identified by '+' prefixes in '__new hunk__' sections.
{%- if not focus_only_on_problems %}
- Prioritize suggestions that address potential issues, critical problems, and bugs in the PR code. Avoid repeating changes already implemented in the PR. If no pertinent suggestions are applicable, return an empty list.
{%- else %}
- Only give suggestions that address critical problems and bugs in the PR code. If no relevant suggestions are applicable, return an empty list.
{%- endif %}
- Don't suggest to add docstring, type hints, or comments, to remove unused imports, or to use more specific exception types.
- When referencing variables or names from the code, enclose them in backticks (`). Example: "ensure that `variable_name` is..."
- Be mindful you are viewing a partial PR code diff, not the full codebase. Avoid suggestions that might conflict with unseen code or alerting variables not declared in the visible scope, as the context is incomplete.
@ -67,12 +77,14 @@ class CodeSuggestion(BaseModel):
relevant_file: str = Field(description="Full path of the relevant file")
language: str = Field(description="Programming language used by the relevant file")
suggestion_content: str = Field(description="An actionable suggestion to enhance, improve or fix the new code introduced in the PR. Don't present here actual code snippets, just the suggestion. Be short and concise")
existing_code: str = Field(description="A short code snippet from a '__new hunk__' section that the suggestion aims to enhance or fix. Include only complete code lines, without line numbers. Use ellipsis (...) for brevity if needed. This snippet should represent the specific PR code targeted for improvement.")
existing_code: str = Field(description="A short code snippet from a '__new hunk__' section that the suggestion aims to enhance or fix. Include only complete code lines. Use ellipsis (...) for brevity if needed. This snippet should represent the specific PR code targeted for improvement.")
improved_code: str = Field(description="A refined code snippet that replaces the 'existing_code' snippet after implementing the suggestion.")
one_sentence_summary: str = Field(description="A concise, single-sentence overview of the suggested improvement. Focus on the 'what'. Be general, and avoid method or variable names.")
relevant_lines_start: int = Field(description="The relevant line number, from a '__new hunk__' section, where the suggestion starts (inclusive). Should be derived from the hunk line numbers, and correspond to the beginning of the 'existing code' snippet above")
relevant_lines_end: int = Field(description="The relevant line number, from a '__new hunk__' section, where the suggestion ends (inclusive). Should be derived from the hunk line numbers, and correspond to the end of the 'existing code' snippet above")
label: str = Field(description="A single, descriptive label that best characterizes the suggestion type. Possible labels include 'security', 'possible bug', 'possible issue', 'performance', 'enhancement', 'best practice', 'maintainability'. Other relevant labels are also acceptable.")
{%- if not focus_only_on_problems %}
label: str = Field(description="A single, descriptive label that best characterizes the suggestion type. Possible labels include 'security', 'possible bug', 'possible issue', 'performance', 'enhancement', 'best practice', 'maintainability', 'typo'. Other relevant labels are also acceptable.")
{%- else %}
label: str = Field(description="A single, descriptive label that best characterizes the suggestion type. Possible labels include 'security', 'critical bug', 'general'. The 'general' section should be used for suggestions that address a major issue, but are necessarily on a critical level.")
{%- endif %}
class PRCodeSuggestions(BaseModel):
@ -95,8 +107,6 @@ code_suggestions:
...
one_sentence_summary: |
...
relevant_lines_start: 12
relevant_lines_end: 13
label: |
...
```
@ -112,7 +122,7 @@ Title: '{{title}}'
The PR Diff:
======
{{ diff|trim }}
{{ diff_no_line_numbers|trim }}
======

8
pr_agent/settings/pr_code_suggestions_reflect_prompts.toml
View File

@ -15,8 +15,8 @@ Be particularly vigilant for suggestions that:
- Contradict or ignore parts of the PR's modifications
In such cases, assign the suggestion a score of 0.
For valid suggestions, your role is to provide an impartial and precise score assessment that accurately reflects each suggestion's potential impact on the PR's correctness, quality and functionality.
Evaluate each valid suggestion by scoring its potential impact on the PR's correctness, quality and functionality.
In addition, you should also detect the line numbers in the '__new hunk__' section that correspond to the 'existing_code' snippet.
Key guidelines for evaluation:
- Thoroughly examine both the suggestion content and the corresponding PR code diff. Be vigilant for potential errors in each suggestion, ensuring they are logically sound, accurate, and directly derived from the PR code diff.
@ -82,6 +82,8 @@ The output must be a YAML object equivalent to type $PRCodeSuggestionsFeedback,
class CodeSuggestionFeedback(BaseModel):
suggestion_summary: str = Field(description="Repeated from the input")
relevant_file: str = Field(description="Repeated from the input")
relevant_lines_start: int = Field(description="The relevant line number, from a '__new hunk__' section, where the suggestion starts (inclusive). Should be derived from the hunk line numbers, and correspond to the beginning of the relevant 'existing code' snippet")
relevant_lines_end: int = Field(description="The relevant line number, from a '__new hunk__' section, where the suggestion ends (inclusive). Should be derived from the hunk line numbers, and correspond to the end of the relevant 'existing code' snippet")
suggestion_score: int = Field(description="Evaluate the suggestion and assign a score from 0 to 10. Give 0 if the suggestion is wrong. For valid suggestions, score from 1 (lowest impact/importance) to 10 (highest impact/importance).")
why: str = Field(description="Briefly explain the score given in 1-2 sentences, focusing on the suggestion's impact, relevance, and accuracy.")
@ -96,6 +98,8 @@ code_suggestions:
- suggestion_summary: |
Use a more descriptive variable name here
relevant_file: "src/file1.py"
relevant_lines_start: 13
relevant_lines_end: 14
suggestion_score: 6
why: |
The variable name 't' is not descriptive enough

207
pr_agent/tools/pr_code_suggestions.py
View File

@ -3,6 +3,7 @@ import copy
import difflib
import re
import textwrap
import traceback
from functools import partial
from typing import Dict, List
@ -48,7 +49,7 @@ class PRCodeSuggestions:
self.is_extended = self._get_is_extended(args or [])
except:
self.is_extended = False
num_code_suggestions = get_settings().pr_code_suggestions.num_code_suggestions_per_chunk
num_code_suggestions = int(get_settings().pr_code_suggestions.num_code_suggestions_per_chunk)
self.ai_handler = ai_handler()
@ -73,11 +74,13 @@ class PRCodeSuggestions:
"description": self.pr_description,
"language": self.main_language,
"diff": "", # empty diff for initial calculation
"diff_no_line_numbers": "", # empty diff for initial calculation
"num_code_suggestions": num_code_suggestions,
"extra_instructions": get_settings().pr_code_suggestions.extra_instructions,
"commit_messages_str": self.git_provider.get_commit_messages(),
"relevant_best_practices": "",
"is_ai_metadata": get_settings().get("config.enable_ai_metadata", False),
"focus_only_on_problems": get_settings().get("pr_code_suggestions.focus_only_on_problems", False),
}
self.pr_code_suggestions_prompt_system = get_settings().pr_code_suggestions_prompt.system
@ -114,15 +117,17 @@ class PRCodeSuggestions:
if not data:
data = {"code_suggestions": []}
if (data is None or 'code_suggestions' not in data or not data['code_suggestions']
and get_settings().config.publish_output):
get_logger().warning('No code suggestions found for the PR.')
if (data is None or 'code_suggestions' not in data or not data['code_suggestions']):
pr_body = "## PR Code Suggestions ✨\n\nNo code suggestions found for the PR."
get_logger().debug(f"PR output", artifact=pr_body)
if self.progress_response:
self.git_provider.edit_comment(self.progress_response, body=pr_body)
get_logger().warning('No code suggestions found for the PR.')
if get_settings().config.publish_output and get_settings().config.publish_output_no_suggestions:
get_logger().debug(f"PR output", artifact=pr_body)
if self.progress_response:
self.git_provider.edit_comment(self.progress_response, body=pr_body)
else:
self.git_provider.publish_comment(pr_body)
else:
self.git_provider.publish_comment(pr_body)
get_settings().data = {"artifact": ""}
return
if (not self.is_extended and get_settings().pr_code_suggestions.rank_suggestions) or \
@ -199,8 +204,11 @@ class PRCodeSuggestions:
self.git_provider.remove_comment(self.progress_response)
else:
get_logger().info('Code suggestions generated for PR, but not published since publish_output is False.')
get_settings().data = {"artifact": data}
return
except Exception as e:
get_logger().error(f"Failed to generate code suggestions for PR, error: {e}")
get_logger().error(f"Failed to generate code suggestions for PR, error: {e}",
artifact={"traceback": traceback.format_exc()})
if get_settings().config.publish_output:
if self.progress_response:
self.progress_response.delete()
@ -332,7 +340,7 @@ class PRCodeSuggestions:
if self.patches_diff:
get_logger().debug(f"PR diff", artifact=self.patches_diff)
self.prediction = await self._get_prediction(model, self.patches_diff)
self.prediction = await self._get_prediction(model, self.patches_diff, self.patches_diff_no_line_number)
else:
get_logger().warning(f"Empty PR diff")
self.prediction = None
@ -340,42 +348,76 @@ class PRCodeSuggestions:
data = self.prediction
return data
async def _get_prediction(self, model: str, patches_diff: str) -> dict:
async def _get_prediction(self, model: str, patches_diff: str, patches_diff_no_line_number: str) -> dict:
variables = copy.deepcopy(self.vars)
variables["diff"] = patches_diff # update diff
variables["diff_no_line_numbers"] = patches_diff_no_line_number # update diff
environment = Environment(undefined=StrictUndefined)
system_prompt = environment.from_string(self.pr_code_suggestions_prompt_system).render(variables)
user_prompt = environment.from_string(get_settings().pr_code_suggestions_prompt.user).render(variables)
response, finish_reason = await self.ai_handler.chat_completion(
model=model, temperature=get_settings().config.temperature, system=system_prompt, user=user_prompt)
if not get_settings().config.publish_output:
get_settings().system_prompt = system_prompt
get_settings().user_prompt = user_prompt
# load suggestions from the AI response
data = self._prepare_pr_code_suggestions(response)
# self-reflect on suggestions
if get_settings().pr_code_suggestions.self_reflect_on_suggestions:
model_turbo = get_settings().config.model_turbo # use turbo model for self-reflection, since it is an easier task
response_reflect = await self.self_reflect_on_suggestions(data["code_suggestions"],
patches_diff, model=model_turbo)
if response_reflect:
response_reflect_yaml = load_yaml(response_reflect)
code_suggestions_feedback = response_reflect_yaml["code_suggestions"]
if len(code_suggestions_feedback) == len(data["code_suggestions"]):
for i, suggestion in enumerate(data["code_suggestions"]):
try:
suggestion["score"] = code_suggestions_feedback[i]["suggestion_score"]
suggestion["score_why"] = code_suggestions_feedback[i]["why"]
except Exception as e: #
get_logger().error(f"Error processing suggestion score {i}",
artifact={"suggestion": suggestion,
"code_suggestions_feedback": code_suggestions_feedback[i]})
suggestion["score"] = 7
suggestion["score_why"] = ""
else:
# get_logger().error(f"Could not self-reflect on suggestions. using default score 7")
# self-reflect on suggestions (mandatory, since line numbers are generated now here)
model_reflection = get_settings().config.model
response_reflect = await self.self_reflect_on_suggestions(data["code_suggestions"],
patches_diff, model=model_reflection)
if response_reflect:
response_reflect_yaml = load_yaml(response_reflect)
code_suggestions_feedback = response_reflect_yaml["code_suggestions"]
if len(code_suggestions_feedback) == len(data["code_suggestions"]):
for i, suggestion in enumerate(data["code_suggestions"]):
suggestion["score"] = 7
suggestion["score_why"] = ""
try:
suggestion["score"] = code_suggestions_feedback[i]["suggestion_score"]
suggestion["score_why"] = code_suggestions_feedback[i]["why"]
if 'relevant_lines_start' not in suggestion:
relevant_lines_start = code_suggestions_feedback[i].get('relevant_lines_start', -1)
relevant_lines_end = code_suggestions_feedback[i].get('relevant_lines_end', -1)
suggestion['relevant_lines_start'] = relevant_lines_start
suggestion['relevant_lines_end'] = relevant_lines_end
if relevant_lines_start < 0 or relevant_lines_end < 0:
suggestion["score"] = 0
try:
if get_settings().config.publish_output:
suggestion_statistics_dict = {'score': int(suggestion["score"]),
'label': suggestion["label"].lower().strip()}
get_logger().info(f"PR-Agent suggestions statistics",
statistics=suggestion_statistics_dict, analytics=True)
except Exception as e:
get_logger().error(f"Failed to log suggestion statistics, error: {e}")
pass
except Exception as e: #
get_logger().error(f"Error processing suggestion score {i}",
artifact={"suggestion": suggestion,
"code_suggestions_feedback": code_suggestions_feedback[i]})
suggestion["score"] = 7
suggestion["score_why"] = ""
# if the before and after code is the same, clear one of them
try:
if suggestion['existing_code'] == suggestion['improved_code']:
get_logger().debug(
f"edited improved suggestion {i + 1}, because equal to existing code: {suggestion['existing_code']}")
if get_settings().pr_code_suggestions.commitable_code_suggestions:
suggestion['improved_code'] = "" # we need 'existing_code' to locate the code in the PR
else:
suggestion['existing_code'] = ""
except Exception as e:
get_logger().error(f"Error processing suggestion {i + 1}, error: {e}")
else:
# get_logger().error(f"Could not self-reflect on suggestions. using default score 7")
for i, suggestion in enumerate(data["code_suggestions"]):
suggestion["score"] = 7
suggestion["score_why"] = ""
return data
@ -385,10 +427,10 @@ class PRCodeSuggestions:
suggestion_truncation_message = get_settings().get("PR_CODE_SUGGESTIONS.SUGGESTION_TRUNCATION_MESSAGE", "")
if max_code_suggestion_length > 0:
if len(suggestion['improved_code']) > max_code_suggestion_length:
suggestion['improved_code'] = suggestion['improved_code'][:max_code_suggestion_length]
suggestion['improved_code'] += f"\n{suggestion_truncation_message}"
get_logger().info(f"Truncated suggestion from {len(suggestion['improved_code'])} "
f"characters to {max_code_suggestion_length} characters")
suggestion['improved_code'] = suggestion['improved_code'][:max_code_suggestion_length]
suggestion['improved_code'] += f"\n{suggestion_truncation_message}"
return suggestion
def _prepare_pr_code_suggestions(self, predictions: str) -> Dict:
@ -403,8 +445,7 @@ class PRCodeSuggestions:
one_sentence_summary_list = []
for i, suggestion in enumerate(data['code_suggestions']):
try:
needed_keys = ['one_sentence_summary', 'label', 'relevant_file', 'relevant_lines_start',
'relevant_lines_end']
needed_keys = ['one_sentence_summary', 'label', 'relevant_file']
is_valid_keys = True
for key in needed_keys:
if key not in suggestion:
@ -415,6 +456,11 @@ class PRCodeSuggestions:
if not is_valid_keys:
continue
if get_settings().get("pr_code_suggestions.focus_only_on_problems", False):
CRITICAL_LABEL = 'critical'
if CRITICAL_LABEL in suggestion['label'].lower(): # we want the published labels to be less declarative
suggestion['label'] = 'possible issue'
if suggestion['one_sentence_summary'] in one_sentence_summary_list:
get_logger().debug(f"Skipping suggestion {i + 1}, because it is a duplicate: {suggestion}")
continue
@ -426,13 +472,6 @@ class PRCodeSuggestions:
continue
if ('existing_code' in suggestion) and ('improved_code' in suggestion):
if suggestion['existing_code'] == suggestion['improved_code']:
get_logger().debug(
f"edited improved suggestion {i + 1}, because equal to existing code: {suggestion['existing_code']}")
if get_settings().pr_code_suggestions.commitable_code_suggestions:
suggestion['improved_code'] = "" # we need 'existing_code' to locate the code in the PR
else:
suggestion['existing_code'] = ""
suggestion = self._truncate_if_needed(suggestion)
one_sentence_summary_list.append(suggestion['one_sentence_summary'])
suggestion_list.append(suggestion)
@ -535,9 +574,33 @@ class PRCodeSuggestions:
return True
return False
def remove_line_numbers(self, patches_diff_list: List[str]) -> List[str]:
# create a copy of the patches_diff_list, without line numbers for '__new hunk__' sections
try:
self.patches_diff_list_no_line_numbers = []
for patches_diff in self.patches_diff_list:
patches_diff_lines = patches_diff.splitlines()
for i, line in enumerate(patches_diff_lines):
if line.strip():
if line[0].isdigit():
# find the first letter in the line that starts with a valid letter
for j, char in enumerate(line):
if not char.isdigit():
patches_diff_lines[i] = line[j + 1:]
break
self.patches_diff_list_no_line_numbers.append('\n'.join(patches_diff_lines))
return self.patches_diff_list_no_line_numbers
except Exception as e:
get_logger().error(f"Error removing line numbers from patches_diff_list, error: {e}")
return patches_diff_list
async def _prepare_prediction_extended(self, model: str) -> dict:
self.patches_diff_list = get_pr_multi_diffs(self.git_provider, self.token_handler, model,
max_calls=get_settings().pr_code_suggestions.max_number_of_calls)
# create a copy of the patches_diff_list, without line numbers for '__new hunk__' sections
self.patches_diff_list_no_line_numbers = self.remove_line_numbers(self.patches_diff_list)
if self.patches_diff_list:
get_logger().info(f"Number of PR chunk calls: {len(self.patches_diff_list)}")
get_logger().debug(f"PR diff:", artifact=self.patches_diff_list)
@ -545,12 +608,14 @@ class PRCodeSuggestions:
# parallelize calls to AI:
if get_settings().pr_code_suggestions.parallel_calls:
prediction_list = await asyncio.gather(
*[self._get_prediction(model, patches_diff) for patches_diff in self.patches_diff_list])
*[self._get_prediction(model, patches_diff, patches_diff_no_line_numbers) for
patches_diff, patches_diff_no_line_numbers in
zip(self.patches_diff_list, self.patches_diff_list_no_line_numbers)])
self.prediction_list = prediction_list
else:
prediction_list = []
for i, patches_diff in enumerate(self.patches_diff_list):
prediction = await self._get_prediction(model, patches_diff)
for patches_diff, patches_diff_no_line_numbers in zip(self.patches_diff_list, self.patches_diff_list_no_line_numbers):
prediction = await self._get_prediction(model, patches_diff, patches_diff_no_line_numbers)
prediction_list.append(prediction)
data = {"code_suggestions": []}
@ -559,18 +624,16 @@ class PRCodeSuggestions:
score_threshold = max(1, int(get_settings().pr_code_suggestions.suggestions_score_threshold))
for i, prediction in enumerate(predictions["code_suggestions"]):
try:
if get_settings().pr_code_suggestions.self_reflect_on_suggestions:
score = int(prediction.get("score", 1))
if score >= score_threshold:
data["code_suggestions"].append(prediction)
else:
get_logger().info(
f"Removing suggestions {i} from call {j}, because score is {score}, and score_threshold is {score_threshold}",
artifact=prediction)
else:
score = int(prediction.get("score", 1))
if score >= score_threshold:
data["code_suggestions"].append(prediction)
else:
get_logger().info(
f"Removing suggestions {i} from call {j}, because score is {score}, and score_threshold is {score_threshold}",
artifact=prediction)
except Exception as e:
get_logger().error(f"Error getting PR diff for suggestion {i} in call {j}, error: {e}")
get_logger().error(f"Error getting PR diff for suggestion {i} in call {j}, error: {e}",
artifact={"prediction": prediction})
self.data = data
else:
get_logger().warning(f"Empty PR diff list")
@ -621,7 +684,7 @@ class PRCodeSuggestions:
if get_settings().pr_code_suggestions.final_clip_factor != 1:
max_len = max(
len(data_sorted),
get_settings().pr_code_suggestions.num_code_suggestions_per_chunk,
int(get_settings().pr_code_suggestions.num_code_suggestions_per_chunk),
)
new_len = int(0.5 + max_len * get_settings().pr_code_suggestions.final_clip_factor)
if new_len < len(data_sorted):
@ -654,10 +717,7 @@ class PRCodeSuggestions:
header = f"Suggestion"
delta = 66
header += "&nbsp; " * delta
if get_settings().pr_code_suggestions.self_reflect_on_suggestions:
pr_body += f"""<thead><tr><td>Category</td><td align=left>{header}</td><td align=center>Score</td></tr>"""
else:
pr_body += f"""<thead><tr><td>Category</td><td align=left>{header}</td></tr>"""
pr_body += f"""<thead><tr><td>Category</td><td align=left>{header}</td><td align=center>Score</td></tr>"""
pr_body += """<tbody>"""
suggestions_labels = dict()
# add all suggestions related to each label
@ -668,12 +728,11 @@ class PRCodeSuggestions:
suggestions_labels[label].append(suggestion)
# sort suggestions_labels by the suggestion with the highest score
if get_settings().pr_code_suggestions.self_reflect_on_suggestions:
suggestions_labels = dict(
sorted(suggestions_labels.items(), key=lambda x: max([s['score'] for s in x[1]]), reverse=True))
# sort the suggestions inside each label group by score
for label, suggestions in suggestions_labels.items():
suggestions_labels[label] = sorted(suggestions, key=lambda x: x['score'], reverse=True)
suggestions_labels = dict(
sorted(suggestions_labels.items(), key=lambda x: max([s['score'] for s in x[1]]), reverse=True))
# sort the suggestions inside each label group by score
for label, suggestions in suggestions_labels.items():
suggestions_labels[label] = sorted(suggestions, key=lambda x: x['score'], reverse=True)
counter_suggestions = 0
for label, suggestions in suggestions_labels.items():
@ -732,16 +791,14 @@ class PRCodeSuggestions:
{example_code.rstrip()}
"""
if get_settings().pr_code_suggestions.self_reflect_on_suggestions:
pr_body += f"<details><summary>Suggestion importance[1-10]: {suggestion['score']}</summary>\n\n"
pr_body += f"Why: {suggestion['score_why']}\n\n"
pr_body += f"</details>"
pr_body += f"<details><summary>Suggestion importance[1-10]: {suggestion['score']}</summary>\n\n"
pr_body += f"Why: {suggestion['score_why']}\n\n"
pr_body += f"</details>"
pr_body += f"</details>"
# # add another column for 'score'
if get_settings().pr_code_suggestions.self_reflect_on_suggestions:
pr_body += f"</td><td align=center>{suggestion['score']}\n\n"
pr_body += f"</td><td align=center>{suggestion['score']}\n\n"
pr_body += f"</td></tr>"
counter_suggestions += 1

2
pr_agent/tools/pr_description.py
View File

@ -506,7 +506,7 @@ extra_file_yaml =
pr_body += "</details>\n"
elif 'pr_files' in key.lower() and get_settings().pr_description.enable_semantic_files_types:
changes_walkthrough, pr_file_changes = self.process_pr_files_prediction(changes_walkthrough, value)
changes_walkthrough = f"{PRDescriptionHeader.CHANGES_WALKTHROUGH}\n{changes_walkthrough}"
changes_walkthrough = f"{PRDescriptionHeader.CHANGES_WALKTHROUGH.value}\n{changes_walkthrough}"
else:
# if the value is a list, join its items by comma
if isinstance(value, list):

2
pr_agent/tools/ticket_pr_compliance_check.py
View File

@ -108,7 +108,7 @@ async def extract_tickets(git_provider):
async def extract_and_cache_pr_tickets(git_provider, vars):
if get_settings().get('config.require_ticket_analysis_review', False):
if not get_settings().get('pr_reviewer.require_ticket_analysis_review', False):
return
related_tickets = get_settings().get('related_tickets', [])
if not related_tickets:

9
requirements.txt
View File

@ -1,9 +1,10 @@
aiohttp==3.9.5
anthropic[vertex]==0.37.1
anthropic[vertex]==0.39.0
atlassian-python-api==3.41.4
azure-devops==7.1.0b3
azure-identity==1.15.0
boto3==1.33.6
certifi==2024.8.30
dynaconf==3.2.4
fastapi==0.111.0
GitPython==3.1.41
@ -11,17 +12,17 @@ google-cloud-aiplatform==1.38.0
google-generativeai==0.8.3
google-cloud-storage==2.10.0
Jinja2==3.1.2
litellm==1.50.2
litellm==1.52.0
loguru==0.7.2
msrest==0.7.1
openai==1.52.1
openai==1.54.1
pytest==7.4.0
PyGithub==1.59.*
PyYAML==6.0.1
python-gitlab==3.15.0
retry==0.9.2
starlette-context==0.3.6
tiktoken==0.7.0
tiktoken==0.8.0
ujson==5.8.0
uvicorn==0.22.0
tenacity==8.2.3