pr-agent/Usage.md

## Usage Guide

### Table of Contents
- [Introduction](#introduction)
- [Working from a local repo (CLI)](#working-from-a-local-repo-cli)
- [Online usage](#online-usage)
- [Working with GitHub App](#working-with-github-app)
- [Working with GitHub Action](#working-with-github-action)
- [Changing a model](#changing-a-model)
- [Working with large PRs](#working-with-large-prs)
- [Appendix - additional configurations walkthrough](#appendix---additional-configurations-walkthrough)

### Introduction

See the **[installation guide](/INSTALL.md)** for instructions on how to setup PR-Agent. After installation, there are three basic ways to invoke CodiumAI PR-Agent:
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 PR-Agent tools to run automatically when a new PR is opened


Specifically, CLI commands can be issued by invoking a pre-built [docker image](/INSTALL.md#running-from-source), or by invoking a [locally cloned repo](INSTALL.md#method-2-run-from-source).
For online usage, you will need to setup either a [GitHub App](INSTALL.md#method-5-run-as-a-github-app), or a [GitHub Action](INSTALL.md#method-3-run-as-a-github-action).
GitHub App and GitHub Action also enable to run PR-Agent specific tool automatically when a new PR is opened.


#### The configuration file
The different tools and sub-tools used by CodiumAI PR-Agent are adjustable via the **[configuration file](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](/pr_agent/settings/configuration.toml#L16) section in the configuration file.

The [Tools Guide](./docs/TOOLS_GUIDE.md) provides a detailed description of the different tools and their configurations.

#### git provider
The [git_provider](pr_agent/settings/configuration.toml#L4) field in the configuration file determines the GIT provider that will be used by PR-Agent. Currently, the following providers are supported:
`
"github", "gitlab", "azure", "codecommit", "local", "gerrit"
`

[//]: # (** online usage:**)

[//]: # (Options that are available in the configuration file can be specified at run time when calling actions. Two examples:)

[//]: # (```)

[//]: # (- /review --pr_reviewer.extra_instructions="focus on the file: ...")

[//]: # (- /describe --pr_description.add_original_user_description=false -pr_description.extra_instructions="make sure to mention: ...")

[//]: # (```)

### Working from a local repo (CLI)
When running from your local repo (CLI), your local configuration file will be used.
Examples for 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: 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=true
verbosity_level=2
```
This is useful for debugging or experimenting with the different tools.


### Online usage

Online usage means invoking PR-Agent 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`
- **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](pr_agent/settings/configuration.toml) file can be similarly edited. comment `/config` to see the list of available configurations.


### Working with GitHub App
When running PR-Agent from [GitHub App](INSTALL.md#method-5-run-as-a-github-app), the default configurations from a pre-built docker will be initially loaded.

#### GitHub app automatic tools
The [github_app](pr_agent/settings/configuration.toml#L56) section defines GitHub app specific configurations. 
An important parameter is `pr_commands`, which is a list of tools that will be **run automatically** when a new PR is opened:
```
[github_app]
pr_commands = [
    "/describe --pr_description.add_original_user_description=true --pr_description.keep_original_user_title=true",
    "/auto_review",
]
```
This means that when a new PR is opened, PR-Agent will run the `describe` and `auto_review` tools.
For the describe tool, the `add_original_user_description` and `keep_original_user_title` parameters will be set to true.

You can override the default tool parameters by uploading a local configuration file called `.pr_agent.toml` to the root of your repo.
For example, if your local `.pr_agent.toml` file contains:
```
[pr_description]
add_original_user_description = false
keep_original_user_title = false
```
When a new PR is opened, PR-Agent will run the `describe` tool with the above parameters.

Note that a local `.pr_agent.toml` file enables you to edit and customize the default parameters of any tool, not just the ones that are run automatically.

#### Editing the prompts
The prompts for the various PR-Agent 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](./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](./pr_agent/tools/pr_description.py#L137).

### Working with GitHub Action
You can configure settings in GitHub action by adding environment variables under the env section in `.github/workflows/pr_agent.yml` 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
        github_action.auto_review: "true" # Enable auto review
        github_action.auto_describe: "true" # Enable auto describe
        github_action.auto_improve: "false" # Disable auto improve      
```
specifically, `github_action.auto_review`, `github_action.auto_describe` and `github_action.auto_improve` are used to enable/disable automatic tools that run when a new PR is opened.

If not set, the default option is that only the `review` tool will run automatically when a new PR is opened.

### Changing a model

See [here](pr_agent/algo/__init__.py) for the list of available models.
To use a different model than the default (GPT-4), you need to edit [configuration file](pr_agent/settings/configuration.toml#L2).
For models and environments not from OPENAI, you might need to provide additional keys and other parameters. See below for instructions.

#### Azure
To use Azure, set in your .secrets.toml: 
```
api_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 
```
[config]
model="" # the OpenAI model you've deployed on Azure (e.g. gpt-3.5-turbo)
```
in the configuration.toml 

#### Huggingface

**Local**  
You can run Huggingface 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 Huggingface model locally via Ollama, set:
```
[__init__.py]
MAX_TOKENS = {
    "model-name-on-ollama": <max_tokens>
}
e.g.
MAX_TOKENS={
    ...,
    "llama2": 4096
}


[config] # in configuration.toml
model = "ollama/llama2"

[ollama] # in .secrets.toml
api_base = ... # the base url for your huggingface inference endpoint 
```

**Inference Endpoints**

To use a new model with Huggingface 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"

[huggingface] # in .secrets.toml
key = ... # your huggingface api key
api_base = ... # the base url for your huggingface 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"
[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](pr_agent/algo/ai_handler.py) file for instruction how to set keys for other models.

### 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 provide 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](./PR_COMPRESSION.md).

However, for very large PRs, or in case you want to emphasize quality over speed and cost, there are 2 possible solutions:
1) [Use a model](#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](./docs/IMPROVE.md) (`/improve --extended`), 
which divides the PR to chunks, and process each chunk separately. With this mode, regardless of the model, no compression will be done (but for large PRs, multiple model calls may occur)

### Appendix - additional configurations walkthrough


#### Extra instructions
All PR-Agent 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 ..."
```

#### Patch Extra Lines
By default, around any change in your PR, git patch provides 3 lines of context above and below the change.
For the `review`, `describe`, `ask` and `add_docs` tools, if the token budget allows, PR-Agent tries to increase the number of lines of context, via the parameter:
```
[config]
patch_extra_lines=3
```
Increasing this number provides more context to the model, but will also increase the token budget.
If the PR is too large (see [PR Compression strategy](./PR_COMPRESSION.md)), we automatically set this number to 0 


#### Azure DevOps provider
To use Azure DevOps provider use the following settings in configuration.toml:
```
[config]
git_provider="azure"
use_repo_settings_file=false
```

And use the following settings (you have to replace the values) in .secrets.toml:
```
[azure_devops]
org = "https://dev.azure.com/YOUR_ORGANIZATION/"
pat = "YOUR_PAT_TOKEN"
```