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74 lines
3.9 KiB
Markdown
74 lines
3.9 KiB
Markdown
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# PR-Agent — Quick Capabilities Summary
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**Overview:**
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- PR-Agent is a CLI and integration tool that automates pull request (PR) review tasks using LLMs. It provides automated PR reviews, descriptions, code suggestions, documentation helpers, and related workflows for multiple Git providers.
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**Core Capabilities:**
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- **/review (PR review):** Generate a reviewer-style audit of a PR including security, tests, effort, and best-practice suggestions.
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- **/describe (PR description):** Produce a clear PR description and changelog updates from the diff and user notes.
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- **/improve (Code suggestions):** Suggest code improvements, refactorings, and non-functional improvements (style, tests, docs).
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- **/add_docs (Docs generation):** Create or update documentation for changed code or new APIs.
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- **/custom_prompt:** Run a custom prompt against the PR context.
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- **/ask (Interactive questions):** Ask follow-up questions about a PR and receive focused answers.
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- **CLI:** `pr-agent` command-line tool to run review/describe/improve locally or in CI.
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- **GitHub Actions & App:** Integrations for automated runs in workflows and as a GitHub App.
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**Integration / Providers:**
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- **Git providers:** GitHub, GitLab, Gitea, Bitbucket, Bitbucket Server, Gerrit, local git.
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- **LLM Providers via LiteLLM:** OpenAI-compatible endpoints (including Blackbox.ai via `OPENAI_API_BASE`), Anthropic, Cohere, HuggingFace, and others supported by LiteLLM. Configuration uses provider-prefixed model strings (e.g., `openai/gpt-4o`).
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- **Secret providers:** AWS Secrets Manager and Google Cloud Storage secret provider are supported for secure secret management.
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**Configuration & Secrets:**
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- Settings are managed with `dynaconf` and loaded from `pr_agent/settings/*` and optional repository-level `pyproject.toml` under `tool.pr-agent`.
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- Local secret file: `pr_agent/settings/.secrets.toml` (DO NOT commit real tokens). The template is `pr_agent/settings/.secrets_template.toml`.
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- Key settings:
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- `openai.key` and `openai.api_base` for OpenAI-compatible endpoints.
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- `config.model` controls default model (use provider-prefixed strings LiteLLM expects).
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**Extensibility:**
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- The codebase provides modular AI handler layers (`algo/ai_handlers`) so new providers/adapters can be added.
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- Token handling and patch generation are pluggable to tune prompt size and chunking.
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**Development / Quick Start:**
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- Create a Python virtualenv and install:
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```bash
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python3 -m venv .venv
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source .venv/bin/activate
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pip install -e .
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```
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- Provide secrets locally in `pr_agent/settings/.secrets.toml` or export env vars (preferred for CI):
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```bash
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export OPENAI_API_KEY="<YOUR_KEY>"
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export OPENAI_API_BASE="https://api.blackbox.ai" # if using Blackbox
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```
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- Example local run (review):
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```bash
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python cli.py --pr_url="https://github.com/<org>/<repo>/pull/123" review
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```
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**Security & Best Practices:**
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- Never commit API keys or `.secrets.toml` to version control.
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- If secrets are accidentally pushed, rotate and remove from history (BFG or git filter-repo) immediately.
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- Use a secrets manager for CI and production deployments.
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**Where to get help / docs:**
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- Project docs are under `docs/` and `pr_agent/settings/*.toml` contain configuration docs and prompts.
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- For LiteLLM provider formats, see: https://docs.litellm.ai/docs/providers
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**Files of interest:**
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- `pr_agent/cli.py` — CLI entrypoint.
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- `pr_agent/config_loader.py` — dynaconf initialization and settings loading.
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- `pr_agent/settings/` — configuration and prompt files.
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- `pr_agent/algo/` — core logic: token handling, prompt preparation, AI handlers.
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- `pr_agent/git_providers/` — adapters for Git hosting providers.
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If you want, I can:
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- Add this content into the main `README.md` replacing or merging with the existing one.
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- Generate a one-page `CONTRIBUTING` snippet for local development and secret handling.
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- Commit the new README file and create a small PR with the change.
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