# OpenRabbit

Enterprise-grade AI code review system for **Gitea** with automated PR review, issue triage, interactive chat, and codebase analysis.

---

## Features

| Feature | Description |
|---------|-------------|
| **PR Review** | Inline comments, security scanning, severity-based CI failure |
| **PR Summaries** | Auto-generate comprehensive PR summaries with change analysis and impact assessment |
| **Issue Triage** | On-demand classification, labeling, priority assignment via `@codebot triage` |
| **Chat** | Interactive AI chat with codebase search and web search tools |
| **@codebot Commands** | `@codebot summarize`, `changelog`, `explain`, `suggest`, `triage`, `review-again` in comments |
| **Codebase Analysis** | Health scores, tech debt tracking, weekly reports |
| **Security Scanner** | 17 OWASP-aligned rules for vulnerability detection |
| **Enterprise Ready** | Audit logging, metrics, Prometheus export |
| **Gitea Native** | Built for Gitea workflows and API |

---

## Quick Start

### 1. Set Repository/Organization Secrets

```
OPENAI_API_KEY      - OpenAI API key (or use OpenRouter/Ollama)
SEARXNG_URL         - (Optional) SearXNG instance URL for web search
```

**For Gitea:**
```
AI_REVIEW_TOKEN     - Bot token with repo + issue permissions
```

**For GitHub:**
The built-in `GITHUB_TOKEN` is used automatically.

### 2. Add Workflows to Repository

Workflows are located in `.gitea/workflows/`.

#### Gitea Example

#### Gitea PR Review Workflow

```yaml
# .gitea/workflows/enterprise-ai-review.yml
name: AI PR Review
on: [pull_request]

jobs:
  ai-review:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
        with:
          fetch-depth: 0

      - uses: actions/checkout@v4
        with:
          repository: YourOrg/OpenRabbit
          path: .ai-review
          token: ${{ secrets.AI_REVIEW_TOKEN }}

      - uses: actions/setup-python@v5
        with:
          python-version: "3.11"

      - run: pip install requests pyyaml

      - name: Run AI Review
        env:
          AI_REVIEW_TOKEN: ${{ secrets.AI_REVIEW_TOKEN }}
          AI_REVIEW_REPO: ${{ gitea.repository }}
          AI_REVIEW_API_URL: https://your-gitea.example.com/api/v1
          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
        run: |
          cd .ai-review/tools/ai-review
          python main.py pr ${{ gitea.repository }} ${{ gitea.event.pull_request.number }}
```

See `.gitea/workflows/` for all workflow examples.

### 3. Create Labels (Automatic Setup)

**Option A: Automatic Setup (Recommended)**

Create an issue and comment:
```
@codebot setup-labels
```

The bot will automatically:
- Detect your existing label schema (e.g., `Kind/Bug`, `Priority - High`)
- Map existing labels to OpenRabbit's auto-labeling system
- Create only the missing labels you need
- Follow your repository's naming convention

**Option B: Manual Setup**

Create these labels in your repository for auto-labeling:
- `priority: critical`, `priority: high`, `priority: medium`, `priority: low`
- `type: bug`, `type: feature`, `type: question`, `type: documentation`
- `ai-approved`, `ai-changes-required`, `ai-reviewed`

---

## Project Structure

```
tools/ai-review/
├── agents/                 # Agent implementations
│   ├── base_agent.py       # Abstract base agent
│   ├── issue_agent.py      # Issue triage & @codebot commands
│   ├── pr_agent.py         # PR review with security scan
│   ├── codebase_agent.py   # Codebase health analysis
│   └── chat_agent.py       # Interactive chat with tool calling
├── clients/                # API clients
│   ├── gitea_client.py     # Gitea REST API wrapper
│   └── llm_client.py       # Multi-provider LLM client with tool support
├── security/               # Security scanning
│   └── security_scanner.py # 17 OWASP-aligned rules
├── enterprise/             # Enterprise features
│   ├── audit_logger.py     # JSONL audit logging
│   └── metrics.py          # Prometheus-compatible metrics
├── prompts/                # AI prompt templates
├── main.py                 # CLI entry point
└── config.yml              # Configuration

.github/workflows/          # GitHub Actions workflows
├── ai-review.yml           # PR review workflow
├── ai-issue-triage.yml     # Issue triage workflow
├── ai-codebase-review.yml  # Codebase analysis
├── ai-comment-reply.yml    # @codebot command responses
└── ai-chat.yml             # Interactive AI chat

.gitea/workflows/           # Gitea Actions workflows
├── enterprise-ai-review.yml
├── ai-issue-triage.yml
├── ai-codebase-review.yml
├── ai-comment-reply.yml
└── ai-chat.yml
```

---

## CLI Commands

```bash
# Review a pull request
python main.py pr owner/repo 123

# Triage an issue
python main.py issue owner/repo 456

# Respond to @codebot command
python main.py comment owner/repo 456 "@codebot explain"

# Analyze codebase
python main.py codebase owner/repo

# Chat with the AI bot
python main.py chat owner/repo "How does authentication work?"
python main.py chat owner/repo "Find all API endpoints" --issue 789
```

---

## @codebot Commands

### Issue Commands

In any issue comment:

| Command | Description |
|---------|-------------|
| `@codebot help` | **Help:** Show all available commands with examples |
| `@codebot setup-labels` | **Setup:** Automatically create/map repository labels for auto-labeling |
| `@codebot triage` | Full issue triage with auto-labeling and analysis |
| `@codebot summarize` | Summarize the issue in 2-3 sentences |
| `@codebot explain` | Explain what the issue is about |
| `@codebot suggest` | Suggest solutions or next steps |
| `@codebot` (any question) | Chat with AI using codebase/web search tools |

### Pull Request Commands

In any PR comment:

| Command | Description |
|---------|-------------|
| `@codebot summarize` | Generate a comprehensive PR summary with changes, files affected, and impact |
| `@codebot changelog` | Generate Keep a Changelog format entries ready for CHANGELOG.md |
| `@codebot review-again` | Re-run AI code review on current PR state without new commits |

#### PR Summary (`@codebot summarize`)

**Features:**
- 📋 Generates structured summary of PR changes
- ✨ Categorizes change type (Feature/Bugfix/Refactor/Documentation/Testing)
- 📝 Lists what was added, modified, and removed
- 📁 Shows all affected files with descriptions
- 🎯 Assesses impact scope (small/medium/large)
- 🤖 Automatically generates on PRs with empty descriptions

**When to use:**
- When a PR lacks a description
- To quickly understand what changed
- For standardized PR documentation
- Before reviewing complex PRs

**Example output:**
```markdown
## 📋 Pull Request Summary
This PR implements automatic PR summary generation...

**Type:** ✨ Feature

## Changes
✅ Added:
- PR summary generation in PRAgent
- Auto-summary for empty PR descriptions

📝 Modified:
- Updated config.yml with new settings

## Files Affected
- ➕ `tools/ai-review/prompts/pr_summary.md` - New prompt template
- 📝 `tools/ai-review/agents/pr_agent.py` - Added summary methods

## Impact
🟡 **Scope:** Medium
Adds new feature without affecting existing functionality
```

#### Changelog Generator (`@codebot changelog`)

**Features:**
- 📋 Generates Keep a Changelog format entries
- 🏷️ Categorizes changes (Added/Changed/Fixed/Removed/Security)
- ⚠️ Detects breaking changes automatically
- 📊 Includes technical details (files, LOC, components)
- 📝 Ready to copy-paste into CHANGELOG.md

**When to use:**
- Preparing release notes
- Maintaining CHANGELOG.md
- Customer-facing announcements
- Version documentation

**Example output:**
```markdown
## 📋 Changelog for PR #123

### ✨ Added
- User authentication system with JWT tokens
- Password reset functionality via email

### 🔄 Changed
- Updated database schema for user table
- Refactored login endpoint for better error handling

### 🐛 Fixed
- Session timeout bug causing premature logouts
- Security vulnerability in password validation

### 🔒 Security
- Fixed XSS vulnerability in user input validation

---

### ⚠️ BREAKING CHANGES
- **Removed legacy API endpoint /api/v1/old - migrate to /api/v2**

---

### 📊 Technical Details
- **Files changed:** 15
- **Lines:** +450 / -120
- **Main components:** auth/, api/users/, database/
```

#### Review Again (`@codebot review-again`)

**Features:**
- ✅ Shows diff from previous review (resolved/new/changed issues)
- 🏷️ Updates labels based on new severity
- ⚡ No need for empty commits to trigger review
- 🔧 Respects latest `.ai-review.yml` configuration

**When to use:**
- After addressing review feedback in comments
- When AI flagged a false positive and you explained it
- After updating `.ai-review.yml` security rules
- To re-evaluate severity after code clarification

**Example:**
```
The hardcoded string at line 45 is a public API URL, not a secret.
@codebot review-again
```

**New to OpenRabbit?** Just type `@codebot help` in any issue to see all available commands!

### Label Setup Command

The `@codebot setup-labels` command intelligently detects your existing label schema and sets up auto-labeling:

**For repositories with existing labels (e.g., `Kind/Bug`, `Priority - High`):**
- Detects your naming pattern (prefix/slash, prefix-dash, or colon-style)
- Maps your existing labels to OpenRabbit's schema
- Creates only missing labels following your pattern
- Zero duplicate labels created

**For fresh repositories:**
- Creates OpenRabbit's default label set
- Uses `type:`, `priority:`, and status labels

**Example output:**
```
@codebot setup-labels

✅ Found 18 existing labels with pattern: prefix_slash

Detected Categories:
- Kind (7 labels): Bug, Feature, Documentation, Security, Testing
- Priority (4 labels): Critical, High, Medium, Low

Proposed Mapping:
| OpenRabbit Expected | Your Existing Label | Status |
|---------------------|---------------------|--------|
| type: bug          | Kind/Bug            | ✅ Map |
| priority: high     | Priority - High     | ✅ Map |
| ai-reviewed        | (missing)           | ⚠️ Create |

✅ Created Kind/Question (#cc317c)
✅ Created Status - AI Reviewed (#1d76db)

Setup Complete! Auto-labeling will use your existing label schema.
```

---

## Interactive Chat

The chat agent is an interactive AI assistant with tool-calling capabilities:

**Tools Available:**
- `search_codebase` - Search repository files and code
- `read_file` - Read specific files
- `search_web` - Search the web via SearXNG

**Example:**
```
@codebot How do I configure rate limiting in this project?
```

The bot will search the codebase, read relevant files, and provide a comprehensive answer.

---

## Configuration

Edit `tools/ai-review/config.yml`:

```yaml
provider: openai   # openai | openrouter | ollama

model:
  openai: gpt-4.1-mini
  openrouter: anthropic/claude-3.5-sonnet
  ollama: codellama:13b

agents:
  issue:
    enabled: true
    auto_label: true
  pr:
    enabled: true
    inline_comments: true
    security_scan: true
  codebase:
    enabled: true
  chat:
    enabled: true
    searxng_url: ""  # Or set SEARXNG_URL env var

interaction:
  respond_to_mentions: true
  mention_prefix: "@codebot"  # Customize your bot name here!
  commands:
    - summarize
    - explain
    - suggest
```

---

## Customizing the Bot Name

The default bot name is `@codebot`. To change it:

**Step 1:** Edit `tools/ai-review/config.yml`:
```yaml
interaction:
  mention_prefix: "@yourname"  # e.g., "@assistant", "@reviewer", etc.
```

**Step 2:** Update all workflow files in `.gitea/workflows/`:
- `ai-comment-reply.yml`
- `ai-chat.yml`
- `ai-issue-triage.yml`

Look for and update:
```yaml
if: contains(github.event.comment.body, '@codebot')
```

Change `@codebot` to your new bot name.

---

## Security Scanning

17 rules covering OWASP Top 10:

| Category | Examples |
|----------|----------|
| Injection | SQL injection, command injection, XSS |
| Access Control | Hardcoded secrets, private keys |
| Crypto Failures | Weak hashing (MD5/SHA1), insecure random |
| Misconfiguration | Debug mode, CORS wildcard, SSL bypass |

---

## Documentation

| Document | Description |
|----------|-------------|
| [Getting Started](docs/getting-started.md) | Quick setup guide |
| [Configuration](docs/configuration.md) | All options explained |
| [Agents](docs/agents.md) | Agent documentation |
| [Security](docs/security.md) | Security rules reference |
| [Workflows](docs/workflows.md) | GitHub & Gitea workflow examples |
| [API Reference](docs/api-reference.md) | Client and agent APIs |
| [Enterprise](docs/enterprise.md) | Audit logging, metrics |
| [Troubleshooting](docs/troubleshooting.md) | Common issues |

---

## LLM Providers

| Provider | Model | Use Case |
|----------|-------|----------|
| OpenAI | gpt-4.1-mini | Fast, reliable |
| OpenRouter | claude-3.5-sonnet | Multi-provider access |
| Ollama | codellama:13b | Self-hosted, private |

---

## Enterprise Features

- **Audit Logging**: JSONL logs with daily rotation
- **Metrics**: Prometheus-compatible export
- **Rate Limiting**: Configurable request limits
- **Custom Security Rules**: Define your own patterns via YAML
- **Tool Calling**: LLM function calling for interactive chat

---

## License

MIT