Jason Woltje
a5416e4a66
Updated pnpm version from 10.19.0 to 10.27.0 to fix HIGH severity vulnerabilities (CVE-2025-69262, CVE-2025-69263, CVE-2025-6926). Changes: - apps/api/Dockerfile: line 8 - apps/web/Dockerfile: lines 8 and 81 Fixes #180
110 lines
3.2 KiB
Markdown
110 lines
3.2 KiB
Markdown
# Issue #158: Implement issue parser agent
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## Objective
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Create an AI agent using Anthropic's Sonnet model that parses Gitea issue markdown bodies to extract structured metadata for autonomous task coordination.
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## Approach
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### 1. Dependencies
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- Add `anthropic` package to pyproject.toml
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- Add `ANTHROPIC_API_KEY` to config.py
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### 2. Data Models (src/models.py)
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- `IssueMetadata`: Pydantic model for parsed metadata
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- `estimated_context`: int (tokens)
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- `difficulty`: str (easy/medium/hard)
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- `assigned_agent`: str (sonnet/haiku/opus/glm)
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- `blocks`: list[int] (issue numbers this blocks)
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- `blocked_by`: list[int] (issue numbers blocking this)
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### 3. Parser Agent (src/parser.py)
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- `parse_issue_metadata(issue_body: str, issue_number: int) -> IssueMetadata`
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- Uses Anthropic API with claude-sonnet-4.5 model
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- Structured JSON extraction via prompt
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- Cache results using simple in-memory dict (issue_number -> metadata)
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- Graceful fallback to defaults on parse failure
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### 4. Integration
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- Update `webhook.py` to call parser in `handle_assigned_event()`
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- Log parsed metadata
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## Progress
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- [x] Create scratchpad
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- [x] Update pyproject.toml with anthropic dependency
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- [x] Create models.py with IssueMetadata (TEST FIRST)
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- [x] Create parser.py with parse function (TEST FIRST)
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- [x] Update config.py with ANTHROPIC_API_KEY
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- [x] Write comprehensive tests (9 test cases)
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- [x] Run quality gates (mypy, ruff, pytest)
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- [x] Verify 95% coverage (exceeds 85% requirement)
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- [x] Create .env.example
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- [x] Update README.md
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- [x] All quality gates pass
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- [x] Commit changes
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## Testing
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### Unit Tests (test_parser.py)
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- Test parsing complete issue body → valid metadata
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- Test parsing minimal issue body → defaults used
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- Test parsing malformed markdown → graceful failure
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- Test caching (same issue parsed twice = 1 API call)
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- Test different difficulty levels
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- Test blocks/blocked_by extraction
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- Mock Anthropic API for unit tests
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- Integration test with real API (optional, can be skipped if no key)
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### Test Cases
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1. **Complete issue body** - All fields present
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2. **Minimal issue body** - Only required fields
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3. **Missing Context Estimate** - Default to reasonable value
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4. **Missing Difficulty** - Default to "medium"
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5. **Missing Agent** - Default to "sonnet"
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6. **Malformed blocks/blocked_by** - Empty lists
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7. **API failure** - Return defaults with error logged
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8. **Cache hit** - Second parse returns cached result
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## Notes
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### Default Values
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- estimated_context: 50000 (reasonable default for medium issues)
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- difficulty: "medium"
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- assigned_agent: "sonnet"
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- blocks: []
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- blocked_by: []
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### Prompt Strategy
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Use structured output with clear instructions to extract from markdown sections:
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- "Context Estimate" section → estimated_context
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- "Difficulty" section → difficulty
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- "Dependencies" section → blocks, blocked_by
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### Performance Target
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- Average parse time < 2 seconds
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- Cache to avoid redundant API calls
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- Log token usage for cost tracking
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### API Integration
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- Use `anthropic.Anthropic()` client
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- Model: `claude-sonnet-4.5-20250929`
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- Max tokens: 1024 (responses are small)
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- Temperature: 0 (deterministic parsing)
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## Token Tracking
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- Estimated: 46,800 tokens
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- Actual: TBD after implementation
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