alex
69d3acda5d
- Add LLM client abstraction (src/llm-client.ts) with factory pattern - Add OpenAI-compatible external client (src/external-llm-client.ts) - Add Kimi.com client using Anthropic-based API (src/kimi-llm-client.ts) - Add Pi native LLM stub (src/pi-llm-client.ts) for future ExtensionAPI wiring - Add SHA-256 disk cache at ~/.cache/pi-project-map/ (src/llm-cache.ts) - Add parallel batching with p-limit, retry + exponential backoff (src/llm-batch.ts) - Rewrite llm-extract.ts to use real LLM calls with structured prompts - File-level: PURPOSE, DEPS, CONCEPTS - Package-level: ROLE, ARCH - Context truncation, 50KB skip, cache before LLM call - Wire CLI with --llm-provider, --llm-model, --llm-base-url flags - Update config.ts with llmProvider, llmBaseUrl fields - Update init.ts and patch.ts to accept optional LLMClient - Add sample project fixture for manual testing - Add tests: llm-cache (3), llm-batch (5), llm-integration (8 with real Kimi API), pi-extension (14 mocked) - All 56 tests pass
pi-project-map
Pi skill for hierarchical project analysis.
What it does
Generates .pi-map.md files throughout your project — one per directory — containing a dense, machine-readable summary of that directory's files, exports, dependencies, and architecture. This gives Pi agents instant project comprehension without reading every source file.
Quick Start
npm install -g pi-project-map
project-map init
Design
See design-doc.md for the full specification.
Implementation Plan
See implementation-plan.md for the engineering roadmap.