feat: M7 proper LLM integration with dual providers, caching, and parallel batching

- 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

package.json

@@ -42,6 +42,8 @@
   },
   "dependencies": {
     "ignore": "^5.3.0",
+    "openai": "^6.42.0",
+    "p-limit": "^7.3.0",
     "picocolors": "^1.1.1",
     "tree-sitter": "^0.21.0",
     "tree-sitter-go": "^0.25.0",