Commit Graph
3 Commits
Author SHA1 Message Date
saidsurucuandClaude Opus 4.7 42731a2c03 feat(semantic_search): make embedding model configurable (#22)
google/gemini-embedding-001 became paid on OpenRouter, leaving
users without credit unable to run the semantic_search tool. The
old code hardcoded the model and 3072 dimensions in three places.

Make OpenRouterEmbedder accept model/dimension via constructor
args or OPENROUTER_EMBEDDING_MODEL / OPENROUTER_EMBEDDING_DIMENSION
env vars, with the previous values as backward-compatible defaults.
Switch the VectorStore and the response payload in mcp_server_main
to read embedder.dimension instead of the hardcoded 3072 so a
configured non-Gemini model does not produce shape mismatches.

Bad dimension input (non-int or non-positive) now raises a clear
ValueError instead of a downstream shape error.

Documented the new env vars in .env.example.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-03 01:46:33 +03:00
saidsurucu 77e2748ade feat(semantic-search): Replace local embedding model with OpenRouter API
- Replace EmbeddingGemma local model with OpenRouter API integration
- Use google/gemini-embedding-001 model via OpenRouter (3072 dimensions)
- Add conditional tool registration: auto-disable if OPENROUTER_API_KEY not set
- Add openai and numpy dependencies to pyproject.toml
- Update .env.example with OPENROUTER_API_KEY configuration
- Fix ruff lint issues in semantic_search module
2025-12-13 18:33:47 +03:00
saidsurucuandClaude e771c5b3c5 feat: Add semantic search module
Add semantic search capabilities with:
- embedder.py: Text embedding operations
- processor.py: Document processing
- vector_store.py: Vector storage and retrieval

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-13 17:15:12 +03:00