Add a named OrcaRouterEmbedder mirroring the existing OpenRouterEmbedder:
a production AI gateway that proxies 200+ models on one OpenAI-compatible
endpoint (https://api.orcarouter.ai/v1). Selecting it is a one-line switch:
set ORCAROUTER_API_KEY instead of OPENROUTER_API_KEY.
- get_embedder() prefers OrcaRouter when ORCAROUTER_API_KEY is present
- is_semantic_search_available() now also enables on OrcaRouter keys
- document the new option in README (Alternatif 3) and .env.example
Co-Authored-By: Claude <noreply@anthropic.com>
Signed-off-by: jinhao.song <jinhao.song@myflashcloud.com>
Adds a LocalEmbedder that targets any OpenAI-compatible embedding
endpoint (Ollama, llama.cpp, vLLM, LM Studio, ...). Zero new
Python dependencies — reuses the existing openai SDK with a
custom base_url. Defaults to Ollama at http://localhost:11434/v1
with nomic-embed-text @ 768 dims; override via env vars for other
servers/models (e.g. bge-m3 @ 1024 dims for better Turkish).
Refactors the shared encode/similarity logic into a private base
class so OpenRouterEmbedder and LocalEmbedder don't duplicate ~50
lines. OpenRouter keeps its ranking headers; local sends none.
Adds get_embedder() factory selecting the provider based on
EMBEDDING_PROVIDER (local) or OPENROUTER_API_KEY presence, and
is_semantic_search_available() that returns True for either path.
mcp_server_main now uses these so the semantic_search tool is
exposed when only a local server is configured.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
- 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
