saidsurucuandClaude Opus 4.7
fb29146755
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>
24 lines
525 B
Python
24 lines
525 B
Python
# semantic_search/__init__.py
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from .embedder import (
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OpenRouterEmbedder,
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LocalEmbedder,
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get_embedder,
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is_openrouter_available,
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is_local_embedding_configured,
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is_semantic_search_available,
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)
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from .vector_store import VectorStore
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from .processor import DocumentProcessor
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__all__ = [
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'OpenRouterEmbedder',
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'LocalEmbedder',
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'get_embedder',
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'is_openrouter_available',
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'is_local_embedding_configured',
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'is_semantic_search_available',
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'VectorStore',
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'DocumentProcessor',
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]
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