Chris Coutinho
5b484c9226
Refactored LLM provider infrastructure to support sustainable additions of new providers with both embedding and text generation capabilities.
## Major Changes
### Unified Provider Architecture (ADR-015)
- Created `nextcloud_mcp_server/providers/` with unified Provider ABC
- Providers now support optional capabilities (embeddings and/or generation)
- Auto-detection registry with priority: Bedrock → Ollama → Simple
- Backward compatible - existing code continues to work
### New Providers
- **BedrockProvider**: Full Amazon Bedrock integration
- Embeddings: Titan Embed, Cohere Embed models
- Generation: Claude, Llama, Titan Text, Mistral models
- Model-specific request/response handling
- AWS credential chain integration
- **OllamaProvider**: Migrated with both capabilities support
- **AnthropicProvider**: Moved from test code to production providers
- **SimpleProvider**: Migrated in-memory fallback provider
### Breaking Changes
None - full backward compatibility maintained:
- `embedding.get_embedding_service()` still works
- RAG evaluation tests updated to use unified providers
- All existing tests pass (127 unit tests)
### Testing
- Added 9 comprehensive Bedrock unit tests with mocked boto3
- All existing unit tests pass
- Type checking (ty) and linting (ruff) pass
- Verified backward compatibility
### Documentation
- `docs/ADR-015-unified-provider-architecture.md`: Comprehensive ADR
- `docs/bedrock-setup.md`: AWS setup guide with IAM permissions
- `CLAUDE.md`: Updated with provider architecture section
### Dependencies
- Added `boto3>=1.35.0` to dev dependencies (optional)
## Environment Variables
### Bedrock
- `AWS_REGION`: AWS region (e.g., "us-east-1")
- `BEDROCK_EMBEDDING_MODEL`: Model ID for embeddings
- `BEDROCK_GENERATION_MODEL`: Model ID for generation
- `AWS_ACCESS_KEY_ID`, `AWS_SECRET_ACCESS_KEY`: Optional credentials
### Ollama
- `OLLAMA_BASE_URL`: API URL
- `OLLAMA_EMBEDDING_MODEL`: Embedding model (default: "nomic-embed-text")
- `OLLAMA_GENERATION_MODEL`: Generation model
## AWS Bedrock Permissions Required
Minimal IAM policy:
```json
{
"Effect": "Allow",
"Action": ["bedrock:InvokeModel"],
"Resource": ["arn:aws:bedrock:*::foundation-model/*"]
}
```
See `docs/bedrock-setup.md` for detailed setup instructions.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
103 lines
2.6 KiB
Python
103 lines
2.6 KiB
Python
"""Embedding service with provider detection.
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DEPRECATED: This module is maintained for backward compatibility.
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New code should use nextcloud_mcp_server.providers.get_provider() directly.
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"""
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import logging
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from nextcloud_mcp_server.providers import get_provider
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from .bm25_provider import BM25SparseEmbeddingProvider
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logger = logging.getLogger(__name__)
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class EmbeddingService:
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"""
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Unified embedding service with automatic provider detection.
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DEPRECATED: This class wraps the new unified provider infrastructure
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for backward compatibility. New code should use
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nextcloud_mcp_server.providers.get_provider() directly.
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"""
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def __init__(self):
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"""Initialize embedding service with auto-detected provider."""
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self.provider = get_provider()
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async def embed(self, text: str) -> list[float]:
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"""
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Generate embedding vector for text.
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Args:
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text: Input text to embed
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Returns:
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Vector embedding as list of floats
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"""
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return await self.provider.embed(text)
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async def embed_batch(self, texts: list[str]) -> list[list[float]]:
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"""
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Generate embeddings for multiple texts.
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Args:
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texts: List of texts to embed
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Returns:
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List of vector embeddings
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"""
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return await self.provider.embed_batch(texts)
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def get_dimension(self) -> int:
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"""
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Get embedding dimension.
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Returns:
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Vector dimension
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"""
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return self.provider.get_dimension()
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async def close(self):
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"""Close provider resources."""
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if hasattr(self.provider, "close") and callable(
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getattr(self.provider, "close")
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):
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close_method = getattr(self.provider, "close")
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await close_method()
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# Singleton instance
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_embedding_service: EmbeddingService | None = None
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def get_embedding_service() -> EmbeddingService:
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"""
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Get singleton embedding service instance.
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Returns:
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Global EmbeddingService instance
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"""
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global _embedding_service
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if _embedding_service is None:
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_embedding_service = EmbeddingService()
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return _embedding_service
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# BM25 sparse embedding singleton
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_bm25_service: BM25SparseEmbeddingProvider | None = None
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def get_bm25_service() -> BM25SparseEmbeddingProvider:
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"""
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Get singleton BM25 sparse embedding service instance.
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Returns:
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Global BM25SparseEmbeddingProvider instance
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"""
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global _bm25_service
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if _bm25_service is None:
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_bm25_service = BM25SparseEmbeddingProvider()
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return _bm25_service
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