feat: add unified provider architecture with Amazon Bedrock support
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>
This commit is contained in:
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"""Embedding service with provider detection."""
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"""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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import os
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from .base import EmbeddingProvider
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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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from .ollama_provider import OllamaEmbeddingProvider
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from .simple_provider import SimpleEmbeddingProvider
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logger = logging.getLogger(__name__)
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class EmbeddingService:
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"""Unified embedding service with automatic provider detection."""
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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 = self._detect_provider()
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def _detect_provider(self) -> EmbeddingProvider:
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"""
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Auto-detect available embedding provider.
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Checks environment variables in order:
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1. OLLAMA_BASE_URL - Use Ollama provider (production)
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2. OPENAI_API_KEY - Use OpenAI provider (future)
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3. Fallback to SimpleEmbeddingProvider (testing/development)
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Returns:
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Configured embedding provider
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"""
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# Ollama provider (production)
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ollama_url = os.getenv("OLLAMA_BASE_URL")
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if ollama_url:
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logger.info(f"Using Ollama embedding provider: {ollama_url}")
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return OllamaEmbeddingProvider(
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base_url=ollama_url,
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model=os.getenv("OLLAMA_EMBEDDING_MODEL", "nomic-embed-text"),
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verify_ssl=os.getenv("OLLAMA_VERIFY_SSL", "true").lower() == "true",
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)
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# OpenAI provider (future implementation)
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# openai_key = os.getenv("OPENAI_API_KEY")
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# if openai_key:
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# return OpenAIEmbeddingProvider(api_key=openai_key)
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# Fallback to simple provider for development/testing
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logger.warning(
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"No embedding provider configured (OLLAMA_BASE_URL or OPENAI_API_KEY not set). "
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"Using SimpleEmbeddingProvider for testing/development. "
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"For production, configure an external embedding service."
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)
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return SimpleEmbeddingProvider(dimension=384)
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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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