Vector Store Providers

pip install remina-memory[chroma]

"vector_store": {
    "provider": "chroma",
    "config": {
        "path": "~/.remina/chroma",
        "collection_name": "remina",
    }
}

pip install remina-memory[qdrant]

"vector_store": {
    "provider": "qdrant",
    "config": {
        "url": "http://localhost:6333",
        "api_key": None,
        "collection_name": "remina",
        "embedding_dims": 1536,
    }
}

docker run -d \
  --name remina-qdrant \
  -p 6333:6333 \
  -p 6334:6334 \
  -v qdrant_storage:/qdrant/storage \
  qdrant/qdrant

pip install remina-memory[pinecone]

"vector_store": {
    "provider": "pinecone",
    "config": {
        "api_key": "your-api-key",
        "index_name": "remina",
        "namespace": "default",
        "embedding_dims": 768,
        "cloud": "aws",
        "region": "us-east-1",
    }
}

class VectorStoreBase(ABC):
    async def upsert(self, id: str, embedding: List[float], metadata: Dict) -> None
    async def upsert_batch(self, items: List[Tuple[str, List[float], Dict]]) -> None
    async def search(self, embedding: List[float], limit: int = 10, filters: Dict = None) -> List[VectorSearchResult]
    async def delete(self, ids: List[str]) -> None
    async def close(self) -> None