Comments (4)
What index are you using? What retriever?
from llama_index.
What index are you using? What retriever?
i'm using index = VectorStoreIndex , and index.as_query_engine()
from llama_index.
The default vector store index and query engine does not follow or use the node relationships 👀 you'd have to introduce a node postprocessor to use them
from llama_index.
The default vector store index and query engine does not follow or use the node relationships 👀 you'd have to introduce a node postprocessor to use them
So what method should I use to refer to relocationship when retrever? Is there an example? I'm thinking about faiss, chroma, etc. as vector db right now.
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Related Issues (20)
- [Question]: How to insert/delete document to/from VectorStoreIndex when using IngestionPipeline? HOT 2
- Compatibility issue between Qdrant and DSPy when Qdrant is used as the VectorStoreIndex's storage context HOT 5
- [Question]: AttributeError: 'property' object has no attribute 'context_window' HOT 1
- [Question]: The created knowledge graph does not have edge relationships neo4j HOT 14
- [Documentation]: Some of the URL Not Working HOT 3
- [Question]: Unable to understand how document storage works in case nodes are deleted HOT 1
- [Documentation]: Broken 'Examples' Link HOT 3
- [Feature Request]: Add a notebook to show llamaindex agent works with graphRAG and Vertex AI
- [Bug]: File rename error in llama-index-finetuning/llama_index/finetuning/mistralai/utils.py HOT 1
- [Question]: How to enable "Calling function" print out after querying from Multi-Document Agent example HOT 6
- [Question]: Access LLM's response object CompleteResponse() attribute `additional_kwarg` in RAG HOT 2
- [Bug]: Error in initializing neo4j HOT 2
- Indexes cannot be created correctly using the MilvusVectorStore. HOT 13
- How should the dim parameter value of MilvusVectorStore be calculated? HOT 4
- [Bug]: ERROR: Failed building wheel for pystemmer HOT 1
- How to deploy open-source embedding models in auto-merging retriever: ValueError: shapes (1024,) and (384,) not aligned: 1024 (dim 0) != 384 (dim 0) HOT 3
- [Bug]: No module named 'llama_index.llms.openai.base HOT 1
- [Bug]: [OpenAILike] Cannot use llm_chat_callback on an instance without a callback_manager attribute HOT 4
- [Feature Request]: Version pinning for sub packages HOT 2
- I wonder how to use llama_index to retrieve the Milvus collection after it is created and indexed using the MilvusVectorStore. HOT 8
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