Comments (2)
Hey @vkaul11! 👋 I'm here to help you with bugs, questions, and becoming a contributor. I'm a bot named Dosu.
No, the VectorIndexRetriever
is not the same as semantic search. The VectorStoreQueryMode
enum defines different query modes, including SEMANTIC_HYBRID
, which suggests that semantic search is a specific mode of querying within the vector store. However, this does not equate to the VectorIndexRetriever
itself [1].
To continue talking to Dosu, mention @dosu.
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Yes, by default it's top-k search based on embeddings
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Related Issues (20)
- [Bug]: poetry add llama-index failing for v0.10.65 HOT 6
- [Bug]: impossible to use PDfReader with an S3 file because of Path() casting HOT 1
- [Bug]: impossible to use PDfReader with an S3 file because of Path() casting HOT 1
- [Question]: How to run HuggingFaceEmbedding on multiple available GPUs? HOT 1
- [Question]: HOT 2
- [Question]: Constructing hybrid indices with Qdrant. HOT 10
- [Bug]: NeptuneAnalyticsPropertyGraphStore incorrectly assigning the embedding to the chunk instead of the entity HOT 2
- [Question]: Data disappear after build vector store with VectorStoreIndex.from_documents() HOT 7
- [Bug]: VectorStoreIndex.build_index_from_nodes() missing 1 required positional argument: 'self' HOT 5
- Pydantic V2 migration (llms)
- Pydantic V2 migration (graph-stores & indices) HOT 1
- Pydantic V2 migration (agent, embeddings, callbacks, extractors, multi-modal-llms, postprocessor)
- Pydantic V2 migration (node parsers, output parsers, program, question gen)
- [Question]: how to insert custom embeddings into qdrant instead of document HOT 1
- [Feature Request]: Support to configure the base url of jina.ai
- [Bug]: ModuleNotFoundError: No module named 'llama_index.legacy.finetuning.gradient' HOT 3
- [Question]: LlamaIndex with OpenSearch: MetadataFilters not working as expected HOT 2
- [Feature Request]:
- Pydantic V2 migration (readers)
- Pydantic V2 migration (vector stores)
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