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* update dataprep readme Signed-off-by: letonghan <letong.han@intel.com> * update vectorstore readme Signed-off-by: letonghan <letong.han@intel.com> * udpate retriever readme Signed-off-by: letonghan <letong.han@intel.com> * update retriever readme Signed-off-by: letonghan <letong.han@intel.com> * udpate embedding readme Signed-off-by: letonghan <letong.han@intel.com> * update guardrails readme Signed-off-by: letonghan <letong.han@intel.com> * update other readmes Signed-off-by: letonghan <letong.han@intel.com> * update reranks readme Signed-off-by: letonghan <letong.han@intel.com> * update llm&lvms readme Signed-off-by: letonghan <letong.han@intel.com> * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Signed-off-by: letonghan <letong.han@intel.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
36 lines
1.9 KiB
Markdown
36 lines
1.9 KiB
Markdown
# Retriever Microservice
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This retriever microservice is a highly efficient search service designed for handling and retrieving embedding vectors. It operates by receiving an embedding vector as input and conducting a similarity search against vectors stored in a VectorDB database. Users must specify the VectorDB's URL and the index name, and the service searches within that index to find documents with the highest similarity to the input vector.
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The service primarily utilizes similarity measures in vector space to rapidly retrieve contentually similar documents. The vector-based retrieval approach is particularly suited for handling large datasets, offering fast and accurate search results that significantly enhance the efficiency and quality of information retrieval.
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Overall, this microservice provides robust backend support for applications requiring efficient similarity searches, playing a vital role in scenarios such as recommendation systems, information retrieval, or any other context where precise measurement of document similarity is crucial.
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## Retriever Microservice with Redis
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For details, please refer to this [langchain readme](redis/langchain/README.md) or [llama_index readme](redis/llama_index/README.md)
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## Retriever Microservice with Milvus
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For details, please refer to this [readme](milvus/langchain/README.md)
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## Retriever Microservice with PGVector
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For details, please refer to this [readme](pgvector/langchain/README.md)
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## Retriever Microservice with Pathway
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For details, please refer to this [readme](pathway/langchain/README.md)
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## Retriever Microservice with QDrant
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For details, please refer to this [readme](qdrant/haystack/README.md)
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## Retriever Microservice with VDMS
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For details, please refer to this [readme](vdms/langchain/README.md)
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## Retriever Microservice with Multimodal
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For details, please refer to this [readme](multimodal/redis/langchain/README.md)
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