docs/tutorials/retrievers/ #28864
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I get an error when setting Mistral API key like this (as suggested in the code): The correct way is to set |
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I am trying out a simple vector similarity search and I am seeing poor performance across Nomic embeddings and Llama 32. 1b embeddings. Any help is appreciated. Code to reproduce
Output
^ Above output is not relevant at all to the question prompt. |
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They Voyage AI for import is wrong. Currently its Just some helpful tidbid, maybe the authors can quickly fix it aswell! |
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docs/tutorials/retrievers/
This tutorial will familiarize you with LangChain's document loader, embedding, and vector store abstractions. These abstractions are designed to support retrieval of data-- from (vector) databases and other sources-- for integration with LLM workflows. They are important for applications that fetch data to be reasoned over as part of model inference, as in the case of retrieval-augmented generation, or RAG (see our RAG tutorial here).
https://python.langchain.com/docs/tutorials/retrievers/
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