Harrison/from methods #1912
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Harrison/from methods #1912
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# Why - Since making vectors of texts can be done outside of langchain Faiss, this PR is to add functionality to pass text and its vector pair to initialize and add embedding to Faiss. # What - Add `from_embedding` method in Faiss to initialize Faiss index by passing the embeddings paired with original text made outside of the langchain. - Add `add_embedding` method to add embedding paired with original text to append the embedding made outside of the langchain.
baskaryan
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Oct 19, 2023
- **Description:** Provide a way to use different text for embedding. - For example, if you are ingesting stack-overflow Q&As for RAG, you would want to embed the questions and return the answer(s) for the hits. With this change, the consumer of langchain can implement that easily. - I noticed the similar function is added on faiss.py with #1912 which was for performance reason, but I see the same function can be used to achieve what I thought. So instead of changing Document class to have embedding_content, I mimicked the implementation of faiss.py. - The test should provide some guidance on how to use it. It would be more intuitive if I just pass texts and embedding_texts as separate arguments, but I chose to use `zip`-ed object for the consistency with faiss.py implementation. - I plan to make similar pull request for OpenSearch. - **Issue:** N/A - **Dependencies:** None other than the existing ones. Co-authored-by: Bagatur <baskaryan@gmail.com>
hoanq1811
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Feb 2, 2024
- **Description:** Provide a way to use different text for embedding. - For example, if you are ingesting stack-overflow Q&As for RAG, you would want to embed the questions and return the answer(s) for the hits. With this change, the consumer of langchain can implement that easily. - I noticed the similar function is added on faiss.py with langchain-ai#1912 which was for performance reason, but I see the same function can be used to achieve what I thought. So instead of changing Document class to have embedding_content, I mimicked the implementation of faiss.py. - The test should provide some guidance on how to use it. It would be more intuitive if I just pass texts and embedding_texts as separate arguments, but I chose to use `zip`-ed object for the consistency with faiss.py implementation. - I plan to make similar pull request for OpenSearch. - **Issue:** N/A - **Dependencies:** None other than the existing ones. Co-authored-by: Bagatur <baskaryan@gmail.com>
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