mirror of
https://github.com/hwchase17/langchain
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480626dc99
…tch]: import models from community ran ```bash git grep -l 'from langchain\.chat_models' | xargs -L 1 sed -i '' "s/from\ langchain\.chat_models/from\ langchain_community.chat_models/g" git grep -l 'from langchain\.llms' | xargs -L 1 sed -i '' "s/from\ langchain\.llms/from\ langchain_community.llms/g" git grep -l 'from langchain\.embeddings' | xargs -L 1 sed -i '' "s/from\ langchain\.embeddings/from\ langchain_community.embeddings/g" git checkout master libs/langchain/tests/unit_tests/llms git checkout master libs/langchain/tests/unit_tests/chat_models git checkout master libs/langchain/tests/unit_tests/embeddings/test_imports.py make format cd libs/langchain; make format cd ../experimental; make format cd ../core; make format ```
17 lines
441 B
Python
17 lines
441 B
Python
from langchain.retrievers import CohereRagRetriever
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from langchain_community.chat_models import ChatCohere
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rag = CohereRagRetriever(llm=ChatCohere())
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def get_docs_message(message):
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docs = rag.get_relevant_documents(message)
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message_doc = next(
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(x for x in docs if x.metadata.get("type") == "model_response"), None
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)
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return message_doc.page_content
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def librarian_rag(x):
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return get_docs_message(x["message"])
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