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https://github.com/open-webui/open-webui
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revert: original rag pipeline
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7d88689f51
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@ -18,6 +18,9 @@ from langchain.retrievers import (
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EnsembleRetriever,
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EnsembleRetriever,
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)
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)
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from sentence_transformers import CrossEncoder
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from typing import Optional
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from config import SRC_LOG_LEVELS, CHROMA_CLIENT
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from config import SRC_LOG_LEVELS, CHROMA_CLIENT
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@ -28,12 +31,14 @@ log.setLevel(SRC_LOG_LEVELS["RAG"])
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def query_embeddings_doc(
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def query_embeddings_doc(
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collection_name: str,
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collection_name: str,
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query: str,
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query: str,
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k: int,
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r: float,
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embeddings_function,
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embeddings_function,
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reranking_function,
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k: int,
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reranking_function: Optional[CrossEncoder] = None,
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r: Optional[float] = None,
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):
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):
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try:
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try:
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if reranking_function:
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# if you use docker use the model from the environment variable
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# if you use docker use the model from the environment variable
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collection = CHROMA_CLIENT.get_collection(name=collection_name)
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collection = CHROMA_CLIENT.get_collection(name=collection_name)
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@ -71,7 +76,19 @@ def query_embeddings_doc(
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"documents": [[d.page_content for d in result]],
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"documents": [[d.page_content for d in result]],
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"metadatas": [[d.metadata for d in result]],
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"metadatas": [[d.metadata for d in result]],
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}
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}
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else:
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# if you use docker use the model from the environment variable
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query_embeddings = embeddings_function(query)
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log.info(f"query_embeddings_doc {query_embeddings}")
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collection = CHROMA_CLIENT.get_collection(name=collection_name)
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result = collection.query(
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query_embeddings=[query_embeddings],
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n_results=k,
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)
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log.info(f"query_embeddings_doc:result {result}")
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return result
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return result
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except Exception as e:
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except Exception as e:
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raise e
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raise e
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