adding USE_MEMORY flag
Browse files- semantic.py +44 -22
semantic.py
CHANGED
@@ -26,9 +26,15 @@ from globals import (
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VECTOR_STORE_PATH
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)
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from qdrant_client import QdrantClient
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RAG_PROMPT = """
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@@ -61,7 +67,7 @@ class SemanticStoreFactory:
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if path.exists() and path.is_dir() and any(path.iterdir()):
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_logger.info(f"\tQdrant loading ...")
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store = Qdrant(
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client=
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embeddings=embeddings,
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collection_name=META_SEMANTIC_COLLECTION,
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)
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@@ -75,11 +81,14 @@ class SemanticStoreFactory:
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cls
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) -> VectorStore:
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documents = PyMuPDFLoader(META_10K_FILE_PATH).load()
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semantic_chunker = SemanticChunker(
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@@ -87,13 +96,23 @@ class SemanticStoreFactory:
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breakpoint_threshold_type="percentile"
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)
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semantic_chunks = semantic_chunker.create_documents([d.page_content for d in documents])
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return semantic_chunk_vectorstore
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@classmethod
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@@ -101,13 +120,16 @@ class SemanticStoreFactory:
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cls
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) -> VectorStore:
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if cls._semantic_vectorstore is None:
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return cls._semantic_vectorstore
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VECTOR_STORE_PATH
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)
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USE_MEMORY = True
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from qdrant_client import QdrantClient
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qclient: QdrantClient
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if USE_MEMORY == True:
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qclient = QdrantClient(":memory:")
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else:
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qclient = QdrantClient(path=VECTOR_STORE_PATH)
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RAG_PROMPT = """
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if path.exists() and path.is_dir() and any(path.iterdir()):
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_logger.info(f"\tQdrant loading ...")
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store = Qdrant(
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client=qclient,
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embeddings=embeddings,
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collection_name=META_SEMANTIC_COLLECTION,
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)
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cls
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) -> VectorStore:
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if USE_MEMORY == True:
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_logger.info(f"creating semantic vector store: {USE_MEMORY}")
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else:
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_logger.info(f"creating semantic vector store: {VECTOR_STORE_PATH}")
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path = Path(VECTOR_STORE_PATH)
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if not path.exists():
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path.mkdir(parents=True, exist_ok=True)
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_logger.info(f"Directory '{path}' created.")
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documents = PyMuPDFLoader(META_10K_FILE_PATH).load()
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semantic_chunker = SemanticChunker(
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breakpoint_threshold_type="percentile"
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)
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semantic_chunks = semantic_chunker.create_documents([d.page_content for d in documents])
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if USE_MEMORY == True:
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semantic_chunk_vectorstore = Qdrant.from_documents(
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semantic_chunks,
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embeddings,
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location=":memory:",
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collection_name=META_SEMANTIC_COLLECTION,
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force_recreate=True
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)
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else:
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semantic_chunk_vectorstore = Qdrant.from_documents(
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semantic_chunks,
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embeddings,
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path=VECTOR_STORE_PATH,
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collection_name=META_SEMANTIC_COLLECTION,
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force_recreate=True
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)
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return semantic_chunk_vectorstore
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@classmethod
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cls
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) -> VectorStore:
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if cls._semantic_vectorstore is None:
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if USE_MEMORY == True:
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cls._semantic_vectorstore = cls.__create_semantic_store()
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else:
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print(f"Loading semantic vectorstore {META_SEMANTIC_COLLECTION} from: {VECTOR_STORE_PATH}")
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try:
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# first try to load the store
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cls._semantic_vectorstore = cls.__load_semantic_store()
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except Exception as e:
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_logger.warning(f"cannot load: {e}")
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cls._semantic_vectorstore = cls.__create_semantic_store()
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return cls._semantic_vectorstore
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