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Updare retrive creation
Browse files- seminar_edition_ai.py +6 -1
seminar_edition_ai.py
CHANGED
@@ -278,13 +278,18 @@ def predictArgumentQuestionBuild(questionAnswer, llmModelList = []):
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)
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global retriever
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global HISTORY_ANSWER
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if retriever == None:
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doc = Document(page_content="text", metadata={"source": "local"})
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vectorstore = Chroma.from_documents(
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documents=[doc],
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-
embedding=embed_model,
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persist_directory="chroma_db_dir_sermon", # Local mode with in-memory storage only
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collection_name="sermon_lab_ai"
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)
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)
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global retriever
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global HISTORY_ANSWER
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global embed_model
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if embed_model == None:
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llmBuilder = GeminiLLM()
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embed_model = llmBuilder.getEmbeddingsModel()
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if retriever == None:
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doc = Document(page_content="text", metadata={"source": "local"})
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vectorstore = Chroma.from_documents(
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documents=[doc],
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embedding = embed_model,
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persist_directory="chroma_db_dir_sermon", # Local mode with in-memory storage only
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collection_name="sermon_lab_ai"
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)
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