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	Update local changes
Browse files- seminar_edition_ai.py +11 -1
 
    	
        seminar_edition_ai.py
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         @@ -134,13 +134,18 @@ def predictFromInit( sermonTopic, llmModelList): 
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                keyStr = 'BIBLE_VERSICLE'
         
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              global retriever
         
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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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         @@ -180,6 +185,11 @@ def predictQuestionBuild(sermonTopic): 
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                   ['SERMON_IDEA', 'context']
         
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                  )
         
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              global retriever
         
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              if retriever == None:
         
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                  doc = Document(page_content="text", metadata={"source": "local"})
         
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                keyStr = 'BIBLE_VERSICLE'
         
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              global retriever
         
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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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                   ['SERMON_IDEA', 'context']
         
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                  )
         
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              global retriever
         
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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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