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Neurolingua
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Update app.py
Browse files
app.py
CHANGED
@@ -95,17 +95,26 @@ def extract_text_from_pdf(pdf_filepath):
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def query_rag(query_text: str, chat_history):
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try:
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embedding_function = HuggingFaceEmbeddings()
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db = Chroma(persist_directory=CHROMA_PATH, embedding_function=embedding_function)
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results = db.similarity_search_with_score(query_text, k=5)
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if not results:
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return "Sorry, I couldn't find any relevant information."
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context_text = "\n\n---\n\n".join([doc.page_content for doc, _score in results])
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prompt = f"Context:\n{context_text}\n\nQuestion:\n{query_text}"
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response = generate_response(prompt, chat_history)
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return response
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@@ -114,6 +123,7 @@ def query_rag(query_text: str, chat_history):
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return "An error occurred while querying the RAG system."
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def save_pdf_and_update_database(pdf_filepath):
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try:
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text = extract_text_from_pdf(pdf_filepath)
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def query_rag(query_text: str, chat_history):
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try:
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# Ensure the database is initialized
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initialize_chroma()
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embedding_function = HuggingFaceEmbeddings()
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db = Chroma(persist_directory=CHROMA_PATH, embedding_function=embedding_function)
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# Perform similarity search
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results = db.similarity_search_with_score(query_text, k=5)
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if not results:
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print("No relevant information found.")
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return "Sorry, I couldn't find any relevant information."
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# Combine document contents for context
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context_text = "\n\n---\n\n".join([doc.page_content for doc, _score in results])
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# Prepare the prompt for the Falcon model
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prompt = f"Context:\n{context_text}\n\nQuestion:\n{query_text}"
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# Generate a response using the Falcon model
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response = generate_response(prompt, chat_history)
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return response
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return "An error occurred while querying the RAG system."
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def save_pdf_and_update_database(pdf_filepath):
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try:
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text = extract_text_from_pdf(pdf_filepath)
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