Spaces:
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Update app.py
Browse files
app.py
CHANGED
@@ -34,16 +34,17 @@ def stream_chat_with_rag(
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# Build the conversation prompt including system prompt and history
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conversation = system_prompt + "\n\n" + f"For Client: {client_name}\n"
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# Prepare the data to send to the API
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# Remove 'history' from the payload since the API does not accept it
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api_payload = {
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"message": conversation, # Include the history in the message
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"client_name": client_name,
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"system_prompt": "", # Optionally set to empty if included in message
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"num_retrieved_docs": num_retrieved_docs,
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"num_docs_final": num_docs_final,
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"temperature": temperature,
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@@ -53,27 +54,92 @@ def stream_chat_with_rag(
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"penalty": penalty,
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}
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# Function to handle PDF processing API call
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# Build the conversation prompt including system prompt and history
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conversation = system_prompt + "\n\n" + f"For Client: {client_name}\n"
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if history: # Check if history exists
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for user_input, assistant_response in history:
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conversation += f"User: {user_input}\nAssistant: {assistant_response}\n"
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conversation += f"User: {message}\nAssistant:" # Add the current message
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# Prepare the data to send to the API
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api_payload = {
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"message": conversation, # Include the history in the message,
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"history": history
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"client_name": client_name,
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"system_prompt": "", # Optionally set to empty if included in the message
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"num_retrieved_docs": num_retrieved_docs,
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"num_docs_final": num_docs_final,
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"temperature": temperature,
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"penalty": penalty,
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}
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try:
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# Make the API call to get the assistant's reply
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response = client.predict(
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api_name="/chat",
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**api_payload
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)
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# Extract the assistant's reply
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if isinstance(response, tuple):
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answer = response[0]
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else:
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answer = response
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# Debugging statements
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print("The Answer in stream_chat_with_rag:")
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print(answer)
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# Update the conversation history
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history.append((message, answer))
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# except Exception as e:
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# print(f"An error occurred: {e}")
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# answer = "There was an error retrieving the response."
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# # Return the updated history
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# return history
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# def stream_chat_with_rag(
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# message: str,
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# history: list,
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# client_name: str,
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# system_prompt: str,
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# num_retrieved_docs: int = 10,
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# num_docs_final: int = 9,
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# temperature: float = 0,
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# max_new_tokens: int = 1024,
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# top_p: float = 1.0,
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# top_k: int = 20,
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# penalty: float = 1.2,
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# ):
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# print(f"Message: {message}")
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# print(f"History: {history}")
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# # Build the conversation prompt including system prompt and history
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# conversation = system_prompt + "\n\n" + f"For Client: {client_name}\n"
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# for user_input, assistant_response in history:
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# conversation += f"User: {user_input}\nAssistant: {assistant_response}\n"
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# conversation += f"User: {message}\nAssistant:"
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# # Prepare the data to send to the API
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# # Remove 'history' from the payload since the API does not accept it
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# api_payload = {
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# "message": conversation, # Include the history in the message
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# "client_name": client_name,
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# "system_prompt": "", # Optionally set to empty if included in message
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# "num_retrieved_docs": num_retrieved_docs,
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# "num_docs_final": num_docs_final,
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# "temperature": temperature,
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# "max_new_tokens": max_new_tokens,
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# "top_p": top_p,
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# "top_k": top_k,
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# "penalty": penalty,
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# }
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# # Make the API call to get the assistant's reply
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# response = client.predict(
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# api_name="/chat",
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# **api_payload
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# )
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# # Extract the assistant's reply
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# if isinstance(response, tuple):
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# answer = response[0]
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# else:
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# answer = response
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# # Debugging statements
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# print("The Answer in stream_chat_with_rag:")
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# print(answer)
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# # Update the conversation history
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# history.append((message, answer))
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# # Return the updated history
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# #return history
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# Function to handle PDF processing API call
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