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Delete utils/chatbot_logic.py
Browse files- utils/chatbot_logic.py +0 -61
utils/chatbot_logic.py
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import os
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import logging
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from utils.response_manager import ResponseManager # Import the ResponseManager class
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# Vector store ID for the retrieval of knowledge base documents
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vector_store_id = os.getenv('VECTOR_STORE_ID')
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# Check if the VECTOR_STORE_ID environment variable is set
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if not vector_store_id:
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logging.error("VECTOR_STORE_ID environment variable is not set.")
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raise ValueError("VECTOR_STORE_ID environment variable is not set.")
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# Initialize the ResponseManager with the vector store ID
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response_manager = ResponseManager(vector_store_id)
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# Constants for response generation
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DEFAULT_MODEL = "gpt-4o-mini" # Set the model to be used for response generation
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DEFAULT_TEMPERATURE = 0 # Set the temperature for response generation
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DEFAULT_MAX_OUTPUT_TOKENS = 800 # Set the maximum number of output tokens
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DEFAULT_MAX_NUM_RESULTS = 15 # Set the maximum number of knowledge base documents to return for retrieval
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def conversation(query: str, history: list) -> list:
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"""
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Function to handle the chatbot interaction and maintain conversation history.
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:param query: The user query to respond to.
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:param history: The conversation history (list of [input, output] pairs).
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:return: Updated conversation history.
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"""
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logging.info("Received query: %s", query)
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try:
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# Validate the query
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if not query.strip():
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logging.warning("Empty or invalid query received.")
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history.append((query, "Please enter a valid query."))
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return history
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# Generate a response using the ResponseManager
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logging.info("Generating response for the query...")
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response = response_manager.create_response(
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query=query,
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model=DEFAULT_MODEL,
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temperature=DEFAULT_TEMPERATURE,
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max_output_tokens=DEFAULT_MAX_OUTPUT_TOKENS,
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max_num_results=DEFAULT_MAX_NUM_RESULTS
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)
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# Handle cases where no response is generated
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if not response:
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logging.warning("No response generated for the query.")
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response = "Sorry, I couldn't generate a response at this time. Please try again later."
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# Append the query and response to the conversation history
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history.append((query, response))
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logging.info("Response generated successfully.")
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return history
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except Exception as e:
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# Log the error and append it to the conversation history
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logging.error("An error occurred while generating a response: %s", str(e))
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history.append((query, f"An error occurred: {str(e)}"))
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return history
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