import os
from utils.response_manager import ResponseManager  # Import the ResponseManager class

# Vector store ID for the retrieval of knowledge base documents
# Load the vector store ID from the environment variable
vector_store_id = os.getenv('VECTOR_STORE_ID')

# Check if the VECTOR_STORE_ID environment variable is set
if not vector_store_id:
    raise ValueError("VECTOR_STORE_ID environment variable is not set.")

# Initialize the ResponseManager with the vector store ID
response_manager = ResponseManager(vector_store_id)

# Set parameters for the response generation
model = "gpt-4o-mini"  # Set the model to be used for response generation
temperature = 0  # Set the temperature for response generation
max_output_tokens = 800  # Set the maximum number of output tokens
max_num_results = 15  # Set the maximum number of knowledge base documents to return for retrieval


def conversation(query: str, history):
    """
    Function to handle the chatbot interaction and maintain conversation history.
    :param query: The user query to respond to.
    :param history: The conversation history (list of [input, output] pairs).
    :return: Updated conversation history.
    """
    try:
        if query.strip():
            response = response_manager.create_response(query, model, temperature, max_output_tokens, max_num_results)
            if not response:
                response = "Sorry, I couldn't generate a response at this time. Please try again later."
            # Append the conversation
            history.append((query, response))
        else:
            history.append((query, "Please enter a valid query."))
        return history
    except Exception as e:
        history.append((query, str(e)))
        return history