utils/response_manager.py

import os
import openai
import logging
from typing import Optional
import asyncio

class ResponseManager:
    """
    This class initializes the OpenAI client and provides methods to create responses, 
    maintain conversation history, and handle user queries.
    """

    def __init__(self, 
                 vector_store_id: Optional[str] = None, 
                 api_key: Optional[str] = None, 
                 meta_prompt_file: Optional[str] = None,
                 model: str = "gpt-4.1-nano",
                 temperature: float = 0,
                 max_output_tokens: int = 600,
                 max_num_results: int = 5):
        """
        Initialize the ResponseManager with optional parameters for configuration.
        :param vector_store_id: The ID of the vector store to use for file search.
        :param api_key: The OpenAI API key for authentication.
        :param meta_prompt_file: Path to the meta prompt file (default: 'config/meta_prompt.txt').
        :param model: The OpenAI model to use (default: 'gpt-4o-mini').
        :param temperature: The temperature for response generation (default: 0).
        :param max_output_tokens: The maximum number of output tokens (default: 800).
        :param max_num_results: The maximum number of search results to return (default: 15).
        """
        # Load vector_store_id and api_key from environment variables if not provided
        self.vector_store_id = vector_store_id or os.getenv('USS_DOCUMENTATION_VECTOR_STORE')
        if not self.vector_store_id:
            logging.error("VECTOR_STORE_ID is not provided or set in the environment.")
            raise ValueError("VECTOR_STORE_ID is required.")

        self.api_key = api_key or os.getenv('SETTING_UP_API_KEY')
        if not self.api_key:
            logging.error("OPENAI_API_KEY is not provided or set in the environment.")
            raise ValueError("OPENAI_API_KEY is required.")

        # Initialize other attributes
        self.meta_prompt_file = meta_prompt_file or 'config/meta_prompt.txt'
        self.previous_response_id = None

        # Initialize the OpenAI client
        self.client = openai.OpenAI(api_key=self.api_key)

        # Load the meta prompt from the specified file
        self.meta_prompt = self._load_meta_prompt(self.meta_prompt_file)

        # Set default parameters for response generation
        self.model = model
        self.temperature = temperature
        self.max_output_tokens = max_output_tokens
        self.max_num_results = max_num_results

    def _load_meta_prompt(self, meta_prompt_file: str) -> str:
        """
        Load the meta prompt from the specified file.
        :param meta_prompt_file: Path to the meta prompt file.
        :return: The meta prompt as a string.
        """
        if not os.path.exists(meta_prompt_file):
            logging.error(f"Meta prompt file '{meta_prompt_file}' not found.")
            raise FileNotFoundError(f"Meta prompt file '{meta_prompt_file}' not found.")
        with open(meta_prompt_file, 'r', encoding='utf-8') as file:
            meta_prompt = file.read().strip()
        logging.info(f"Meta prompt loaded successfully from '{meta_prompt_file}'.")
        return meta_prompt

    async def generate_response(self, query: str, history: list) -> list:
        """
        Generate a response to a user query using the OpenAI API.
        This method interacts with the OpenAI API to create a response based on the user's query.
        It supports optional parameters for model configuration and handles errors gracefully.
        Args:
            query (str): The user query to respond to.
            history (list): The conversation history from the chatbot.
        Returns:
            list: A list of dictionaries representing the conversation, including the generated response.
        """
        # Prepare the input for the API call
        input_data = [{"role": "developer", "content": self.meta_prompt}] if self.previous_response_id is None else []
        input_data.append({"role": "user", "content": query})
        
        # Validate the query
        if not query.strip():
            logging.warning("Empty or invalid query received.")
            warning_message = "Please enter a valid query."
            input_data.append({"role": "assistant", "content": warning_message})
            return history + input_data

        try:
            logging.info("Sending request to OpenAI API...")
            loop = asyncio.get_running_loop()
            response = await loop.run_in_executor(
                None,  # default executor
                lambda:  self.client.responses.create(
                    model=self.model,
                    previous_response_id=self.previous_response_id,
                    input=input_data,
                    tools=[{
                        "type": "file_search",
                        "vector_store_ids": [self.vector_store_id],
                        "max_num_results": self.max_num_results
                    }],
                    truncation="auto",
                    temperature=self.temperature,
                    max_output_tokens=self.max_output_tokens
                )
            )
            self.previous_response_id = response.id
            logging.info("Response received successfully.")
            input_data.append({"role": "assistant", "content": response.output_text})
            return history + input_data

        except Exception as e:
            logging.error(f"An error occurred while generating a response: {e}")
            error_message = "Sorry, I couldn't generate a response at this time. Please try again later."
            input_data.append({"role": "assistant", "content": error_message})
            return history + input_data 

    def reset_conversation(self):
        """
        Reset the conversation state internally maintained by OpenAI Response API.
        """
        self.previous_response_id = None
        logging.info("Previous response id reset to None.")