HMC-CIS/HMC-CIS-chatbot-UI-testing

1import os2import openai3"""4A module to manage responses from the OpenAI Response API for an IT Helpdesk assistant 5at Harvey Mudd College. This module initializes the OpenAI client and provides a method 6to create responses using RAG (Retrieval-Augmented Generation) to user queries. It uses 7a vector store for retrieval of knowledge base documents and generates responses using 8the specified OpenAI model. The module also loads a developer message from a text file 9to prompt engineer responses from the AI model.10"""11 12# Load the OpenAI API key from the environment variable13# If the API key is not set, raise an error.14if "OPENAI_API_KEY" not in os.environ:15    raise ValueError("OPENAI_API_KEY environment variable is not set.")16api_key=os.getenv("OPENAI_API_KEY")17 18class ResponseManager:19    """20    A class to manage responses from the OpenAI API for an IT Helpdesk assistant.21    This class initializes the OpenAI client and provides a method to create responses22    to user queries using the specified OpenAI model.23    """24    def __init__(self, vector_store_id):25        """26        Initialize the ResponseManager with a vector store ID.27        :param vector_store_id: The ID of the vector store to use for file search.28        """29        # Initialize the OpenAI client30        # Note: The OpenAI client is initialized with the API key set in the environment variable31        # This is a placeholder for the actual OpenAI client initialization32        # In a real-world scenario, you would use the appropriate OpenAI client library33        # For example, if using the OpenAI Python library, you would do:    34        self.client = openai.OpenAI(api_key=api_key)35        self.vector_store_id = vector_store_id36        self.previous_response_id = None37        38        # Load the meta prompt from the text file39        # This message is used to provide context for the AI model40        meta_prompt_file = 'config/meta_prompt.txt'41        if not os.path.exists(meta_prompt_file):42            raise FileNotFoundError(f"Meta prompt file '{meta_prompt_file}' not found.")43        with open(meta_prompt_file, 'r') as file:44            self.meta_prompt = file.read().strip()45 46    def create_response(self, query, model: str= "gpt-4o-mini",47                        temperature=0, max_output_tokens=800,48                        max_num_results=7):49        """50        Create a response to a user query using the OpenAI API.51        :param query: The user query to respond to.52        :param model: The OpenAI model to use (default is "gpt-4o-mini").53        :param temperature: The temperature for the response (default is 0).54        :param max_output_tokens: The maximum number of output tokens (default is 800).55        :param max_num_results: The maximum number of search results to return (default is 7).56        :param verbose: Whether to print the response (default is False).57        :return: The response text from the OpenAI API.58        """59        if self.previous_response_id is None:60            input=[{"role": "developer", "content": self.meta_prompt}, 61                   {"role": "user", "content": query}]62        else:63            input=[{"role": "user", "content": query}]64 65        response = self.client.responses.create(66            model=model,67            previous_response_id=self.previous_response_id,68            input=input,69            tools=[{70                "type": "file_search",71                "vector_store_ids": [self.vector_store_id], # ["<vector_store_id>"]72                "max_num_results": max_num_results}73            ],74            temperature=temperature,75            max_output_tokens = max_output_tokens,76            # include=["output[*].file_search_call.search_results"]77        )78        self.previous_response_id = response.id79 80        return response.output_text