Update utils/chatbot_interface.py

utils/chatbot_interface.py

@@ -1,14 +1,30 @@
 import os
 import json
 import logging
+from typing import Optional
 import gradio as gr
 from utils.response_manager import ResponseManager 
 
 class ChatbotInterface:
-    def __init__(self, config_path: str = 'config/gradio_config.json'):
+   def __init__(self, 
+                 config_path: str = 'config/gradio_config.json',
+                 model: str = "gpt-4o-mini",
+                 temperature: float = 0,
+                 max_output_tokens: int = 800,
+                 max_num_results: int = 15,
+                 vector_store_id: Optional[str] = None, 
+                 api_key: Optional[str] = None, 
+                 meta_prompt_file: Optional[str] = None):
         """
-        Initialize the ChatbotInterface with configuration.
+        Initialize the ChatbotInterface with configuration and custom parameters for ResponseManager.
         :param config_path: Path to the configuration JSON file.
+        :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).
+        :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 .
         """
         self.config = self.load_config(config_path)
         self.title = self.config["chatbot_title"]
@@ -18,10 +34,34 @@ class ChatbotInterface:
         self.output_label = self.config["chatbot_output_label"]
         self.reset_button = self.config["chatbot_reset_button"]
         self.submit_button = self.config["chatbot_submit_button"]
-        self.response_manager = ResponseManager()
-        self.conversation = self.response_manager.generate_response  # Shortcut to the conversation method
-        logging.info("ChatbotInterface initialized with configuration.")
 
+        # Initialize ResponseManager with custom parameters
+        try:
+            self.response_manager = ResponseManager(
+                model=model,
+                temperature=temperature,
+                max_output_tokens=max_output_tokens,
+                max_num_results=max_num_results,
+                vector_store_id=vector_store_id,
+                api_key=api_key,
+                meta_prompt_file=meta_prompt_file
+            )
+            self.generate_response = self.response_manager.generate_response  
+            logging.info(
+                "ChatbotInterface initialized with the following parameters:\n"
+                f"  - Model: {model}\n"
+                f"  - Temperature: {temperature}\n"
+                f"  - Max Output Tokens: {max_output_tokens}\n"
+                f"  - Max Number of Results: {max_num_results}\n"
+                f"  - Vector Store ID: {vector_store_id}\n"
+                f"  - API Key: {'Provided' if api_key else 'Not Provided'}\n"
+                f"  - Meta Prompt File: {meta_prompt_file or 'Default'}"
+            )
+        except Exception as e:
+            logging.error(f"Failed to initialize ResponseManager: {e}")
+            raise
+    
+       
     @staticmethod
     def load_config(config_path: str) -> dict:
         """
@@ -84,8 +124,8 @@ class ChatbotInterface:
                 submit = gr.Button(self.submit_button, variant="primary")
 
             # Button actions
-            submit.click(fn=self.conversation, inputs=[user_input, chatbot_output], outputs=chatbot_output)
-            user_input.submit(fn=self.conversation, inputs=[user_input, chatbot_output], outputs=chatbot_output)
+            submit.click(fn=self.generate_response, inputs=[user_input, chatbot_output], outputs=chatbot_output)
+            user_input.submit(fn=self.generate_response, inputs=[user_input, chatbot_output], outputs=chatbot_output)
             reset.click(fn=self.reset_output, inputs=None, outputs=chatbot_output)
 
         logging.info("Gradio interface created successfully.")