Updated vector store

app.py

@@ -6,9 +6,10 @@ from utils.response_manager import ResponseManager  # Import the ResponseManager
 This script sets up a Gradio interface to host an AI chatbot using RAG (Retrieval-Augmented Generation)
 to provide responses to user queries. Response API from OpenAI is used for both retrieval and generation of responses.
 """
+
 # 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')
+vector_store_id = "vs_67d49daee8e881918b6abd6f28bfffea" #os.getenv('VECTOR_STORE_ID')
 
 # Check if the VECTOR_STORE_ID environment variable is set
 if not vector_store_id:
@@ -40,7 +41,7 @@ chatbot_submit_button = config["chatbot_submit_button"]
 chatbot_reset_button = config["chatbot_reset_button"]
 
 # Check if the configuration parameters are set correctly
-if not all([header_message, title, description,
+if not all([title, description,
             chatbot_input_label, chatbot_input_placeholder,
             chatbot_output_label, chatbot_output_placeholder,
             chatbot_submit_button, chatbot_reset_button]):
@@ -76,5 +77,7 @@ iface = gr.Interface(fn=chatbot,
                      theme="default",
                      live=True)
 
+
 if __name__ == "__main__":
-    iface.launch()
+    iface.launch(share=True, 
+                 server_name="HMC CIS IT Helpdesk")

config/gradio_config.json

@@ -8,7 +8,4 @@
     "chatbot_output_placeholder": "The AI assistant will respond here",
     "chatbot_submit_button": "Ask",
     "chatbot_reset_button": "Reset"
-}
-// This JSON file contains configuration settings for a Gradio chatbot interface.
-// It includes settings for the header message, title, description, input and output labels,
-// placeholders, and button labels. 
+}

utils/response_manager.py

@@ -38,10 +38,10 @@ class ResponseManager:
         # Load the meta prompt from the text file
         # This message is used to provide context for the AI model
         meta_prompt_file = 'config/meta_prompt.txt'
-        if not os.path.exists(developer_message_file):
+        if not os.path.exists(meta_prompt_file):
             raise FileNotFoundError(f"Meta prompt file '{meta_prompt_file}' not found.")
         with open(meta_prompt_file, 'r') as file:
-            self.meta_prompt_file = file.read().strip()
+            self.meta_prompt = file.read().strip()
 
     def create_response(self, query, model: str= "gpt-4o-mini",
                         temperature=0, max_output_tokens=800,
@@ -57,7 +57,7 @@ class ResponseManager:
         :return: The response text from the OpenAI API.
         """
         if self.previous_response_id is None:
-            input=[{"role": "developer", "content": self.developer_message}, 
+            input=[{"role": "developer", "content": self.meta_prompt}, 
                    {"role": "user", "content": query}]
         else:
             input=[{"role": "user", "content": query}]