Update app.py

app.py

@@ -54,14 +54,14 @@ class CitingSources(BaseModel):
         description="List of sources to cite. Should be an URL of the source."
     )
 
-def chatbot_interface(message, system_prompt, history, model, temperature, num_calls, use_embeddings):
+def chatbot_interface(message, history, model, temperature, num_calls, use_embeddings, system_prompt):
     if not message.strip():
         return "", history
 
     history = history + [(message, "")]
 
     try:
-        for response in respond(message, system_prompt, history, model, temperature, num_calls, use_embeddings):
+        for response in respond(message, history, model, temperature, num_calls, use_embeddings, system_prompt):
             history[-1] = (message, response)
             yield history
     except gr.CancelledError:
@@ -71,34 +71,29 @@ def chatbot_interface(message, system_prompt, history, model, temperature, num_c
         history[-1] = (message, f"An unexpected error occurred: {str(e)}")
         yield history
 
-def retry_last_response(system_prompt, history, model, temperature, num_calls, use_embeddings):
+def retry_last_response(history, model, temperature, num_calls, use_embeddings, system_prompt):
     if not history:
         return history
     
     last_user_msg = history[-1][0]
     history = history[:-1]  # Remove the last response
     
-    return chatbot_interface(last_user_msg, system_prompt, history, model, temperature, num_calls, use_embeddings)
+    return chatbot_interface(last_user_msg, history, model, temperature, num_calls, use_embeddings, system_prompt)
 
-def respond(message, system_prompt, history, model, temperature, num_calls, use_embeddings):
+def respond(message, history, model, temperature, num_calls, use_embeddings, system_prompt):
     logging.info(f"User Query: {message}")
     logging.info(f"Model Used: {model}")
     logging.info(f"Use Embeddings: {use_embeddings}")
     logging.info(f"System Prompt: {system_prompt}")
 
     try:
-        full_response = ""
         for main_content, sources in get_response_with_search(message, model, num_calls=num_calls, temperature=temperature, use_embeddings=use_embeddings, system_prompt=system_prompt):
-            full_response += main_content
-            yield history + [(message, full_response)]
-        
-        if sources:
-            full_response += f"\n\nSources:\n{sources}"
-            yield history + [(message, full_response)]
+            response = f"{main_content}\n\n{sources}"
+            first_line = response.split('\n')[0] if response else ''
+            yield response
     except Exception as e:
         logging.error(f"Error with {model}: {str(e)}")
-        error_message = f"An error occurred with the {model} model: {str(e)}. Please try again or select a different model."
-        yield history + [(message, error_message)]
+        yield f"An error occurred with the {model} model: {str(e)}. Please try again or select a different model."
 
 def create_web_search_vectors(search_results):
     embed = get_embeddings()
@@ -111,9 +106,7 @@ def create_web_search_vectors(search_results):
     
     return FAISS.from_documents(documents, embed)
 
-def get_response_with_search(query, model, system_prompt=DEFAULT_SYSTEM_PROMPT, num_calls=3, temperature=0.2, use_embeddings=True):
-    logging.info(f"get_response_with_search - Query: {query}")
-    logging.info(f"get_response_with_search - System Prompt: {system_prompt}")
+def get_response_with_search(query, model, num_calls=3, temperature=0.2, use_embeddings=True, system_prompt=DEFAULT_SYSTEM_PROMPT):
     search_results = duckduckgo_search(query)
     
     if use_embeddings:
@@ -196,14 +189,24 @@ css = """
 /* Fine-tune chatbox size */
 """
 
+def initial_conversation():
+    return [
+        (None, "Welcome! I'm your AI assistant for web search. Here's how you can use me:\n\n"
+                "1. Ask me any question, and I'll search the web for information.\n"
+                "2. You can adjust the model, temperature, number of API calls, whether to use embeddings, and the system prompt for fine-tuned responses.\n"
+                "3. For any queries, feel free to reach out @[email protected] or discord - shreyas094\n\n"
+                "To get started, ask me a question!")
+    ]
+
 demo = gr.ChatInterface(
-    fn=respond,
+    respond,
+    additional_inputs_accordion=gr.Accordion(label="⚙️ Parameters", open=True, render=False),
     additional_inputs=[
-        gr.Textbox(label="System Prompt", lines=5, value=DEFAULT_SYSTEM_PROMPT),
         gr.Dropdown(choices=MODELS, label="Select Model", value=MODELS[3]),
         gr.Slider(minimum=0.1, maximum=1.0, value=0.2, step=0.1, label="Temperature"),
         gr.Slider(minimum=1, maximum=5, value=1, step=1, label="Number of API Calls"),
         gr.Checkbox(label="Use Embeddings", value=False),
+        gr.Textbox(label="System Prompt", lines=5, value=DEFAULT_SYSTEM_PROMPT),
     ],
     title="AI-powered Web Search Assistant",
     description="Ask questions and get answers from web search results.",
@@ -217,11 +220,12 @@ demo = gr.ChatInterface(
     cache_examples=False,
     analytics_enabled=False,
     textbox=gr.Textbox(placeholder="Ask a question", container=False, scale=7),
-    chatbot=gr.Chatbot(  
+    chatbot = gr.Chatbot(  
         show_copy_button=True,
         likeable=True,
         layout="bubble",
-        height=400
+        height=400,
+        value=initial_conversation()
     )
 )