Update app.py

app.py

@@ -207,7 +207,6 @@ def run_agent(
 
     """
     Generate text based on user queries.
-
     Args:
         query: User's query
         model: LLM like "gpt-4o"
@@ -215,15 +214,18 @@ def run_agent(
         image_urls: List of URLs for images
         temperature: Value between 0 and 1. Defaults to 0.7
         agent_type: 'Tool Calling' or 'ReAct'
-
     Return:
         generated text
-
     The chat prompt and message history are stored in
     st.session_state variables.
     """
 
     try:
+        # Ensure retriever tool is included in tools
+        if "Retrieval" in st.session_state.tool_names[0] and st.session_state.retriever_tool:
+            if st.session_state.retriever_tool not in tools:
+                tools.append(st.session_state.retriever_tool)
+
         llm = get_chat_model(model, temperature, [StreamHandler(st.empty())])
         if llm is None:
             st.error(f"Unsupported model: {model}", icon="🚨")
@@ -236,26 +238,32 @@ def run_agent(
 
         history_query = {"chat_history": chat_history, "input": query}
         
+        # Generate message content
         message_with_no_image = st.session_state.chat_prompt.invoke(history_query)
         message_content = message_with_no_image.messages[0].content
 
         if image_urls:
+            # Handle images if provided
             generated_text = process_with_images(llm, message_content, image_urls)
             human_message = HumanMessage(
                 content=query, additional_kwargs={"image_urls": image_urls}
             )
         elif tools:
+            # Use tools for query execution
             generated_text = process_with_tools(
                 llm, tools, agent_type, st.session_state.agent_prompt, history_query
             )
             human_message = HumanMessage(content=query)
         else:
+            # Fall back to basic query execution without tools
             generated_text = llm.invoke(message_with_no_image).content
             human_message = HumanMessage(content=query)
 
+        # Convert response into plain text
         if isinstance(generated_text, list):
             generated_text = generated_text[0]["text"]
 
+        # Update conversation history
         st.session_state.history.append(human_message)
         st.session_state.history.append(AIMessage(content=generated_text))
 
@@ -266,6 +274,7 @@ def run_agent(
         return None
 
 
+
 def openai_create_image(
     description: str, model: str="dall-e-3", size: str="1024x1024"
 ) -> Optional[str]: