Update app.py

app.py

@@ -7,14 +7,20 @@ from sentence_transformers import SentenceTransformer, CrossEncoder
 from research_agent.config import AgentConfig
 from research_agent.agent import get_clarifying_questions, research_and_plan, write_report_stream
 
-# --- CSS for a professional, ChatGPT-inspired look ---
+
+google_key = os.getenv("GOOGLE_API_KEY")
+tavily_key = os.getenv("TAVILY_API_KEY")
+
+if not google_key or not tavily_key:
+    raise ValueError("API keys not found.")
+
+
+
 CSS = """
 body, .gradio-container { font-family: 'Inter', sans-serif; background-color: #343541; color: #ECECEC; }
 .gradio-container { max-width: 800px !important; margin: auto !important; padding-top: 2rem !important;}
 h1 { text-align: center; font-weight: 700; font-size: 2.5em; color: white; }
 .sub-header { text-align: center; color: #C5C5D2; margin-bottom: 2rem; font-size: 1.1em; }
-.accordion { background-color: #40414F; border: 1px solid #565869 !important; border-radius: 8px !important; }
-.accordion .gr-button { background-color: #4B4C5A; color: white; }
 #chatbot { box-shadow: none !important; border: none !important; background-color: transparent !important; }
 .message-bubble { background: #40414F !important; border: 1px solid #565869 !important; color: #ECECEC !important;}
 .message-bubble.user { background: #343541 !important; border: none !important; }
@@ -29,14 +35,15 @@ footer { display: none !important; }
 
 # --- Model Initialization ---
 config = AgentConfig()
+
 writer_model, planner_model, embedding_model, reranker, tavily_client = None, None, None, None, None
-IS_PROCESSING = False # Add a lock to prevent concurrent runs
+IS_PROCESSING = False
 
-def initialize_models(google_key, tavily_key):
+def initialize_models():
+    """Initializes all the models and clients using keys from environment variables."""
     global writer_model, planner_model, embedding_model, reranker, tavily_client, IS_PROCESSING
-    if not google_key or not tavily_key:
-        raise gr.Error("API keys are required.")
     try:
+
         genai.configure(api_key=google_key)
         tavily_client = TavilyClient(api_key=tavily_key)
         writer_model = genai.GenerativeModel(config.WRITER_MODEL)
@@ -44,50 +51,54 @@ def initialize_models(google_key, tavily_key):
         embedding_model = SentenceTransformer('all-MiniLM-L6-v2', device='cpu')
         reranker = CrossEncoder('cross-encoder/ms-marco-MiniLM-L-6-v2', device='cpu')
     except Exception as e:
-        raise gr.Error(f"Failed to initialize models. Error: {str(e)}")
-    IS_PROCESSING = False # Ensure lock is free on initialization
+        # This error will be displayed in the Hugging Face logs
+        print(f"FATAL: Failed to initialize models. Error: {str(e)}")
+        # Raise an exception to stop the app from running incorrectly
+        raise gr.Error(f"Failed to initialize models. Please check the logs. Error: {str(e)}")
+    IS_PROCESSING = False
+    print("Models and clients initialized successfully.")
+
+# --- 3. Initialize models on application startup ---
+initialize_models()
 
 # --- Gradio Application Logic ---
 with gr.Blocks(css=CSS, theme=gr.themes.Base()) as app:
     gr.Markdown("<h1>Mini DeepSearch Agent</h1>")
     gr.Markdown("<p class='sub-header'>Your AI partner for in-depth research and analysis.</p>")
 
-    agent_state = gr.State("INITIAL") 
+    agent_state = gr.State("INITIAL")
     initial_topic_state = gr.State("")
 
-    with gr.Accordion("API & Settings", open=True, elem_classes="accordion") as settings_accordion:
-        with gr.Row():
-            google_api_key_input = gr.Textbox(label="Google API Key", type="password", placeholder="Enter Google AI API Key", scale=2)
-            tavily_api_key_input = gr.Textbox(label="Tavily API Key", type="password", placeholder="Enter Tavily Search API Key", scale=2)
-            init_button = gr.Button("Initialize Agent", scale=1)
-    
+
     chatbot = gr.Chatbot(
         elem_id="chatbot",
         bubble_full_width=False,
         height=500,
-        visible=False
+        # --- 5. Make the chatbot visible from the start ---
+        visible=True,
+        value=[(None, "Agent is ready. What would you like to research?")]
     )
-    
+
     with gr.Row(elem_id="chat-input-container"):
-        chat_input = gr.Textbox(placeholder="What would you like to research?", interactive=False, visible=False, show_label=False, scale=8)
-        submit_button = gr.Button("Submit", elem_id="submit-button", visible=False, scale=1)
-
-    def handle_initialization(google_key, tavily_key):
-        initialize_models(google_key, tavily_key)
-        return {
-            chatbot: gr.update(visible=True, value=[(None, "Agent initialized. Please enter your research topic to begin.")]),
-            chat_input: gr.update(interactive=True, visible=True),
-            submit_button: gr.update(visible=True),
-            settings_accordion: gr.update(open=False)
-        }
+        chat_input = gr.Textbox(
+            placeholder="What would you like to research?",
+            # --- 6. Make the input box interactive and visible from the start ---
+            interactive=True,
+            visible=True,
+            show_label=False,
+            scale=8
+        )
+        submit_button = gr.Button("Submit", elem_id="submit-button", visible=True, scale=1)
+
+    # The handle_initialization function is no longer needed.
 
     def chat_step_wrapper(user_input, history, current_agent_state, topic_state):
         """A wrapper to manage the processing lock."""
         global IS_PROCESSING
         if IS_PROCESSING:
             print("Ignoring duplicate request while processing.")
-            if False: # This makes the function a generator
-                yield
+            # This is a generator, so we must yield something. An empty yield is fine.
+            if False: yield
             return
 
         IS_PROCESSING = True
@@ -107,7 +118,7 @@ with gr.Blocks(css=CSS, theme=gr.themes.Base()) as app:
     def chat_step(user_input, history, current_agent_state, topic_state):
         history = history or []
         history.append((user_input, None))
-        
+
         if current_agent_state == "INITIAL":
             yield history, "CLARIFYING", user_input, gr.update(interactive=False, placeholder="Thinking...")
             questions = get_clarifying_questions(planner_model, user_input)
@@ -118,35 +129,26 @@ with gr.Blocks(css=CSS, theme=gr.themes.Base()) as app:
             thinking_message = "Got it. Generating your full research report. This will take a moment..."
             history[-1] = (user_input, thinking_message)
             yield history, "GENERATING", topic_state, gr.update(interactive=False, placeholder="Generating...")
-            
+
             try:
                 plan = research_and_plan(config, planner_model, tavily_client, topic_state, user_input)
                 report_generator = write_report_stream(config, writer_model, tavily_client, embedding_model, reranker, plan)
-                
+
                 stream_content = ""
                 for update in report_generator:
                     stream_content = update
                     history[-1] = (user_input, stream_content)
                     yield history, "GENERATING", topic_state, gr.update(interactive=False)
-                
+
                 yield history, "INITIAL", "", gr.update(interactive=True, placeholder="Research complete. What's the next topic?")
-            
+
             except Exception as e:
                 error_message = f"An error occurred: {str(e)}"
                 history.append((None, error_message))
                 yield history, "INITIAL", "", gr.update(interactive=True, placeholder="Let's try again. What's the topic?")
 
     # --- Event Listeners ---
-    # This section is rewritten to prevent duplicate triggers.
-    
-    init_button.click(
-        fn=handle_initialization,
-        inputs=[google_api_key_input, tavily_api_key_input],
-        outputs=[chatbot, chat_input, submit_button, settings_accordion]
-    )
-    
-    # We define a single submission event and trigger it from both the button and the textbox.
-    # It now calls the wrapper function to handle the processing lock.
+
     submit_event = submit_button.click(
         fn=chat_step_wrapper,
         inputs=[chat_input, chatbot, agent_state, initial_topic_state],
@@ -169,4 +171,4 @@ with gr.Blocks(css=CSS, theme=gr.themes.Base()) as app:
         queue=False
     )
 
-app.launch(debug=True) 
+app.launch(debug=True)