Update app.py

app.py

@@ -14,6 +14,24 @@ from huggingface_hub.utils import build_hf_headers, get_session, hf_raise_for_st
 
 # Removed the debugging print that attempts to read GOOGLE_API_KEY from environment
 
+# --- Define Gemini Model Information ---
+# Dictionary mapping internal model name to (Display Name, Description)
+GEMINI_MODELS = {
+    "gemini-1.5-flash": ("Gemini 1.5 Flash", "Fast and versatile performance across a diverse variety of tasks."),
+    "gemini-1.5-pro": ("Gemini 1.5 Pro", "Complex reasoning tasks requiring more intelligence."),
+    "gemini-1.5-flash-8b": ("Gemini 1.5 Flash 8B", "High volume and lower intelligence tasks."),
+    "gemini-2.0-flash": ("Gemini 2.0 Flash", "Next generation features, speed, thinking, realtime streaming, and multimodal generation."),
+    "gemini-2.0-flash-lite": ("Gemini 2.0 Flash-Lite", "Cost efficiency and low latency."),
+    # Note: Preview models might have shorter lifespans or different capabilities
+    # "gemini-2.5-flash-preview-04-17": ("Gemini 2.5 Flash Preview (04-17)", "Adaptive thinking, cost efficiency."),
+    # "gemini-2.5-pro-preview-03-25": ("Gemini 2.5 Pro Preview (03-25)", "Enhanced thinking and reasoning, multimodal understanding, advanced coding, and more."),
+}
+
+# Create the list of choices for the Gradio Radio component
+# Format is (Display Name, Internal Name)
+GEMINI_MODEL_CHOICES = [(display_name, internal_name) for internal_name, (display_name, description) in GEMINI_MODELS.items()]
+# Define the default model to be selected
+DEFAULT_GEMINI_MODEL = "gemini-1.5-flash" # Ensure this key exists in GEMINI_MODELS
 
 # --- Helper functions for Hugging Face integration ---
 
@@ -66,7 +84,7 @@ def upload_file_to_space_action(
     profile: gr.OAuthProfile,
     token: gr.OAuthToken
 ) -> None:
-    """Uploads a file to a Hugging Face Space repository."""
+    """Uploads a file to a Huging Face Space repository."""
     if not (profile and token and repo_id):
         raise ValueError("Hugging Face profile, token, or repo_id is missing.")
     try:
@@ -149,11 +167,19 @@ def configure_gemini(api_key: str | None, model_name: str | None) -> str:
         # This will raise an exception if the key is invalid or model not found
         genai.GenerativeModel(model_name).generate_content("ping", stream=False)
         # This message indicates the API call *for configuration check* was successful
-        return f"✅ Gemini configured successfully with **{model_name}**."
+        return f"✅ Gemini configured successfully with **{GEMINI_MODELS.get(model_name, ('Unknown Model', ''))[0]}**."
     except Exception as e:
         # This message indicates the API call *for configuration check* failed
         return f"❌ Error configuring Gemini: {e}"
 
+def get_model_description(model_name: str | None) -> str:
+    """Retrieves the description for a given model name."""
+    if model_name is None:
+        return "Select a model to see its description."
+    # Use .get with a default value to handle cases where the key might not be found
+    return GEMINI_MODELS.get(model_name, (model_name, "No description available."))[1]
+
+
 def call_gemini(prompt: str, api_key: str, model_name: str, use_grounding: bool = False) -> str:
     """Calls the Gemini API with a given prompt, optionally using grounding."""
     # This check is crucial - it will raise an error *before* the API call if prereqs aren't met
@@ -265,6 +291,11 @@ def wrapper_configure_gemini(prev_output, api_key: str | None, model_name: str |
 def wrapper_greet(prev_output):
      return greet()
 
+# Wrapper function for get_model_description when called in a .then() chain
+# It accepts the output of the previous function as the first arg and discards it.
+def wrapper_get_model_description(prev_output, model_name: str | None) -> str:
+    return get_model_description(model_name)
+
 
 # This is the main generator function for the workflow, triggered by the 'Send' button
 # NOTE: This function MUST accept ALL state variables as inputs that it might need to modify or pass through.
@@ -895,8 +926,8 @@ with gr.Blocks(title="AI-Powered HF Space App Builder") as ai_builder_tab:
     hf_token     = gr.State(None)
     # Initialize gemini_api_key_state to empty string
     gemini_api_key_state   = gr.State("")  # start with no key
-    # Initialize gemini_model_state
-    gemini_model_state     = gr.State("gemini-1.5-flash") # Default selected model
+    # Initialize gemini_model_state with the default model key
+    gemini_model_state     = gr.State(DEFAULT_GEMINI_MODEL) # Default selected model
 
     repo_id      = gr.State(None) # Stores the ID of the created Space
     workflow     = gr.State(STATE_IDLE) # Stores the current state of the AI workflow
@@ -932,16 +963,18 @@ with gr.Blocks(title="AI-Powered HF Space App Builder") as ai_builder_tab:
 
             # Define model_selector before it's used in its change handler
             model_selector = gr.Radio(
-                choices=[
-                    ("Gemini 1.5 Flash", "gemini-1.5-flash"),
-                    ("Gemini 1.5 Pro", "gemini-1.5-pro"),
-                    ("Gemini 1.0 Pro", "gemini-1.0-pro"),
-                ],
-                value="gemini-1.5-flash", # Default selection
+                # Use the list of choices generated from the GEMINI_MODELS dictionary
+                choices=GEMINI_MODEL_CHOICES,
+                value=DEFAULT_GEMINI_MODEL, # Default selection using the key
                 label="Select model",
                 interactive=True
             )
 
+            # Add a markdown field to display the model description
+            # Initialize with the description of the default model
+            model_description_text = gr.Markdown(get_model_description(DEFAULT_GEMINI_MODEL))
+
+
             # Define grounding checkbox before its change handler
             use_grounding_checkbox = gr.Checkbox(
                 label="Enable Grounding with Google Search",
@@ -1012,7 +1045,7 @@ with gr.Blocks(title="AI-Powered HF Space App Builder") as ai_builder_tab:
         inputs=[gemini_input],
         outputs=[gemini_api_key_state] # This output becomes the implicit first arg for the .then() chain
     ).then(
-        # Wrap configure_gemini because it's in a .then() chain and receives the output of the prior step
+        # Configure Gemini using the updated state variables
         wrapper_configure_gemini, # Use the wrapper
         inputs=[gemini_api_key_state, gemini_model_state], # Explicitly pass the required states
         outputs=[gemini_status] # Update Gemini status display
@@ -1024,13 +1057,18 @@ with gr.Blocks(title="AI-Powered HF Space App Builder") as ai_builder_tab:
         outputs=send_button_update_output
     )
 
-    # Handle Gemini Model Selector change: Update model state -> Configure Gemini status -> Update send button state
+    # Handle Gemini Model Selector change: Update model state -> Update description -> Configure Gemini status -> Update send button state
     model_selector.change(
         lambda m: m, # Updates gemini_model_state
         inputs=[model_selector],
-        outputs=[gemini_model_state] # This output becomes the implicit first arg for the .then() chain
+        outputs=[gemini_model_state] # This output becomes the implicit first arg for the next .then() in this chain
+    ).then(
+        # Update the model description display
+        wrapper_get_model_description, # Use the wrapper
+        inputs=[gemini_model_state], # Get the new state value
+        outputs=[model_description_text] # Update description UI
     ).then(
-        # Wrap configure_gemini because it's in a .then() chain
+        # Configure Gemini using the updated state variables
         wrapper_configure_gemini, # Use the wrapper
         inputs=[gemini_api_key_state, gemini_model_state], # Explicitly pass the required states
         outputs=[gemini_status] # Update Gemini status display
@@ -1107,10 +1145,16 @@ with gr.Blocks(title="AI-Powered HF Space App Builder") as ai_builder_tab:
         # Action 3: After initial load checks, update the button state based on initial states
         # check_send_button_ready signature now handles the implicit previous output + explicit inputs
         check_send_button_ready,
-        inputs=send_button_interactive_binding_inputs, # Pass all 4 prerequisite states
+        inputs=send_button_interactive_binding_inputs,
         outputs=send_button_update_output, # Update the send button. This output becomes implicit first arg for next .then()
     ).then(
-        # Action 4: Add the initial welcome message to the chat history
+        # Action 4: Update the model description text based on the default selected model
+        # Use the wrapper because it's in a .then() chain
+        wrapper_get_model_description,
+        inputs=[gemini_model_state], # Get the default model name from state
+        outputs=[model_description_text] # Update description UI
+    ).then(
+        # Action 5: Add the initial welcome message to the chat history
         # Wrap greet because it's in a .then() chain and receives the output of the prior step (check_send_button_ready)
         wrapper_greet, # Use the wrapper
         inputs=None, # Greet takes no explicit inputs