Always keep the dropdown because it still determines the question types

app.py

@@ -1,7 +1,7 @@
 import gradio as gr
 import game
 import ai
-
+import bee
 
 
 
@@ -152,6 +152,8 @@ examples = examples_states
 # Create wrapper function that handles both local and cloud modes
 # Local mode wrapper function
 def custom_respond(message, history, game_mode_selection, game_type_selection):
+    if game_type_selection == game.TYPE_GEOGRAPHY_BEE:
+        return bee.respond(message, history, game_mode_selection)
     return respond(message, history, "", 4000, 0.3, 0.6, game_mode_selection, None)
 
 def get_examples_for_mode(mode):
@@ -180,7 +182,7 @@ with gr.Blocks() as demo:
         value=game.MODE_STATES,
         label="Game Mode",
         info="Choose what type of location to guess",
-        visible=False
+        visible=True
     )
     
     # ChatInterface without built-in examples
@@ -210,7 +212,7 @@ with gr.Blocks() as demo:
     def update_examples_visibility(game_type):
         is_visible = (game_type == game.TYPE_TWENTY_QUESTIONS)
         return (
-            gr.Dropdown(visible=is_visible),  # mode_dropdown
+            gr.Dropdown(visible=True),  # mode_dropdown
             gr.Markdown(visible=is_visible),   # examples_header
             gr.Dataset(visible=is_visible)     # examples_dataset
         )

bee.py

@@ -0,0 +1,92 @@
+import gradio as gr
+import game 
+from app import format_game_result
+def respond(
+    message,
+    history: list[dict[str, str]],
+    system_message,
+    max_tokens,
+    temperature,
+    top_p,
+    game_mode_selection,
+    hf_token: gr.OAuthToken | None = None,
+):
+    """
+    For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
+    """
+
+    # If this is the start of a new conversation (empty history), generate a new country/state
+    if not history:
+        game.guess_number = 0
+        if game_mode_selection == game.MODE_STATES:
+            game.current_system = game.get_system_message(game.MODE_STATES)
+            print(f"🔍 DEBUG - New session started, selected state: {game.selected_country}")
+        else:
+            game.current_system = game.get_system_message(game.MODE_COUNTRIES)
+            print(f"🔍 DEBUG - New session started, selected country: {game.selected_country}")
+
+    game.guess_number += 1
+    messages = [{"role": "system", "content": game.current_system + str(game.guess_number)}]
+    messages.append({"role": "user", "content": message})
+
+    # Debug: Calculate approximate input token count
+    total_input_chars = sum(len(str(msg.get("content", ""))) for msg in messages)
+    estimated_input_tokens = total_input_chars // 4  # Rough approximation: 4 chars per token
+    print(f"🔍 DEBUG - Estimated input tokens: {estimated_input_tokens}")
+    print(f"🔍 DEBUG - Messages count: {len(messages)}")
+    print(f"🔍 DEBUG - Max tokens setting: {max_tokens}")
+    
+    # Debug: Show each message type and length
+    for i, msg in enumerate(messages):
+        role = msg.get("role", "unknown")
+        content = str(msg.get("content", ""))
+        print(f"🔍 DEBUG - Message {i+1} ({role}): {len(content)} chars")
+        if role == "system":
+            print(f"🔍 DEBUG - System message preview: ...{content[-100:]}")
+        elif role == "user":
+            print(f"🔍 DEBUG - User message: {content}")
+        elif role == "assistant":
+            print(f"🔍 DEBUG - Assistant message: {content[:50]}...")
+
+   
+
+    response = ""
+    output_token_count = 0
+
+    try:
+        for message_chunk in ai.client.chat_completion(
+            messages,
+            stream=True,
+            response_format={"type": "text"},
+        ):
+            choices = message_chunk.choices
+            token = ""
+            if len(choices) and choices[0].delta.content:
+                token = choices[0].delta.content
+                output_token_count += 1
+
+            response += token
+
+        # Debug: Show output token statistics
+        estimated_output_tokens = len(response) // 4  # Rough approximation
+        print(f"🔍 DEBUG - Output token chunks received: {output_token_count}")
+        print(f"🔍 DEBUG - Estimated output tokens (by chars): {estimated_output_tokens}")
+        print(f"🔍 DEBUG - Response length: {len(response)} characters")
+        print(f"🔍 DEBUG - Raw response: {response}")
+
+        # Clean the response to remove unwanted artifacts
+        response = ai.clean_response(response)
+        print(f"🔍 DEBUG - Cleaned response: {response}")
+
+        # Check if this is a game end response and format it nicely
+        if "The country was" in response or "The state was" in response:
+            print(f"🔍 DEBUG - Game end detected! Location extracted: {game.selected_country}")
+            return format_game_result(response)
+        elif game.guess_number == 20:
+            print(f"🔍 DEBUG - Maximum guesses reached: {game.guess_number}")
+            return format_game_result(response)
+        else:
+            print("🔍 DEBUG - Regular response (no game end)")
+            return response
+    except Exception as e:
+        return f"Error during inference: {str(e)}"