Update app.py

app.py

@@ -1,34 +1,78 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
 
+# --- CONFIGURATION ---
+# We use the Instruct version of the 1B model as it follows rules best
+MODEL_ID = "meta-llama/Llama-3.2-1B-Instruct"
+
+# --- THE RIDDLES (DATABASE) ---
+# Each riddle has a public 'scenario' and a hidden 'solution'.
+RIDDLES = {
+    "The Dead Man": {
+        "scenario": "A man lies dead in a field. Next to him is an unopened package. There are no footprints around him. How did he die?",
+        "solution": "The man jumped from a plane. The package was his parachute, which failed to open."
+    },
+    "The Barman": {
+        "scenario": "A man walks into a bar and asks for a glass of water. The barman pulls out a gun and points it at him. The man says 'Thank you' and walks out. Why?",
+        "solution": "The man had the hiccups. The barman used the gun to scare him, curing the hiccups. The man was thankful."
+    },
+    "The Cabin": {
+        "scenario": "Two men are in a cabin in the woods. One is dead. The cabin did not burn down, but the dead man is charred. How happened?",
+        "solution": "The cabin is the cabin of a crashed airplane. The man died in the crash/fire."
+    },
+    "The Suitcase": {
+        "scenario": "A woman opens her suitcase and finds a dead man inside. She is not arrested or afraid. Why?",
+        "solution": "The 'suitcase' is actually a coffin. The woman is attending a funeral."
+    }
+}
 
 def respond(
     message,
     history: list[dict[str, str]],
-    system_message,
+    system_message, # We will ignore the user input for this and build our own
     max_tokens,
     temperature,
     top_p,
     hf_token: gr.OAuthToken,
+    selected_riddle, # The dropdown input
 ):
     """
-    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
+    This function handles the game logic. It injects the hidden solution 
+    into the system prompt based on the user's selection.
     """
-    client = InferenceClient(token=hf_token.token, model="openai/gpt-oss-20b")
+    client = InferenceClient(token=hf_token.token, model=MODEL_ID)
 
-    messages = [{"role": "system", "content": system_message}]
+    # 1. Get the current riddle data
+    current_game = RIDDLES[selected_riddle]
+    
+    # 2. Construct the Strict Game Master Prompt
+    # This is where the "Context Learning" happens. We teach the model the rules in-context.
+    game_master_prompt = (
+        f"You are the Game Master of a lateral thinking puzzle. "
+        f"CURRENT PUZZLE SCENARIO: '{current_game['scenario']}' "
+        f"HIDDEN SOLUTION (User does not know this!): '{current_game['solution']}' "
+        f"\n\n"
+        f"RULES FOR YOU:"
+        f"1. The user will ask questions to figure out the solution."
+        f"2. You must analyze their question against the HIDDEN SOLUTION."
+        f"3. Answer ONLY with 'Yes', 'No', or 'Irrelevant'. "
+        f"4. If the user guesses the solution correctly, say 'CORRECT! You solved it: [Explain solution]'."
+        f"5. Do NOT give hints. Do NOT explain your 'Yes/No' answers."
+    )
 
+    # 3. Build message history
+    messages = [{"role": "system", "content": game_master_prompt}]
     messages.extend(history)
-
     messages.append({"role": "user", "content": message})
 
     response = ""
 
+    # 4. Stream the response
     for message in client.chat_completion(
         messages,
         max_tokens=max_tokens,
         stream=True,
-        temperature=temperature,
+        temperature=temperature, # Low temp = more strict adherence to Yes/No
         top_p=top_p,
     ):
         choices = message.choices
@@ -40,31 +84,56 @@ def respond(
         yield response
 
 
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-chatbot = gr.ChatInterface(
-    respond,
-    type="messages",
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
-)
+# --- UI SETUP ---
+# We use Blocks to add the Dropdown menu cleanly above the chat
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    
+    # Header
+    gr.Markdown("# 🕵️ The Yes/No Detective")
+    gr.Markdown(
+        "**Instructions:** I am thinking of a strange situation. "
+        "Ask me questions to figure out the truth! I can only answer **Yes**, **No**, or **Irrelevant**."
+    )
+
+    with gr.Row():
+        # The Dropdown to select the "Level"
+        riddle_select = gr.Dropdown(
+            choices=list(RIDDLES.keys()), 
+            value="The Dead Man", 
+            label="Select a Mystery Case", 
+            interactive=True
+        )
+    
+    # Display the current scenario description dynamically
+    scenario_display = gr.Textbox(
+        label="The Scenario (Clue)", 
+        value=RIDDLES["The Dead Man"]["scenario"],
+        interactive=False 
+    )
 
-with gr.Blocks() as demo:
+    # Function to update the text box when dropdown changes
+    def update_scenario(choice):
+        return RIDDLES[choice]["scenario"]
+    
+    riddle_select.change(fn=update_scenario, inputs=riddle_select, outputs=scenario_display)
+
+    # The Chat Interface
+    # Note: We hide the system message input because we hardcode it in the function
+    chatbot = gr.ChatInterface(
+        respond,
+        type="messages",
+        additional_inputs=[
+            gr.Textbox(value="Game Master", visible=False), # Hidden system prompt placeholder
+            gr.Slider(minimum=1, maximum=512, value=100, step=1, label="Max tokens", visible=False),
+            gr.Slider(minimum=0.1, maximum=2.0, value=0.2, step=0.1, label="Temperature"), # Low temp for precision
+            gr.Slider(minimum=0.1, maximum=1.0, value=0.9, step=0.05, label="Top-p"),
+            riddle_select # Pass the selected riddle to the function
+        ],
+    )
+    
+    # Sidebar for login
     with gr.Sidebar():
         gr.LoginButton()
-    chatbot.render()
-
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()