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README.md

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----
-title: RPS Game
-emoji: 🌖
-colorFrom: yellow
-colorTo: blue
-sdk: gradio
-sdk_version: 5.29.0
-app_file: app.py
-pinned: false
-license: mit
-short_description: a rps game against AI
----
+# Rock Paper Scissors - Simple Demo
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+Play Rock Paper Scissors against a random AI!
+
+- Click one of the buttons (Rock, Paper, Scissors) to make your move.
+- The result of the round and the running score for this session will be displayed below.
+
+This is a basic demo built with Gradio and deployed on Hugging Face Spaces.

RockPaperScissor/models/__init__.py

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+from .random_ai import RandomAI
+
+__all__ = ['RandomAI'] # Expose only RandomAI for this demo

RockPaperScissor/models/random_ai.py

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+import random
+from typing import Dict, Any, Tuple, Optional
+
+class RandomAI:
+    """
+    AI that makes random moves. Simple version for Gradio demo.
+    """
+    def __init__(self):
+        self.possible_moves = ["rock", "paper", "scissors"]
+
+    def make_move(self, model_state: Optional[Dict[str, Any]] = None) -> Tuple[str, Dict[str, Any]]:
+        """
+        Makes a random move. Ignores model_state in this simple version.
+
+        Args:
+            model_state (dict, optional): Not used in this strategy.
+
+        Returns:
+            tuple[str, dict]: A random choice and an empty state dictionary.
+        """
+        ai_choice = random.choice(self.possible_moves)
+        # Return the move and an empty dictionary as the state (since it's stateless)
+        return ai_choice, {}

app.py

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+import gradio as gr
+from RockPaperScissor.models import RandomAI # Import the AI model
+
+# --- Initialize AI ---
+ai_model = RandomAI()
+
+# --- Helper Function ---
+def _determine_winner(player_move, ai_move):
+    """Determines the winner and returns a result code and message."""
+    if player_move == ai_move:
+        return "draw", f"It's a draw! (Both chose {player_move})"
+    elif (player_move == "rock" and ai_move == "scissors") or \
+         (player_move == "paper" and ai_move == "rock") or \
+         (player_move == "scissors" and ai_move == "paper"):
+        return "player_win", f"You win! ({player_move} beats {ai_move})"
+    else:
+        return "ai_win", f"AI wins! ({ai_move} beats {player_move})"
+
+# --- Main Gradio Function ---
+def play_round(player_choice, current_stats):
+    """
+    Handles one round of the game.
+    Updates stats stored in the Gradio state.
+    """
+    print(f"Player chose: {player_choice}") # Optional: for debugging in Space logs
+    print(f"Current stats before round: {current_stats}")
+
+    # Get AI's move (state is ignored by RandomAI)
+    ai_choice, _ = ai_model.make_move()
+    print(f"AI chose: {ai_choice}")
+
+    # Determine winner
+    result_code, result_message = _determine_winner(player_choice, ai_choice)
+
+    # Update stats (modify the dictionary directly)
+    if result_code == "player_win":
+        current_stats["wins"] += 1
+    elif result_code == "ai_win":
+        current_stats["losses"] += 1
+    else:
+        current_stats["draws"] += 1
+
+    print(f"Current stats after round: {current_stats}")
+
+    # Format output strings
+    full_result_message = f"You chose: {player_choice}\nAI chose: {ai_choice}\n\n{result_message}"
+    stats_string = f"Wins: {current_stats['wins']} | Losses: {current_stats['losses']} | Draws: {current_stats['draws']}"
+
+    # Return updated components AND the modified state dictionary
+    return full_result_message, stats_string, current_stats
+
+# --- Build Gradio Interface ---
+with gr.Blocks(title="Rock Paper Scissors Demo") as demo:
+    gr.Markdown("# Rock Paper Scissors - Simple Demo")
+    gr.Markdown("Play against a Random AI. Choose your move:")
+
+    # State to store session scores
+    session_state = gr.State(value={"wins": 0, "losses": 0, "draws": 0})
+
+    with gr.Row():
+        rock_btn = gr.Button("🪨 Rock")
+        paper_btn = gr.Button("📄 Paper")
+        scissors_btn = gr.Button("✂️ Scissors")
+
+    result_output = gr.Textbox(label="Round Result", lines=3) # Use Textbox for multi-line
+    stats_output = gr.Label(label="Session Score")
+
+    # --- Connect Buttons to Function ---
+    # Use lambda functions to pass the specific choice string
+    rock_btn.click(
+        fn=play_round,
+        inputs=[gr.Textbox("rock", visible=False), session_state], # Pass "rock" implicitly
+        outputs=[result_output, stats_output, session_state] # Update outputs AND state
+    )
+    paper_btn.click(
+        fn=play_round,
+        inputs=[gr.Textbox("paper", visible=False), session_state], # Pass "paper" implicitly
+        outputs=[result_output, stats_output, session_state]
+    )
+    scissors_btn.click(
+        fn=play_round,
+        inputs=[gr.Textbox("scissors", visible=False), session_state], # Pass "scissors" implicitly
+        outputs=[result_output, stats_output, session_state]
+    )
+
+# --- Launch the App ---
+demo.launch() # share=True creates a public link when running locally

pyproject.toml

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+[project]
+name = "rps-simple-demo"
+version = "0.1.0"
+description = "Simple Rock Paper Scissors Gradio demo for Hugging Face Spaces"
+authors = [
+    {name = "Your Name",email = "[email protected]"}
+]
+readme = "README.md"
+requires-python = "^3.10"
+dependencies = [
+    "gradio (>=5.29.0,<6.0.0)"
+]
+
+
+[build-system]
+requires = ["poetry-core>=2.0.0,<3.0.0"]
+build-backend = "poetry.core.masonry.api"

requirements.txt

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+gradio