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Update app.py
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app.py
CHANGED
@@ -8,17 +8,17 @@ import numpy as np
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model = Llama(
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model_path=hf_hub_download(
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repo_id=os.environ.get("REPO_ID", "Lyte/QuadConnect2.5-0.5B-
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filename=os.environ.get("MODEL_FILE", "unsloth.Q8_0.gguf"),
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)
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)
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SYSTEM_PROMPT = """You are a Connect Four player
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<reasoning>
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Explain your reasoning
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</reasoning>
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<move>
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The column
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</move>
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"""
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@@ -81,8 +81,8 @@ class ConnectFour:
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if self.board[row][col] != 0:
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col_letter = chr(ord('a') + col)
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row_num = str(6 - row) # Convert to 1-based indexing
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player = "X" if self.board[row][col] == 1 else "O"
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moves.append(f"{col_letter}{row_num}
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return ", ".join(moves)
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def parse_ai_move(self, move_str):
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@@ -146,7 +146,7 @@ def create_interface():
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padding: 0 15px;
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}
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#column-buttons button {
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margin: 0px
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}
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div.svelte-1nguped {
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display: block;
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@@ -163,7 +163,7 @@ def create_interface():
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status = gr.Markdown("Your turn! Click a button to drop your piece!", elem_id="ai-status")
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# Column buttons
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with gr.Group(elem_id="column-buttons"):
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col_buttons = []
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for i in range(7):
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btn = gr.Button(f"⬇️ {i+1}", scale=1)
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@@ -211,7 +211,9 @@ def create_interface():
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# AI move
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game.current_player = 2
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board_state = game.board_to_string()
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prompt = f"Current Board: {board_state}. Make a move."
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# Get AI response
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response = model.create_chat_completion(
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@@ -321,4 +323,4 @@ def render_board(board=None):
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# Launch the interface
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if __name__ == "__main__":
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interface = create_interface()
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interface.launch(
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model = Llama(
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model_path=hf_hub_download(
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repo_id=os.environ.get("REPO_ID", "Lyte/QuadConnect2.5-0.5B-v0.0.2b"),
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filename=os.environ.get("MODEL_FILE", "unsloth.Q8_0.gguf"),
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)
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)
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SYSTEM_PROMPT = """You are a Connect Four player. Connect Four is played on a 6x7 grid. Given the current board state, predict the next *column* to play in. Moves are specified by the column letter (a-g). Respond in the following format:
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<reasoning>
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Explain your reasoning, considering the board state and potential future moves.
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</reasoning>
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<move>
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The column letter (a-g) of your move.
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</move>
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"""
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if self.board[row][col] != 0:
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col_letter = chr(ord('a') + col)
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row_num = str(6 - row) # Convert to 1-based indexing
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#player = "X" if self.board[row][col] == 1 else "O"
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moves.append(f"{col_letter}{row_num}")#={player}")
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return ", ".join(moves)
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def parse_ai_move(self, move_str):
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padding: 0 15px;
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}
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#column-buttons button {
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margin: 0px 7px;
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}
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div.svelte-1nguped {
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display: block;
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status = gr.Markdown("Your turn! Click a button to drop your piece!", elem_id="ai-status")
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# Column buttons
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with gr.Group(elem_id="column-buttons", elem_classes=["fitter"]):
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col_buttons = []
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for i in range(7):
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btn = gr.Button(f"⬇️ {i+1}", scale=1)
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# AI move
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game.current_player = 2
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board_state = game.board_to_string()
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prompt = f"Current Board: {board_state}. Make a move."
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#print(prompt)
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# Get AI response
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response = model.create_chat_completion(
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# Launch the interface
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if __name__ == "__main__":
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interface = create_interface()
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interface.launch()
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