Add function calling from modal

app.py

@@ -5,10 +5,29 @@ import gradio as gr
 from src.util.board_vis import colored_unicode_board
 from src.util.pgn_util import pgn_string_to_game, read_pgn
 from src.thinksqure_engine import ThinkSquareEngine
+from modal import Function
+import logging
+
+logging.basicConfig(level=logging.INFO)
+
+
+def get_best_move(fen: Optional[str] = None) -> str:
+    try:
+        modal_fn = Function.from_name("ThinkSquare-Backend", "get_best_move")
+        best_move_san = modal_fn.remote(fen)
+        logging.info("Best move retrieved from Modal function.")
+
+    except Exception as e:
+        logging.error(f"Error getting best move from Modal: {e}")
+
+        # Fallback to local engine if Modal function fails
+        best_move_san = ThinkSquareEngine.get_best_move(fen)
+
+    return best_move_san
 
 
 def annotate_pgn_file(
-    file, analysis_time_per_move: float = 0.1, style: Optional[str] = "expert"
+    file, depth_level: str = "standard", style: Optional[str] = "expert"
 ) -> str:
     """Annotate a chess game from a PGN file.
     This function takes a PGN file and annotates the chess game using an engine.
@@ -17,6 +36,13 @@ def annotate_pgn_file(
     """
     pgn_text = read_pgn(file.name)
 
+    if depth_level == "standard":
+        analysis_time_per_move = 0.1
+    elif depth_level == "deep":
+        analysis_time_per_move = 0.5
+    else:
+        analysis_time_per_move = 0.1
+
     annotated_game = annotate_pgn(
         pgn_text,
         analysis_time_per_move=analysis_time_per_move,
@@ -40,7 +66,7 @@ def suggest_move(fen: Optional[str] = None) -> str:
     if fen is None or fen == "" or fen.lower() == "none" or fen.lower() == "null":
         fen = None
 
-    best_move_san = ThinkSquareEngine.get_best_move(fen)
+    best_move_san = get_best_move(fen)
 
     return best_move_san
 
@@ -86,9 +112,19 @@ def annotate_pgn(
     except ValueError:
         raise ValueError("Analysis time must be a number.")
 
-    annotated_game = ThinkSquareEngine.annotate(
-        game, analysis_time=analysis_time_per_move, llm_character=style
-    )
+    # try Modal function first
+    try:
+        modal_fn = Function.from_name("ThinkSquare-Backend", "annotate")
+        annotated_game = modal_fn.remote(pgn_input, analysis_time_per_move, style)
+        logging.info("Annotated game using Modal function.")
+
+    except Exception as e:
+        logging.error(f"Error annotating PGN with Modal: {e}")
+
+        # Fallback to local engine if Modal function fails
+        annotated_game = ThinkSquareEngine.annotate(
+            game, analysis_time=analysis_time_per_move, llm_character=style
+        )
 
     return str(annotated_game)
 
@@ -146,11 +182,14 @@ def play_chess(
             - Pass the FEN string representing the board state prior to the user's last move.
             - Pass a move in long algebraic notation (e.g., "e4", "Nf3", "Bb5") for engine to play the next move.
 
+        About rendering:
+            - LLMs must use ascii as render_mode unless otherwise specified by user. While rendering ascii, LLMs must use monospaced font.
+
     Args:
         move: The move to play in long algebraic notation. If None, the engine will play a move.
         fen: The FEN string representing the board state prior to the user's last move. If None, the game starts from the initial position.
         draw_board: Whether to draw the board in ASCII/Unicode/svg format. Defaults to True.
-        render_mode: The rendering mode for the board. Defaults to "ascii". This can be "ascii", "svg", or "unicode". LLMs should default to "ascii".
+        render_mode: The rendering mode for the board. Defaults to "ascii". This can be "ascii", "svg", or "unicode".
 
     Returns:
         The best move played by the engine, the updated board state in FEN notation, and  a board representation if draw_board is True else None.
@@ -171,7 +210,7 @@ def play_chess(
 
         assert fen is not None, "FEN after move should not be None"
 
-    bestmove_san = ThinkSquareEngine.get_best_move(fen)
+    bestmove_san = get_best_move(fen)
     fen_after_move = ThinkSquareEngine.get_fen_after_move(bestmove_san, fen)
 
     if draw_board:
@@ -228,12 +267,24 @@ with gr.Blocks(title="ThinkSquare") as app:
 
         gr.Markdown("### Analyze and Annotate a PGN File")
         pgn_file = gr.File(label="Upload PGN", file_types=[".pgn"])
-        analysis_time = gr.Textbox(
-            label="Analysis Time per Move (seconds)", value="0.1"
+
+        analysis_depth = gr.Radio(
+            label="Analysis Depth", choices=["standard", "deep"], value="standard"
         )
+
         style_dropdown = gr.Dropdown(
             label="Style",
-            choices=["expert", "novice", "jarvis", "natural"],
+            choices=[
+                "expert",
+                "novice",
+                "jarvis",
+                "natural",
+                "yoda",
+                "oracle",
+                "bored guy",
+                "angry granny",
+                "Sheldon Cooper (The Big Bang Theory)",
+            ],
             value="expert",
         )
 
@@ -253,7 +304,7 @@ with gr.Blocks(title="ThinkSquare") as app:
 
         analyze_btn.click(
             fn=annotate_pgn_file,
-            inputs=[pgn_file, analysis_time, style_dropdown],
+            inputs=[pgn_file, analysis_depth, style_dropdown],
             outputs=annotated_pgn_file,
         )