chore: Create Errors and update MongoDB

docker-compose.yml

@@ -6,10 +6,8 @@ services:
     container_name: games-api
     environment:
       - NODE_ENV=production
-      - REDIS_HOST=${REDIS_HOST:-redis}
-      - REDIS_PORT=${REDIS_PORT:-1118}
-      - REDIS_USERNAME=${REDIS_USERNAME:-admin}
-      - REDIS_PASSWORD=${REDIS_PASSWORD:-default}
+      - MONGODB=${MONGODB:-mongodb://username:password@host:port}
+      - BROKER_URL=${BROKER_URL:-ws://localhost:8070}
     restart: unless-stopped # options: always, unless-stopped, on-failure
     ports:
       - '8060:8060' # Expose port 8060 on the host

games_ai/doc.md

@@ -0,0 +1,39 @@
+# install
+
+brew update
+brew upgrade
+
+pip3 --version
+pip 21.2.4 from /Applications/Xcode.app/Contents/Developer/Library/Frameworks/Python3.framework/Versions/3.9/lib/python3.9/site-packages/pip (python 3.9)
+
+- pip3 install mlx
+
+# logs
+
+==> node@20
+node@20 is keg-only, which means it was not symlinked into /opt/homebrew,
+because this is an alternate version of another formula.
+
+If you need to have node@20 first in your PATH, run:
+echo 'export PATH="/opt/homebrew/opt/node@20/bin:$PATH"' >> /Users/pedrodarma/.zshrc
+
+For compilers to find node@20 you may need to set:
+export LDFLAGS="-L/opt/homebrew/opt/node@20/lib"
+export CPPFLAGS="-I/opt/homebrew/opt/node@20/include"
+==> ruby
+By default, binaries installed by gem will be placed into:
+/opt/homebrew/lib/ruby/gems/3.4.0/bin
+
+You may want to add this to your PATH.
+
+ruby is keg-only, which means it was not symlinked into /opt/homebrew,
+because macOS already provides this software and installing another version in
+parallel can cause all kinds of trouble.
+
+If you need to have ruby first in your PATH, run:
+echo 'export PATH="/opt/homebrew/opt/ruby/bin:$PATH"' >> /Users/pedrodarma/.zshrc
+
+For compilers to find ruby you may need to set:
+export LDFLAGS="-L/opt/homebrew/opt/ruby/lib"
+export CPPFLAGS="-I/opt/homebrew/opt/ruby/include"
+pedrodarma@Mini-Mini-Darma games-api %

games_ai/generate_dataset.py

@@ -0,0 +1,94 @@
+# print("Hello from games_ai/play.py")
+
+from pymongo import MongoClient
+import numpy as np
+import pandas as pd
+
+
+POSITION_MAP = {
+    "a0": 0, "a1": 1, "a2": 2,
+    "b0": 3, "b1": 4, "b2": 5,
+    "c0": 6, "c1": 7, "c2": 8,
+}
+
+def convert_games_to_samples():
+    client = MongoClient("mongodb://admin:G49vm222-3d02ksc!@192.168.15.17:27018/")
+    db = client["logs"]
+    # games = db["qtt_logs"].find({"status": "finished", "winner": {"$ne": None}})
+    games = db["qtt_logs"].find({"status": "finished", "type": {"$eq": "game_over_win"}})
+
+    samples = []
+
+    print("Converting games to samples...")
+    # print("Total games found:", games.total())
+
+    for game in games:
+        board = [0]*9
+        winner = game.get("winner")
+        x_id = game.get("playerXId")
+        o_id = game.get("playerOId")
+
+        # print(game)
+
+        x_moves = [POSITION_MAP[m] for m in game.get("playerXMoves", [])]
+        o_moves = [POSITION_MAP[m] for m in game.get("playerOMoves", [])]
+
+        # print("X moves:", x_moves)
+        # print("O moves:", o_moves)
+
+        board = [0]*9
+        for i in range(len(x_moves)):
+            board[x_moves[i]] = 1
+
+        for i in range(len(o_moves)):
+            board[o_moves[i]] = -1
+
+        state = board.copy()
+
+        print("Final board state:", state)
+
+        # # Reconstroi o jogo movimento a movimento
+        # for i in range(max(len(x_moves), len(o_moves))):
+        #     # Jogada do X
+        #     if i < len(x_moves):
+        #         move = x_moves[i]
+        #         state = board.copy()
+        #         samples.append({
+        #             "board": state,
+        #             "player": 1,
+        #             "move": move,
+        #             "winner": 1 if winner == x_id else -1
+        #         })
+        #         board[move] = 1
+
+        #     # Jogada do O
+        #     if i < len(o_moves):
+        #         move = o_moves[i]
+        #         state = board.copy()
+        #         samples.append({
+        #             "board": state,
+        #             "player": -1,
+        #             "move": move,
+        #             "winner": 1 if winner == o_id else -1
+        #         })
+        #         board[move] = -1
+
+    return samples
+
+# Exemplo de uso:
+if __name__ == "__main__":
+    samples = convert_games_to_samples()
+    print(samples[:5])  # mostra as 5 primeiras amostras
+
+    rows = []
+    for s in samples:
+        rows.append({
+            **{f"cell_{i}": v for i, v in enumerate(s["board"])},
+            "player": s["player"],
+            "move": s["move"],
+            "winner": s["winner"]
+        })
+
+    df = pd.DataFrame(rows)
+    df.to_csv("tictactoe_dataset.csv", index=False)
+    print("Dataset salvo com", len(df), "amostras")

games_ai/generate_dataset_copy copy.py

@@ -0,0 +1,75 @@
+# print("Hello from games_ai/play.py")
+
+from pymongo import MongoClient
+import numpy as np
+import pandas as pd
+
+
+POSITION_MAP = {
+    "a0": 0, "a1": 1, "a2": 2,
+    "b0": 3, "b1": 4, "b2": 5,
+    "c0": 6, "c1": 7, "c2": 8,
+}
+
+def convert_games_to_samples():
+    client = MongoClient("mongodb://admin:G49vm222-3d02ksc!@192.168.15.17:27018/")
+    db = client["logs"]
+    # games = db["qtt_logs"].find({"status": "finished"})
+    games = db["qtt_logs"].find({"status": "finished", "type": {"$eq": "game_over_win"}})
+
+    samples = []
+
+    for game in games:
+        board = [0]*9
+        winner = game.get("winner")
+        x_id = game.get("playerXId")
+        o_id = game.get("playerOId")
+
+        x_moves = [POSITION_MAP[m] for m in game.get("playerXMoves", [])]
+        o_moves = [POSITION_MAP[m] for m in game.get("playerOMoves", [])]
+
+        # Reconstroi o jogo movimento a movimento
+        for i in range(max(len(x_moves), len(o_moves))):
+            # Jogada do X
+            if i < len(x_moves):
+                move = x_moves[i]
+                state = board.copy()
+                samples.append({
+                    "board": state,
+                    "player": 1,
+                    "move": move,
+                    "winner": 1 if winner == x_id else -1
+                })
+                board[move] = 1
+
+            # Jogada do O
+            if i < len(o_moves):
+                move = o_moves[i]
+                state = board.copy()
+                samples.append({
+                    "board": state,
+                    "player": -1,
+                    "move": move,
+                    "winner": 1 if winner == o_id else -1
+                })
+                board[move] = -1
+
+    return samples
+
+# Exemplo de uso:
+if __name__ == "__main__":
+    samples = convert_games_to_samples()
+    print(samples[:5])  # mostra as 5 primeiras amostras
+
+    rows = []
+    for s in samples:
+        rows.append({
+            **{f"cell_{i}": v for i, v in enumerate(s["board"])},
+            "player": s["player"],
+            "move": s["move"],
+            "winner": s["winner"]
+        })
+
+    df = pd.DataFrame(rows)
+    df.to_csv("tictactoe_dataset.csv", index=False)
+    print("Dataset salvo com", len(df), "amostras")

games_ai/generate_dataset_copy.py

@@ -0,0 +1,75 @@
+# print("Hello from games_ai/play.py")
+
+from pymongo import MongoClient
+import numpy as np
+import pandas as pd
+
+
+POSITION_MAP = {
+    "a0": 0, "a1": 1, "a2": 2,
+    "b0": 3, "b1": 4, "b2": 5,
+    "c0": 6, "c1": 7, "c2": 8,
+}
+
+def convert_games_to_samples():
+    client = MongoClient("mongodb://admin:G49vm222-3d02ksc!@192.168.15.17:27018/")
+    db = client["logs"]
+    # games = db["qtt_logs"].find({"status": "finished"})
+    games = db["qtt_logs"].find({"status": "finished", "type": {"$eq": "game_over_win"}})
+
+    samples = []
+
+    for game in games:
+        board = [0]*9
+        winner = game.get("winner")
+        x_id = game.get("playerXId")
+        o_id = game.get("playerOId")
+
+        x_moves = [POSITION_MAP[m] for m in game.get("playerXMoves", [])]
+        o_moves = [POSITION_MAP[m] for m in game.get("playerOMoves", [])]
+
+        # Reconstroi o jogo movimento a movimento
+        for i in range(max(len(x_moves), len(o_moves))):
+            # Jogada do X
+            if i < len(x_moves):
+                move = x_moves[i]
+                state = board.copy()
+                samples.append({
+                    "board": state,
+                    "player": 1,
+                    "move": move,
+                    "winner": 1 if winner == x_id else -1
+                })
+                board[move] = 1
+
+            # Jogada do O
+            if i < len(o_moves):
+                move = o_moves[i]
+                state = board.copy()
+                samples.append({
+                    "board": state,
+                    "player": -1,
+                    "move": move,
+                    "winner": 1 if winner == o_id else -1
+                })
+                board[move] = -1
+
+    return samples
+
+# Exemplo de uso:
+if __name__ == "__main__":
+    samples = convert_games_to_samples()
+    print(samples[:5])  # mostra as 5 primeiras amostras
+
+    rows = []
+    for s in samples:
+        rows.append({
+            **{f"cell_{i}": v for i, v in enumerate(s["board"])},
+            "player": s["player"],
+            "move": s["move"],
+            "winner": s["winner"]
+        })
+
+    df = pd.DataFrame(rows)
+    df.to_csv("tictactoe_dataset.csv", index=False)
+    print("Dataset salvo com", len(df), "amostras")

games_ai/play.py

@@ -0,0 +1,2 @@
+if __name__ == "__main__":
+    print("Hello from games_ai/play.py")

games_ai/requirements.txt

@@ -0,0 +1,4 @@
+mlx
+pymongo
+numpy
+pandas