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import os | |
import json | |
import asyncio | |
import random | |
# --- OpenAI --- | |
from openai import AsyncOpenAI, APIError | |
# --- Google Gemini --- | |
from google import genai | |
from google.genai import types | |
# --- Mistral AI --- | |
from mistralai import Mistral | |
# --- Poke-Env --- | |
from poke_env.player import Player | |
from poke_env.environment.battle import Battle | |
from poke_env.environment.move import Move | |
from poke_env.environment.pokemon import Pokemon | |
from typing import Optional, Dict, Any, Union | |
# --- Helper Function & Base Class --- | |
def normalize_name(name: str) -> str: | |
"""Lowercase and remove non-alphanumeric characters.""" | |
return "".join(filter(str.isalnum, name)).lower() | |
STANDARD_TOOL_SCHEMA = { | |
"choose_move": { | |
"name": "choose_move", | |
"description": "Selects and executes an available attacking or status move.", | |
"parameters": { | |
"type": "object", | |
"properties": { | |
"move_name": { | |
"type": "string", | |
"description": "The exact name or ID (e.g., 'thunderbolt', 'swordsdance') of the move to use. Must be one of the available moves.", | |
}, | |
}, | |
"required": ["move_name"], | |
}, | |
}, | |
"choose_switch": { | |
"name": "choose_switch", | |
"description": "Selects an available Pokémon from the bench to switch into.", | |
"parameters": { | |
"type": "object", | |
"properties": { | |
"pokemon_name": { | |
"type": "string", | |
"description": "The exact name of the Pokémon species to switch to (e.g., 'Pikachu', 'Charizard'). Must be one of the available switches.", | |
}, | |
}, | |
"required": ["pokemon_name"], | |
}, | |
}, | |
} | |
# --- OpenAI Tools Schema (with 'type' field) --- | |
OPENAI_TOOL_SCHEMA = { | |
"choose_move": { | |
"type": "function", | |
"function": { | |
"name": "choose_move", | |
"description": "Selects and executes an available attacking or status move.", | |
"parameters": { | |
"type": "object", | |
"properties": { | |
"move_name": { | |
"type": "string", | |
"description": "The exact name or ID (e.g., 'thunderbolt', 'swordsdance') of the move to use. Must be one of the available moves.", | |
}, | |
}, | |
"required": ["move_name"], | |
}, | |
} | |
}, | |
"choose_switch": { | |
"type": "function", | |
"function": { | |
"name": "choose_switch", | |
"description": "Selects an available Pokémon from the bench to switch into.", | |
"parameters": { | |
"type": "object", | |
"properties": { | |
"pokemon_name": { | |
"type": "string", | |
"description": "The exact name of the Pokémon species to switch to (e.g., 'Pikachu', 'Charizard'). Must be one of the available switches.", | |
}, | |
}, | |
"required": ["pokemon_name"], | |
}, | |
} | |
}, | |
} | |
class LLMAgentBase(Player): | |
def __init__(self, *args, **kwargs): | |
super().__init__(*args, **kwargs) | |
self.standard_tools = STANDARD_TOOL_SCHEMA | |
self.battle_history = [] | |
def _format_battle_state(self, battle: Battle) -> str: | |
active_pkmn = battle.active_pokemon | |
active_pkmn_info = f"Your active Pokemon: {active_pkmn.species} " \ | |
f"(Type: {'/'.join(map(str, active_pkmn.types))}) " \ | |
f"HP: {active_pkmn.current_hp_fraction * 100:.1f}% " \ | |
f"Status: {active_pkmn.status.name if active_pkmn.status else 'None'} " \ | |
f"Boosts: {active_pkmn.boosts}" | |
opponent_pkmn = battle.opponent_active_pokemon | |
opp_info_str = "Unknown" | |
if opponent_pkmn: | |
opp_info_str = f"{opponent_pkmn.species} " \ | |
f"(Type: {'/'.join(map(str, opponent_pkmn.types))}) " \ | |
f"HP: {opponent_pkmn.current_hp_fraction * 100:.1f}% " \ | |
f"Status: {opponent_pkmn.status.name if opponent_pkmn.status else 'None'} " \ | |
f"Boosts: {opponent_pkmn.boosts}" | |
opponent_pkmn_info = f"Opponent's active Pokemon: {opp_info_str}" | |
available_moves_info = "Available moves:\n" | |
if battle.available_moves: | |
available_moves_info += "\n".join( | |
[f"- {move.id} (Type: {move.type}, BP: {move.base_power}, Acc: {move.accuracy}, PP: {move.current_pp}/{move.max_pp}, Cat: {move.category.name})" | |
for move in battle.available_moves] | |
) | |
else: | |
available_moves_info += "- None (Must switch or Struggle)" | |
available_switches_info = "Available switches:\n" | |
if battle.available_switches: | |
available_switches_info += "\n".join( | |
[f"- {pkmn.species} (HP: {pkmn.current_hp_fraction * 100:.1f}%, Status: {pkmn.status.name if pkmn.status else 'None'})" | |
for pkmn in battle.available_switches] | |
) | |
else: | |
available_switches_info += "- None" | |
state_str = f"{active_pkmn_info}\n" \ | |
f"{opponent_pkmn_info}\n\n" \ | |
f"{available_moves_info}\n\n" \ | |
f"{available_switches_info}\n\n" \ | |
f"Weather: {battle.weather}\n" \ | |
f"Terrains: {battle.fields}\n" \ | |
f"Your Side Conditions: {battle.side_conditions}\n" \ | |
f"Opponent Side Conditions: {battle.opponent_side_conditions}" | |
return state_str.strip() | |
def _find_move_by_name(self, battle: Battle, move_name: str) -> Optional[Move]: | |
normalized_name = normalize_name(move_name) | |
# Prioritize exact ID match | |
for move in battle.available_moves: | |
if move.id == normalized_name: | |
return move | |
# Fallback: Check display name (less reliable) | |
for move in battle.available_moves: | |
if move.name.lower() == move_name.lower(): | |
print(f"Warning: Matched move by display name '{move.name}' instead of ID '{move.id}'. Input was '{move_name}'.") | |
return move | |
return None | |
def _find_pokemon_by_name(self, battle: Battle, pokemon_name: str) -> Optional[Pokemon]: | |
normalized_name = normalize_name(pokemon_name) | |
for pkmn in battle.available_switches: | |
# Normalize the species name for comparison | |
if normalize_name(pkmn.species) == normalized_name: | |
return pkmn | |
return None | |
async def choose_move(self, battle: Battle) -> str: | |
battle_state_str = self._format_battle_state(battle) | |
decision_result = await self._get_llm_decision(battle_state_str) | |
print(decision_result) | |
decision = decision_result.get("decision") | |
error_message = decision_result.get("error") | |
action_taken = False | |
fallback_reason = "" | |
if decision: | |
function_name = decision.get("name") | |
args = decision.get("arguments", {}) | |
if function_name == "choose_move": | |
move_name = args.get("move_name") | |
if move_name: | |
chosen_move = self._find_move_by_name(battle, move_name) | |
if chosen_move and chosen_move in battle.available_moves: | |
action_taken = True | |
chat_msg = f"AI Decision: Using move '{chosen_move.id}'." | |
print(chat_msg) | |
return self.create_order(chosen_move) | |
else: | |
fallback_reason = f"LLM chose unavailable/invalid move '{move_name}'." | |
else: | |
fallback_reason = "LLM 'choose_move' called without 'move_name'." | |
elif function_name == "choose_switch": | |
pokemon_name = args.get("pokemon_name") | |
if pokemon_name: | |
chosen_switch = self._find_pokemon_by_name(battle, pokemon_name) | |
if chosen_switch and chosen_switch in battle.available_switches: | |
action_taken = True | |
chat_msg = f"AI Decision: Switching to '{chosen_switch.species}'." | |
print(chat_msg) | |
return self.create_order(chosen_switch) | |
else: | |
fallback_reason = f"LLM chose unavailable/invalid switch '{pokemon_name}'." | |
else: | |
fallback_reason = "LLM 'choose_switch' called without 'pokemon_name'." | |
else: | |
fallback_reason = f"LLM called unknown function '{function_name}'." | |
if not action_taken: | |
if not fallback_reason: | |
if error_message: | |
fallback_reason = f"API Error: {error_message}" | |
elif decision is None: | |
fallback_reason = "LLM did not provide a valid function call." | |
else: | |
fallback_reason = "Unknown error processing LLM decision." | |
print(f"Warning: {fallback_reason} Choosing random action.") | |
if battle.available_moves or battle.available_switches: | |
return self.choose_random_move(battle) | |
else: | |
print("AI Fallback: No moves or switches available. Using Struggle/Default.") | |
return self.choose_default_move(battle) | |
async def _get_llm_decision(self, battle_state: str) -> Dict[str, Any]: | |
raise NotImplementedError("Subclasses must implement _get_llm_decision") | |
# --- Google Gemini Agent --- | |
class GeminiAgent(LLMAgentBase): | |
"""Uses Google Gemini API for decisions.""" | |
def __init__(self, api_key: str = None, model: str = "gemini-2.5-pro-preview-03-25", avatar: str = "steven", *args, **kwargs): | |
# Set avatar before calling parent constructor | |
kwargs['avatar'] = avatar | |
kwargs['start_timer_on_battle_start'] = True | |
super().__init__(*args, **kwargs) | |
self.model_name = model | |
used_api_key = api_key or os.environ.get("GOOGLE_API_KEY") | |
if not used_api_key: | |
raise ValueError("Google API key not provided or found in GOOGLE_API_KEY env var.") | |
# Initialize Gemini client using the correct API | |
self.genai_client = genai.Client(api_key=used_api_key) | |
# Configure the tools for function calling | |
self.function_declarations = list(self.standard_tools.values()) | |
async def _get_llm_decision(self, battle_state: str) -> Dict[str, Any]: | |
"""Sends state to the Gemini API and gets back the function call decision.""" | |
prompt = ( | |
"Based on the current battle state, decide the best action: either use an available move or switch to an available Pokémon. " | |
"Consider type matchups, HP, status conditions, field effects, entry hazards, and potential opponent actions. " | |
"Only choose actions listed as available using their exact ID (for moves) or species name (for switches). " | |
"Use the provided functions to indicate your choice.\n\n" | |
f"Current Battle State:\n{battle_state}\n\n" | |
"Choose the best action by calling the appropriate function ('choose_move' or 'choose_switch')." | |
) | |
try: | |
# Configure tools using the Gemini API format | |
tools = genai.types.Tool(function_declarations=self.function_declarations) | |
config = genai.types.GenerateContentConfig(tools=[tools],automatic_function_calling=types.AutomaticFunctionCallingConfig(disable=True)) | |
# Send request to the model | |
response = self.genai_client.models.generate_content( | |
model=self.model_name, | |
contents=prompt, | |
config=config | |
) | |
try: | |
function_calls = response.function_calls | |
if function_calls: | |
function_name = function_calls[0].name | |
arguments = function_calls[0].args | |
return {"decision": {"name": function_name, "arguments": arguments}} | |
else: | |
return {"error": "Gemini did not return a function call."} | |
except Exception as e: | |
return {"error": f"Model called unknown @function '{function_name}'."} | |
# No function call found | |
return {"error": "Gemini did not return a function call."} | |
except Exception as e: | |
print(f"Unexpected error during Gemini processing: {e}") | |
import traceback | |
traceback.print_exc() | |
return {"error": f"Unexpected error: {str(e)}"} | |
# --- OpenAI Agent --- | |
class OpenAIAgent(LLMAgentBase): | |
"""Uses OpenAI API for decisions.""" | |
def __init__(self, api_key: str = None, model: str = "gpt-4.1", avatar: str = "giovanni", *args, **kwargs): | |
# Set avatar before calling parent constructor | |
kwargs['avatar'] = avatar | |
kwargs['start_timer_on_battle_start'] = True | |
super().__init__(*args, **kwargs) | |
self.model = model | |
used_api_key = api_key or os.environ.get("OPENAI_API_KEY") | |
if not used_api_key: | |
raise ValueError("OpenAI API key not provided or found in OPENAI_API_KEY env var.") | |
self.openai_client = AsyncOpenAI(api_key=used_api_key) | |
# Use the OpenAI-specific schema with type field | |
self.openai_tools = list(OPENAI_TOOL_SCHEMA.values()) | |
async def _get_llm_decision(self, battle_state: str) -> Dict[str, Any]: | |
system_prompt = ( | |
"You are a skilled Pokemon battle AI. Your goal is to win the battle. " | |
"Based on the current battle state, decide the best action: either use an available move or switch to an available Pokémon. " | |
"Consider type matchups, HP, status conditions, field effects, entry hazards, and potential opponent actions. " | |
"Only choose actions listed as available using their exact ID (for moves) or species name (for switches). " | |
"Use the provided functions to indicate your choice." | |
) | |
user_prompt = f"Current Battle State:\n{battle_state}\n\nChoose the best action by calling the appropriate function ('choose_move' or 'choose_switch')." | |
try: | |
response = await self.openai_client.chat.completions.create( | |
model=self.model, | |
messages=[ | |
{"role": "system", "content": system_prompt}, | |
{"role": "user", "content": user_prompt}, | |
], | |
tools=self.openai_tools, | |
tool_choice="auto", # Let the model choose | |
temperature=0.5, | |
) | |
message = response.choices[0].message | |
print("OPENAI RESPONSE : ",response) | |
# Check for tool calls in the response | |
if message.tool_calls: | |
tool_call = message.tool_calls[0] # Get the first tool call | |
function_name = tool_call.function.name | |
try: | |
arguments = json.loads(tool_call.function.arguments or '{}') | |
if function_name in self.standard_tools: | |
return {"decision": {"name": function_name, "arguments": arguments}} | |
else: | |
return {"error": f"Model called unknown function '{function_name}'."} | |
except json.JSONDecodeError: | |
return {"error": f"Error decoding function arguments: {tool_call.function.arguments}"} | |
else: | |
# Model decided not to call a function | |
return {"error": f"OpenAI did not return a function call. Response: {message.content}"} | |
except APIError as e: | |
print(f"Error during OpenAI API call: {e}") | |
return {"error": f"OpenAI API Error: {e.status_code} - {e.message}"} | |
except Exception as e: | |
print(f"Unexpected error during OpenAI API call: {e}") | |
return {"error": f"Unexpected error: {e}"} | |
# --- Mistral Agent --- | |
class MistralAgent(LLMAgentBase): | |
"""Uses Mistral AI API for decisions.""" | |
def __init__(self, api_key: str = None, model: str = "mistral-large-latest", avatar: str = "alder", *args, **kwargs): | |
# Set avatar before calling parent constructor | |
kwargs['avatar'] = avatar | |
kwargs['start_timer_on_battle_start'] = True | |
super().__init__(*args, **kwargs) | |
self.model = model | |
used_api_key = api_key or os.environ.get("MISTRAL_API_KEY") | |
if not used_api_key: | |
raise ValueError("Mistral API key not provided or found in MISTRAL_API_KEY env var.") | |
self.mistral_client = Mistral(api_key=used_api_key) | |
# Convert standard schema to Mistral's tool format with "function" wrapper | |
self.mistral_tools = [] | |
for tool_name, tool_schema in self.standard_tools.items(): | |
self.mistral_tools.append({ | |
"type": "function", | |
"function": { | |
"name": tool_schema["name"], | |
"description": tool_schema["description"], | |
"parameters": tool_schema["parameters"] | |
} | |
}) | |
async def _get_llm_decision(self, battle_state: str) -> Dict[str, Any]: | |
system_prompt = ( | |
"You are a skilled Pokemon battle AI. Your goal is to win the battle. " | |
"Based on the current battle state, decide the best action: either use an available move or switch to an available Pokémon. " | |
"Consider type matchups, HP, status conditions, field effects, entry hazards, and potential opponent actions. " | |
"Only choose actions listed as available using their exact ID (for moves) or species name (for switches). " | |
"Use the provided tools to indicate your choice." | |
) | |
user_prompt = f"Current Battle State:\n{battle_state}\n\nChoose the best action by calling the appropriate function ('choose_move' or 'choose_switch')." | |
try: | |
# Create the messages array | |
messages = [ | |
{"role": "system", "content": system_prompt}, | |
{"role": "user", "content": user_prompt} | |
] | |
# Call the Mistral API with tool_choice set to "any" to force tool usage | |
response = self.mistral_client.chat.complete( | |
model=self.model, | |
messages=messages, | |
tools=self.mistral_tools, | |
tool_choice="any", # Force the model to use a tool | |
temperature=0.3, | |
) | |
print("Mistral RESPONSE : ", response) | |
# Check for tool calls in the response | |
message = response.choices[0].message | |
if hasattr(message, 'tool_calls') and message.tool_calls: | |
tool_call = message.tool_calls[0] # Get the first tool call | |
function_name = tool_call.function.name | |
try: | |
# Parse the function arguments from JSON string | |
arguments = json.loads(tool_call.function.arguments or '{}') | |
if function_name in self.standard_tools: | |
return {"decision": {"name": function_name, "arguments": arguments}} | |
else: | |
return {"error": f"Model called unknown function '{function_name}'."} | |
except json.JSONDecodeError: | |
return {"error": f"Error decoding function arguments: {tool_call.function.arguments}"} | |
else: | |
# Model did not return a tool call | |
return {"error": f"Mistral did not return a tool call. Response: {message.content}"} | |
except Exception as e: | |
print(f"Error during Mistral API call: {e}") | |
import traceback | |
traceback.print_exc() | |
return {"error": f"Unexpected error: {str(e)}"} |