app.py

from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool
import datetime
import requests
import pytz
import yaml
import os
import json
from tools.final_answer import FinalAnswerTool

from Gradio_UI import GradioUI

LANGFUSE_SECRET_KEY="sk-lf-7b384eb0-6ca0-4963-b2e8-25a65f5bd421"
LANGFUSE_PUBLIC_KEY="pk-lf-d5c4d040-b4c6-43fd-beae-ee88eb0a7def"
LANGFUSE_BASE_URL="https://cloud.langfuse.com"


@tool
def game_memory_tool(
    game: str,
    event_type: str,    
    content: str,
    importance: int) -> str:
    """
    A tool that stores important game memories for an autonomous game-playing agent.
    Args:
        game: The name of the game the agent is playing, e.g. "Pokemon Emerald".
        event_type: The type of memory being saved. Must be one of: observation, decision, battle, quest, inventory, strategy.
        content: A clear description of what happened or what the agent decided.
        importance: A number from 1 to 10 showing how important this memory is.
    """
    valid_event_types = {"observation", "decision", "battle", "quest", "inventory", "strategy"}
    if event_type not in valid_event_types:
        return f"Error: event_type must be one of {sorted(valid_event_types)}. Got: '{event_type}'."
    try:
        if importance < 1 or importance > 10:
            return "Error: importance must be between 1 and 10."
        # ... rest of your code unchanged
        memory = {
            "game": game,
            "event_type": event_type,
            "content": content,
            "importance": importance,
            "timestamp": datetime.datetime.now().isoformat()
        }

        with open("game_agent_memory.jsonl", "a", encoding="utf-8") as file:
            file.write(json.dumps(memory, ensure_ascii=False) + "\n")

        return (
            f"Memory saved for {game}. "
            f"Type: {event_type}. "
            f"Importance: {importance}/10."
        )

    except Exception as e:
        return f"Error saving game memory: {str(e)}"
@tool
def get_current_time_in_timezone(timezone: str) -> str:
    """A tool that fetches the current local time in a specified timezone.
    Args:
        timezone: A string representing a valid timezone (e.g., 'America/New_York').
    """
    try:
        # Create timezone object
        tz = pytz.timezone(timezone)
        # Get current time in that timezone
        local_time = datetime.datetime.now(tz).strftime("%Y-%m-%d %H:%M:%S")
        return f"The current local time in {timezone} is: {local_time}"
    except Exception as e:
        return f"Error fetching time for timezone '{timezone}': {str(e)}"


final_answer = FinalAnswerTool()

# If the agent does not answer, the model is overloaded, please use another model or the following Hugging Face Endpoint that also contains qwen2.5 coder:
# model_id='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud' 

model = HfApiModel(
max_tokens=2096,
temperature=0.5,
model_id='Qwen/Qwen2.5-Coder-32B-Instruct',# it is possible that this model may be overloaded
custom_role_conversions=None,
)



os.environ["LANGFUSE_PUBLIC_KEY"] = LANGFUSE_PUBLIC_KEY
os.environ["LANGFUSE_SECRET_KEY"] = LANGFUSE_SECRET_KEY
os.environ["LANGFUSE_HOST"] = LANGFUSE_BASE_URL


# Import tool from Hub
image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)

with open("prompts.yaml", 'r') as stream:
    prompt_templates = yaml.safe_load(stream)
    
agent = CodeAgent(
    model=model,
    tools=[final_answer], ## add your tools here (don't remove final answer)
    max_steps=6,
    verbosity_level=1,
    grammar=None,
    planning_interval=None,
    name=None,
    description=None,
    prompt_templates=prompt_templates
)


GradioUI(agent).launch()