app.py

import os
import datetime
import requests
import pytz
import yaml
from dotenv import load_dotenv
from smolagents import CodeAgent, DuckDuckGoSearchTool, HfApiModel, LiteLLMModel, tool

from tools.read_rss_feed import ReadRssFeedTool
from tools.final_answer import FinalAnswerTool
from Gradio_UI import GradioUI

load_dotenv()

@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)}"

# 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' 

def choose_model():
    if os.getenv("OLLAMA_MODEL"):
        print("Using an Ollama model: ", os.getenv("OLLAMA_MODEL"))

        return LiteLLMModel(
            model_id=os.getenv("OLLAMA_MODEL"),
            api_base=os.getenv("OLLAMA_ENDPOINT"),
            api_key=os.getenv("OLLAMA_KEY"),
        )
    else:
        print("Using a HuggingFace model")
        return HfApiModel(
            max_tokens=2096,
            temperature=0.5,
            model_id='Qwen/Qwen2.5-Coder-32B-Instruct',
            custom_role_conversions=None,
        )

with open("prompts.yaml", "r") as stream:
    prompt_templates = yaml.safe_load(stream)

model = choose_model()
read_rss_feed = ReadRssFeedTool()
final_answer = FinalAnswerTool()

agent = CodeAgent(
    model=model,
    tools=[read_rss_feed, final_answer],
    max_steps=6,
    verbosity_level=1,
    grammar=None,
    planning_interval=None,
    name=None,
    description=None,
    prompt_templates=prompt_templates
)

GradioUI(agent).launch()