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| # app.py | |
| from smolagents import CodeAgent, DuckDuckGoSearchTool, load_tool, tool, InferenceClientModel | |
| import datetime | |
| import requests | |
| import pytz | |
| import yaml | |
| from tools.final_answer import FinalAnswerTool | |
| # Weather-specific imports | |
| import openmeteo_requests | |
| import pandas as pd | |
| import requests_cache | |
| from retry_requests import retry | |
| from Gradio_UI import GradioUI | |
| # Example tool | |
| def hourly_temperature(latitude: float, longitude: float) -> str: | |
| """Fetch hourly temperature from Open-Meteo API. | |
| Args: | |
| latitude: Latitude of the location | |
| longitude: Longitude of the location | |
| """ | |
| cache_session = requests_cache.CachedSession('.cache', expire_after=3600) | |
| retry_session = retry(cache_session, retries=5, backoff_factor=0.2) | |
| openmeteo = openmeteo_requests.Client(session=retry_session) | |
| url = "https://api.open-meteo.com/v1/forecast" | |
| params = { | |
| "latitude": latitude, | |
| "longitude": longitude, | |
| "hourly": "temperature_2m", | |
| } | |
| response = openmeteo.weather_api(url, params=params) | |
| hourly = response.Hourly() | |
| hourly_temperature_2m = hourly.Variables(0).ValuesAsNumpy() | |
| data = {"temperature_2m": hourly_temperature_2m} | |
| return data["temperature_2m"] | |
| def get_current_time_in_timezone(timezone: str) -> str: | |
| """Fetch current local time for a given timezone. | |
| Args: | |
| timezone: A string representing a valid timezone (e.g., 'Africa/Kigali'). | |
| """ | |
| try: | |
| tz = pytz.timezone(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 tool | |
| final_answer = FinalAnswerTool() | |
| # Create model using latest smolagents class | |
| model = InferenceClientModel( | |
| model_id="Qwen/Qwen2.5-Coder-32B-Instruct", | |
| temperature=0.5, | |
| max_new_tokens=2048 | |
| ) | |
| # Load additional tool from Hub | |
| image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True) | |
| # Load prompt templates | |
| with open("prompts.yaml", 'r') as stream: | |
| prompt_templates = yaml.safe_load(stream) | |
| # Create agent | |
| agent = CodeAgent( | |
| model=model, | |
| tools=[final_answer, hourly_temperature, get_current_time_in_timezone, image_generation_tool], | |
| max_steps=6, | |
| verbosity_level=1, | |
| #grammar=None, | |
| planning_interval=None, | |
| name="DormAI", | |
| description="AI agent for dorm management", | |
| prompt_templates=prompt_templates | |
| ) | |
| # Test the tools | |
| hourly_temperature(32.9, 15) | |
| get_current_time_in_timezone('Africa/Kigali') | |
| # Launch UI | |
| GradioUI(agent).launch() | |