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| from smolagents import CodeAgent,DuckDuckGoSearchTool, GoogleSearchTool, VisitWebpageTool, HfApiModel,load_tool,tool | |
| import datetime | |
| import requests | |
| import pytz | |
| import yaml | |
| import math | |
| from typing import Optional, Tuple | |
| from tools.final_answer import FinalAnswerTool | |
| from Gradio_UI import GradioUI | |
| def calculate_cargo_travel_time( | |
| origin_coords: Tuple[float, float], | |
| destination_coords: Tuple[float, float], | |
| cruising_speed_kmh: Optional[float] = 750.0, # Average speed for cargo planes | |
| ) -> float: | |
| """ | |
| Calculate the travel time for a cargo plane between two points on Earth using great-circle distance. | |
| Args: | |
| origin_coords: Tuple of (latitude, longitude) for the starting point | |
| destination_coords: Tuple of (latitude, longitude) for the destination | |
| cruising_speed_kmh: Optional cruising speed in km/h (defaults to 750 km/h for typical cargo planes) | |
| Returns: | |
| float: The estimated travel time in hours | |
| Example: | |
| >>> # Chicago (41.8781° N, 87.6298° W) to Sydney (33.8688° S, 151.2093° E) | |
| >>> result = calculate_cargo_travel_time((41.8781, -87.6298), (-33.8688, 151.2093)) | |
| """ | |
| def to_radians(degrees: float) -> float: | |
| return degrees * (math.pi / 180) | |
| # Extract coordinates | |
| lat1, lon1 = map(to_radians, origin_coords) | |
| lat2, lon2 = map(to_radians, destination_coords) | |
| # Earth's radius in kilometers | |
| EARTH_RADIUS_KM = 6371.0 | |
| # Calculate great-circle distance using the haversine formula | |
| dlon = lon2 - lon1 | |
| dlat = lat2 - lat1 | |
| a = ( | |
| math.sin(dlat / 2) ** 2 | |
| + math.cos(lat1) * math.cos(lat2) * math.sin(dlon / 2) ** 2 | |
| ) | |
| c = 2 * math.asin(math.sqrt(a)) | |
| distance = EARTH_RADIUS_KM * c | |
| # Add 10% to account for non-direct routes and air traffic controls | |
| actual_distance = distance * 1.1 | |
| # Calculate flight time | |
| # Add 1 hour for takeoff and landing procedures | |
| flight_time = (actual_distance / cruising_speed_kmh) + 1.0 | |
| # Format the results | |
| return round(flight_time, 2) | |
| # Tool to suggest a menu based on the occasion | |
| def suggest_menu(occasion: str) -> str: | |
| """ | |
| Suggests a menu based on the occasion. | |
| Args: | |
| occasion: The type of occasion for the party. | |
| """ | |
| if occasion == "casual": | |
| return "Pizza, snacks, and drinks." | |
| elif occasion == "formal": | |
| return "3-course dinner with wine and dessert." | |
| elif occasion == "superhero": | |
| return "Buffet with high-energy and healthy food." | |
| else: | |
| return "Custom menu for the butler." | |
| # Below is an example of a tool that does nothing. Amaze us with your creativity ! | |
| def my_custom_tool(arg1:str, arg2:int)-> str: #it's import to specify the return type | |
| #Keep this format for the description / args / args description but feel free to modify the tool | |
| """A tool that does nothing yet | |
| Args: | |
| arg1: the first argument | |
| arg2: the second argument | |
| """ | |
| return "What magic will you build ?" | |
| 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}" | |
| return f"{local_time}" | |
| except Exception as e: | |
| return f"Error fetching time for timezone '{timezone}': {str(e)}" | |
| final_answer = FinalAnswerTool() | |
| duck_duck_search = DuckDuckGoSearchTool() | |
| # 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 | |
| #model_id='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud', | |
| model_id='deepseek-ai/DeepSeek-R1', | |
| custom_role_conversions=None, | |
| ) | |
| # 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, DuckDuckGoSearchTool(), VisitWebpageTool(), calculate_cargo_travel_time], ## 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() |