from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool import datetime import requests import pytz import yaml from tools.final_answer import FinalAnswerTool from Gradio_UI import GradioUI @tool def recommend_pet(personality: str) -> str: """A tool that recommends a pet based on your personality description. Args: personality: A description of your personality traits. Returns: A string with a pet recommendation. """ # Normalize input to lowercase for matching. personality_lower = personality.lower() # Map personality traits to pet suggestions. traits_to_pets = { "shy": "cat", "curious": "cat", "energetic": "dog", "active": "dog", "calm": "fish", "peaceful": "fish", "adventurous": "ferret", "creative": "parrot", "imaginative": "parrot" } # Count matching traits for each pet. scores = {} for trait, pet in traits_to_pets.items(): if trait in personality_lower: scores[pet] = scores.get(pet, 0) + 1 # If any traits matched, select the pet with the highest score. # Otherwise, default to "cat". if scores: recommended_pet = max(scores, key=scores.get) else: recommended_pet = "cat" return f"Based on your personality ('{personality}'), I recommend a {recommended_pet} as your companion!" 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 model_id='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud', custom_role_conversions=None, ) with open("prompts.yaml", 'r') as stream: prompt_templates = yaml.safe_load(stream) agent = CodeAgent( model=model, tools=[final_answer,recommend_pet], ## 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()