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| 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 | |
| # Below is an example of a tool that does nothing. Amaze us with your creativity ! | |
| def multiply(arg1:float, arg2:float)-> float: #it's important 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 arg1 * arg2 | |
| 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)}" | |
| web_search = DuckDuckGoSearchTool() | |
| 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='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud' ,# it is possible that this model may be overloaded | |
| #custom_role_conversions=None, | |
| #) | |
| class DummyModel: | |
| def __init__(self): | |
| self.last_input_token_count = 0 | |
| self.last_output_token_count = 0 | |
| def __call__(self, prompt, **kwargs): | |
| def safe_str(msg): | |
| if isinstance(msg["content"], list): | |
| return "\n".join(map(str, msg["content"])) | |
| return str(msg["content"]) | |
| # Recompose le texte à partir de la liste des messages | |
| text_prompt = "\n".join([safe_str(msg) for msg in prompt if "content" in msg]) | |
| self.last_input_token_count = len(text_prompt.split()) | |
| self.last_output_token_count = 10 | |
| return { | |
| "text": """Thought: I now know the final answer. | |
| Final Answer: 6.2""" | |
| } | |
| model = DummyModel() | |
| # 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, multiply, get_current_time_in_timezone, image_generation_tool, web_search], ## 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() |