from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool import datetime import requests import pytz import yaml from tools.final_answer import FinalAnswerTool from smolagents import GradioUI from smolagents import LiteLLMModel import os import litellm litellm._turn_on_debug() # Below is an example of a tool that does nothing. Amaze us with your creativity ! @tool 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?" @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)}" @tool def crypto_analysis(crypto_name: str) -> str: """ Fetches current cryptocurrency data for a given crypto currency name use the data extracted to perform crypto analysis. Args: crypto_name: The crypto currency id (e.g., 'bitcoin') Returns: A JSON-formatted string containing the crypto analysis if successful, otherwise an error message """ url = f"https://rest.coincap.io/v3/assets/{crypto_name}?apiKey={os.getenv(key='coincap_api')}" search_tool = DuckDuckGoSearchTool() output = "" try: response = requests.get(url) response.raise_for_status() # Raise exception for bad status codes data = response.json() crypto_info = data["data"] return crypto_info except Exception as e: raise f"Error: {str(e)}" 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='meta-llama/Llama-3.1-8B-Instruct',# it is possible that this model may be overloaded # custom_role_conversions=None, # ) model = LiteLLMModel(model_id="gemini/gemini-2.0-flash-lite", api_key=os.getenv(key="gemini_api")) # model = LiteLLMModel( # model_id="ollama_chat/qwen2:7b", # Or try other Ollama-supported models # api_base=os.getenv(key='ollama_server_ip'), # Default Ollama local server # num_ctx=8192, # ) # 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,crypto_analysis,image_generation_tool], ## 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()