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9b5b26a c19d193 123afbe 6aae614 8fe992b 9b5b26a 5df72d6 9b5b26a 3d1237b 9b5b26a 8c01ffb 6aae614 ae7a494 e121372 bf6d34c 29ec968 fe328e0 13d500a 8c01ffb 9b5b26a 8c01ffb 861422e 9b5b26a 8c01ffb 8fe992b d2f6a24 8c01ffb 861422e 8fe992b 9b5b26a 123afbe | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 | from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool
import datetime
import requests
import pytz
import yaml
import gradio as gr
import spaces
from tools.final_answer import FinalAnswerTool
# 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)}"
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
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], ## 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
)
# Questa è la funzione che verrà eseguita quando l'utente scrive una domanda
# Il decoratore @spaces.GPU fa sì che Hugging Face metta in coda l'esecuzione sulla GPU
@spaces.GPU(enable_queue=True)
def process_query(question):
# L'agente esegue il ragionamento e chiama i tool (come quello dell'ora o quello delle immagini)
return agent.run(question)
# Creo una semplice interfaccia Gradio con un campo di testo in input e uno in output
demo = gr.Interface(
fn=process_query,
inputs=gr.Textbox(label="La tua domanda", placeholder="Chiedimi qualsiasi cosa...", lines=4),
outputs=gr.Textbox(label="Risposta", lines=15),
title="Il mio Agente CodeAgent",
description="Agente con Qwen2.5 Coder e tool personalizzati (tempo, immagini, ecc.)"
)
# Lancia l'interfaccia (share=False è automatico su Spaces)
demo.launch() |