File size: 3,055 Bytes
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()