File size: 2,126 Bytes
03f7f4c
9b5b26a
 
 
c19d193
6aae614
8fe992b
9b5b26a
 
5df72d6
9b5b26a
cc721cc
9b5b26a
cc721cc
9b5b26a
cc721cc
 
9b5b26a
cc721cc
9b5b26a
 
 
 
 
 
 
 
 
 
 
 
 
 
 
8c01ffb
 
6aae614
ae7a494
 
 
 
03f7f4c
 
 
 
 
 
13d500a
8c01ffb
861422e
 
9b5b26a
03f7f4c
8c01ffb
8fe992b
03f7f4c
8c01ffb
 
 
 
 
861422e
8fe992b
 
03f7f4c
 
9b5b26a
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
from smolagents import CodeAgent, DuckDuckGoSearchTool, FinalAnswerTool, InferenceClientModel, 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 !
@tool
def add(a:int, b:int)-> int: #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 adds two integers. 
    Args:
        a: the first integer
        b: the second integer
    """
    return a + b;

@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' 

final_answer = FinalAnswerTool()
model = InferenceClientModel(
    max_tokens=2096,
    temperature=0.5,
    model_id='Qwen/Qwen2.5-Coder-32B-Instruct',
    custom_role_conversions=None,
)

with open("prompts.yaml", 'r') as stream:
    prompt_templates = yaml.safe_load(stream)
    
# We're creating our CodeAgent
agent = CodeAgent(
    model=model,
    tools=[final_answer], # add your tools here (don't remove final_answer)
    max_steps=6,
    verbosity_level=1,
    planning_interval=None,
    name=None,
    description=None,
    prompt_templates=prompt_templates
)

GradioUI(agent).launch()