Smolagent / app.py
jonas-luehrs's picture
Add a tool
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from smolagents import CodeAgent, DuckDuckGoSearchTool, HfApiModel, load_tool, tool, Tool
import datetime
import requests
import pytz
import yaml
from tools.final_answer import FinalAnswerTool
from Gradio_UI import GradioUI
class HFModelDownloadsTool(Tool):
name = "model_download_counter"
description = """
This is a tool that returns the most downloaded model of a given task on the Hugging Face Hub.
It returns the name of the checkpoint."""
inputs = {
"task": {
"type": "string",
"description": "the task category (such as text-classification, depth-estimation, etc)",
}
}
output_type = "string"
def forward(self, task: str):
from huggingface_hub import list_models
model = next(iter(list_models(filter=task, sort="downloads", direction=-1)))
return model.id
# Below is an example of a tool that does nothing. Amaze us with your creativity !
@tool
def calculator_multiply(num1:int, num2:int)-> int:
"""A tool that multiplies the two provided numbers.
Args:
num1: the first argument
num2: the second argument
"""
return num1 * num2
@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 search_wikipedia(query: str) -> str:
"""
Fetches a summary of a Wikipedia page for a given query.
Args:
query: The search term to look up on Wikipedia.
Returns:
str: A summary of the Wikipedia page if successful, or an error message if the request fails.
Raises:
requests.exceptions.RequestException: If there is an issue with the HTTP request.
"""
url = f"https://en.wikipedia.org/api/rest_v1/page/summary/{query}"
try:
response = requests.get(url)
response.raise_for_status()
data = response.json()
title = data["title"]
extract = data["extract"]
return f"Summary for {title}: {extract}"
except requests.exceptions.RequestException as e:
return f"Error fetching Wikipedia data: {str(e)}"
final_answer = FinalAnswerTool()
model = HfApiModel(
max_tokens=2096,
temperature=0.5,
model_id='Qwen/Qwen2.5-Coder-32B-Instruct',
custom_role_conversions=None,
)
# Import tool from Hub
image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)
web_search_tool = DuckDuckGoSearchTool()
model_downloads_tool = HFModelDownloadsTool()
object_detection_tool = Tool.from_space(
space_id="kadirnar/Yolov10",
name="object-detector",
description="Detect objects within an image"
)
with open("prompts.yaml", 'r') as stream:
prompt_templates = yaml.safe_load(stream)
agent = CodeAgent(
model=model,
tools=[final_answer, image_generation_tool, web_search_tool, model_downloads_tool, object_detection_tool, search_wikipedia], ## 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()