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from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool
import datetime
import requests
import pytz
import yaml
from tools.final_answer import FinalAnswerTool
from huggingface_hub import InferenceClient
from transformers import pipeline
from Gradio_UI import GradioUI
grammar_corrector = pipeline("text2text-generation", model="vennify/t5-base-grammar-correction")
# Below is an example of a tool that does nothing. Amaze us with your creativity !
@tool
def my_custom_tool(arg1:int, arg2:str)-> 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 writes out the string in the number of times of the integer
Args:
arg1: the first argument
arg2: the second argument
"""
return arg2 * arg1
@tool
def correct_grammar(sentence: str) -> str:
"""A tool that checks and corrects grammatical errors in a given sentence.
Args:
sentence: A string containing the sentence to correct.
Returns:
A grammatically corrected version of the input sentence.
"""
try:
tool = language_tool_python.LanguageTool('en-US')
matches = tool.check(sentence)
corrected = language_tool_python.utils.correct(sentence, matches)
return corrected
except Exception as e:
return f"Error correcting sentence: {str(e)}"
# Example usage
if __name__ == "__main__":
test_sentence = "He go to school everyday."
print("Original:", test_sentence)
print("Corrected:", correct_grammar(test_sentence))
@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
)
GradioUI(agent).launch() |