app.py

from smolagents import CodeAgent, tool, Tool,LiteLLMModel, OpenAIServerModel
from tools.final_answer import FinalAnswerTool
import requests
import pytz
import yaml
import pandas as pd
import os, json
from PIL import Image

from Gradio_UI import GradioUI

# 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_g5_data() -> dict:
    """Returns G5 dataset in a dictionary format.
    G5 dataset contains informations relating to the movements of ships in space and time, mostly between the mid-18th and mid-19th centuries
    """
    df = pd.read_csv("g5data.csv", sep=";", encoding="utf-8")
    return df.to_dict()

@tool
def save_figure()-> None:
  """Save the chart in a image.png file located at "/content/gdrive/MyDrive/ColabNotebooks/Portic" path
  Returns the image displayed"""
  image_path = '/content/gdrive/MyDrive/ColabNotebooks/Portic/image.png'
  return Image.open(image_path)

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 = LiteLLMModel(model_id="gemini/gemini-1.5-flash",  api_key=os.environ["GOOGLE_API_KEY"])

# 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,get_g5_data,save_figure], ## 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()