app.py

from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool
import datetime
import requests
import pytz
import yaml
from tools.final_answer import FinalAnswerTool
from IPython.display import Audio
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 ?"

leak_warning_img = "leakage.png"
safe_status_img = "no leakage.jpeg"
alarm_sound_file = "alarm_sound.wav"

@tool
def leakage_alarm_checker(current_leakage_level: float, safe_threshold: float) -> tuple[str, "Image", "Audio | None"]:
    """
    Checks if the leakage level has exceeded a safe threshold and triggers an alarm.
    
    Args:
        current_leakage_level: The measured leakage level.
        safe_threshold: The maximum allowable leakage before triggering an alert.
    
    Returns:
        A tuple containing:
        - str: Alert message
        - Image: Warning or safe image
        - Audio | None: Alarm sound (if alert is triggered)
    """
    try:
        dif_leakage = current_leakage_level - safe_threshold
        if dif_leakage > 0:  
            alert_message = f"🚨 ALERT: Leakage level is {current_leakage_level} (Threshold: {safe_threshold}). IMMEDIATE ACTION REQUIRED!"
            warning_image = Image.open("leak_warning.png")  # Ensure this file exists
            return alert_message, warning_image, Audio("alarm_sound.wav", autoplay=True)
        else:
            alert_message = f"✅ SAFE: Leakage level is {current_leakage_level}, within the safe limit of {safe_threshold}. System is operating normally."
            safe_image = Image.open("safe_status.png")  # Ensure this file exists
            return alert_message, safe_image, None
    except Exception as e:
        return f"Error processing leakage levels: {str(e)}", Image.new("RGB", (200, 200), "gray"), None


@tool
def alarm_comparator_degrees(weather_average_degrees:float, optimal_fermentation_degrees:float)-> 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 compares the actual weathers degrees and the optimal fermentation degrees of a product in order to flag with an alert!!
    
    Args:
        weather_average_degrees: A float representing the avarage degrees of current weather.
        optimal_fermentation_degrees: A float representing the degrees that should be the fermentation process.
    """
    try:
        dif_degrees = weather_average_degrees - optimal_fermentation_degrees
        if abs(dif_degrees) >= 1.5:
            if dif_degrees < 0:
                return f"RED LIGHT - the difference degrees between optimal and current weather are {str(dif_degrees)}ºC - YOU SHOULD INCREASE THE HEATER BY {str(dif_degrees)}ºC!"   
            else:
                return f"RED LIGHT - the difference degrees between optimal and current weather are {str(dif_degrees)}ºC - YOU SHOULD DECREASE THE HEATER BY {str(dif_degrees)}ºC!"  
        else:
            return f"GREEN LIGHT - the difference degrees between optimal and current weather are {str(dif_degrees)} - DEGREES FOR FERMENTATION IN RANGE!"
    except Exception as e:
        return f"Error fetching {str(weather_average_degrees)} and {str(optimal_fermentation_degrees)}."
    

@tool
def convert_usd_to_eur(usd_amount: float) -> str:
    """
    Converts USD to EUR using a fixed exchange rate (mock).
    Args:
        usd_amount: The amount in USD.
    """
    # Example fixed rate: 1 USD = 0.9 EUR
    eur_amount = usd_amount * 0.9
    return f"${usd_amount} is approximately €{eur_amount:.2f}."


@tool
def daily_gold_oil_updates() -> str:
    """
    A tool that searches DuckDuckGo for daily gold and oil stock updates.
    """
    # Create an instance of the DuckDuckGoSearchTool
    ddg_tool = DuckDuckGoSearchTool()

    # Customize your search query as desired
    search_query = (
        "Gold and oil stock prices today. "
        "Daily updates, latest news, and current market data."
    )

    # Perform the search and return the raw results as a string
    results = ddg_tool.run(search_query)
    return results


@tool
def daily_weather_search(location: str) -> str:
    """
    A tool that searches DuckDuckGo for current weather in the specified location.

    Args:
        location: The city or region to get weather info for.

    Returns:
        A string containing raw DuckDuckGo search results about the current weather.
    """
    ddg_tool = DuckDuckGoSearchTool()
    search_query = f"Current weather in {location}, local forecast, temperature, humidity."
    results = ddg_tool.run(search_query)
    return results


@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
model_id='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud',
#model_id = 'deepseek-ai/DeepSeek-R1-Distill-Qwen-32B',
    

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,image_generation_tool ], ## add your tools here (don't remove final answer)
    tools=[
        final_answer,               # Final answer tool (don't remove)
        image_generation_tool,      # The text-to-image tool from the Hub
        convert_usd_to_eur,         # Your custom currency converter
        get_current_time_in_timezone,  # Your custom time tool
        daily_gold_oil_updates,
        daily_weather_search,
        alarm_comparator_degrees,
        leakage_alarm_checker
    ],
    max_steps=6,
    verbosity_level=1,
    grammar=None,
    planning_interval=None,
    name=None,
    description=None,
    prompt_templates=prompt_templates
)
GradioUI(agent).launch()


# import os
# import openai
# import datetime
# import requests
# import pytz
# import yaml
# from smolagents import CodeAgent, DuckDuckGoSearchTool, load_tool, tool
# from smolagents.models.openai_model import OpenAIModel  # OpenAI Model Import
# from tools.final_answer import FinalAnswerTool
# from Gradio_UI import GradioUI
# from smolagents.openai_model import OpenAIModel




# # Set your OpenAI API key securely
# openai.api_key = os.getenv("OPENAI_API_KEY")

# @tool
# def convert_usd_to_eur(usd_amount: float) -> str:
#     """
#     Converts USD to EUR using a fixed exchange rate (mock).
#     Args:
#         usd_amount: The amount in USD.
#     """
#     eur_amount = usd_amount * 0.9  # Example fixed rate
#     return f"${usd_amount} is approximately €{eur_amount:.2f}."

# @tool
# def daily_gold_oil_updates() -> str:
#     """
#     A tool that searches DuckDuckGo for daily gold and oil stock updates.
#     """
#     ddg_tool = DuckDuckGoSearchTool()
#     search_query = "Gold and oil stock prices today. Daily updates and market trends."
#     return ddg_tool.run(search_query)

# @tool
# def daily_weather_search(location: str) -> str:
#     """
#     A tool that searches DuckDuckGo for current weather in the specified location.
#     """
#     ddg_tool = DuckDuckGoSearchTool()
#     search_query = f"Current weather in {location}, temperature, and forecast."
#     return ddg_tool.run(search_query)

# @tool
# def get_current_time_in_timezone(timezone: str) -> str:
#     """Fetches the current local time in a specified timezone."""
#     try:
#         tz = pytz.timezone(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()

# # Using OpenAI GPT-4 instead of Hugging Face API
# model = OpenAIModel(
#     model_name="gpt-4",  # or "gpt-3.5-turbo"
#     temperature=0.5,
#     max_tokens=2048
# )

# # Import tool from Hugging Face 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,  # Final answer tool
#         image_generation_tool,  # Text-to-image tool
#         convert_usd_to_eur,  # Currency conversion tool
#         get_current_time_in_timezone,  # Timezone tool
#         daily_gold_oil_updates,  # Gold and oil updates tool
#         daily_weather_search  # Weather search tool
#     ],
#     max_steps=6,
#     verbosity_level=1,
#     prompt_templates=prompt_templates
# )

# GradioUI(agent).launch()