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 smolagents import GradioUI
from smolagents import LiteLLMModel
import os

import litellm

litellm._turn_on_debug()

# 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_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 crypto_analysis(crypto_name: str) -> str:
    """
    Fetches current cryptocurrency data for a given crypto currency name use the data extracted  to perform crypto analysis.
    
    Args:
        crypto_name: The crypto currency id (e.g., 'bitcoin')
    
    Returns:
        A JSON-formatted string containing the crypto analysis if successful,
        otherwise an error message
    """
    
    url = f"https://rest.coincap.io/v3/assets/{crypto_name}?apiKey={os.getenv(key='coincap_api')}"
    try:
        response = requests.get(url)
        response.raise_for_status()  # Raise exception for bad status codes
        data = response.json()
        return data

    except requests.exceptions.RequestException as e:
        raise f"Error: {str(e)}"
    
        
        
    #         crypto_info = data['data']
    #         # Extract key metrics for analysis
    #         price = float(crypto_info["priceUsd"])
    #         market_cap = float(crypto_info["marketCapUsd"])
    #         volume_24h = float(crypto_info["volumeUsd24Hr"])
    #         change_24h = float(crypto_info["changePercent24Hr"])
            
    #         # Targeted search for information
    #         queries = [
    #             f"{crypto_info['name']} price movement reasons",
    #             f"{crypto_info['name']} market analysis",
    #             f"{crypto_info['name']} future predictions",
    #             f"{crypto_info['name']} recent developments"
    #         ]
            
    #         # Fetch relevant information from search
    #         search_results = {}
    #         for query in queries:
    #             search_results[query] = search_tool(query)
                
    #         # Compile final results
    #         analysis = {
    #             "basic_info": {
    #                 "name": crypto_info["name"],
    #                 "symbol": crypto_info["symbol"],
    #                 "current_price_usd": price,
    #                 "market_cap_usd": market_cap,
    #                 "rank": int(crypto_info["rank"]),
    #             },
    #             "technical_indicators": {
    #                 "24h_change_percent": change_24h,
    #                 "24h_volume_usd": volume_24h,
    #                 "supply_info": {
    #                     "current_supply": float(crypto_info["supply"]),
    #                     "max_supply": float(crypto_info["maxSupply"]) if crypto_info.get("maxSupply") else None,
    #                     "percent_of_max_issued": (float(crypto_info["supply"]) / float(crypto_info["maxSupply"]) * 100) 
    #                         if crypto_info.get("maxSupply") else None
    #                 }
    #             },
    #             "market_sentiment": {
    #                 "recent_news": search_results,
    #                 "sentiment_indicator": "positive" if change_24h > 0 else "negative",
    #             }
    #         }
            
    #         return json.dumps(analysis)
            
    #     except ValueError as error:
    #         return f"Error: Failed to process values in cryptocurrency data: {str(error)}"
        
    # except requests.exceptions.RequestException as e:
    #     return f"Error: API request failed: {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='meta-llama/Llama-3.1-8B-Instruct',# it is possible that this model may be overloaded
# custom_role_conversions=None,
# )

model = LiteLLMModel(model_id="gemini/gemini-2.0-flash-lite", api_key=os.getenv(key="gemini_api")) 

# 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,crypto_analysis], ## 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()