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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 | |
import os | |
from Gradio_UI import GradioUI | |
# Below is an example of a tool that does nothing. Amaze us with your creativity ! | |
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 ?" | |
def search_flights(departure: str, destination: str, date: str) -> str: | |
"""Finds flights from departure to destination on the given date using DuckDuckGo. | |
Args: | |
departure: The city or airport code where the flight starts. | |
destination: The city or airport code where the flight ends. | |
date: The departure date in YYYY-MM-DD format. | |
Returns: | |
A string containing flight search results. | |
""" | |
query = f"flights from {departure} to {destination} on {date}" | |
search_results = DuckDuckGoSearchTool()(query) # Calls DuckDuckGo search | |
return f"Here are some flight options:\n{search_results}" | |
API_KEY = os.getenv("FREECURRENCYAPI_KEY") | |
def convert_currency(amount: float, from_currency: str, to_currency: str) -> str: | |
"""Converts currency from one to another using FreeCurrencyAPI. | |
Args: | |
amount: The amount to convert. | |
from_currency: The original currency (e.g., "USD"). | |
to_currency: The target currency (e.g., "EUR"). | |
Returns: | |
The converted amount in the target currency. | |
""" | |
try: | |
url = f"https://api.freecurrencyapi.com/v1/latest?apikey={API_KEY}&base_currency={from_currency.upper()}" | |
response = requests.get(url).json() | |
# ✅ Check if the API returned valid exchange rates | |
if "data" in response and to_currency.upper() in response["data"]: | |
rate = response["data"][to_currency.upper()] | |
converted_amount = amount * rate | |
return f"{amount} {from_currency.upper()} is approximately {converted_amount:.2f} {to_currency.upper()}." | |
return f"Error: Could not find exchange rate for {to_currency.upper()}." | |
except Exception as e: | |
return f"Error fetching exchange rates: {str(e)}" | |
chat_history = [] # Store conversation history | |
def chat_with_ai(message: str) -> str: | |
"""A tool that allows the AI to engage in general conversation with memory. | |
Args: | |
message: The user's message. | |
""" | |
global chat_history | |
# Keep the last 5 messages for context | |
if len(chat_history) > 5: | |
chat_history.pop(0) | |
# Add user message to history | |
chat_history.append({"role": "user", "content": message}) | |
# Format the history as input for the AI model | |
formatted_history = "\n".join(f"{msg['role']}: {msg['content']}" for msg in chat_history) | |
# ✅ Ensure AI response is handled correctly | |
try: | |
response = model(formatted_history) # Call model | |
# ✅ Handle both string and dictionary responses | |
if isinstance(response, dict): | |
response_text = response.get("text", str(response)) # Extract text if available | |
else: | |
response_text = str(response) # Convert non-dict responses to string | |
# Add AI response to history | |
chat_history.append({"role": "assistant", "content": response_text}) | |
return response_text | |
except Exception as e: | |
return f"Error processing chat: {str(e)}" | |
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=512, | |
temperature=0.5, | |
model_id='deepseek-ai/DeepSeek-R1-Distill-Qwen-32B',# 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, | |
get_current_time_in_timezone, | |
my_custom_tool, | |
chat_with_ai, # Regular chat tool | |
search_flights, | |
#scrape_webpage, | |
convert_currency, | |
#get_weather, | |
#generate_ai_image | |
], | |
max_steps=8, | |
verbosity_level=5, | |
prompt_templates=prompt_templates | |
) | |
GradioUI(agent).launch() |