Spaces:
Sleeping
Sleeping
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 huggingface_hub import InferenceClient | |
from Gradio_UI import GradioUI | |
from dotenv import load_dotenv | |
load_dotenv() | |
hf_token = os.getenv("HF_TOKEN") | |
# Below is an example of a tool that does nothing. Amaze us with your creativity ! | |
# it's import to specify the return type | |
def my_custom_tool(arg1: str, arg2: int) -> str: | |
# 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 get_weather_report_at_coordinates(coordinates, date_time): | |
# Dummy function, returns a list of [temperature in °C, risk of rain on a scale 0-1, wave height in m] | |
return [28.0, 0.35, 0.85] | |
def convert_location_to_coordinates(location): | |
# Returns dummy coordinates | |
return [3.3, -42.0] | |
def get_weather_api(location: str, date_time: str) -> str: | |
""" | |
Returns the weather report. | |
Args: | |
location: the name of the place that you want the weather for. | |
date_time: the date and time for which you want the report. | |
""" | |
lon, lat = convert_location_to_coordinates(location) | |
date_time = datetime.strptime(date_time) | |
return str(get_weather_report_at_coordinates((lon, lat), date_time)) | |
user_data = {} | |
def update_personality(name: str, personality: str) -> str: | |
"""Asks the user about his personality before predicting his future | |
""" | |
user_data[name] = personality | |
return f"Great! Thanks {name} I ve updates your personality traits, now ask me about your future." | |
''' | |
I would like to use an AI model that takes the name and personality and predicts number of kids, career etc ''' | |
client = InferenceClient(model="Qwen/Qwen2.5-Coder-32B-Instruct") | |
def predict_future_with_model(name: str, personality: str) -> str: | |
""" | |
Returns: | |
str: A fun and futuristic AI-generated prediction. | |
Args: | |
name: The user's name. | |
personality: A description of the user's personality traits. | |
""" | |
prompt = f""" | |
Given the name '{name}' and personality traits '{personality}', generate a fun, futuristic prediction for their life. | |
Your response should include: | |
- A career path | |
- A major life event | |
- The number of kids they might have | |
- A quirky or funny twist related to their personality | |
Keep it engaging, futuristic, and a little humorous! | |
""" | |
try: | |
response = client.text_generation(prompt, max_new_tokens=100) | |
return f"🔮 **Future Prediction for {name}:**\n{response}" | |
except Exception as e: | |
return f"Oops! I couldn't predict the future this time. Error: {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)}" | |
def tell_joke() -> str: | |
"""stored jokes. | |
""" | |
jokes = ["Why do we tell actors to 'break a leg?' Because every play has a cast.", | |
"I told my wife she should embrace her mistakes. She gave me a hug.", | |
"I'm reading a book on the history of glue. I just can't seem to put it down.", | |
"I would tell you a joke about an elevator, but it's an uplifting experience.", | |
"I told my computer I needed a break and now it won't stop sending me vacation ads.", | |
"I used to play piano by ear, but now I use my hands"] | |
return random.choice(jokes) | |
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, | |
# it is possible that this model may be overloaded | |
model_id='Qwen/Qwen2.5-Coder-32B-Instruct', | |
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() | |