fprogr's picture
Removed my_env from repository
569c81e
raw
history blame
5.16 kB
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 !
@tool
# 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]
@tool
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")
@tool
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)}"
@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)}"
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()