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import os
import datetime
import requests
import pytz
import yaml
from dotenv import load_dotenv
from smolagents import CodeAgent, DuckDuckGoSearchTool, HfApiModel, LiteLLMModel, tool
from tools.read_rss_feed import ReadRssFeedTool
from tools.final_answer import FinalAnswerTool
from Gradio_UI import GradioUI
load_dotenv()
@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)}"
# 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'
def choose_model():
if os.getenv("OLLAMA_MODEL"):
print("Using an Ollama model: ", os.getenv("OLLAMA_MODEL"))
return LiteLLMModel(
model_id=os.getenv("OLLAMA_MODEL"),
api_base=os.getenv("OLLAMA_ENDPOINT"),
api_key=os.getenv("OLLAMA_KEY"),
)
else:
print("Using a HuggingFace model")
return HfApiModel(
max_tokens=2096,
temperature=0.5,
model_id='Qwen/Qwen2.5-Coder-32B-Instruct',
custom_role_conversions=None,
)
with open("prompts.yaml", "r") as stream:
prompt_templates = yaml.safe_load(stream)
model = choose_model()
read_rss_feed = ReadRssFeedTool()
final_answer = FinalAnswerTool()
agent = CodeAgent(
model=model,
tools=[read_rss_feed, final_answer],
max_steps=6,
verbosity_level=1,
grammar=None,
planning_interval=None,
name=None,
description=None,
prompt_templates=prompt_templates
)
GradioUI(agent).launch() |