File size: 2,358 Bytes
29d384c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 |
# app.py
from smolagents import CodeAgent, DuckDuckGoSearchTool, HfApiModel, load_tool, tool
from tools.final_answer import FinalAnswerTool
import datetime
import pytz
import yaml
import gradio as gr
# ✅✅✅ ---- Natural language time tool ----
@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., 'Europe/London').
"""
try:
tz = pytz.timezone(timezone)
local_time = datetime.datetime.now(tz).strftime("%A, %B %d, %Y %I:%M %p")
return f"The current local time in {timezone} is {local_time}."
except Exception as e:
return f"Sorry, I couldn’t find the time for {timezone}: {str(e)}"
# ✅✅✅ ---- Final Answer Tool ----
final_answer = FinalAnswerTool()
# ✅✅✅ ---- Hugging Face Model ----
model = HfApiModel(
max_tokens=2048,
temperature=0.5,
model_id='Qwen/Qwen2.5-Coder-32B-Instruct',
)
# ✅✅✅ ---- Load optional tool from Hub ----
image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)
# ✅✅✅ ---- System prompt template ----
# This will ensure the agent keeps full sentences!
prompt_templates = {
"system": """You are a helpful agent that thinks step by step.
You must always return your final answer as a clear, complete sentence in natural language.
If you call tools, use their output exactly and do not strip details.
When you have the final information, pass it using the FinalAnswerTool.
"""
}
# ✅✅✅ ---- Build the CodeAgent ----
agent = CodeAgent(
model=model,
tools=[
get_current_time_in_timezone,
DuckDuckGoSearchTool(),
image_generation_tool,
final_answer
],
max_steps=6,
verbosity_level=1,
prompt_templates=prompt_templates
)
# ✅✅✅ ---- Gradio UI ----
def agentic_chat(user_input):
result = agent.run(user_input)
if hasattr(result, 'final_answer'):
return result.final_answer
else:
return str(result)
iface = gr.Interface(
fn=agentic_chat,
inputs="text",
outputs="text",
title="Agentic AI Example",
description="Ask me anything! I will reason step-by-step and provide clear final answers."
)
if __name__ == "__main__":
iface.launch() |