app.py

from smolagents import CodeAgent, DuckDuckGoSearchTool, HfApiModel, load_tool, tool
import datetime
import requests
import pytz
import yaml
from tools.final_answer import FinalAnswerTool
from Gradio_UI import GradioUI
from transformers import pipeline

# 0. Tool to get the topic from the user
@tool
def get_topic() -> str:
    """A tool to prompt the user for a topic.
    Returns:
        str: The topic entered by the user.
    """
    # For demonstration purposes, we use input(). In a production UI this might be replaced by a text field.
    topic = input("Enter the topic you want to explore: ")
    return topic

# 1. Tool to search the web using DuckDuckGo
@tool
def search_web(query: str) -> str:
    """A tool that searches the web for the provided query.
    Args:
        query: The search query.
    Returns:
        str: A snippet from the top search result.
    """
    # Leverage the built-in DuckDuckGo search functionality
    results = DuckDuckGoSearchTool.search(query=query)
    if results and len(results) > 0:
        # Return a snippet from the first result for brevity.
        return results[0].get('snippet', "No snippet available.")
    return "No results found."

# 2. Tool to summarize content using a Hugging Face summarization pipeline
@tool
def summarise_content(text: str) -> str:
    """A tool that summarizes text content.
    Args:
        text: The content to summarize.
    Returns:
        str: The summarized text.
    """
    summarizer = pipeline("summarization")
    # Adjust max/min length as needed
    summary = summarizer(text, max_length=130, min_length=30, do_sample=False)
    return summary[0]['summary_text']

# 3. Tool to generate a social media post based on the summary
@tool
def write_social_media_post(summary: str) -> str:
    """A tool that crafts a social media post using the provided summary.
    Args:
        summary: The summary text to base the post on.
    Returns:
        str: A drafted social media post.
    """
    # Using a simple template; feel free to enhance with hashtags or formatting as needed.
    post = f"Check this out: {summary} #news #update"
    return post

final_answer = FinalAnswerTool()

# Define our Hugging Face model for the CodeAgent
model = HfApiModel(
    max_tokens=2096,
    temperature=0.5,
    model_id='Qwen/Qwen2.5-Coder-32B-Instruct',
)

# Optional: Load an image generation tool if you wish to expand functionality
image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)

# Load prompt templates from a YAML file
with open("prompts.yaml", 'r') as stream:
    prompt_templates = yaml.safe_load(stream)

# Instantiate the agent with our custom tools (plus final_answer to ensure a response)
agent = CodeAgent(
    model=model,
    tools=[
        final_answer, 
        get_topic, 
        search_web, 
        summarise_content, 
        write_social_media_post
    ],
    max_steps=6,
    verbosity_level=1,
    prompt_templates=prompt_templates
)

# Launch the Gradio UI to interact with the agent
GradioUI(agent).launch()