app.py

from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool
from bs4 import BeautifulSoup
import datetime
import requests
import pytz
import yaml
from tools.final_answer import FinalAnswerTool

from Gradio_UI import GradioUI



@tool
def webpage_summarizer(url: str) -> str:
    """Extracts and summarizes main content from a webpage
    Args:
        url: URL of the webpage to summarize
    Returns:
        str: A summary of the webpage content including title and main text
    """
    try:
        # Add headers to mimic a browser request
        headers = {
            'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36'
        }

        # Fetch the webpage
        response = requests.get(url, headers=headers, timeout=10)
        response.raise_for_status()  # Raise an exception for bad status codes

        # Parse the HTML
        soup = BeautifulSoup(response.text, 'html.parser')

        # Get the title
        title = soup.title.string if soup.title else "No title found"

        # Remove script and style elements
        for script in soup(["script", "style"]):
            script.decompose()

        # Extract text from paragraphs
        paragraphs = soup.find_all('p')
        text_content = []

        for p in paragraphs:
            text = p.get_text().strip()
            if len(text) > 50:  # Only include substantial paragraphs
                text_content.append(text)

        # Combine the content
        summary = f"Title: {title}\n\nContent Summary:\n"
        summary += "\n\n".join(text_content[:5])  # Include first 5 substantial paragraphs

        # Limit the total length
        if len(summary) > 1500:
            summary = summary[:1500] + "..."

        return summary

    except requests.RequestException as e:
        return f"Error fetching webpage: {str(e)}"
    except Exception as e:
        return f"Error processing webpage: {str(e)}"

final_answer = FinalAnswerTool()
model = HfApiModel(
    max_tokens=2096,
    temperature=0.5,
    #model_id='deepseek-ai/DeepSeek-V2.5',
    model_id='Qwen/Qwen2.5-Coder-32B-Instruct',
    custom_role_conversions=None,
)

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


# Create the agent with the webpage summarizer tool
agent = CodeAgent(
    model=model,
    tools=[final_answer, webpage_summarizer],
    max_steps=6,
    verbosity_level=1,
    grammar=None,
    planning_interval=None,
    name=None,
    description=None,
    prompt_templates=prompt_templates
)

# Launch the Gradio interface
GradioUI(agent).launch()