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import streamlit as st
# Used for Streamlit deployment
from swarm import Swarm, Agent
from bs4 import BeautifulSoup
import requests
from dotenv import load_dotenv
import os
# Load environment variables from .env file if available
load_dotenv()
# Function to set OpenAI API key dynamically in the session state
def set_openai_api_key():
api_key_input = st.text_input("Enter your OpenAI API Key", type="password")
if api_key_input:
os.environ['OPENAI_API_KEY'] = api_key_input
st.success("OpenAI API Key set successfully!")
else:
st.warning("Please enter your OpenAI API Key to continue.")
# Initialize the Swarm client
def initialize_swarm_client():
return Swarm()
# Define the scraping function
def scrape_website(url):
"""Scrapes the content of the website."""
try:
response = requests.get(url)
response.raise_for_status()
soup = BeautifulSoup(response.text, 'html.parser')
return soup.get_text() # Return the text content from the HTML
except requests.exceptions.RequestException as e:
return f"Error during scraping: {str(e)}"
# Scraper Agent
scraper_agent = Agent(
name="Scraper Agent",
instructions="You are an agent that scrapes content from websites.",
functions=[scrape_website] # The agent can use the scrape_website function
)
# Define the analysis function
def analyze_content(content):
"""Analyzes the scraped content for key points."""
summary = f"Summary of content: {content[:200]}..." # A simple placeholder summarization
return summary
# Research Agent
research_agent = Agent(
name="Research Agent",
instructions="You are an agent that analyzes content and extracts key insights.",
functions=[analyze_content] # The agent can use the analyze_content function
)
# Define the writing function
def write_summary(context_variables):
"""Writes a summary based on the analysis."""
analysis = context_variables.get('analysis', '')
summary = f"Here's a detailed report based on the research: {analysis}"
return summary
# Writer Agent
writer_agent = Agent(
name="Writer Agent",
instructions="You are an agent that writes summaries of research.",
functions=[write_summary] # The agent can use the write_summary function
)
# Orchestrate the workflow
def orchestrate_workflow(client, url):
# Step 1: Scrape the website
scrape_result = client.run(
agent=scraper_agent,
messages=[{"role": "user", "content": f"Scrape the following website: {url}"}]
)
scraped_content = scrape_result.messages[-1]["content"]
# Check for any error during scraping
if "Error during scraping" in scraped_content:
return scraped_content
# Step 2: Analyze the scraped content
research_result = client.run(
agent=research_agent,
messages=[{"role": "user", "content": f"Analyze the following content: {scraped_content}"}]
)
analysis_summary = research_result.messages[-1]["content"]
# Step 3: Write the summary based on the analysis
writer_result = client.run(
agent=writer_agent,
messages=[{"role": "user", "content": f"Write a summary based on this analysis: {analysis_summary}"}],
context_variables={"analysis": analysis_summary} # Pass the analysis to the writer agent
)
final_summary = writer_result.messages[-1]["content"]
return final_summary
# Streamlit App UI
st.title("🔍 OpenAI SWARM Web Scraping and Content Analysis with Multi-Agent System")
st.caption("This app scrapes a website, analyzes the content, and generates a summary using a multi-agent system built on OpenAI's Swarm framework.")
# Input for OpenAI API Key
st.subheader("OpenAI API Key Setup")
set_openai_api_key()
# Initialize Swarm client only after API key is set
if 'OPENAI_API_KEY' in os.environ and os.environ['OPENAI_API_KEY']:
# Initialize the Swarm client after API key is entered
client = initialize_swarm_client()
# Input field for the website URL
url = st.text_input("Enter the URL of the website you want to scrape", placeholder="https://example.com")
# Run Workflow button
if st.button("Run Workflow"):
if url:
with st.spinner("Running the multi-agent workflow..."):
final_report = orchestrate_workflow(client, url)
st.success("Workflow complete!")
st.write("### Final Report:")
st.write(final_report)
else:
st.error("Please enter a valid URL.")
else:
st.warning("Please set your OpenAI API Key to proceed.")
# Footer with credits
st.write("---")
st.write("**Acknowledgement:**") |