Create app.py

app.py

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+import streamlit as st
+
+# Used for Streamlit deployment
+from swarm import Swarm, Agent
+
+# For local deployment, use the following importations instead
+'''
+from swarm.core import Swarm
+from swarm.types import 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:**")