import streamlit as st from smolagents import CodeAgent, DuckDuckGoSearchTool, HfApiModel from io import BytesIO # Initialize the content generation agent with DuckDuckGo tool content_agent = CodeAgent( tools=[DuckDuckGoSearchTool()], model=HfApiModel() ) # Function to display agent activity def display_agent_activity(prompt, result): st.write("### Agent Activity:") st.write("**Prompt Sent to Agent:**") st.code(prompt, language="text") st.write("**Agent Output:**") st.code(result, language="text") # Function to enhance generated content def enhance_content(content): return f"{content}\n\n---\nGenerated with insights and enhanced formatting." # Function to save content as a downloadable text file def generate_text_download(content, filename="generated_blog.txt"): b = BytesIO() b.write(content.encode()) b.seek(0) return b, filename # Function to save content as a downloadable PDF def generate_pdf_download(content, filename="generated_blog.pdf"): from fpdf import FPDF pdf = FPDF() pdf.add_page() pdf.set_font("Arial", size=12) pdf.multi_cell(0, 10, content) b = BytesIO() pdf.output(b) b.seek(0) return b, filename # Streamlit app title st.title("SmolAgent Content Writer") # Tabs for the interface tabs = st.tabs(["Generate Content", "Agent Activity", "Download Options"]) # Tab 1: Generate Content with tabs[0]: st.header("Generate Content") st.write("Generate high-quality blog content enriched with real-time insights using SmolAgent.") # Input field for blog topic or prompt blog_prompt = st.text_area("Enter your blog topic or prompt:", placeholder="E.g., The Future of Technology in Healthcare") # Input field for choosing content tone tone = st.selectbox("Choose the tone of the content:", ["Professional", "Casual", "Persuasive", "Informative"]) # Option to include a summary include_summary = st.checkbox("Include a summary of the generated content") # Button to trigger blog content generation if st.button("Generate Blog Content"): if blog_prompt: with st.spinner("Generating blog content, please wait..."): try: # Generate blog content using the agent blog_result = content_agent.run(f"{blog_prompt}\nTone: {tone}") # Optionally enhance the content blog_result = enhance_content(blog_result) # Display the generated blog content st.subheader("Generated Blog Content") st.write(blog_result) # Display a summary if requested if include_summary: summary_prompt = f"Summarize this content:\n{blog_result}" summary_result = content_agent.run(summary_prompt) st.subheader("Content Summary") st.write(summary_result) # Store result for download st.session_state["last_content"] = blog_result except Exception as e: st.error("An error occurred while generating content. Please try again.") else: st.warning("Please enter a valid blog topic or prompt.") # Tab 2: Agent Activity with tabs[1]: st.header("Agent Activity") if "last_content" in st.session_state: display_agent_activity(blog_prompt, st.session_state["last_content"]) else: st.write("No recent activity to display.") # Tab 3: Download Options with tabs[2]: st.header("Download Options") if "last_content" in st.session_state: content = st.session_state["last_content"] # Text file download text_file, text_filename = generate_text_download(content) st.download_button(label="Download as Text File", data=text_file, file_name=text_filename, mime="text/plain") # PDF file download pdf_file, pdf_filename = generate_pdf_download(content) st.download_button(label="Download as PDF", data=pdf_file, file_name=pdf_filename, mime="application/pdf") else: st.write("No content available for download. Generate content first.")