import asyncio # this will help us handle tasks without blocking execution import streamlit as st from typing import Dict, Any, List from agents import Agent, Runner, trace from agents import set_default_openai_key from firecrawl import FirecrawlApp from agents.tool import function_tool ## setiing up page configuration st.set_page_config( page_title= "Greg's Personal Deep Research AI Agent", page_icon= "📚", layout= "wide" ) ## initialize session state for API key if "OPENAI_API_KEY" not in st.session_state: st.session_state.openai_api_key= "" if "firecrawl_api_key" not in st.session_state: st.session_state.firecrawl_api_key= "" ## sidebar for api key with st.sidebar: st.title("API Configuration") openai_api_key= st.text_input( "OPENAI API Key", value= st.session_state.openai_api_key, type= "password" ) firecrawl_api_key= st.text_input( "FIRECRAWL API KEY", value= st.session_state.firecrawl_api_key, type= "password" ) if openai_api_key: st.session_state.openai_api_key= openai_api_key set_default_openai_key(openai_api_key) if firecrawl_api_key: st.session_state.firecrawl_api_key= firecrawl_api_key ## Main application and Input Field st.title("🔍 Greg's Personal Deep Research AI Agent") st.markdown("This Agent from OpenAI Agent SDK Performs Deep Research On Any Topic") #take the user input research_topic= st.text_input("Enter research topic: ", placeholder= "e.g: Research on the top 10 jobs in 2025 and their salary expectations") ## working with the deep research tool #This function tools help us to register the function to the agent @function_tool async def deep_research(query: str, max_depth: int, time_limit: int, max_urls: int): """ Performs comprehensive web research using Firecrawl's deep research endpoint. """ try: firecrawl_app= FirecrawlApp(api_key= st.session_state.firecrawl_api_key) params= { "max_depth": max_depth, "time_limit": time_limit, "max_urls": max_urls } def on_activity(activity): st.write(f"[{activity['type']}] {activity['message']}") ##helps us track realtime updates ## Run the deep research with firecrawl with st.spinner("Performing Deep Research..."): resp= firecrawl_app.deep_research( query= query, on_activity= on_activity, **params ) return { "success": True, "final_analysis": resp["data"]["finalAnalysis"], "sources_count": len(resp["data"]["sources"]), "sources": resp["data"]["sources"] } except Exception as e: st.error(f"Deep Research Error: {str(e)}") return{ "error":str(e), "success": False } ## defining agents for specific task research_agent= Agent( name= "research_agent", instructions= """ you are a research assistant that can perform deep web research on any topic. When given a research topic, or question: 1. Use the deep_research tool to gather comprehensive information - Always use these parameters: - max_depth: 3 (for moderate depth) - time_limit: 180 (3 minutes) - max_urls: 10 (sufficient resources) 2. The tool will search the web, analyze multiple sources and provide a synthesis 3. Review the research result and organize them into a well-structured report 4. Include proper citations for all sources 5.highlight key findings and insights """, tools= [deep_research] ) elaboration_agent= Agent( name= "elaboration_agent", instructions= """ You are an expert content enhancer specializing in research elaboration. When given a research report: 1. Analyze the structure and content of the report 2. Enhance the report by: - Adding more detailed explanation of complex concepts - Include relevant examples, case studies, and real world application. - Expanding on key points with additional context and nuance - Adding visual elements descriptions (charts, diagrams, infographics) - Incorporating the latest trends and future predictions - Suggesting practical implications for different stakeholders 3.Maintain academic rigor and factually accuracy 4. Preserve the original structure as well while making it more comprehensive 5. Ensure all additions are relevant and valuable to topic. """ ) ## creating another asynchronous function async def run_research_process(topic: str): """Run the complete research process. """ ## Step 1- Initial Research with st.spinner("Conducting initial research..."): research_results = await Runner.run(research_agent, topic) initial_report = research_results.final_output ##displaying the initial report with st.expander("View Initial Research Report: "): st.markdown(initial_report) ## Step 2- Enchance the report with st.spinner("Enhancing the report with additional information..."): elaboration_input= f""" RESEARCH_TOPIC= {topic} INITIAL RESEARCH REPORT: {initial_report} Please enchance this research report with additional information, examples,case studies, deeper insights while maintaining its academic rigor and factual accuracy """ elaboration_result= await Runner.run(elaboration_agent, elaboration_input) enhanced_report= elaboration_result.final_output return enhanced_report ## Main Research Process if st.button("Start Research", disabled= not (openai_api_key and firecrawl_api_key and research_topic)): if not openai_api_key or not firecrawl_api_key: st.warning("Please enter both API keys to start the research!") elif not research_topic: st.warning("No topic provided! Please enter a research topic") else: try: ## create a placeholder for final report report_placeholder= st.empty() # Run the research process enhanced_report = asyncio.run(run_research_process(research_topic)) # Display the results report_placeholder.markdown(f"## {research_topic} Report") report_placeholder.markdown(enhanced_report) ## Add a download button st.download_button( "Download Report", enhanced_report, file_name= f"{research_topic.replace(' ','_')}_report.md", mime= "text/markdown" ) except Exception as e: st.error(f"An error occurred: {str(e)}") ## Footer st.markdown("----------") st.markdown("Powered by OpenAI SDK and Firecrawl")