Merge pull request #144 from Madhuvod/openai-agents-sdk
Added new Demo: Deep Research Agent using OpenAI Agents SDK
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Shubham Saboo
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ai_agent_tutorials/ai_deep_research_agent/README.md
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ai_agent_tutorials/ai_deep_research_agent/README.md
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# Deep Research Agent with OpenAI Agents SDK and Firecrawl
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A powerful research assistant that leverages OpenAI's Agents SDK and Firecrawl's deep research capabilities to perform comprehensive web research on any topic and any question.
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## Features
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- **Deep Web Research**: Automatically searches the web, extracts content, and synthesizes findings
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- **Enhanced Analysis**: Uses OpenAI's Agents SDK to elaborate on research findings with additional context and insights
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- **Interactive UI**: Clean Streamlit interface for easy interaction
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- **Downloadable Reports**: Export research findings as markdown files
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## How It Works
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1. **Input Phase**: User provides a research topic and API credentials
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2. **Research Phase**: The tool uses Firecrawl to search the web and extract relevant information
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3. **Analysis Phase**: An initial research report is generated based on the findings
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4. **Enhancement Phase**: A second agent elaborates on the initial report, adding depth and context
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5. **Output Phase**: The enhanced report is presented to the user and available for download
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## Requirements
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- Python 3.8+
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- OpenAI API key
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- Firecrawl API key
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- Required Python packages (see `requirements.txt`)
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## Installation
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1. Clone this repository:
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```bash
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git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
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cd ai_agent_tutorials/ai_deep_research_agent
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```
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2. Install the required packages:
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```bash
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pip install -r requirements.txt
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```
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## Usage
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1. Run the Streamlit app:
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```bash
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streamlit run deep_research_openai.py
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```
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2. Enter your API keys in the sidebar:
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- OpenAI API key
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- Firecrawl API key
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3. Enter your research topic in the main input field
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4. Click "Start Research" and wait for the process to complete
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5. View and download your enhanced research report
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## Example Research Topics
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- "Latest developments in quantum computing"
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- "Impact of climate change on marine ecosystems"
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- "Advancements in renewable energy storage"
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- "Ethical considerations in artificial intelligence"
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- "Emerging trends in remote work technologies"
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## Technical Details
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The application uses two specialized agents:
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1. **Research Agent**: Utilizes Firecrawl's deep research endpoint to gather comprehensive information from multiple web sources.
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2. **Elaboration Agent**: Enhances the initial research by adding detailed explanations, examples, case studies, and practical implications.
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The Firecrawl deep research tool performs multiple iterations of web searches, content extraction, and analysis to provide thorough coverage of the topic.
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import asyncio
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import streamlit as st
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from typing import Dict, Any, List
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from agents import Agent, Runner, trace
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from agents import set_default_openai_key
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from firecrawl import FirecrawlApp
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from agents.tool import function_tool
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# Set page configuration
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st.set_page_config(
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page_title="Enhanced Research Assistant",
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page_icon="🔍",
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layout="wide"
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)
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# Initialize session state for API keys if not exists
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if "openai_api_key" not in st.session_state:
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st.session_state.openai_api_key = ""
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if "firecrawl_api_key" not in st.session_state:
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st.session_state.firecrawl_api_key = ""
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# Sidebar for API keys
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with st.sidebar:
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st.title("API Configuration")
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openai_api_key = st.text_input(
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"OpenAI API Key",
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value=st.session_state.openai_api_key,
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type="password"
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)
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firecrawl_api_key = st.text_input(
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"Firecrawl API Key",
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value=st.session_state.firecrawl_api_key,
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type="password"
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)
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if openai_api_key:
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st.session_state.openai_api_key = openai_api_key
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set_default_openai_key(openai_api_key)
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if firecrawl_api_key:
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st.session_state.firecrawl_api_key = firecrawl_api_key
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# Main content
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st.title("🔍 Enhanced Deep Research Agent")
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st.markdown("This OpenAI Agent from the OpenAI Agents SDK performs deep research on any topic using Firecrawl")
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# Research topic input
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research_topic = st.text_input("Enter your research topic:", placeholder="e.g., Latest developments in AI")
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# Keep the original deep_research tool
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@function_tool
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async def deep_research(query: str, max_depth: int, time_limit: int, max_urls: int) -> Dict[str, Any]:
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"""
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Perform comprehensive web research using Firecrawl's deep research endpoint.
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"""
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try:
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# Initialize FirecrawlApp with the API key from session state
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firecrawl_app = FirecrawlApp(api_key=st.session_state.firecrawl_api_key)
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# Define research parameters
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params = {
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"maxDepth": max_depth,
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"timeLimit": time_limit,
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"maxUrls": max_urls
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}
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# Set up a callback for real-time updates
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def on_activity(activity):
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st.write(f"[{activity['type']}] {activity['message']}")
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# Run deep research
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with st.spinner("Performing deep research..."):
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results = firecrawl_app.deep_research(
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query=query,
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params=params,
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on_activity=on_activity
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)
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return {
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"success": True,
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"final_analysis": results['data']['finalAnalysis'],
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"sources_count": len(results['data']['sources']),
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"sources": results['data']['sources']
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}
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except Exception as e:
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st.error(f"Deep research error: {str(e)}")
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return {"error": str(e), "success": False}
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# Keep the original agents
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research_agent = Agent(
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name="research_agent",
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instructions="""You are a research assistant that can perform deep web research on any topic.
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When given a research topic or question:
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1. Use the deep_research tool to gather comprehensive information
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- Always use these parameters:
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* max_depth: 3 (for moderate depth)
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* time_limit: 180 (3 minutes)
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* max_urls: 10 (sufficient sources)
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2. The tool will search the web, analyze multiple sources, and provide a synthesis
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3. Review the research results and organize them into a well-structured report
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4. Include proper citations for all sources
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5. Highlight key findings and insights
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"""
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)
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elaboration_agent = Agent(
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name="elaboration_agent",
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instructions="""You are an expert content enhancer specializing in research elaboration.
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When given a research report:
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1. Analyze the structure and content of the report
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2. Enhance the report by:
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- Adding more detailed explanations of complex concepts
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- Including relevant examples, case studies, and real-world applications
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- Expanding on key points with additional context and nuance
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- Adding visual elements descriptions (charts, diagrams, infographics)
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- Incorporating latest trends and future predictions
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- Suggesting practical implications for different stakeholders
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3. Maintain academic rigor and factual accuracy
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4. Preserve the original structure while making it more comprehensive
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5. Ensure all additions are relevant and valuable to the topic
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"""
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)
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# Attach the deep research tool to the research agent
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research_agent.tools.append(deep_research)
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async def run_research_process(topic: str):
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"""Run the complete research process."""
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# Step 1: Initial Research
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with st.spinner("Conducting initial research..."):
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research_result = await Runner.run(research_agent, topic)
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initial_report = research_result.final_output
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# Display initial report in an expander
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with st.expander("View Initial Research Report"):
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st.markdown(initial_report)
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# Step 2: Enhance the report
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with st.spinner("Enhancing the report with additional information..."):
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elaboration_input = f"""
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RESEARCH TOPIC: {topic}
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INITIAL RESEARCH REPORT:
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{initial_report}
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Please enhance this research report with additional information, examples, case studies,
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and deeper insights while maintaining its academic rigor and factual accuracy.
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"""
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elaboration_result = await Runner.run(elaboration_agent, elaboration_input)
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enhanced_report = elaboration_result.final_output
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return enhanced_report
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# Main research process
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if st.button("Start Research", disabled=not (openai_api_key and firecrawl_api_key and research_topic)):
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if not openai_api_key or not firecrawl_api_key:
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st.warning("Please enter both API keys in the sidebar.")
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elif not research_topic:
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st.warning("Please enter a research topic.")
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else:
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try:
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# Create placeholder for the final report
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report_placeholder = st.empty()
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# Run the research process
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enhanced_report = asyncio.run(run_research_process(research_topic))
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# Display the enhanced report
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report_placeholder.markdown("## Enhanced Research Report")
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report_placeholder.markdown(enhanced_report)
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# Add download button
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st.download_button(
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"Download Report",
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enhanced_report,
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file_name=f"{research_topic.replace(' ', '_')}_report.md",
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mime="text/markdown"
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)
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except Exception as e:
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st.error(f"An error occurred: {str(e)}")
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# Footer
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st.markdown("---")
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st.markdown("Powered by OpenAI Agents SDK and Firecrawl")
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@ -0,0 +1,4 @@
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openai-agents
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firecrawl
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streamlit
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firecrawl-py
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