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Add agentic_rag_gpt5 example with GPT-5 integration
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‎examples/python/tools/exa-tool/rag_examples/agentic_rag_gpt5/README.md‎

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# 🧠 Agentic RAG with GPT-5
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An agentic RAG application built with the PraisonAI Agents framework, featuring GPT-5 and built-in vector search for efficient knowledge retrieval and question answering.
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## ✨ Features
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- **🤖 GPT-5**: Latest OpenAI model for intelligent responses
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- **🗄️ Built-in Vector Search**: ChromaDB integration for fast similarity search
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- **🔍 Agentic RAG**: Intelligent retrieval augmented generation
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- **📝 Markdown Formatting**: Beautiful, structured responses
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- **🌐 Dynamic Knowledge**: Add URLs to expand knowledge base
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- **⚡ Real-time Responses**: Fast answer generation- **🎯 Clean Interface**: Simplified UI without configuration complexity
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## 🚀 Quick Start
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### Prerequisites
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- Python 3.11+
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- OpenAI API key with GPT-5 access
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### Installation
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1. **Clone and navigate to the project**
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```bash
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cd rag_examples/agentic_rag_gpt5
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```
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2. **Install dependencies**
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```bash
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pip install -r requirements.txt
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```
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3. **Set up your OpenAI API key**
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```bash
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export OPENAI_API_KEY="your-api-key-here"
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```
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Or create a `.env` file:
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```
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OPENAI_API_KEY=your-api-key-here
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```
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4. **Run the application**
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```bash
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streamlit run agentic_rag_gpt5.py
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```
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## 🎯 How to Use
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1. **Enter your OpenAI API key** in the sidebar
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2. **Add knowledge sources** by entering URLs in the sidebar
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3. **Ask questions** using the text area or suggested prompts
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4. **Get answers** with markdown formatting
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### Suggested Questions
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- **"What is PraisonAI?"** - Learn about the PraisonAI Agents framework
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- **"Teams in PraisonAI"** - Understand how teams work in PraisonAI
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- **"Build RAG system"** - Get a step-by-step guide to building RAG systems
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## 🏗️ Architecture
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### Core Components
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- **`Agent`**: PraisonAI Agents framework for intelligent Q&A
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- **`knowledge`**: Built-in knowledge base that handles URLs and documents
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- **`llm`**: OpenAI GPT-5-nano for generating responses
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- **Built-in Vector Search**: Automatic similarity search without external setup
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### Data Flow
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1. **Knowledge Loading**: URLs are processed and stored in the built-in vector database
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2. **Vector Search**: OpenAI embeddings enable semantic search
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3. **Response Generation**: GPT-5-nano processes information and generates answers
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4. **Formatted Output**: Markdown-formatted responses
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## 🔧 Configuration
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### Database Settings
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- **Vector DB**: Built-in vector database with automatic indexing
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- **Storage**: Local storage managed by PraisonAI Agents
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- **Search**: Automatic similarity search
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### Model Configuration
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- **LLM**: OpenAI GPT-5-nano
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- **Embeddings**: Automatic handling by PraisonAI Agents
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- **Vector Store**: Built-in with automatic document processing
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## 📚 Knowledge Management
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### Adding Sources
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- Use the sidebar to add new URLs
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- Sources are automatically processed and indexed
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- Current sources are displayed as numbered list
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### Default Knowledge
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- Starts with PraisonAI documentation: `https://docs.praisonai.com/introduction/agents.md`
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- Expandable with any web-based documentation
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## 🎨 UI Features
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### Sidebar
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- **API Key Management**: Secure input for OpenAI credentials
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- **URL Addition**: Dynamic knowledge base expansion
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- **Current Sources**: Numbered list of loaded URLs
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### Main Interface
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- **Suggested Prompts**: Quick access to common questions
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- **Query Input**: Large text area for custom questions
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- **Fast Responses**: Quick answer generation
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- **Markdown Rendering**: Beautiful formatted responses
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## 🛠️ Technical Details
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### Dependencies
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```
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streamlit>=1.28.0
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praisonaiagents>=0.1.0
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openai>=1.0.0
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python-dotenv>=1.0.0
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```
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### Key Features
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- **Built-in Knowledge Base**: Automatic document processing and indexing
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- **Vector Search**: Efficient similarity search with built-in database
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- **Caching**: Efficient resource loading with Streamlit caching
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- **Error Handling**: Graceful handling of API and processing errors
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## 🔍 Troubleshooting
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### Common Issues
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**Knowledge base not loading**
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- Check OpenAI API key is valid
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- Ensure URLs are accessible
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- Verify internet connection
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**Agent initialization errors**
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- Check if PraisonAI Agents is properly installed
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- Verify OpenAI API key has sufficient credits
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- Ensure Python version is 3.11+
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### Performance Tips
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- **Cache Resources**: Knowledge base and agent are cached for efficiency
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- **Built-in Vector Search**: Fast similarity search without external setup
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- **Local Storage**: Optimized local storage for optimal performance
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## 🎯 Use Cases
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- **Documentation Q&A**: Ask questions about technical documentation
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- **Research Assistant**: Get answers from multiple knowledge sources
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- **Learning Tool**: Interactive exploration of complex topics
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- **Content Discovery**: Find relevant information across multiple sources
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**Built with ❤️ using PraisonAI Agents and GPT-5**

‎examples/python/tools/exa-tool/rag_examples/agentic_rag_gpt5/agentic_rag_gpt5.py‎

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import streamlit as st
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import os
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from praisonaiagents import Agent
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from dotenv import load_dotenv
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# Load environment variables
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load_dotenv()
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# Page configuration
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st.set_page_config(
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page_title="Agentic RAG with GPT-5",
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page_icon="🧠",
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layout="wide"
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)
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# Main title and description
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st.title("🧠 Agentic RAG with GPT-5")
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st.markdown("""
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This app demonstrates an intelligent AI agent that:
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1. **Answers** your questions clearly and concisely using GPT-5
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⚠️ **Note**: Knowledge base functionality is temporarily disabled due to a compatibility issue with the current version of PraisonAI Agents.
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Enter your OpenAI API key in the sidebar to get started!
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""")
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# Sidebar for API key and settings
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with st.sidebar:
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st.header("🔧 Configuration")
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# OpenAI API Key
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openai_key = st.text_input(
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"OpenAI API Key",
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type="password",
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value=os.getenv("OPENAI_API_KEY", ""),
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help="Get your key from https://platform.openai.com/"
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)
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# Add URLs to knowledge base
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st.subheader("🌐 Add Knowledge Sources")
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st.info("⚠️ Knowledge base functionality is temporarily disabled due to compatibility issues.")
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new_url = st.text_input(
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"Add URL",
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placeholder="https://docs.praisonai.com/introduction",
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help="Enter a URL to add to the knowledge base (currently disabled)"
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)
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if st.button("➕ Add URL", type="primary", disabled=True):
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st.info("Knowledge base functionality is temporarily disabled.")
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# Check if API key is provided
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if openai_key:
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# Initialize knowledge base (cached to avoid reloading)
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@st.cache_resource(show_spinner="📚 Loading knowledge base...")
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def load_knowledge() -> list:
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"""Load and initialize the knowledge base with default URL"""
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return ["https://docs.praisonai.com/introduction/agents.md"] # Default URL
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# Initialize agent (cached to avoid reloading)
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@st.cache_resource(show_spinner="🤖 Loading agent...")
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def load_agent(_knowledge: list) -> Agent:
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"""Create an agent with reasoning capabilities"""
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# Note: Temporarily removed knowledge parameter to avoid rerank error
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# TODO: Re-enable when PraisonAI Agents knowledge issue is resolved
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return Agent(
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name="Knowledge Agent",
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instructions=[
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"You are a helpful AI assistant. Answer questions based on your general knowledge.",
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"Provide clear, well-structured answers in markdown format.",
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"Use proper markdown formatting with headers, lists, and emphasis where appropriate.",
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"Structure your response with clear sections and bullet points when helpful.",
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],
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llm="gpt-5-nano
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markdown=True,
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verbose=True
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)
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# Load knowledge and agent
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knowledge = load_knowledge()
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agent = load_agent(knowledge)
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# Display current URLs in knowledge base
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if knowledge:
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st.sidebar.subheader("📚 Current Knowledge Sources")
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for i, url in enumerate(knowledge, 1):
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st.sidebar.markdown(f"{i}. {url}")
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# Handle URL additions
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if hasattr(st.session_state, 'urls_to_add') and st.session_state.urls_to_add:
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with st.spinner("📥 Loading new documents..."):
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knowledge.append(st.session_state.urls_to_add)
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# Reinitialize agent with new knowledge
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agent = load_agent(knowledge)
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st.success(f"✅ Added: {st.session_state.urls_to_add}")
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del st.session_state.urls_to_add
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st.rerun()
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# Main query section
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st.divider()
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st.subheader("🤔 Ask a Question")
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# Suggested prompts
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st.markdown("**Try these prompts:**")
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col1, col2, col3 = st.columns(3)
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with col1:
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if st.button("What is PraisonAI?", use_container_width=True):
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st.session_state.query = "What is PraisonAI and how do Agents work?"
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with col2:
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if st.button("Teams in PraisonAI", use_container_width=True):
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st.session_state.query = "What are Teams in PraisonAI and how do they work?"
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with col3:
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if st.button("Build RAG system", use_container_width=True):
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st.session_state.query = "Give me a step-by-step guide to building a RAG system."
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# Query input
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query = st.text_area(
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"Your question:",
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value=st.session_state.get("query", "What are AI Agents?"),
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height=100,
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help="Ask anything about the loaded knowledge sources"
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)
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# Run button
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if st.button("🚀 Get Answer", type="primary"):
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if query:
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# Create container for answer
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st.markdown("### 💡 Answer")
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answer_container = st.container()
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answer_placeholder = answer_container.empty()
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# Get the agent's response
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with st.spinner("🔍 Searching and generating answer..."):
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try:
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st.info("🤖 Agent is processing your question...")
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response = agent.start(query)
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answer_placeholder.markdown(
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response,
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unsafe_allow_html=True
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)
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except Exception as e:
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st.error(f"Error getting response: {str(e)}")
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st.error(f"Error type: {type(e).__name__}")
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st.error(f"Full error details: {repr(e)}")
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# Try to provide a helpful response
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answer_placeholder.markdown("""
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**⚠️ Error occurred while processing your question.**
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This might be due to:
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- Knowledge base configuration issues
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- Model access problems
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- Network connectivity issues
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Please try again or check your OpenAI API key.
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""")
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else:
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st.error("Please enter a question")
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else:
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# Show instructions if API key is missing
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st.info("""
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👋 **Welcome! To use this app, you need:**
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- **OpenAI API Key** (set it in the sidebar)
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- Sign up at [platform.openai.com](https://platform.openai.com/)
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- Generate a new API key
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Once you enter the key, the app will load the knowledge base and agent.
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""")
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# Footer with explanation
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st.divider()
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with st.expander("📖 How This Works"):
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st.markdown("""
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**This app uses the PraisonAI Agents framework to create an intelligent Q&A system:**
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⚠️ **Current Status**: Knowledge base functionality is temporarily disabled due to compatibility issues with the current version of PraisonAI Agents (v0.0.157).
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**What Works Now:**
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1. **GPT-5 Integration**: OpenAI's GPT-5 model for generating intelligent responses
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2. **Markdown Formatting**: Beautiful, structured responses
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3. **Agent Framework**: PraisonAI Agents for orchestration
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**What's Temporarily Disabled:**
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- URL-based knowledge base
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- Vector search and retrieval
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- Document processing
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**Key Components:**
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- `Agent`: PraisonAI Agents framework for creating intelligent agents
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- `llm`: OpenAI GPT-5-nano for generating responses
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**Why PraisonAI Agents?**
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- Easy-to-use agent framework
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- Built-in error handling
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- Clean API design
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- Perfect for prototyping and production applications
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**Next Steps:**
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- Monitor PraisonAI Agents updates for knowledge base fixes
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- Re-enable knowledge functionality when compatible version is available
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""")

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