GRADIO_SUMMARY.md

Gradio Chat UI - Project Summary

📁 Files Created

Main Application Files

1. gradio_app.py - Original Gradio chat UI

   • Uses vertexai.agent_engines._agent_engines.AgentEngine
   • Simple agent selection and chat interface

2. gradio_app_v2.py ⭐ RECOMMENDED

   • Uses google.cloud.aiplatform_v1beta1.AgentEnginesServiceClient
   • More robust agent listing and querying
   • Better error handling
   • Session ID support for conversation continuity
   • Enhanced UI with examples and tips

3. run_gradio.py - Simple launcher script

   • Quick way to start the Gradio app

Setup & Documentation

4. setup_gradio.sh - Setup script

   • Checks prerequisites
   • Installs dependencies
   • Provides next steps

5. GRADIO_README.md - Comprehensive documentation

   • Features overview
   • Installation guide
   • Usage examples
   • Troubleshooting tips

6. QUICKSTART_GRADIO.md - Quick start guide

   • Step-by-step setup instructions
   • Running options
   • Common issues and solutions
   • Success checklist

Updated Files

7. requirements.txt - Added dependencies
   • gradio==5.8.0
   • python-dotenv==1.0.0

🚀 How to Use

Quick Start (3 steps)

# 1. Install dependencies
pip install -r requirements.txt

# 2. Authenticate
gcloud auth application-default login

# 3. Run the app
python gradio_app_v2.py

Then open http://localhost:7860 in your browser!

Alternative Methods

# Using launcher
python run_gradio.py

# Using setup script
./setup_gradio.sh

✨ Key Features

Agent Discovery

• Automatically lists all deployed agents from Agent Engine
• Refresh button to update agent list dynamically
• Clear display names for easy selection

Chat Interface

• Real-time conversation with selected agent
• Chat history with copy functionality
• Session ID for conversation continuity
• Modern, clean UI built with Gradio

RAG Capabilities

The agents support full RAG operations:

• 📋 List document corpora
• 🔍 Query documents
• ➕ Create new corpora
• 📄 Add documents
• ℹ️ Get corpus information
• 🗑️ Delete documents/corpora

📊 Architecture

User Browser
    ↓
Gradio Web UI (Port 7860)
    ↓
gradio_app_v2.py
    ↓
AgentEnginesServiceClient
    ↓
Google Cloud Agent Engine
    ↓
Deployed RAG Agent
    ↓
Vertex AI RAG Service
    ↓
Document Corpora

🔧 Configuration

Environment Variables (in rag_agent/.env)

GOOGLE_CLOUD_PROJECT="your-project-id"
GOOGLE_CLOUD_LOCATION="us-central1"  # or your region
GOOGLE_GENAI_USE_VERTEXAI="true"

Customization Options

In gradio_app_v2.py, you can modify:

• Server Port: Default is 7860

  demo.launch(server_port=8080)
  

• Theme: Change the UI theme

  gr.Blocks(theme=gr.themes.Glass())
  

• Share: Create public temporary URL

  demo.launch(share=True)
  

🎯 Example Usage

List Available Corpora

User: List all available corpora
Agent: Here are the available corpora:
       1. tech-docs
       2. company-handbook
       3. research-papers

Query Documents

User: What information do you have about machine learning?
Agent: Based on the documents in the 'research-papers' corpus, 
       here's what I found about machine learning...

Create Corpus

User: Create a new corpus called 'customer-feedback'
Agent: ✅ Successfully created corpus 'customer-feedback'

Add Data

User: Add this Google Drive file to the corpus: https://drive.google.com/file/d/abc123
Agent: ✅ Successfully added the document to the corpus

🐛 Common Issues & Solutions

No Agents Found

• Cause: No agents deployed to Agent Engine
• Solution: Run make deploy to deploy an agent

Authentication Error

• Cause: Not authenticated with Google Cloud
• Solution: Run gcloud auth application-default login

Module Not Found

• Cause: Dependencies not installed
• Solution: Run pip install -r requirements.txt

Wrong Location

• Cause: GOOGLE_CLOUD_LOCATION doesn't match agent location
• Solution: Update .env file with correct location

📈 Next Steps

Enhancements You Can Add

1. File Upload: Add Gradio File component for document upload

   file_upload = gr.File(label="Upload Document")
   

2. Multi-modal: Add image support

   image_input = gr.Image(label="Upload Image")
   

3. Analytics: Track usage and conversations

   # Log queries to BigQuery or Cloud Logging
   

4. Authentication: Add user authentication

   demo.launch(auth=("username", "password"))
   

5. Streaming: Add streaming responses

   # Use generator pattern for streaming
   

📚 Resources

• Gradio: https://gradio.app/docs
• Vertex AI Agent Engine: https://cloud.google.com/agent-engine/docs
• Google ADK: https://github.com/google/genai-adk

🎉 Summary

You now have a fully functional Gradio chat UI that:

• ✅ Lists all deployed agents
• ✅ Allows agent selection via dropdown
• ✅ Provides real-time chat interface
• ✅ Supports full RAG operations
• ✅ Maintains conversation context
• ✅ Has modern, user-friendly UI

Ready to chat with your RAG agents! 🤖💬