Update README.md

README.md

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-# Vertex AI RAG Agent with ADK
-
-This repository contains a Google Agent Development Kit (ADK) implementation of a Retrieval Augmented Generation (RAG) agent using Google Cloud Vertex AI.
-
-## Overview
-
-The Vertex AI RAG Agent allows you to:
-
-- Query document corpora with natural language questions
-- List available document corpora
-- Create new document corpora
-- Add new documents to existing corpora
-- Get detailed information about specific corpora
-- Delete corpora when they're no longer needed
-
-## Prerequisites
-
-- A Google Cloud account with billing enabled
-- A Google Cloud project with the Vertex AI API enabled
-- Appropriate access to create and manage Vertex AI resources
-- Python 3.9+ environment
-
-## Setting Up Google Cloud Authentication
-
-Before running the agent, you need to set up authentication with Google Cloud:
-
-1. **Install Google Cloud CLI**:
-   - Visit [Google Cloud SDK](https://cloud.google.com/sdk/docs/install) for installation instructions for your OS
-
-2. **Initialize the Google Cloud CLI**:
-   ```bash
-   gcloud init
-   ```
-   This will guide you through logging in and selecting your project.
-
-3. **Set up Application Default Credentials**:
-   ```bash
-   gcloud auth application-default login
-   ```
-   This will open a browser window for authentication and store credentials in:
-   `~/.config/gcloud/application_default_credentials.json`
-
-4. **Verify Authentication**:
-   ```bash
-   gcloud auth list
-   gcloud config list
-   ```
-
-5. **Enable Required APIs** (if not already enabled):
-   ```bash
-   gcloud services enable aiplatform.googleapis.com
-   ```
-
-## Installation
-
-1. **Set up a virtual environment**:
-   ```bash
-   python -m venv .venv
-   source .venv/bin/activate  # On Windows: .venv\Scripts\activate
-   ```
-
-2. **Install Dependencies**:
-   ```bash
-   pip install -r requirements.txt
-   ```
-
-## Using the Agent
-
-The agent provides the following functionality through its tools:
-
-### 1. Query Documents
-Allows you to ask questions and get answers from your document corpus:
-- Automatically retrieves relevant information from the specified corpus
-- Generates informative responses based on the retrieved content
-
-### 2. List Corpora
-Shows all available document corpora in your project:
-- Displays corpus names and basic information
-- Helps you understand what data collections are available
-
-### 3. Create Corpus
-Create a new empty document corpus:
-- Specify a custom name for your corpus
-- Sets up the corpus with recommended embedding model configuration
-- Prepares the corpus for document ingestion
-
-### 4. Add New Data
-Add documents to existing corpora or create new ones:
-- Supports Google Drive URLs and GCS (Google Cloud Storage) paths
-- Automatically creates new corpora if they don't exist
-
-### 5. Get Corpus Information
-Provides detailed information about a specific corpus:
-- Shows document count, file metadata, and creation time
-- Useful for understanding corpus contents and structure
-
-### 6. Delete Corpus
-Removes corpora that are no longer needed:
-- Requires confirmation to prevent accidental deletion
-- Permanently removes the corpus and all associated files
-
-## Troubleshooting
-
-If you encounter issues:
-
-- **Authentication Problems**:
-  - Run `gcloud auth application-default login` again
-  - Check if your service account has the necessary permissions
-
-- **API Errors**:
-  - Ensure the Vertex AI API is enabled: `gcloud services enable aiplatform.googleapis.com`
-  - Verify your project has billing enabled
-
-- **Quota Issues**:
-  - Check your Google Cloud Console for any quota limitations
-  - Request quota increases if needed
-
-- **Missing Dependencies**:
-  - Ensure all requirements are installed: `pip install -r requirements.txt`
-
-## Additional Resources
-
-- [Vertex AI RAG Documentation](https://cloud.google.com/vertex-ai/generative-ai/docs/rag-overview)
-- [Google Agent Development Kit (ADK) Documentation](https://github.com/google/agents-framework)
-- [Google Cloud Authentication Guide](https://cloud.google.com/docs/authentication)
+---
+title: Hello Earth
+emoji: 🌎
+colorFrom: gray
+colorTo: yellow
+sdk: gradio
+sdk_version: 5.49.1
+app_file: gradio/gradio_app_v2.py
+pinned: false
+python_version: 3.13.5
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference