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Text2Everything Integration Summary

This document provides a complete overview of the Text2Everything integration guides and validates that all components work together seamlessly.

📚 Documentation Overview​

Created Guides​

  1. Developer Starter Guide - Comprehensive step-by-step guide
  2. Quick Reference Guide - Condensed reference for experienced developers

Key Features Covered​

✅ H2O Drive Integration

  • Data upload using Simple_Drive_Upload.ipynb approach
  • Organized data structure (schema_metadata, contexts, golden_examples)
  • Bulk upload operations with error handling

✅ Text2Everything API Configuration

  • SDK initialization and authentication
  • Project creation and management
  • Bulk data operations using H2O_Drive_to_T2E_End_to_End.ipynb workflow

✅ Snowflake Connector Setup

  • Database connection configuration
  • Connector creation via T2E API
  • Connection testing and validation

✅ CustomGPT Configuration

  • H2OGPTE UI navigation and setup
  • Collection and prompt creation
  • Model and tool configuration

✅ Agent Environment Setup

  • Environment variable configuration
  • Authentication setup in H2OGPTE UI
  • Production-ready deployment

🔧 Technical Validation​

SDK Validation Methods Used​

The guides now properly use the SDK's built-in validation methods:

# Schema validation examples from the guides
errors = sdk_client.schema_metadata.validate_schema(schema_data, schema_type)

Supported Schema Types:

  • "table" - Requires table and table.columns
  • "dimension" - Requires table.dimension and table.dimension.content
  • "metric" - Requires table.metric and table.metric.content
  • "relationship" - Requires relationship

Integration Flow Validation​

Step 1: H2O Drive → Step 2: Text2Everything

# Data flows seamlessly from H2O Drive to T2E
project_data = await drive_manager.load_project_data(selected_drive_project)
sdk_ready_data = prepare_data_for_sdk(project_data)
contexts = sdk_client.contexts.bulk_create(project_id=project.id, contexts=sdk_ready_data['contexts'])

Step 2: Text2Everything → Step 3: Snowflake

# T2E project connects to Snowflake for SQL execution
snowflake_connector = sdk_client.connectors.create(...)
answer_response = sdk_client.chat.chat_to_answer(
    project_id=project.id,
    connector_id=snowflake_connector.id,
    query="Your business question"
)

Step 4: CustomGPT → Step 5: Agent Environment

# Environment variables flow from setup to agent configuration
TEXT2EVERYTHING_PROJECT_ID = project.id
TEXT2EVERYTHING_CONNECTOR_ID = snowflake_connector.id

🎯 End-to-End Workflow Verification​

Complete Integration Test​

The guides include a comprehensive test function that validates:

  1. ✅ H2O Drive connectivity
  2. ✅ Text2Everything API access
  3. ✅ Snowflake connector functionality
  4. ✅ SQL generation capabilities
  5. ✅ Query execution with results

Production Usage Examples​

Both guides include real-world business query examples:

  • "What are our top 10 customers by total revenue?"
  • "Show me monthly sales trends for the last 12 months"
  • "Find customers who haven't placed orders in the last 90 days"
  • "What's the average order value by customer segment?"

🚨 Error Handling & Troubleshooting​

Comprehensive Error Coverage​

H2O Drive Issues:

  • Connection failures
  • Authentication problems
  • Data upload errors

Text2Everything API Issues:

  • Authentication failures
  • Validation errors using SDK methods
  • Rate limiting and timeouts

Snowflake Connector Issues:

  • Connection configuration problems
  • Credential validation
  • Database connectivity testing

Data Validation Issues:

  • Schema structure validation using sdk_client.schema_metadata.validate_schema()
  • Required field checking for different schema types
  • Bulk upload error handling

📋 Configuration Checklist​

Environment Variables Required​

# H2O Drive
H2O_CLOUD_ENVIRONMENT=https://your-environment.h2o.ai/
H2O_CLOUD_CLIENT_PLATFORM_TOKEN=your-h2o-token-here

# Text2Everything
TEXT2EVERYTHING_URL=http://text2everything.text2everything.svc.cluster.local:8000
H2OGPTE_API_KEY=your-h2ogpte-api-key-here

# Snowflake (optional)
SNOWFLAKE_ACCOUNT=your-account.snowflakecomputing.com
SNOWFLAKE_USERNAME=your-username
SNOWFLAKE_PASSWORD=your-password
SNOWFLAKE_DATABASE=your-database
SNOWFLAKE_WAREHOUSE=COMPUTE_WH

H2OGPTE UI Configuration​

# Agent Environment Variables
TEXT2EVERYTHING_URL = "http://text2everything.text2everything.svc.cluster.local:8000"
TEXT2EVERYTHING_PROJECT_ID = "<project_id_from_step_2>"
TEXT2EVERYTHING_CONNECTOR_ID = "<connector_id_from_step_3>"
H2OGPTE_API_KEY = "<your_api_key>"

CustomGPT Settings​

  • Model: claude-3-7
  • Temperature: 0.0
  • Tools: Python and Shell Scripting
  • Collection: Attached with relevantprompt

🔄 Data Flow Architecture​

Local Data
    ↓
H2O Drive (organized structure)
    ↓
Text2Everything API (via SDK)
    ↓
Snowflake Connector (for execution, via SDK)
    ↓
Agent Environment (to enable agent <> API orchestration)
    ↓
CustomGPT (for putting all settings together)

📊 Success Metrics​

After following both guides, developers should achieve:

  1. Data Accessibility: All project data uploaded and accessible in H2O Drive
  2. API Integration: Successful Text2Everything project with contexts, schemas, and examples
  3. Database Connectivity: Working Snowflake connector for SQL execution
  4. Agentic orchestration: Configured CustomGPT with proper authentication and variables

🚀 Next Steps for Users​

Immediate Actions​

  1. Follow the Developer Starter Guide step-by-step
  2. Use the Quick Reference Guide for ongoing development
  3. Run the diagnostic scripts to validate setup
  4. Test with sample business queries

Continuous Improvement​

  1. Refine prompts based on query results
  2. Add more golden examples for better SQL quality
  3. Optimize performance with different elements-in-prompt limits
  4. Train team members on the integrated workflow

📞 Support Resources​

Integration Status: ✅ Complete and Validated

This integration summary confirms that all components work together seamlessly to provide a complete Text2Everything solution for developers and data scientists.

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