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Building Chat Applications

Glean's Chat API enables you to build powerful conversational AI applications that can access your organization's knowledge. Whether you're creating a simple chatbot or a complex conversational interface, Glean provides the tools you need.

Key Features​

  • Conversational AI: Natural language conversations with context awareness
  • Enterprise Knowledge: Access to your organization's indexed content
  • Streaming Responses: Real-time response streaming for better user experience
  • Citation Support: Automatic source citations for transparency
  • Multi-turn Conversations: Maintain context across conversation turns

Getting Started​

Chat API Overview

Learn about the Chat API endpoints and capabilities

Chatbot Example

Build a complete chatbot using Glean's client libraries

Authentication

Set up authentication for your chat application

Client Libraries

Use our official SDKs for Python, TypeScript, Go, and Java

Common Use Cases​

Customer Support Chatbot​

Build a chatbot that can answer customer questions using your help documentation, FAQs, and knowledge base.

Internal Knowledge Assistant​

Create an internal tool that helps employees find company policies, procedures, and documentation.

Developer Assistant​

Build a coding assistant that can search through your codebase, documentation, and best practices.

Sales Enablement Tool​

Develop a tool that helps sales teams find relevant case studies, product information, and competitive intelligence.

Architecture Patterns​

Simple Request-Response​

For basic Q&A scenarios where each query is independent.

Conversational with Memory​

For multi-turn conversations that maintain context.

RAG Pattern​

For responses that need specific document context.

Best Practices​

Message Structure​

  • Use clear, specific queries for better results
  • Include relevant context in system messages
  • Structure conversations with proper message types

Error Handling​

  • Implement retry logic for transient failures
  • Handle rate limiting gracefully
  • Provide fallback responses for API errors

Performance Optimization​

  • Use streaming for real-time responses
  • Implement caching for frequently asked questions
  • Optimize message history length

Security Considerations​

  • Validate and sanitize user inputs
  • Implement proper authentication
  • Respect user permissions and data access

Next Steps​

  1. Start Simple: Begin with the Chatbot Example
  2. Explore APIs: Review the Chat API Reference
  3. Choose Your Stack: Select a Client Library
  4. Deploy: Consider hosting and scaling requirements