Developer Overview¶
Welcome to the Rememberizer developer documentation. This section provides comprehensive information about the tools, APIs, and integration options available to developers working with Rememberizer's semantic search and knowledge management capabilities.
Overview of Rememberizer's Developer Features¶
Rememberizer offers a robust set of developer tools designed to help you integrate powerful semantic search capabilities into your applications. As a developer, you can:
- Access semantic search through RESTful APIs with vector embedding technology
- Integrate Rememberizer with your own applications using OAuth2 or API keys
- Build custom applications that leverage users' knowledge bases
- Create vector stores for specialized semantic search databases
- Connect with AI models including OpenAI GPTs and LangChain
Core Components¶
Rememberizer's architecture consists of several key components that work together to provide a comprehensive knowledge management and semantic search system:
| Component | Description |
|---|---|
| API Service | RESTful endpoints providing access to Rememberizer's features |
| Authentication System | OAuth2 and API key management for secure access |
| Vector Stores | Specialized databases optimized for semantic search |
| Mementos | Configurable access filters for knowledge sources |
| Integrations | Connectors to external data sources (Slack, Google Drive, etc.) |
| Document Processing | Systems for chunking, embedding, and indexing content |
Authentication Options¶
Rememberizer supports two primary authentication methods:
- OAuth2 Authentication: For applications requiring access to specific user data and documents. This flow allows users to authorize your application to access their knowledge through configurable mementos.
- API Key Authentication: For accessing vector stores or common knowledge bases directly, without the OAuth flow. This provides a simpler integration path for applications that don't need user-specific data.
Developer Documentation Roadmap¶
This documentation is organized to help you quickly find the information you need:
Getting Started¶
- Registering Rememberizer Apps - Create developer applications
- Authorizing Rememberizer Apps - Implement OAuth2 authorization
- Registering and Using API Keys - Work with API key authentication
Core Features¶
- Vector Stores - Create and manage semantic search databases
- Creating a Rememberizer GPT - Integrate with OpenAI's GPT models
- LangChain Integration - Connect with LangChain applications
- Enterprise Integration Patterns - Architectural patterns for enterprise deployments
API Reference¶
- API Documentation - Comprehensive API reference
- Authentication, search, document management, and more specialized endpoints
Examples and Sample Code¶
- Talk-to-Slack Sample Web App - Example integration
Example Integration Flow¶
Here's a typical flow for integrating Rememberizer with your application:
- Register an application in the Rememberizer developer portal
- Implement OAuth2 authorization in your application
- Request access to user mementos
- Make API calls to search and retrieve knowledge
- Process and display results in your application
// Example: Making an authenticated API request with OAuth token
async function searchUserKnowledge(query, token) {
const response = await fetch('https://api.rememberizer.ai/api/v1/search/', {
method: 'POST',
headers: {
'Authorization': `Bearer ${token}`,
'Content-Type': 'application/json'
},
body: JSON.stringify({ query })
});
return response.json();
}
Next Steps¶
Start by registering your application to obtain client credentials, then explore the API documentation to learn about available endpoints.