TypeScript
Install the TypeScript/Node.js SDK and start building AI applications with semantic memory.
Build AI applications with TypeScript or JavaScript using the Graphlit SDK.
Installation
Install the Graphlit client with npm or yarn:
npm install graphlit-clientyarn add graphlit-clientpnpm add graphlit-clientRequirements:
Node.js 18 or higher
Graphlit account with API credentials
Quick Start
import { Graphlit } from 'graphlit-client';
async function main() {
const graphlit = new Graphlit();
const response = await graphlit.ingestText(
'Our AI agent needs persistent memory across sessions...',
'Product Requirements',
);
console.log(`✅ Memory created: ${response.ingestText.id}`);
}
main().catch((error) => {
console.error(error);
process.exit(1);
});import { Graphlit } from 'graphlit-client';
async function main() {
const graphlit = new Graphlit();
const response = await graphlit.ingestText(
'Our AI agent needs persistent memory across sessions...',
'Product Requirements'
);
console.log(`✅ Memory created: ${response.ingestText.id}`);
}
main().catch((error) => {
console.error(error);
process.exit(1);
});require('dotenv/config');
const { Graphlit } = require('graphlit-client');
async function main() {
const graphlit = new Graphlit();
const response = await graphlit.ingestText(
'Our AI agent needs persistent memory across sessions...',
'Product Requirements'
);
console.log(`✅ Memory created: ${response.ingestText.id}`);
}
main().catch((error) => {
console.error(error);
process.exit(1);
});That's it! You now have semantic memory for your AI application.
Configuration Options
Environment Variables (Recommended)
import { Graphlit } from 'graphlit-client';
const graphlit = new Graphlit();Security: Never commit credentials to git. Use environment variables or secrets management in production.
Alternative: Explicit Configuration
Only use if you need to override environment variables:
import { Graphlit } from 'graphlit-client';
const graphlit = new Graphlit({
organizationId: process.env.GRAPHLIT_ORGANIZATION_ID,
environmentId: process.env.GRAPHLIT_ENVIRONMENT_ID,
jwtSecret: process.env.GRAPHLIT_JWT_SECRET,
});Common Patterns
Ingest Content
// From URL
const pdf = await graphlit.ingestUri(
'https://example.com/document.pdf',
'Product Brief',
undefined,
true,
);
console.log(`📄 PDF ready: ${pdf.ingestUri.id}`);
// From text
const notes = await graphlit.ingestText(
'Discussion about Q4 planning...',
'Meeting Notes',
);
console.log(`📝 Notes ready: ${notes.ingestText.id}`);Search Memory
const response = await graphlit.queryContents({
search: 'quarterly planning'
});
for (const content of response.contents?.results ?? []) {
console.log(`📄 ${content.name}`);
}Chat with Context
// Create conversation
const conversation = await graphlit.createConversation({
name: 'AI Assistant',
});
// Ask questions
const answer = await graphlit.promptConversation(
'What did we discuss about Q4 planning?',
conversation.createConversation.id,
);
console.log(answer.promptConversation.message?.message);Next Steps
Quickstarts:
Quickstart: Your First Agent - Build a streaming agent in 7 minutes
AI Agents - Create agents with persistent memory
MCP Integration - Connect to your IDE
Examples:
Next.js Applications - Full-stack chat apps
MCP Server - Production MCP implementation
Resources:
Use Case Library - 100+ code examples
Ask Graphlit - AI code assistant
Join Discord - Get help from the community
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