FalkorDB integration for LangChain.js - A blazing fast graph database for AI applications.
FalkorDB is a high-performance graph database that enables you to build knowledge graphs and perform complex graph queries with blazing speed. This package provides seamless integration between FalkorDB and LangChain.js, allowing you to leverage graph-based knowledge for your AI applications.
- π Fast Graph Queries: Built on Redis with optimized graph operations
- π Cypher Support: Use Cypher query language for graph operations
- π§ LLM Integration: Works seamlessly with LangChain's QA chains
- π Schema Management: Automatic schema detection and updates
- π Async/Await: Modern async API
- π TypeScript: Full TypeScript support with type definitions
npm install @falkordb/langchain-ts falkordbYou'll also need LangChain and a language model:
npm install langchain @langchain/openai @langchain/communityThe easiest way to run FalkorDB is with Docker:
docker run -p 6379:6379 -it --rm falkordb/falkordb:latestimport { FalkorDBGraph } from "@falkordb/langchain-ts";
import { OpenAI } from "@langchain/openai";
import { GraphCypherQAChain } from "@langchain/community/chains/graph_qa/cypher";
// Initialize connection
const graph = await FalkorDBGraph.initialize({
host: "localhost",
port: 6379,
graph: "movies"
});
// Create some data
await graph.query(
"CREATE (a:Actor {name:'Bruce Willis'})" +
"-[:ACTED_IN]->(:Movie {title: 'Pulp Fiction'})"
);
// Refresh schema
await graph.refreshSchema();
// Set up QA chain
const model = new OpenAI({ temperature: 0 });
// Note: Type assertion needed for LangChain compatibility
const chain = GraphCypherQAChain.fromLLM({
llm: model,
graph: graph as any,
});
// Ask questions about your graph
const response = await chain.run("Who played in Pulp Fiction?");
console.log(response);
// Output: Bruce Willis played in Pulp Fiction.
// Clean up
await graph.close();The library supports multiple ways to connect to FalkorDB:
// Simple URL connection
const graph = await FalkorDBGraph.initialize({
url: "falkor://localhost:6379",
graph: "movies"
});
// URL with authentication
const graph = await FalkorDBGraph.initialize({
url: "falkor://username:password@myserver:6379",
graph: "movies"
});This is useful when you need full control over the driver configuration or want to share a driver across multiple graph instances:
import { FalkorDB } from "falkordb";
// Create a driver with custom configuration
const driver = await FalkorDB.connect({
socket: {
host: "localhost",
port: 6379,
connectTimeout: 10000
},
username: "myuser",
password: "mypassword",
poolOptions: {
min: 2,
max: 10
}
});
// Use the driver with multiple graphs
const moviesGraph = await FalkorDBGraph.initialize({
driver: driver,
graph: "movies"
});
const booksGraph = await FalkorDBGraph.initialize({
driver: driver,
graph: "books"
});
// Close graphs (won't close the shared driver)
await moviesGraph.close();
await booksGraph.close();
// Close the driver when done
await driver.close();Creates and initializes a new FalkorDB connection.
Config Options:
host(string, optional): Database host. Default:"localhost"(ignored ifurlordriveris provided)port(number, optional): Database port. Default:6379(ignored ifurlordriveris provided)graph(string, optional): Graph name to useurl(string, optional): Connection URL format:falkor[s]://[[username][:password]@][host][:port][/db-number]. Takes precedence overhostandportusername(string, optional): Username for authenticationpassword(string, optional): Password for authenticationdriver(FalkorDB, optional): Pre-initialized FalkorDB driver instance. When provided, all other connection options are ignoredenhancedSchema(boolean, optional): Enable enhanced schema details. Default:false
Examples:
Using host and port:
const graph = await FalkorDBGraph.initialize({
host: "localhost",
port: 6379,
graph: "myGraph",
enhancedSchema: true
});Using connection URL:
const graph = await FalkorDBGraph.initialize({
url: "falkor://localhost:6379",
graph: "myGraph"
});Using connection URL with authentication:
const graph = await FalkorDBGraph.initialize({
url: "falkor://username:password@localhost:6379",
graph: "myGraph"
});Using a pre-initialized driver:
import { FalkorDB } from "falkordb";
const driver = await FalkorDB.connect({
socket: { host: "localhost", port: 6379 },
username: "myuser",
password: "mypassword"
});
const graph = await FalkorDBGraph.initialize({
driver: driver,
graph: "myGraph"
});
// When using a pre-initialized driver, you're responsible for closing it
await graph.close(); // This won't close the driver
await driver.close(); // Close the driver manuallyExecutes a Cypher query on the graph.
const result = await graph.query(
"MATCH (n:Person) RETURN n.name LIMIT 10"
);Updates the graph schema information.
await graph.refreshSchema();
console.log(graph.getSchema());Returns the current graph schema as a formatted string.
Returns the structured schema object containing node properties, relationship properties, and relationships.
Switches to a different graph.
await graph.selectGraph("anotherGraph");Closes the database connection.
await graph.close();const graph = await FalkorDBGraph.initialize({
host: "localhost",
port: 6379,
graph: "movies"
});
// Complex query
const result = await graph.query(`
MATCH (a:Actor)-[:ACTED_IN]->(m:Movie)
WHERE m.year > 2000
RETURN a.name, m.title, m.year
ORDER BY m.year DESC
LIMIT 10
`);
console.log(result.data);await graph.executeQueries([
"CREATE (p:Person {name: 'Alice'})",
"CREATE (p:Person {name: 'Bob'})",
"MATCH (a:Person {name: 'Alice'}), (b:Person {name: 'Bob'}) CREATE (a)-[:KNOWS]->(b)"
]);await graph.refreshSchema();
// Get formatted schema
const schema = graph.getSchema();
console.log(schema);
// Get structured schema
const structuredSchema = graph.getStructuredSchema();
console.log(structuredSchema.nodeProps);
console.log(structuredSchema.relationships);try {
const graph = await FalkorDBGraph.initialize({
host: "localhost",
port: 6379,
graph: "myGraph"
});
await graph.query("CREATE (n:Node {name: 'test'})");
} catch (error) {
console.error("Error:", error.message);
} finally {
await graph.close();
}Check out the examples directory for more use cases:
- Basic Queries - Basic graph operations
- Graph DB FalkorDB - Working with FalkorDB
- Quickstart - Quick start guide
- Node.js >= 18
- FalkorDB server running (Redis-compatible)
- LangChain >= 0.1.0
# Clone the repository
git clone https://github.com/FalkorDB/FalkorDB-Langchain-js.git
cd FalkorDB-Langchain-js
# Install dependencies
npm install
# Build
npm run build
# Run tests
npm test
# Run integration tests (requires FalkorDB running)
npm run test:intContributions are welcome! Please feel free to submit a Pull Request.
MIT Β© FalkorDB
- π« GitHub Issues
- π¬ FalkorDB Discord
- π§ Email: support@falkordb.com
- π Website: https://www.falkordb.com/
Special thanks to the LangChain team for their excellent framework and the FalkorDB team for their amazing graph database.