GenAI Tools
FalkorDB provides powerful tools and integrations for building intelligent GenAI applications with graph databases and Large Language Models (LLMs).
Topics in This Section
- GraphRAG-SDK: Build intelligent GraphRAG applications with FalkorDB and LLMs.
- AG2: Build multi-agent AI systems with AG2 (formerly AutoGen) and FalkorDB GraphRAG.
- LangChain: Integration with LangChain for AI agents with memory (Python and JavaScript/TypeScript).
- LangGraph: Build stateful, multi-actor agentic applications with LangGraph.
- LlamaIndex: Simplify development of LLM-powered applications with LlamaIndex.
- GraphRAG Toolkit: AWS GraphRAG Toolkit integration for building knowledge graph applications.
- FalkorDB MCP Server: Enable AI assistants like Claude to interact with FalkorDB using the Model Context Protocol.
- QueryWeaver: Open-source Text2SQL tool that converts plain-English questions into SQL using graph-powered schema understanding.
- Code-Graph: Visualize codebases as knowledge graphs to analyze dependencies, detect bottlenecks, and query code structure.
Frequently Asked Questions 5
What are FalkorDB GenAI Tools?
FalkorDB GenAI Tools are a collection of integrations and SDKs that enable developers to build intelligent AI applications using graph-based knowledge retrieval. They include GraphRAG SDK, LangChain/LlamaIndex integrations, AG2 multi-agent framework, LangGraph, MCP Server, QueryWeaver, and Code-Graph.
Which LLM providers are supported?
FalkorDB GenAI Tools support multiple LLM providers including OpenAI, Google Gemini, Anthropic, Groq, Cohere, and Azure OpenAI. The specific providers available depend on the tool you are using.
Do I need a running FalkorDB instance to use these tools?
Yes, all GenAI Tools require a FalkorDB instance. You can run one locally with docker run -p 6379:6379 -it --rm falkordb/falkordb:edge or use FalkorDB Cloud for a managed solution.
What is GraphRAG and how does FalkorDB implement it?
GraphRAG (Graph Retrieval-Augmented Generation) combines knowledge graphs with LLMs to provide more accurate, contextual, and explainable AI responses. FalkorDB implements GraphRAG by storing data as a graph, converting natural language to Cypher queries, and using the retrieved graph data to generate answers.
Which programming languages are supported?
Most FalkorDB GenAI Tools support Python as the primary language. The LangChain integration also supports JavaScript/TypeScript. The MCP Server is built with Node.js. Code-Graph analyzes Python, Java, and C# codebases.