GenAI Frameworks

While current foundation models (language, image, speech, embeddings) are available through APIs and can be used just with a http request or a few lines of code, the devil is as always in the details. It is not just about a single API call but full applications, workflows and architectures.

In the last years a number of really powerful open-source orchestration libraries have been developed, many with a large contributor community and a lot of momentum. Even the large cloud providers and AI companies contributed and are using these libraries as in this fast moving world it is hard to keep up otherwise.

Those libraries cover a number of aspects:

  • LLM usage, including Prompt and Output

  • Embedding generation

  • Vector and database integration

  • RAG workflows

  • Agentic workflows

  • Monitoring, Observability and Deployment

GenAI Frameworks

Neo4j and our community have contributed integrations to many of these frameworks. You can find overviews of these integrations in the pages of this section, as well as code examples, tutorials and more.

GraphAcademy Courses

If you want to learn how LLMs and Knowledge Graphs combine to improve GenAI applications, check out the Neo4j & LLM courses on GraphAcademy.

llm fundamentals