|
LangChain
|
Build LLM applications with memory, agents, and chat models using LanceDB as a vector store |
|
LlamaIndex
|
Create data-aware LLM applications with structured data retrieval and RAG pipelines |
|
Kiln AI
|
Build and evaluate RAG pipelines with a drag-and-drop UI or Python library, deploy to LanceDB |
|
PromptTools
|
Evaluate and optimize LLM prompts with LanceDB for storing and retrieving evaluation results |
|
Pydantic
|
Define structured data models and schemas for LanceDB tables with type safety |
|
GenKit
|
Build AI applications with Google’s GenKit framework using LanceDB for vector storage |
|
Meta Llama Synthetic Data Kit
|
Generate high-quality synthetic datasets for fine-tuning large language models (LLMs) |
