A data framework for connecting documents and databases to language models, with a prompt template layer that can be overridden per query engine. It is commonly used to build retrieval-augmented prompt pipelines.
Image from the business's own website.
Source: Official GitHub repository. Last checked 2026-09-18. Spot an error? Tell us.
Nearby and similar
A written set of principles for building reliable LLM software, including factors on owning your prompts, owning context construction and treating tools as structured output.
A library for building LLM applications that also auto-tunes them, optimizing prompt text and few-shot demonstrations against a training set. It aims to make prompt tuning as routine as model training.
An open-source, locally running SDK that provides one interface for calling many model providers, with batching, retries and caching handled in the library rather than a hosted service.
The community-maintained continuation of the original AutoGen codebase, providing conversational multi-agent patterns with configurable system messages and group chat managers.
A development framework for generative AI applications with a chained request syntax that builds structured prompts and enforces an expected output schema.
A Python framework and runtime for building agents with instructions, tools, memory and knowledge, then serving them behind an API. It emphasises low overhead per agent instance.