

Langroid
Overview :
Langroid is a lightweight, scalable, and principled Python framework designed for effortlessly constructing applications based on LLMs. You can set up agents, equip them with optional components (LLM, vector store, and methods), assign them tasks, and let them collaborate to solve problems by exchanging messages. The inspiration for this multi-agent paradigm comes from the Actor framework (but no prior knowledge is required!). Langroid offers a fresh approach to LLM application development, meticulously designed to simplify the developer experience; it does not use Langchain. We welcome contributions – please refer to the contribution documentation for ideas.
Target Users :
["Rapid development of LLM-powered applications","Build Q&A and conversational systems","Extract structured information from unstructured text","Knowledge extraction and Q&A","Semantic search and recommendation systems"]
Use Cases
Direct interaction with LLM
Define agents, tasks, and run
Communication between multiple agents
Function call example for extracting structured information from text
Features
Support for OpenAI and hundreds of other LLM providers
Support for caching LLM responses
Support for vector storage Qdrant and Chroma
Support for retrieval augmented generation
Support for external document access and citation tracking
Built-in function calls and tool support
Detailed logging and multi-agent interaction tracking
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