Repository History
4 repositories tagged with LLM Framework
EasyInstruct: An Easy-to-Use Instruction Processing Framework for LLMs
EasyInstruct is an open-source Python framework designed to simplify instruction processing for Large Language Models (LLMs). Accepted at ACL 2024, it offers modularized components for instruction generation, selection, and prompting, supporting various LLMs like GPT-4 and LLaMA. This framework is ideal for researchers and developers working on LLM-based experiments and applications.
GenAIScript: Automatable GenAI Scripting with TypeScript/JavaScript
GenAIScript is an open-source project from Microsoft that enables programmatic assembly of prompts for Large Language Models (LLMs) using JavaScript and TypeScript. It allows developers to orchestrate LLMs, tools, and data directly in code, streamlining the development of GenAI applications. This framework offers seamless Visual Studio Code integration and a flexible command-line interface for efficient GenAI scripting.
fast-agent: Build and Orchestrate Multimodal AI Agents and Workflows
fast-agent is a powerful Python framework designed for creating and interacting with sophisticated multimodal AI agents and workflows. It offers a simple, declarative syntax for defining agents, comprehensive model support, and unique features like end-to-end tested MCP (Multi-modal Communication Protocol) integration. Developers can rapidly build, test, and deploy complex agent applications with advanced capabilities such as structured outputs, vision, and various orchestration patterns.
ROMA: Recursive Open Meta-Agents for High-Performance Multi-Agent Systems
ROMA is a powerful meta-agent framework designed for building high-performance multi-agent systems using recursive hierarchical structures. It simplifies complex problem-solving by breaking tasks into parallelizable components, offering transparent development and proven performance. This open-source framework is extensible, allowing developers to customize agents and benefit from community-driven improvements.