A programming framework for agentic AI 🤖

Harness LLMs with Multi-Agent Programming

AICI: Prompts as (Wasm) Programs

No-code multi-agent framework to build LLM Agents, workflows and applications with your data

[ICML 2024] LLMCompiler: An LLM Compiler for Parallel Function Calling

The open-source LLMOps platform: prompt playground, prompt management, LLM evaluation, and LLM Observability all in one place.

[AI Agent Application Development Framework] - 🚀 Build AI agent native application in very few code 💬 Easy to interact with AI agent in code using structure data and chained-calls syntax 🧩 Enhance AI Agent using plugins instead of rebuild a whole new agent

Low code tool to rapidly build and coordinate multi-agent teams

Langtrace 🔍 is an open-source, Open Telemetry based end-to-end observability tool for LLM applications, providing real-time tracing, evaluations and metrics for popular LLMs, LLM frameworks, vectorDBs and more.. Integrate using Typescript, Python. 🚀💻📊

On-Call Assistant for Prometheus Alerts - Get a head start on fixing alerts with AI investigation

Official Repo for ICML 2024 paper "Executable Code Actions Elicit Better LLM Agents" by Xingyao Wang, Yangyi Chen, Lifan Yuan, Yizhe Zhang, Yunzhu Li, Hao Peng, Heng Ji.

The llama-cpp-agent framework is a tool designed for easy interaction with Large Language Models (LLMs). Allowing users to chat with LLM models, execute structured function calls and get structured output. Works also with models not fine-tuned to JSON output and function calls.

Build, Improve Performance, and Productionize your LLM Application with an Integrated Framework

InternEvo is an open-sourced lightweight training framework aims to support model pre-training without the need for extensive dependencies.

Integrating AI into every workflow with our open-source, no-code platform, powered by the actor model for dynamic, graph-based solutions.

FineTune LLMs in few lines of code (Text2Text, Text2Speech, Speech2Text)

Design, conduct and analyze results of AI-powered surveys and experiments. Simulate social science and market research with large numbers of AI agents and LLMs.

AI-to-AI Testing | Simulation framework for LLM-based applications

ICLR 2024 论文和开源项目合集

Super-Efficient RLHF Training of LLMs with Parameter Reallocation