#Llm-framework
Showing 45 of 45 repositories tagged #llm-framework, ranked by stars
A programming framework for agentic AI
Pocket Flow: Codebase to Tutorial
Pocket Flow: 100-line LLM framework. Let Agents build Agents!
The open-source LLMOps platform: prompt playground, prompt management, LLM evaluation, and LLM observability all in one place.
Harness LLMs with Multi-Agent Programming
Automatable GenAI Scripting
SRE Agent - CNCF Sandbox Project
No-code multi-agent framework to build LLM Agents, workflows and applications with your data
AICI: Prompts as (Wasm) Programs
[ICML 2024] LLMCompiler: An LLM Compiler for Parallel Function Calling
ContextGem: Effortless LLM extraction from documents
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.
Langtrace ๐ 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. ๐๐ป๐
Virtualized Elastic KV Cache for Dynamic GPU Sharing and Beyond
The foundation layer for agentic intelligence.
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.
ๅๅนดICLR่ฎบๆๅๅผๆบ้กน็ฎๅ้๏ผๅ ๅซICLR2021ใICLR2022ใICLR2023ใICLR2024ใICLR2025.
The TypeScript framework for agents & workflows with react-like components. Lightning fast dev loop. Easy to learn. Easy to extend.
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.
Build, Improve Performance, and Productionize your AI Application
Minimal typescript agent framework that keeps it simple and gives you control - no BS
Ruby's capable AI runtime
A powerful AI observability framework that provides comprehensive insights into agent interactions across platforms, enabling developers to monitor, analyze, and optimize AI-driven applications with minimal integration effort.
A handy lib for smooth interaction with large language models (LLMs) and crafting AI apps.
Modular Python SDK and monorepo for AI agents, LLM integrations, tools, parsers, embeddings, vector stores, and extensible application workflows.
Toolchain built around the Megatron-LM for Distributed Training
โถ๐ Playbooks is a semantic programming system for AI agents
A Typescript library to use LLM providers APIs in a unified way.
A simple and well-tailored LLM application framework that enables you to seamlessly integrate LLM capabilities in the most "Code-Centric" and "Context-Centric" manner. LLM As Function, Prompt As Code.
Self-hosting Langfuse on Amazon ECS with Fargate using CDK Python
Portable AI runtime inspired by docker-compose. Compose agents, RAG pipelines, and MCP servers in one YAML file and run them anywhere.
Continuum โ the agent runtime by ShyftLabs. Build, orchestrate, ship.
It is a comprehensive resource hub compiling all LLM papers accepted at the International Conference on Learning Representations (ICLR) in 2024.
GoalChain for goal-orientated LLM conversation flows
This project aims to introduce and demonstrate the practical applications of RAG using Python code in a Jupyter Notebook environment.
Production-grade ML - F# power & precision guiding Torch performance
LLM security and privacy
npm like package ecosystem for Prompts ๐ค
A framework that uses multi-agents to enable users to perform a systematic data science pipeline with just two inputs.
GeneticPromptLab uses genetic algorithms for automated prompt engineering (for LLMs), enhancing quality and diversity through iterative selection, crossover, and mutation, while efficiently exploring minimal yet diverse samples from the training set.
LLM Security Platform.
Minimal, async-first Python framework for production LLM apps- 2 hard deps, no magic, no SaaS.
Python for logic. English for intelligence.
Cactus AI framework plugin for UE5 to run local LLMs at runtime. https://github.com/cactus-compute/cactus
Pocket Flow: A minimalist LLM framework. Let Agents build Agents!