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LLMs can generate feedback on their work, use it to improve the output, and repeat this process iteratively.

one sentence generates any graph

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 high-performance AI models with modular building blocks

Leverage hallucinations from Large Language Models (LLMs) for novelty-driven explorations.

Run LLaMA (and Stanford-Alpaca) inference on Apple Silicon GPUs.

Python API client for AI providers that intends to replace LangChain and LangGraph for most common use cases.

This project is a digital human that can talk and listen to you. It uses OpenAI's GPT to generate responses, OpenAI's Whisper to transcript the audio, Eleven Labs to generate voice and Rhubarb Lip Sync to generate the lip sync.

Give your AI agents persistent memory.

News reader with tags, scoring, and LLM

Transform developer documentation to clean Markdown

OpenLens AI: A Fully Autonomous Multimodal Research Agent｜ OpenLens AI：全自主多模态科研智能体

Scala client for OpenAI API and other major LLM providers

We turn natural language descriptions of behaviors into machine-executable code

Testing and evaluation framework for voice agents

[deprecated] AI Gateway - core infrastructure stack for building production-ready AI Applications

Make your LLM agent and chat with it simple and fast!