Tags: #ai-framework

LangChain is a framework for building robust LLM-powered applications and intelligent agents by chaining together interoperable components and third-party integrations.

An open-source AI orchestration framework for building production-ready LLM applications with modular pipelines and agent workflows.

A Python framework for rapidly building and deploying production-ready conversational AI applications.

A multi-agent framework for studying emergent behaviors and scaling laws in AI systems through simulation and interaction.

A unified and efficient framework for fine-tuning over 100 large language models (LLMs) and vision-language models (VLMs) with both CLI and Web UI.

An all-in-one AI framework for semantic search, LLM orchestration, and language model workflows, powered by an embeddings database.

A programming framework for building multi-agent AI applications that can operate autonomously or collaboratively with humans.

An open-source framework for building real-time, multimodal conversational AI agents with advanced features like voice assistance, diarization, and lip-sync.

Ax is a TypeScript framework that simplifies building reliable AI applications by abstracting prompt engineering and LLM provider complexities, allowing developers to define inputs and outputs.

A low-code, declarative framework for building and deploying custom large language models (LLMs) and other deep neural networks with ease and efficiency.

A cutting-edge framework for multi-agent collaboration to automate real-world tasks using AI.

An open-source framework designed to make large AI model training and inference cheaper, faster, and more accessible through advanced distributed computing and memory optimization techniques.

BAML is an AI framework that transforms prompt engineering into schema engineering, enabling developers to build reliable, type-safe AI workflows and agents across multiple programming languages.

xTuring simplifies the process of fine-tuning and deploying open-source Large Language Models (LLMs) on private data, ensuring privacy, efficiency, and scalability.

A config-based framework for building, managing, and iterating on generative AI applications by separating AI behavior from application code.

VLM-R1 is a stable and generalizable R1-style Large Vision-Language Model that leverages reinforcement learning to significantly improve visual understanding tasks.