Awesome Chatgpt

What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers?

[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.

Test your prompts, agents, and RAGs. Red teaming/pentesting/vulnerability scanning for AI. Compare performance of GPT, Claude, Gemini, DeepSeek, and more. Simple declarative configs with command line and CI/CD integration. Used by OpenAI and Anthropic.

⌥ AI Coding agent for the terminal — hash-anchored edits, optimized tool harness, LSP, Python, browser, subagents, and more

🤖 Chat with your SQL database 📊. Accurate Text-to-SQL Generation via LLMs using Agentic Retrieval 🔄.

Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.

Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities

🤗 The largest hub of ready-to-use datasets for AI models with fast, easy-to-use and efficient data manipulation tools

🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.

Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.

An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control.

Open source observability platform for logs, metrics, traces, frontend monitoring, pipelines and LLM observability. A sophisticated, simple and highly performant alternative to Datadog, Splunk, and Elasticsearch with 140x lower storage costs and single binary deployment.

SWE-agent takes a GitHub issue and tries to automatically fix it, using your LM of choice. It can also be employed for offensive cybersecurity or competitive coding challenges. [NeurIPS 2024]

Toolkit for linearizing PDFs for LLM datasets/training

AI Agent Framework, the Pydantic way

A Flexible Framework for Experiencing Heterogeneous LLM Inference/Fine-tune Optimizations

Evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks.

GenBI (Generative BI) for AI agents, an open-source, governed text-to-SQL through an open context layer that turns natural-language questions into trusted dashboards, charts, and SQL across 20+ data sources, such as BigQuery, Snowflake, PostgreSQL, ClickHouse, Amazon Redshift, Databricks and more.

Open-source AI coworker, with memory

Browser Harness | Self-healing harness that enables LLMs to complete any task.

Memori is agent-native memory infrastructure. A LLM-agnostic layer that turns agent execution and conversation into structured, persistent state for production systems. Built for enterprise, Memori works with the data infrastructure you already run, no rip-and-replace, and deploys across managed cloud, single-tenant cloud, VPC, and on-premises.

SkillOpt is a text-space optimizer that trains reusable natural-language skills for frozen LLM agents through trajectory-driven edits, validation-gated updates, and deployable best_skill.md artifacts.

MCP Toolbox for Databases is an open source MCP server for databases.

Python SDK for Agent AI Observability, Monitoring and Evaluation Framework. Includes features like agent, llm and tools tracing, debugging multi-agentic system, self-hosted dashboard and advanced analytics with timeline and execution graph view

MNN: A blazing-fast, lightweight inference engine battle-tested by Alibaba, powering high-performance on-device LLMs and Edge AI.

Nano vLLM

TensorRT LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and supports state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT LLM also contains components to create Python and C++ runtimes that orchestrate the inference execution in a performant way.

Talk to any LLM with hands-free voice interaction, voice interruption, and Live2D taking face running locally across platforms

20+ high-performance LLMs with recipes to pretrain, finetune and deploy at scale.

Unity MCP acts as a bridge between AI assistants and your Unity Editor. Give your LLM tools to manage assets, control scenes, edit scripts, and automate tasks within Unity.

🌐 The open-source Agentic browser; alternative to ChatGPT Atlas, Perplexity Comet, Dia.

text and image to video generation: CogVideoX (2024) and CogVideo (ICLR 2023)

Easy-to-use and powerful LLM and SLM library with awesome model zoo.

💡 All-in-one AI framework for semantic search, LLM orchestration and language model workflows

Access large language models from the command-line

Graph-Native Infrastructure for Context and Accountable AI Systems

Build high-quality LLM apps - from prototyping, testing to production deployment and monitoring.

LMCache: Supercharge Your LLM with the Fastest KV Cache Layer

🌸 Run LLMs at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading

The fullstack MCP framework to develop MCP Apps for ChatGPT / Claude & MCP Servers for AI Agents.

"AutoAgent: Fully-Automated and Zero-Code LLM Agent Framework"

High-speed Large Language Model Serving for Local Deployment

ChatRWKV is like ChatGPT but powered by RWKV (100% RNN) language model, and open source.

Swap GPT for any LLM by changing a single line of code. Xinference lets you run open-source, speech, and multimodal models on cloud, on-prem, or your laptop — all through one unified, production-ready inference API.

Crawlee—A web scraping and browser automation library for Python to build reliable crawlers. Extract data for AI, LLMs, RAG, or GPTs. Download HTML, PDF, JPG, PNG, and other files from websites. Works with Parsel, BeautifulSoup, Playwright, and raw HTTP. Both headful and headless mode. With proxy rotation.

Running large language models on a single GPU for throughput-oriented scenarios.

Enterprise-grade, commercial-friendly agentic workflow platform for building next-generation SuperAgents.

Automate your mobile devices with natural language commands - an LLM agnostic mobile Agent 🤖

KAG is a logical form-guided reasoning and retrieval framework based on OpenSPG engine and LLMs. It is used to build logical reasoning and factual Q&A solutions for professional domain knowledge bases. It can effectively overcome the shortcomings of the traditional RAG vector similarity calculation model.

the LLM vulnerability scanner