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Young Security's Projects

ai-langchain icon ai-langchain

⚡ Building applications with LLMs through composability ⚡

ai-llama_index icon ai-llama_index

LlamaIndex (formerly GPT Index) is a data framework for your LLM applications

ai-localai icon ai-localai

:robot: The free, Open Source OpenAI alternative. Self-hosted, community-driven and local-first. Drop-in replacement for OpenAI running on consumer-grade hardware. No GPU required. Runs ggml, gguf, GPTQ, onnx, TF compatible models: llama, llama2, rwkv, whisper, vicuna, koala, cerebras, falcon, dolly, starcoder, and many others

ai-localgpt icon ai-localgpt

Chat with your documents on your local device using GPT models. No data leaves your device and 100% private.

ai-metagpt icon ai-metagpt

🌟 The Multi-Agent Framework: Given one line Requirement, return PRD, Design, Tasks, Repo

ai-nightfall_gitub_dlp_action icon ai-nightfall_gitub_dlp_action

GitHub Data Loss Prevention (DLP) Action: Scan Pull Requests for sensitive data, like credentials & secrets, PII, credit card numbers, and more.

ai-ollama icon ai-ollama

Get up and running with Llama 2, Mistral, and other large language models locally.

ai-openai-assistant-swarm icon ai-openai-assistant-swarm

Introducing the Assistant Swarm. An extension to the OpenAI Node SDK to automatically delegate work to any assistant you create in OpenAi through one united interface and manager. Now you can delegate work to a swarm of assistant all specialized with specific tasks you define.

ai-openui icon ai-openui

OpenUI let's you describe UI using your imagination, then see it rendered live.

ai-petals icon ai-petals

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

ai-r2r icon ai-r2r

The framework for fast development and deployment of RAG backends.

ai-rags icon ai-rags

Build ChatGPT over your data, all with natural language

ai-swe-agent icon ai-swe-agent

SWE-agent takes a GitHub issue and tries to automatically fix it, using GPT-4, or your LM of choice. It solves 12.29% of bugs in the SWE-bench evaluation set and takes just 1.5 minutes to run.

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