#typescript #agent #ai #anthropic #backend_as_a_service #chatbot #gemini #genai #gpt #gpt_4 #llama3 #llm #llmops #nextjs #openai #orchestration #python #rag #workflow #workflows

Dify is an open-source platform for developing AI applications, especially those using Large Language Models (LLMs). It offers a user-friendly interface to build and test AI workflows, integrate various LLMs, and manage models. Key features include a visual workflow builder, comprehensive model support (including GPT, Mistral, and more), a prompt IDE for crafting and testing prompts, RAG pipeline capabilities for document ingestion and retrieval, and agent capabilities with pre-built tools like Google Search and DALL·E.

Using Dify, you can quickly move from prototyping to production with features like observability to monitor application performance and backend-as-a-service for easy integration into your business logic. You can deploy Dify via their cloud service or self-host it in your environment. This makes it highly versatile and beneficial for developers looking to leverage AI efficiently in their projects.

https://github.com/langgenius/dify

#go #gemma #gemma2 #go #golang #llama #llama2 #llama3 #llava #llm #llms #mistral #ollama #phi3

Ollama is a tool that lets you use large language models on your own computer. You can download and install it for macOS, Windows, or Linux. It supports various models like Llama 3.2, Phi 3, and others, which you can run locally using simple commands. For example, to run the Llama 3.2 model, you just need to type `ollama run llama3.2`.

The benefit to you is that you can use powerful language models without relying on cloud services, ensuring your data stays private and secure. You can also customize the models with specific prompts and settings to fit your needs. Additionally, there are many community integrations and libraries available to extend its functionality in various applications.

https://github.com/ollama/ollama

#python #agent #ai #chatglm #fine_tuning #gpt #instruction_tuning #language_model #large_language_models #llama #llama3 #llm #lora #mistral #moe #peft #qlora #quantization #qwen #rlhf #transformers

LLaMA Factory is a tool that makes it easy to fine-tune large language models. It supports many different models like LLaMA, ChatGLM, and Qwen, among others. You can use various training methods such as full-tuning, freeze-tuning, LoRA, and QLoRA, which are efficient and save GPU memory. The tool also includes advanced algorithms and practical tricks to improve performance.

Using LLaMA Factory, you can train models up to 3.7 times faster with better results compared to other methods. It provides a user-friendly interface through Colab, PAI-DSW, or local machines, and even offers a web UI for easier management. The benefit to you is that it simplifies the process of fine-tuning large language models, making it faster and more efficient, which can be very useful for research and development projects.

https://github.com/hiyouga/LLaMA-Factory

#javascript #agent_framework_javascript #ai_agents #crewai #custom_ai_agents #desktop_app #llama3 #llm #llm_application #llm_webui #lmstudio #local_llm #localai #multimodal #nodejs #ollama #rag #vector_database #webui

AnythingLLM is an all-in-one AI app that lets you chat with your documents, use AI agents, and manage multiple users without complicated setup. You can choose from various large language models (LLMs) and vector databases, and it supports different document types like PDF, TXT, and DOCX. It also has a simple chat interface with drag-and-drop functionality and clear citations. You can run it locally or host it remotely, and it includes features like custom AI agents, multi-modal support, and cost-saving measures for managing large documents. This makes it easy to use AI with your documents in a flexible and efficient way.

https://github.com/Mintplex-Labs/anything-llm

#cplusplus #ai #api #audio_generation #distributed #gemma #gpt4all #image_generation #kubernetes #llama #llama3 #llm #mamba #mistral #musicgen #p2p #rerank #rwkv #stable_diffusion #text_generation #tts

LocalAI is a free, open-source alternative to OpenAI that you can run on your own computer or server. It allows you to generate text, images, and audio locally without needing a GPU. You can use it with various models and it supports multiple functionalities like text-to-audio, audio-to-text, and image generation. LocalAI is easy to set up using an installer script or Docker, and it has a user-friendly web interface. This tool is beneficial because it saves you money by not requiring cloud services and gives you full control over your data privacy. Plus, it's community-driven, so there are many resources and integrations available to help you get started and customize it to your needs.

https://github.com/mudler/LocalAI

#python #deepseek #deepseek_r1 #fine_tuning #finetuning #gemma #gemma2 #llama #llama3 #llm #llms #lora #mistral #phi3 #qlora #unsloth

Using Unsloth.ai, you can finetune AI models like Llama, Mistral, and others up to 2x faster and with 70% less memory. The process is beginner-friendly; you just need to add your dataset, click "Run All" in the provided notebooks, and you'll get a faster, finetuned model that can be exported or uploaded to platforms like Hugging Face. This saves time and resources, making it easier to work with large AI models without needing powerful hardware. Additionally, Unsloth supports various features like 4-bit quantization, long context windows, and integration with tools from Hugging Face, making it a powerful tool for AI model development.

https://github.com/unslothai/unsloth

#python #cuda #deepseek #deepseek_llm #deepseek_v3 #inference #llama #llama2 #llama3 #llama3_1 #llava #llm #llm_serving #moe #pytorch #transformer #vlm

SGLang is a tool that makes working with large language models and vision language models much faster and more manageable. It has a fast backend runtime that optimizes model performance with features like prefix caching, continuous batching, and quantization. The frontend language is flexible and easy to use, allowing for complex tasks like chained generation calls and multi-modal inputs. SGLang supports many different models and has an active community behind it. This means you can get your models running quickly and efficiently, saving time and resources. Additionally, the extensive documentation and community support make it easier to get started and resolve any issues.

https://github.com/sgl-project/sglang

#swift #ai #aichat #chatbot #chatgpt #deepseek #deepseek_r1 #gemma #gemma3 #gguf #llama #llama3 #llm #macos #qwen #qwen2 #qwq #qwq_32b #rag #swift #swiftui

Sidekick is a local-first AI application for Macs that helps you find information from your files, folders, and websites without needing the internet. It's private, so your data stays secure on your device. You can ask questions like "Did the Aztecs use captured Spanish weapons?" and get answers with references. Sidekick also supports image generation, LaTeX rendering, and more. This makes it useful for research and work because it keeps your data safe and provides quick access to relevant information.

https://github.com/johnbean393/Sidekick

#jupyter_notebook #chatglm #chatglm3 #gemma_2b_it #glm_4 #internlm2 #llama3 #llm #lora #minicpm #q_wen #qwen #qwen1_5 #qwen2

This guide helps beginners set up and use open-source large language models (LLMs) on Linux or cloud platforms like AutoDL, with step-by-step instructions for environment setup, model deployment, and fine-tuning for models such as LLaMA, ChatGLM, and InternLM[2][4][5]. It covers everything from basic installation to advanced techniques like LoRA and distributed fine-tuning, and supports integration with tools like LangChain and online demo deployment. The main benefit is making powerful AI models accessible and easy to use for students, researchers, and anyone interested in experimenting with or customizing LLMs for their own projects[2][4][5].

https://github.com/datawhalechina/self-llm

#go #gemma3 #go #gpt_oss #granite4 #llama #llama3 #llm #on_device_ai #phi3 #qwen3 #qwen3vl #sdk #stable_diffusion #vlm

NexaSDK runs AI models locally on CPUs, GPUs, and NPUs with a single command, supports GGUF/MLX/.nexa formats, and offers NPU-first Android and macOS support for fast, multimodal (text, image, audio) inference, plus an OpenAI‑compatible API for easy integration. This gives you low-latency, private on-device AI across laptops, phones, and embedded systems, reduces cloud costs and data exposure, and lets you deploy and test new models immediately on target hardware for faster development and better user experience.

https://github.com/NexaAI/nexa-sdk