Open Source TypeScript Large Language Models (LLM)
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TypeScript Large Language Models (LLM)
View 380 business solutionsBrowse free open source TypeScript Large Language Models (LLM) and projects below. Use the toggles on the left to filter open source TypeScript Large Language Models (LLM) by OS, license, language, programming language, and project status.
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Langflow
Low-code app builder for RAG and multi-agent AI applications
Langflow is a low-code app builder for RAG and multi-agent AI applications. It’s Python-based and agnostic to any model, API, or database. -
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Clippy
Clippy, now with some AI
Clippy is an open-source desktop assistant that allows users to run modern large language models locally while presenting them through a nostalgic interface inspired by Microsoft’s classic Clippy assistant from the 1990s. The project serves as both a playful homage to the early days of personal computing and a practical demonstration of local AI inference. Clippy integrates with the llama.cpp runtime to run models directly on a user’s computer without requiring cloud-based AI services. It supports models in the GGUF format, which allows it to run many publicly available open-source LLMs efficiently on consumer hardware. Users interact with the system through a simple animated assistant interface that can answer questions, generate text, and perform conversational tasks. The application includes one-click installation support for several popular models such as Meta’s Llama, Google’s Gemma, and other open models. -
3
Dify
One API for plugins and datasets, one interface for prompt engineering
Dify is an easy-to-use LLMOps platform designed to empower more people to create sustainable, AI-native applications. With visual orchestration for various application types, Dify offers out-of-the-box, ready-to-use applications that can also serve as Backend-as-a-Service APIs. Unify your development process with one API for plugins and datasets integration, and streamline your operations using a single interface for prompt engineering, visual analytics, and continuous improvement. Out-of-the-box web sites supporting form mode and chat conversation mode A single API encompassing plugin capabilities, context enhancement, and more, saving you backend coding effort Visual data analysis, log review, and annotation for applications -
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Flowise
Drag & drop UI to build your customized LLM flow
Open source UI visual tool to build your customized LLM flow using LangchainJS, written in Node Typescript/Javascript. Conversational agent for a chat model which utilizes chat-specific prompts and buffer memory. Open source is the core of Flowise, and it will always be free for commercial and personal usage. Flowise support different environment variables to configure your instance. You can specify the following variables in the .env file inside the packages/server folder. -
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OmniRoute
OmniRoute is an AI gateway for multi-provider LLM
OmniRoute is a routing and orchestration framework designed to simplify the handling of requests, workflows, or data flows across multiple services or endpoints in a unified manner. It focuses on providing a flexible abstraction layer where developers can define routing logic that dynamically directs traffic based on conditions, context, or predefined rules. The project emphasizes modularity and extensibility, allowing users to plug in different services or handlers without tightly coupling components. It is particularly useful in distributed systems where requests need to be intelligently routed between APIs, microservices, or processing pipelines. OmniRoute aims to reduce boilerplate by centralizing routing logic and providing reusable patterns for managing complex flows. Its architecture supports scalability and maintainability, making it suitable for both small applications and larger systems with multiple integrations. -
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promptfoo
Evaluate and compare LLM outputs, catch regressions, improve prompts
Ensure high-quality LLM outputs with automatic evals. Use a representative sample of user inputs to reduce subjectivity when tuning prompts. Use built-in metrics, LLM-graded evals, or define your own custom metrics. Compare prompts and model outputs side-by-side, or integrate the library into your existing test/CI workflow. Use OpenAI, Anthropic, and open-source models like Llama and Vicuna, or integrate custom API providers for any LLM API. -
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OpenClaude
Claude Code opened to any LLM
OpenClaude is an open-source alternative or extension inspired by Claude-style agent systems, designed to provide similar capabilities in a customizable and self-hosted environment. The project focuses on enabling users to run their own AI agents with full control over data, workflows, and integrations, reducing reliance on proprietary platforms. It likely includes support for executing tasks, managing context, and interacting with external tools, allowing agents to perform real-world actions beyond simple text generation. The architecture emphasizes flexibility, enabling developers to adapt the system to different use cases and integrate it with various models or APIs. It may also include modular components for extending functionality, such as plugins or skills. The project reflects a broader trend toward open and decentralized AI systems that prioritize transparency and control. -
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WebLLM
Bringing large-language models and chat to web browsers
WebLLM is a modular, customizable javascript package that directly brings language model chats directly onto web browsers with hardware acceleration. Everything runs inside the browser with no server support and is accelerated with WebGPU. We can bring a lot of fun opportunities to build AI assistants for everyone and enable privacy while enjoying GPU acceleration. WebLLM offers a minimalist and modular interface to access the chatbot in the browser. The WebLLM package itself does not come with UI, and is designed in a modular way to hook to any of the UI components. The following code snippet demonstrates a simple example that generates a streaming response on a webpage. -
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Eidos
An extensible framework for Personal Data Management
Eidos is an extensible personal data management platform designed to help users organize and interact with their information using a local-first architecture. The system transforms SQLite into a flexible personal database that can store structured and unstructured information such as notes, documents, datasets, and knowledge resources. Its interface is inspired by tools like Notion, allowing users to create documents, databases, and custom views to organize personal information. Unlike cloud-based knowledge tools, Eidos runs entirely on the user’s machine, ensuring privacy and high performance through local storage. The platform integrates large language models to enable AI-assisted features such as summarizing documents, translating content, and interacting with stored data conversationally. It also includes an extension system that allows developers to create custom tools, scripts, and workflows using programming languages such as TypeScript or Python. -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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Lobe Icons
Brings AI/LLM brand logos to your React & React Native apps
Lobe Icons is an open-source icon library designed to provide developers with a comprehensive collection of logos and visual assets representing popular artificial intelligence platforms, language models, and related technologies. The project focuses on making it easy for developers to include recognizable AI brand icons in applications such as dashboards, AI tools, documentation sites, or developer portals. The library includes icons for a wide range of AI providers and models, allowing developers to visually represent integrations with tools such as large language models, AI APIs, and machine learning platforms. These icons are distributed in multiple formats including SVG, PNG, and WebP so they can be used in both web and mobile applications. -
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RWKV Runner
A RWKV management and startup tool, full automation, only 8MB
RWKV (pronounced as RwaKuv) is an RNN with GPT-level LLM performance, which can also be directly trained like a GPT transformer (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, fast training, saves VRAM, "infinite" ctxlen, and free text embedding. Moreover it's 100% attention-free. Default configs has enabled custom CUDA kernel acceleration, which is much faster and consumes much less VRAM. If you encounter possible compatibility issues, go to the Configs page and turn off Use Custom CUDA kernel to Accelerate. -
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Superset LLM
Run an army of Claude Code, Codex, etc. on your machine
Superset is a development environment and terminal-based platform designed to orchestrate multiple AI coding agents simultaneously within a single workspace. The tool enables developers to run many autonomous coding agents in parallel without the typical overhead of manually managing multiple terminals, repositories, or branches. Each agent task is isolated in its own Git worktree, ensuring that code changes from different agents do not interfere with each other while allowing developers to track their progress independently. The platform includes built-in monitoring capabilities so users can observe the activity of each agent, receive notifications when tasks are completed, and quickly review changes produced by automated coding workflows. Superset also integrates tools for reviewing code differences, editing generated outputs, and managing the development environment directly from the interface. -
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Deta Surf
Personal AI Notebooks. Organize files & webpages and generate notes
Surf is an open-source AI-driven development tool designed to simplify the process of building and experimenting with artificial intelligence applications. The platform provides a streamlined development environment where developers can test models, run experiments, and deploy small AI services with minimal infrastructure overhead. It focuses on simplicity and speed, allowing developers to prototype ideas quickly without managing complex cloud configurations. Surf integrates modern AI workflows such as prompt-based applications, lightweight APIs, and automated deployment pipelines. The platform is particularly useful for developers who want to experiment with AI models locally while maintaining the option to deploy them in production environments later. Its architecture is designed to minimize setup complexity while still supporting scalable application structures. -
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LangWatch
The platform for LLM evaluations and AI agent testing
LangWatch is an open-source observability and monitoring platform designed to help developers evaluate and improve applications built with large language models. The platform provides tools for tracking model interactions, analyzing prompt behavior, and identifying issues such as hallucinations, latency problems, or unexpected responses. By collecting telemetry data from AI applications, LangWatch allows developers to understand how their systems perform in real-world usage scenarios. The platform includes dashboards that visualize model behavior, enabling teams to monitor trends in response quality and reliability over time. It also provides evaluation tools that allow developers to test prompts and compare outputs across different models or configurations. Through integration with popular AI development frameworks, LangWatch can be embedded directly into AI pipelines to provide continuous monitoring and evaluation. -
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Secret Llama
Fully private LLM chatbot that runs entirely with a browser
Secret Llama is a privacy-first large-language-model chatbot that runs entirely inside your web browser, meaning no server is required and your conversation data never leaves your device. It focuses on open-source model support, letting you load families like Llama and Mistral directly in the client for fully local inference. Because everything happens in-browser, it can work offline once models are cached, which is helpful for air-gapped environments or travel. The interface mirrors the modern chat UX you’d expect—streaming responses, markdown, and a clean layout—so there’s no usability tradeoff to gain privacy. Under the hood it uses a web-native inference engine to accelerate model execution with GPU/WebGPU when available, keeping responses responsive even without a backend. It’s a great option for developers and teams who want to prototype assistants or handle sensitive text without sending prompts to external APIs. -
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Vercel AI SDK
Build AI-powered applications with React, Svelte, Vue, and Solid
The Vercel AI SDK is a library for building AI-powered streaming text and chat UIs. -
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llama.vscode
VS Code extension for LLM-assisted code/text completion
llama.vscode is a Visual Studio Code extension that provides AI-assisted coding features powered primarily by locally running language models. The extension is designed to be lightweight and efficient, enabling developers to use AI tools even on consumer-grade hardware. It integrates with the llama.cpp runtime to run language models locally, eliminating the need to rely entirely on external APIs or cloud providers. The extension supports common AI development features such as code completion, conversational chat assistance, and AI-assisted code editing directly within the IDE. Developers can select and manage models through a configuration interface that automatically downloads and runs the required models locally. The extension also supports agent-style coding workflows, where AI tools can perform more complex tasks such as analyzing project context or editing multiple files. -
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oh my PI
AI Coding agent for the terminal
Oh-My-Pi is an open-source AI agent toolkit focused on creating intelligent coding assistants that operate directly from the terminal environment. The project provides a command-line coding agent capable of analyzing repositories, generating commits, editing code, and interacting with development tools through an integrated tool system. Instead of functioning as a simple prompt-based assistant, the system includes an agent architecture that can inspect Git repositories, analyze changes, and perform development actions with fine-grained control. The platform also supports tool-based workflows where the agent can run shell commands, read files, modify code, and stage changes during development tasks. It includes infrastructure for integrating different AI providers and models through a unified API layer, allowing developers to switch between models while keeping the same agent interface. -
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Chat with GPT
An open-source ChatGPT app with a voice
Chat with GPT is an open-source conversational interface designed to provide an enhanced user experience for interacting with ChatGPT-style language models. The application serves as a customizable alternative client that allows users to connect to language model APIs using their own credentials. Built with modern web technologies such as React and TypeScript, the platform provides a responsive chat interface with advanced features for conversation management. Users can review past chat sessions, modify system prompts, and adjust model parameters such as temperature to control response creativity. The platform also integrates speech capabilities by connecting to text-to-speech systems and speech recognition engines, enabling voice-based conversations with the AI assistant. Additional features include message editing, response regeneration, and the ability to share conversations through public links. -
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FreedomGPT
React and Electron-based app that executes the FreedomGPT LLM locally
FreedomGPT is a locally executed large language model (LLM) application built using React and Electron, allowing users to interact with AI models privately on their Mac or Windows devices. The app enables offline operation, ensuring privacy and security while providing a chat-based interface for seamless communication with the AI. It supports integration with models like Liberty Edge and offers an open-source solution for those seeking more control over their AI interactions. The app's setup is simple, and it includes clear installation guides for both macOS and Windows platforms, as well as detailed instructions for building necessary libraries like llama.cpp. -
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Gemini Fullstack LangGraph Quickstart
Get started w/ building Fullstack Agents using Gemini 2.5 & LangGraph
gemini-fullstack-langgraph-quickstart is a fullstack reference application from Google DeepMind’s Gemini team that demonstrates how to build a research-augmented conversational AI system using LangGraph and Google Gemini models. The project features a React (Vite) frontend and a LangGraph/FastAPI backend designed to work together seamlessly for real-time research and reasoning tasks. The backend agent dynamically generates search queries based on user input, retrieves information via the Google Search API, and performs reflective reasoning to identify knowledge gaps. It then iteratively refines its search until it produces a comprehensive, well-cited answer synthesized by the Gemini model. The repository provides both a browser-based chat interface and a command-line script (cli_research.py) for executing research queries directly. For production deployment, the backend integrates with Redis and PostgreSQL to manage persistent memory, streaming outputs, & background task coordination. -
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Hollama
A minimal LLM chat app that runs entirely in your browser
Hollama is a lightweight open-source chat application designed to run entirely within the browser while interacting with large language model servers. The project provides a minimal but powerful user interface for communicating with local or remote LLMs, including servers powered by Ollama or OpenAI-compatible APIs. Because the application runs as a static web interface, it does not require complex backend infrastructure and can be easily deployed or self-hosted. Hollama supports both text-based and multimodal interactions, allowing users to work with models that process images as well as text. The interface includes features for editing prompts, retrying responses, copying generated code snippets, and storing conversation history locally within the browser. Mathematical expressions can be rendered using KaTeX, and Markdown formatting allows code blocks and structured outputs to appear clearly within conversations. -
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Nanocoder
A beautiful local-first coding agent running in your terminal
Nanocoder is an open-source, local-first coding assistant that runs in the command line and allows developers to use AI models to assist with programming tasks directly from their terminal environment. The tool is designed as a privacy-focused alternative to proprietary AI coding assistants, allowing users to run local models or connect to external APIs while keeping full control over their data and development workflow. Built with TypeScript and distributed as a CLI application, nanocoder enables developers to interact with AI agents that can read files, modify code, execute commands, and assist with debugging tasks. The platform supports multiple AI providers through OpenAI-compatible APIs and can also integrate with local model runtimes such as Ollama or LM Studio. Its architecture emphasizes extensibility through custom commands and integration with Model Context Protocol servers that allow the AI agent to access additional tools. -
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TaxHacker
Self-hosted AI accounting app. LLM analyzer for receipts
TaxHacker is an open-source, self-hosted accounting application that uses artificial intelligence to automate financial record management for freelancers, independent developers, and small businesses. The system is designed to simplify bookkeeping by automatically processing financial documents such as receipts, invoices, and transaction records. It integrates large language models to analyze these documents, extract relevant financial information, and categorize expenses or income based on configurable rules. Users can deploy the application on their own infrastructure, ensuring that financial data remains private and under their control rather than being processed by external services. The software provides tools for tracking income streams, monitoring expenses, and organizing financial records in a structured format. Because the system supports customizable prompts and categories, users can adapt the AI analysis to match their accounting workflows or tax requirements. -
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node-llama-cpp
Run AI models locally on your machine with node.js bindings for llama
node-llama-cpp is a JavaScript and Node.js binding that allows developers to run large language models locally using the high-performance inference engine provided by llama.cpp. The library enables applications built with Node.js to interact directly with local LLM models without requiring a remote API or external service. By using native bindings and optimized model execution, the framework allows developers to integrate advanced language model capabilities into desktop applications, server software, and command-line tools. The system automatically detects the available hardware on a machine and selects the most appropriate compute backend, including CPU or GPU acceleration. Developers can use the library to perform tasks such as text generation, conversational chat, embedding generation, and structured output generation. Because it runs models locally, the platform is particularly useful for privacy-sensitive environments or offline AI deployments.
