Search Results for "mistral"
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Showing 49 open source projects for "mistral"
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Mistral Inference
Official inference library for Mistral models
Open and portable generative AI for devs and businesses. We release open-weight models for everyone to customize and deploy where they want it. Our super-efficient model Mistral Nemo is available under Apache 2.0, while Mistral Large 2 is available through both a free non-commercial license, and a commercial license. -
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Mistral Vibe CLI
Minimal CLI coding agent by Mistral
Mistral Vibe is an AI-powered “vibe-coding” command-line interface (CLI) and coding-assistant framework built by Mistral AI to let developers write, refactor, search, and manage code through natural language and context-aware automation, rather than manual typing only. It aims to take developers out of repetitive boilerplate and let them stay “in the flow”: you can ask the tool to generate functions, refactor code, search across the codebase, manipulate files, commit changes via Git, or run commands — all from a unified CLI interface. ... -
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mistral.rs
Fast, flexible LLM inference
mistral.rs is a fast and flexible LLM inference engine implemented in Rust, designed to run and serve modern language models with an emphasis on performance and practical deployment. It provides multiple entry points for developers, including a CLI for running models locally and an HTTP server that exposes an OpenAI-compatible API surface for easy integration with existing clients. The project includes hardware-aware tooling that can benchmark a system and choose sensible quantization and... -
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Mistral Finetune
Memory-efficient and performant finetuning of Mistral's models
mistral-finetune is an official lightweight codebase designed for memory-efficient and performant finetuning of Mistral’s open models (e.g. 7B, instruct variants). It builds on techniques like LoRA (Low-Rank Adaptation) to allow customizing models without full parameter updates, which reduces GPU memory footprint and training cost. The repo includes utilities for data preprocessing (e.g. reformat_data.py), validation scripts, and example YAML configs for training variants like 7B base or instruct models. ... -
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bolt.diy
Prompt, run, edit, & deploy full-stack web applications using any LLM
bolt.diy is an open-source platform that allows you to easily create, run, edit, and deploy full-stack web applications using a variety of large language models (LLMs). It supports popular models like OpenAI, Anthropic, Ollama, OpenRouter, Gemini, LMStudio, Mistral, xAI, HuggingFace, DeepSeek, and Groq, and provides the flexibility to integrate additional models through the Vercel AI SDK. Whether you’re experimenting with pre-built models or developing custom AI-driven applications, bolt.diy offers a smooth and intuitive experience for building AI-powered web apps. Its open-source nature invites community contributions, and it serves as an ideal platform for developers looking to leverage the latest AI technologies. -
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Jan.ai
Open source alternative to ChatGPT that runs 100% offline
...It allows you to download and run LLMs (local language models) offline while also offering optional integration with cloud-based model providers—giving you full control over your data and AI interactions. Download and run LLMs (Llama, Gemma, Qwen, GPT-oss etc.) from HuggingFace. Connect to GPT models via OpenAI, Claude models via Anthropic, Mistral, Groq, and others. Create specialized AI assistants for your tasks. MCP integration for agentic capabilities. -
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SGLang
SGLang is a fast serving framework for large language models
SGLang is a fast serving framework for large language models and vision language models. It makes your interaction with models faster and more controllable by co-designing the backend runtime and frontend language. -
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Zola
Open chat interface for all your models
Zola is an open-source chat interface that gives users one place to interact with multiple AI models. It supports providers such as OpenAI, Mistral, Claude, Gemini, OpenRouter, and locally hosted Ollama models. Users can bring their own API keys, upload files, and customize system prompts and layouts. The interface is responsive and includes light and dark themes. Zola can be self-hosted and also supports Docker-based deployment, including setups with Ollama. Its stack uses Next.js, Tailwind CSS, shadcn/ui, the Vercel AI SDK, and Supabase, while MCP support is under development. -
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aisuite
Simple, unified interface to multiple Generative AI providers
...Today, the library is primarily focused on chat completions. We will expand it to cover more use cases in the near future. Currently supported providers are - OpenAI, Anthropic, Azure, Google, AWS, Groq, Mistral, HuggingFace and Ollama. To maximize stability, aisuite uses either the HTTP endpoint or the SDK for making calls to the provider. -
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Portia SDK Python
Portia Labs Python SDK for building agentic workflows
...It supports tool-backed agents capable of real-world interactions—like web browsing, API access, and human-in-the-loop clarifications—while maintaining transparency and auditability through structured plans and execution hooks. Designed for production environments, the SDK integrates with local or cloud LLMs (e.g. OpenAI, Anthropic, Mistral, Gemini) and supports extensive tool registries, session handling, and memory management. -
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Jlama
Jlama is a modern LLM inference engine for Java
...This allows organizations to integrate generative AI features into their systems while maintaining full control over data privacy and infrastructure. The engine supports a wide range of open-source model architectures and formats, including variants of Llama, Mistral, and other transformer-based models. It provides tools for running chat interactions, completing prompts, or exposing an OpenAI-compatible REST API for applications that expect standard LLM endpoints. The project focuses on performance and portability by using native Java optimizations and the Java Vector API to accelerate inference workloads. -
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RunAnywhere
Production ready toolkit to run AI locally
...By running models entirely on device, the platform eliminates network latency and protects user data because information does not leave the device. The SDK supports popular open-source models such as Llama, Mistral, and Qwen, enabling developers to build AI-powered features such as chat interfaces and voice assistants with minimal external dependencies. It also includes integrated pipelines that combine speech-to-text, large language models, and text-to-speech into a complete conversational system. -
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Pruna AI
Pruna is a model optimization framework built for developers
Pruna is an open-source, self-hostable AI inference engine designed to help teams deploy and manage large language models (LLMs) efficiently across private or hybrid infrastructures. Built with performance and developer ergonomics in mind, Pruna simplifies inference workflows by enabling multi-model orchestration, autoscaling, GPU resource allocation, and compatibility with popular open-source models. It is ideal for companies or teams looking to reduce reliance on external APIs while... -
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LazyLLM
Easiest and laziest way for building multi-agent LLMs applications
LazyLLM is an optimized, lightweight LLM server designed for easy and fast deployment of large language models. It is fully compatible with the OpenAI API specification, enabling developers to integrate their own models into applications that normally rely on OpenAI’s endpoints. LazyLLM emphasizes low resource usage and fast inference while supporting multiple models. -
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Axolotl
Go ahead and axolotl questions
Axolotl is a powerful and flexible framework for fine-tuning large language models on custom datasets. Built for researchers and developers, Axolotl simplifies the process of adapting LLMs for specific tasks, including chat, code generation, and instruction following. It supports a wide variety of model architectures and offers out-of-the-box optimization strategies for efficient training. -
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DevoxxGenie
DevoxxGenie is a plugin for IntelliJ IDEA that uses local LLM's
Devoxx Genie is a fully Java-based LLM Code Assistant plugin for IntelliJ IDEA, designed to integrate with local LLM providers such as Ollama, LMStudio, GPT4All, Llama.cpp, and Exo but also cloud-based LLMs such as OpenAI, Anthropic, Mistral, Groq, Gemini, DeepInfra, DeepSeek, OpenRouter and Azure OpenAI. -
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Open WebUI
User-friendly AI Interface
Open WebUI is an extensible, feature-rich, and user-friendly self-hosted AI platform designed to operate entirely offline. It supports various LLM runners like Ollama and OpenAI-compatible APIs, with a built-in inference engine for Retrieval Augmented Generation (RAG), making it a powerful AI deployment solution. Key features include effortless setup via Docker or Kubernetes, seamless integration with OpenAI-compatible APIs, granular permissions and user groups for enhanced security,... -
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Mirascope
LLM abstractions that aren't obstructions
Mirascope is a powerful, flexible, and user-friendly library that simplifies the process of working with LLMs through a unified interface that works across various supported providers, including OpenAI, Anthropic, Mistral, Gemini, Groq, Cohere, LiteLLM, Azure AI, Vertex AI, and Bedrock. Whether you're generating text, extracting structured information, or developing complex AI-driven agent systems, Mirascope provides the tools you need to streamline your development process and create powerful, robust applications. -
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Ptero
AI Chat with powerful models for free
Ptero is a free, open-source multi-model AI chat platform built around a simple browser interface. It provides access to several language-model families, including DeepSeek, Llama, Qwen, MiniMax, and Mistral. Users can switch models quickly to compare responses without creating an account. Conversations are stored locally in the browser rather than saved as server-side chat history. Project workspaces help organize chats, while a media library lets users attach and manage files for additional context. Ptero can also be embedded into WordPress sites through its PHP plugin and shortcode. ... -
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5ire
5ire is a cross-platform desktop AI assistant, MCP client
5ire is a sleek, cross‑platform desktop AI assistant and MCP client that connects to major service providers, supports a local knowledge base and tool integration via MCP servers, enabling robust RAG and assistant features. These components are required as they constitute the runtime environment for the MCP Server. If you don't anticipate using the tools feature immediately, you may choose to skip this installation step and complete it later when the need arises. MCP is an open protocol that... -
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any-llm
Communicate with an LLM provider using a single interface
any-llm is a unified SDK and platform developed by Mozilla AI that allows developers to interact with multiple large language model providers through a single, consistent interface. Instead of rewriting code for each provider, developers can switch between services like OpenAI, Anthropic, Mistral, and Ollama simply by changing configuration parameters. The project is designed to be framework-agnostic, making it easy to integrate into scripts, applications, or production systems without being tied to a specific stack. It includes a core SDK for direct usage as well as an optional gateway layer that adds enterprise features such as budget management, API key control, usage analytics, and multi-tenant support. ... -
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ChatGPT-Telegram-Workers
Deploy your own Telegram ChatGPT bot on Cloudflare Workers with ease
The simplest and fastest way to deploy your own ChatGPT Telegram bot. Use Cloudflare Workers, single file, copy and paste directly, no dependencies required, no need to configure local development environment, no domain name required, serverless. You can customize the system initialization information so that your debugged personality never disappears. -
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How to Train Your GPT
Build a modern LLM from scratch. Every line commented
...It is written for learners with minimal machine-learning background, using simple explanations, commented code, and practical examples. The project covers the same broad family of architecture behind systems such as GPT-style models, LLaMA-style models, Claude-style systems, and Mistral-style models. It includes chapters and topic explainers on tokenizers, embeddings, attention, RoPE, RMSNorm, SwiGLU, KV cache, AdamW, mixed precision, training loops, and inference. The guide emphasizes writing every important component manually rather than only calling high-level APIs. Its purpose is to make the internals of language models understandable through runnable code and step-by-step explanations. -
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ProxyAI
The leading open-source AI copilot for JetBrains
ProxyAI is an open-source AI-powered coding assistant designed primarily for JetBrains IDEs, offering a highly customizable alternative to tools like GitHub Copilot while maintaining flexibility across multiple AI providers and deployment environments. It allows developers to connect to a wide range of language models, including cloud-based services and locally hosted models, enabling both online and fully offline workflows depending on user preferences. The platform emphasizes deep... -
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RubyLLM
One beautiful Ruby API for OpenAI, Anthropic, Gemini, Bedrock
...The library is designed to simplify the process of integrating AI capabilities into Ruby applications by abstracting away differences between model providers and API formats. Developers can use RubyLLM to communicate with a wide range of AI services including OpenAI, Anthropic, Google Gemini, Mistral, Ollama, and other compatible platforms through a single programming interface. The library supports advanced capabilities such as tool calling, structured responses, and schema-based outputs that enable developers to build more reliable AI-driven applications. RubyLLM also integrates smoothly with modern Ruby frameworks and development workflows, making it easier to embed AI functionality into web services, background jobs, and automation scripts.
