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llmfit
157 models, 30 providers, one command to find what runs on hardware
llmfit is a terminal-based utility that helps developers determine which large language models can realistically run on their local hardware by analyzing system resources and model requirements. The tool automatically detects CPU, RAM, GPU, and VRAM specifications, then ranks available models based on performance factors such as speed, quality, and memory fit. It provides both an interactive terminal user interface and a traditional CLI mode, enabling flexible workflows for different user... -
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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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BAML
The AI framework that adds the engineering to prompt engineering
BAML is an open-source framework and domain-specific language designed to bring structured engineering practices to prompt development for large language model applications. Instead of treating prompts as unstructured text, BAML introduces a schema-driven approach where prompts are defined as typed functions with explicit inputs and outputs. This design allows developers to treat language model interactions as predictable software components rather than ad-hoc prompt strings. The framework... -
4
pgvecto.rs
Vector database plugin for Postgres, written in Rust
pgvecto.rs is a Postgres extension that provides vector similarity search functions. It is written in Rust and based on pgrx. It is currently under heavy development, please take care when using it in production. pgvecto.rs is a Postgres extension, which means that you can use it directly within your existing database. This makes it easy to integrate into your existing workflows and applications. pgvecto.rs supports filtering. You can set conditions when searching or retrieving points. This... -
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5
lumen
Beautiful git diff viewer, generate commits with AI
Lumen is an open-source command-line developer tool that enhances Git workflows by combining advanced diff visualization with AI-powered code assistance. The tool provides an ergonomic interface for reviewing code changes directly in the terminal, offering syntax-highlighted diffs and structured output to make change analysis easier. In addition to displaying differences between commits, Lumen integrates AI services that can explain code changes, generate commit messages, and assist with Git... -
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Cake
Distributed LLM and StableDiffusion inference
Cake is a compact, powerful toolkit that combines a flexible TCP/UDP proxy, port forwarding system, and connection manager designed for both development and penetration testing scenarios. It enables users to create complex networking flows where traffic can be proxied, relayed, and manipulated between endpoints — useful for debugging networked applications, inspecting protocols, or tunneling traffic through different hops. The tool is designed to work with multiple protocols and supports... -
7
MusicGPT
Generate music based on natural language prompts using LLMs
...Instead, it provides a lightweight environment capable of executing music generation models locally on CPUs or GPUs while maintaining strong performance across operating systems including Windows, macOS, and Linux. Users can describe a musical style, mood, or instrumentation using text prompts, and the system produces original audio samples based on those instructions. The application currently integrates with models such as MusicGen and is designed to support additional models transparently in the future. In addition to a command-line interface, the project includes a web-based interface that enables conversational interaction with the AI model. -
8
Extractous
Fast and efficient unstructured data extraction
Extractous is a Rust-based unstructured data extraction library focused on fast local parsing of documents and other content-heavy files. Its purpose is to extract text and metadata efficiently from formats such as PDF, Word, HTML, email archives, images, and more, without depending on external APIs or separate parsing servers. The project emphasizes performance and low memory usage, and its maintainers describe it as a local-first alternative to heavier extraction stacks. For broader format... -
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Floneum
Instant, controllable, local pre-trained AI models in Rust
Floneum is an open-source platform for building AI-powered workflows using large language models through a visual and extensible interface. The system allows users to design complex AI pipelines using a drag-and-drop workflow builder rather than writing extensive code. It focuses on enabling developers and researchers to create language model applications that combine different tools, data sources, and AI capabilities into automated workflows. Floneum supports a plugin architecture that... -
Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
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Paddler
Open-source LLM load balancer and serving platform for hosting LLMs
Paddler is an open-source LLM infrastructure platform designed to deploy, manage, and scale large language models on private infrastructure. The system acts as a specialized load balancer and serving layer for language models, enabling organizations to run inference workloads without relying on external API providers. It supports running models locally through engines such as llama.cpp while distributing requests across multiple compute nodes to improve performance and reliability. The... -
11
rtk
CLI proxy that reduces LLM token consumption
rtk is an open-source command-line proxy designed to optimize interactions between AI coding agents and the terminal by reducing unnecessary token consumption. When AI assistants execute shell commands during software development tasks, the resulting terminal output often contains large amounts of repetitive or irrelevant information that can overwhelm the model’s context window. RTK intercepts these command outputs and compresses them into concise summaries before sending them to the... -
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HASH
The best way to use and work with blocks
This is HASH's public monorepo which contains our public code, docs, and other key resources. HASH is a platform for decision-making, which helps you integrate, understand and use data in a variety of different ways. HASH does this by combining various different powerful tools together into one simple interface. These range from data pipelines and a graph database, through to an all-in-one workspace, no-code tool builder, and agent-based simulation engine. These exist at varying stages of... -
13
LangChain Rust
LangChain for Rust, the easiest way to write LLM-based programs
LangChain Rust is an open-source Rust implementation inspired by the LangChain ecosystem for building applications powered by large language models. The library aims to provide Rust developers with a structured framework for orchestrating prompts, chains, agents, and external tools within LLM-driven workflows. By adapting LangChain concepts to the Rust programming language, the project emphasizes performance, safety, and efficient memory management. Developers can use the framework to build... -
14
uzu
A high-performance inference engine for AI models
uzu is a high-performance inference engine designed to run artificial intelligence models efficiently on Apple Silicon hardware. Written primarily in Rust and leveraging Apple’s Metal framework, the project focuses on maximizing performance when executing large language models and other AI workloads on devices such as Mac computers with M-series chips. The engine implements a hybrid architecture in which model layers can be executed either as custom GPU kernels or through Apple’s MPSGraph... -
15
Korvus
Korvus is a search SDK that unifies the entire RAG pipeline
Korvus is an open-source retrieval-augmented generation (RAG) pipeline designed to run entirely inside PostgreSQL, allowing developers to build AI search and knowledge systems directly within a database environment. The project consolidates the typical steps of a RAG pipeline—including embedding generation, document retrieval, reranking, and text generation—into a single query executed within the Postgres ecosystem. By leveraging PostgresML and vector extensions such as pgvector, Korvus... -
16
gptcommit
A git prepare-commit-msg hook for authoring commit messages with GPT-3
A git prepare-commit-msg hook for authoring commit messages with GPT-3. With this tool, you can easily generate clear, comprehensive and descriptive commit messages letting you focus on writing code. To use gptcommit, simply run git commit as you normally would. The hook will automatically generate a commit message for you using a large language model like GPT. If you're not satisfied with the generated message, you can always edit it before committing. By default, gptcommit uses the GPT-3... -
17
gptee
LLMs done the UNIX-y way
Output from a language model using standard input as the prompt. Now supporting GPT3.5 chat completions! gptee was designed for use within shell scripts and other programs and also works in interactive shells. You can compose commands and execute them in a script. Proceed with caution before running arbitrary shell scripts. Using a chat completion model (like gpt-3.5-turbo), you can then inject a system message with -s or --system messages. For davinci and other non-chat models, the output... -
18
aigc
An e-book about the real-world application of LLM
"Building Large Language Model Applications: Application Development and Architecture Design" is an open source e-book about the real-world application of LLM. It introduces the basics and applications of large language models, as well as how to build your own models. These include writing, developing, and managing prompts, exploring what the best large language models can bring, and pattern and architecture design for LLM application development. -
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llm-chain
Rust crate for building chains in large language models
We offer a collection of Rust crates packed with features that make working with Large Language Models easy and seamless. With llm-chain, you can focus on building powerful AI applications. Create reusable and easily customizable prompt templates for consistent and structured interactions with LLMs. Build powerful chains of prompts that allow you to execute more complex tasks, step by step, leveraging the full potential of LLMs. Provides seamless integration with LLaMa models, enabling... -
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SmartGPT
A program that provides LLMs with ability to complete complex tasks
SmartGPT is an experimental autonomous agent framework built to help large language models tackle complex tasks with minimal or no additional user input. It works by decomposing larger objectives into smaller steps and gathering information from the internet and other outside sources as needed. The project is written in Rust and emphasizes modularity, allowing developers to compose different “Autos” depending on the workflow they want to build. Its architecture separates responsibility... -
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llm
An ecosystem of Rust libraries for working with large language models
llm is an ecosystem of Rust libraries for working with large language models - it's built on top of the fast, efficient GGML library for machine learning. The primary entry point for developers is the llm crate, which wraps the llm-base and the supported model crates. Documentation for the released version is available on Docs.rs. For end-users, there is a CLI application, llm-cli, which provides a convenient interface for interacting with supported models. Text generation can be done as a...
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