Search Results for "linux gpib support"
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Showing 13 open source projects for "linux gpib support"
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1
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. -
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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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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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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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5
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... -
6
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... -
7
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... -
8
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... -
9
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... -
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10
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
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... -
12
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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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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