Search Results for "ai coding model" - Page 3
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Showing 86 open source projects for "ai coding model"
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Rust Docs MCP Server
Prevents outdated Rust code suggestions from AI assistants
The Rust Docs MCP Server fetches documentation for specified Rust crates, generates embeddings for the content, and provides an MCP tool to answer questions about the crate based on the documentation context. -
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OpenFang
Open-source Agent Operating System
OpenFang is an open-source agent operating system designed to orchestrate autonomous AI agents and workflows in a structured, production-oriented environment. Written primarily in Rust, the project focuses on building a high-performance runtime where multiple specialized agents can collaborate to complete complex computational or development tasks. It aims to move beyond simple chat-based agents by providing infrastructure for persistent agent memory, task coordination, and scalable... -
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shimmy
Python-free Rust inference server
...Written primarily in Rust, the tool provides a small standalone binary that exposes an API compatible with the OpenAI interface, allowing existing applications to interact with local models without significant code changes. This compatibility enables developers to replace remote AI services with locally hosted models while keeping their existing software architecture intact. Shimmy focuses on performance and simplicity, using efficient runtime components to minimize memory usage and startup time compared to heavier inference frameworks. It supports modern model formats such as GGUF and SafeTensors and can automatically discover models stored locally or in common directories used by other AI tools. ... -
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Plano
Delivery infrastructure for agentic apps
Plano is an AI-native proxy and data plane designed to simplify the infrastructure required to deploy and operate agentic applications in production environments. It removes repetitive plumbing work from application code by centralizing capabilities such as agent routing, orchestration, guardrails, observability, and model selection. Built on modern proxy technology and compatible with any language or AI framework, Plano enables developers to focus on core agent logic instead of infrastructure complexity. ... -
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GitButler
The GitButler version control client, backed by Git
...It keeps Git compatibility at the core, meaning your work still maps to commits, branches, and pushes to standard Git servers, but it rethinks how you interact with that underlying model. The project is designed around developer productivity, emphasizing smoother workflows for handling multiple streams of work, reviewing changes, and recovering from mistakes without the usual friction. It also positions itself for AI-assisted development patterns, where tooling needs to support rapid iteration and parallel work while staying understandable and reversible. ... -
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riddle
The diary of Tom Riddle for the reMarkable Paper Pro
Riddle turns a reMarkable Paper Pro into an interactive AI-powered version of Tom Riddle's enchanted diary. Users write directly on the e-ink page, pause, and watch their ink fade before a handwritten response appears stroke by stroke. The Rust application captures pressure-sensitive pen events, converts completed pages to images, and sends them to a vision-capable language model. Responses are transformed into thin pen paths and animated through either a windowed display or a low-latency full-screen takeover mode. ... -
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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 API, allowing it to balance performance and compatibility depending on the workload. By utilizing Apple’s unified memory architecture, uzu reduces memory copying overhead and improves inference throughput for local AI workloads. ... -
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clawhip
claw + whip: Event-to-channel notification router
...It acts as a central event-processing system that listens to sources such as Git, GitHub, tmux sessions, and custom CLI events, then routes them through a typed pipeline. Built with a clean separation between routing, rendering, and delivery, Clawhip ensures reliable and organized notifications without polluting AI agent contexts. It integrates seamlessly with tools like OpenClaw, OMX (oh-my-codex), and OMC (oh-my-claudecode) to monitor coding sessions and automate updates. The system emphasizes normalized event contracts (like session.* and agent.*) for consistent automation and routing logic. Overall, Clawhip serves as an operational backbone for developer workflows, enabling real-time visibility and control over distributed AI-driven tasks. -
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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. -
Build Securely on Azure with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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Destructive Command Guard
The Destructive Command Guard (dcg) is for blocking dangerous git
Destructive Command Guard is a high-performance safety hook for AI coding agents and command-line workflows. It intercepts shell commands before execution and blocks operations that could erase files, rewrite Git history, destroy infrastructure, or remove data. The Rust implementation uses fast filtering and context-aware rules to distinguish dangerous execution from harmless text matches. Its modular security packs cover Git, filesystems, databases, containers, cloud platforms, Kubernetes, Terraform, and other tools. ... -
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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... -
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DeepProve
Framework to prove inference of ML models blazingly fast
DeepProve is an advanced cryptographic framework designed to verify machine learning model inference using zero-knowledge proofs, enabling trustless validation of AI computations without exposing underlying data. The project focuses on zkML, a rapidly emerging field that combines machine learning with zero-knowledge cryptography to ensure both privacy and correctness. It supports neural network architectures such as multilayer perceptrons and convolutional neural networks, allowing developers to prove that a model’s output is correct without revealing inputs or model details. deep-prove leverages advanced proof systems such as sumcheck protocols and GKR-based constructions to achieve significantly faster proving times compared to earlier approaches. ... -
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Rig
Rust framework for building modular and scalable LLM-powered apps
Rig is an open source Rust framework designed to help developers build modular and scalable applications powered by large language models. It provides a unified set of abstractions that allow applications to interact with many AI model providers and vector databases through a single interface. Its architecture emphasizes modularity, enabling developers to integrate only the components and integrations they need for a specific application. Rig includes built-in support for agent workflows, allowing systems to perform multi-turn reasoning, tool calling, and retrieval-based tasks within structured pipelines. ... -
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LaReview
The code review workbench
LaReview is a developer-first, local-first code review workbench designed to transform complex pull requests or diffs into structured, high-signal review workflows powered by AI assistance. Instead of overwhelming developers with raw diffs or automated comment spam, the tool analyzes code changes and generates an intent-driven review plan that groups changes into logical flows such as authentication, API behavior, or data handling, and prioritizes them based on risk. It operates as a desktop... -
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CCC
Claude Opus 4.6 wrote a dependency-free C compiler in Rust
Claude’s C Compiler is a remarkable experiment in automated software generation: a full C compiler written from scratch in Rust entirely by an AI model (Claude Opus 4.6) with minimal human intervention, capable of targeting multiple architectures like x86-64, i686, ARM, and RISC-V. The project implements every part of a traditional compiler — the lexer, parser, intermediate representation, optimizer, code generator, assembler, linker, and debug info emitter — without relying on any external toolchain, producing standalone executables in the ELF format. ... -
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Monty
A minimal, secure Python interpreter written in Rust for use by AI
Monty is an experimental, security-focused Python interpreter implemented in Rust and intended for running AI-generated Python safely under strict constraints. The project’s core goal is to enable code execution in environments where untrusted or model-produced code must be tightly sandboxed to reduce risk. Rather than offering a full “general-purpose Python runtime with everything enabled,” Monty is designed to be minimal and controlled, making it easier to reason about what code can do and what it cannot. ... -
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Switchyard
Switchyard lets LLM applications route traffic across models
...Prometheus metrics track requests, errors, latency, tokens, and routing overhead. Developers can run it as a standalone server, launch coding agents through it, or embed its routing logic in Rust applications. The project is currently pre-alpha and explicitly marked experimental rather than production-ready. -
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MusicGPT
Generate music based on natural language prompts using LLMs
...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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OpenAI Harmony
Renderer for the harmony response format to be used with gpt-oss
Harmony is a response format developed by OpenAI for use with the gpt-oss model series. It defines a structured way for language models to produce outputs, including regular text, reasoning traces, tool calls, and structured data. By mimicking the OpenAI Responses API, Harmony provides developers with a familiar interface while enabling more advanced capabilities such as multiple output channels, instruction hierarchies, and tool namespaces. The format is essential for ensuring gpt-oss... -
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DeepReasoning
High-performance API combining reasoning and creative AI models
DeepReasoning is a high-performance large language model inference API designed to unify advanced reasoning and creative generation capabilities into a single system. It combines DeepSeek R1’s chain-of-thought reasoning with Claude’s strengths in code generation and conversational output, enabling more capable and balanced responses. DeepReasoning provides both an API and a chat interface, allowing developers and users to interact with the combined models in a streamlined way. It emphasizes... -
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HelixDB
Graph-vector database for building unified AI backends fast
HelixDB is an open source database designed to unify multiple data storage paradigms into a single platform tailored for AI-driven applications. It combines graph and vector data models, allowing developers to manage relationships and embeddings within the same system without relying on separate services. HelixDB is built from scratch in Rust and uses LMDB as its storage engine, enabling high performance and low-latency query execution. HelixDB also supports additional data formats such as... -
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agentgateway
Next Generation Agentic Proxy for AI Agents and MCP servers
Agentgateway is an open-source “data plane” built specifically for agentic AI connectivity, focusing on how agents talk to other agents and to tools across different frameworks and environments. It presents itself as a complete connectivity solution that adds drop-in security, observability, and governance to agent-to-agent and agent-to-tool communication without requiring you to rebuild your agent stack. The project supports interoperable protocols designed for this ecosystem, including Agent2Agent (A2A) and Model Context Protocol (MCP), which helps standardize how tools and agents interoperate. ... -
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LangChain Rust
LangChain for Rust, the easiest way to write LLM-based programs
...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 chatbots, autonomous agents, and knowledge-augmented AI systems that interact with external data sources. The library provides abstractions for model providers, prompt templates, conversation memory, and vector search integrations. It also enables the construction of multi-step pipelines where LLM outputs feed into subsequent actions or tool calls. -
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Ollama-rs
A simple and easy-to-use library for interacting with the Ollama API
...It follows the official Ollama API closely, ensuring compatibility while offering an idiomatic Rust experience with strong typing and asynchronous execution. The library supports a wide range of operations, including text generation, chat interactions, embeddings, and model management, making it suitable for both simple applications and more advanced AI workflows. It includes streaming capabilities for real-time output, allowing developers to process responses incrementally rather than waiting for full completions. The project also introduces support for tool calling and custom function integration, enabling more dynamic and agent-like behavior within applications. -
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agentOS
A portable open-source operating system for agents. ~6 ms coldstarts
...AgentOS is designed to run directly within an application process, enabling agents to interact with host functions and resources without network overhead or complex orchestration layers. It includes a permission-based security model that restricts access to system resources such as file systems and networks by default, ensuring safe execution of potentially untrusted code.
