Search Results for "model-builder"
Sort By:
Showing 55 open source projects for "model-builder"
View related business solutions-
$300 Free Credits to Build on Google CloudStart your next project with $300 in free Google Cloud credit. Spin up VMs, run containers, query petabytes in BigQuery, or build agents with Gemini Enterprise Agent Platform. Once your credits are used, keep building with 20+ always-free tier products including Compute Engine, Cloud Storage, GKE, and Cloud Run functions. No commitment required—just sign up and start building.
-
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
-
1
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 allows external components to extend the platform while maintaining isolation and security. ... -
2
Goose
AI coding agent that's more than suggestions - install, execute, edit+
Goose is an open-source, extensible AI agent that enhances the software development process by going beyond traditional code suggestions. It allows developers to install, execute, edit, and test code with any large language model (LLM), facilitating a more efficient and streamlined workflow. Designed to operate locally within a developer's environment, Goose integrates seamlessly with various tools and platforms, providing a customizable and powerful assistant for coding tasks. Its architecture supports extensibility, enabling users to tailor the agent to their specific needs and preferences. ... -
3
CodeGeeX4
CodeGeeX4-ALL-9B, a versatile model for all AI software development
CodeGeeX4 is the fourth-generation open source multilingual code large language model (LLM) developed by ZhipuAI. Designed as a powerful AI coding assistant, it supports over 100 programming languages and has been trained on a massive code and natural language corpus. Compared to its predecessors, CodeGeeX4 introduces improved reasoning, stronger alignment with developer needs, and better performance on real-world programming benchmarks. -
4
HASH
The best way to use and work with blocks
...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 maturity, and while some are polished, not all are ready for real-world production use. You can read more about our big-picture vision at hash.dev -
Atera - an All-in-one platform for IT managementYour IT essentials, integrated & elevated. Take your IT management from automated to autonomous, download Atera's agent to start your free trial!
-
5
Meetily
Privacy first, AI meeting assistant with 4x faster Parakeet/Whisper
...It’s built for organizations that want meeting intelligence without sending recordings or transcripts to third-party cloud services, which helps address compliance and data sovereignty requirements. The app supports live transcription with local model options (including Whisper- and Parakeet-based workflows) and presents the transcript as the meeting happens, making it useful both for note-taking and accessibility. After or during the session, it can produce structured, AI-generated summaries, and it’s designed to be flexible about where that summarization comes from, supporting local providers as well as external endpoints when allowed by policy. -
6
rtk
CLI proxy that reduces LLM 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 language model. This process helps maintain important information while removing redundant data such as boilerplate logs, long directory listings, or repetitive test outputs. By minimizing the amount of noise sent to the AI model, the tool improves reasoning quality and allows longer development sessions within the same context window. The system is implemented as a lightweight Rust binary that runs locally and integrates easily with common AI coding environments. -
7
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 preferences. llmfit also supports advanced configurations including multi-GPU setups, mixture-of-experts architectures, and dynamic quantization recommendations. ... -
8
DeepSeek TUI
Coding agent for DeepSeek models that runs in your terminal
...It provides a text-based chat experience directly within the command line, making it ideal for developers who prefer minimal interfaces. The tool supports streaming responses, allowing real-time interaction with the model. It includes features for managing prompts, sessions, and conversation history within the terminal environment. DeepSeek-TUI emphasizes speed and simplicity, avoiding heavy graphical dependencies. It is particularly useful for local or remote environments where graphical interfaces are impractical. Overall, it delivers an efficient CLI-first experience for AI interaction. -
9
ort
Fast ML inference & training for ONNX models in Rust
...One of its key strengths is its flexibility, as it supports multiple backends and allows developers to configure execution providers depending on available hardware. ort also includes advanced capabilities such as model compilation and optimization, reducing startup time and improving runtime performance in production systems. -
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
10
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 enables developers to define prompt logic in a dedicated language while integrating it into applications written in various programming languages such as Python, TypeScript, Ruby, and Go. ... -
11
gptcommit
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 model. Please ensure you have sufficient credits in your OpenAI account to use it. Commit messages are a key channel for developers to communicate their work with others, especially in code reviews. ... -
12
ZeroClaw
Fast, small, and fully autonomous AI assistant infrastructure
ZeroClaw is a Rust-native autonomous AI agent framework engineered for teams and developers who need highly efficient, secure, and modular AI automation infrastructure that can run reliably in both production and self-hosted environments. It is designed around a trait-based architecture so that model providers, communication channels, memory systems, and tooling integrations can be swapped or extended without rewriting core components, giving engineers flexibility and long-term maintainability. The framework features a compact single binary with fast cold and warm startup times and very low memory overhead, making it suitable even for resource-constrained hardware like small servers or edge devices. ... -
13
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. The system provides intelligent LLM routing APIs that support model agility, along with filter chains for safety, moderation, and memory hooks. It also exposes rich traces, metrics, and logs to support continuous improvement of agent behavior in production. ... -
14
shimmy
Python-free Rust inference server
...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. Advanced capabilities include CPU offloading for Mixture-of-Experts models and GPU acceleration, enabling large models to run on consumer hardware with limited VRAM. -
15
Moltis
A Rust-native claw you can trust
Moltis is an open-source personal AI assistant platform written in Rust that is designed to run as a fully self-hosted, local-first agent environment. It compiles the entire assistant stack, including the web interface, model routing, memory, and tools, into a single self-contained binary with no external runtime dependencies. The system supports multiple large language model providers alongside local models, enabling users to maintain privacy while still accessing cloud capabilities when needed. Moltis emphasizes security through sandboxed execution environments, where commands and browsing tasks run in isolated containers and require explicit approval. ... -
16
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. ... -
17
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. -
18
OpenHuman
Your Personal AI super intelligence. Private, simple and powerful
...The project connects to common productivity tools, gathers fresh information from integrations, and organizes user knowledge into a local memory system. It also includes practical agent tools such as web search, web fetching, file access, coding utilities, voice input, text-to-speech, and model routing. Its goal is to make an AI assistant feel continuously useful across meetings, messages, documents, tasks, and personal workflows. Since it is still in early beta, it is best suited for technical users and early adopters who want to experiment with a customizable personal AI environment. -
19
rust-bert
Rust native ready-to-use NLP pipelines and transformer-based models
...It allows developers to run state-of-the-art NLP models like BERT, GPT-2, and DistilBERT directly within Rust applications while maintaining high performance and memory efficiency. The library integrates with Rust machine learning infrastructure using crates such as tch-rs and ONNX Runtime for model execution. It also includes tokenization utilities, model architectures, and task-specific pipelines that simplify the development of NLP applications. Because Rust is known for its safety and performance, this project enables developers to deploy modern NLP models in production systems written in Rust. -
20
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... -
21
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. ... -
22
Every Code
Local AI coding agent CLI with multi-agent orchestration tools
...It is a community-driven fork of the Codex CLI, with a strong emphasis on improving real-world developer ergonomics and workflows. Every Code enhances the traditional coding assistant model by introducing multi-agent orchestration, allowing multiple AI agents to collaborate, compare solutions, and refine outputs in parallel. It supports integration with various AI providers, enabling users to route tasks across different models depending on their needs. Every Code also includes browser integration and automation capabilities, extending its usefulness beyond simple code generation into more complex development tasks. ... -
23
Tokenizers
Fast State-of-the-Art Tokenizers optimized for Research and Production
...Even with destructive normalization, it’s always possible to get the part of the original sentence that corresponds to any token. Does all the pre-processing: Truncation, Padding, add the special tokens your model needs. -
24
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... -
25
Spice.ai OSS
A self-hostable CDN for databases
...The Spice runtime, written in Rust, is built-with industry-leading technologies such as Apache DataFusion, Apache Arrow, Apache Arrow Flight, SQLite, and DuckDB. Spice makes it easy and fast to query data from one or more sources using SQL. You can co-locate a managed dataset with your application or machine learning model, and accelerate it with Arrow in-memory, SQLite/DuckDB, or with attached PostgreSQL for fast, high-concurrency, low-latency queries. Accelerated engines give you flexibility and control over query cost and performance.
