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Showing 221 open source projects for "main"
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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.
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$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
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DeepSeek GUI
AI agent workspace for DeepSeek models, with Code and Claw modes
...It targets users who want a dedicated desktop-like workspace for DeepSeek-based coding, reasoning, and productivity. The project is released under the MIT license and has builds for major desktop platforms, including macOS and Windows. Its main value is making DeepSeek agent workflows easier to access through a focused visual interface. -
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NeuralNote
Audio Plugin for Audio to MIDI transcription using deep learning
...The software functions as an audio plugin that can be used inside digital audio workstations as well as a standalone application for music production and analysis. Its main purpose is to perform audio-to-MIDI transcription, allowing musicians to record a performance and automatically transform it into editable MIDI notes. NeuralNote supports polyphonic transcription, meaning it can detect multiple notes played simultaneously, making it useful for instruments such as piano or guitar. The system relies on neural network models to analyze audio signals and infer pitch, timing, and other musical attributes that can be represented as MIDI data. ... -
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CodeGraph
Pre-indexed code knowledge graph for Claude Code, Codex, Cursor
...It is designed for tools such as Claude Code, Codex, Cursor, and OpenCode, with MCP support for agent access. CodeGraph stores project data locally, which helps reduce token usage and repeated file exploration. Its main purpose is to make agent-assisted coding faster, cheaper, and more context-aware. -
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ZeroGPU Router
Cut inference costs without dumbing down your agent
...Its main value is letting agents reserve expensive frontier models for complex reasoning while offloading routine language tasks to cheaper specialized routes. -
Stop vibe-debugging.AppSignal's MCP server hands Claude, Cursor, or Zed your real errors, traces, and the deploy that shipped them. AI writes the fix; you review the diff.
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NSFWDetector
A NSFW detector with CoreML
NSFWDetector is a small (17 kB) CoreML Model to scan images for nudity. It was trained using CreateML to distinguish between porn/nudity and appropriate pictures. With the main focus on distinguishing between Instagram model-like pictures and porn. -
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Codex Mobile
Run Codex Mobile Anywhere: Linux, Windows, or Termux on Android
...It can also create a Cloudflare tunnel by default, making remote access easier when the local setup allows it. Codex Mobile is useful for developers who want to control coding-agent sessions from a phone, tablet, remote browser, or nonstandard environment. Its main value is making Codex app workflows more portable, accessible, and usable beyond a traditional desktop terminal. -
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Read Frog
Open Source Immersive Translate
...Instead of forcing learners to switch between translation tools and the original text, the extension displays translations alongside the source language, making comprehension immediate and continuous. The system automatically extracts the main content of an article using intelligent parsing techniques, allowing users to focus on the most relevant text without distractions. AI models are used to generate summaries, introductions, and explanations for words, phrases, and sentences based on the learner’s language level, making the experience personalized and adaptive. -
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OpenMed
Open source healthcare AI
...The project includes a curated registry of more than a dozen medical NER models focused on areas such as diseases, drugs, anatomy, genes, and protected health information, and it is built to support both research and deployment scenarios. OpenMed can be used in three main ways: as a simple Python API for scripts and notebooks, as a Docker-friendly FastAPI service for backend integration, and as a batch-processing system for multi-document workflows. -
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AirLLM
AirLLM 70B inference with single 4GB GPU
AirLLM is an open source Python library that enables extremely large language models to run on consumer hardware with very limited GPU memory. The project addresses one of the main barriers to local LLM experimentation by introducing a memory-efficient inference technique that loads model layers sequentially rather than storing the entire model in GPU memory. This layer-wise inference approach allows models with tens of billions of parameters to run on devices with only a few gigabytes of VRAM. AirLLM preprocesses model weights so that each transformer layer can be loaded independently during computation, reducing the memory footprint while still performing full inference. ... -
Stop Cyber Threats with VM-Series Next-Gen Firewall on AzureGain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
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OpenMythos
A theoretical reconstruction of the Claude Mythos architecture
...The project explores the idea that instead of stacking hundreds of unique transformer layers, a smaller set of layers can be reused iteratively during inference to achieve deeper reasoning without increasing parameter count. It divides computation into three main stages, including a pre-processing phase, a looped recurrent reasoning block, and a final output refinement stage, creating a structured pipeline for inference. The architecture incorporates advanced techniques such as mixture-of-experts routing, adaptive computation time, and multiple attention mechanisms to dynamically allocate compute where needed. ... -
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TensorRT Backend For ONNX
ONNX-TensorRT: TensorRT backend for ONNX
Parses ONNX models for execution with TensorRT. Development on the main branch is for the latest version of TensorRT 8.4.1.5 with full dimensions and dynamic shape support. For previous versions of TensorRT, refer to their respective branches. Building INetwork objects in full dimensions mode with dynamic shape support requires calling the C++ and Python API. Current supported ONNX operators are found in the operator support matrix. -
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No Cost AI
80+ free AI services for chat, image, video, voice & APIs
...It is useful for students, developers, creators, and experimenters who want to test AI tools with minimal cost. The repository also warns that free AI services can change, disappear, rate-limit users, or become unreliable over time. Its main value is discovery, not guaranteed infrastructure, so it works best as a resource map rather than a production dependency. -
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Tesseract.js
A pure Javascript Multilingual OCR
...Tesseract.js can run either in a browser and on a server with NodeJS. Tesseract.js is a javascript library that gets words in almost any spoken language out of images. The main Tesseract.js functions (ex. recognize, detect) take an image parameter, which should be something that is like an image. What's considered "image-like" differs depending on whether it is being run from the browser or through NodeJS. -
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Agent Reach
Give your AI agent eyes to see the entire internet
...It can be useful for research agents, automation workflows, competitive monitoring, content analysis, and social listening. Agent-Reach also supports modern agent environments by exposing capabilities that can be connected into larger AI workflows. Its main value is making scattered web platforms easier for agents to query, inspect, and summarize from the command line. -
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MagicTime
Time-lapse Video Generation Models as Metamorphic Simulators
This repository is the official implementation of MagicTime, a metamorphic video generation pipeline based on the given prompts. The main idea is to enhance the capacity of video generation models to accurately depict the real world through our proposed methods and dataset. Compared to general videos, metamorphic videos contain physical knowledge, long persistence, and strong variation, making them difficult to generate. -
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Gajae-Code
Gajae Code MVP
...It includes tmux-backed execution options for coordinating parallel workers when a task is large enough to benefit from them. Gajae-Code is useful for developers who want coding agents to behave less like single-prompt assistants and more like disciplined project collaborators. Its main value is giving AI coding work a clearer loop for interviews, plans, goals, execution checks, and evidence. -
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Easy AI
Easy-to-understand AI learning resources for beginners
...It includes visual and interactive explanations for core topics such as tokens, prompts, LLMs, Transformers, and evaluation benchmarks. It also organizes AI-related works, tutorials, and daily updates so users can explore both fundamentals and current developments. Its main value is making AI knowledge easier to browse, understand, and apply. -
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LazyCodex
The one and only agent harness for complex codebases
...LazyCodex also emphasizes verified completion, which means the workflow is built around checking whether tasks are actually finished rather than only generating code. Its main value is turning Codex into a more disciplined coding agent environment for larger and more demanding repositories. -
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aaif-goose
An open source, extensible AI agent that goes beyond code suggestions
...The project provides a desktop app, command-line interface, and API, which gives users multiple ways to work with the agent. goose is designed to connect with tools and local context so it can help complete practical tasks instead of only answering chat prompts. It is useful for developers, analysts, writers, and technical users who want an extensible assistant that can operate inside their environment. Its main value is bringing a native, flexible, and open agent workflow to everyday computer-based work. -
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SuperPrompt
Experimental prompt framework exploring reasoning structures in AI
...It explores structured prompt engineering techniques that combine symbolic expressions, logical constructs, and conceptual frameworks to guide large language models toward deeper reasoning processes. Its main concept revolves around a highly structured prompt format that includes tagged sections for reasoning, analysis, conceptual expansion, and recursive thinking patterns. These sections act as a kind of meta-instruction system intended to influence how an AI model approaches problem solving and conceptual exploration. SuperPrompt also incorporates ideas from mathematics, recursion, abstract algebra, and theoretical reasoning to encourage models to perform multi-step conceptual synthesis rather than simple direct responses. -
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FEniCS.jl
A scientific machine learning (SciML) wrapper for the FEniCS
...A low-level development API and provides some functionality to make directly dealing with the library a little bit easier, but still requires knowledge of FEniCS itself. Interfaces have been provided for the main functions and their attributes, and instructions to add further ones can be found here. A high-level API for usage with DifferentialEquations. An example can be seen in solving the heat equation with high-order adaptive time-stepping. Various gists/jupyter notebooks have been created to provide a brief overview of the overall functionality and of any differences between the pythonic FEniCS and the Julian wrapper. ... -
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BERTopic
Leveraging BERT and c-TF-IDF to create easily interpretable topics
...However, that takes quite some time and lacks a global representation. Instead, we can visualize the topics that were generated in a way very similar to LDAvis. By default, the main steps for topic modeling with BERTopic are sentence-transformers, UMAP, HDBSCAN, and c-TF-IDF run in sequence. -
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Future AGI
Open-source platform for evaluating, observing, and improving LLM
...It supports both cloud and self-hosted deployment models, making it useful for teams with different privacy, infrastructure, and compliance needs. Future AGI is especially relevant for agent-heavy products where reliability, regression testing, and safety checks matter before and after release. Its main value is turning AI agent development into a measurable engineering process instead of an informal cycle of prompting, guessing, and manual review. -
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AI Engineer Coach
Better agentic engineering
...It focuses on agentic engineering habits such as prompt quality, context management, review discipline, tool use, and session hygiene. The project is read-only and emphasizes that data stays on the user’s machine. Its main value is helping developers measure and improve their AI-assisted coding process instead of treating agent use as an untracked black box. -
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Google Gen AI SDK
Google Gen AI Python SDK provides an interface for developers
...It is intended to replace older Gemini Python SDK patterns with a more unified and actively maintained API surface. The project is useful for application developers, data scientists, AI engineers, and backend teams building Gemini-powered features. Its main value is providing a supported, production-ready Python interface for Google’s current generative AI ecosystem.
