Search Results for "columba source code" - Page 14
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Showing 1521 open source projects for "columba source code"
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Sim
Build, deploy, and orchestrate AI agents
Sim is an open-source platform designed to build, deploy, and orchestrate AI agent workflows through a unified intelligence layer. It positions itself as infrastructure for managing an “AI workforce,” enabling developers and teams to coordinate multiple agents and automate complex processes from a central environment. The project focuses on low-code and no-code accessibility while still supporting advanced customization through TypeScript and modern web tooling. ... -
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LTX-2
Python inference and LoRA trainer package for the LTX-2 audio–video
...The framework targets both interactive graphical applications and media-rich experiences, making it a solid foundation for games, creative tools, or visualization systems that demand both performance and flexibility. While being low-level, it also provides sensible defaults and helper abstractions that reduce boilerplate and help teams maintain clear, maintainable code. -
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Generative AI Docs
Documentation for Google's Gen AI site - including Gemini API & Gemma
...It contains guides, API references, and examples for developers building applications using Google’s large language models, text-to-image models, embeddings, and multimodal capabilities. The repository includes markdown source files that power the Google AI developer documentation site, as well as sample code snippets in Python, JavaScript, and other languages that demonstrate how to use Google’s Generative AI SDKs and REST APIs effectively. -
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CLIP
CLIP, Predict the most relevant text snippet given an image
CLIP (Contrastive Language-Image Pretraining) is a neural model that links images and text in a shared embedding space, allowing zero-shot image classification, similarity search, and multimodal alignment. It was trained on large sets of (image, caption) pairs using a contrastive objective: images and their matching text are pulled together in embedding space, while mismatches are pushed apart. Once trained, you can give it any text labels and ask it to pick which label best matches a given... -
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DeepCamera
Open-Source AI Camera. Empower any camera/CCTV
...The source code is here It leverages Yolov7 as a person detector, FastReID for person feature extraction, Milvus the local vector database for self-supervised learning to identify unseen persons, Labelstudio to host images locally and for further usage such as label data and train your own classifier. It also integrates with Home-Assistant to empower smart homes with AI technology. -
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repo2txt
Web-based tool converts GitHub repository contents
repo2txt is an open-source developer tool that converts the contents of a code repository into a single structured text file that can be easily consumed by large language models. The tool is designed to address the challenge of analyzing entire codebases with AI assistants, where code is normally distributed across many files and directories. By collecting repository contents and formatting them into a single text document, repo2txt allows developers to feed complete projects into AI systems for analysis, documentation, or code explanation tasks. ... -
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emgucv
Cross platform .Net wrapper to the OpenCV image processing library
Emgu CV is a cross platform .Net wrapper to the OpenCV image processing library. Allowing OpenCV functions to be called from .NET compatible languages. The wrapper can be compiled by Visual Studio and Unity, it can run on Windows, Linux, Mac OS, iOS and Android. -
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Agent Development Kit (ADK) for Java
An open-source, code-first Java toolkit
Google’s Agent Development Kit for Java is an open-source toolkit that helps developers design, evaluate, and deploy advanced AI agents using the Java programming language. The framework follows a code-first approach that treats agent development as a structured software engineering task rather than a collection of prompt scripts. It provides abstractions and tools that allow developers to create agents capable of executing complex workflows, calling tools, and interacting with external services. ... -
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ChatGLM3
ChatGLM3 series: Open Bilingual Chat LLMs | Open Source Bilingual Chat
ChatGLM3 is ZhipuAI & Tsinghua KEG’s third-gen conversational model suite centered on the 6B-parameter ChatGLM3-6B. It keeps the series’ smooth dialog and low deployment cost while adding native tool use (function calling), a built-in code interpreter, and agent-style workflows. The family includes base and long-context variants (8K/32K/128K). The repo ships Python APIs, CLI and web demos (Gradio/Streamlit), an OpenAI-format API server, and a compact fine-tuning kit. Quantization (4/8-bit),... -
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Kun
AI agent workspace with Code and Write modes built into your apps
Kun is a desktop AI agent workspace focused on a requirement-first coding workflow. Instead of starting with a vague prompt and immediately changing files, it guides users through requirement clarification, design, planning, todos, implementation, and review. The application includes a Code workspace for real repositories and a Write workspace for Markdown writing, editing, previewing, and exporting. It uses DeepSeek, Xiaomi MiMo, and MiniMax as its default model combination while still... -
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abtop
Like htop, but for AI coding agents. Monitor Claude Code & Codex CLI
abtop is a terminal monitoring tool for AI coding agents, inspired by system monitors like htop and btop. It gives users a real-time view of active Claude Code, Codex CLI, and OpenCode sessions from local process and file state. The dashboard helps developers track token usage, context window percentage, rate limits, child processes, open ports, and multiple active profiles. It is read-only, so it does not require API keys or authentication and does not control the agents it observes. abtop... -
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How to Train Your GPT
Build a modern LLM from scratch. Every line commented
How to Train Your GPT is an interactive textbook that teaches users how to build, train, and run a modern language model from scratch. It is written for learners with minimal machine-learning background, using simple explanations, commented code, and practical examples. The project covers the same broad family of architecture behind systems such as GPT-style models, LLaMA-style models, Claude-style systems, and Mistral-style models. It includes chapters and topic explainers on tokenizers,... -
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Kodezi Chronos
Kodezi Chronos is a debugging-first language model
Kodezi Chronos is a research project focused on developing a specialized language model designed specifically for debugging software and understanding large code repositories. Unlike general-purpose language models that focus primarily on code generation, Chronos is built to diagnose and repair bugs by analyzing complex relationships across files within a codebase. The project introduces architectural techniques such as Adaptive Graph-Guided Retrieval, which allows the system to navigate... -
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SERA CLI
A tool to use the Ai2 Open Coding Agents Soft-Verified Agents
SERA CLI is a command-line tool created by AllenAI to enable developers to interact with the SERA (Soft-Verified Efficient Repository Agents) model family using Claude Code as the execution front end. It provides a convenient interface for deploying, testing, and using SERA models without needing to write scaffold code from scratch, acting as both a proxy and utility wrapper to simplify workflows that involve large agent models. Through sera-cli, users can connect to local or cloud-hosted... -
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NextJS Ollama LLM UI
Fully-featured web interface for Ollama LLMs
NextJS Ollama LLM UI is a web-based frontend interface built with Next.js to make interacting with Ollama-hosted large language models easy and fast. Its goal is to remove the complexity of setting up and managing UI components for local or offline LLM usage by providing a straightforward chat experience with support for responsive layouts, light and dark themes, and local chat history storage in the browser. The interface stores conversations in local storage, so no separate backend... -
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UltraRAG
Less Code, Lower Barrier, Faster Deployment
UltraRAG 2.0 is a low-code, MCP-enabled RAG framework that aims to lower the barrier to building complex retrieval pipelines for research and production. It provides end-to-end recipes—from encoding and indexing corpora to deploying retrievers and LLMs—so users can reproduce baselines and iterate rapidly. The toolkit comes with built-in support for popular RAG datasets, large corpora, and canonical baselines, plus documentation that walks from “quick start” to debugging and case analysis. It... -
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LLM Foundry
LLM training code for MosaicML foundation models
Introducing MPT-7B, the first entry in our MosaicML Foundation Series. MPT-7B is a transformer trained from scratch on 1T tokens of text and code. It is open source, available for commercial use, and matches the quality of LLaMA-7B. MPT-7B was trained on the MosaicML platform in 9.5 days with zero human intervention at a cost of ~$200k. Large language models (LLMs) are changing the world, but for those outside well-resourced industry labs, it can be extremely difficult to train and deploy these models. ... -
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effective-html
Agent skill for elegant and simple html plans, architecture diagrams
effective-html is an agent skill package for generating polished, self-contained HTML visual artifacts. It focuses on pragmatic outputs such as plans, architecture diagrams, system diagrams, and general-purpose HTML pages. The repository includes separate skills for standard HTML artifacts, full-screen HTML diagrams, and HTML plan pages. It is designed to work with agent tooling such as Skills, Claude Code plugins, and Codex plugins. The skill emphasizes strong visual structure, high-quality... -
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improve
Use your most capable model to audit your codebase
improve is an agent skill that audits a codebase and writes implementation plans for other agents or humans to execute. Its core idea is to use a stronger model for understanding, judgment, and planning, then hand the actual implementation to cheaper or separate execution agents. The skill does not modify code by default, because its main output is a self-contained plan. It can run full, quick, deep, security-focused, branch-scoped, and feature-suggestion audits. It maps repository... -
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ZeroGPU Router
Cut inference costs without dumbing down your agent
ZeroGPU Router is a task router for AI agents that sends simple, focused workloads to smaller specialized models. It is designed to reduce inference costs without replacing the main reasoning model used by the agent. The router exposes tools for tasks such as summarization, classification, PII redaction, entity extraction, JSON extraction, follow-up generation, and short chat. It works through MCP for OpenClaw and through a CLI plus plugin workflow for Claude Code. Each routed call can... -
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Z-Image
Image generation model with single-stream diffusion transformer
Z-Image is an efficient, open-source image generation foundation model built to make high-quality image synthesis more accessible. With just 6 billion parameters — far fewer than many large-scale models — it uses a novel “single-stream diffusion Transformer” architecture to deliver photorealistic image generation, demonstrating that excellence does not always require extremely large model sizes. The project includes several variants: Z-Image-Turbo, a distilled version optimized for speed and... -
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Generative AI for Beginners (Version 3)
21 Lessons, Get Started Building with Generative AI
Generative AI for Beginners is a 21-lesson course by Microsoft Cloud Advocates that teaches the fundamentals of building generative AI applications in a practical, project-oriented way. Lessons are split into “Learn” modules for core concepts and “Build” modules with hands-on code in Python and TypeScript, so you can jump in at any point that matches your goals. The course covers everything from model selection, prompt engineering, and chat/text/image app patterns to secure development practices and UX for AI. It also walks through modern application techniques such as function calling, RAG with vector databases, working with open source models, agents, fine-tuning, and using SLMs. ... -
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nanobot
🐈 nanobot: The Ultra-Lightweight Clawdbot / OpenClaw
nanobot is an ultra-lightweight personal AI assistant designed to deliver powerful agent capabilities without unnecessary complexity. Built in just ~4,000 lines of clean, readable code, it offers a minimalist alternative to heavyweight agent frameworks while retaining core intelligence and extensibility. nanobot is optimized for speed and efficiency, enabling fast startup times and low resource usage across environments. Its research-ready architecture makes it easy for developers to... -
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Browser MCP
Browser MCP is a Model Context Provider (MCP) server
Browser MCP is an MCP server plus browser integration that lets AI apps automate the user’s real browser instead of launching a separate automation session. By adapting a Playwright-style approach to control the running browser profile, it reuses logged-in sessions and cookies, which reduces re-authentication friction and helps avoid some bot-detection heuristics. The server exposes structured tools for navigation, element interaction, and artifact capture (DOM, screenshots, logs), all... -
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CARLA Simulator
Open-source simulator for autonomous driving research.
CARLA has been developed from the ground up to support development, training, and validation of autonomous driving systems. In addition to open-source code and protocols, CARLA provides open digital assets (urban layouts, buildings, vehicles) that were created for this purpose and can be used freely. The simulation platform supports flexible specification of sensor suites, environmental conditions, full control of all static and dynamic actors, maps generation and much more. Multiple clients in the same or in different nodes can control different actors. ...
