Open Source Linux Artificial Intelligence Software - Page 29
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Artificial Intelligence Software for Linux
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Tabby
Self-hosted AI coding assistant
Tabby is an open-source, self-hosted AI coding assistant that provides code completion and suggestions within your preferred development environment. It enhances developer productivity by leveraging machine learning models to predict and generate code snippets. -
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Telegram API Library
Complete async capable Telegram bot API implementation for PHP7
This is a PHP7 bot API implementation for Telegram implementing the vast majority of Bot API up until v4.7. The only thing it does not implement is Telegram Passport which was introduced in Bot API v4.0. It is unlikely to be introduced as it may introduce security vulnerabilities. However, if you think you have a strong case for the need, feel free to let me know. Enables you to anything supported by the Telegram Bot API: messages, stickers, location, inline bots and any other supported method via PHP to a Telegram user (either direct conversation, channel, group or supergroup). Respects and implements the default types and methods made by Telegram itself. Have any doubts about any method? Just check the original documentation, this implementation will not differ too much. Doesn't need any mandatory dependencies, except for ReactPHP, which you can inject if you already use it elsewhere. -
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VADER
Lexicon and rule-based sentiment analysis tool
VADER (Valence Aware Dictionary and sEntiment Reasoner) is a lexicon and rule-based sentiment analysis tool designed for analyzing the sentiment of text, particularly in social media and short text formats. It is optimized for quick and accurate analysis of positive, negative, and neutral sentiments. -
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Vibe-Trading
Vibe-Trading: Your Personal Trading Agent
Vibe-Trading is an AI-powered multi-agent financial workspace that converts natural language inputs into executable trading strategies and market analysis. It allows users to describe investment ideas in plain language, which are then translated into code, backtested, and evaluated across global markets. The platform integrates multiple data sources, including equities, crypto, and derivatives, with automatic fallback mechanisms. It features a swarm-based architecture with prebuilt expert agent teams for research, trading, and risk management. Advanced backtesting engines provide statistical validation, optimization, and performance metrics. The system also includes persistent memory, enabling it to learn from past interactions and refine strategies over time. Overall, it delivers an end-to-end AI-driven trading environment for both research and execution. -
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VideoSrt
Windows-GUI
This is an open source Windows-GUI software tool that can recognize video speech and automatically generate subtitle SRT files. VideoSrtIt is written in Golanglanguage and developed based on lxn/walk Windows-GUI toolkit. Open source software tool that can recognize video speech and automatically generate subtitle SRT files. It is suitable for business scenarios that quickly and batch generate Chinese/English subtitles and text files for media (video/audio). Recognize video/audio speech to generate subtitle files (support Chinese-English translation, bilingual subtitles) Extract speech text from video/audio. Batch translation, filter processing/encoding SRT subtitle files. Using the Alibaba Cloud speech recognition interface, the accuracy is high, and the standard Mandarin/English recognition rate is over 95%. Video recognition does not need to upload the original video, which is convenient, fast and time-saving. -
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VoiceFixer
General Speech Restoration
VoiceFixer is a machine-learning framework for “speech restoration”: given a degraded or distorted audio recording — with noise, clipping, low sampling rate, reverberation, or other artifacts — it attempts to recover high-fidelity, clean speech. The architecture works in two stages: first an analysis stage that tries to extract “clean” intermediate features from the noisy audio (e.g. removing noise, denoising, dereverberation, upsampling), and then a neural vocoder-based synthesis stage that reconstructs a high-quality waveform from those features. Unlike many single-purpose noise reduction tools, VoiceFixer targets a “general speech restoration” problem (GSR), capable of handling multiple types of distortions at once, which makes it suitable for old recordings, phone-call audio, amateur voice recordings, or archival media. Evaluations show that VoiceFixer significantly improves both objective and subjective audio quality compared to baseline speech-enhancement methods. -
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Weaviate
Weaviate is a cloud-native, modular, real-time vector search engine
Weaviate in a nutshell: Weaviate is a vector search engine and vector database. Weaviate uses machine learning to vectorize and store data, and to find answers to natural language queries. With Weaviate you can also bring your custom ML models to production scale. Weaviate in detail: Weaviate is a low-latency vector search engine with out-of-the-box support for different media types (text, images, etc.). It offers Semantic Search, Question-Answer-Extraction, Classification, Customizable Models (PyTorch/TensorFlow/Keras), and more. Built from scratch in Go, Weaviate stores both objects and vectors, allowing for combining vector search with structured filtering with the fault-tolerance of a cloud-native database, all accessible through GraphQL, REST, and various language clients. -
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Whisper-WebUI
A Web UI for easy subtitle using whisper model
Whisper WebUI is an open-source browser-based interface that simplifies the use of Whisper speech recognition models by providing an intuitive graphical environment for transcription, translation, and subtitle generation. Built with Gradio, it allows users to upload audio or video files, process them locally, and generate accurate text outputs without relying on command-line tools. The platform integrates optimized implementations such as faster-whisper, significantly improving transcription speed and reducing memory usage compared to standard models. It supports multiple input sources including local files, YouTube content, and microphone input, making it versatile for different workflows. Whisper WebUI also includes advanced preprocessing and postprocessing features such as voice activity detection, background music separation, and speaker diarization, enabling more accurate and structured outputs. -
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agents.md
A simple, open format for guiding coding agents
openai/agents.md is a repository whose primary file is AGENTS.md, a proposed open, lightweight convention (i.e. Markdown file) for guiding coding agents in software repositories. The idea is that AGENTS.md acts as a “README for agents”: a predictable, structured place where humans can put instructions, conventions, build/test commands, environment setup, and other guidance that generative agents (e.g. code-writing, code-assisting tools) should consult when operating in the repo. Instead of putting everything in README or doc files (which are more human-oriented and might mix high-level narrative), AGENTS.md is intended to surface agent-relevant details that help them “do the right thing” (tests, style, project structure, tooling). -
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clone-voice
A sound cloning tool with a web interface, using your voice
Clone-voice is a local voice-cloning tool that lets you synthesize speech in any target voice or convert one recording into another voice using the same timbre. It is built around Coqui’s XTTS-v2 model, so it inherits multilingual support and modern neural TTS quality while wrapping it in a user-friendly desktop workflow. The app is designed to be very easy to use: you download a precompiled package, double-click app.exe, and it launches a browser-based web interface where you control cloning and synthesis. It does not require an NVIDIA GPU to run basic tasks, although GPU acceleration can be used when available, making it accessible on modest machines. The tool supports around sixteen languages, including Chinese, English, Japanese, Korean, French, German, Italian, and others, and can capture reference voices directly from a microphone or from uploaded audio. -
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codebase-memory-mcp
High-performance code intelligence MCP server
codebase-memory-mcp is a high-performance code intelligence MCP server built for AI coding agents. It indexes codebases into a persistent knowledge graph so agents can understand architecture, symbols, call chains, routes, and cross-service relationships without reading every file repeatedly. The project uses tree-sitter AST analysis across 158 languages and adds Hybrid LSP type resolution for major languages like Python, TypeScript, JavaScript, Go, C#, Java, Rust, C, and C++. It is built for speed, with average repositories indexed in milliseconds and structural queries answered in under one millisecond. It ships as a single static binary for macOS, Linux, and Windows with no shared library dependencies. It also includes semantic search, BM25 search, graph visualization, auto-indexing, and cross-repository intelligence. -
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ex-skill
Distill your ex into an AI Skill
ex-skill is an experimental AI tooling project that allows users to transform personal memories, particularly past relationships, into interactive AI “skills” that replicate the communication style, personality, and behavioral patterns of a specific individual. The system works by ingesting various forms of personal data such as chat logs, social media content, photos, and user-provided descriptions, then structuring this information into a layered representation that combines memory and persona modeling. It is designed to run within Claude Code environments, where users can generate, manage, and interact with these personalized AI entities through command-based interfaces. The project emphasizes emotional realism by reconstructing conversational tone, habits, and contextual memories, enabling interactions that feel consistent with the original person. -
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gemini-web2api
Convert Google Gemini web into OpenAI-compatible API
gemini-web2api is a Python bridge that exposes Google Gemini web access through OpenAI-compatible API endpoints. It is designed to let OpenAI-style clients connect to Gemini-like models through routes such as chat completions, models, responses, and native Gemini-compatible endpoints. The project can run as a simple local server and uses a mostly single-file design with an optional dependency for streaming. It supports model aliases for Flash, Thinking, Pro-style routing, Auto, and Lite variants. The tool also includes optional API keys, function calling, SSE streaming, web search access, Docker deployment, and client examples for OpenAI SDK-style usage. It is useful for developers who want local experimentation with OpenAI-compatible tooling while routing requests through Gemini web behavior. -
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gpt-engineer
Full stack AI software engineer
gpt-engineer is an open-source platform designed to help developers automate the software development process using natural language. The platform allows users to specify software requirements in plain language, and the AI generates and executes the corresponding code. It can also handle improvements and iterative development, giving users more control over the software they’re building. Built with a terminal-based interface, gpt-engineer is customizable, enabling developers to experiment with AI-assisted programming and refine their development process. It is especially useful for automating the coding and iterative feedback loop in software development. -
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pytorch-cpp
C++ Implementation of PyTorch Tutorials for Everyone
C++ Implementation of PyTorch Tutorials for Everyone. This repository provides tutorial code in C++ for deep learning researchers to learn PyTorch (i.e. Section 1 to 3) Interactive Tutorials are currently running on LibTorch Nightly Version. Libtorch only supports 64bit Windows and an x64 generator needs to be specified. Create all required script module files for pre-learned models/weights during the build. Requires installed python3 with PyTorch and torch-vision. You can choose to only build tutorials in one of the categories basics, intermediate, advanced or popular. You can build and run the tutorials (on CPU) in a Docker container using the provided Dockerfile and docker-compose.yml files. -
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segment-geospatial
A Python package for segmenting geospatial data with the SAM
The segment-geospatial package draws its inspiration from segment-anything-eo repository authored by Aliaksandr Hancharenka. To facilitate the use of the Segment Anything Model (SAM) for geospatial data, I have developed the segment-anything-py and segment-geospatial Python packages, which are now available on PyPI and conda-forge. My primary objective is to simplify the process of leveraging SAM for geospatial data analysis by enabling users to achieve this with minimal coding effort. I have adapted the source code of segment-geospatial from the segment-anything-eo repository, and credit for its original version goes to Aliaksandr Hancharenka. -
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smolagents
Agents write python code to call tools and orchestrate other agents
This library is the simplest framework out there to build powerful agents. We provide our definition in this page, where you’ll also find tips for when to use them or not (spoilers: you’ll often be better off without agents). smolagents is a lightweight framework for building AI agents using large language models (LLMs). It simplifies the development of AI-driven applications by providing tools to create, train, and deploy language model-based agents. -
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xiaohongshu-mcp
MCP for xiaohongshu.com
xiaohongshu-mcp is a Model Context Protocol (MCP) server that equips AI assistants with first-class tools for working on Xiaohongshu (Little Red Book), focusing on day-to-day creator and operator workflows rather than generic browsing. The project centers on authenticated actions and data access that matter to content operations, such as checking login state, publishing or scheduling content, fetching recommendations and search results, reading post details, and acting on comments. It’s packaged so MCP-capable clients (e.g., Claude Desktop, Cursor) can discover its tools via schemas instead of prompt guesswork, which improves reliability and reduces brittle automation. The repo highlights a growing community and provides links to a hosted landing page, signaling that the server is intended for practical use beyond a proof of concept. By exposing typed resources and procedures, it enables repeatable, auditable automation in social workflows where UI changes are frequent. -
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Presage
the intelligent predictive text entry platform
Presage (formerly Soothsayer) is an intelligent predictive text entry system. Presage generates predictions by modelling natural language as a combination of redundant information sources. Presage computes probabilities for words which are most likely to be entered next by merging predictions generated by the different predictive algorithms. Presage's modular and extensible architecture allows its language model to be extended and customized to utilize statistical, syntactic, and semantic predictive algorithms. Presage's predictive capabilities are implemented by predictive plugins. Predictive plugins use services provided by the platform to implement multiple prediction techniques. -
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The Mars Simulation Project is an open source Java project to create a simulation of future human settlement on the planet Mars. See https://github.com/mars-sim/mars-sim for the LATEST issues/wiki/code change
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Fast Artificial Neural Network Library is a free open source neural network library, which implements multilayer artificial neural networks in C with support for both fully connected and sparsely connected networks. Cross-platform execution in both fixed and floating point are supported. It includes a framework for easy handling of training data sets. It is easy to use, versatile, well documented, and fast. Bindings to more than 15 programming languages are available. An easy to read introduction article and a reference manual accompanies the library with examples and recommendations on how to use the library. Several graphical user interfaces are also available for the library.
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008
Open-source event-driven AI powered Softphone
008 is an open-source event-driven AI powered WebRTC Softphone compatible with macOS, Windows, and Linux. It is also accessible on the web (though official support for browser-related issues is not provided). The name '008' or 'agent 008' reflects our ambition: beyond crafting the premier Open Source Softphone, we aim to introduce a programmable, event-driven AI agent. This agent utilizes embedded artificial intelligence models operating directly on the softphone, ensuring efficiency and reduced operational costs. This project is a WebRTC softphone, and communication is achieved via SIP over a socket. Leading PBX systems like Asterisk or Freeswitch support socket connections. If your provider does not offer this feature, consider using a SIP proxy such as Kamailio, Opensip or Routr. The softphone is internally configured using a JSON definition. The configuration file can be loaded from either a server or a local file. 008 reads the file only once. -
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AIChat
All-in-one LLM CLI tool featuring Shell Assistant
AIChat is a lightweight terminal-based chatbot powered by GPT models, enabling AI-driven conversations directly from the command line. -
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Agency Agents
A complete AI agency at your fingertips
Agency Agents is a framework focused on orchestrating multiple AI agents that collaborate to complete complex tasks through structured coordination. It is designed around the idea of “agency,” where each agent has a defined role, responsibility, and interaction pattern within a larger system. The framework enables developers to define workflows where agents communicate, delegate tasks, and share context, creating a distributed problem-solving environment. It supports modular design, allowing agents to be composed into reusable systems that can be adapted across different use cases. The project emphasizes clarity in agent responsibilities, which helps reduce ambiguity and improve reliability in multi-agent workflows. It also provides mechanisms for managing interactions, ensuring that communication between agents remains structured and predictable. Overall, agency-agents serves as a foundation for building collaborative AI systems that operate through coordinated agent behavior. -
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Agent Orchestrator
Agentic orchestrator for parallel coding agents
Agent Orchestrator from Composio is an open-source orchestration layer designed to manage fleets of parallel AI coding agents working on a shared codebase. It enables each agent to operate independently in isolated git worktrees, handling tasks like fixing CI failures, addressing code review comments, and creating pull requests. The platform automates the coordination of multiple agents, reducing the need for manual oversight in complex development workflows. It supports a wide range of agents, runtimes, and tools, making it flexible and framework-agnostic. Through a centralized dashboard, developers can monitor progress, review outputs, and intervene only when human judgment is required. Agent Orchestrator transforms AI-assisted development into a scalable, autonomous system for continuous code improvement.
