1146 projects for "python::module" with 2 filters applied:

  • Queue Management System for Busy Service Providers | WaitWell Icon
    Queue Management System for Busy Service Providers | WaitWell

    The queue management system that perfectly adapts to your workflows

    The queue management system that perfectly adapts to your workflows. Improve operational efficiency in weeks with the most configurable enterprise queue system.
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  • 1
    LTX-2

    LTX-2

    Python inference and LoRA trainer package for the LTX-2 audio–video

    LTX-2 is a powerful, open-source toolkit developed by Lightricks that provides a modular, high-performance base for building real-time graphics and visual effects applications. It is architected to give developers low-level control over rendering pipelines, GPU resource management, shader orchestration, and cross-platform abstractions so they can craft visually compelling experiences without starting from scratch. Beyond basic rendering scaffolding, LTX-2 includes optimized math libraries,...
    Downloads: 83 This Week
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  • 2
    llama.cpp

    llama.cpp

    Port of Facebook's LLaMA model in C/C++

    The llama.cpp project enables the inference of Meta's LLaMA model (and other models) in pure C/C++ without requiring a Python runtime. It is designed for efficient and fast model execution, offering easy integration for applications needing LLM-based capabilities. The repository focuses on providing a highly optimized and portable implementation for running large language models directly within C/C++ environments.
    Downloads: 152 This Week
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  • 3
    Practical Machine Learning with Python

    Practical Machine Learning with Python

    Master the essential skills needed to recognize and solve problems

    ...The repository emphasizes end-to-end workflows rather than isolated code snippets, showing how to handle common challenges like class imbalance, overfitting, hyperparameter optimization, and interpretability. By leveraging popular Python libraries such as pandas, scikit-learn, XGBoost, and visualization tools, it illustrates how to build reproducible and robust solutions that scale beyond small demos.
    Downloads: 0 This Week
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  • 4
    Whisper

    Whisper

    Robust Speech Recognition via Large-Scale Weak Supervision

    OpenAI Whisper is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multitasking model that can perform multilingual speech recognition, speech translation, and language identification. A Transformer sequence-to-sequence model is trained on various speech processing tasks, including multilingual speech recognition, speech translation, spoken language identification, and voice activity detection. These tasks are jointly represented...
    Downloads: 73 This Week
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    Manage and optimise Google, Facebook and Microsoft Ads faster and gain a competitive advantage with our digital advertising platform.

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  • 5
    Monty

    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. ...
    Downloads: 7 This Week
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  • 6
    Spring AI Alibaba Examples

    Spring AI Alibaba Examples

    Spring AI Alibaba examples for building and testing AI apps

    ...It is designed to help developers understand core concepts, explore practical implementations, and follow best practices when building AI-powered systems using the Spring ecosystem. Each module focuses on a specific use case such as chat, image processing, audio handling, graph workflows, and retrieval-augmented generation. The examples highlight how to integrate AI models, manage prompts, handle memory, and build multi-model or multi-agent workflows. Developers can explore individual project folders for detailed instructions and implementation guidance. ...
    Downloads: 1 This Week
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  • 7
    Claude Skills

    Claude Skills

    Public repository for Agent Skills

    Claude Skills is a public repository that showcases and serves as a collection of skills — modular, reusable packages of instructions, scripts, and resources that Claude and other compatible agents can dynamically discover and load to extend their capabilities on specialized tasks. Rather than relying on handcrafted prompts every time, Skills teach an AI agent procedural knowledge and task-specific workflows so it can apply that expertise reliably, whether the task involves document...
    Downloads: 91 This Week
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  • 8
    Gemini-API

    Gemini-API

    Reverse-engineered Python API for Google Gemini web app

    Gemini-API is a community-created asynchronous Python wrapper for the web interface of Google’s Gemini models (formerly Bard). It is the result of reverse-engineering the Gemini web app and exposing its functionality through a programmatic API. This enables developers to incorporate Gemini into Python applications, scripts, bots, or tools without relying solely on official SDKs. The wrapper supports streaming responses, model selection, and handling of the web-based authentication/session mechanisms used by Google’s interface. ...
    Downloads: 5 This Week
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  • 9
    SAM 3

    SAM 3

    Code for running inference and finetuning with SAM 3 model

    SAM 3 (Segment Anything Model 3) is a unified foundation model for promptable segmentation in both images and videos, capable of detecting, segmenting, and tracking objects. It accepts both text prompts (open-vocabulary concepts like “red car” or “goalkeeper in white”) and visual prompts (points, boxes, masks) and returns high-quality masks, boxes, and scores for the requested concepts. Compared with SAM 2, SAM 3 introduces the ability to exhaustively segment all instances of an...
    Downloads: 51 This Week
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  • Easily build robust connections between Salesforce and any platform Icon
    Easily build robust connections between Salesforce and any platform

    We help companies using Salesforce connect their data with a no-code Salesforce-native solution.

    Like having Postman inside Salesforce! Declarative Webhooks allows users to quickly and easily configure bi-directional integrations between Salesforce and external systems using a point-and-click interface. No coding is required, making it a fast and efficient and as a native solution, Declarative Webhooks seamlessly integrates with Salesforce platform features such as Flow, Process Builder, and Apex. You can also leverage the AI Integration Agent feature to automatically build your integration templates by providing it with links to API documentation.
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  • 10
    WebGLM

    WebGLM

    An Efficient Web-enhanced Question Answering System

    ...Instead of relying solely on knowledge stored in the model’s training data, the system retrieves relevant web content and integrates it into the reasoning process. WebGLM introduces several components that coordinate this process, including a retrieval module that selects relevant web documents, a generator that produces answers, and a scoring system that evaluates the quality of generated responses. The architecture aims to improve the reliability and usefulness of AI systems that answer questions about current or external knowledge sources.
    Downloads: 0 This Week
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  • 11
    LLMCompiler

    LLMCompiler

    An LLM Compiler for Parallel Function Calling

    ...The framework builds a dependency graph of required operations, identifying which tasks must run sequentially and which can be executed simultaneously. Its architecture includes components such as a planning module that constructs the task graph, a task dispatcher that manages dependencies, and an executor that performs parallel calls.
    Downloads: 0 This Week
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  • 12
    Synthetic Data Generator

    Synthetic Data Generator

    SDG is a specialized framework

    ...The system supports multiple generation methods including statistical models, generative adversarial networks, and large language model–based synthesis. It also includes a data processing module capable of handling different data types, preprocessing columns, managing missing values, and converting formats automatically before model training.
    Downloads: 0 This Week
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  • 13
    VoxCPM

    VoxCPM

    TTS for Context-Aware Speech Generation and True-to-Life Voice Cloning

    VoxCPM is a tokenizer-free text-to-speech system that models speech in a continuous space, aiming for extremely realistic, context-aware synthesis and true-to-life zero-shot voice cloning. Instead of converting speech into discrete tokens, it uses an end-to-end diffusion-autoregressive architecture built on the MiniCPM-4 backbone, combining hierarchical language modeling, finite scalar quantization (FSQ), and local Diffusion Transformers. This design helps decouple semantic and acoustic...
    Downloads: 63 This Week
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  • 14
    Hunyuan3D-2.1

    Hunyuan3D-2.1

    From Images to High-Fidelity 3D Assets

    ...Physically Based Rendering texture synthesis to model realistic material effects, including reflections, subsurface scattering, etc. Cross-platform support (MacOS, Windows, Linux) via Python / PyTorch, including diffusers-style APIs.
    Downloads: 14 This Week
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  • 15
    OBLITERATUS

    OBLITERATUS

    OBLITERATE THE CHAINS THAT BIND YOU

    OBLITERATUS is an advanced open-source toolkit designed to analyze and modify the internal behavior of large language models by identifying and removing mechanisms responsible for refusal or restricted responses. It implements a set of techniques collectively referred to as “abliteration,” which target specific internal representations within neural networks to alter how models respond to certain prompts. Unlike traditional fine-tuning approaches, OBLITERATUS operates directly on model...
    Downloads: 19 This Week
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  • 16
    nanocode

    nanocode

    Minimal Claude Code alternative. Single Python file, zero dependencies

    nanocode is a minimalist coding agent implementation designed as a compact alternative to Claude Code, packaged in a single Python file with no external dependencies and totaling around 250 lines of code. It implements a full agentic loop where the model can reason, decide when to use tools, execute those tools, and iterate until producing a final answer, making it useful for simple AI-assisted coding workflows. It includes a set of integrated tools such as read, write, edit, glob, grep, and bash that let the agent interact with the file system and shell commands directly from the terminal, and it keeps a conversation history with colored terminal output for readability. ...
    Downloads: 4 This Week
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  • 17
    second-brain-ai-assistant-course

    second-brain-ai-assistant-course

    Learn to build your Second Brain AI assistant with LLMs

    The Second Brain AI Assistant Course is an open-source educational project designed to teach developers how to build a personal AI assistant that interacts with a user’s knowledge base. The course provides a structured curriculum that walks learners through the architecture and implementation of a production-ready AI system powered by large language models. The concept of a “second brain” refers to a personal knowledge repository containing notes, research, and documents that can be queried...
    Downloads: 0 This Week
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  • 18
    FLUX.2

    FLUX.2

    Official inference repo for FLUX.2 models

    FLUX.2 is a state-of-the-art open-weight image generation and editing model released by Black Forest Labs aimed at bridging the gap between research-grade capabilities and production-ready workflows. The model offers both text-to-image generation and powerful image editing, including editing of multiple reference images, with fidelity, consistency, and realism that push the limits of what open-source generative models have achieved. It supports high-resolution output (up to ~4 megapixels),...
    Downloads: 45 This Week
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  • 19
    DeepSeek-V3

    DeepSeek-V3

    Powerful AI language model (MoE) optimized for efficiency/performance

    DeepSeek-V3 is a robust Mixture-of-Experts (MoE) language model developed by DeepSeek, featuring a total of 671 billion parameters, with 37 billion activated per token. It employs Multi-head Latent Attention (MLA) and the DeepSeekMoE architecture to enhance computational efficiency. The model introduces an auxiliary-loss-free load balancing strategy and a multi-token prediction training objective to boost performance. Trained on 14.8 trillion diverse, high-quality tokens, DeepSeek-V3...
    Downloads: 120 This Week
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  • 20
    MemPalace

    MemPalace

    The highest-scoring AI memory system ever benchmarked

    MemPalace is an open-source AI memory system designed to solve one of the most persistent limitations of large language models: the loss of context between sessions. Instead of relying on summarization or selective extraction like most memory tools, it takes a radically different approach by storing conversations in their entirety and making them retrievable through structured organization and semantic search. The system is inspired by the classical “memory palace” mnemonic technique,...
    Downloads: 54 This Week
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  • 21
    MemMachine

    MemMachine

    Universal memory layer for AI Agents

    ...Unlike ephemeral LLM prompt state, MemMachine supports distinct memory types—short-term conversational context, long-term persistent knowledge, and profile memory for personalized facts—persisted in optimized stores (e.g., graph databases for episodic lines of reasoning and SQL for user facts) to support robust, context-aware intelligence in agents. It offers flexible APIs, a Python SDK, REST interfaces, and MCP (Model Context Protocol) connectivity to integrate seamlessly with agent frameworks receiving and storing memories over time, effectively boosting relevance, continuity, and tailored behavior.
    Downloads: 5 This Week
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  • 22
    AI Runner

    AI Runner

    Offline inference engine for art, real-time voice conversations

    AI Runner is an offline inference engine designed to run a collection of AI workloads on your own machine, including image generation for art, real-time voice conversations, LLM-powered chatbots and automated workflows. It is implemented as a desktop-oriented Python application and emphasizes privacy and self-hosting, allowing users to work with text-to-speech, speech-to-text, text-to-image and multimodal models without sending data to external services. At the core of its LLM stack is a mode-based architecture with specialized “modes” such as Author, Code, Research, QA and General, and a workflow manager that automatically routes user requests to the right agent based on the task. ...
    Downloads: 12 This Week
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  • 23
    Sunfish

    Sunfish

    Sunfish: a Python Chess Engine in 111 lines of code

    sunfish is a minimalist yet surprisingly strong chess engine written in Python, designed to demonstrate how powerful algorithms can be implemented in a highly compact codebase. Despite being only around a hundred lines of core logic, the engine achieves competitive performance, reaching ratings above 2000 on online platforms. It implements classic chess engine techniques such as alpha-beta pruning and efficient board representation while maintaining readability and simplicity. ...
    Downloads: 6 This Week
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  • 24
    Frigate

    Frigate

    NVR with realtime local object detection for IP cameras

    Frigate - NVR With Realtime Object Detection for IP Cameras A complete and local NVR designed for Home Assistant with AI object detection. Uses OpenCV and Tensorflow to perform realtime object detection locally for IP cameras. Use of a Google Coral Accelerator is optional, but highly recommended. The Coral will outperform even the best CPUs and can process 100+ FPS with very little overhead.
    Downloads: 40 This Week
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  • 25
    Learn AI Engineering

    Learn AI Engineering

    Learn AI and LLMs from scratch using free resources

    ...The curation recognizes modern AI realities, including data pipelines, evaluation, prompt engineering, retrieval-augmented generation, and cost/performance trade-offs. It’s equally useful for refreshers—dipping into a specific module before a project—as it is for a full, self-directed curriculum. By centralizing the best references in one place, the repo reduces the overhead of finding, filtering, and sequencing resources, letting you focus on learning and building.
    Downloads: 0 This Week
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