Showing 2757 open source projects for "python"

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  • 1
    Fantasy PL MCP

    Fantasy PL MCP

    Fantasy Premier League MCP Server

    Fantasy Premier League MCP Server is a Model Context Protocol (MCP) server that provides access to Fantasy Premier League (FPL) data and tools. It allows interaction with FPL data in MCP-compatible clients, enabling users to manage their fantasy teams effectively. ​
    Downloads: 5 This Week
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  • 2
    LoRAX

    LoRAX

    Multi-LoRA inference server that scales to 1000s of fine-tuned LLMs

    Lorax is a multi-LoRA (Low-Rank Adaptation) inference server that scales to thousands of fine-tuned Large Language Models (LLMs). It enables efficient deployment and management of numerous fine-tuned models, facilitating scalable AI applications. Lorax is designed to handle high concurrency and provides a robust infrastructure for serving multiple LLMs simultaneously.
    Downloads: 5 This Week
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  • 3
    Agentic Security

    Agentic Security

    Agentic LLM Vulnerability Scanner / AI red teaming kit

    The open-source Agentic LLM Vulnerability Scanner.
    Downloads: 5 This Week
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  • 4
    doccano

    doccano

    Open source annotation tool for machine learning practitioners

    doccano is an open-source text annotation tool for humans. It provides annotation features for text classification, sequence labeling and sequence-to-sequence tasks. So, you can create labeled data for sentiment analysis, named entity recognition, text summarization and so on. Just create a project, upload data and start annotating. You can build a dataset in hours.
    Downloads: 5 This Week
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  • 5
    Faster Whisper

    Faster Whisper

    Faster Whisper transcription with CTranslate2

    Faster Whisper is an optimized implementation of the Whisper speech recognition model designed to deliver significantly faster inference while maintaining comparable accuracy. It leverages efficient inference engines and optimized computation strategies to reduce latency and resource consumption. The system is particularly useful for real-time or large-scale transcription tasks where performance is critical. It supports multiple model sizes, allowing users to balance speed and accuracy based...
    Downloads: 15 This Week
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  • 6
    Code-Graph-RAG

    Code-Graph-RAG

    The ultimate RAG for your monorepo

    Code-Graph-RAG is an advanced retrieval-augmented generation system designed specifically for understanding and interacting with large, multi-language codebases by transforming them into structured knowledge graphs. It uses Tree-sitter to parse source code into abstract syntax trees, extracting relationships between functions, classes, and modules to build a graph-based representation of the entire codebase. This structured approach enables more accurate and context-aware querying compared...
    Downloads: 19 This Week
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  • 7
    Whisper-WebUI

    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...
    Downloads: 19 This Week
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  • 8
    qxresearch-event-1

    qxresearch-event-1

    Python hands on tutorial with 50+ Python Application

    qxresearch-event-1 is an open-source educational repository that provides a collection of lightweight Python applications designed to demonstrate programming concepts and artificial intelligence techniques in simple and accessible examples. The repository contains dozens of small programs, many implemented with minimal lines of code, covering topics such as machine learning, graphical user interfaces, computer vision, and API integration.
    Downloads: 0 This Week
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  • 9
    Memobase

    Memobase

    Fast backend for long-term AI user memory via structured profiles

    ...The system focuses on three principal performance metrics: high search performance, reduced large language model (LLM) costs through batch processing techniques, and low latency with minimal SQL operations. Memobase supports integration with existing LLM workflows via APIs and SDKs (including Python, Node, and Go), making it easy to adopt within diverse application stacks.
    Downloads: 4 This Week
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  • 10
    GLM-4.5

    GLM-4.5

    GLM-4.5: Open-source LLM for intelligent agents by Z.ai

    GLM-4.5 is a cutting-edge open-source large language model designed by Z.ai for intelligent agent applications. The flagship GLM-4.5 model has 355 billion total parameters with 32 billion active parameters, while the compact GLM-4.5-Air version offers 106 billion total parameters and 12 billion active parameters. Both models unify reasoning, coding, and intelligent agent capabilities, providing two modes: a thinking mode for complex reasoning and tool usage, and a non-thinking mode for...
    Downloads: 80 This Week
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  • 11
    Agno

    Agno

    Lightweight framework for building Agents with memory, knowledge, etc.

    Agno is a modular, open-source artificial general intelligence (AGI) research platform that allows developers to build, evaluate, and experiment with cognitive architectures in a composable way. It provides a flexible framework for modeling reasoning, memory, decision-making, and planning, aimed at long-term AI research beyond narrow learning. Agno embraces multi-agent environments and symbolic reasoning as part of its core design, enabling experiments with structured knowledge,...
    Downloads: 6 This Week
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  • 12
    Supabase MCP Server

    Supabase MCP Server

    Query MCP enables end-to-end management of Supabase via chat interface

    An open-source MCP server that enables comprehensive management of Supabase projects through natural language interactions, providing capabilities such as SQL execution, schema management, and API integration. ​
    Downloads: 6 This Week
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  • 13
    OpenAI Agents SDK

    OpenAI Agents SDK

    A lightweight, powerful framework for multi-agent workflows

    The OpenAI Agents Python SDK is a powerful yet lightweight framework for developing multi-agent workflows. This framework enables developers to create and manage agents that can coordinate tasks autonomously, using a set of instructions, tools, guardrails, and handoffs. The SDK allows users to configure workflows in which agents can pass control to other agents as necessary, ensuring dynamic task management.
    Downloads: 4 This Week
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  • 14
    GPTme

    GPTme

    Your agent in your terminal, equipped with local tools

    GPTMe is a personal AI chatbot designed for self-reflection, journaling, and productivity, using GPT models to generate personalized insights and responses.
    Downloads: 6 This Week
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  • 15
    pyAudioAnalysis

    pyAudioAnalysis

    Python Audio Analysis Library: Feature Extraction, Classification

    pyAudioAnalysis is an open-source Python library designed for audio signal analysis, machine learning, and music information retrieval tasks. The project provides a collection of tools that allow developers to extract meaningful features from audio files and use those features for classification, segmentation, and analysis. The library supports multiple audio processing workflows, including feature extraction from raw audio signals, training of machine learning models, and automatic audio segmentation. ...
    Downloads: 1 This Week
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  • 16
    nanobot

    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...
    Downloads: 28 This Week
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  • 17
    GLM-OCR

    GLM-OCR

    Accurate × Fast × Comprehensive

    GLM-OCR is an open-source multimodal optical character recognition (OCR) model built on a GLM-V encoder–decoder foundation that brings robust, accurate document understanding to complex real-world layouts and modalities. Designed to handle text recognition, table parsing, formula extraction, and general information retrieval from documents containing mixed content, GLM-OCR excels across major benchmarks while remaining highly efficient with a relatively compact parameter size (~0.9B),...
    Downloads: 23 This Week
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  • 18
    optillm

    optillm

    Optimizing inference proxy for LLMs

    OptiLLM is an optimizing inference proxy for Large Language Models (LLMs) that implements state-of-the-art techniques to enhance performance and efficiency. It serves as an OpenAI API-compatible proxy, allowing for seamless integration into existing workflows while optimizing inference processes. OptiLLM aims to reduce latency and resource consumption during LLM inference.
    Downloads: 7 This Week
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  • 19
    TextWorld

    TextWorld

    ​TextWorld is a sandbox learning environment for the training

    TextWorld is a learning environment designed to train reinforcement learning agents to play text-based games, where actions and observations are entirely in natural language. Developed by Microsoft Research, TextWorld focuses on language understanding, planning, and interaction in complex, narrative-driven environments. It generates games procedurally, enabling scalable testing of agents’ natural language processing and decision-making abilities.
    Downloads: 7 This Week
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  • 20
    WhatsApp MCP Server

    WhatsApp MCP Server

    WhatsApp MCP server enabling AI access to chats and messaging

    ...It acts as a bridge between WhatsApp and large language models, allowing controlled access to messages, chats, and contacts. whatsapp-mcp is composed of two main components: a Go-based bridge that connects to the WhatsApp Web API and stores data locally, and a Python-based MCP server that exposes tools for AI interaction. All message data is stored in a local SQLite database and is only accessed when explicitly requested through defined tools, giving users control over how their data is used. It supports both sending and receiving messages, including various media types such as images, audio, videos, and documents. ...
    Downloads: 3 This Week
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  • 21
    NVIDIA cuOpt

    NVIDIA cuOpt

    GPU accelerated decision optimization

    ...Built primarily in C++, cuOpt leverages NVIDIA GPUs to deliver near real-time solutions for optimization tasks involving millions of variables and constraints. The platform provides multiple interfaces, including C, Python, and server APIs, allowing developers to integrate optimization capabilities into applications and services. cuOpt is designed for high-performance environments and can be deployed across cloud, hybrid, or on-premise infrastructures. By combining GPU acceleration with scalable APIs, cuOpt enables organizations to solve large optimization challenges in logistics, operations research, and decision-making systems.
    Downloads: 3 This Week
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  • 22
    LLMs-from-scratch

    LLMs-from-scratch

    Implement a ChatGPT-like LLM in PyTorch from scratch, step by step

    ...It emphasizes building blocks—tokenization, embeddings, attention, feed-forward layers, normalization, and training loops—so learners understand not just how to use a model but how it works internally. The repository favors clear Python and NumPy or PyTorch implementations that can be run and modified without heavyweight frameworks obscuring the logic. Chapters and notebooks progress from tiny toy models to more capable transformer stacks, including sampling strategies and evaluation hooks. The focus is on readability, correctness, and experimentation, making it ideal for students and practitioners transitioning from theory to working systems. ...
    Downloads: 3 This Week
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  • 23
    Granite TSFM

    Granite TSFM

    Foundation Models for Time Series

    ...The repository focuses on end-to-end workflows: loading data, building datasets, fine-tuning forecasters, running evaluations, and serving models. It documents the currently supported Python versions and points users to where the core TSFM models are hosted and how to wire up service components. Issues and examples in the tracker illustrate common tasks such as slicing inference windows or using pipeline helpers that return pandas DataFrames, grounding the library in day-to-day time-series operations. The ecosystem around TSFM also includes a community cookbook of “recipes” that showcase capabilities and patterns. ...
    Downloads: 3 This Week
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  • 24
    CodeLlama

    CodeLlama

    Inference code for CodeLlama models

    Code Llama is a family of Llama-based code models optimized for programming tasks such as code generation, completion, and repair, with variants specialized for base coding, Python, and instruction following. The repo documents the sizes and capabilities (e.g., 7B, 13B, 34B) and highlights features like infilling and large input context to support real IDE workflows. It targets both general software synthesis and language-specific productivity, offering strong performance among open models at release time. ...
    Downloads: 3 This Week
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  • 25
    nanoGPT

    nanoGPT

    The simplest, fastest repository for training/finetuning models

    NanoGPT is a minimalistic yet powerful reimplementation of GPT-style transformers created by Andrej Karpathy for educational and research use. It distills the GPT architecture into a few hundred lines of Python code, making it far easier to understand than large, production-scale implementations. The repo is organized with a training pipeline (dataset preprocessing, model definition, optimizer, training loop) and inference script so you can train a small GPT on text datasets like Shakespeare or custom corpora. It emphasizes readability and clarity: the training loop is cleanly written, and the code avoids heavy abstractions, letting students follow the architecture step by step. ...
    Downloads: 3 This Week
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