Showing 743 open source projects for "python ai"

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  • 1
    MCP ZoomEye

    MCP ZoomEye

    A Model Context Protocol server that provides network asset info

    The ZoomEye MCP Server is a Model Context Protocol server that provides network asset information based on query conditions, allowing Large Language Models to obtain data by querying ZoomEye using dorks and other search parameters. ​
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  • 2
    VikingDB MCP Server

    VikingDB MCP Server

    A mcp server for vikingdb store and search

    An MCP server that interfaces with VikingDB, a high-performance vector database developed by ByteDance, enabling efficient vector storage and search capabilities. ​
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  • 3
    Elasticsearch MCP Server

    Elasticsearch MCP Server

    A Model Context Protocol (MCP) server implementation

    This MCP server implementation provides interaction capabilities with Elasticsearch and OpenSearch, enabling functionalities such as document searching, index analysis, and cluster management through a set of tools. ​
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  • 4
    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.
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  • 5
    DOLMA

    DOLMA

    Data and tools for generating and inspecting OLMo pre-training data

    DOLMA (Data Optimization and Learning for Model Alignment) is a framework designed to manage large-scale datasets for training and fine-tuning language models efficiently.
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  • 6
    FastRAG

    FastRAG

    Efficient Retrieval Augmentation and Generation Framework

    fastRAG is a research framework for efficient and optimized retrieval augmented generative pipelines, incorporating state-of-the-art LLMs and Information Retrieval. fastRAG is designed to empower researchers and developers with a comprehensive tool set for advancing retrieval augmented generation.
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  • 7
    PromptTools

    PromptTools

    Open-source tools for prompt testing and experimentation

    Welcome to prompttools created by Hegel AI! This repo offers a set of open-source, self-hostable tools for experimenting with, testing, and evaluating LLMs, vector databases, and prompts. The core idea is to enable developers to evaluate using familiar interfaces like code, notebooks, and a local playground.
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  • 8
    Core ML Stable Diffusion

    Core ML Stable Diffusion

    Stable Diffusion with Core ML on Apple Silicon

    Run Stable Diffusion on Apple Silicon with Core ML. python_coreml_stable_diffusion, a Python package for converting PyTorch models to Core ML format and performing image generation with Hugging Face diffusers in Python. StableDiffusion, a Swift package that developers can add to their Xcode projects as a dependency to deploy image generation capabilities in their apps. The Swift package relies on the Core ML model files generated by python_coreml_stable_diffusion. Hugging Face ran...
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  • 9
    PyBoy

    PyBoy

    Game Boy emulator written in Python

    It is highly recommended to read the report to get a light introduction to Game Boy emulation. But do be aware, that the Python implementation has changed a lot. The report is relevant, even though you want to contribute to another emulator or create your own. If you are looking to make a bot or AI, you can find all the external components in the PyBoy Documentation. There is also a short example on our Wiki page Scripts, AI and Bots as well as in the examples directory. If more features...
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  • 10
    DataProfiler

    DataProfiler

    Extract schema, statistics and entities from datasets

    DataProfiler is an AI-powered tool for automatic data analysis and profiling, designed to detect patterns, anomalies, and schema inconsistencies in structured and unstructured datasets. The DataProfiler is a Python library designed to make data analysis, monitoring, and sensitive data detection easy. Loading Data with a single command, the library automatically formats & loads files into a DataFrame. Profiling the Data, the library identifies the schema, statistics, entities (PII / NPI...
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  • 11
    fairseq2

    fairseq2

    FAIR Sequence Modeling Toolkit 2

    fairseq2 is a modern, modular sequence modeling framework developed by Meta AI Research as a complete redesign of the original fairseq library. Built from the ground up for scalability, composability, and research flexibility, fairseq2 supports a broad range of language, speech, and multimodal content generation tasks, including instruction fine-tuning, reinforcement learning from human feedback (RLHF), and large-scale multilingual modeling. Unlike the original fairseq—which evolved...
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  • 12
    Pearl

    Pearl

    A Production-ready Reinforcement Learning AI Agent Library

    Pearl is a production-ready reinforcement learning and contextual bandit agent library built for real-world sequential decision making. It is organized around modular components—policy learners, replay buffers, exploration strategies, safety modules, and history summarizers—that snap together to form reliable agents with clear boundaries and strong defaults. The library implements classic and modern algorithms across two regimes: contextual bandits (e.g., LinUCB, LinTS, SquareCB, neural...
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  • 13
    CodeGeeX4

    CodeGeeX4

    CodeGeeX4-ALL-9B, a versatile model for all AI software development

    CodeGeeX4 is the fourth-generation open source multilingual code large language model (LLM) developed by ZhipuAI. Designed as a powerful AI coding assistant, it supports over 100 programming languages and has been trained on a massive code and natural language corpus. Compared to its predecessors, CodeGeeX4 introduces improved reasoning, stronger alignment with developer needs, and better performance on real-world programming benchmarks. It supports tasks such as code completion, generation...
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  • 14
    Stable Virtual Camera

    Stable Virtual Camera

    Stable Virtual Camera: Generative View Synthesis with Diffusion Models

    Stable Virtual Camera is a multi-view diffusion model developed by Stability AI that transforms 2D images into immersive 3D videos with realistic depth and perspective. Unlike traditional methods that require complex reconstruction or scene-specific optimization, this model allows users to generate novel views from any number of input images and define custom camera trajectories, enabling dynamic exploration of scenes. It supports various aspect ratios and can produce 3D-consistent videos up...
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  • 15
    Deep Lake

    Deep Lake

    Data Lake for Deep Learning. Build, manage, and query datasets

    Deep Lake (formerly known as Activeloop Hub) is a data lake for deep learning applications. Our open-source dataset format is optimized for rapid streaming and querying of data while training models at scale, and it includes a simple API for creating, storing, and collaborating on AI datasets of any size. It can be deployed locally or in the cloud, and it enables you to store all of your data in one place, ranging from simple annotations to large videos. Deep Lake is used by Google, Waymo, Red...
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  • 16
    MuJoCo MPC

    MuJoCo MPC

    Real-time behaviour synthesis with MuJoCo, using Predictive Control

    ... that achieves robust real-time control. The system supports multi-shooting optimization, enabling precise motion planning across diverse domains like quadruped locomotion, humanoid tracking, and dexterous manipulation. In addition to its C++ core, MJPC includes an experimental Python API, enabling integration with custom models and MuJoCo tasks for flexible scripting and experimentation.
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  • 17
    Granite TSFM

    Granite TSFM

    Foundation Models for Time Series

    granite-tsfm collects public notebooks, utilities, and serving components for IBM’s Time Series Foundation Models (TSFM), giving practitioners a practical path from data prep to inference for forecasting and anomaly-detection use cases. 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...
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  • 18
    UCO3D

    UCO3D

    Uncommon Objects in 3D dataset

    ... modeling experiments. The repository includes automated downloaders with checksum verification, fine-grained controls to fetch only selected modalities or super-categories, and a lightweight Python API for loading frames, geometry, and splats on demand. Metadata is indexed in SQLite for quick queries at scale, and helper builders handle alignment, undistortion, frame extraction from videos, and cropping around the object.
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  • 19
    xFormers

    xFormers

    Hackable and optimized Transformers building blocks

    ... attention mechanisms (e.g. FlashAttention, Linformer, Performer) via interchangeable modules. The library includes memory-efficient operator implementations in both Python and optimized C++/CUDA, ensuring that performance isn’t sacrificed for modularity. It also integrates with PyTorch seamlessly so you can drop in its blocks to existing models, replace default attention layers, or build new architectures from scratch. xformers includes training, deployment, and memory profiling tools.
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  • 20
    ImageReward

    ImageReward

    [NeurIPS 2023] ImageReward: Learning and Evaluating Human Preferences

    ImageReward is the first general-purpose human preference reward model (RM) designed for evaluating text-to-image generation, introduced alongside the NeurIPS 2023 paper ImageReward: Learning and Evaluating Human Preferences for Text-to-Image Generation. Trained on 137k expert-annotated image pairs, ImageReward significantly outperforms existing scoring methods like CLIP, Aesthetic, and BLIP in capturing human visual preferences. It is provided as a Python package (image-reward) that enables...
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  • 21
    Tiktoken

    Tiktoken

    tiktoken is a fast BPE tokeniser for use with OpenAI's models

    ... names to match different model contexts. It also offers extension mechanisms so that custom encodings can be registered. Internally, it includes the core tokenizer logic (often implemented in Rust or efficient lower-level code), APIs for encoding, decoding, and counting tokens, and binding layers to Python (and sometimes other languages) for easy use.
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  • 22
    Kaleidoscope-SDK

    Kaleidoscope-SDK

    User toolkit for analyzing and interfacing with Large Language Models

    kaleidoscope-sdk is a Python module used to interact with large language models hosted via the Kaleidoscope service available at: https://github.com/VectorInstitute/kaleidoscope. It provides a simple interface to launch LLMs on an HPC cluster, asking them to perform basic features like text generation, but also retrieve intermediate information from inside the model, such as log probabilities and activations. Users must authenticate using their Vector Institute cluster credentials. This can...
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  • 23
    Kor

    Kor

    LLM

    This is a half-baked prototype that “helps” you extract structured data from text using LLMs. Specify the schema of what should be extracted and provide some examples. Kor will generate a prompt, send it to the specified LLM and parse out the output. You might even get results back.
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  • 24
    aisuite

    aisuite

    Simple, unified interface to multiple Generative AI providers

    Simple, unified interface to multiple Generative AI providers. aisuite makes it easy for developers to use multiple LLM through a standardized interface. Using an interface similar to OpenAI's, aisuite makes it easy to interact with the most popular LLMs and compare the results. It is a thin wrapper around Python client libraries and allows creators to seamlessly swap out and test responses from different LLM providers without changing their code. Today, the library is primarily focused on chat...
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  • 25
    Swirl

    Swirl

    Swirl queries any number of data sources with APIs

    Swirl queries any number of data sources with APIs and uses spaCy and NLTK to re-rank the unified results without extracting and indexing anything! Includes zero-code configs for Apache Solr, ChatGPT, Elastic Search, OpenSearch, PostgreSQL, Google BigQuery, RequestsGet, Google PSE, NLResearch.com, Miro & more! SWIRL adapts and distributes queries to anything with a search API - search engines, databases, noSQL engines, cloud/SaaS services etc - and uses AI (Large Language Models) to re-rank...
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