Showing 63 open source projects for "platform"

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  • Build Agents and Models on One Platform Icon
    Build Agents and Models on One Platform

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  • 1
    II Agent

    II Agent

    A new open-source framework to build and deploy intelligent agents

    II-Agent is an open-source intelligent assistant framework designed to automate complex workflows across multiple domains using large language models and external tools. The platform allows users to interact with multiple AI models within a single environment while connecting those models to external services and knowledge sources. Through a unified interface, users can switch between models, access specialized tools, and execute tasks that require information retrieval, code execution, or file analysis. The architecture focuses on transforming traditional software tools into autonomous assistants capable of completing tasks independently based on user instructions. ...
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  • 2
    AgentBench

    AgentBench

    A Comprehensive Benchmark to Evaluate LLMs as Agents (ICLR'24)

    AgentBench is an open-source benchmark designed to evaluate the capabilities of large language models when used as autonomous agents. Unlike traditional language model benchmarks that focus on static text tasks, AgentBench measures how models perform in interactive environments that require planning, reasoning, and decision-making. The benchmark includes multiple environments that simulate realistic scenarios such as web interaction, database querying, and problem solving tasks. These...
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  • 3
    Chat with LLMs Everywhere

    Chat with LLMs Everywhere

    Run PyTorch LLMs locally on servers, desktop and mobile

    TorchChat is an open-source project from the PyTorch ecosystem designed to demonstrate how large language models can be executed efficiently across different computing environments. The project provides a compact codebase that illustrates how to run conversational AI systems using PyTorch models on laptops, servers, and mobile devices. It is intended primarily as a reference implementation that shows developers how to integrate large language models into applications without requiring a...
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  • 4
    FastDeploy

    FastDeploy

    High-performance Inference and Deployment Toolkit for LLMs and VLMs

    ...Developed within the PaddlePaddle ecosystem, the toolkit focuses on providing high-performance deployment capabilities for modern AI models including large language models and vision-language systems. The platform enables developers to deploy trained models quickly using optimized inference pipelines that support GPUs, specialized AI accelerators, and other hardware architectures. FastDeploy includes advanced acceleration technologies such as speculative decoding, multi-token prediction, and efficient KV cache management to improve throughput and latency during inference. ...
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  • Stop Cyber Threats with VM-Series Next-Gen Firewall on Azure Icon
    Stop Cyber Threats with VM-Series Next-Gen Firewall on Azure

    Native application identity and user-based security for your Azure cloud

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  • 5
    LLM Workflow Engine

    LLM Workflow Engine

    Power CLI and Workflow manager for LLMs (core package)

    LLM Workflow Engine is an open-source command-line framework designed to integrate large language models into automated workflows and developer environments. The platform allows users to interact with AI models directly from the terminal, enabling conversational AI access through shell commands and scripts. Instead of focusing solely on chat interactions, the system is built to embed LLM calls into larger automation pipelines where model outputs can drive decision making or trigger additional processes. ...
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  • 6
    E2B Cookbook

    E2B Cookbook

    Examples of using E2B

    E2B Cookbook is an open-source collection of example projects, guides, and reference implementations demonstrating how to build applications using the E2B platform. The repository acts as a practical learning resource for developers who want to integrate AI agents with secure cloud execution environments that allow large language models to run code and interact with tools. The examples illustrate how developers can build AI workflows capable of performing tasks such as data analysis, code execution, and application generation inside isolated sandbox environments. ...
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  • 7
    handy-ollama

    handy-ollama

    Implement CPU from scratch and play with large model deployments

    handy-ollama is an open-source educational project designed to help developers and AI enthusiasts learn how to deploy and run large language models locally using the Ollama platform. The repository serves as a structured tutorial that explains how to install, configure, and use Ollama to run modern language models on personal hardware without requiring advanced infrastructure. A key focus of the project is enabling users to run large models even without GPUs by leveraging optimized CPU-based inference pipelines. ...
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  • 8
    InternGPT

    InternGPT

    Open source demo platform where you can easily showcase your AI models

    InternGPT is an open-source multimodal AI framework designed to extend large language models beyond text interactions into visual reasoning and image manipulation tasks. The system integrates conversational AI with computer vision models so users can interact with images, videos, and visual environments through natural language instructions. Unlike traditional chat systems that rely solely on text prompts, InternGPT allows users to interact with visual content using both language and...
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  • 9
    LLM Foundry

    LLM Foundry

    LLM training code for MosaicML foundation models

    ...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. This has led to a flurry of activity centered on open-source LLMs, such as the LLaMA series from Meta, the Pythia series from EleutherAI, the StableLM series from StabilityAI, and the OpenLLaMA model from Berkeley AI Research.
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  • $300 Free Credits for Your Google Cloud Projects Icon
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  • 10
    AI-Codereview-Gitlab

    AI-Codereview-Gitlab

    GitLab automatic code review tool based on large models

    ...The system monitors GitLab repositories and analyzes commits or merge requests using AI models to identify potential issues, coding mistakes, and quality improvements before the code is merged. By leveraging multiple large language model providers—including OpenAI, DeepSeek, ZhipuAI, or local models through Ollama—the platform allows teams to choose the AI engine that best fits their infrastructure and privacy requirements. When code changes occur, the system can automatically generate review comments and feedback that are posted directly into GitLab merge requests, allowing developers to see suggestions alongside human reviewer comments. In addition to code analysis, the tool can produce daily development summaries and notifications that help teams track progress and review activity across projects.
    Downloads: 0 This Week
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  • 11
    LangChain-ChatGLM-Webui

    LangChain-ChatGLM-Webui

    Automatic question answering for local knowledge bases based on LLM

    LangChain-ChatGLM-Webui is an open-source web interface that integrates the ChatGLM large language model with the LangChain framework to create an interactive conversational AI platform. The project provides a graphical interface that allows users to interact with language models through chat sessions while also connecting those models to external knowledge sources. It supports retrieval-augmented generation workflows that enable the system to answer questions based on local documents or knowledge bases. By leveraging the LangChain framework, the platform allows developers to integrate tools such as vector databases, document loaders, and prompt chains into the chatbot workflow. ...
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  • 12
    GPT Neo

    GPT Neo

    An implementation of model parallel GPT-2 and GPT-3-style models

    An implementation of model & data parallel GPT3-like models using the mesh-tensorflow library. If you're just here to play with our pre-trained models, we strongly recommend you try out the HuggingFace Transformer integration. Training and inference is officially supported on TPU and should work on GPU as well. This repository will be (mostly) archived as we move focus to our GPU-specific repo, GPT-NeoX. NB, while neo can technically run a training step at 200B+ parameters, it is very...
    Downloads: 1 This Week
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  • 13
    NewsNotFound

    NewsNotFound

    This is the entire source code for NewsNotFound's article gen process

    Our mission is to lead the way in AI journalism by providing completely neutral and unbiased news articles that can be governed by the public. NewsNotFound is a news website located at https://newsnotfound.com. We want to build the most unbiased news platform on the internet.
    Downloads: 0 This Week
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