Showing 393 open source projects for "base-files"

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  • 1
    Codai

    Codai

    Codai is an AI code assistant that helps developers

    Codai is an AI code assistant designed to help developers efficiently manage their daily tasks through a session-based CLI, such as adding new features, refactoring, and performing detailed code reviews. What makes codai stand out is its deep understanding of the entire context of your project, enabling it to analyze your code base and suggest improvements or new code based on your context. This AI-powered tool supports multiple LLM providers, such as OpenAI, Azure OpenAI, Ollama, Anthropic...
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  • 2
    kener

    kener

    Kener is a Modern Self hosted Status Page, batteries included

    Kener: Open-source Node.js status page tool, designed to make service monitoring and incident handling a breeze. It offers a sleek and user-friendly interface that simplifies tracking service outages and improves how we communicate during incidents. And the best part? Kener integrates seamlessly with GitHub, making incident management a team effort—making it easier for us to track and fix issues together in a collaborative and friendly environment.
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  • 3
    FullTClash

    FullTClash

    General proxy performance testing tool based on Clash using Telegram

    Back end part useClash project(It can also be called nowmihomo)The relevant code is used as the outing agent. The front end part uses Telegram API as the interactive interface, which needs to be used in conjunction with Telegram, that is, a Telegram robot (bot), FullTClash bot is a Telegram robot (hereinafter referred to as bot) carrying its test tasks.
    Downloads: 0 This Week
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  • 4
    Prompt flow

    Prompt flow

    Build high-quality LLM apps

    Prompt flow is a suite of development tools designed to streamline the end-to-end development cycle of LLM-based AI applications, from ideation, prototyping, testing, and evaluation to production deployment and monitoring. It makes prompt engineering much easier and enables you to build LLM apps with production quality.
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  • 5
    Stable Baselines3

    Stable Baselines3

    PyTorch version of Stable Baselines

    Stable Baselines3 (SB3) is a set of reliable implementations of reinforcement learning algorithms in PyTorch. It is the next major version of Stable Baselines. You can read a detailed presentation of Stable Baselines3 in the v1.0 blog post or our JMLR paper. These algorithms will make it easier for the research community and industry to replicate, refine, and identify new ideas, and will create good baselines to build projects on top of. We expect these tools will be used as a base around which...
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  • 6
    Sweep AI

    Sweep AI

    Sweep: AI-powered Junior Developer for small features and bug fixes

    Let Sweep handle your tech debt so you can focus on the exciting problems. Sweep is an AI junior developer that transforms bug reports & feature requests into code changes. Describe bugs, small features, and refactors like you would to a junior developer and Sweep.
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  • 7
    Chainlit

    Chainlit

    Build Python LLM apps in minutes

    Chainlit is an open-source Python package that makes it incredibly fast to build and share LLM apps. Integrate the Chainlit API in your existing code to spawn a ChatGPT-like interface in minutes! Integrate seamlessly with an existing code base or start from scratch in minutes. Understand the intermediary steps that produced an output at a glance. Deep dive into prompts in the Prompt Playground to understand where things went wrong and iterate. Invite your teammates, create annotated datasets...
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  • 8
    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...
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  • 9
    DeepEval
    DeepEval is a simple-to-use, open-source LLM evaluation framework, for evaluating and testing large-language model systems. It is similar to Pytest but specialized for unit testing LLM outputs. DeepEval incorporates the latest research to evaluate LLM outputs based on metrics such as G-Eval, hallucination, answer relevancy, RAGAS, etc., which uses LLMs and various other NLP models that run locally on your machine for evaluation. Whether your application is implemented via RAG or fine-tuning,...
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  • 10
    GaiaNet

    GaiaNet

    Install and run your own AI agent service

    Gaia is building an active, intelligent ecosystem that supports applications that learn, improve and grow over time. Put your knowledge to work and watch it evolve by creating a node on Gaia or by contributing to a domain supporting an existing knowledge base. Gaia’s decentralized platform ensures robust protection for user data and IP. Gaia allows secure ownership and monetization of IP without compromising privacy. Gaia’s living knowledge organisms continuously adapt and grow in real-time...
    Downloads: 0 This Week
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  • 11
    SalesGPT

    SalesGPT

    Context-aware AI Sales Agent to automate sales outreach

    This repo is an implementation of a context-aware AI Agent for Sales using LLMs and can work across voice, email and texting (SMS, WhatsApp, WeChat, Weibo, Telegram, etc.). SalesGPT is context-aware, which means it can understand what stage of a sales conversation it is in and act accordingly. Moreover, SalesGPT has access to tools, such as your own pre-defined product knowledge base, significantly reducing hallucinations.
    Downloads: 0 This Week
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  • 12
    Spark NLP

    Spark NLP

    State of the Art Natural Language Processing

    Experience the power of large language models like never before, unleashing the full potential of Natural Language Processing (NLP) with Spark NLP, the open source library that delivers scalable LLMs. The full code base is open under the Apache 2.0 license, including pre-trained models and pipelines. The only NLP library built natively on Apache Spark. The most widely used NLP library in the enterprise. Spark ML provides a set of machine learning applications that can be built using two main...
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  • 13
    LLM Foundry

    LLM Foundry

    LLM training code for MosaicML foundation models

    Introducing MPT-7B, the first entry in our MosaicML Foundation Series. 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...
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  • 14
    Chinese-LLaMA-Alpaca 2

    Chinese-LLaMA-Alpaca 2

    Chinese LLaMA-2 & Alpaca-2 Large Model Phase II Project

    This project is developed based on the commercially available large model Llama-2 released by Meta. It is the second phase of the Chinese LLaMA&Alpaca large model project. The Chinese LLaMA-2 base model and the Alpaca-2 instruction fine-tuning large model are open-sourced. These models expand and optimize the Chinese vocabulary on the basis of the original Llama-2, use large-scale Chinese data for incremental pre-training, and further improve the basic semantics and command understanding...
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  • 15
    Alpaca.cpp

    Alpaca.cpp

    Locally run an Instruction-Tuned Chat-Style LLM

    Run a fast ChatGPT-like model locally on your device. This combines the LLaMA foundation model with an open reproduction of Stanford Alpaca a fine-tuning of the base model to obey instructions (akin to the RLHF used to train ChatGPT) and a set of modifications to llama.cpp to add a chat interface. Download the zip file corresponding to your operating system from the latest release. The weights are based on the published fine-tunes from alpaca-lora, converted back into a PyTorch checkpoint...
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  • 16
    Lightweight' GAN

    Lightweight' GAN

    Implementation of 'lightweight' GAN, proposed in ICLR 2021

    Implementation of 'lightweight' GAN proposed in ICLR 2021, in Pytorch. The main contribution of the paper is a skip-layer excitation in the generator, paired with autoencoding self-supervised learning in the discriminator. Quoting the one-line summary "converge on single gpu with few hours' training, on 1024 resolution sub-hundred images". Augmentation is essential for Lightweight GAN to work effectively in a low data setting. You can test and see how your images will be augmented before...
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  • 17
    MMAction2

    MMAction2

    OpenMMLab's Next Generation Video Understanding Toolbox and Benchmark

    OpenMMLab's next generation video understanding toolbox and benchmark. MMAction2 is an open-source toolbox for video understanding based on PyTorch. It is a part of the OpenMMLab project. Modular design: We decompose a video understanding framework into different components. One can easily construct a customized video understanding framework by combining different modules. Support four major video understanding tasks: MMAction2 implements various algorithms for multiple video understanding...
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  • 18
    amazon-connect-wisdomjs

    amazon-connect-wisdomjs

    Gives you the power to build your own Wisdom widget

    Amazon Connect Wisdom, a feature of Amazon Connect, delivers agents the information they need, reducing the time spent searching for answers. Today, knowledge articles, wikis, and FAQs are spread across separate repositories. Agents lose a lot of time trying to navigate all those different sources of information, and in the meantime, the customer waits for an answer. Amazon Connect Wisdom connects relevant knowledge repositories with built-in connectors for third-party applications like...
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  • 19
    Stanza

    Stanza

    Stanford NLP Python library for many human languages

    Stanza is a collection of accurate and efficient tools for the linguistic analysis of many human languages. Starting from raw text to syntactic analysis and entity recognition, Stanza brings state-of-the-art NLP models to languages of your choosing. Stanza is a Python natural language analysis package. It contains tools, which can be used in a pipeline, to convert a string containing human language text into lists of sentences and words, to generate base forms of those words, their parts...
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  • 20
    Telegram File Stream Bot

    Telegram File Stream Bot

    A telegram bot that will give instant stream links for telegram files

    A Telegram bot to generate direct link for your Telegram files.
    Downloads: 0 This Week
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  • 21
    cognee

    cognee

    Deterministic LLMs Outputs for AI Applications and AI Agents

    ... works; unstructured text or raw media files, PDFs, tables, presentations, JSON files, and so many more. Add small or large files, or many files at once. We map out a knowledge graph from all the facts and relationships we extract from your data. Then, we establish graph topology and connect related knowledge clusters, enabling the LLM to "understand" the data.
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  • 22
    tgState

    tgState

    Using Telegram as a stored file chain system

    A file chain system with Telegram as a storage. No limit to file size and format. It can be used as a telegram drawing bed or as a telegram net. Support web upload files and telegram upload directly.
    Downloads: 0 This Week
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  • 23
    Promptr

    Promptr

    Promptr is a CLI tool that lets you use plain English to instruct GPT3

    Promptr is a CLI tool that lets you use plain English to instruct OpenAI LLM models to make changes to your codebase. Changes are applied directly to the files that you reference from your prompt.
    Downloads: 0 This Week
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  • 24
    Mentat

    Mentat

    Mentat - The AI Coding Assistant

    Mentat is the AI tool that assists you with any coding task, right from your command line. Unlike Copilot, Mentat coordinates edits across multiple locations and files. And unlike ChatGPT, Mentat already has the context of your project, no copy and pasting is required. Run Mentat from within your project directory. Mentat uses Git, so if your project doesn't already have Git set up, run git init. List the files you would like Mentat to read and edit as arguments. Mentat will add each of them...
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  • 25
    pytorch-cpp

    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...
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