Search Results for "python user interface" - Page 12
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Showing 831 open source projects for "python user interface"
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1
files-to-prompt
Concatenate a directory full of files into a single prompt
files-to-prompt is a Python command-line tool that takes one or more files or entire directories and concatenates their contents into a single, LLM-friendly prompt. It walks the directory tree, outputting each file preceded by its relative path and a separator, so a model can understand which content came from where. The tool is aimed at workflows where you want to ask an LLM questions about a whole codebase, documentation set, or notes folder without manually copying files together. It... -
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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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web-eval-agent MCP Server
An MCP server that autonomously evaluates web applications
web-eval-agent is a Model Context Protocol (MCP) server that spins up a browser-use–capable debugging agent to autonomously run and evaluate web apps straight from your editor. It’s positioned as a “let the coding agent debug itself” companion: the agent launches the app, navigates flows, captures evidence, and iterates on failures without manual copy-pasting of logs. The repository focuses on developer ergonomics, exposing typed MCP tools so clients like Claude Desktop can start sessions,... -
4
MetaGPT
The Multi-Agent Framework
The Multi-Agent Framework: Given one line Requirement, return PRD, Design, Tasks, Repo. Assign different roles to GPTs to form a collaborative software entity for complex tasks. MetaGPT takes a one-line requirement as input and outputs user stories / competitive analysis/requirements/data structures / APIs / documents, etc. Internally, MetaGPT includes product managers/architects/project managers/engineers. It provides the entire process of a software company along with carefully orchestrated SOPs. -
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5
HunyuanWorld-Voyager
RGBD video generation model conditioned on camera input
HunyuanWorld-Voyager is a next-generation video diffusion framework developed by Tencent-Hunyuan for generating world-consistent 3D scene videos from a single input image. By leveraging user-defined camera paths, it enables immersive scene exploration and supports controllable video synthesis with high realism. The system jointly produces aligned RGB and depth video sequences, making it directly applicable to 3D reconstruction tasks. At its core, Voyager integrates a world-consistent video... -
6
Colab-MCP
An MCP server for interacting with Google Colab
Colab-MCP is an open-source Model Context Protocol server developed by Google that enables AI agents to directly interact with and control Google Colab environments programmatically, transforming Colab into a fully automated, agent-accessible workspace. Instead of relying on manual notebook usage, the system allows MCP-compatible agents to execute code, manage files, install dependencies, and orchestrate entire development workflows within Colab’s cloud infrastructure. This approach bridges... -
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Cactus
Low-latency AI inference engine optimized for mobile devices
Cactus is a low-latency, energy-efficient AI inference framework designed specifically for mobile devices and wearables, enabling advanced machine learning capabilities directly on-device. It provides a full-stack architecture composed of an inference engine, a computation graph system, and highly optimized hardware kernels tailored for ARM-based processors. Cactus emphasizes efficient memory usage through techniques such as zero-copy computation graphs and quantized model formats, allowing... -
8
Qodo Cover
AI tool that generates tests to improve code coverage quickly
Qodo Cover is an open source developer tool designed to automate the creation of unit tests using generative AI, helping teams improve code coverage with minimal manual effort. It operates as a command-line interface and can also be integrated into continuous integration workflows, making it adaptable to different development environments. It analyzes an existing codebase, identifies gaps in test coverage, and generates new tests that target uncovered or weakly tested areas. It follows an... -
9
LEANN
Local RAG engine for private multimodal knowledge search on devices
LEANN is an open source system designed to enable retrieval-augmented generation (RAG) and semantic search across personal data while running entirely on local devices. It focuses on dramatically reducing the storage overhead typically required for vector search and embedding indexes, enabling efficient large-scale knowledge retrieval on consumer hardware. LEANN introduces a storage-efficient approximate nearest neighbor index combined with on-the-fly embedding recomputation to avoid storing... -
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Sage Chat
Chat with any codebase in under two minutes | Fully local
Sage is an open-source AI developer assistant designed to help engineers understand and work with complex codebases more effectively. The tool functions similarly to an intelligent research agent that can analyze a repository and answer questions about how the software works. Instead of focusing solely on code generation, Sage emphasizes code comprehension, system architecture analysis, and integration guidance. Developers can ask natural language questions about a project, and the system... -
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Index
The SOTA Open-Source Browser Agent
Index is an open-source browser automation agent designed to autonomously perform complex tasks across websites by transforming web interfaces into programmable APIs. The system enables developers to instruct an AI agent to interact with web pages using natural language rather than traditional automation scripts. Instead of writing detailed browser automation code, users can describe the desired task and allow the agent to interpret the page structure, interact with elements, and complete... -
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Cradle framework
The Cradle framework is a first attempt at General Computer Control
Cradle is an open-source framework designed to enable AI agents to perform complex computer tasks by interacting with software environments in a way similar to human users. The system introduces the concept of General Computer Control, where AI agents receive screenshots as input and perform actions through simulated keyboard and mouse operations. This approach allows agents to interact with any software interface without relying on specialized APIs or predefined automation scripts. The... -
13
Sparrow
Structured data extraction and instruction calling with ML, LLM
Sparrow is an open-source platform designed to extract structured information from documents, images, and other unstructured data sources using machine learning and large language models. The system focuses on transforming complex documents such as invoices, receipts, forms, and scanned pages into structured formats like JSON that can be processed by downstream applications. It combines several components, including OCR pipelines, vision-language models, and LLM-based reasoning modules to... -
14
Sandstorm
One API call, pull Claude agent, completely sandboxed
Sandstorm is an open-source project that wraps a powerful Claude-based AI agent within a completely sandboxed, ephemeral API service designed to make agentic AI workflows easy to deploy and scale without infrastructure complexity. The core idea is to provide “one API call” access to a robust Claude agent loop that runs inside a secure sandbox, so you can upload files, connect tools, and run long-running tasks — all managed behind a simple REST-style interface that disappears when the work is... -
15
LLM TLDR
95% token savings. 155x faster queries. 16 languages
LLM TLDR is a tool that leverages large language models (LLMs) to generate concise, coherent summaries (TL;DRs) of long documents, articles, or text files, helping users quickly understand large amounts of content without reading every word. It integrates with LLM APIs to handle input texts of varying lengths and complexity, applying techniques like chunking, context management, and multi-pass summarization to preserve accuracy even when the source is very large. The system supports both... -
16
4M
4M: Massively Multimodal Masked Modeling
4M is a training framework for “any-to-any” vision foundation models that uses tokenization and masking to scale across many modalities and tasks. The same model family can classify, segment, detect, caption, and even generate images, with a single interface for both discriminative and generative use. The repository releases code and models for multiple variants (e.g., 4M-7 and 4M-21), emphasizing transfer to unseen tasks and modalities. Training/inference configs and issues discuss things... -
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OpenCompass
OpenCompass is an LLM evaluation platform
Just like a compass guides us on our journey, OpenCompass will guide you through the complex landscape of evaluating large language models. With its powerful algorithms and intuitive interface, OpenCompass makes it easy to assess the quality and effectiveness of your NLP models. OpenCompass is a one-stop platform for large model evaluation, aiming to provide a fair, open, and reproducible benchmark for large model evaluation. Pre-support for 20+ HuggingFace and API models, a model evaluation... -
18
AIDE ML
AI-Driven Exploration in the Space of Code
...The project implements the AIDE algorithm, which uses a tree-search strategy guided by large language models to iteratively generate, evaluate, and refine code. Instead of relying on manual experimentation, the agent autonomously drafts machine learning pipelines, debugs errors, and benchmarks performance against user-defined evaluation metrics. The system repeatedly improves its generated code by exploring different implementation paths and selecting the best-performing solutions. AIDE ML is packaged as a Python toolkit with built-in utilities such as command-line tools, configuration presets, and visualization interfaces that allow researchers to observe how the search process evolves. ... -
19
ktrain
ktrain is a Python library that makes deep learning AI more accessible
ktrain is a Python library that makes deep learning and AI more accessible and easier to apply. ktrain is a lightweight wrapper for the deep learning library TensorFlow Keras (and other libraries) to help build, train, and deploy neural networks and other machine learning models. Inspired by ML framework extensions like fastai and ludwig, ktrain is designed to make deep learning and AI more accessible and easier to apply for both newcomers and experienced practitioners. With only a few lines... -
20
Dendrite
Tools to build web AI agents that can authenticate
Dendrite Python SDK is a toolkit for building web AI agents that can authenticate, interact with, and extract data from any website, facilitating web automation tasks. -
21
Nerfstudio
A collaboration friendly studio for NeRFs
Nerfstudio provides a simple API that allows for a simplified end-to-end process of creating, training, and testing NeRFs. The library supports a more interpretable implementation of NeRFs by modularizing each component. With more modular NeRFs, we hope to create a more user-friendly experience in exploring the technology. This is a contributor-friendly repo with the goal of building a community where users can more easily build upon each other’s contributions. Nerfstudio initially launched... -
22
Skyvern
Automate browser-based workflows with LLMs and Computer Vision
Skyvern uses a combination of computer vision and AI to understand content on a webpage, making it adaptable to any website. Skyvern takes instructions in natural language, allowing it to execute complex objectives with simple commands. Skyvern is an API-first product. Workflows execute in the cloud, allowing it to run hundreds of workflows at the same time. Skyvern's AI decisions come with built-in explanations, providing clear summaries and justifications for every action. Support for... -
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FLAML
A fast library for AutoML and tuning
FLAML is a lightweight Python library that finds accurate machine learning models automatically, efficiently and economically. It frees users from selecting learners and hyperparameters for each learner. For common machine learning tasks like classification and regression, it quickly finds quality models for user-provided data with low computational resources. -
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Integuru v0
The first AI agent that builds permissionless integrations
Integuru is an open-source AI agent designed to automatically create integrations between software platforms by reverse-engineering their internal APIs. Instead of relying on official developer documentation or publicly available APIs, the system analyzes network traffic generated by user interactions within a web application. Developers capture browser requests and authentication data, which the agent then uses to infer the structure of the platform’s internal API endpoints. Based on this... -
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XHS-Downloader
GUI/CLI tool for downloading Xiaohongshu
XHS-Downloader is a GUI/CLI tool for downloading Xiaohongshu (Little Red Book) content without watermarks, supporting both graphics and video posts. Prebuilt packages for Windows and macOS are available from Releases and GitHub Actions artifacts, so most users can run it by unzipping and launching the included executable. The project offers two execution paths—run the compiled app or run from source—and documents default download and configuration paths to simplify first use. Recent releases...
