Search Results for "code framework" - Page 3
Sort By:
Showing 376 open source projects for "code framework"
View related business solutions-
$300 Free Credits to Build on Google CloudPut your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
-
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
-
1
autoresearch for AMD
AI agents running research on single-GPU nanochat training
...During each iteration, the agent edits the training code, runs an experiment within a fixed time budget, evaluates performance metrics, and decides whether to retain or discard the changes. This loop allows the system to explore a wide range of architectural and hyperparameter configurations without human intervention. The framework emphasizes simplicity and reproducibility, ensuring that experiments are comparable and results are traceable over time. -
2
Enferno
Modern Flask framework optimized for AI-assisted development
Enferno is a framework for building developer-first cloud backends using PostgreSQL and TypeScript. It offers primitives for defining data models, APIs, and access rules directly in code, enabling quick iteration and deployment. Enferno is designed to accelerate SaaS and internal tool development by combining the benefits of traditional backends with developer ergonomics. -
3
Scrapling
An adaptive Web Scraping framework
Scrapling is an adaptive web scraping framework designed to handle everything from a single HTTP request to large-scale, concurrent crawls. Built for modern websites, it intelligently adapts to structural changes by automatically relocating elements when page layouts update. The framework includes advanced fetchers capable of bypassing anti-bot protections such as Cloudflare Turnstile using stealth and browser automation techniques. Its powerful spider system supports multi-session crawling,... -
4
BlackSheep
Fast ASGI web framework for Python
BlackSheep is an asynchronous web framework to build event-based web applications with Python. A rich code API, based on dependency injection and inspired by Flask and ASP.NET Core. A typing-friendly codebase, which enables a comfortable development experience thanks to hints when coding with IDEs. Built-in generation of OpenAPI Documentation, supporting version 3, YAML, and JSON. -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
-
5
AI Berkshire
AI-era Berkshire: a value investing research framework
AI Berkshire is an AI-assisted value investing research framework designed for Claude Code and Codex workflows. It turns the investment methods of Warren Buffett, Charlie Munger, Duan Yongping, and Li Lu into structured research agents. The project is meant to improve research depth, decision discipline, and analytical consistency compared with asking a general AI model for a one-off stock opinion. -
6
VidGear
A High-performance cross-platform Video Processing Python framework
VidGear is a high-performance Python framework that provides a unified and extensible solution for building real-time video processing applications. It acts as an abstraction layer over powerful multimedia libraries such as OpenCV, FFmpeg, and ZeroMQ, simplifying complex workflows into concise and efficient APIs. The framework is built around modular components called “gears,” each responsible for tasks such as video capture, streaming, encoding, and network transmission. ... -
7
Checkov
Prevent cloud misconfigurations during build-time for Terraform
...Scan cloud resources in build-time for misconfigured attributes with a simple Python policy-as-code framework. Analyze relationships between cloud resources using Checkov’s graph-based YAML policies. Execute, test, and modify runner parameters in the context of a subject repository CI/CD and version control integrations. -
8
PyTorch Lightning
The lightweight PyTorch wrapper for high-performance AI research
Scale your models, not your boilerplate with PyTorch Lightning! PyTorch Lightning is the ultimate PyTorch research framework that allows you to focus on the research while it takes care of everything else. It's designed to decouple the science from the engineering in your PyTorch code, simplifying complex network coding and giving you maximum flexibility. PyTorch Lightning can be used for just about any type of research, and was built for the fast inference needed in AI research and production. ... -
9
Unsloth Studio
Unified web UI for training and running open models locally
...It allows users to work with a wide range of models for text, audio, vision, embeddings, and more without relying heavily on cloud infrastructure. Built on top of the Unsloth framework, it focuses on high-performance training with reduced VRAM usage and faster speeds compared to traditional methods. The platform supports fine-tuning, pretraining, and reinforcement learning workflows, making it suitable for both experimentation and production use. Users can interact with models through chat, upload files like PDFs or images, and execute code within the environment to improve outputs. ... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
10
SentenceTransformers
Multilingual sentence & image embeddings with BERT
...This can be useful for semantic textual similar, semantic search, or paraphrase mining. The framework is based on PyTorch and Transformers and offers a large collection of pre-trained models tuned for various tasks. Further, it is easy to fine-tune your own models. Our models are evaluated extensively and achieve state-of-the-art performance on various tasks. Further, the code is tuned to provide the highest possible speed. -
11
Gigi
Framework for rapid prototyping and development of real-time rendering
Gigi is software designed for rapid prototyping and rapid development of real-time rendering techniques. It is meant for use by professionals, researchers, students, and hobbyists. The goal is to allow work at the speed of thought, and then easily use what was created in real applications using various APIs or engines. Gigi is being actively used and developed but is young software. You may hit bugs or missing features. Please report these so we can improve Gigi and push forward in the most... -
12
Dash
Build beautiful web-based analytic apps, no JavaScript required
Dash is a Python framework for building beautiful analytical web applications without any JavaScript. Built on top of Plotly.js, React and Flask, Dash easily achieves what an entire team of designers and engineers normally would. It ties modern UI controls and displays such as dropdown menus, sliders and graphs directly to your analytical Python code, and creates exceptional, interactive analytics apps. -
13
AI-DLC
AI-Driven Life Cycle (AI-DLC) adaptive workflow steering rules for AI
AI-DLC is an open-source workflow framework from AWS Labs designed to structure software development around AI-assisted engineering processes. The project promotes an “AI-Driven Life Cycle” methodology where coding assistants, IDE agents, and automation systems participate directly in planning, implementation, testing, and operational workflows. Rather than focusing on a single model or IDE, the framework provides reusable rules, templates, and orchestration patterns compatible with tools such as Amazon Q Developer, Claude Code, Cursor, GitHub Copilot, and Cline. ... -
14
Agent S
Agent S: an open agentic framework that uses computers like a human
...It supports flexible deployment via CLI, SDK, or cloud, and integrates with multiple model providers including OpenAI, Anthropic, Gemini, Azure, and Hugging Face endpoints. With optional local code execution, reflection mechanisms, and compositional planning, Agent S provides a scalable and research-driven framework for building advanced computer-use agents. -
15
AutoTrain Advanced
Faster and easier training and deployments
AutoTrain Advanced is an open-source machine learning training framework developed by Hugging Face that simplifies the process of training and fine-tuning state-of-the-art AI models. The project provides a no-code and low-code interface that allows users to train models using custom datasets without needing extensive expertise in machine learning engineering. It supports a wide range of tasks including text classification, sequence-to-sequence modeling, token classification, sentence embedding training, and large language model fine-tuning. ... -
16
Phone Harness
Let your agent control your phone
...It requires no jailbreak, Xcode project, WebDriverAgent, or custom software installed on the phone. Screenshots of the mirrored window provide visual input, while Apple's Vision framework extracts visible text and tap-ready coordinates. macOS CGEvents supply taps, long presses, drags, scrolling, keyboard input, and iPhone Mirroring shortcuts. After performing an action, the agent captures the screen again to verify the actual resulting state. The harness can be installed as an agent skill for systems such as Claude Code or Codex. ... -
17
Spirit
Spirit is a modern Python based forum built on top of Django framework
...Spirit automatically saves your unfinished comments so you can complete them later. Highlight any comment you want with a "like." Spirit is mobile-first, it's meant to work in the same way in any given device. The code has been written on python employing django's framework and it can be easily integrated to pre-existing projects. Spirit is part of the open source initiative, and it's a project released under the terms of the MIT license. -
18
Lagent
A lightweight framework for building LLM-based agents
Lagent is a lightweight open-source framework designed to help developers build autonomous agents powered by large language models. The framework provides tools and abstractions that allow language models to interact with external tools, execute tasks, and perform multi-step reasoning processes. Instead of using LLMs only for text generation, Lagent enables developers to transform models into agents capable of performing actions such as retrieving data, executing code, or interacting with APIs. ... -
19
Lingvo
Framework for building neural networks
Lingvo is a TensorFlow based framework focused on building and training sequence models, especially for language and speech tasks. It was originally developed for internal research and later open sourced to support reproducible experiments and shared model implementations. The framework provides a structured way to define models, input pipelines, and training configurations using a common interface for layers, which encourages reuse across different tasks. It has been used to implement state... -
20
Connexion
Swagger/OpenAPI First framework for Python on top of Flask
Connexion is a framework on top of Flask that automagically handles HTTP requests defined using OpenAPI (formerly known as Swagger), supporting both v2.0 and v3.0 of the specification. Connexion allows you to write these specifications, then maps the endpoints to your Python functions. This is what makes it unique from other tools that generate the specification based on your Python code. -
21
Buildbot
Python-based continuous integration testing framework
Buildbot is an open-source framework for automating software build, test, and release processes. At its core, Buildbot is a job scheduling system: it queues jobs, executes the jobs when the required resources are available, and reports the results. Your Buildbot installation has one or more masters and a collection of workers. The masters monitor source-code repositories for changes, coordinate the activities of the workers, and report results to users and developers. ... -
22
UltraRAG
Less Code, Lower Barrier, Faster Deployment
UltraRAG 2.0 is a low-code, MCP-enabled RAG framework that aims to lower the barrier to building complex retrieval pipelines for research and production. It provides end-to-end recipes—from encoding and indexing corpora to deploying retrievers and LLMs—so users can reproduce baselines and iterate rapidly. The toolkit comes with built-in support for popular RAG datasets, large corpora, and canonical baselines, plus documentation that walks from “quick start” to debugging and case analysis. ... -
23
embedchain
Framework to easily create LLM powered bots over any dataset
Embedchain is a framework to easily create LLM-powered bots over any dataset. If you want a javascript version, check out embedchain-js. Embedchain empowers you to create chatbot models similar to ChatGPT, using your own evolving dataset. Start building LLM powered bots under 30 seconds. -
24
any-llm
Communicate with an LLM provider using a single interface
any-llm is a unified SDK and platform developed by Mozilla AI that allows developers to interact with multiple large language model providers through a single, consistent interface. Instead of rewriting code for each provider, developers can switch between services like OpenAI, Anthropic, Mistral, and Ollama simply by changing configuration parameters. The project is designed to be framework-agnostic, making it easy to integrate into scripts, applications, or production systems without being tied to a specific stack. It includes a core SDK for direct usage as well as an optional gateway layer that adds enterprise features such as budget management, API key control, usage analytics, and multi-tenant support. ... -
25
Axolotl
Go ahead and axolotl questions
Axolotl is a powerful and flexible framework for fine-tuning large language models on custom datasets. Built for researchers and developers, Axolotl simplifies the process of adapting LLMs for specific tasks, including chat, code generation, and instruction following. It supports a wide variety of model architectures and offers out-of-the-box optimization strategies for efficient training.
