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Showing 2804 open source projects for "mysql-python"
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AI-powered service management for IT and enterprise teamsGive your IT, operations, and business teams the ability to deliver exceptional services—without the complexity. Maximize operational efficiency with refreshingly simple, AI-powered Freshservice.
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Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
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AWS Toolkit for Visual Studio Code
Local Lambda debug, CodeWhisperer, SAM/CFN syntax, etc.
...Amazon CodeWhisperer provides inline code suggestions using machine learning and natural language processing on the contents of your current file. Supported languages include Java, Python and Javascript. -
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deepclaude
Use Claude Code's agent loop with DeepSeek V4 Pro, OpenRouter & more
deepclaude is a lightweight proxy tool that enables developers to run Claude Code’s autonomous coding agent loop using alternative AI backends like DeepSeek V4 Pro, OpenRouter, or other Anthropic-compatible models. It preserves the full Claude Code experience—including file editing, terminal execution, and multi-step agent workflows—while dramatically reducing operational costs. By swapping out the underlying model instead of the interface, deepclaude delivers the same familiar UX with... -
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SuggestArr
Request recommended movies, TV shows and anime to Jellyseer/Overseer
SuggestArr is an open-source automation platform designed to recommend and automatically request movies, TV shows, and anime based on a user’s viewing history in self-hosted media servers. The project integrates with popular media management systems such as Jellyfin, Plex, and Emby, allowing it to analyze recently watched content and identify similar titles using metadata from the TMDb database. Once potential recommendations are identified, SuggestArr can automatically send download or... -
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AI-Codereview-Gitlab
GitLab automatic code review tool based on large models
AI-Codereview-Gitlab is an open-source automation tool that integrates large language models into the GitLab development workflow to perform automated code reviews. 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... -
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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Sourcery AI Code Review
Instant AI code reviews
Sourcery is an AI-powered code assistant designed to help developers write cleaner, more maintainable Python code by suggesting real-time refactorings, improvements, and best-practice rewrites directly in popular editors and IDEs. Instead of just offering autocomplete, Sourcery analyzes existing functions and code patterns to provide context-aware suggestions that can simplify logic, reduce duplication, improve naming, and correct anti-patterns, helping developers adhere to idiomatic style without manual review. ... -
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1D Visual Tokenization and Generation
This repo contains the code for 1D tokenizer and generator
The 1D Visual Tokenization and Generation project from ByteDance introduces a novel “one-dimensional” tokenizer designed for images: instead of representing images with large grids of 2D tokens (as in many prior generative/image-modeling systems), it compresses images into as few as 32 discrete tokens (or more, optionally) — thereby achieving a very compact, efficient representation that drastically speeds up generation and reconstruction while retaining strong fidelity. This compact... -
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UNO
A Universal Customization Method for Single and Multi Conditioning
UNO is a project by ByteDance introduced in 2025, titled “A Universal Customization Method for Both Single and Multi-Subject Conditioning.” It suggests a framework for image (or more general generative) modeling where the model can be conditioned either on a single subject or multiple subjects — which may correspond to generating or customizing images featuring specific people, styles, or objects, possibly with fine-grained control over subject identity or composition. Because the project is... -
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DreamO
A Unified Framework for Image Customization
DreamO is a unified, open-source framework from ByteDance for advanced image customization and generation that consolidates multiple “image manipulation” tasks into a single system, rather than requiring separate specialized models. Built on a diffusion-transformer (DiT) backbone, it supports a diverse set of tasks — including identity preservation, virtual “try-on” (e.g. clothing, accessories), style transfer, IP adaptation (objects/characters), and layout/condition-aware customizations —... -
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InfiniteYou
Flexible Photo Recrafting While Preserving Your Identity
InfiniteYou is an open-source image-generation and “identity-preserving image editing / generation” framework from ByteDance, designed to generate high-fidelity images that preserve a subject’s identity while allowing flexible editing or re-creation according to textual prompts. Using an architecture built around diffusion transformers (DiTs), InfiniteYou introduces a component called InfuseNet that injects identity features derived from reference images into the generation process — via... -
Fully Managed MySQL, PostgreSQL, and SQL ServerCloud SQL handles your database ops end to end, so you can focus on your app.
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Matrix
Multi-Agent daTa geneRation Infra and eXperimentation framework
Matrix is a distributed, large-scale engine for multi-agent synthetic data generation and experiments: it provides the infrastructure to run thousands of “agentic” workflows concurrently (e.g. multiple LLMs interacting, reasoning, generating content, data-processing pipelines) by leveraging distributed computing (like Ray + cluster management). The idea is to treat data generation as a “data-to-data” transformation: each input item defines a task, and the runtime orchestrates asynchronous,... -
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Dia
A TTS model capable of generating ultra-realistic dialogue
Dia is a neural text-to-speech model designed specifically for generating ultra-realistic dialogue in a single pass. Instead of focusing on isolated sentences or flat narration, it is optimized for conversational audio, complete with natural turn-taking, prosody, and pacing. The model can be conditioned on a reference audio sample, allowing you to control emotion, tone, and other stylistic aspects of the speech. It can also produce nonverbal vocalizations like laughter, coughs, clearing the... -
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Controllable-RAG-Agent
This repository provides an advanced RAG
Controllable-RAG-Agent is an advanced Retrieval-Augmented Generation (RAG) system designed specifically for complex, multi-step question answering over your own documents. Instead of relying solely on simple semantic search, it builds a deterministic control graph that acts as the “brain” of the agent, orchestrating planning, retrieval, reasoning, and verification across many steps. The pipeline ingests PDFs, splits them into chapters, cleans and preprocesses text, then constructs vector... -
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Learn AI Engineering
Learn AI and LLMs from scratch using free resources
Learn AI Engineering is a learning path for AI engineering that consolidates high-quality, free resources across the full stack: math, Python foundations, machine learning, deep learning, LLMs, agents, tooling, and deployment. Rather than a loose bookmark list, it organizes topics into a progression so learners can start from fundamentals and move toward practical, production-oriented skills. It mixes courses, articles, code labs, and videos, emphasizing materials that teach both concepts and hands-on implementation. ... -
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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,... -
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UForm
Multi-Modal Neural Networks for Semantic Search, based on Mid-Fusion
UForm is a Multi-Modal Modal Inference package, designed to encode Multi-Lingual Texts, Images, and, soon, Audio, Video, and Documents, into a shared vector space! It comes with a set of homonymous pre-trained networks available on HuggingFace portal and extends the transfromers package to support Mid-fusion Models. Late-fusion models encode each modality independently, but into one shared vector space. Due to independent encoding late-fusion models are good at capturing coarse-grained... -
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marqo
Tensor search for humans
A tensor-based search and analytics engine that seamlessly integrates with your applications, websites, and workflows. Marqo is a versatile and robust search and analytics engine that can be integrated into any website or application. Due to horizontal scalability, Marqo provides lightning-fast query times, even with millions of documents. Marqo helps you configure deep-learning models like CLIP to pull semantic meaning from images. It can seamlessly handle image-to-image, image-to-text and... -
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DocArray
The data structure for multimodal data
DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer multimodal data with a Pythonic API. Door to multimodal world: super-expressive data structure for representing complicated/mixed/nested text, image, video, audio, 3D mesh data. The foundation data structure of Jina, CLIP-as-service, DALL·E Flow, DiscoArt etc. Data... -
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Tiny CUDA Neural Networks
Lightning fast C++/CUDA neural network framework
...Lower-end cards must reduce the n_neurons parameter or use the CutlassMLP (better compatibility but slower) instead. tiny-cuda-nn comes with a PyTorch extension that allows using the fast MLPs and input encodings from within a Python context. These bindings can be significantly faster than full Python implementations; in particular for the multiresolution hash encoding. -
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PyTorch/XLA
Enabling PyTorch on Google TPU
PyTorch/XLA is a Python package that uses the XLA deep learning compiler to connect the PyTorch deep learning framework and Cloud TPUs. You can try it right now, for free, on a single Cloud TPU with Google Colab, and use it in production and on Cloud TPU Pods with Google Cloud. Take a look at one of our Colab notebooks to quickly try different PyTorch networks running on Cloud TPUs and learn how to use Cloud TPUs as PyTorch devices. -
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Jina
Build cross-modal and multimodal applications on the cloud
Jina is a framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to every developer. Build applications that deliver fresh insights from multiple data types such as text, image, audio, video, 3D mesh, PDF with Jina AI’s DocArray. Polyglot gateway that supports gRPC, Websockets, HTTP,... -
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Smile
Statistical machine intelligence and learning engine
Smile is a fast and comprehensive machine learning engine. With advanced data structures and algorithms, Smile delivers the state-of-art performance. Compared to this third-party benchmark, Smile outperforms R, Python, Spark, H2O, xgboost significantly. Smile is a couple of times faster than the closest competitor. The memory usage is also very efficient. If we can train advanced machine learning models on a PC, why buy a cluster? Write applications quickly in Java, Scala, or any JVM languages. Data scientists and developers can speak the same language now! ... -
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GLM-4.1V
GLM-4.6V/4.5V/4.1V-Thinking, towards versatile multimodal reasoning
GLM-4.1V — often referred to as a smaller / lighter version of the GLM-V family — offers a more resource-efficient option for users who want multimodal capabilities without requiring large compute resources. Though smaller in scale, GLM-4.1V maintains competitive performance, particularly impressive on many benchmarks for models of its size: in fact, on a number of multimodal reasoning and vision-language tasks it outperforms some much larger models from other families. It represents a... -
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GLM-4.5V
GLM-4.6V/4.5V/4.1V-Thinking, towards versatile multimodal reasoning
GLM-4.5V is the preceding iteration in the GLM-V series that laid much of the groundwork for general multimodal reasoning and vision-language understanding. It embodies the design philosophy of mixing visual and textual modalities into a unified model capable of general-purpose reasoning, content understanding, and generation, while already supporting a wide variety of tasks: from image captioning and visual question answering to content recognition, GUI-based agents, video understanding,... -
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Sa2VA
Official Repo For "Sa2VA: Marrying SAM2 with LLaVA
Sa2VA is a cutting-edge open-source multi-modal large language model (MLLM) developed by ByteDance that unifies dense segmentation, visual understanding, and language-based reasoning across both images and videos. It merges the segmentation power of a state-of-the-art video segmentation model (based on SAM‑2) with the vision-language reasoning capabilities of a strong LLM backbone (derived from models like InternVL2.5 / Qwen-VL series), yielding a system that can answer questions about... -
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Trae Agent
LLM-based agent for general purpose software engineering tasks
Trae Agent is an open-source, LLM-based agent system also developed by ByteDance, focused primarily on automating software engineering workflows. It provides a command-line interface (CLI) that accepts natural-language instructions (e.g. “refactor this module,” “write a unit test,” “generate a REST API skeleton”), and then orchestrates tool-based workflows — such as file editing, shell/batch commands, code generation, code formatting or refactoring — to carry out complex engineering tasks....