Search Results for "code::block" - Page 8
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Showing 767 open source projects for "code::block"
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The full-stack observability platform that protects your dataLayer, tags and conversion dataCode-Cube.io detects issues instantly, alerts you in real time and helps you resolve them fast. No manual QA. No unreliable data. Just data you can trust and act on.
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Iris Powered By Generali - Iris puts your customer in control of their identity.Iris Identity Protection API sends identity monitoring and alerts data into your existing digital environment – an ideal solution for businesses that are looking to offer their customers identity protection services without having to build a new product or app from scratch.
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pyttsx3
Offline Text To Speech synthesis for python
...On Windows it uses SAPI5, on Linux it typically uses eSpeak or eSpeak-NG, and on macOS it can use NSSpeechSynthesizer or AVSpeechSynthesizer, giving it broad cross-platform compatibility. The library exposes a simple but flexible API for controlling voice selection, speaking rate, volume, and other synthesis parameters from Python code. It supports both a high-level speak convenience function and a lower-level engine object with event hooks, queuing, and saving output to audio files. The repository includes examples and documentation that show how to adjust properties dynamically, persist synthesized output, and integrate pyttsx3 into GUIs or background services. -
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Vulnhuntr
AI tool for detecting complex vulnerabilities in Python codebases
Vulnhuntr is an open source security tool that uses large language models to analyze codebases and identify remotely exploitable vulnerabilities. It focuses on Python projects and applies static code analysis combined with LLM reasoning to trace how user input flows through an application. Instead of scanning entire repositories at once, it builds call chains step by step, allowing deeper inspection of complex, multi-stage issues that traditional tools may miss. Vulnhuntr can generate detailed findings, including vulnerability explanations and potential exploit paths, helping developers and security teams understand risks faster. ... -
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DeepAnalyze
Autonomous LLM agent for end-to-end data science workflows
...DeepAnalyze is capable of conducting open-ended data research across multiple data formats such as structured tables, semi-structured files, and unstructured text, enabling flexible and comprehensive analysis workflows. It integrates execution-based reasoning by generating and running code as part of its analysis process, allowing it to iteratively refine results and produce more accurate outputs. DeepAnalyze provides multiple interaction interfaces, including a web-based UI, a command-line interface, and a Jupyter-style notebook environment for interactive workflows. -
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LaVague
Framework for building AI agents that automate complex web tasks
...LaVague is centered around a World Model that analyzes the current webpage state and determines the next set of instructions, combined with an Action Engine that converts those instructions into executable automation code. It can use browser automation tools such as Selenium or Playwright to interact with websites programmatically. Developers can integrate various language models and configure the agent’s reasoning and execution behavior to suit different automation scenarios. -
AestheticsPro Medical Spa SoftwareAestheticsPro is the most complete Aesthetics Software on the market today. HIPAA Cloud Compliant with electronic charting, integrated POS, targeted marketing and results driven reporting; AestheticsPro delivers the tools you need to manage your medical spa business. It is our mission To Provide an All-in-One Cutting Edge Software to the Aesthetics Industry.
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Context Engineering Template
Context engineering is the new vibe coding
...The repository provides templates such as CLAUDE.md for defining global project rules, INITIAL.md for feature requests, and folders for examples, PRPs, validation scripts, and settings to support systematic prompt generation and execution with tools like Claude Code. By using this template, teams can ensure consistency across AI outputs, reduce errors that stem from contextual misunderstandings, and build reusable patterns. -
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DINOv2
PyTorch code and models for the DINOv2 self-supervised learning
...The core promise is that a single pretrained backbone can transfer well to many downstream tasks—from linear probing on classification to retrieval, detection, and segmentation—often requiring little or no fine-tuning. The repository includes code for training, evaluating, and feature extraction, with utilities to run k-NN or linear evaluation baselines to assess representation quality. Pretrained checkpoints cover multiple model sizes so practitioners can trade accuracy for speed and memory depending on their deployment constraints. -
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CodiumAI Cover-Agent
CodiumAI Cover-Agent: An AI-Powered Tool for Automated Test Generation
CodiumAI Cover Agent aims to help efficiently increasing code coverage, by automatically generating qualified tests to enhance existing test suites. -
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Marvin
A batteries-included library for building AI-powered software
...Marvin's job is to integrate AI directly into your codebase by making it look and feel like any other function. Marvin introduces a new concept called AI Functions. These functions differ from conventional ones in that they don’t rely on source code, but instead generate their outputs on-demand through AI. With AI functions, you don't have to write complex code for tasks like extracting entities from web pages, scoring sentiment, or categorizing items in your database. Just describe your needs, call the function, and you're done. AI functions work with native data types, so you can seamlessly integrate them into any codebase and chain them into sophisticated pipelines. ... -
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BioEmu
Inference code for scalable emulation of protein equilibrium ensembles
Biomolecular Emulator (BioEmu for short) is a model that samples from the approximated equilibrium distribution of structures for a protein monomer, given its amino acid sequence. By default, unphysical structures (steric clashes or chain discontinuities) will be filtered out, so you will typically get fewer samples in the output than requested. The difference can be very large if your protein has large disordered regions, which are very likely to produce clashes. BioEmu outputs structures... -
Award-Winning Medical Office Software Designed for Your SpecialtyRXNT is an ambulatory healthcare technology pioneer that empowers medical practices and healthcare organizations to succeed and scale through innovative, data-backed, AI-powered software.
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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. -
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Groq Python
The official Python Library for the Groq API
Groq Python is the official Python SDK for the Groq REST API, giving Python developers straightforward access to Groq’s LLM, chat, audio, and other AI services. Through this library, you can call Groq’s models from Python code — for example to request chat completions, code generation, transcription, or any supported endpoint — using idiomatic Python syntax. The SDK handles authentication (via environment variable or parameter), defines proper type-safe request/response data types, and supports both synchronous and asynchronous usage patterns depending on your application needs. ... -
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GLM-OCR
Accurate × Fast × Comprehensive
...The model’s multimodal capabilities allow it to reason across image and text content holistically, capturing structured and unstructured information from pages that include dense tables, seals, code snippets, and varied document graphics. GLM-OCR integrates a comprehensive SDK and inference toolchain that makes it easy for developers to install, invoke, and embed into production pipelines with simple commands or APIs. -
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graphify
AI coding assistant skill (Claude Code, Codex, OpenCode, OpenClaw)
graphify is a data visualization and transformation tool designed to convert structured or semi-structured data into graph-based representations, enabling better understanding of relationships and dependencies. It focuses on building visual models such as nodes and edges that represent entities and their connections, making complex datasets easier to interpret. The system likely supports dynamic updates, allowing graphs to evolve as data changes or new inputs are introduced. It is... -
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Microsandbox
Secure local-first microVM sandbox for running untrusted code fast
...It provides a local-first and self-hosted approach, allowing users to maintain full ownership of their execution environment without depending on external cloud services. Microsandbox is particularly geared toward AI agent workflows, offering integrations that enable automated systems to safely run generated code and commands. It also supports standard container images, making it compatible with existing development ecosystems and tooling. -
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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. -
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MLE-bench
AI multi-agent framework for automating data-driven R&D workflows
...RD-Agent can analyze data, generate experimental code, run evaluations, and learn from outcomes to improve future iterations. -
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Machine learning algorithms
Minimal and clean examples of machine learning algorithms
...The repository includes implementations of both supervised and unsupervised learning techniques, along with dimensionality reduction and clustering methods. Many of the algorithms are written in a simplified style that prioritizes clarity and educational value over production-level optimization. Because the code is compact and easy to follow, it is often used as a learning resource by developers who want to understand how machine learning algorithms are constructed. -
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Transfer Learning Repo
Transfer learning / domain adaptation / domain generalization
...In addition to academic references, the project provides practical code implementations of many transfer learning algorithms so that researchers can reproduce experiments or build their own applications. The repository also catalogs well-known scholars, research laboratories, and datasets relevant to transfer learning studies. -
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LongBench
LongBench v2 and LongBench (ACL 25'&24')
...Traditional language model benchmarks typically evaluate tasks involving relatively short inputs, which does not reflect many real-world applications such as analyzing large documents or entire code repositories. LongBench addresses this gap by providing datasets that require models to process and reason over long sequences of text across multiple tasks. The benchmark includes multiple categories such as single-document question answering, multi-document reasoning, summarization, long dialogue understanding, and code analysis. ... -
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vim-ai
AI-powered code assistant for Vim. OpenAI and ChatGPT plugin for Vim
vim-ai is an AI-powered assistant plugin for Vim and Neovim that brings language-model features directly into the editor. It allows users to generate code or text, edit selections in place, and carry on interactive chat-style conversations without leaving the terminal editing environment. The plugin is built around OpenAI-compatible APIs, which means it can work not only with OpenAI itself but also with compatible proxies and alternative providers. Its command set covers text completion, editing, chat continuation, image generation, and debugging utilities, making it more versatile than a narrow autocomplete add-on. ... -
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DocETL
A system for agentic LLM-powered data processing and ETL
...Instead of relying on single prompts or ad-hoc scripts, DocETL provides a declarative pipeline framework that breaks complex document analysis tasks into manageable operations that can be optimized and orchestrated automatically. Pipelines are typically defined using a low-code YAML interface, giving users full control over prompts and processing steps while still simplifying workflow creation. -
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Unstract
No-code LLM Platform to launch APIs and ETL Pipelines
Unstract is a powerful open-source, no-code platform built to automate the extraction and structuring of unstructured documents using large language models and flexible workflows, enabling developers and data teams to turn messy files into organized JSON content without complex coding. It integrates a visual Prompt Studio environment where users can iteratively design extraction schemas, compare outputs from different models, and monitor costs and accuracy side by side, making it easier to refine prompts and extraction logic before deploying at scale. ... -
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AWS Agent Skills
AWS Skills for Agents
...The skills cover critical AWS services such as IAM, Lambda, DynamoDB, S3, API Gateway, EKS, and many more, letting agents offer actionable advice on infrastructure as code, debugging, security configurations, and architectural workflows. Skills are kept up to date with weekly documentation checks, ensuring they reflect current AWS patterns and service changes. -
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FramePack
Lets make video diffusion practical
FramePack explores compact representations for sequences of image frames, targeting tasks where many near-duplicate frames carry redundant information. The idea is to “pack” frames by detecting shared structure and storing differences efficiently, which can accelerate training or inference on video-like data. By reducing I/O and memory bandwidth, datasets become lighter to load while models still see the essential temporal variation. The repository demonstrates both packing and unpacking... -
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UpTrain
Your open-source LLM evaluation toolkit
...By quantifying degree of hallucination and quality of retrieved context, UpTrain helps to detect responses with low factual accuracy and prevent them before serving to the end-users. Unleash unparalleled power with a single line of code and tailor every detail as per as your use-case.
