Search Results for "python programming language" - Page 3
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1155 projects for "python programming language" with 1 filter applied:
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Gen AI apps are built with MongoDB AtlasMongoDB Atlas provides built-in vector search and a flexible document model so developers can build, scale, and run gen AI apps without stitching together multiple databases. From LLM integration to semantic search, Atlas simplifies your AI architecture—and it’s free to get started.
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Siddhi Core Libraries
Stream Processing and Complex Event Processing Engine
... to various endpoints in real time. Agile development experience with SQL-like query language and graphical drag-and-drop editor supporting event simulation. Lightweight runtime that can natively run on Kubernetes, Docker, VM, or bare metal, and embedded in any Java or Python application. Scalable, and highly available distributed event processing on Kubernetes, with NATS Streaming and Siddhi Kubernetes Operator. -
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DeepSeek VL2
Mixture-of-Experts Vision-Language Models for Advanced Multimodal
DeepSeek-VL2 is DeepSeek’s vision + language multimodal model—essentially the next-gen successor to their first vision-language models. It combines image and text inputs into a unified embedding / reasoning space so that you can query with text and image jointly (e.g. “What’s going on in this scene?” or “Generate a caption appropriate to context”). The model supports both image understanding (vision tasks) and multimodal reasoning, and is likely used as a component in agent systems to process... -
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Tencent-Hunyuan-Large
Open-source large language model family from Tencent Hunyuan
Tencent-Hunyuan-Large is the flagship open-source large language model family from Tencent Hunyuan, offering both pre-trained and instruct (fine-tuned) variants. It is designed with long-context capabilities, quantization support, and high performance on benchmarks across general reasoning, mathematics, language understanding, and Chinese / multilingual tasks. It aims to provide competitive capability with efficient deployment and inference. FP8 quantization support to reduce memory usage (~50... -
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Comprehensive Rust
This is the Rust course used by the Android team at Google
Comprehensive Rust is an open source training course developed by Google to provide a complete introduction to the Rust programming language. Originally created for Google engineers, it has since been released publicly for the broader developer community. The course is structured into modular lessons that cover the fundamentals of Rust, including ownership, lifetimes, traits, generics, and error handling, before progressing to advanced topics like concurrency, async programming, unsafe Rust... -
Photo and Video Editing APIs and SDKsUnlock Picsart's full editing suite by embedding our Editor SDK directly into your platform. Offer your users the power of a full design suite without leaving your site.
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towhee
Framework that is dedicated to making neural data processing
Towhee is an open-source machine-learning pipeline that helps you encode your unstructured data into embeddings. You can use our Python API to build a prototype of your pipeline and use Towhee to automatically optimize it for production-ready environments. From images to text to 3D molecular structures, Towhee supports data transformation for nearly 20 different unstructured data modalities. We provide end-to-end pipeline optimizations, covering everything from data decoding/encoding, to model... -
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Google Style Guides
Style guides for Google-originated open source projects
Google Styleguide is a comprehensive collection of coding style guides created and maintained by Google to ensure consistency, readability, and maintainability across its vast array of software projects. These guides define best practices and conventions for writing code in multiple programming languages, from C++ and Python to JavaScript, Go, and Swift. By adhering to these standards, developers can more easily collaborate, review code, and maintain high-quality software across teams and open... -
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Tiktoken
tiktoken is a fast BPE tokeniser for use with OpenAI's models
... names to match different model contexts. It also offers extension mechanisms so that custom encodings can be registered. Internally, it includes the core tokenizer logic (often implemented in Rust or efficient lower-level code), APIs for encoding, decoding, and counting tokens, and binding layers to Python (and sometimes other languages) for easy use. -
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Chonkie
The no-nonsense RAG chunking library
Chonkie is an AI-powered framework designed for building conversational agents and chatbots with natural language understanding and multi-turn conversation support. -
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Claude Code Security Review
An AI-powered security review GitHub Action using Claude
...), generates findings (with explanations, severity, and remediation suggestions), filters false positives using custom prompt logic, and posts comments directly on the PR. It supports configuration inputs (which files/directories to skip, model timeout, whether to comment on the PR, etc). The tool is language-agnostic (it doesn’t need language-specific parsers), uses contextual understanding rather than simplistic rules, and aims to reduce noise with smarter filtering. -
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Catlab.jl
A framework for applied category theory in the Julia language
Catlab.jl is a framework for applied and computational category theory, written in the Julia language. Catlab provides a programming library and interactive interface for applications of category theory to scientific and engineering fields. It emphasizes monoidal categories due to their wide applicability but can support any categorical structure that is formalizable as a generalized algebraic theory. First and foremost, Catlab provides data structures, algorithms, and serialization for applied... -
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DynaMix
A new take on polymorphism
DynaMix (Dynamic Mixins) is an alternative take on object-oriented programming and dynamic polymorphism. It lets users compose and modify polymorphic objects at run time. The main target language is C++, but C is also supported. The library is a means to create a project's architecture rather than achieve its purpose. It helps with extensibility, readability, scalability, and interoperability. It focuses on maximal performance and minimal memory overhead. The library uses the type dynamix... -
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MGIE
Guiding Instruction-based Image Editing via Multimodal Large Language
MGIE—Guiding Instruction-based Image Editing—demonstrates how a multimodal LLM can parse natural-language editing instructions and then drive image transformations accordingly. The project focuses on making edits explainable and controllable: the model interprets text guidance, reasons over image content, and outputs edits aligned with user intent. It’s positioned as an ICLR 2024 Spotlight work, with code and references that show how to connect language planning to concrete image operations... -
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Large Concept Model
Language modeling in a sentence representation space
Large Concept Model is a research codebase centered on concept-centric representation learning at scale, aiming to capture shared structure across many categories and modalities. It organizes training around concepts (rather than just raw labels), encouraging models to understand attributes, relations, and compositional structure that transfer across tasks. The repository provides training loops, data tooling, and evaluation routines to learn and probe these concept embeddings, typically... -
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Sapiens
High-resolution models for human tasks
Sapiens is a research framework from Meta AI focused on embodied intelligence and human-like multimodal learning, aiming to train agents that can perceive, reason, and act in complex environments. It integrates sensory inputs such as vision, audio, and proprioception into a unified learning architecture that allows agents to understand and adapt to their surroundings dynamically. The project emphasizes long-horizon reasoning and cross-modal grounding—connecting language, perception, and action... -
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GPT-2 Output Dataset
Dataset of GPT-2 outputs for research in detection, biases, and more
The GPT-2 Output Dataset is a large collection of model-generated text, released by OpenAI alongside the GPT-2 research paper to study the behaviors and limitations of large language models. It contains 250,000 samples of GPT-2 outputs, generated with different sampling strategies such as top-k truncation, to highlight the diversity and quality of model completions. The dataset also includes corresponding human-written text for comparison, enabling researchers to explore methods... -
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Papers We Love
Papers from the computer science community to read and discuss
... copies with an emoji. The community encourages participation through local meetups, where members gather to discuss and analyze key works spanning topics such as programming languages, distributed systems, and software engineering. In addition to the repository, Papers We Love maintains an active Discord server and YouTube channel, fostering ongoing dialogue around the ideas and applications found in computer science literature. Contributions are welcome. -
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Barfi
A Python visual Flow Based Programming library
A Python visual Flow-Based Programming library that integrates into your existing workflow. Barfi is a Flow-Based Programming environment that provides a graphical programming interface. It is integratable into your existing Python workflows. A schema is built using barfi.Blocks. Then the schema is executed with barfi.ComputeEngine. Each barfi.Block has some properties that enable the FBP and schema building. Firstly, each Block has Input and Output interfaces that link to other Blocks. Each... -
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Rust Course
It has been the world's most popular language for 8 consecutive years
The Rust语言圣经 (Rust Language Bible) is a comprehensive, Chinese-language Rust tutorial that aims to take learners from beginner concepts to advanced mastery. The course is carefully designed with a structured catalog, vivid and approachable language, and an engaging style that avoids the dry and mechanical tone of many technical books. It covers the basics of Rust, such as ownership, borrowing, lifetimes, traits, and generics, but also dives deep into advanced topics like performance... -
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Raglite
RAGLite is a Python toolkit for Retrieval-Augmented Generation
Raglite is a lightweight framework for building Retrieval-Augmented Generation (RAG) pipelines with minimal configuration. It connects large language models to vector databases for context-aware responses, enabling developers to prototype and deploy RAG systems quickly. Raglite focuses on simplicity and modularity for fast experimentation. -
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Awesome Network Analysis
A curated list of awesome network analysis resources
awesome-network-analysis is a curated list of resources focused on network and graph analysis, including libraries, frameworks, visualization tools, datasets, and academic papers. It covers multiple programming languages and domains like sociology, biology, and computer science. This repository serves as a central reference for researchers, analysts, and developers working with network data. -
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ML Ferret
Refer and Ground Anything Anywhere at Any Granularity
Ferret is Apple’s end-to-end multimodal large language model designed specifically for flexible referring and grounding: it can understand references of any granularity (boxes, points, free-form regions) and then ground open-vocabulary descriptions back onto the image. The core idea is a hybrid region representation that mixes discrete coordinates with continuous visual features, so the model can fluidly handle “any-form” referring while maintaining precise spatial localization. The repo... -
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Build your own X
Master programming by recreating your favorite technologies
build-your-own-x is a massive, community-curated roadmap of hands-on tutorials that teach you to re-implement complex systems from scratch—things like databases, compilers, operating systems, interpreters, web servers, neural networks, regex engines, and more. Rather than offering abstract theory, it organizes step-by-step guides by topic and by programming language, so you can pick a project that fits your stack and skill level. The focus is on demystifying internals: you don’t just use a tool... -
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miso
A tasty Haskell front-end framework
... be introduced into the system via the Effect data type. Miso makes heavy use of the GHCJS FFI and therefore has minimal dependencies. Miso can be considered a shallow embedded domain-specific language for modern web programming. -
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DeepSeek VL
Towards Real-World Vision-Language Understanding
DeepSeek-VL is DeepSeek’s initial vision-language model that anchors their multimodal stack. It enables understanding and generation across visual and textual modalities—meaning it can process an image + a prompt, answer questions about images, caption, classify, or reason about visuals in context. The model is likely used internally as the visual encoder backbone for agent use cases, to ground perception in downstream tasks (e.g. answering questions about a screenshot). The repository includes... -
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Standard Webhooks
The Standard Webhooks specification
Standard Webhooks is a community-driven specification and set of open-source tools designed to make webhooks consistent, secure, and interoperable across providers. The project defines strict guidelines covering aspects like signature formats, headers, timestamps, replay protection, and forward compatibility. It includes reference implementations for signature verification and signing across multiple languages such as Python, JavaScript/TypeScript, Go, Rust, Ruby, PHP, C#, Java, and Elixir...
