Search Results for "code snippets"
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17 projects for "code snippets" with 2 filters applied:
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Claude Code
Claude Code is an agentic coding tool that lives in your terminal
Claude Code is an intelligent agentic coding assistant that lives in your terminal and understands your entire codebase. It helps developers code faster by executing routine tasks, explaining complex code snippets, and managing git workflows—all via natural language commands. Claude Code integrates seamlessly into your terminal, IDE, or GitHub by tagging @claude to interact with your code context. -
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ai-cookbook
Examples and tutorials to help developers build AI systems
ai-cookbook is an open-source repository that provides practical tutorials, code examples, and reusable snippets designed to help developers build real-world artificial intelligence applications quickly. The project focuses on delivering hands-on engineering guidance rather than theoretical explanations, allowing developers to copy, adapt, and integrate working code directly into their own systems. The repository contains examples that demonstrate how to build AI workflows using modern tools such as large language models, autonomous agents, and external APIs. ... -
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DeepSeek Coder
DeepSeek Coder: Let the Code Write Itself
DeepSeek-Coder is a series of code-specialized language models designed to generate, complete, and infill code (and mixed code + natural language) with high fluency in both English and Chinese. The models are trained from scratch on a massive corpus (~2 trillion tokens), of which about 87% is code and 13% is natural language. This dataset covers project-level code structure (not just line-by-line snippets), using a large context window (e.g. 16K) and a secondary fill-in-the-blank objective to encourage better contextual completions and infilling. ... -
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Generative AI Docs
Documentation for Google's Gen AI site - including Gemini API & Gemma
...It contains guides, API references, and examples for developers building applications using Google’s large language models, text-to-image models, embeddings, and multimodal capabilities. The repository includes markdown source files that power the Google AI developer documentation site, as well as sample code snippets in Python, JavaScript, and other languages that demonstrate how to use Google’s Generative AI SDKs and REST APIs effectively. -
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Fragments by E2B
Open source template for AI-powered code generation apps w/ sandboxes
Fragments is an open source template designed for building applications where artificial intelligence generates and executes code directly from natural language prompts. It provides a ready-to-use web interface where users can chat with AI models to create code snippets, applications, or scripts in various programming environments. Generated code can be executed safely in isolated sandbox environments using the E2B SDK, which helps protect the host system while running AI-produced programs. ... -
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OpenAI Quickstart Node
Node.js example app from the OpenAI API quickstart tutorial
...The project is a practical starting point for building AI-powered applications, serving as a foundation for experimentation and integration into larger projects. It simplifies onboarding by offering step-by-step setup instructions and ready-to-use code snippets that can be adapted for custom needs. -
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Hollama
A minimal LLM chat app that runs entirely in your browser
...Hollama supports both text-based and multimodal interactions, allowing users to work with models that process images as well as text. The interface includes features for editing prompts, retrying responses, copying generated code snippets, and storing conversation history locally within the browser. Mathematical expressions can be rendered using KaTeX, and Markdown formatting allows code blocks and structured outputs to appear clearly within conversations. -
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OpenAI Cookbook
Examples and guides for using the OpenAI API
openai-cookbook is a repository containing example code, tutorials, and guidance for how to build real applications on top of the OpenAI API. It covers a wide range of use cases: prompt engineering, embeddings and semantic search, fine-tuning, agent architectures, function calling, working with images, chat workflows, and more. The content is primarily in Python (notebooks, scripts), but the conceptual guidance is applicable across languages. -
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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. -
Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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Adrenaline
AI tool that answers and explains programming questions interactively
...Adrenaline aims to respond to a wide range of technical queries, including those about GitHub repositories, documentation sources, and code snippets. It enhances responses by performing multi-step reasoning, allowing it to tackle more complex or layered programming questions effectively. Additionally, it can generate diagrams to visually explain concepts, improving comprehension for users. -
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Practical Machine Learning with Python
Master the essential skills needed to recognize and solve problems
Practical Machine Learning with Python is a comprehensive repository built to accompany a project-centered guide for applying machine learning techniques to real-world problems using Python’s mature data science ecosystem. It centralizes example code, datasets, model pipelines, and explanatory notebooks that teach users how to approach problems from data ingestion and cleaning all the way through feature engineering, model selection, evaluation, tuning, and production-ready deployment patterns. The repository emphasizes end-to-end workflows rather than isolated code snippets, showing how to handle common challenges like class imbalance, overfitting, hyperparameter optimization, and interpretability. ... -
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Visual Studio Code client for Tabnine
Visual Studio Code client for Tabnine
This extension is for Tabnine’s Starter (free), Pro and Enterprise SaaS users only. Tabnine Enterprise users with the self-hosted setup should use the Tabnine Enterprise extension in the VSCode Marketplace. Tabnine is an AI code assistant that makes you a better developer. Tabnine will increase your development velocity with real-time code completions, chat, and code generation in all the most popular coding languages and IDEs. Whether you call it IntelliSense, intelliCode, autocomplete, AI-assisted code completion, AI-powered code completion, AI copilot, AI code snippets, code suggestion, code prediction, code hinting, content assist, unit test generation or documentation generation, using Tabnine can massively impact your coding velocity, significantly cutting down your coding time. -
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CodeSearchNet
Datasets, tools, and benchmarks for representation learning of code
...These pairs allow machine learning models to learn relationships between natural language descriptions and programming code. The dataset currently covers several widely used programming languages, including Python, JavaScript, Ruby, Go, Java, and PHP. In addition to the dataset itself, the repository includes baseline models, evaluation tools, and instructions for building code retrieval systems that can map user queries to relevant code snippets. -
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An excercise in construction of self-modifying, self-exploring reflective system. The approach is to use autonomous code snippets inspectable and mutable by other code snippets, plus a hierarchy of their abstractions.
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ReinventCommunity
Jupyter Notebook tutorials for REINVENT 3.2
This repository is a collection of useful jupyter notebooks, code snippets and example JSON files illustrating the use of Reinvent 3.2. -
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Activity Recognition
Resources about activity recognition
This repository is a curated collection of resources, papers, code, and summaries relating to human activity recognition/behavior recognition. It is not a single integrated software package but rather a knowledge base organizing feature extraction methods, deep learning approaches, transfer learning strategies, datasets, and representative research in behavior recognition. The repository includes links to code in MATLAB, Python, summaries of algorithms, datasets, and relevant research... -
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Repl.it
Online REPL for 15+ languages
This repository preserves an early open-source snapshot of the service that became Replit, a platform for writing and running code directly in the browser. The project’s core idea is instant, zero-setup programming: open a page, pick a language, type, and run—no local installs or environment wrangling. It combines an in-browser editor with a runnable backend or sandbox so code can execute safely and return output in seconds. Sharing and collaboration are first-class: code can be saved,...
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