Search Results for "forum source code" - Page 27
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Showing 1524 open source projects for "forum source code"
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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.
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Better Chatbot
Just a Better Chatbot. Powered by MCP Client & Workflows
Better‑chatbot is an AI chatbot framework powered by MCP protocols and workflows, allowing developers to deploy and integrate AI-powered chat systems with ease. Integrates all major LLMs: OpenAI, Anthropic, Google, xAI, Ollama, and more. MCP protocol, web search, JS/Python code execution, data visualization. Custom agents, visual workflows, artifact generation. Custom agents, visual workflows, artifact generation. Realtime voice chat with full MCP tool integration. -
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Guardrails
Adding guardrails to large language models
Guardrails is a Python package that lets a user add structure, type and quality guarantees to the outputs of large language models (LLMs). At the heart of Guardrails is the rail spec. rail is intended to be a language-agnostic, human-readable format for specifying structure and type information, validators and corrective actions over LLM outputs. We create a RAIL spec to describe the expected structure and types of the LLM output, the quality criteria for the output to be considered valid,... -
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Skills For Real Engineers
Skills for Real Engineers. Straight from my .claude directory
Skills For Real Engineers is a curated collection of modular AI “skills” designed to improve how developers interact with coding agents by enforcing structured engineering workflows. Each skill is a small, focused instruction set that guides an AI through tasks such as planning, refactoring, testing, or architectural analysis. Instead of relying on vague prompts, the system encodes repeatable processes that ensure consistent and higher-quality outputs. The repository includes tools for... -
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Vision Transformer Pytorch
Implementation of Vision Transformer, a simple way to achieve SOTA
This repository provides a from-scratch, minimalist implementation of the Vision Transformer (ViT) in PyTorch, focusing on the core architectural pieces needed for image classification. It breaks down the model into patch embedding, positional encoding, multi-head self-attention, feed-forward blocks, and a classification head so you can understand each component in isolation. The code is intentionally compact and modular, which makes it easy to tinker with hyperparameters, depth, width, and... -
Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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Segment Anything
Provides code for running inference with the SegmentAnything Model
Segment Anything (SAM) is a foundation model for image segmentation that’s designed to work “out of the box” on a wide variety of images without task-specific fine-tuning. It’s a promptable segmenter: you guide it with points, boxes, or rough masks, and it predicts high-quality object masks consistent with the prompt. The architecture separates a powerful image encoder from a lightweight mask decoder, so the heavy vision work can be computed once and the interactive part stays fast. A... -
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PML
The easiest way to use deep metric learning in your application
This library contains 9 modules, each of which can be used independently within your existing codebase, or combined together for a complete train/test workflow. To compute the loss in your training loop, pass in the embeddings computed by your model, and the corresponding labels. The embeddings should have size (N, embedding_size), and the labels should have size (N), where N is the batch size. The TripletMarginLoss computes all possible triplets within the batch, based on the labels you... -
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TensorFlow Model Garden
Models and examples built with TensorFlow
The TensorFlow Model Garden is a repository with a number of different implementations of state-of-the-art (SOTA) models and modeling solutions for TensorFlow users. We aim to demonstrate the best practices for modeling so that TensorFlow users can take full advantage of TensorFlow for their research and product development. To improve the transparency and reproducibility of our models, training logs on TensorBoard.dev are also provided for models to the extent possible though not all models... -
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DSH Web UI
Plugin and skin collection for DeepSeek Harness (DSH) Web UI
DSH Web UI is a modular plugin and skin collection that expands the DeepSeek Harness browser interface into a broader development workspace. Its components attach through the official DSH profile mechanism without modifying the Harness source code. Users can add a task board that executes real agent sessions and supports scheduled jobs through cron expressions. A Git graph visualizes branches and commit history, while additional panels provide files, editing, terminals, Git operations, and browser access. Remote access lets paired phones or computers control sessions, models, permissions, and conversations with live synchronization. ... -
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Search with Lepton
Lightweight demo to build a conversational AI search engine quickly
Search with Lepton is an open source demonstration project that shows how to build a conversational search engine using the Lepton AI framework. It combines traditional web search with large language models to provide natural language answers to user queries. It retrieves information from supported search engines and uses that context to generate responses through a retrieval-augmented generation approach. -
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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WebLLM
Bringing large-language models and chat to web browsers
WebLLM is a modular, customizable javascript package that directly brings language model chats directly onto web browsers with hardware acceleration. Everything runs inside the browser with no server support and is accelerated with WebGPU. We can bring a lot of fun opportunities to build AI assistants for everyone and enable privacy while enjoying GPU acceleration. WebLLM offers a minimalist and modular interface to access the chatbot in the browser. The WebLLM package itself does not come... -
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OpenCLIP
An open source implementation of CLIP
The goal of this repository is to enable training models with contrastive image-text supervision and to investigate their properties such as robustness to distribution shift. Our starting point is an implementation of CLIP that matches the accuracy of the original CLIP models when trained on the same dataset. Specifically, a ResNet-50 model trained with our codebase on OpenAI's 15 million image subset of YFCC achieves 32.7% top-1 accuracy on ImageNet. OpenAI's CLIP model reaches 31.3% when... -
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Telegram.Bot
.NET Client for Telegram Bot API
Telegram.Bot is the most popular .NET Client for Telegram Bot API. The Bot API is an HTTP-based interface created for developers keen on building bots for Telegram. Check Bots: An introduction for developers to understand what a Telegram bot is and what it can do. All Bot API methods are already documented by Telegram but this book covers all you need to know to create a chatbot in .NET. There are also many concrete examples written in C#. The guides here can even be useful to bot developers... -
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MiniMax-M2
MiniMax-M2, a model built for Max coding & agentic workflows
MiniMax-M2 is an open-weight large language model designed specifically for high-end coding and agentic workflows while staying compact and efficient. It uses a Mixture-of-Experts (MoE) architecture with 230 billion total parameters but only 10 billion activated per token, giving it the behavior of a very large model at a fraction of the runtime cost. The model is tuned for end-to-end developer flows such as multi-file edits, compile–run–fix loops, and test-validated repairs across real... -
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files-to-prompt
Concatenate a directory full of files into a single prompt
files-to-prompt is a Python command-line tool that takes one or more files or entire directories and concatenates their contents into a single, LLM-friendly prompt. It walks the directory tree, outputting each file preceded by its relative path and a separator, so a model can understand which content came from where. The tool is aimed at workflows where you want to ask an LLM questions about a whole codebase, documentation set, or notes folder without manually copying files together. It... -
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TEN
Open-source framework for conversational voice AI agents
...Using components like graph-based workflow design, drag-and-drop UI (via TMAN Designer), and reusable extensions such as real-time avatars, RAG (Retrieval-Augmented Generation), and image generation, TEN enables highly customizable, scalable agent development with minimal code. -
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Simple MCP
A simple TypeScript library for creating MCP servers
simple-mcp is a TypeScript library designed to facilitate the creation of Model Context Protocol (MCP) servers. It offers a straightforward API, enabling developers to set up MCP servers with minimal code. The library emphasizes type safety through full TypeScript integration and incorporates parameter validation using Zod. It fully implements the MCP, ensuring compatibility with MCP clients. -
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Elyra
Elyra extends JupyterLab with an AI centric approach
Elyra is a set of AI-centric extensions to JupyterLab Notebooks. The Elyra Getting Started Guide includes more details on these features. A version-specific summary of new features is located on the releases page. -
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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. -
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ContextGem
ContextGem: Effortless LLM extraction from documents
ContextGem is an open-source framework designed to simplify the extraction of structured data and insights from documents using large language models (LLMs). It provides a flexible, intuitive API that minimizes boilerplate code, enabling developers to build complex extraction workflows efficiently. ContextGem supports various document formats and integrates with multiple LLM providers, making it a versatile tool for tasks like contract analysis, anomaly detection, and information retrieval. -
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Reinforcement Learning Course Materials
Lecture notes, tutorial tasks including solutions
Lecture notes, tutorial tasks including solutions as well as online videos for the reinforcement learning course hosted by Paderborn University. The source code for the entire course material is open and everyone is cordially invited to use it for self-learning (students) or to set up their own course (lecturers). -
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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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VibeSDK
Open source full-stack AI vibe coding platform & web app generator
VibeSDK is an open source “vibe coding” platform. VibeSDK is a project built by Cloudflare. It provides a full-stack reference implementation of an AI-driven system. Users describe the application they want in natural language, and the system generates, previews, and deploys the resulting web app. It uses Cloudflare’s infrastructure (Workers, Containers, sandboxes). -
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FlowGram
Extensible workflow development framework
FlowGram is an open-source, node-based workflow development framework and toolkit aimed at helping developers build custom AI-workflow platforms or automation systems through a visual, drag-and-drop interface. Instead of shipping as a ready-made product, it provides the building blocks — a canvas for wiring together nodes, a form engine for configuring node parameters, a variable-scope and type-inference engine, and a set of “materials” (pre-built node types such as code execution, conditional logic, LLM calls, etc.) that can be composed into larger workflows. ... -
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geo-seo-claude
GEO-first SEO skill for Claude Code
geo-seo-claude is an AI-powered tool designed to automate the creation of geographically optimized SEO content using large language models, helping businesses improve their visibility in local search results. It leverages AI to generate location-specific content tailored to different regions, allowing users to scale SEO efforts across multiple cities or markets without manual content creation. The system focuses on producing structured and keyword-optimized pages that align with search... -
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verl
Volcano Engine Reinforcement Learning for LLMs
VERL is a reinforcement-learning–oriented toolkit designed to train and align modern AI systems, from language models to decision-making agents. It brings together supervised fine-tuning, preference modeling, and online RL into one coherent training stack so teams can move from raw data to aligned policies with minimal glue code. The library focuses on scalability and efficiency, offering distributed training loops, mixed precision, and replay/buffering utilities that keep accelerators busy....
