Search Results for "build apps" - Page 2
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Showing 36 open source projects for "build apps"
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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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Application Monitoring That Won't Slow Your App DownFull APM with errors, performance, logs, and uptime monitoring. 99.999% uptime SLA on the platform itself.
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AIConfig
AIConfig is a config-based framework to build generative AI apps
AIConfig is an open-source framework designed to simplify the development and management of generative AI applications by separating AI logic from application code. The framework allows prompts, model configurations, and parameters to be stored as structured configuration files that can be version controlled and managed independently from the rest of the software system. This approach improves collaboration between developers, prompt engineers, and machine learning practitioners by turning... -
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PC_Workman_HCK
AI-powered PC monitoring that explains. Not shows numbers/spikes.
PC_Workman is what 680 hours of coding after warehouse shifts looks like. Built on a laptop hitting 94°C, this AI-powered monitoring tool does what Task Manager can't: it understands your system, not just measures it. Features: - Time travel monitoring - debug issues from hours ago - AI diagnostics with HCK_GPT - Custom fan curves with profiles - Floating always-on-top widget - 2D system map - Cross-GPU support (NVIDIA/AMD/Intel) Four complete rebuilds. 29 features killed.... -
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CodinIT.dev
Free, local, open-source AI app builder
CodinIT.dev is a free, local, open source AI app builder that lets you go from idea to full-stack application entirely on your machine, no coding required, just chat with AI. You can build unlimited apps with real-time previews, instant undo, and responsive, frictionless workflows. Deep Supabase integration means you can create UI and backend logic in one cohesive environment, while the model-agnostic architecture lets you connect to any AI, whether cloud-based (Gemini 3 Pro, GPT-5, Claude Sonnet 4.5) or local via Ollama, so you’re never locked in. ... -
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autollm
Ship RAG based LLM web apps in seconds
autollm is an open-source Python framework designed to make it much faster to build retrieval-augmented generation applications and expose them as usable services with minimal setup. The project focuses on simplifying the usual stack of model selection, document ingestion, vector storage, querying, and API deployment into a more unified developer experience. Its core idea is that a developer can create a query engine from a document set in just a few lines and then turn that same engine into... -
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InternLM
Official release of InternLM series
InternLM is an open-source family of multilingual foundation and chat models, accompanied by an ecosystem that supports training, inference, and application development. The repository highlights multiple model sizes intended to serve different needs, from efficient research and prototyping to more capable deployments for complex scenarios. Beyond model weights, the project emphasizes an ecosystem view, pointing developers to compatible tools and projects across training and inference so... -
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EvaDB
Database system for building simpler and faster AI-powered application
Over the last decade, AI models have radically changed the world of natural language processing and computer vision. They are accurate on various tasks ranging from question answering to object tracking in videos. To use an AI model, the user needs to program against multiple low-level libraries, like PyTorch, Hugging Face, Open AI, etc. This tedious process often leads to a complex AI app that glues together these libraries to accomplish the given task. This programming complexity prevents... -
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langchain-prefect
Tools for using Langchain with Prefect
Large Language Models (LLMs) are interesting and useful - building apps that use them responsibly feels like a no-brainer. Tools like Langchain make it easier to build apps using LLMs. We need to know details about how our apps work, even when we want to use tools with convenient abstractions that may obfuscate those details. Prefect is built to help data people build, run, and observe event-driven workflows wherever they want. -
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UnionML
Build and deploy machine learning microservices
Creating ML apps should be simple and frictionless. UnionML is an open-source Python framework built on top of Flyte™, unifying the complex ecosystem of ML tools into a single interface. Combine the tools that you love using a simple, standardized API so you can stop writing so much boilerplate and focus on what matters: the data and the models that learn from them. Fit the rich ecosystem of tools and frameworks into a common protocol for machine learning. Using industry-standard machine... -
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AI Chatbots based on GPT Architecture
Training & Implementation of chatbots leveraging GPT-like architecture
Training & Implementation of chatbots leveraging GPT-like architecture with the aitextgen package to enable dynamic conversations. It sure seems like there are a lot of text-generation chatbots out there, but it's hard to find a python package or model that is easy to tune around a simple text file of message data. This repo is a simple attempt to help solve that problem. ai-msgbot covers the practical use case of building a chatbot that sounds like you (or some dataset/persona you choose)... -
Forever Free Full-Stack Observability | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
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MLOps Course
Learn how to design, develop, deploy and iterate on ML apps
The MLOps Course by Goku Mohandas is an open-source curriculum that teaches how to combine machine learning with solid software engineering to build production-grade ML applications. It is structured around the full lifecycle: data pipelines, modeling, experiment tracking, deployment, testing, monitoring, and iteration. The repository itself contains configuration, code examples, and links to accompanying lessons hosted on the Made With ML site, which provide detailed narrative explanations... -
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Universe Starter Agent
A starter agent that can solve a number of universe environments
The universe-starter-agent repository is an archived OpenAI codebase designed as a starter reinforcement-learning agent that can interact with and solve tasks in OpenAI’s Universe environment platform. Its purpose is to serve as a baseline or reference implementation so researchers or developers can see how to build agents that operate in real-time, visual environments (e.g., games, browser apps) via pixel observations and keyboard/mouse actions. Under the hood, this starter agent implements a version of the A3C (Asynchronous Advantage Actor-Critic) algorithm, adapted for the specific challenges of Universe environments (e.g., network latency, VNC streaming, asynchronous observations). ...
