Top Builders

Explore the top contributors showcasing the highest number of app submissions within our community.

OpenGPTs

OpenGPTs, powered by LangChain's technology stack, offers developers a versatile framework for harnessing AI capabilities. Leveraging over 60 language models, LangSmith's prompt customization, and a suite of 100+ tools, OpenGPTs provides unparalleled control and flexibility in AI model configurations.

General
AuthorLangChain
RepositoryGitHub - LangChain OpenGPTs
TypeCustomizable AI Model Framework

Framework Overview

OpenGPTs serves as a customizable AI framework, allowing users to fine-tune language models, prompts, tools, vector databases, retrieval algorithms, and chat history databases. This level of control surpasses direct usage of OpenAI, enabling developers to interact with APIs directly and craft tailored user interfaces.

Technology Tutorials

Customization

  • 1. Language Models (LLMs): Select from over 60 LLMs integrated with LangChain. Note the varying prompts required for different models.
  • 2. Prompt Customization: Debug and fine-tune prompts with LangSmith for enhanced accuracy.
  • 3. Tool Integration: Access a diverse suite of 100+ tools provided by LangChain or easily create custom tools.
  • 4. Vector Databases: Choose from 60+ vector database integrations within LangChain.
  • 5. Retrieval Algorithms: Optimize retrieval algorithms based on project requirements.
  • 6. Chat History Databases: Tailor chat history databases to suit specific project needs.

Agent Types (Default):

  1. "GPT 3.5 Turbo"
  2. "GPT 4"
  3. "Azure OpenAI"
  4. "Claude 2"

OpenGPTs' appeal lies in its high level of customization compared to direct usage of OpenAI. Users gain control over language model selection, seamless addition of custom tools, and direct API utilization. Furthermore, developers can craft custom UIs as needed.

Utilize OpenGPTs to harness the power of AI tailored precisely to your project requirements.

For a deeper dive into usage and configuration, refer to the OpenGPTs Documentation.

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Langchain OpenGPTs AI technology Hackathon projects

Discover innovative solutions crafted with Langchain OpenGPTs AI technology, developed by our community members during our engaging hackathons.

SANCTUMSIM

SANCTUMSIM

SANCTUM-SIM is a simulation-first robotics platform that demonstrates autonomous infrastructure management under real-world constraints. In a simulated geothermal and logistics facility, mobile inspection and maintenance robots operate in dynamic heat zones, energy limits, and failure-prone environments. Unlike scripted demos, each agent continuously evaluates tradeoffs between energy use, time, and operational risk using cost functions and a planner-based decision engine. Every action generates a structured, explainable rationale—showing why a robot rerouted, delayed, escalated, or conserved power. The system introduces sensor noise, randomized failures, and environmental volatility to demonstrate robustness, recovery, and graceful degradation. A browser dashboard visualizes agent states, decisions, and performance metrics in real time. SANCTUM-SIM enables energy operators and infrastructure teams to simulate, validate, and build trust in autonomous systems before real-world deployment.

NeuroPilot

NeuroPilot

People who could benefit from hands-free control, for example those with limited mobility, often cannot access it. NeuroPilot changes that: open-source BCI middleware that turns a Muse 2 headband into a real control interface. Muse 2 is already connected to the app, and we have a working integration with DJI Tello. Users train in a 3D simulation and in a training environment; when their brainwave pattern matches a chosen action (move left, right, up, down), the backend fires configurable webhooks or WebSockets. We accumulate 5 actions from the headband; YOLOv8 runs on the Tello camera feed to detect obstacles and Tello state. That batch and the vision data are sent to Gemini, which decides the movement. Every command sent to the DJI Tello is the result of an AI API call, so BCI intent is refined by vision and reasoning before it reaches the drone. The stack is software-only and simulation-first: a Next.js frontend, a FastAPI + WebSocket backend, a web Lab (Three.js), a machine/Connect dashboard for status and live feedback, and per-control webhook URLs. No lab hardware or locked-in vendors. Teams can integrate with existing sims, digital twins, or robots via HTTP.

SentinelOps AI Autonomous Robotics Engine

SentinelOps AI Autonomous Robotics Engine

SentinelOps AI is a simulation-first robotics platform designed to demonstrate how autonomous systems reason, decide, and adapt in dynamic environments. The platform combines a robotics state simulator, an AI-driven decision engine, and structured event logging into a modular backend architecture built with FastAPI. Each simulation step updates the robot’s state, generates events, and triggers an AI reasoning loop that selects the next optimal action with confidence scoring. All decisions and events are logged for traceability, auditability, and system analysis. The goal of SentinelOps AI is to bridge the gap between artificial intelligence and robotics by showcasing clean API design, scalable backend structure, and autonomous control logic in a production-style system. The project emphasizes transparency, modularity, and intelligent automation as foundations for next-generation robotics platforms.

AstraBots Autonomous Simulation-Platform

AstraBots Autonomous Simulation-Platform

In logistics, warehousing, and manufacturing, inefficiencies caused by human coordination, slow task execution, and operational errors cost billions annually. AstraBots solves this problem by providing a fully simulated, AI-powered robotics platform that can perform autonomous tasks, adapt to changing environments, and measure efficiency metrics in real time. Companies can simulate, test, and optimize workflows before investing in expensive hardware, dramatically reducing risk and cost. AstraBots combines a modern tech stack — FastAPI, Uvicorn, cloud-hosted simulations, and AI decision-making — to create a startup-ready platform. Robots in the simulation plan actions autonomously, react to environmental changes, and complete objectives without manual intervention. The platform tracks performance metrics like task efficiency, throughput, and reliability. This simulation-first approach allows rapid iteration, scalable deployment, and eventual integration with real robotic systems, making AstraBots the most versatile and cost-effective robotics solution for startups and enterprises globally.

MetaIntent

MetaIntent

🔹 Project Vision Our vision is to empower businesses & designers to build their own local metaverse environments with full data protection & sovereignty, without relying on centralized intermediary platforms, making metaverse creation accessible & scalable as web publishing. 🔹 Core Innovation: In-Platform Metaverse Building Instead of searching external 3D libraries, users build metaverse environments directly inside the platform. By providing a natural language description, the AI agent generates the required 3D model & replaces or updates it inside the virtual environment in real time, reducing design time & eliminating dependency on external repositories. # No-Code Templates & Customization #We provide ready-made virtual environments & templates that companies can customize using drag-and-drop tools or AI-driven generation without technical expertise. #Cross-Device Deployment The platform is device-agnostic, enabling creation & publishing from desktops, mobile devices, & VR platforms, with global web access for users. 🔹 Monetization & Export Channels Businesses use environments as interactive digital export channels to showcase products & services, integrate online payments, & create multiple global revenue streams. 🔹 Data Protection & Local Deployment We enable local metaverse deployment with strong data governance, regulatory compliance, & full control over sensitive data & intellectual property. 🔹 Development Status & Roadmap We completed the system architecture & design phase & started implementing the core platform & AI agent modules, with a roadmap to transition from custom deployments to a scalable AI-powered platform. 🔹 Partnerships & Market Validation We established 2 strategic partnerships & are preparing pilot deployments to demonstrate platform value through real-world use cases & accelerate adoption. 🔹 Impact The platform enables economic empowerment, multiple income streams for creators & enterprises, globally, with full data sovereignty.

CareSight AI - Autonomous Healthcare Assistant

CareSight AI - Autonomous Healthcare Assistant

CareSight AI is an autonomous, multimodal healthcare assistant designed to reduce clinical paperwork and improve care readiness across the patient journey. The system uses computer vision, OCR, speech recognition, and LLM reasoning (Gemma 3N) to perceive and structure unorganized healthcare data such as documents, images, and spoken responses. Patients begin with a mobile web app to upload IDs, insurance cards, lab reports, and clinical images, or provide voice responses. CareSight AI extracts structured data, validates completeness, and prepares an intake summary. During nurse check-in, the system assists by auto-filling forms, flagging inconsistencies, and supporting preliminary screenings such as cognitive memory tests by recording sessions, transcribing responses, and automatically scoring recall accuracy. Doctors receive a concise, explainable summary highlighting key findings and uncertainties. CareSight AI functions as an autonomous agent following a perception–reasoning–action loop, supporting clinicians without replacing them and enabling scalable, remote-ready healthcare workflows.