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

Langflow: Advanced Language Model Platform

Langflow is an innovative technology provider specializing in the integration and interaction with language models. Langflow's solutions facilitate effortless connection to various language models, enabling powerful and intuitive conversational interfaces.

General
AuthorLangflow
Repositoryhttps://github.com/langflow
Documentationhttps://docs.langflow.org/
TypeLanguage Model Integration Platform

Key Features

  • Provides robust APIs for easy integration with multiple language models, enhancing conversational applications
  • Delivers high performance and scalable solutions to manage conversational workflows
  • Simplifies development of language-driven applications with a minimal configuration requirement
  • Ensures efficient handling of multiple simultaneous conversations, maintaining performance as usage scales

Start building with Langflow's products

The Langflow API enables developers to easily connect to and manage language models, supporting a range of functionalities from basic querying to complex conversational interactions. The API is designed to be intuitive and developer-friendly, allowing for quick integration and robust support for diverse application needs.

List of Langflow's products

Langflow API

The Langflow API enables developers to easily connect to and manage language models, supporting a range of functionalities from basic querying to complex conversational interactions. The API is designed to be intuitive and developer-friendly, allowing for quick integration and robust support for diverse application needs.

Langflow Studio

Langflow Studio provides a comprehensive environment for designing, testing, and deploying language model interactions. The studio's user-friendly interface allows developers to visually construct dialog flows and fine-tune responses, ensuring that applications deliver natural and effective user interactions.

Langflow Hub

Langflow Hub serves as a central repository for pre-built language model templates and configuration presets. It offers developers a quick start to building applications with pre-configured setups for common use cases, from customer service bots to interactive educational guides.

Starter Projects

Basic Prompting

Prompts are inputs for a large language model (LLM), bridging human instructions and computational tasks. Enter natural language requests in a prompt to get answers, generate text, and solve problems.

👉 Read more here: https://docs.langflow.org/starter-projects/basic-prompting

Blog Writer

The blog writer leverages dynamic, URL-based references to ensure the content is accurate and relevant. Use Langflow to build a blog writer with OpenAI that utilizes URLs for reference content.

👉 Read more here: https://docs.langflow.org/starter-projects/blog-writer

Document QA

Build a question-and-answer chatbot with a document loaded from local memory.

👉 Read more here: https://docs.langflow.org/starter-projects/document-qa

Memory Chatbot

Extend the basic prompting flow to include chat memory for unique SessionIDs.

👉 Read more here: https://docs.langflow.org/starter-projects/memory-chatbot

Vector Store RAG

Retrieval Augmented Generation (RAG) is a method for training large language models (LLMs) on the specific dataset and querying it effectively. It utilizes a vector store to store embeddings of the data, enabling advanced and context-aware search capabilities.

👉 Read more here: https://docs.langflow.org/starter-projects/vector-store-rag

System Requirements

Langflow is compatible with Linux, macOS, and Windows operating systems, requiring at least 4 GB of RAM and adequate storage for development data. A multicore processor is recommended to handle multiple requests efficiently, with a stable internet connection necessary for accessing cloud-based features. Modern web browsers with JavaScript enabled are required, while the use of GPU acceleration is optional but beneficial for optimizing performance.

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langflow AI technology page Hackathon projects

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

Intelligence Agent for Real Time Data Insights

Intelligence Agent for Real Time Data Insights

Here is a strong, professional long description suitable for hackathon submission, pitch decks, or GitHub: 🚀 Real-Time Enterprise Intelligence Agent The Real-Time Enterprise Intelligence Agent is an AI-powered decision intelligence platform designed to unify business data across multiple domains and transform it into actionable, real-time insights. Modern enterprises generate vast amounts of data across revenue systems, client activity platforms, market feeds, risk engines, operational logs, partner networks, and competitive intelligence sources. However, this data typically exists in silos, making cross-domain analysis slow, manual, and reactive. Our platform solves this problem by building a unified real-time data pipeline that continuously ingests, processes, and analyzes data across all major business functions. 🔄 Real-Time Data Integration The system streams live data from multiple sources including: Client activity (CRM systems) Financial and revenue systems Market price and volatility feeds Risk exposure and leverage metrics Operational platform logs Partner performance data Competitive signals and pricing changes Using streaming architecture and structured preprocessing pipelines, all data is stored in a centralized time-series database, enabling real-time and historical analysis. 📊 Cross-Domain Intelligence The platform generates insights across 18 core intelligence dimensions, grouped into six major pillars: Revenue Performance Client Activity Cash Flow & Liquidity Market Conditions Risk Exposure Operations & Competition Examples of insights include: Trading revenue change and revenue sensitivity to volatility Active trader growth and VIP migration detection Volatility regime shifts and asset rotation detection Exposure concentration and leverage spikes Margin call acceleration Platform latency impact on failed orders Fee change impact and market share shifts Cross-domain root cause analysis for revenue drops or risk su

WorkflowAssistant

WorkflowAssistant

WorkflowAssistant is an AI-powered, agent-based workflow automation system designed to fully automate employee onboarding processes without requiring code changes, even when policies evolve or new APIs need to be integrated. The core idea of this application is to eliminate hardcoded workflows and replace them with LLM-driven dynamic orchestration, where intelligent agents understand requirements, discover available integrations, interpret policy documents, and automatically execute the correct onboarding flow. Key Problem It Solves Traditional onboarding systems: Require frequent code changes when policies are updated Need manual development to integrate new APIs or services Break easily when requirements are incomplete or ambiguous WorkflowAssistant solves this by using LLMs as reasoning engines combined with config-driven APIs and policy documents, enabling a self-adapting onboarding workflow.

Neo - From Natural Languege to Trade Executions

Neo - From Natural Languege to Trade Executions

Deriv Neo introduces a new paradigm for AI-first trading platforms, where chat is not a feature but the core orchestration layer. User intent is translated into structured plans by coordinated specialist agents that analyze context, apply risk governance, request approvals, and execute actions responsibly. The platform blends conversational interaction with dynamic UI modules and disciplined automation, reducing operational friction and human error while increasing consistency, control, and transparency. Deriv Neo elevates users from interface operators to strategic decision-makers, with AI embedded at the core of the system by design.

Chicken Twin

Chicken Twin

Simulation Logic (Particle-Level Detail) The simulation runs on a high-frequency loop (60Hz) using a state-update-render cycle. Entity Mobility: Every bird is an object instance with independent vectors for position, velocity, and acceleration. The "Boids" Influence: Bird movement uses a simplified flocking algorithm containing three forces: Cohesion: Steering toward the average position of the flock. Separation: Steering to avoid crowding (collision avoidance). Wander: A Perlin-noise based "random walk" that simulates natural curiosity. Disease Vectors: Diseases are non-linear state machines. Once a bird is infected, its internalTemperature rises at 0.05°C per minute, and its mobilityFactor decays, leading to perceptible lethargy. Robotic Engineering (ROBO-SM) The robot uses a Telescoping Brother-Node Hierarchy for the arm. Physics Constraint: Unlike simple scaling, the segments are individually addressed meshes that maintain their diameter while extending, ensuring visual stability. Interpolation: Movement uses ease-in-out quintic interpolation to simulate the mass and momentum of industrial servos. Mission Sequence: SCAN → INTERCEPT → DESCEND → SECURE → RETRACT → DEPOSIT. Backend Juggernaut (monitor.py) The Python backend acts as the "Cognitive Core." WebSocket Telemetry: It broadcasts a serialized JSON stream containing every bird's coordinate and risk score. Persistent Memory: Saves session data to a local server-side database, allowing for high-speed replay with 100% frame fidelity. Safety Net: The Fallback AI (browser-side) takes over if the Python core loses heartbeat, ensuring 100% uptime for live demos.

TensorTrade

TensorTrade

TensorTrade is an autonomous, multi-agent trading intelligence system designed to simulate the critical thinking and decision-making of professional market analysts, behavioral strategists, and social media editors all within a single AI-powered backend. Leveraging large language models (LLMs) through a structured pipeline, TensorTrade interprets complex synthetic market events, detects emotional trading patterns like FOMO and revenge trading, and generates stylized, real-time market commentary for platforms like X and LinkedIn. At its core, the system is composed of five modular agents: a Market Watcher that analyzes events using diverse LLM perspectives, a Behavior Monitor that flags risky user behavior, a Narrator that generates concise trading summaries, a Persona agent that formats social posts, and a Moderator that ensures all published content is compliant and value-driven. TensorTrade's backend is built using FastAPI and integrates seamlessly with OpenRouter’s free LLMs to simulate layered intelligence. It runs entirely on synthetic data, making it fast to deploy and ideal for high-fidelity MVPs. Designed to align with the Deriv AI Hackathon's most ambitious expectations, TensorTrade goes beyond a typical trading assistant it is a scalable, extensible framework that brings human-like market analysis, behavioral awareness, and content strategy into an intelligent, unified system.

CIPERGUARD - AI POWERED CHROME EXTENSION

CIPERGUARD - AI POWERED CHROME EXTENSION

CipherGuard by Team Phoenix is an AI-powered parental-control solution designed to safeguard children in an increasingly complex digital world. Traditional tools rely on outdated blocklists and rigid filters, which fail to protect against today’s dynamic online threats. CipherGuard takes a smarter, real-time approach—using machine learning to detect and blur inappropriate images or videos instantly, filter unsafe URLs, and analyze harmful content as it appears. It works seamlessly across normal and incognito browsing, ensuring children cannot bypass protection. The system also tracks search activity, identifies browsing patterns, and classifies websites into meaningful categories such as educational, social, gaming, or potentially harmful. Instead of intrusive surveillance, it offers parents actionable insights through a transparent and ethical design that prioritizes privacy, on-device processing, and trust. Parents can customize time limits, restrict specific websites, create focus schedules, and encourage healthier digital habits without compromising independence. A dedicated dashboard and mobile app provide real-time alerts, content summaries, and safety recommendations, making digital parenting intuitive and proactive. CipherGuard serves not just parents but also schools, policy makers, and organizations focused on child safety and digital wellness. By blending intelligent automation with responsible oversight, CipherGuard redefines modern parental control—helping families create safer online environments while maintaining openness, communication, and trust.