HyperFlow: Generative AI Development & Orchestration Platform

What is HyperFlow?

HyperFlow is a visual development and orchestration platform for building production-ready generative AI applications. Think of it as a no-code/low-code IDE for AI workflows, combined with a robust execution engine and hosting infrastructure.

Core Value Proposition

Instead of hard-coding AI logic, you visually design flow-graphs in the HyperFlow IDE - directed graphs where nodes represent AI operations (LLM calls, RAG queries, data transforms, etc.). Once published, these flow-graphs become production AI backends accessible via a RESTful Control API.

In practice:

• Developers build and debug AI workflows visually in the HyperFlow IDE
• Published flow-graphs become production APIs
• Custom applications (like this project) control those flow-graphs via the Control API
• End users interact with AI through your custom UI, powered by HyperFlow's execution engine

Architecture Overview

┌─────────────────────────────────────────────────────────┐
│                   Your Custom Application                │
│         (React/Vue/Mobile App with Custom UI)           │
└────────────────────┬────────────────────────────────────┘
                     │ Control API
                     │ (REST + Long-polling)
                     ↓
┌─────────────────────────────────────────────────────────┐
│              HyperFlow Platform (Backend)                │
├─────────────────────────────────────────────────────────┤
│  Production Flow-Graph Engine                           │
│  ├── Published Flow-Graph Execution                     │
│  ├── Session Management & State                         │
│  └── Control API (start, progress, streaming)          │
├─────────────────────────────────────────────────────────┤
│  Service Orchestration Layer                            │
│  ├── 50+ Flow-Graph Nodes                              │
│  ├── 50+ Service Adapters (LLMs, Vector DBs, etc.)     │
│  └── ML Worker Job Queue (Python, RabbitMQ)            │
├─────────────────────────────────────────────────────────┤
│  IDE Flow-Graph Engine (Development Mode)               │
│  └── Visual Editor, Debugger, Test Runner              │
└─────────────────────────────────────────────────────────┘

Key Concepts

1. Flow-Graphs

Visual workflows that orchestrate AI operations:

• Nodes = Operations (Call LLM, Search Knowledge DB, Transform Data, User Input, etc.)
• Edges = Data flow connections between nodes
• Execution = Server-side orchestration with full state management

Example Flow-Graph:

[User Input] → [Search Knowledge DB] → [Call LLM with Context] → [Response]
      ↓                                          ↑
      └────────[Generate Follow-up]─────────────┘