PromptDAG Builder
🕸️ Visual Suggestion: Consider adding a flowchart showing how a multi-node prompt graph connects nodes like summarizer → classifier → action decision prompt.
The PromptDAG Builder is a visual and programmatic interface for designing and executing multi-prompt workflows using a directed acyclic graph (DAG) abstraction. It enables developers and non-technical users to construct complex semantic flows by chaining prompts into structured logic graphs.
┌────────────────────────────────────────────────────────────────────────────────┐
│ PROMPTDAG EXAMPLE WORKFLOW │
│ │
│ ┌───────────────┐ ┌─────────────────┐ ┌───────────────────┐ │
│ │ │ │ │ │ │ │
│ │ Document │────▶│ Summarizer │────▶│ Sentiment │ │
│ │ Extractor │ │ │ │ Analyzer │ │
│ │ │ │ │ │ │ │
│ └───────────────┘ └─────────────────┘ └───────┬───────────┘ │
│ │ │
│ ▼ │
│ ┌─────────────────────────┐ │
│ │ │ │
│ │ Conditional Branch │ │
│ │ │ │
│ │ │ │
│ └────────┬────────────────┘ │
│ │ │
│ ┌──────────────────────┐ │ ┌────────────────────┐ │
│ │ │ │ │ │ │
│ │ Negative Feedback │◀─┴─▶│ Recommendation │ │
│ │ Handler │ │ Generator │ │
│ │ │ │ │ │
│ └──────────────────────┘ └────────────────────┘ │
│ │
└────────────────────────────────────────────────────────────────────────────────┘1. Conceptual Model
Each prompt within PromptHub can act as a node within a DAG. These nodes can:
Accept input from previous nodes
Transform or reformat data
Invoke LLMs or agent modules
Produce intermediate outputs for downstream tasks
DAG edges define data flow, execution order, and conditional branching.
2. Features
Visual Editor: Web-based composer to drag-and-drop prompt modules, connect them, and assign parameters
Parameter Propagation: Output of one node can be passed as dynamic input to the next
Conditional Execution: Nodes can execute only if certain outputs match predicates
Parallel Execution: Independent branches can be executed in parallel and merged downstream
Reusable Subgraphs: DAG fragments can be saved, versioned, reused, and shared
3. On-Chain Representation
Each PromptDAG is hashed and stored on-chain as a unique flow asset. This allows:
Transparent and reproducible agent behavior
Version tracking and flow auditing
DAG-specific licensing and monetization
4. Integration with Agents
PromptDAGs can be directly consumed by:
Autonomous agents (e.g. AutoGPT) to replace custom toolchains
Smart contracts that call semantic AI modules
DAO workflows for dynamic governance proposals
The DAG builder transforms PromptHub from a prompt registry into a full-fledged semantic orchestration layer for AI-native computation.
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