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# workflow-function-manifold
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> A TypeScript/JavaScript library for building dynamic, LLM-driven workflows using a region-based execution model
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## Overview
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`workflow-function-manifold` enables you to create dynamic workflows that:
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- Navigate between different execution regions based on LLM-interpreted intents
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- Execute operations within regions based on state and context
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- Maintain workflow state across operations
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- Support flexible region-to-region connections
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```mermaid
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graph TD
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MF[Workflow Function Manifold] -->|Initialize| CR[Current Region]
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MF -->|Navigate| AR[Adjacent Regions]
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MF -->|Execute| OP[Operators]
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OP -->|Use| LLM[LLM Service]
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LLM -->|Match| INT[Intent]
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INT --> OP
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OP -->|Update| ST[Workflow State]
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ST -->|Inform| AR
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AR -->|Check| NR[Next Region]
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NR -->|If Valid| CR
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CR -->|Continue| OP
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NR -->|If Invalid| END[End]
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style MF fill:#000000,stroke:#FFFFFF,stroke-width:4px,color:#ffffff
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style CR fill:#222222,stroke:#FFFFFF,stroke-width:2px,color:#ffffff
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style AR fill:#222222,stroke:#FFFFFF,stroke-width:2px,color:#ffffff
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style OP fill:#333333,stroke:#FFFFFF,stroke-width:2px,color:#ffffff
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style LLM fill:#333333,stroke:#FFFFFF,stroke-width:2px,color:#ffffff
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style INT fill:#333333,stroke:#FFFFFF,stroke-width:2px,color:#ffffff
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style NR fill:#333333,stroke:#FFFFFF,stroke-width:2px,color:#ffffff
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style END fill:#222222,stroke:#FFFFFF,stroke-width:2px,color:#ffffff
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style ST fill:#444444,stroke:#FFFFFF,stroke-width:2px,color:#ffffff
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```
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## Installation
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```bash
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npm install workflow-function-manifold
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```
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## Quick Start
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```javascript
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import {
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WorkflowFunctionManifold,
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ManifoldRegion,
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WorkflowOperator,
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DummyLlmService
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} from 'workflow-function-manifold';
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// Initialize the manifold with an LLM service
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const llm = new DummyLlmService();
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const manifold = new WorkflowFunctionManifold(llm);
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// Create an operator
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const analysisOperator = new WorkflowOperator('analysis', async (state) => {
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console.log('Analyzing data...');
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return { ...state, analyzed: true };
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});
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// Create and connect regions
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const analysisRegion = new ManifoldRegion('analysis', [analysisOperator]);
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manifold.addRegion(analysisRegion);
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// Execute workflow
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await manifold.navigate('analyze the data');
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await manifold.executeWorkflow('analyze the data');
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```
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## Core Components
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### WorkflowFunctionManifold
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The main class that orchestrates workflow execution.
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```javascript
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const manifold = new WorkflowFunctionManifold(llmService);
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// Add regions
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manifold.addRegion(region);
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// Navigate between regions
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await manifold.navigate(prompt);
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// Execute operations
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await manifold.executeWorkflow(prompt);
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```
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### ManifoldRegion
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Represents a workflow region containing operators and connections to other regions.
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```javascript
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const region = new ManifoldRegion('regionName', [operator1, operator2]);
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// Connect regions
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region.connectTo(otherRegion);
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// Add operators
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region.addOperator(newOperator);
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```
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### WorkflowOperator
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Defines operations that can be executed within regions.
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```javascript
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const operator = new WorkflowOperator('operatorName', async (state) => {
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// Modify state
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return newState;
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});
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```
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### DummyLlmService
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A simple LLM service simulation for intent matching.
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```javascript
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const llm = new DummyLlmService();
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const intent = await llm.query('analyze the data');
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// Returns: { confidence: 0.9, action: 'analysis' }
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```
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## Complete Example
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Here's a full example demonstrating a three-stage workflow:
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```javascript
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async function createWorkflow() {
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const llm = new DummyLlmService();
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const manifold = new WorkflowFunctionManifold(llm);
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// Create operators
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const analysisOp = new WorkflowOperator('analysis', async (state) => {
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return { ...state, analyzed: true };
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});
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const processingOp = new WorkflowOperator('processing', async (state) => {
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return { ...state, processed: true };
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});
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const transformOp = new WorkflowOperator('transformation', async (state) => {
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return { ...state, transformed: true };
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});
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// Create and connect regions
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const analysisRegion = new ManifoldRegion('analysis', [analysisOp]);
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const processingRegion = new ManifoldRegion('processing', [processingOp]);
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const transformRegion = new ManifoldRegion('transformation', [transformOp]);
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analysisRegion.connectTo(processingRegion);
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processingRegion.connectTo(transformRegion);
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// Add regions to manifold
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manifold.addRegion(analysisRegion);
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manifold.addRegion(processingRegion);
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manifold.addRegion(transformRegion);
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return manifold;
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}
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// Execute workflow
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const manifold = await createWorkflow();
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const prompts = [
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'analyze the data',
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'process the results',
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'transform the output'
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];
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for (const prompt of prompts) {
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await manifold.navigate(prompt);
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await manifold.executeWorkflow(prompt);
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}
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```
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## API Reference
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### WorkflowFunctionManifold
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#### Constructor
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- `constructor(llmService: LLMService)`
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#### Methods
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- `addRegion(region: ManifoldRegion): void`
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- `async navigate(prompt: string): Promise<boolean>`
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- `async executeWorkflow(prompt: string): Promise<boolean>`
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### ManifoldRegion
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#### Constructor
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- `constructor(name: string, operators: WorkflowOperator[] = [])`
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#### Methods
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- `addOperator(operator: WorkflowOperator): void`
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- `connectTo(region: ManifoldRegion): void`
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- `async getValidOperators(state: any): Promise<WorkflowOperator[]>`
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### WorkflowOperator
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#### Constructor
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- `constructor(name: string, operation: (state: any) => Promise<any>)`
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#### Methods
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- `async execute(state: any): Promise<any>`
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## State Management
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The workflow maintains state across operations. Each operator can access and modify the state:
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```javascript
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const operator = new WorkflowOperator('example', async (state) => {
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// Access existing state
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const { previousValue } = state;
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// Return modified state
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return {
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...state,
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newValue: 'updated'
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};
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});
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```
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## LLM Integration
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The system uses LLM services for intent recognition. The default `DummyLlmService` provides basic intent matching, but you can implement your own LLM service:
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```javascript
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class CustomLLMService {
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async query(prompt) {
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// Implement custom LLM logic
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return {
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confidence: number,
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action: string
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};
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}
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}
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```
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## Contributing
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1. Fork the repository
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2. Create your feature branch: `git checkout -b feature/my-feature`
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3. Commit your changes: `git commit -am 'Add new feature'`
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4. Push to the branch: `git push origin feature/my-feature`
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5. Submit a pull request
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## License
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MIT © 2024 Geoff Seemueller
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