manifold-workflow-engine/README.md

# workflow-function-manifold

> A TypeScript/JavaScript library for building dynamic, LLM-driven workflows using a region-based execution model

![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)
![Node Version](https://img.shields.io/badge/node-%3E%3D%2014.0.0-brightgreen)

## Table of Contents
- [Overview](#overview)
- [Installation](#installation)
- [Quick Start](#quick-start)
- [Core Components](#core-components)
- [Complete Example](#complete-example)
- [API Reference](#api-reference)
- [State Management](#state-management)
- [LLM Integration](#llm-integration)
- [Error Handling](#error-handling)
- [Contributing](#contributing)
- [License](#license)

## Overview

`workflow-function-manifold` enables you to create dynamic workflows that:
- Navigate between different execution regions based on LLM-interpreted intents
- Execute operations within regions based on state and context
- Maintain workflow state across operations
- Support flexible region-to-region connections

```mermaid
graph TD
   MF[Workflow Function Manifold] -->|Initialize| CR[Current Region]
   MF -->|Navigate| AR[Adjacent Regions]
   MF -->|Execute| OP[Operators]
   OP -->|Use| LLM[LLM Service]
   LLM -->|Match| INT[Intent]
   INT --> OP
   OP -->|Update| ST[Workflow State]
   ST -->|Inform| AR
   AR -->|Check| NR[Next Region]
   NR -->|If Valid| CR
   CR -->|Continue| OP
   NR -->|If Invalid| END[End]

   style MF fill:#000000,stroke:#FFFFFF,stroke-width:4px,color:#ffffff
   style CR fill:#222222,stroke:#FFFFFF,stroke-width:2px,color:#ffffff
   style AR fill:#222222,stroke:#FFFFFF,stroke-width:2px,color:#ffffff
   style OP fill:#333333,stroke:#FFFFFF,stroke-width:2px,color:#ffffff
   style LLM fill:#333333,stroke:#FFFFFF,stroke-width:2px,color:#ffffff
   style INT fill:#333333,stroke:#FFFFFF,stroke-width:2px,color:#ffffff
   style NR fill:#333333,stroke:#FFFFFF,stroke-width:2px,color:#ffffff
   style END fill:#222222,stroke:#FFFFFF,stroke-width:2px,color:#ffffff
   style ST fill:#444444,stroke:#FFFFFF,stroke-width:2px,color:#ffffff
```

## Installation

```bash
npm install workflow-function-manifold
```

## Quick Start

```javascript
import { 
  WorkflowFunctionManifold, 
  ManifoldRegion, 
  WorkflowOperator, 
  DummyLlmService 
} from 'workflow-function-manifold';

// Initialize the manifold with an LLM service
const llm = new DummyLlmService();
const manifold = new WorkflowFunctionManifold(llm);

// Create an operator
const analysisOperator = new WorkflowOperator('analysis', async (state) => {
  console.log('Analyzing data...');
  return { ...state, analyzed: true };
});

// Create and connect regions
const analysisRegion = new ManifoldRegion('analysis', [analysisOperator]);
manifold.addRegion(analysisRegion);

// Execute workflow
await manifold.navigate('analyze the data');
await manifold.executeWorkflow('analyze the data');
```

## Core Components

### WorkflowFunctionManifold

The main class that orchestrates workflow execution.

```javascript
const manifold = new WorkflowFunctionManifold(llmService);

// Add regions
manifold.addRegion(region);

// Navigate between regions
await manifold.navigate(prompt);

// Execute operations
await manifold.executeWorkflow(prompt);
```

### ManifoldRegion

Represents a workflow region containing operators and connections to other regions.

```javascript
const region = new ManifoldRegion('regionName', [operator1, operator2]);

// Connect regions
region.connectTo(otherRegion);

// Add operators
region.addOperator(newOperator);
```

### WorkflowOperator

Defines operations that can be executed within regions.

```javascript
const operator = new WorkflowOperator('operatorName', async (state) => {
  // Modify state
  return newState;
});
```

### DummyLlmService

A simple LLM service simulation for intent matching.

```javascript
const llm = new DummyLlmService();
const intent = await llm.query('analyze the data');
// Returns: { confidence: 0.9, action: 'analysis' }
```

## Complete Example

Here's a full example demonstrating a three-stage workflow:

```javascript
async function createWorkflow() {
  const llm = new DummyLlmService();
  const manifold = new WorkflowFunctionManifold(llm);

  // Create operators
  const analysisOp = new WorkflowOperator('analysis', async (state) => {
    return { ...state, analyzed: true };
  });
  const processingOp = new WorkflowOperator('processing', async (state) => {
    return { ...state, processed: true };
  });
  const transformOp = new WorkflowOperator('transformation', async (state) => {
    return { ...state, transformed: true };
  });

  // Create and connect regions
  const analysisRegion = new ManifoldRegion('analysis', [analysisOp]);
  const processingRegion = new ManifoldRegion('processing', [processingOp]);
  const transformRegion = new ManifoldRegion('transformation', [transformOp]);

  analysisRegion.connectTo(processingRegion);
  processingRegion.connectTo(transformRegion);

  // Add regions to manifold
  manifold.addRegion(analysisRegion);
  manifold.addRegion(processingRegion);
  manifold.addRegion(transformRegion);

  return manifold;
}

// Execute workflow
const manifold = await createWorkflow();
const prompts = [
  'analyze the data',
  'process the results',
  'transform the output'
];

for (const prompt of prompts) {
  await manifold.navigate(prompt);
  await manifold.executeWorkflow(prompt);
}
```

## API Reference

### WorkflowFunctionManifold

#### Constructor
- `constructor(llmService: LLMService)`

#### Methods
- `addRegion(region: ManifoldRegion): void`
- `async navigate(prompt: string): Promise<boolean>`
- `async executeWorkflow(prompt: string): Promise<boolean>`

### ManifoldRegion

#### Constructor
- `constructor(name: string, operators: WorkflowOperator[] = [])`

#### Methods
- `addOperator(operator: WorkflowOperator): void`
- `connectTo(region: ManifoldRegion): void`
- `async getValidOperators(state: any): Promise<WorkflowOperator[]>`

### WorkflowOperator

#### Constructor
- `constructor(name: string, operation: (state: any) => Promise<any>)`

#### Methods
- `async execute(state: any): Promise<any>`

## State Management

The workflow maintains state across operations. Each operator can access and modify the state:

```javascript
const operator = new WorkflowOperator('example', async (state) => {
  // Access existing state
  const { previousValue } = state;
  
  // Return modified state
  return {
    ...state,
    newValue: 'updated'
  };
});
```

## LLM Integration

The system uses LLM services for intent recognition. The default `DummyLlmService` provides basic intent matching, but you can implement your own LLM service:

```javascript
class CustomLLMService {
  async query(prompt) {
    // Implement custom LLM logic
    return {
      confidence: number,
      action: string
    };
  }
}
```

#### **Error Handling**

This library includes basic error handling to ensure workflows continue running smoothly, even when unexpected issues arise.

#### **Navigation Errors**

If a prompt doesn't match a valid adjacent region, the system will:
- Log a warning: `No valid region found for prompt: "<prompt>"`
- Continue without changing the current region.

#### **Operator Execution Errors**

If no matching operator is found for a prompt, or an operator encounters an error during execution:
- Log a warning: `No matching operator found for intent: <intent>`
- Log an error if execution fails: `Error during workflow execution for prompt "<prompt>": <error message>`

#### **LLM Query Errors**

In case of issues querying the LLM service:
- Log an error: `Error during navigation for prompt "<prompt>": <error message>`

#### **Example Error Logging**

```javascript
const manifold = new WorkflowFunctionManifold(new DummyLlmService());

try {
    await manifold.navigate('unknown command');
} catch (error) {
    console.error('Critical navigation error:', error);
}

try {
    await manifold.executeWorkflow('perform unknown action');
} catch (error) {
    console.error('Critical execution error:', error);
}
```


## Contributing

1. Fork the repository
2. Create your feature branch: `git checkout -b feature/my-feature`
3. Commit your changes: `git commit -am 'Add new feature'`
4. Push to the branch: `git push origin feature/my-feature`
5. Submit a pull request

## License

MIT © 2024 Geoff Seemueller