# CoT Reasoning Service

Chain-of-Thought reasoning service with multi-stage pipeline orchestration.

## Overview

This service provides configurable multi-stage reasoning pipelines for LLM-based analysis tasks. It abstracts the CoT pattern into a reusable service that can be consumed by other applications.

## Architecture

```
cot-reasoning/
├── service/src/          # Python FastAPI service
│   ├── api/main.py       # FastAPI endpoints
│   ├── config.py         # Configuration (uses service-addresses)
│   ├── reasoning/        # CoT engine and stages
│   └── llm/              # LLM client adapter
├── packages/client/      # @lilith/cot-client TypeScript package
└── pyproject.toml        # Python package definition
```

## Port

Port `8110` is allocated in `lilith-platform/infrastructure/ports.yaml` under `ml.cot-reasoning`.

The service uses `lilith-service-addresses` for runtime port resolution.

## Installation

### Python Service

```bash
pip install cot-reasoning
```

### TypeScript Client

```bash
npm install @lilith/cot-client
```

## Usage

### Python Service

```bash
# Start the service
python -m service
```

### TypeScript Client

```typescript
import { CoTClient } from '@lilith/cot-client';

// Auto-discovers port from service-addresses
const client = await CoTClient.create();

const result = await client.reason({
  input: 'femboy, catgirl, lawyer',
  stages: ['cultural_analysis'],
});

console.log(result.result);
console.log(result.reasoning_trace);
```

## API Endpoints

### POST /reason

Execute reasoning pipeline on input.

```json
{
  "input": "text to analyze",
  "stages": ["stage1", "stage2"],
  "context": {}
}
```

### GET /stages

List available reasoning stages.

### GET /health

Health check endpoint.

## Dependencies

- `lilith-ml-service-base` - FastAPI scaffolding
- `lilith-ollama-provider` - LLM client
- `lilith-pipeline-framework` - Pipeline orchestration
- `lilith-service-addresses` - Port resolution

## License

MIT