# Confidence Engine

An experimental prototype that tests whether an LLM can build and maintain an evidence-based reconstruction of a situation over multiple turns.

## Purpose

This is Milestone 1 — a technical vertical slice only. It demonstrates:

- Sending a scenario to a local Ollama model via a Next.js server route
- Receiving structured JSON output
- Validating the result with Zod schemas
- Displaying the reconstruction and diagnostic information in a plain UI

## Prerequisites

- **Node.js 18+** (LTS recommended)
- **npm** (or equivalent package manager)
- **Ollama** installed and running on your local network, with a model pulled (e.g., `ollama pull llama3`)

## Installation

```bash
cd confidence-engine
npm install
cp .env.example .env.local
```

Edit `.env.local` and set:

- `OLLAMA_BASE_URL` — your Ollama server address (e.g., `http://192.168.1.100:11434`)
- `OLLAMA_MODEL` — the model name (e.g., `llama3`)

## Development Commands

```bash
npm run dev        # Start development server on localhost:3000
npm run build      # Production build
npm run start      # Run production server
npm run lint       # ESLint check
```

## Testing Commands

```bash
npm test           # Run all tests (one-shot)
npm run test:watch # Run tests in watch mode
```

Tests mock the Ollama network request. No real Ollama server is needed to run them.

## Verifying Ollama Connectivity

1. Start the dev server: `npm run dev`
2. Open http://localhost:3000/api/health
3. You should see JSON with `"reachable": true` and your model name

## Current Limitations

- **Single-turn only** — no conversation memory or multi-turn dialogue
- **No persistence** — results are not saved between requests
- **Ollama only** — the provider abstraction exists but only Ollama is implemented
- **JSON mode reliance** — output quality depends on the model's ability to produce valid structured JSON
- **No question generation** — no follow-up questions or uncertainty resolution yet
- **No real-time streaming** — waits for full response before displaying results
- **Plain UI** — no animations, theming, or responsive polish beyond basic layout

## Deliberately Not Implemented

- Authentication / user accounts
- Billing / rate limiting
- Database or file storage
- Vector databases or embeddings
- Deployment configuration (Docker, Vercel, etc.)
- External cloud LLM providers (OpenAI, Anthropic, etc.)
- Agent frameworks or tool use
- Complex state management (Zustand, Redux, etc.)
- Multi-turn conversation history
- Question generation or ranking

## Architecture Notes

The application uses a **provider abstraction** in `lib/llm/provider.js`. The server routes call the provider, which hides the Ollama-specific implementation. To add a new provider, implement the same interface:

```js
{
  generateReconstruction(scenario, modelName): Promise<Reconstruction>
}
```READMEEOF