# Vector-sync HTTP embedding provider

This provider supports two endpoints:

- `POST {baseUrl}/vector-sync` for single-text requests
- `POST {baseUrl}/vectorize-batch` for batch document requests

## Single request

Request body:
```json
{
  "model": "intfloat/multilingual-e5-large",
  "text": "This is a sample text to vectorize"
}
```

## Batch request

Request body:
```json
{
  "model": "intfloat/multilingual-e5-large",
  "truncate_text": false,
  "truncate_length": 512,
  "chunk_size": 20,
  "items": [
    {
      "id": "2f48fd5c-9d39-4d80-9225-ea0c59c77c9a",
      "text": "This is a sample text to vectorize"
    }
  ]
}
```

## Provider configuration

```yaml
batch-request:
  truncate-text: false
  truncate-length: 512
  chunk-size: 20
```

These values are used for `/vectorize-batch` calls and can also be overridden per request via `EmbeddingRequest.providerOptions()`.

## Orchestrator batch processing

To let `RepresentationEmbeddingOrchestrator` send multiple representations in one provider call, enable batch processing for jobs and for the model:

```yaml
dip:
  embedding:
    jobs:
      enabled: true
      process-in-batches: true
      execution-batch-size: 20

    models:
      e5-default:
        supports-batch: true
```

Notes:
- jobs are grouped by `modelKey`
- non-batch-capable models still fall back to single-item execution
- `execution-batch-size` controls how many texts are sent in one `/vectorize-batch` request