> ## Documentation Index
> Fetch the complete documentation index at: https://www.everbility.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Uploads and transcription

> Create notes with Markdown, PDFs, and large audio uploads.

## Create a Markdown note

Use `POST /clients/{client_id}/notes` when you already have text content.

```bash theme={null}
curl -s \
  -X POST \
  -H "Authorization: Bearer <api_key>" \
  -H "Content-Type: application/json" \
  -d '{"title":"Case summary","markdown":"Session summary in Markdown"}' \
  "https://api.everbility.com/v1/public/clients/864/notes"
```

Response:

```json theme={null}
{
  "note_id": "67d5..."
}
```

## Upload a PDF

Use `POST /clients/{client_id}/notes/upload` for PDF files.

The endpoint returns a `job_id` immediately. Poll `GET /jobs/{job_id}` until the job completes.

## Upload a large audio file

Use `POST /clients/{client_id}/transcriptions/upload-large` for large audio files.

This reuses Everbility’s existing asynchronous transcription workflow.

The endpoint returns a `job_id` immediately. Poll `GET /jobs/{job_id}` until the job completes.

## Poll job status

Jobs return:

* `status`: `in_progress`, `completed`, or `failed`
* `progress`: current progress value
* `result`: completion payload when available

For completed PDF and audio jobs, `result.note_id` contains the created note ID.

Example:

```json theme={null}
{
  "job_id": "8a77...",
  "task_type": "transcript",
  "status": "completed",
  "progress": 100,
  "result": {
    "note_id": "67d5..."
  }
}
```

## What happens after upload

* PDF uploads create notes inside Everbility after processing finishes.
* Large audio uploads create transcribed notes inside Everbility after processing finishes.
* Those note IDs can then be used in report generation requests.