import os
from datagrid_ai import Datagrid

client = Datagrid(
    api_key=os.environ.get("DATAGRID_API_KEY"),  # This is the default and can be omitted
)
batch_prediction = client.batch_predictions.create(
    items=[{
        "custom_id": "drawing_001",
        "file_id": "file_abc123",
        "page": 1,
    }, {
        "custom_id": "drawing_002",
        "file_id": "file_def456",
    }],
    model="gemini-2.5-flash",
    output_schema={
        "type": "object",
        "additionalProperties": False,
        "properties": {
            "project_name": {
                "type": "string"
            },
            "sheet_title": {
                "type": "string"
            },
            "revision": {
                "type": "string"
            },
        },
        "required": ["project_name", "sheet_title"],
    },
    prompt="Extract the project name, sheet title, and revision from this drawing.",
    completion_window="24h",
    metadata={
        "project": "alpha"
    },
)
print(batch_prediction.id)

{
  "object": "batch_prediction",
  "id": "bpred_abc123",
  "status": "completed",
  "model": "gemini-2.5-flash",
  "completion_window": "24h",
  "created_at": "2026-04-10T12:00:00.000Z",
  "expires_at": "2026-04-11T12:00:00.000Z",
  "in_progress_at": "2026-04-10T12:01:00.000Z",
  "finalizing_at": "2026-04-10T12:05:00.000Z",
  "completed_at": "2026-04-10T12:06:00.000Z",
  "failed_at": null,
  "cancelling_at": null,
  "cancelled_at": null,
  "expired_at": null,
  "request_counts": {
    "total": 2,
    "processing": 0,
    "succeeded": 2,
    "errored": 0,
    "canceled": 0,
    "expired": 0
  },
  "metadata": {
    "project": "alpha"
  },
  "error": null,
  "results_url": "/v1/batch-predictions/bpred_abc123/results"
}