Fix custom plugin downloaders

Change get_as_dataframe call signature

src/gisaf/api/download.py

@@ -9,11 +9,13 @@ from sqlalchemy.orm import selectinload, joinedload
 
 from gisaf.database import pandas_query, fastapi_db_session as db_session
 from gisaf.models.geo_models_base import GeoModel, PlottableModel
+from gisaf.models.info import Downloader
 from gisaf.security import (
     Token, authenticate_user, get_current_active_user, create_access_token,
     )
 from gisaf.models.authentication import (User, UserRead, Role, RoleRead)
 from gisaf.registry import registry, NotInRegistry
+from gisaf.plugins import DownloadResponse, manager as plugin_manager
 
 logger = logging.getLogger(__name__)
 
@@ -47,7 +49,8 @@ async def download_csv(
     if custom_getter:
         df = await custom_getter(model_id)
     else:
-        df = await values_model.get_as_dataframe(model_id=model_id, with_only_columns=[value])
+        item = await db_session.get(model, model_id)
+        df = await values_model.get_as_dataframe(item=item, with_only_columns=[value])
     if len(df) == 0:
         raise HTTPException(status.HTTP_204_NO_CONTENT)
     if resample and resample != '0':
@@ -75,3 +78,49 @@ async def download_csv(
                                     'Content-Disposition': f"attachment; filename={filename}"
                                  })
     return response
+
+
+@api.get('/plugin/{name}/{store}/{id}')
+async def execute_action(
+        name: str,
+        store: str,
+        id: int,
+        db_session: db_session,
+        user: Annotated[UserRead, Depends(get_current_active_user)]
+    ):
+    """
+    Download the result of an action
+    """
+    ## TODO: implement permissions for actions
+    #await check_permission(info.context['request'], 'action')
+    try:
+        store_record = registry.stores.loc[store]
+        model: type[GeoModel] = store_record.model
+        values_model = registry.values_for_model[model][0]
+    except KeyError:
+        raise HTTPException(status_code=status.HTTP_404_NOT_FOUND)
+    item = await db_session.get(model, id)
+    dls: list[Downloader] = [dl for dl in plugin_manager.downloaders_stores[store]
+                                  if dl.name == name]
+    if len(dls) == 0:
+        raise HTTPException(status.HTTP_501_NOT_IMPLEMENTED,
+                            detail=f'No downloader {name} for {store}')
+    elif len(dls) > 1:
+        raise HTTPException(status.HTTP_500_INTERNAL_SERVER_ERROR,
+                            detail=f'Too many downloaders ({len(dls)}) {name} for {store}')
+    downloader = dls[0]
+    result: DownloadResponse
+    try:
+        result = await downloader._plugin.execute(model, item)
+    except Exception as err:
+        logging.exception(err)
+        raise HTTPException(status.HTTP_500_INTERNAL_SERVER_ERROR,
+                            detail=f'Error in action: {err.args[0]}'
+        )
+    return StreamingResponse(
+        iter([result.content]),
+        headers = {
+            'Content-Disposition': f'attachment; filename="{result.file_name}"'
+        },
+        media_type=result.content_type,
+    )

src/gisaf/api/main.py

@@ -178,11 +178,14 @@ async def get_model_list(
     return resp
 
 @api.get('/{store_name}/values/{value}')
-async def get_model_values(store_name: str, value: str,
-                           response: Response,
-                           where: str,
-                           resample: str | None = None,
-                           ):
+async def get_model_values(
+    db_session: db_session,
+    store_name: str,
+    value: str,
+    response: Response,
+    where: str,
+    resample: str | None = None,
+    ):
     """
     Get values
     """
@@ -202,7 +205,8 @@ async def get_model_values(store_name: str, value: str,
     if getter:
         df = await getter(model_id)
     else:
-        df = await values_model.get_as_dataframe(model_id=model_id,
+        item = await db_session.get(model, model_id)
+        df = await values_model.get_as_dataframe(item=item,
                                                  with_only_columns=[value])
 
     if len(df) == 0: