diff --git a/appinfo/info.xml b/appinfo/info.xml
index dc002c8..553c246 100644
--- a/appinfo/info.xml
+++ b/appinfo/info.xml
@@ -27,6 +27,7 @@
 		</docker-install>
 		<scopes>
 			<value>AI_PROVIDERS</value>
+			<value>TASK_PROCESSING</value>
 		</scopes>
 		<system>false</system>
 	</external-app>
diff --git a/lib/main.py b/lib/main.py
index 408d4d2..d9af0df 100644
--- a/lib/main.py
+++ b/lib/main.py
@@ -3,6 +3,7 @@
 
 import queue
 import threading
+import time
 import typing
 from contextlib import asynccontextmanager
 from time import perf_counter
@@ -13,7 +14,7 @@
 from nc_py_api import AsyncNextcloudApp, NextcloudApp
 from nc_py_api.ex_app import LogLvl, anc_app, run_app, set_handlers
 
-chains = generate_chains()
+#chains = generate_chains()
 
 @asynccontextmanager
 async def lifespan(_app: FastAPI):
@@ -27,19 +28,29 @@ async def lifespan(_app: FastAPI):
 
 
 APP = FastAPI(lifespan=lifespan)
-TASK_LIST: queue.Queue = queue.Queue(maxsize=100)
 
 
 class BackgroundProcessTask(threading.Thread):
     def run(self, *args, **kwargs):  # pylint: disable=unused-argument
+        nc = NextcloudApp()
+
         while True:
-            task = TASK_LIST.get(block=True)
+            task = nc.providers.task_processing.next_task("core:text2text")
+
+            print(task)
+
+            # TODO: Load chain and execute task and report result
+
+            time.sleep(5)
+            continue
+
             try:
                 chain_name = task.get("chain")
                 print(f"chain: {chain_name}", flush=True)
+                """
                 chain_load = chains.get(chain_name)
                 if chain_load is None:
-                    NextcloudApp().providers.text_processing.report_result(
+                    NextcloudApp().providers.task_processing.report_result(
                         task["id"], error="Requested model is not available"
                     )
                     continue
@@ -49,8 +60,10 @@ def run(self, *args, **kwargs):  # pylint: disable=unused-argument
                 result = chain.invoke(task.get("prompt")).get("text")
                 del chain
                 print(f"reply generated: {perf_counter() - time_start}s", flush=True)
+                """
+                result = "test"
                 print(result, flush=True)
-                NextcloudApp().providers.text_processing.report_result(
+                NextcloudApp().providers.task_processing.report_result(
                     task["id"],
                     str(result).split(sep="<|assistant|>", maxsplit=1)[-1].strip(),
                 )
@@ -58,39 +71,20 @@ def run(self, *args, **kwargs):  # pylint: disable=unused-argument
                 print(str(e), flush=True)
                 nc = NextcloudApp()
                 nc.log(LogLvl.ERROR, str(e))
-                nc.providers.text_processing.report_result(task["id"], error=str(e))
-
-
-class Input(pydantic.BaseModel):
-    prompt: str
-    task_id: int
-
-
-@APP.post("/chain/{chain_name}")
-async def tiny_llama(
-    _nc: typing.Annotated[AsyncNextcloudApp, Depends(anc_app)],
-    req: Input,
-    chain_name=None,
-):
-    try:
-        TASK_LIST.put({"prompt": req.prompt, "id": req.task_id, "chain": chain_name}, block=False)
-    except queue.Full:
-        return responses.JSONResponse(content={"error": "task queue is full"}, status_code=429)
-    return responses.Response()
-
+                nc.providers.task_processing.report_result(task["id"], error=str(e))
 
 async def enabled_handler(enabled: bool, nc: AsyncNextcloudApp) -> str:
     print(f"enabled={enabled}", flush=True)
     if enabled is True:
-        for chain_name, _ in chains.items():
-            (model, task) = chain_name.split(":", 2)
-            await nc.providers.text_processing.register(
-                "llm2:"+chain_name, "Local Large language Model: " + model, "/chain/" + chain_name, task
-            )
+        #for chain_name, _ in chains.items():
+        #    (model, task) = chain_name.split(":", 2)
+        await nc.providers.task_processing.register(
+            "llm2:"+"test", "Local Large language Model: " + "test", "core:text2text"
+        )
     else:
-        for chain_name, chain in chains.items():
-            (model, task) = chain_name.split(":", 2)
-            await nc.providers.text_processing.unregister(model)
+        #for chain_name, chain in chains.items():
+        #    (model, task) = chain_name.split(":", 2)
+        await nc.providers.task_processing.unregister("test")
     return ""