diff --git a/bindings/ceylon/examples/llm/app.py b/bindings/ceylon/examples/llm/process_llm_app.py
similarity index 94%
rename from bindings/ceylon/examples/llm/app.py
rename to bindings/ceylon/examples/llm/process_llm_app.py
index 655c0da..0482e68 100644
--- a/bindings/ceylon/examples/llm/app.py
+++ b/bindings/ceylon/examples/llm/process_llm_app.py
@@ -2,7 +2,7 @@
 
 from ceylon.llm.agent import LLMConfig, LLMAgent
 from ceylon.llm.models.ollama import OllamaModel
-from ceylon.processor.agent import ProcessWorker, ProcessRequest, ProcessResponse
+from ceylon.processor.agent import ProcessRequest, ProcessResponse
 from ceylon.processor.playground import ProcessPlayGround
 
 
@@ -46,3 +46,4 @@ async def main():
 
 if __name__ == "__main__":
     asyncio.run(main())
+
diff --git a/bindings/ceylon/examples/llm/task_llm_app.py b/bindings/ceylon/examples/llm/task_llm_app.py
new file mode 100644
index 0000000..2be90dd
--- /dev/null
+++ b/bindings/ceylon/examples/llm/task_llm_app.py
@@ -0,0 +1,52 @@
+import asyncio
+
+from ceylon.llm.agent import LLMConfig, LLMAgent
+from ceylon.llm.models.ollama import OllamaModel
+from ceylon.processor.agent import ProcessRequest, ProcessResponse
+from ceylon.processor.playground import ProcessPlayGround
+from ceylon.task.data import Task, TaskResult
+from ceylon.task.playground import TaskProcessingPlayground
+
+
+async def main():
+    # Create playground and worker
+    playground = TaskProcessingPlayground()
+    llm_model = OllamaModel(
+        model_name="deepseek-r1:8b",
+        base_url="http://localhost:11434"
+    )
+
+    # Configure LLM agent
+    llm_config = LLMConfig(
+        system_prompt=(
+            "You are an expert content writer specializing in technology topics. "
+        ),
+        temperature=0.7,
+        max_tokens=1000,
+        retry_attempts=1
+    )
+
+    # Create LLM agent
+    llm_agent = LLMAgent(
+        name="writer_1",
+        llm_model=llm_model,
+        config=llm_config,
+        role="writer"
+    )
+
+    # Start the system
+    async with playground.play(workers=[llm_agent]) as active_playground:
+        active_playground: TaskProcessingPlayground = active_playground
+        # Send some test requests
+        response: TaskResult = await active_playground.add_and_execute_task(
+            Task(
+                name="Process Data 1",
+                processor="writer",
+                input_data={"request": "A Simple title for a blog post about AI"}
+            )
+        )
+        print(f"Response received: {response.output}")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())