reset parallelism

app.py

@@ -91,7 +91,7 @@ async def websocket_endpoint(websocket: WebSocket):
     while True:
         data = await websocket.receive_text()
 
-        async for chunk in generate(data):
+        for chunk in generate(data):
             await websocket.send_text(chunk)
 
         await websocket.send_text("<<END>>")

lib.py

@@ -4,8 +4,6 @@ This module provides functionality to generate content using Google's Gemini mod
 with Vertex AI RAG (Retrieval-Augmented Generation) support.
 """
 
-import asyncio
-from concurrent.futures import ThreadPoolExecutor
 from google import genai
 from google.genai import types
 from dotenv import load_dotenv
@@ -19,15 +17,15 @@ CORPUS: str = "projects/520464122471/locations/europe-west3/ragCorpora/230584300
 # Gemini model name
 GEMINI_MODEL: str = "gemini-3-pro-preview"
 
-# Thread pool for blocking API calls
-_executor = ThreadPoolExecutor(max_workers=10)
 
+def generate(prompt: str):
+    """Generate content using Gemini model with RAG retrieval.
 
-def _generate_sync(prompt: str):
+    This function creates a streaming response from the Gemini model,
-    """Synchronous wrapper for generate_content_stream.
+    augmented with content from the configured RAG corpus.
 
-    This function contains the blocking Google GenAI SDK call.
+    The blocking API call is run in a thread pool to allow concurrent
-    It should be run in a thread pool to avoid blocking the event loop.
+    processing of multiple WebSocket connections.
 
     Args:
         prompt: The user's input prompt to generate content for.
@@ -86,28 +84,3 @@ def _generate_sync(prompt: str):
             continue
 
         yield chunk.text
-
-
-async def generate(prompt: str):
-    """Generate content using Gemini model with RAG retrieval.
-
-    This function creates a streaming response from the Gemini model,
-    augmented with content from the configured RAG corpus.
-
-    The blocking API call is run in a thread pool to allow concurrent
-    processing of multiple WebSocket connections.
-
-    Args:
-        prompt: The user's input prompt to generate content for.
-
-    Yields:
-        str: Text chunks from the generated response.
-    """
-    loop = asyncio.get_running_loop()
-
-    # Run the synchronous generator in a thread pool to avoid blocking the event loop
-    sync_gen = await loop.run_in_executor(_executor, _generate_sync, prompt)
-
-    # Yield from the synchronous generator
-    for chunk in sync_gen:
-        yield chunk