diff --git a/lib.py b/lib.py
index 75a4e80..4683941 100644
--- a/lib.py
+++ b/lib.py
@@ -4,6 +4,8 @@ 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
@@ -17,12 +19,15 @@ 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)
 
-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.
+def _generate_sync(prompt: str):
+    """Synchronous wrapper for generate_content_stream.
+
+    This function contains the blocking Google GenAI SDK call.
+    It should be run in a thread pool to avoid blocking the event loop.
 
     Args:
         prompt: The user's input prompt to generate content for.
@@ -30,9 +35,7 @@ async def generate(prompt: str):
     Yields:
         str: Text chunks from the generated response.
     """
-    client = genai.Client(
-        vertexai=True,
-    )
+    client = genai.Client(vertexai=True)
 
     contents = [
         types.Content(role="user", parts=[types.Part.from_text(text=prompt)]),
@@ -70,7 +73,7 @@ async def generate(prompt: str):
         ),
     )
 
-    async for chunk in client.models.generate_content_stream(
+    for chunk in client.models.generate_content_stream(
         model=GEMINI_MODEL,
         contents=contents,
         config=generate_content_config,
@@ -85,6 +88,26 @@ async def generate(prompt: str):
         yield chunk.text
 
 
-if __name__ == "__main__":
-    for chunk in generate("Come si calcola il rapporto sodio potassio?"):
-        print(chunk, end="")
+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