Update fastapi.md

docs/concepts/fastapi.md

@@ -49,13 +49,32 @@ def endpoint_function(data: UserData) -> UserDetail:
 `FastAPI` supports streaming responses, which is useful for returning large amounts of data. This feature is particularly useful when working with large language models (LLMs) that generate a large amount of data.
 
 ```python hl_lines="6-7"
+import instructor
+
+from fastapi import FastAPI
 from fastapi.responses import StreamingResponse
+from pydantic import BaseModel
+from openai import OpenAI
 from typing import Iterable
 
+# Enables response_model
+client = instructor.patch(OpenAI())
+app = FastAPI()
+
+class UserData(BaseModel):
+    # This can be the model for the input data
+    query: str
+
+class UserDetail(BaseModel):
+    name: str
+    age: int
+
+
 # Route to handle SSE events and return users
 @app.post("/extract", response_class=StreamingResponse)
 async def extract(data: UserData):
-    users = await client.chat.completions.create(
+
+    users = client.chat.completions.create(
         model="gpt-3.5-turbo",
         response_model=Iterable[UserDetail],
         stream=True,