init

README.md

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-# cloud
-Annoucing Instructor Cloud
+# ☁️ Instructor Cloud ☁️
+
+Introducing Instructor Cloud
+
+With Instructor Cloud, you can:
+
+- Extract models from any text with blazing speed 🚀
+- Stream extracted data in real-time
+- Rely on the power of GPT-4* to do your job for you! 🤖
+
+*GPT-4 not included. Accuracy not guaranteed. Use at your own risk.
+
+## Running FastAPI
+
+To run the FastAPI server, use the following command:
+
+```sh
+uvicorn run:app --reload
+```

requirements.txt

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+instructor
+fastapi
+pydantic
+uvicorn

run.py

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+from typing import List
+from fastapi import FastAPI
+from fastapi.responses import StreamingResponse
+from pydantic import BaseModel
+
+
+import instructor
+import openai
+
+app = FastAPI()
+client = instructor.from_openai(openai.OpenAI(), model="gpt-4-turbo-preview")
+
+
+class Property(BaseModel):
+    name: str
+    value: str
+
+
+class User(BaseModel):
+    name: str
+    age: int
+    properties: List[Property]
+
+
+@app.post("/v1/extract_user", response_model=User)
+def extract_user(text: str):
+    user = client.chat.completions.create(
+        messages=[
+            {"role": "user", "content": f"Extract user from `{text}`"},
+        ],
+        response_model=User,
+    )
+    return user
+
+
+@app.post("/v1/extract_user_stream")
+def extract_user_stream(text: str):
+    user_stream = client.chat.completions.create_partial(
+        messages=[
+            {"role": "user", "content": f"Extract user from `{text}`"},
+        ],
+        response_model=User,
+    )
+
+    def stream():
+        for partial_user in user_stream:
+            yield f"data: {partial_user.model_dump_json()}\n\n"
+
+    return StreamingResponse(stream(), media_type="text/event-stream")