참고소스 수정본

참고/instructor-main/examples/classification/multi_prediction.py

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+import enum
+import instructor
+
+from openai import OpenAI
+from pydantic import BaseModel
+
+client = instructor.from_openai(OpenAI())
+
+
+# Define new Enum class for multiple labels
+class MultiLabels(str, enum.Enum):
+    BILLING = "billing"
+    GENERAL_QUERY = "general_query"
+    HARDWARE = "hardware"
+
+
+# Adjust the prediction model to accommodate a list of labels
+class MultiClassPrediction(BaseModel):
+    predicted_labels: list[MultiLabels]
+
+
+# Modify the classify function
+def multi_classify(data: str) -> MultiClassPrediction:
+    return client.chat.completions.create(
+        model="gpt-4o-mini",
+        response_model=MultiClassPrediction,
+        messages=[
+            {
+                "role": "user",
+                "content": f"Classify the following support ticket: {data}",
+            },
+        ],
+    )  # type: ignore
+
+
+# Example using a support ticket
+ticket = (
+    "My account is locked and I can't access my billing info. Phone is also broken."
+)
+prediction = multi_classify(ticket)
+print(prediction)