참고소스 수정본

참고/instructor-main/examples/validated-multiclass/run.py

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+from pydantic import BaseModel, ValidationInfo, model_validator
+import openai
+import instructor
+import asyncio
+
+client = instructor.from_openai(
+    openai.AsyncOpenAI(),
+)
+
+
+class Tag(BaseModel):
+    id: int
+    name: str
+
+    @model_validator(mode="after")
+    def validate_ids(self, info: ValidationInfo):
+        context = info.context
+        if context:
+            tags: list[Tag] = context.get("tags")
+            assert self.id in {tag.id for tag in tags}, (
+                f"Tag ID {self.id} not found in context"
+            )
+            assert self.name in {tag.name for tag in tags}, (
+                f"Tag name {self.name} not found in context"
+            )
+        return self
+
+
+class TagWithInstructions(Tag):
+    instructions: str
+
+
+class TagRequest(BaseModel):
+    texts: list[str]
+    tags: list[TagWithInstructions]
+
+
+class TagResponse(BaseModel):
+    texts: list[str]
+    predictions: list[Tag]
+
+
+async def tag_single_request(text: str, tags: list[Tag]) -> Tag:
+    allowed_tags = [(tag.id, tag.name) for tag in tags]
+    allowed_tags_str = ", ".join([f"`{tag}`" for tag in allowed_tags])
+    return await client.chat.completions.create(
+        model="gpt-4-turbo-preview",
+        messages=[
+            {
+                "role": "system",
+                "content": "You are a world-class text tagging system.",
+            },
+            {"role": "user", "content": f"Describe the following text: `{text}`"},
+            {
+                "role": "user",
+                "content": f"Here are the allowed tags: {allowed_tags_str}",
+            },
+        ],
+        response_model=Tag,
+        # Minizises the hallucination of tags that are not in the allowed tags.
+        validation_context={"tags": tags},
+    )
+
+
+async def tag_request(request: TagRequest) -> TagResponse:
+    predictions = await asyncio.gather(
+        *[tag_single_request(text, request.tags) for text in request.texts]
+    )
+    return TagResponse(
+        texts=request.texts,
+        predictions=predictions,
+    )
+
+
+if __name__ == "__main__":
+    # Tags will be a range of different topics.
+    # Such as personal, phone, email, etc.
+    tags = [
+        TagWithInstructions(id=0, name="personal", instructions="Personal information"),
+        TagWithInstructions(id=1, name="phone", instructions="Phone number"),
+        TagWithInstructions(id=2, name="email", instructions="Email address"),
+        TagWithInstructions(id=3, name="address", instructions="Address"),
+        TagWithInstructions(id=4, name="Other", instructions="Other information"),
+    ]
+
+    # Texts will be a range of different questions.
+    # Such as "How much does it cost?", "What is your privacy policy?", etc.
+    texts = [
+        "What is your phone number?",
+        "What is your email address?",
+        "What is your address?",
+        "What is your privacy policy?",
+    ]
+
+    # The request will contain the texts and the tags.
+    request = TagRequest(texts=texts, tags=tags)
+
+    # The response will contain the texts, the predicted tags, and the confidence.
+    response = asyncio.run(tag_request(request))
+    print(response.model_dump_json(indent=2))