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