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98 lines
2.9 KiB
Python
98 lines
2.9 KiB
Python
from pydantic import BaseModel, Field, model_validator, ValidationInfo
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from collections.abc import Generator
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class CitationMixin(BaseModel):
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"""
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Helpful mixing that can use `validation_context={"context": context}` in `from_response` to find the span of the substring_phrase in the context.
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## Usage
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```python
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from pydantic import BaseModel, Field
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from instructor import CitationMixin
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class User(BaseModel):
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name: str = Field(description="The name of the person")
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age: int = Field(description="The age of the person")
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role: str = Field(description="The role of the person")
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context = "Betty was a student. Jason was a student. Jason is 20 years old"
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user = openai.ChatCompletion.create(
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model="gpt-3.5-turbo",
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messages=[
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{
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"role": "user",
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"content": "Extract jason from {context}",
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},
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response_model=User,
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validation_context={"context": context},
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]
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)
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for quote in user.substring_quotes:
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assert quote in context
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print(user.model_dump())
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```
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## Result
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```
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{
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"name": "Jason Liu",
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"age": 20,
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"role": "student",
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"substring_quotes": [
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"Jason was a student",
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"Jason is 20 years old",
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]
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}
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```
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"""
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substring_quotes: list[str] = Field(
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description="List of unique and specific substrings of the quote that was used to answer the question.",
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)
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@model_validator(mode="after") # type: ignore[misc]
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def validate_sources(self, info: ValidationInfo) -> "CitationMixin":
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"""
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For each substring_phrase, find the span of the substring_phrase in the context.
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If the span is not found, remove the substring_phrase from the list.
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"""
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if info.context is None:
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return self
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# Get the context from the info
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text_chunks = info.context.get("context", None)
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# Get the spans of the substring_phrase in the context
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spans = list(self.get_spans(text_chunks))
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# Replace the substring_phrase with the actual substring
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self.substring_quotes = [text_chunks[span[0] : span[1]] for span in spans]
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return self
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def _get_span(
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self, quote: str, context: str, errs: int = 5
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) -> Generator[tuple[int, int], None, None]:
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import regex
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minor = quote
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major = context
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errs_ = 0
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s = regex.search(f"({minor}){{e<={errs_}}}", major)
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while s is None and errs_ <= errs:
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errs_ += 1
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s = regex.search(f"({minor}){{e<={errs_}}}", major)
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if s is not None:
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yield from s.spans()
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def get_spans(self, context: str) -> Generator[tuple[int, int], None, None]:
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for quote in self.substring_quotes:
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yield from self._get_span(quote, context)
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