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https://github.com/hwchase17/langchain
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61f5ea4b5e
Co-authored-by: Nicholas Larus-Stone <7347808+nlarusstone@users.noreply.github.com> Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
32 lines
929 B
Python
32 lines
929 B
Python
import json
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from pydantic import BaseModel, Field, conint
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class LLMPlateResponse(BaseModel):
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row_start: conint(ge=0) = Field(
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..., description="The starting row of the plate (0-indexed)"
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)
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row_end: conint(ge=0) = Field(
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..., description="The ending row of the plate (0-indexed)"
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)
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col_start: conint(ge=0) = Field(
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..., description="The starting column of the plate (0-indexed)"
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)
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col_end: conint(ge=0) = Field(
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..., description="The ending column of the plate (0-indexed)"
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)
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contents: str
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def parse_llm_output(result: str):
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"""
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Based on the prompt we expect the result to be a string that looks like:
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'[{"row_start": 12, "row_end": 19, "col_start": 1, \
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"col_end": 12, "contents": "Entity ID"}]'
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We'll load that JSON and turn it into a Pydantic model
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"""
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return [LLMPlateResponse(**plate_r) for plate_r in json.loads(result)]
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