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# same content as your current classifier.py, but model name from settings
from __future__ import annotations
from typing import Optional
from pydantic import BaseModel, Field
from langchain_openai import ChatOpenAI
from langchain_core.prompts import ChatPromptTemplate, FewShotChatMessagePromptTemplate
from ..config.settings import settings
class ReportClassification(BaseModel):
category: str = Field(..., description="taxonomy id like 'crime.gunshot'")
label: str = Field(..., description="short human title")
description: Optional[str] = Field(None, description="one sentence, no emojis")
severity: Optional[str] = None
confidence: float = Field(..., ge=0, le=1)
CATEGORY_TO_ICON = {
"crime.gunshot": "3d-gun",
"crime.robbery": "3d-robbery",
"crime.sex_offender": "3d-sex",
"crime.suspicious": "3d-alert",
"incident.missing_person": "3d-user_search",
"incident.lost_item": "3d-search",
"incident.medical": "3d-ambulance",
"incident.car_accident": "3d-car",
"road.flood": "3d-flood",
"road.blocked": "3d-traffic",
"road.construction": "3d-construction",
"help.general": "3d-help",
"help.ride": "3d-ride",
"other.unknown": "3d-info",
}
SYSTEM = ("You classify short community reports into a strict taxonomy. "
"Return ONLY the schema fields. If unclear, choose other.unknown.")
EXAMPLES = [
{"input": "I heard gunshots near 5th and Pine!",
"output_json": '{"category":"crime.gunshot","label":"Gunshots reported","description":"Multiple shots heard near 5th and Pine.","severity":"high","confidence":0.9}'},
{"input": "Car crash blocking the left lane on I-66",
"output_json": '{"category":"incident.car_accident","label":"Car accident","description":"Crash reported blocking the left lane on I-66.","severity":"medium","confidence":0.85}'},
]
example_block = ChatPromptTemplate.from_messages([("human", "{input}"), ("ai", "{output_json}")])
prompt = ChatPromptTemplate.from_messages([
("system", SYSTEM),
FewShotChatMessagePromptTemplate(example_prompt=example_block, examples=EXAMPLES),
("human", "{text}"),
])
_model = ChatOpenAI(model=settings.OPENAI_MODEL_CLASSIFIER, temperature=0).with_structured_output(ReportClassification)
def classify_report_text(text: str) -> ReportClassification:
return (prompt | _model).invoke({"text": text})
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