Spaces:
Running
Running
File size: 1,413 Bytes
590a604 ee1a8a3 1fbc47b a18e93d 1fbc47b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 |
"""
API routes for LexiMind.
Defines REST endpoints for text analysis including summarization,
emotion detection, and topic classification.
Author: Oliver Perrin
Date: December 2025
"""
from typing import cast
from fastapi import APIRouter, Depends, HTTPException, status
from ..inference import EmotionPrediction, InferencePipeline, TopicPrediction
from .dependencies import get_pipeline
from .schemas import SummaryRequest, SummaryResponse
router = APIRouter()
@router.post("/summarize", response_model=SummaryResponse)
def summarize(
payload: SummaryRequest,
pipeline: InferencePipeline = Depends(get_pipeline), # noqa: B008
) -> SummaryResponse:
try:
outputs = pipeline.batch_predict([payload.text])
except Exception as exc: # noqa: BLE001 - surface inference error to client
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=str(exc),
) from exc
summaries = cast(list[str], outputs["summaries"])
emotion_preds = cast(list[EmotionPrediction], outputs["emotion"])
topic_preds = cast(list[TopicPrediction], outputs["topic"])
emotion = emotion_preds[0]
topic = topic_preds[0]
return SummaryResponse(
summary=summaries[0],
emotion_labels=emotion.labels,
emotion_scores=emotion.scores,
topic=topic.label,
topic_confidence=topic.confidence,
)
|