update name

models/label.py

@@ -1,98 +1 @@
-"""Pydantic schemas for key-point matching prediction endpoints"""
-
-from pydantic import BaseModel, Field, ConfigDict
-from typing import List, Optional, Dict
-
-
-class PredictionRequest(BaseModel):
-    """Request model for single key-point/argument prediction"""
-    model_config = ConfigDict(
-        json_schema_extra={
-            "example": {
-                "argument": "Climate change is accelerating due to industrial emissions.",
-                "key_point": "Human industry contributes significantly to global warming."
-            }
-        }
-    )
-
-    argument: str = Field(
-        ..., min_length=5, max_length=1000,
-        description="The argument text to evaluate"
-    )
-    key_point: str = Field(
-        ..., min_length=5, max_length=500,
-        description="The key point used for comparison"
-    )
-
-
-class PredictionResponse(BaseModel):
-    """Response model for single prediction"""
-    model_config = ConfigDict(
-        json_schema_extra={
-            "example": {
-                "prediction": 1,
-                "confidence": 0.874,
-                "label": "MATCH",
-                "probabilities": {
-                    "match": 0.874,
-                    "no_match": 0.126
-                }
-            }
-        }
-    )
-
-    prediction: int = Field(..., description="1 = match, 0 = no match")
-    confidence: float = Field(..., ge=0.0, le=1.0,
-                              description="Confidence score of the prediction")
-    label: str = Field(..., description="MATCH or NO_MATCH")
-    probabilities: Dict[str, float] = Field(
-        ..., description="Dictionary of class probabilities"
-    )
-
-
-class BatchPredictionRequest(BaseModel):
-    """Request model for batch predictions"""
-    model_config = ConfigDict(
-        json_schema_extra={
-            "example": {
-                "pairs": [
-                    {
-                        "argument": "Schools should implement AI tools to support learning.",
-                        "key_point": "AI can improve student engagement."
-                    },
-                    {
-                        "argument": "Governments must reduce plastic usage.",
-                        "key_point": "Plastic waste harms the environment."
-                    }
-                ]
-            }
-        }
-    )
-
-    pairs: List[PredictionRequest] = Field(
-        ..., max_length=100,
-        description="List of argument-keypoint pairs (max 100)"
-    )
-
-
-class BatchPredictionResponse(BaseModel):
-    """Response model for batch key-point predictions"""
-    predictions: List[PredictionResponse]
-    total_processed: int = Field(..., description="Number of processed items")
-
-
-class HealthResponse(BaseModel):
-    """Health check model for the API"""
-    model_config = ConfigDict(
-        json_schema_extra={
-            "example": {
-                "status": "ok",
-                "model_loaded": True,
-                "device": "cuda"
-            }
-        }
-    )
-    
-    status: str = Field(..., description="API health status")
-    model_loaded: bool = Field(..., description="Whether the model is loaded")
-    device: str = Field(..., description="Device used for inference (cpu/cuda)")
+c