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from typing import List, Optional
from pydantic import BaseModel, Field
class RerankRequest(BaseModel):
"""
Request model for document reranking.
Attributes:
query: The search query
documents: List of documents to rerank
model_id: Identifier of the reranking model to use
instruction: Optional instruction for instruction-based models
top_k: Maximum number of documents to return (optional)
"""
query: str = Field(..., description="Search query text")
documents: List[str] = Field(..., min_items=1, description="List of documents to rerank")
model_id: Optional[str] = Field(..., description="Model identifier for reranking")
instruction: Optional[str] = Field(None, description="Optional instruction for reranking task")
top_k: Optional[int] = Field(None, description="Maximum number of results to return")
class RerankResult(BaseModel):
"""
Single reranking result.
Attributes:
text: The document text
score: Relevance score from the reranking model
index: Original index of the document in input list
"""
text: str
score: float
index: int
class RerankResponse(BaseModel):
"""
Response model for document reranking.
Attributes:
results: List of reranked documents with scores
query: The original search query
model_id: Identifier of the model used
processing_time: Time taken to process the request
total_documents: Total number of input documents
returned_documents: Number of documents returned
"""
results: List[RerankResult]
query: str
model_id: str
processing_time: float
total_documents: int
returned_documents: int
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