app/models.py

from pydantic import BaseModel, Field
from typing import List, Optional, Annotated


class EmbedQueryIn(BaseModel):
    text: Annotated[str, Field(..., min_length=1)]


class EmbedQueryOut(BaseModel):
    model: str
    dim: int
    embedding: List[float]


class SearchIn(BaseModel):
    query: Annotated[str, Field(min_length=1)]
    top_k: int = Field(5, ge=1, le=20)
    rerank: bool = True
    include_chunks: bool = False  # New field to control chunk inclusion in response


class ChunkHit(BaseModel):
    id: int
    source: Optional[str] = None
    page: Optional[int] = None
    chunk_index: Optional[int] = None
    score: float
    rerank_score: Optional[float] = None
    text: str


class SearchOut(BaseModel):
    query: str
    answer: str                          
    hits: Optional[List[ChunkHit]] = None  





# from pydantic import BaseModel, Field
# from typing import List, Optional, Annotated

# class EmbedQueryIn(BaseModel):
#     text: Annotated[str, Field(..., min_length=1, description="User question or query text")]

# class EmbedQueryOut(BaseModel):
#     model: str
#     dim: int
#     embedding: List[float]

# class SearchIn(BaseModel):
#     query: Annotated[str, Field(min_length=1)]
#     top_k: int = Field(5, ge=1, le=20)
#     rerank: bool = True

# class ChunkHit(BaseModel):
#     id: int
#     source: str
#     page: int
#     chunk_index: int
#     score: float
#     rerank_score: Optional[float] = None
#     text: str

# class SearchOut(BaseModel):
#     query: str
#     top_k: int
#     rerank: bool
#     hits: List[ChunkHit]



# class SearchAnswerOut(BaseModel):
#     query: str
#     answer: str