"""FastAPI embeddings sidecar.

Exposes two endpoints backed by `fastembed`:
  POST /embed/dense   -> single vectors (sentence-transformers/all-MiniLM-L6-v2)
  POST /embed/colbert -> per-token matrices (colbert-ir/colbertv2.0)

Models are loaded lazily on first request and reused for the lifetime of the
process. The Next.js app calls this service via plain HTTP.
"""

from __future__ import annotations

import os
from contextlib import asynccontextmanager
from pathlib import Path
from typing import List

from dotenv import load_dotenv

# Load shared env from the parent project so HF_TOKEN, RAG_*_MODEL, etc. flow
# through without requiring the user to export them by hand.
_PARENT_ENV = Path(__file__).resolve().parent.parent / ".env.local"
if _PARENT_ENV.is_file():
    load_dotenv(_PARENT_ENV)

from fastapi import FastAPI
from pydantic import BaseModel
from fastembed import TextEmbedding, LateInteractionTextEmbedding

DENSE_MODEL = os.environ.get("RAG_DENSE_MODEL", "sentence-transformers/all-MiniLM-L6-v2")
LATE_MODEL = os.environ.get("RAG_LATE_MODEL", "colbert-ir/colbertv2.0")

_models: dict[str, object] = {}


def _dense() -> TextEmbedding:
    if "dense" not in _models:
        _models["dense"] = TextEmbedding(model_name=DENSE_MODEL)
    return _models["dense"]  # type: ignore[return-value]


def _colbert() -> LateInteractionTextEmbedding:
    if "colbert" not in _models:
        _models["colbert"] = LateInteractionTextEmbedding(model_name=LATE_MODEL)
    return _models["colbert"]  # type: ignore[return-value]


@asynccontextmanager
async def lifespan(_app: FastAPI):
    _dense()
    _colbert()
    yield


app = FastAPI(lifespan=lifespan)


class EmbedRequest(BaseModel):
    texts: List[str]


class DenseResponse(BaseModel):
    vectors: List[List[float]]
    model: str


class ColbertResponse(BaseModel):
    vectors: List[List[List[float]]]
    model: str


@app.get("/health")
def health():
    return {"ok": True, "dense_model": DENSE_MODEL, "late_model": LATE_MODEL}


@app.post("/embed/dense", response_model=DenseResponse)
def embed_dense(req: EmbedRequest):
    vectors = [v.tolist() for v in _dense().embed(req.texts)]
    return {"vectors": vectors, "model": DENSE_MODEL}


@app.post("/embed/colbert", response_model=ColbertResponse)
def embed_colbert(req: EmbedRequest):
    vectors = [v.tolist() for v in _colbert().embed(req.texts)]
    return {"vectors": vectors, "model": LATE_MODEL}


@app.post("/embed/colbert/query", response_model=ColbertResponse)
def embed_colbert_query(req: EmbedRequest):
    vectors = [v.tolist() for v in _colbert().query_embed(req.texts)]
    return {"vectors": vectors, "model": LATE_MODEL}