"""Ollama embedding client with sqlite-vec storage — BSL licensed."""
from __future__ import annotations

import logging
import sqlite3
import struct
from pathlib import Path

import httpx

logger = logging.getLogger(__name__)

EMBEDDING_AVAILABLE: bool = False

try:
    import sqlite_vec  # type: ignore[import]  # noqa: F401
    EMBEDDING_AVAILABLE = True
    logger.debug("sqlite-vec loaded — embedding pipeline enabled")
except ImportError:
    logger.debug("sqlite-vec not available — embedding pipeline disabled")


def embed_chunks(
    db_path: Path,
    document_id: str,
    llm_url: str,
    model: str = "nomic-embed-text",
    timeout: float = 60.0,
) -> int:
    """Embed all unembedded chunks for a document. Returns count embedded. No-op when EMBEDDING_AVAILABLE is False."""
    if not EMBEDDING_AVAILABLE:
        return 0

    conn = sqlite3.connect(str(db_path))
    conn.execute("PRAGMA journal_mode=WAL")
    conn.row_factory = sqlite3.Row
    rows = conn.execute(
        "SELECT id, text FROM context_chunks WHERE document_id=? AND embedding IS NULL",
        (document_id,),
    ).fetchall()

    count = 0
    for row in rows:
        try:
            resp = httpx.post(
                f"{llm_url.rstrip('/')}/api/embeddings",
                json={"model": model, "prompt": row["text"]},
                timeout=timeout,
            )
            resp.raise_for_status()
            vector: list[float] = resp.json().get("embedding") or []
            if vector:
                blob = struct.pack(f"{len(vector)}f", *vector)
                conn.execute(
                    "UPDATE context_chunks SET embedding=? WHERE id=?",
                    (blob, row["id"]),
                )
                count += 1
        except Exception as exc:
            logger.warning("Embedding chunk %s failed: %s", row["id"], exc)

    conn.commit()
    conn.close()
    return count