backend/crud/analysis.py

"""CRUD operations for analysis history."""

from datetime import datetime
from typing import Optional
from bson import ObjectId
from motor.motor_asyncio import AsyncIOMotorDatabase

from backend.core.schema import EnsembleResult
from backend.db.models import AnalysisHistoryDocument, AnalysisHistoryResponse


async def save_analysis(
    db: AsyncIOMotorDatabase,
    filename: str,
    result: EnsembleResult,
) -> str:
    """Save analysis result to MongoDB."""
    doc = AnalysisHistoryDocument.from_ensemble_result(filename, result)
    doc_dict = doc.model_dump(by_alias=False, exclude={"id"})

    result = await db.analysis_history.insert_one(doc_dict)
    return str(result.inserted_id)


async def get_analysis_by_id(
    db: AsyncIOMotorDatabase,
    analysis_id: str,
) -> Optional[dict]:
    """Get analysis by ID."""
    try:
        oid = ObjectId(analysis_id)
    except Exception:
        return None

    return await db.analysis_history.find_one({"_id": oid})


async def get_analysis_history(
    db: AsyncIOMotorDatabase,
    limit: int = 100,
    skip: int = 0,
    verdict: Optional[str] = None,
) -> list[dict]:
    """Get analysis history with optional filtering."""
    query = {}
    if verdict:
        query["verdict"] = verdict

    cursor = db.analysis_history.find(query).sort("created_at", -1).skip(skip).limit(limit)
    return await cursor.to_list(length=limit)


async def get_history_stats(db: AsyncIOMotorDatabase) -> dict:
    """Get summary statistics from analysis history."""
    pipeline = [
        {
            "$group": {
                "_id": "$verdict",
                "count": {"$sum": 1},
                "avg_confidence": {"$avg": "$confidence"},
                "avg_p_fake": {"$avg": "$p_fake"},
            }
        }
    ]

    stats = await db.analysis_history.aggregate(pipeline).to_list(length=None)
    return {item["_id"]: {
        "count": item["count"],
        "avg_confidence": round(item["avg_confidence"], 3),
        "avg_p_fake": round(item["avg_p_fake"], 3),
    } for item in stats}


async def delete_analysis(db: AsyncIOMotorDatabase, analysis_id: str) -> bool:
    """Delete analysis by ID."""
    try:
        oid = ObjectId(analysis_id)
    except Exception:
        return False

    result = await db.analysis_history.delete_one({"_id": oid})
    return result.deleted_count > 0