from fastapi import APIRouter, Depends
from src.core.use_cases.analytics_use_case import AnalyticsUseCase
from src.core.ports.vector_store_port import VectorStorePort
from src.api.dependencies import get_analytics_use_case, get_vector_store_port

router = APIRouter()

@router.get("/sentiment")
def get_sentiment(analytics_use_case: AnalyticsUseCase = Depends(get_analytics_use_case)):
    query = """
    SELECT 
        entity, 
        avg(sentiment_score) as avg_sentiment, 
        count() as mention_count
    FROM sentiment_results
    GROUP BY entity
    ORDER BY mention_count DESC
    LIMIT 10
    """
    results = analytics_use_case.execute_raw_query(query)
    if not results or "error" in results:
        return {"error": "Could not fetch sentiment."}
    
    data = []
    for row in results.get("rows", []):
        data.append({
            "entity": row[0],
            "avg_sentiment": float(row[1]),
            "mention_count": int(row[2])
        })
    return {"data": data}

@router.get("/trends")
def get_trends(
    days: int = 7, 
    analytics_use_case: AnalyticsUseCase = Depends(get_analytics_use_case)
):
    results = analytics_use_case.get_trends(days)
    if not results or "error" in results:
        return {"error": "Could not fetch trends."}
        
    data = []
    for row in results.get("rows", []):
        data.append({
            "topic": row[0],
            "momentum": float(row[1]),
            "volume": int(row[2])
        })
    return {"data": data}

@router.get("/articles-over-time")
def get_articles_over_time(
    days: int = 30, 
    analytics_use_case: AnalyticsUseCase = Depends(get_analytics_use_case)
):
    query = f"""
    SELECT 
        toDate(scraped_at) as date,
        count() as article_count
    FROM sentiment_results
    GROUP BY date
    ORDER BY date ASC
    """
    results = analytics_use_case.execute_raw_query(query)
    if not results or "error" in results:
        return {"error": "Could not fetch articles over time."}
        
    data = []
    for row in results.get("rows", []):
        data.append({
            "date": str(row[0]),
            "count": int(row[1])
        })
    return {"data": data}

@router.get("/source-stats")
def get_source_stats(analytics_use_case: AnalyticsUseCase = Depends(get_analytics_use_case)):
    query = """
    SELECT 
        source, 
        count() as article_count,
        avg(sentiment_score) as avg_sentiment
    FROM sentiment_results
    GROUP BY source
    ORDER BY article_count DESC
    """
    results = analytics_use_case.execute_raw_query(query)
    if not results or "error" in results:
        return {"error": "Could not fetch source stats."}
        
    data = []
    for row in results.get("rows", []):
        data.append({
            "source": row[0],
            "article_count": int(row[1]),
            "avg_sentiment": float(row[2])
        })
    return {"data": data}

@router.get("/pipeline-stats")
def get_pipeline_stats(
    analytics_use_case: AnalyticsUseCase = Depends(get_analytics_use_case),
    vector_store: VectorStorePort = Depends(get_vector_store_port)
):
    qdrant_stats = vector_store.get_collection_stats()
    
    query = "SELECT count() FROM sentiment_results"
    ch_res = analytics_use_case.execute_raw_query(query)
    
    ch_count = 0
    if ch_res and not "error" in ch_res and ch_res.get("rows"):
        ch_count = int(ch_res["rows"][0][0])
    
    return {
        "total_articles_in_vector_db": qdrant_stats.get("vectors_count", 0) if qdrant_stats else 0,
        "total_sentiment_results": ch_count
    }