import os
import time
import requests
import re
import pandas as pd
import plotly.express as px
import gradio as gr
from dotenv import load_dotenv
from scripts.review_summarizer import analyze_reviews

load_dotenv()
GEMINI_API_KEY = os.getenv('GEMINI_API_KEY')

if not os.path.exists("data"):
    os.makedirs("data")

def create_sentiment_plot(df):
    """Creates a pie chart visualization for sentiment distribution"""
    sentiment_counts = df["sentiment_label"].value_counts()
    fig = px.pie(
        values=sentiment_counts.values,
        names=sentiment_counts.index,
        title="Duygu Analizi Dağılımı",
        color_discrete_map={
            "Pozitif": "#2ecc71",
            "Nötr": "#95a5a6",
            "Negatif": "#e74c3c",
        },
    )
    return fig

def create_star_plot(df):
    """Creates a bar chart visualization for star rating distribution"""
    star_counts = df["Yıldız Sayısı"].value_counts().sort_index()
    fig = px.bar(
        x=star_counts.index,
        y=star_counts.values,
        title="Yıldız Dağılımı",
        labels={"x": "Yıldız Sayısı", "y": "Yorum Sayısı"},
        color_discrete_sequence=["#f39c12"],
    )
    fig.update_layout(
        xaxis=dict(
            tickmode="array",
            ticktext=["⭐", "⭐⭐", "⭐⭐⭐", "⭐⭐⭐⭐", "⭐⭐⭐⭐⭐"],
        )
    )
    return fig

def scrape_product_comments_v2(url):
    headers = {
        "accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7",
        "accept-language": "en-US,en;q=0.9",
        "cache-control": "max-age=0",
        "upgrade-insecure-requests": "1",
        "user-agent": "Mozilla/5.0 (iPad; CPU OS 14_6_1 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) FxiOS/129.0 Mobile/15E148 Safari/605.1.15"
    }

    # Extract product_id using regex
    match = re.search(r"-p-(\d+)", url)
    if not match:
        raise ValueError("Product ID not found in URL")
    
    product_id = match.group(1)
    api_url = f"https://apigw.trendyol.com/discovery-web-websfxsocialreviewrating-santral/product-reviews-detailed?contentId={product_id}&page=1&order=DESC&orderBy=Score&channelId=1"

    def fetch_reviews(api_url, headers):
        all_reviews = []
        response = requests.get(api_url, headers=headers)
        if response.status_code != 200:
            raise ConnectionError(f"Initial request failed: {response.status_code}")
        
        data = response.json()
        total_pages = data["result"]["productReviews"]["totalPages"]
        all_reviews.extend(data["result"]["productReviews"]["content"])

        for page in range(2, total_pages + 1):
            paginated_url = api_url.replace("page=1", f"page={page}")
            response = requests.get(paginated_url, headers=headers)
            if response.status_code == 200:
                page_data = response.json()
                all_reviews.extend(page_data["result"]["productReviews"]["content"])
            else:
                print(f"Failed to fetch page {page}: {response.status_code}")

        return all_reviews

    reviews = fetch_reviews(api_url, headers)
    reviews_df = pd.DataFrame(reviews)
    reviews_df = reviews_df.rename(columns={
        "id": "Kullanıcı_id",
        "userFullName": "Kullanıcı Adı",
        "comment": "Yorum",
        "lastModifiedDate": "Tarih",
        "rate": "Yıldız Sayısı"
    })
    reviews_df = reviews_df[["Kullanıcı_id", "Kullanıcı Adı", "Yorum", "Tarih", "Yıldız Sayısı"]]
    return reviews_df

def analyze_product(url, progress=gr.Progress()):
    try:
        # Fetch reviews
        progress(0.1, desc="Yorumlar çekiliyor...")
        df = scrape_product_comments_v2(url)
        
        if df is None or len(df) == 0:
            return None, None, None, None, None, None, None, "Yorumlar çekilemedi. URL'yi kontrol edin."

        # Save to CSV
        data_path = os.path.join("data", "product_comments.csv")
        df.to_csv(data_path, index=False, encoding="utf-8-sig")

        # Analyze reviews
        progress(0.4, desc="Yorumlar analiz ediliyor...")
        summary, analyzed_df = analyze_reviews(data_path, GEMINI_API_KEY)

        progress(0.7, desc="Sonuçlar hazırlanıyor...")
        
        # Calculate metrics
        total_reviews = len(df)
        total_analyzed = len(analyzed_df)
        avg_rating = f"{analyzed_df['Yıldız Sayısı'].mean():.1f}⭐"
        positive_ratio = len(analyzed_df[analyzed_df["sentiment_label"] == "Pozitif"]) / len(analyzed_df) * 100
        positive_ratio_str = f"%{positive_ratio:.1f}"
        
        # Create plots
        sentiment_plot = create_sentiment_plot(analyzed_df)
        star_plot = create_star_plot(analyzed_df)
        
        # Create info message for removed reviews
        removed_reviews = total_reviews - total_analyzed
        info_message = ""
        if removed_reviews > 0:
            info_message = f"Not: Toplam {removed_reviews} adet kargo, teslimat ve satıcı ile ilgili yorum analiz dışı bırakılmıştır."

        progress(1.0, desc="Analiz tamamlandı!")
        
        return (
            str(total_reviews),
            str(total_analyzed),
            avg_rating,
            positive_ratio_str,
            sentiment_plot,
            star_plot,
            summary,
            info_message
        )
        
    except Exception as e:
        return None, None, None, None, None, None, None, f"Bir hata oluştu: {str(e)}"

# Create Gradio interface
with gr.Blocks(title="Trendyol Yorum Analizi") as demo:
    gr.Markdown("""
    # Trendyol Yorum Analizi
    
    Bu uygulama, Trendyol ürün sayfasındaki yorumları çeker, analiz eder ve özetler.
    """)
    
    with gr.Row():
        url_input = gr.Textbox(
            label="Trendyol Ürün Yorumları URL",
            placeholder="ürünün linki"
        )
    
    analyze_btn = gr.Button("Analiz Et")
    
    with gr.Row():
        total_reviews = gr.Textbox(label="Toplam Yorum")
        total_analyzed = gr.Textbox(label="Ürün Değerlendirme Sayısı")
        avg_rating = gr.Textbox(label="Ortalama Puan")
        positive_ratio = gr.Textbox(label="Olumlu Yorum Oranı")
    

    
    summary = gr.Markdown(label="📝 Genel Değerlendirme")
    info_message = gr.Markdown()
    
    with gr.Row():
        sentiment_plot = gr.Plot()
        star_plot = gr.Plot()
    
    error_message = gr.Markdown()
    
    analyze_btn.click(
        analyze_product,
        inputs=[url_input],
        outputs=[
            total_reviews,
            total_analyzed,
            avg_rating,
            positive_ratio,
            sentiment_plot,
            star_plot,
            summary,
            error_message
        ]
    )

if __name__ == "__main__":
    demo.launch()