app.py

import gradio as gr
import re
import logging
from typing import Tuple, Optional

logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

def extract_comment_data(comment_text: str) -> Tuple[Optional[str], Optional[str], int, int]:
    """Извлекает данные из комментария"""
    try:
        # Пропускаем информацию о посте
        if 'отметок "Нравится"' in comment_text:
            return None, None, 0, 0

        # Извлекаем имя пользователя
        username_match = re.search(r"Фото профиля ([^\n]+)", comment_text)
        if not username_match:
            return None, None, 0, 0
        
        username = username_match.group(1).strip()
        
        # Извлекаем текст комментария
        lines = comment_text.split('\n')
        comment = ""
        for i, line in enumerate(lines):
            if username in line and i + 1 < len(lines):
                comment = lines[i + 1].strip()
                # Очищаем комментарий
                comment = re.sub(r'\d+\s*(?:ч\.|нед\.)\s*$', '', comment)
                comment = re.sub(r'"Нравится":\s*\d+\s*Ответить\s*$', '', comment)
                break
        
        # Извлекаем лайки
        likes_match = re.search(r'"Нравится":\s*(\d+)', comment_text)
        likes = int(likes_match.group(1)) if likes_match else 0
        
        # Извлекаем время
        time_match = re.search(r'(\d+)\s*(?:ч\.|нед\.)', comment_text)
        time = int(time_match.group(1)) if time_match else 0
        
        return username, comment.strip(), likes, time

    except Exception as e:
        logger.error(f"Error extracting data: {e}")
        return None, None, 0, 0

def analyze_post(content_type: str, link: str, post_likes: int, 
                post_date: str, description: str, comment_count: int, 
                all_comments: str) -> Tuple[str, str, str, str, str]:
    """Анализирует пост и комментарии"""
    try:
        # Разделяем на блоки комментариев
        blocks = re.split(r'(?=Фото профиля)', all_comments)
        blocks = [b.strip() for b in blocks if b.strip()]
        
        comments_data = []
        
        # Обрабатываем каждый блок
        for block in blocks:
            username, comment, likes, time = extract_comment_data(block)
            if username and comment:
                comments_data.append({
                    'username': username,
                    'comment': comment,
                    'likes': likes,
                    'time': time
                })

        # Формируем выходные данные
        usernames = "\n".join(item['username'] for item in comments_data)
        comments = "\n".join(item['comment'] for item in comments_data)
        likes = "\n".join(str(item['likes']) for item in comments_data)
        total_likes = sum(item['likes'] for item in comments_data)

        analytics = f"""
        📊 Анализ комментариев:
        Всего комментариев: {len(comments_data)}
        Уникальных пользователей: {len(set(item['username'] for item in comments_data))}
        Общее количество лайков: {total_likes}
        """

        return analytics, usernames, comments, likes, str(total_likes)

    except Exception as e:
        logger.error(f"Analysis error: {e}")
        return str(e), "", "", "", "0"

# Интерфейс Gradio
iface = gr.Interface(
    fn=analyze_post,
    inputs=[
        gr.Radio(choices=["Photo", "Video"], label="Content Type", value="Photo"),
        gr.Textbox(label="Link to Post"),
        gr.Number(label="Likes", value=0),
        gr.Textbox(label="Post Date"),
        gr.Textbox(label="Description", lines=3),
        gr.Number(label="Comment Count", value=0),
        gr.Textbox(label="Comments", lines=10)
    ],
    outputs=[
        gr.Textbox(label="Analytics Summary", lines=10),
        gr.Textbox(label="Usernames"),
        gr.Textbox(label="Comments"),
        gr.Textbox(label="Likes Chronology"),
        gr.Textbox(label="Total Likes on Comments")
    ],
    title="Instagram Comment Analyzer",
    description="Анализатор комментариев Instagram"
)

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