from flask import Flask, request, jsonify import google.generativeai as genai import requests import threading import logging import time import datetime import os # Setup logging logging.basicConfig( level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s', handlers=[ logging.FileHandler("instagram_auto_reply.log"), logging.StreamHandler() ] ) logger = logging.getLogger() # Konfigurasi access_token = "IGAAbDRJqoXZAJBZAE9nSHJVZAWlZAVEpaQkdUb1hYc0pQbEp1SDUwT1dFZAVlBeHBmZAkVYbjBJRExoa3pPN3NyUkhraDdBVGs0WDlGV0EzRHVQZAlF3dVVHWVBvblEzeUY2QWRMMkZAhM2ZA4eTQxQ0E1S1ZAVNERwb1lYYXc1S0puZAERtQm5mSGJUVFMyN2ZA3" instagram_account_id = "9654344654586349" post_id = "18011605364714149" # Post ID yang sudah Anda dapatkan gemini_api_key = "AIzaSyA1HyFIryiUzwjvpGX1yGJ3uaHLf7sBvqY" POLLING_INTERVAL = 9 # 15 menit dalam detik # Pastikan file untuk menyimpan komentar yang telah dibalas sudah ada replied_comments_file = "replied_comments.txt" if not os.path.exists(replied_comments_file): with open(replied_comments_file, "w") as f: pass # Konfigurasi Gemini AI genai.configure(api_key=gemini_api_key) app = Flask(__name__) # Fungsi untuk mendapatkan komentar pada post tertentu def get_comments(post_id): url = f"https://graph.instagram.com/v18.0/{post_id}/comments" params = { "access_token": access_token, "fields": "id,text,timestamp,username" } try: response = requests.get(url, params=params) if response.status_code == 200: return response.json().get("data", []) else: logger.error(f"Error mendapatkan komentar: {response.text}") return [] except Exception as e: logger.error(f"Exception saat mengambil komentar: {str(e)}") return [] # Fungsi untuk membalas komentar def reply_to_comment(comment_id, message): url = f"https://graph.instagram.com/v18.0/{comment_id}/replies" params = { "access_token": access_token, "message": message } try: response = requests.post(url, params=params) if response.status_code == 200: return True, response.json() else: return False, response.text except Exception as e: logger.error(f"Exception saat membalas komentar: {str(e)}") return False, str(e) # Fungsi untuk mendapatkan respons AI dari Gemini def get_ai_response(username, comment_text): try: model = genai.GenerativeModel('gemini-2.5-pro-preview-03-25') prompt = f""" Buatkan balasan yang ramah, profesional dan singkat (maksimal 2 kalimat) untuk komentar Instagram berikut: Username: {username} Komentar: {comment_text} Balasan harus sopan, informatif, dan sesuai dengan konteks komentar. """ response = model.generate_content(prompt) return response.text.strip() except Exception as e: logger.error(f"Error saat generate AI response: {str(e)}") return "Terima kasih atas komentar Anda!" # Fallback response # Fungsi untuk menyimpan komentar yang sudah dibalas def save_replied_comments(comment_id): try: with open(replied_comments_file, "a") as file: file.write(f"{comment_id}\n") except Exception as e: logger.error(f"Error menyimpan comment ID: {str(e)}") # Fungsi untuk membaca komentar yang sudah dibalas def get_replied_comments(): try: with open(replied_comments_file, "r") as file: return [line.strip() for line in file.readlines()] except FileNotFoundError: # Jika file belum ada, buat file kosong with open(replied_comments_file, "w") as file: pass return [] # Logika utama untuk auto-reply def auto_reply_system(): current_time = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S") logger.info(f"Mulai proses auto-reply pada {current_time}") try: # Ambil komentar yang sudah pernah dibalas replied_comments = get_replied_comments() # Ambil semua komentar dari post comments = get_comments(post_id) logger.info(f"Mendapatkan {len(comments)} komentar") # Proses setiap komentar for comment in comments: comment_id = comment["id"] username = comment.get("username", "pengguna") comment_text = comment["text"] # Cek apakah komentar sudah pernah dibalas if comment_id not in replied_comments: logger.info(f"Memproses komentar baru dari {username}: '{comment_text}'") # Generate balasan dengan Gemini AI ai_reply = get_ai_response(username, comment_text) # Kirim balasan ke Instagram success, result = reply_to_comment(comment_id, ai_reply) if success: logger.info(f"Berhasil membalas komentar dengan: '{ai_reply}'") # Catat komentar yang sudah dibalas save_replied_comments(comment_id) else: logger.error(f"Gagal membalas komentar: {result}") # Tunggu sebentar agar tidak terkena rate limit time.sleep(5) else: logger.debug(f"Komentar dari {username} sudah pernah dibalas sebelumnya") logger.info(f"Proses auto-reply selesai") return {"status": "success", "processed_comments": len(comments)} except Exception as e: logger.error(f"Error dalam auto_reply_system: {str(e)}") return {"status": "error", "message": str(e)} # Background task untuk polling def background_polling(): while True: try: auto_reply_system() logger.info(f"Tidur selama {POLLING_INTERVAL} detik...") time.sleep(POLLING_INTERVAL) except Exception as e: logger.error(f"Error dalam background polling: {str(e)}") # Tetap coba kembali setelah interval yang ditentukan time.sleep(POLLING_INTERVAL) # Endpoints @app.route('/') def home(): return jsonify({ "status": "active", "service": "Instagram Auto Reply Bot", "version": "1.0.0", "endpoints": { "/check-comments": "Trigger manual untuk memeriksa dan membalas komentar", "/status": "Mendapatkan status sistem", "/webhook": "Endpoint untuk webhook Instagram (POST)" } }) @app.route('/check-comments') def check_comments(): # Jalankan dalam thread terpisah agar tidak memblokir respons thread = threading.Thread(target=auto_reply_system) thread.start() return jsonify({ "status": "initiated", "message": "Pengecekan komentar sedang diproses di background" }) @app.route('/status') def status(): # Cek apakah sistem berjalan dengan mengambil last modified time dari log file try: log_last_modified = os.path.getmtime("instagram_auto_reply.log") last_active = datetime.datetime.fromtimestamp(log_last_modified).strftime('%Y-%m-%d %H:%M:%S') except: last_active = "Unknown" return jsonify({ "status": "active", "post_id": post_id, "last_active": last_active, "polling_interval_seconds": POLLING_INTERVAL }) @app.route('/webhook', methods=['POST']) def webhook(): # Implementasi webhook jika Anda ingin mengintegrasikan dengan webhook Instagram data = request.json logger.info(f"Webhook received: {data}") # Anda bisa menambahkan logika untuk memproses webhook di sini thread = threading.Thread(target=auto_reply_system) thread.start() return jsonify({"status": "received"}) if __name__ == '__main__': # Mulai thread polling di background polling_thread = threading.Thread(target=background_polling) polling_thread.daemon = True # Akan berhenti ketika program utama berhenti polling_thread.start() # Jalankan server Flask app.run(host='0.0.0.0', port=5444, debug=False)