fix: Update gemini_transcribe.py to use Service Account auth and SOCKS5 proxy

gemini_transcribe.py

@@ -2,11 +2,26 @@
 import os
 import sys
 import time
+from google.oauth2 import service_account
 import google.generativeai as genai
 
-# Config API key
+# Setup proxies for Google API routing through SOCKS5 proxy (RKN bypass)
-API_KEY = os.getenv("GOOGLE_API_KEY", "AIzaSyD09NxPpyTk4RZLGqE6dFzJwNxhawRAegc")
+os.environ["https_proxy"] = "socks5h://127.0.0.1:10808"
-genai.configure(api_key=API_KEY)
+os.environ["http_proxy"] = "socks5h://127.0.0.1:10808"
+os.environ["all_proxy"] = "socks5h://127.0.0.1:10808"
+
+# Auth using Service Account (avoids invalid GCP API key errors)
+SERVICE_ACCOUNT_FILE = "/home/matrixhasyou/domovoy_google_creds.json"
+try:
+    creds = service_account.Credentials.from_service_account_file(
+        SERVICE_ACCOUNT_FILE, 
+        scopes=["https://www.googleapis.com/auth/generative-language", "https://www.googleapis.com/auth/drive"]
+    )
+    genai.configure(credentials=creds)
+    print("Authenticated successfully using Google Service Account.", flush=True)
+except Exception as e:
+    print(f"Authentication failed: {e}", flush=True)
+    sys.exit(1)
 
 BOT_TOKEN = "8725618164:AAH1tGalq-pw1l0t4P5c0sdLkCVJdh7IE7M"
 CHAT_ID = "197957361"
@@ -16,31 +31,33 @@ def send_tg(msg):
     import urllib.request
     try:
         url = f"https://api.telegram.org/bot{BOT_TOKEN}/sendMessage"
-        data = urllib.parse.urlencode({"chat_id": CHAT_ID, "text": msg, "parse_mode": "markdown"}).encode("utf-8")
+        # Split message if it's too long for TG limit (4096 chars)
+        for chunk in [msg[i:i+4000] for i in range(0, len(msg), 4000)]:
+            data = urllib.parse.urlencode({"chat_id": CHAT_ID, "text": chunk, "parse_mode": "markdown"}).encode("utf-8")
             req = urllib.request.Request(url, data=data)
             urllib.request.urlopen(req, timeout=15)
     except Exception as e:
-        print(f"Failed to send Telegram message: {e}")
+        print(f"Failed to send Telegram message: {e}", flush=True)
 
 def transcribe_audio(audio_path, output_prefix, model_name="gemini-1.5-pro"):
     if not os.path.exists(audio_path):
-        print(f"Error: File not found: {audio_path}")
+        print(f"Error: File not found: {audio_path}", flush=True)
         sys.exit(1)
         
     size_mb = os.path.getsize(audio_path) / (1024 * 1024)
-    print(f"File size: {size_mb:.2f} MB")
+    print(f"File size: {size_mb:.2f} MB", flush=True)
     
     send_tg(f"🎙 **Транскрибация аудио через Gemini:**\nФайл: `{os.path.basename(audio_path)}` ({size_mb:.1f} MB)\nМодель: `{model_name}`\n\n*Запуск выгрузки в Google API...*")
     
     # 1. Upload file
-    print(f"Uploading {audio_path} to Google Gemini File API...")
+    print(f"Uploading {audio_path} to Google Gemini File API...", flush=True)
     audio_file = genai.upload_file(path=audio_path)
-    print(f"File uploaded successfully! API Name: {audio_file.name}")
+    print(f"File uploaded successfully! API Name: {audio_file.name}", flush=True)
     
     # 2. Wait for processing
     start_time = time.time()
     while audio_file.state.name == "PROCESSING":
-        print("File is processing on Google servers... waiting 10s")
+        print("File is processing on Google servers... waiting 10s", flush=True)
         time.sleep(10)
         audio_file = genai.get_file(name=audio_file.name)
         
@@ -48,8 +65,8 @@ def transcribe_audio(audio_path, output_prefix, model_name="gemini-1.5-pro"):
         send_tg("❌ **Ошибка**: Обработка аудиофайла на сервере Google завершилась неудачей.")
         raise ValueError("Audio processing failed on Google servers.")
         
-    print("Audio file is active and ready!")
+    print("Audio file is active and ready!", flush=True)
-    send_tg("⚡️ **Аудиофайл готов к обработке.** Запускаю генерацию текста в Gemini (это может занять до 2-3 минут)...")
+    send_tg("⚡️ **Аудиофайл готов.** Запускаю расшифровку речи в Gemini (это может занять до 2-3 минут)...")
     
     # 3. Transcribe with model
     model = genai.GenerativeModel(model_name)
@@ -75,19 +92,20 @@ def transcribe_audio(audio_path, output_prefix, model_name="gemini-1.5-pro"):
             f.write(transcript_text)
             
         elapsed = time.time() - start_time
-        print(f"Success! Unpacked in {elapsed:.1f}s")
+        print(f"Success! Unpacked in {elapsed:.1f}s", flush=True)
         
-        send_tg(f"✅ **Расшифровка завершена!**\nПродолжительность операции: {elapsed/60:.1f} мин\n\nРезультаты сохранены в:\n- `{md_file}`\n- `{txt_file}`")
+        # Send transcript to Telegram
+        send_tg(f"✅ **Расшифровка завершена!** ({elapsed/60:.1f} мин)\nРезультаты сохранены в:\n- `{md_file}`\n- `{txt_file}`\n\n📝 **Текст расшифровки:**\n\n{transcript_text}")
         
     except Exception as e:
-        print(f"Error during transcription generation: {e}")
+        print(f"Error during transcription generation: {e}", flush=True)
         send_tg(f"❌ **Ошибка во время генерации текста:**\n`{e}`")
         
     finally:
         # Delete remote file from Google storage
-        print("Cleaning up file from Google storage...")
+        print("Cleaning up file from Google storage...", flush=True)
         genai.delete_file(name=audio_file.name)
-        print("Cleanup done.")
+        print("Cleanup done.", flush=True)
 
 if __name__ == "__main__":
     if len(sys.argv) < 3: