added

video_transcription/ai_transcriber_v2/main.py

@@ -1,6 +1,7 @@
 import argparse
 import os
 import sys
+import socket
 from dotenv import load_dotenv
 
 # Load environment variables from central .env_files directory
@@ -183,7 +184,8 @@ def process_file(file_path, args, source_lang=None, loaded_model=None, service_s
                         tracker.logger.error(f"VALIDATION FAILED: {msg}")
                         tracker.logger.error("Marking translation as failed due to incomplete coverage.")
                         
-                        redo_file = os.path.join(os.path.dirname(file_path), "redo_queue.txt")
+                        hostname = socket.gethostname()
+                        redo_file = os.path.join(os.path.dirname(file_path), f"redo_queue_{hostname}.txt")
                         with open(redo_file, "a", encoding="utf-8") as rf:
                             rf.write(f"{file_path} | {msg}\n")
                         

video_transcription/ai_transcriber_v2/recover_and_fix_v2.py

@@ -3,6 +3,7 @@ import os
 import sys
 import argparse
 import subprocess
+import socket
 from dotenv import load_dotenv
 from datetime import datetime
 import pysubs2
@@ -36,7 +37,8 @@ def process_recovery(folder_path, target_lang="English", prefer_deep=False, pref
     else:
         print("Preference: Gemini (API) > DeepTranslate")
     
-    recovery_log_file = os.path.join(folder_path, "recovery_status.log")
+    hostname = socket.gethostname()
+    recovery_log_file = os.path.join(folder_path, f"recovery_status_{hostname}.log")
     print(f"Logging actions to: {recovery_log_file}")
     
     # Ensure Ollama is ready

video_transcription/ai_transcriber_v2/tracker.py

@@ -1,14 +1,18 @@
 import logging
 import os
+import socket
 from datetime import datetime
 from sqlalchemy import create_engine, Column, Integer, String, DateTime, Enum, Text
 from sqlalchemy.orm import declarative_base, sessionmaker
 import enum
 
+# Get Hostname for namespacing
+HOSTNAME = socket.gethostname()
+
 # Setup Logging
 log_dir = "logs"
 os.makedirs(log_dir, exist_ok=True)
-log_file = os.path.join(log_dir, f"transcriber_{datetime.now().strftime('%Y%m%d')}.log")
+log_file = os.path.join(log_dir, f"transcriber_{HOSTNAME}_{datetime.now().strftime('%Y%m%d')}.log")
 
 logging.basicConfig(
     level=logging.INFO,
@@ -22,7 +26,7 @@ logger = logging.getLogger(__name__)
 
 # Database Setup
 Base = declarative_base()
-DB_FILE = "job_history.db"
+DB_FILE = f"job_history_{HOSTNAME}.db"
 
 class JobStatus(enum.Enum):
     PENDING = "pending"

video_transcription/ai_transcriber_v2/translator.py

@@ -22,6 +22,11 @@ def translate_via_ollama(source_srt_content, target_language="English", model="l
         # Using tqdm for progress bar
         for line in tqdm(subs, desc="  Ollama Progress", unit="line"):
             text = line.text.strip()
+            
+            # Skip empty, numeric-only, or extremely short non-word text
+            if not text or text.isdigit() or len(text) < 2:
+                continue
+
             if text:
                 prompt = (
                     f"Translate this subtitle text to {target_language}. Output ONLY the translation.\n"
@@ -54,6 +59,11 @@ def translate_fallback_mymemory(source_srt_content, target_language="en"):
         
         for line in tqdm(subs, desc="  MyMemory Progress", unit="line"):
             text = line.text.strip()
+            
+            # Skip empty, numeric-only, or extremely short non-word text
+            if not text or text.isdigit() or len(text) < 2:
+                continue
+
             if text:
                 if len(text) > 500: # MyMemory has stricter limits often
                      continue
@@ -89,6 +99,11 @@ def translate_fallback_free(source_srt_content, target_language="en"):
         # Simple line-by-line translation
         for line in tqdm(subs, desc="  DeepTranslate Progress", unit="line"):
             text = line.text.strip()
+            
+            # Skip empty, numeric-only, or extremely short non-word text
+            if not text or text.isdigit() or len(text) < 2:
+                continue
+
             if text:
                 # Sanity check: Skip lines that are too long
                 if len(text) > 4000: