Add setup script for Qwen2.5VL model in Ollama container

setup_model.py

@@ -0,0 +1,114 @@
+#!/usr/bin/env python3
+"""
+Script to ensure the Qwen2.5VL model is available in the Ollama container
+"""
+
+import configparser
+import time
+import sys
+import requests
+
+def load_config():
+    """Load configuration from config.ini"""
+    config = configparser.ConfigParser()
+    config.read('config.ini')
+
+    ollama_host = config.get('DEFAULT', 'ollama_host', fallback='http://ollama:11434')
+    ollama_model = config.get('DEFAULT', 'ollama_model', fallback='qwen2.5vl:7b')
+
+    return ollama_host, ollama_model
+
+def wait_for_ollama(host, max_attempts=30):
+    """Wait for Ollama container to be ready"""
+    print(f"⏳ Waiting for Ollama container at {host}...")
+
+    for attempt in range(1, max_attempts + 1):
+        try:
+            response = requests.get(f"{host}/api/tags", timeout=5)
+            if response.status_code == 200:
+                print("✅ Ollama container is ready!")
+                return True
+        except requests.exceptions.RequestException:
+            pass
+
+        print(f"   Attempt {attempt}/{max_attempts} - waiting...")
+        time.sleep(2)
+
+    print("❌ Ollama container is not responding after maximum attempts")
+    return False
+
+def check_model_exists(host, model_name):
+    """Check if the model is already available"""
+    try:
+        response = requests.get(f"{host}/api/tags", timeout=5)
+        if response.status_code == 200:
+            models = response.json()
+            model_names = [model['name'] for model in models.get('models', [])]
+            return any(model_name in name for name in model_names), model_names
+        return False, []
+    except requests.exceptions.RequestException as e:
+        print(f"❌ Error checking models: {e}")
+        return False, []
+
+def pull_model(host, model_name):
+    """Pull the model from Ollama"""
+    print(f"📥 Pulling model '{model_name}' (this may take several minutes)...")
+
+    try:
+        response = requests.post(
+            f"{host}/api/pull",
+            json={"name": model_name},
+            timeout=600  # 10 minutes timeout
+        )
+
+        if response.status_code == 200:
+            print(f"✅ Successfully pulled model '{model_name}'")
+            return True
+        else:
+            print(f"❌ Failed to pull model: HTTP {response.status_code}")
+            print(f"Response: {response.text}")
+            return False
+    except requests.exceptions.RequestException as e:
+        print(f"❌ Error pulling model: {e}")
+        return False
+
+def main():
+    """Main function to set up the model"""
+    print("🔧 Model Setup for YouTube Video Classifier")
+    print("=" * 50)
+
+    # Load configuration
+    try:
+        ollama_host, ollama_model = load_config()
+        print("📋 Configuration:")
+        print(f"   Host: {ollama_host}")
+        print(f"   Model: {ollama_model}")
+        print()
+    except Exception as e:
+        print(f"❌ Failed to load configuration: {e}")
+        sys.exit(1)
+
+    # Wait for Ollama to be ready
+    if not wait_for_ollama(ollama_host):
+        sys.exit(1)
+
+    # Check if model exists
+    model_exists, available_models = check_model_exists(ollama_host, ollama_model)
+
+    if model_exists:
+        print(f"✅ Model '{ollama_model}' is already available!")
+    else:
+        print(f"📋 Available models: {available_models}")
+        print(f"❌ Model '{ollama_model}' not found")
+
+        if pull_model(ollama_host, ollama_model):
+            print(f"🎉 Model '{ollama_model}' is now ready for use!")
+        else:
+            print(f"❌ Failed to set up model '{ollama_model}'")
+            sys.exit(1)
+
+    print("\n🎬 YouTube Video Classifier is ready!")
+    print("🧪 Run 'python test_ollama.py' to verify the setup")
+
+if __name__ == "__main__":
+    main()