cleanup

README.md

@@ -344,7 +344,7 @@ vector_db = VectorDatabaseService(
 # Add image vector
 point_id = vector_db.add_image_vector(
     image_id="img_123",
-    vector=[0.1, 0.2, ...],  # 512-dimensional vector
+    vector=[0.1, 0.2, ...],  # 1408-dimensional vector
     metadata={"filename": "image.jpg", "size": 1024}
 )
 

deployment/cleanup-images.sh

@@ -1,62 +0,0 @@
-#!/bin/bash
-set -e
-
-# Container Image Cleanup Script
-# This script cleans up container images from Google Container Registry
-# Images are not managed by Terraform, so this provides a manual cleanup option
-
-PROJECT_ID=$(gcloud config get-value project)
-IMAGE_NAME="sereact-api"
-
-if [ -z "$PROJECT_ID" ]; then
-    echo "ERROR: No Google Cloud project is set. Run 'gcloud config set project YOUR_PROJECT_ID'"
-    exit 1
-fi
-
-echo "Cleaning up container images for project: $PROJECT_ID"
-echo "Image repository: gcr.io/$PROJECT_ID/$IMAGE_NAME"
-echo ""
-
-# Check if repository exists
-if ! gcloud container images list-tags "gcr.io/$PROJECT_ID/$IMAGE_NAME" > /dev/null 2>&1; then
-    echo "No container images found for $IMAGE_NAME"
-    exit 0
-fi
-
-echo "Found container images. Listing current images:"
-gcloud container images list-tags "gcr.io/$PROJECT_ID/$IMAGE_NAME"
-echo ""
-
-read -p "Do you want to delete ALL images for $IMAGE_NAME? (yes/no): " confirm
-
-if [ "$confirm" != "yes" ]; then
-    echo "Cleanup cancelled."
-    exit 0
-fi
-
-echo "Deleting container images..."
-
-# Get all image digests and delete them
-DIGESTS=$(gcloud container images list-tags "gcr.io/$PROJECT_ID/$IMAGE_NAME" --format="get(digest)" --filter="tags:*" 2>/dev/null || true)
-UNTAGGED_DIGESTS=$(gcloud container images list-tags "gcr.io/$PROJECT_ID/$IMAGE_NAME" --format="get(digest)" --filter="-tags:*" 2>/dev/null || true)
-
-# Delete tagged images
-if [ ! -z "$DIGESTS" ]; then
-    echo "Deleting tagged images..."
-    for digest in $DIGESTS; do
-        gcloud container images delete "gcr.io/$PROJECT_ID/$IMAGE_NAME@$digest" --force-delete-tags --quiet || echo "Failed to delete $digest"
-    done
-fi
-
-# Delete untagged images
-if [ ! -z "$UNTAGGED_DIGESTS" ]; then
-    echo "Deleting untagged images..."
-    for digest in $UNTAGGED_DIGESTS; do
-        gcloud container images delete "gcr.io/$PROJECT_ID/$IMAGE_NAME@$digest" --quiet || echo "Failed to delete $digest"
-    done
-fi
-
-echo "Container image cleanup completed."
-echo ""
-echo "Note: The repository gcr.io/$PROJECT_ID/$IMAGE_NAME may still exist but should be empty."
-echo "You can verify with: gcloud container images list-tags gcr.io/$PROJECT_ID/$IMAGE_NAME" 

deployment/cloud-function/test_vertex_ai_embeddings.py

@@ -1,107 +0,0 @@
-#!/usr/bin/env python3
-"""
-Simple test script to verify Vertex AI multimodal embeddings work correctly.
-Run this script to test the embedding generation before deploying.
-"""
-
-import os
-import sys
-import logging
-from PIL import Image
-import io
-import numpy as np
-
-# Add the current directory to the path so we can import main
-sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
-
-# Set up logging
-logging.basicConfig(level=logging.INFO)
-logger = logging.getLogger(__name__)
-
-def create_test_image():
-    """Create a simple test image"""
-    # Create a simple 100x100 RGB image with a red square
-    img = Image.new('RGB', (100, 100), color='white')
-    pixels = img.load()
-    
-    # Draw a red square in the center
-    for i in range(25, 75):
-        for j in range(25, 75):
-            pixels[i, j] = (255, 0, 0)  # Red
-    
-    # Convert to bytes
-    img_bytes = io.BytesIO()
-    img.save(img_bytes, format='PNG')
-    return img_bytes.getvalue()
-
-def test_vertex_ai_embeddings():
-    """Test Vertex AI embedding generation"""
-    try:
-        # Set required environment variables for testing
-        os.environ['GOOGLE_CLOUD_PROJECT'] = os.environ.get('GOOGLE_CLOUD_PROJECT', 'your-project-id')
-        os.environ['VERTEX_AI_LOCATION'] = os.environ.get('VERTEX_AI_LOCATION', 'us-central1')
-        
-        # Import the function we want to test
-        from main import generate_image_embeddings
-        
-        # Create test image
-        logger.info("Creating test image...")
-        test_image_data = create_test_image()
-        logger.info(f"Created test image with {len(test_image_data)} bytes")
-        
-        # Generate embeddings
-        logger.info("Generating embeddings using Vertex AI...")
-        embeddings = generate_image_embeddings(test_image_data)
-        
-        if embeddings is None:
-            logger.error("Failed to generate embeddings!")
-            return False
-        
-        # Verify embeddings
-        logger.info(f"Generated embeddings with shape: {embeddings.shape}")
-        logger.info(f"Embeddings dtype: {embeddings.dtype}")
-        logger.info(f"Embeddings range: [{embeddings.min():.4f}, {embeddings.max():.4f}]")
-        logger.info(f"Embeddings norm: {np.linalg.norm(embeddings):.4f}")
-        
-        # Basic validation
-        assert isinstance(embeddings, np.ndarray), "Embeddings should be numpy array"
-        assert embeddings.dtype == np.float32, "Embeddings should be float32"
-        assert len(embeddings.shape) == 1, "Embeddings should be 1D array"
-        assert embeddings.shape[0] == 1408, f"Expected 1408 dimensions, got {embeddings.shape[0]}"
-        
-        # Check if normalized (should be close to 1.0)
-        norm = np.linalg.norm(embeddings)
-        assert 0.9 <= norm <= 1.1, f"Embeddings should be normalized, norm is {norm}"
-        
-        logger.info("✅ All tests passed! Vertex AI embeddings are working correctly.")
-        return True
-        
-    except ImportError as e:
-        logger.error(f"Import error: {e}")
-        logger.error("Make sure you have installed the required dependencies:")
-        logger.error("pip install google-cloud-aiplatform")
-        return False
-    except Exception as e:
-        logger.error(f"Test failed with error: {e}")
-        return False
-
-if __name__ == "__main__":
-    logger.info("Testing Vertex AI multimodal embeddings...")
-    
-    # Check if required environment variables are set
-    project_id = os.environ.get('GOOGLE_CLOUD_PROJECT')
-    if not project_id:
-        logger.error("Please set GOOGLE_CLOUD_PROJECT environment variable")
-        logger.error("Example: export GOOGLE_CLOUD_PROJECT=your-project-id")
-        sys.exit(1)
-    
-    logger.info(f"Using project: {project_id}")
-    
-    success = test_vertex_ai_embeddings()
-    
-    if success:
-        logger.info("🎉 Test completed successfully!")
-        sys.exit(0)
-    else:
-        logger.error("❌ Test failed!")
-        sys.exit(1) 

deployment/fix-cloud-run-deployment.sh

@@ -1,135 +0,0 @@
-#!/bin/bash
-set -e
-
-# Configuration
-PROJECT_ID="gen-lang-client-0424120530"
-REGION="us-central1"
-SERVICE_NAME="sereact"
-
-echo "=== Cloud Run Deployment Fix Script ==="
-echo "Project: $PROJECT_ID"
-echo "Region: $REGION"
-echo "Service: $SERVICE_NAME"
-echo ""
-
-# Function to check if gcloud is authenticated
-check_auth() {
-    if ! gcloud auth list --filter=status:ACTIVE --format="value(account)" | grep -q .; then
-        echo "ERROR: No active gcloud authentication found."
-        echo "Please run: gcloud auth login"
-        exit 1
-    fi
-}
-
-# Function to clean up problematic revisions
-cleanup_revisions() {
-    echo "Step 1: Cleaning up problematic revisions..."
-    
-    # Get all revisions for the service
-    REVISIONS=$(gcloud run revisions list --service=$SERVICE_NAME --region=$REGION --project=$PROJECT_ID --format="value(metadata.name)" 2>/dev/null || echo "")
-    
-    if [ -z "$REVISIONS" ]; then
-        echo "No revisions found or service doesn't exist."
-        return 0
-    fi
-    
-    echo "Found revisions:"
-    echo "$REVISIONS"
-    echo ""
-    
-    # Delete old revisions (keep the latest one for now)
-    REVISION_COUNT=$(echo "$REVISIONS" | wc -l)
-    if [ $REVISION_COUNT -gt 1 ]; then
-        echo "Deleting old revisions to prevent conflicts..."
-        echo "$REVISIONS" | head -n -1 | while read revision; do
-            if [ ! -z "$revision" ]; then
-                echo "Deleting revision: $revision"
-                gcloud run revisions delete "$revision" --region=$REGION --project=$PROJECT_ID --quiet || echo "Failed to delete $revision (may be in use)"
-            fi
-        done
-    fi
-}
-
-# Function to force a new deployment
-force_redeploy() {
-    echo "Step 2: Forcing a new deployment with Terraform..."
-    
-    cd "$(dirname "$0")/terraform"
-    
-    # Taint the Cloud Run service to force recreation
-    echo "Tainting Cloud Run service to force recreation..."
-    terraform taint google_cloud_run_service.sereact || echo "Service not in state or already tainted"
-    
-    # Apply the configuration
-    echo "Applying Terraform configuration..."
-    terraform apply -auto-approve
-    
-    cd - > /dev/null
-}
-
-# Function to verify deployment
-verify_deployment() {
-    echo "Step 3: Verifying deployment..."
-    
-    # Wait a moment for the service to be ready
-    sleep 10
-    
-    # Check service status
-    SERVICE_URL=$(gcloud run services describe $SERVICE_NAME --region=$REGION --project=$PROJECT_ID --format="value(status.url)" 2>/dev/null || echo "")
-    
-    if [ ! -z "$SERVICE_URL" ]; then
-        echo "✅ Service deployed successfully!"
-        echo "Service URL: $SERVICE_URL"
-        
-        # Test the service
-        echo "Testing service health..."
-        if curl -s -o /dev/null -w "%{http_code}" "$SERVICE_URL/health" | grep -q "200"; then
-            echo "✅ Service is responding correctly!"
-        else
-            echo "⚠️  Service deployed but health check failed. Check logs:"
-            echo "gcloud logging read \"resource.type=cloud_run_revision AND resource.labels.service_name=$SERVICE_NAME\" --limit=10 --project=$PROJECT_ID"
-        fi
-    else
-        echo "❌ Service deployment failed."
-        exit 1
-    fi
-}
-
-# Main execution
-main() {
-    echo "Starting Cloud Run deployment fix..."
-    echo ""
-    
-    check_auth
-    cleanup_revisions
-    force_redeploy
-    verify_deployment
-    
-    echo ""
-    echo "=== Deployment Fix Complete ==="
-    echo "If you continue to have issues, try:"
-    echo "1. Building a new image: ./deployment/deploy.sh --deploy --build"
-    echo "2. Checking logs: gcloud logging read \"resource.type=cloud_run_revision AND resource.labels.service_name=$SERVICE_NAME\" --limit=10 --project=$PROJECT_ID"
-}
-
-# Help function
-show_help() {
-    echo "Usage: $0 [--help]"
-    echo ""
-    echo "This script fixes Cloud Run deployment issues by:"
-    echo "1. Cleaning up problematic revisions"
-    echo "2. Forcing a new deployment with Terraform"
-    echo "3. Verifying the deployment"
-    echo ""
-    echo "Options:"
-    echo "  --help    Show this help message"
-}
-
-# Parse arguments
-if [ "$1" = "--help" ]; then
-    show_help
-    exit 0
-fi
-
-# Run main function
-main 

deployment/terraform/scripts/install_qdrant.sh

@@ -172,7 +172,7 @@ curl -X PUT "http://localhost:6333/collections/image_vectors" \
   -H "Content-Type: application/json" \
   -d '{
     "vectors": {
-      "size": 512,
+      "size": 1408,
       "distance": "Cosine"
     },
     "optimizers_config": {

requirements.txt

@@ -7,6 +7,7 @@ google-cloud-storage==2.12.0
 google-cloud-vision==3.4.5
 google-cloud-firestore==2.11.1
 google-cloud-pubsub==2.18.4
+google-cloud-aiplatform==1.38.0
 python-multipart==0.0.6
 python-jose==3.3.0
 passlib==1.7.4

scripts/push.sh

@@ -1,14 +0,0 @@
-#!/bin/bash
-set -e
-
-# Source the build environment to reuse variables
-source "$(dirname "$0")/build.sh"
-
-# Push the Docker image to the registry
-echo "Pushing image: ${FULL_IMAGE_NAME} to registry..."
-docker push "${FULL_IMAGE_NAME}"
-echo "Image pushed successfully"
-
-echo ""
-echo "Image pushed to: ${FULL_IMAGE_NAME}"
-echo ""