pip install pixeltable openai sentence-transformers

import pixeltable as pxt
from pixeltable.functions.openai import vision
from pixeltable.functions.huggingface import sentence_transformer

# Initialize app structure
pxt.drop_dir("image_search", force=True)
pxt.create_dir("image_search")

# Create images table
img_t = pxt.create_table(
    "image_search.images", 
    {"image": pxt.Image}
)

# Add GPT-4 Vision analysis
img_t.add_computed_column(
    image_description=vision(
        prompt="Describe the image. Be specific on the colors you see.",
        image=img_t.image,
        model="gpt-4o-mini",
    )
)

# Configure embedding model
embed_model = sentence_transformer.using(
    model_id="intfloat/e5-large-v2"
)

# Add search capability
img_t.add_embedding_index(
    column="image_description", 
    string_embed=embed_model
)

# Define search query
@pxt.query
def search_images(query_text: str, limit: int = 10):
    sim = img_t.image_description.similarity(query_text)
    return (
        img_t.order_by(sim, asc=False)
        .select(
            img_t.image,
            img_t.image_description, 
            similarity=sim
        )
        .limit(limit)
    )

import pixeltable as pxt

# Connect to your table
img_t = pxt.get_table("image_search.images")

# Sample image URLs
IMAGE_URL = (
    "https://raw.github.com/pixeltable/pixeltable/release/docs/resources/images/"
)

image_urls = [
    IMAGE_URL + doc for doc in [
        "000000000030.jpg",
        "000000000034.jpg",
        "000000000042.jpg",
    ]
]

# Add images to the database
img_t.insert({"image": url} for url in image_urls)

# Search images
@pxt.query
def find_images(query: str, top_k: int = 3):
    sim = img_t.image_description.similarity(query)
    return (
        img_t.order_by(sim, asc=False)
        .select(
            img_t.image,
            img_t.image_description,
            similarity=sim
        )
        .limit(top_k)
    )

# Example search
results = find_images("Show me images containing blue flowers").collect()

# Print results
for r in results:
    print(f"Similarity: {r['similarity']:.3f}")
    print(f"Description: {r['image_description']}")
    print(f"Image URL: {r['image']}\n")