"""
clip-embed-space — CLIP ViT-B/32 embedding service.

Exposes three API endpoints:
  /embed_image     : base64-encoded image  → 512-dim float list
  /embed_text      : text string           → 512-dim float list
  /embed_image_url : image URL             → 512-dim float list

Runs on CPU (ViT-B/32 is small enough — no GPU needed).
Vectors are L2-normalised, matching the local embed_products.py pipeline.
"""

import base64
import io

import gradio as gr
import httpx
import numpy as np
from PIL import Image
from sentence_transformers import SentenceTransformer

MODEL_NAME = "clip-ViT-B-32"

print(f"Loading {MODEL_NAME}...")
model = SentenceTransformer(MODEL_NAME)
print("Model ready.")


def embed_image(image_base64: str) -> list[float]:
    image = Image.open(io.BytesIO(base64.b64decode(image_base64))).convert("RGB")
    return model.encode(image, normalize_embeddings=True).tolist()


def embed_text(text: str) -> list[float]:
    return model.encode(text, normalize_embeddings=True).tolist()


def embed_image_url(image_url: str) -> list[float]:
    resp = httpx.get(image_url, timeout=15, follow_redirects=True)
    resp.raise_for_status()
    image = Image.open(io.BytesIO(resp.content)).convert("RGB")
    return model.encode(image, normalize_embeddings=True).tolist()


with gr.Blocks(title="CLIP Embed") as demo:
    gr.Markdown("## CLIP ViT-B/32 Embedding Service — 512-dim L2-normalised vectors")

    with gr.Row():
        with gr.Column():
            b64_in  = gr.Textbox(label="image_base64", lines=3)
            b64_btn = gr.Button("Embed image (base64)")
            b64_out = gr.JSON(label="embedding [512]")
            b64_btn.click(embed_image, b64_in, b64_out, api_name="embed_image")

        with gr.Column():
            text_in  = gr.Textbox(label="text")
            text_btn = gr.Button("Embed text")
            text_out = gr.JSON(label="embedding [512]")
            text_btn.click(embed_text, text_in, text_out, api_name="embed_text")

        with gr.Column():
            url_in  = gr.Textbox(label="image_url")
            url_btn = gr.Button("Embed image (URL)")
            url_out = gr.JSON(label="embedding [512]")
            url_btn.click(embed_image_url, url_in, url_out, api_name="embed_image_url")


demo.launch()