Supabase edge functions with custom embed model

docker-compose.yml

services:
  # others supabase services ...
  supabase-functions:
      container_name: supabase-edge-functions
      
      # Here you need to specify that you want do docker build a image with your custom model
      image: supabase/edge-runtime:v1.41.2-custom-model
      build:
        context: .
        dockerfile: Dockerfile
      restart: unless-stopped
      # The rest of config doesn't matter, you can keep it as default or your custom

Dockerfile

FROM supabase/edge-runtime:v1.41.2 AS build

# Change here with the HF model name. It must be ONNX runtime compatible
ENV MODEL_NAME=Xenova/paraphrase-multilingual-MiniLM-L12-v2

# Setting up
RUN apt update && apt install curl -y

# Replacing 'gte-small' by $MODEL_NAME
WORKDIR /etc/sb_ai/models/gte-small

# Downloading the custom model
RUN curl -L -o model.onnx https://huggingface.co/${MODEL_NAME}/resolve/main/onnx/model_quantized.onnx?download=true
RUN curl -L -o tokenizer.json https://huggingface.co/${MODEL_NAME}/resolve/main/tokenizer.json?download=true

FROM supabase/edge-runtime:v1.41.2 AS run

COPY --from=build /etc/sb_ai/models/gte-small /etc/sb_ai/models/gte-small

function.ts

/// <reference types="https://esm.sh/@supabase/functions-js/src/edge-runtime.d.ts" />
// gte-small has been overriden by paraphrase-multilingual-MiniLM-L12-v2

// Here you need to keep the 'gte-small' for API compatility. 
// But since we overwrite the model inside container it will use our custom model
const embedder = new Supabase.ai.Session("gte-small");

Deno.serve(async (req) => {
  // ...

  // @ts-ignore Embedder generates unknown type
  const outputEmbed: number[] = await embedder.run("Olá Mundo!", {
    mean_pool: true,
    normalize: true,
  });

  // Rest of your code ...
}