fix(ext/ai): moving types to global.d.ts

Author: kallebysantos

examples/ort-raw-session/index.ts

@@ -1,5 +1,3 @@
-/// /// <reference path="./types.d.ts" />
-
 /*
 const modelUrl = 'https://huggingface.co/kalleby/hp-to-miles/resolve/main/model.onnx?download=true';
 const modelConfigUrl =
@@ -71,45 +69,45 @@ Deno.serve(async (_req: Request) => {
 });
 */
 
-const { Tensor, RawSession } = Supabase.ai;
+const { RawTensor, RawSession } = Supabase.ai;
 
 const session = await RawSession.fromHuggingFace('kallebysantos/vehicle-emission', {
-  path: {
-    modelFile: 'model.onnx',
-  },
+    path: {
+        modelFile: 'model.onnx',
+    },
 });
 
 Deno.serve(async (_req: Request) => {
-  // sample data could be a JSON request
-  const carsBatchInput = [{
-    'Model_Year': 2021,
-    'Engine_Size': 2.9,
-    'Cylinders': 6,
-    'Fuel_Consumption_in_City': 13.9,
-    'Fuel_Consumption_in_City_Hwy': 10.3,
-    'Fuel_Consumption_comb': 12.3,
-    'Smog_Level': 3,
-  }, {
-    'Model_Year': 2023,
-    'Engine_Size': 2.4,
-    'Cylinders': 4,
-    'Fuel_Consumption_in_City': 9.9,
-    'Fuel_Consumption_in_City_Hwy': 7.0,
-    'Fuel_Consumption_comb': 8.6,
-    'Smog_Level': 3,
-  }];
-
-  // Parsing objects to tensor input
-  const inputTensors: Record<string, Supabase.Tensor<'float32'>> = {};
-  session.inputs.forEach((inputKey) => {
-    const values = carsBatchInput.map((item) => item[inputKey]);
-
-    inputTensors[inputKey] = new Tensor('float32', values, [values.length, 1]);
-  });
-
-  const { emissions } = await session.run(inputTensors);
-  console.log(emissions);
-  // [ 289.01, 199.53]
-
-  return Response.json({ result: emissions });
+    // sample data could be a JSON request
+    const carsBatchInput = [{
+        'Model_Year': 2021,
+        'Engine_Size': 2.9,
+        'Cylinders': 6,
+        'Fuel_Consumption_in_City': 13.9,
+        'Fuel_Consumption_in_City_Hwy': 10.3,
+        'Fuel_Consumption_comb': 12.3,
+        'Smog_Level': 3,
+    }, {
+        'Model_Year': 2023,
+        'Engine_Size': 2.4,
+        'Cylinders': 4,
+        'Fuel_Consumption_in_City': 9.9,
+        'Fuel_Consumption_in_City_Hwy': 7.0,
+        'Fuel_Consumption_comb': 8.6,
+        'Smog_Level': 3,
+    }];
+
+    // Parsing objects to tensor input
+    const inputTensors: Record<string, Supabase.ai.RawTensor<'float32'>> = {};
+    session.inputs.forEach((inputKey) => {
+        const values = carsBatchInput.map((item) => item[inputKey]);
+
+        inputTensors[inputKey] = new RawTensor('float32', values, [values.length, 1]);
+    });
+
+    const { emissions } = await session.run(inputTensors);
+    console.log(emissions);
+    // [ 289.01, 199.53]
+
+    return Response.json({ result: emissions });
 });

examples/ort-raw-session/types.d.ts

@@ -1,11 +1,9 @@
-// Setup type definitions for built-in Supabase Runtime APIs
-import 'jsr:@supabase/functions-js/edge-runtime.d.ts';
 import { PreTrainedTokenizer } from 'https://cdn.jsdelivr.net/npm/@huggingface/[email protected]';
 
 // import 'phonemize' code from Kokoro.js repo
 import { phonemize } from './phonemizer.js';
 
-const { Tensor, RawSession } = Supabase.ai;
+const { RawTensor, RawSession } = Supabase.ai;
 
 /* NOTE: Reference [original paper](https://arxiv.org/pdf/2306.07691#Model%20Training):
 > All datasets were resampled to 24 kHz to match LibriTTS, and the texts