use kserve llm as base template instead of sentiment classifier (#79)

functions/assembly/index.ts

@@ -1,18 +1,22 @@
 import { models } from "@hypermode/functions-as";
-import { ClassificationModel } from "@hypermode/models-as/models/experimental/classification";
+import {
+  OpenAIChatModel,
+  SystemMessage,
+  UserMessage,
+} from "@hypermode/models-as/models/openai/chat";
+const modelName = "text-generator";
 
-const modelName = "sentiment-classifier";
-const threshold: f32 = 0.5;
+export function generateText(text: string): string {
+  const model = models.getModel<OpenAIChatModel>(modelName);
 
-export function testClassifier(text: string): string {
-  const model = models.getModel<ClassificationModel>(modelName);
-  const input = model.createInput([text]);
-  const output = model.invoke(input);
+  const input = model.createInput([
+    new SystemMessage("You are a helpful assistant."),
+    new UserMessage(text),
+  ]);
+
+  input.temperature = 0.7;
 
-  const prediction = output.predictions[0];
-  if (prediction.confidence >= threshold) {
-    return prediction.label;
-  }
+  const output = model.invoke(input);
 
-  return "";
+  return output.choices[0].message.content.trim();
 }

hypermode.json

@@ -2,11 +2,11 @@
   "$schema": "https://manifest.hypermode.com/hypermode.json",
   "models": {
     // Models used by your Hypermode project are defined here.
-    // As an example, the particular model below is a sentiment classifier from Hugging Face,
+    // As an example, the particular model below is Meta's Llama 3.1 8B LLM from Hugging Face,
     // which is hosted on Hypermode and used in the starter function in this repository.
     // You can update or remove this model as needed.
-    "sentiment-classifier": {
-      "sourceModel": "distilbert/distilbert-base-uncased-finetuned-sst-2-english",
+    "text-generator": {
+      "sourceModel": "meta-llama/Meta-Llama-3.1-8B-Instruct",
       "provider": "hugging-face",
       "host": "hypermode"
     }