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legacy/examples/scratch.ts

@@ -0,0 +1,19 @@
+import dotenv from 'dotenv-safe'
+import { OpenAIClient } from 'openai-fetch'
+import { z } from 'zod'
+
+import { Agentic } from '../src'
+
+dotenv.config()
+
+async function main() {
+  const openai = new OpenAIClient({ apiKey: process.env.OPENAI_API_KEY! })
+  const $ = new Agentic({ openai })
+
+  const ex1 = await $.gpt4(`generate fake data`)
+    // .output(z.object({ foo: z.string(), bar: z.number() }))
+    .call()
+  console.log(ex1)
+}
+
+main()

legacy/examples/sentiment.ts

@@ -14,7 +14,6 @@ export async function main() {
     `You are an expert sentiment-labelling assistant. Label the following texts as positive or negative: \n{{#texts}}- {{.}}\n{{/texts}}`
   )
     .input(z.object({ texts: z.string().array() }))
-    // TODO: label should be a union of literals
     .output(z.array(z.object({ text: z.string(), label: z.string() })))
     .examples([
       { input: 'The food was digusting', output: 'negative' },
@@ -22,10 +21,6 @@ export async function main() {
       { input: 'Recommended', output: 'positive' },
       { input: 'The waiter was rude', output: 'negative' }
     ])
-    // .assert((output) => output.filter(({ label }) =>
-    //     !['positive', 'negative'].includes(label)
-    //   ).length === 0
-    // })
     .call({
       texts: [
         'I went to this place and it was just so awful.',