feat(example): Add openai integration with nitro

docs/docs/examples/openai-node.md

@@ -0,0 +1,251 @@
+---
+title: Nitro with openai-node
+---
+
+You can migrate from OAI API or Azure OpenAI to Nitro using your existing NodeJS code quickly
+> The ONLY thing you need to do is to override `baseURL` in `openai` init with `Nitro` URL
+- NodeJS OpenAI SDK: https://www.npmjs.com/package/openai
+
+## Chat Completion
+<table>
+<tr>
+<td> Engine </td> <td> Typescript Code </td>
+</tr>
+<tr>
+<td> Nitro </td>
+<td>
+
+```typescript
+import OpenAI from 'openai';
+
+const openai = new OpenAI({
+  apiKey: '', // defaults to process.env["OPENAI_API_KEY"]
+  baseURL: "http://localhost:3928/v1/" // https://api.openai.com/v1
+});
+
+async function chatCompletion() {
+  const stream = await openai.beta.chat.completions.stream({
+    model: 'gpt-3.5-turbo',
+    messages: [{ role: 'user', content: 'Say this is a test' }],
+    stream: true,
+  });
+
+  stream.on('content', (delta, snapshot) => {
+    process.stdout.write(delta);
+  });
+
+  for await (const chunk of stream) {
+    process.stdout.write(chunk.choices[0]?.delta?.content || '');
+  }
+
+  const chatCompletion = await stream.finalChatCompletion();
+  console.log(chatCompletion); // {id: "…", choices: […], …}
+}
+chatCompletion()
+```
+</td>
+</tr>
+<tr>
+<td> OAI </td>
+<td>
+
+```typescript
+import OpenAI from 'openai';
+
+const openai = new OpenAI({
+  apiKey: '', // defaults to process.env["OPENAI_API_KEY"]
+});
+
+async function chatCompletion() {
+  const stream = await openai.beta.chat.completions.stream({
+    model: 'gpt-3.5-turbo',
+    messages: [{ role: 'user', content: 'Say this is a test' }],
+    stream: true,
+  });
+
+  stream.on('content', (delta, snapshot) => {
+    process.stdout.write(delta);
+  });
+
+  for await (const chunk of stream) {
+    process.stdout.write(chunk.choices[0]?.delta?.content || '');
+  }
+
+  const chatCompletion = await stream.finalChatCompletion();
+  console.log(chatCompletion); // {id: "…", choices: […], …}
+}
+chatCompletion()
+```
+
+</td>
+</tr>
+<tr>
+<td> Azure OAI </td>
+<td>
+
+```typescript
+import OpenAI from 'openai';
+// The name of your Azure OpenAI Resource.
+// https://learn.microsoft.com/en-us/azure/cognitive-services/openai/how-to/create-resource?pivots=web-portal#create-a-resource
+const resource = '<your resource name>';
+
+// Corresponds to your Model deployment within your OpenAI resource, e.g. my-gpt35-16k-deployment
+// Navigate to the Azure OpenAI Studio to deploy a model.
+const model = '<your model>';
+
+// https://learn.microsoft.com/en-us/azure/ai-services/openai/reference#rest-api-versioning
+const apiVersion = '2023-06-01-preview';
+
+const apiKey = process.env['AZURE_OPENAI_API_KEY'];
+if (!apiKey) {
+  throw new Error('The AZURE_OPENAI_API_KEY environment variable is missing or empty.');
+}
+
+const openai = new OpenAI({
+  apiKey,
+  baseURL: `https://${resource}.openai.azure.com/openai/deployments/${model}`,
+  defaultQuery: { 'api-version': apiVersion },
+  defaultHeaders: { 'api-key': apiKey },
+});
+
+async function chatCompletion() {
+  const stream = await openai.beta.chat.completions.stream({
+    model: 'gpt-3.5-turbo',
+    messages: [{ role: 'user', content: 'Say this is a test' }],
+    stream: true,
+  });
+
+  stream.on('content', (delta, snapshot) => {
+    process.stdout.write(delta);
+  });
+
+  for await (const chunk of stream) {
+    process.stdout.write(chunk.choices[0]?.delta?.content || '');
+  }
+
+  const chatCompletion = await stream.finalChatCompletion();
+  console.log(chatCompletion); // {id: "…", choices: […], …}
+}
+chatCompletion()
+```
+
+</td>
+</tr>
+</table>
+
+## Embedding
+<table>
+<tr>
+<td> Engine </td> <td> Embedding </td>
+</tr>
+<tr>
+<td> Nitro </td>
+<td>
+
+```typescript
+import OpenAI from 'openai';
+
+const openai = new OpenAI({
+  apiKey: '', // defaults to process.env["OPENAI_API_KEY"]
+  baseURL: "http://localhost:3928/v1/" // https://api.openai.com/v1
+});
+
+async function embedding() {
+  const embedding = await openai.embeddings.create({input: 'Hello How are you?', model: 'text-embedding-ada-002'});
+  console.log(embedding); // {object: "list", data: […], …}
+}
+
+chatCompletion();
+```
+</td>
+</tr>
+<tr>
+<td> OAI </td>
+<td>
+
+```typescript
+import OpenAI from 'openai';
+
+const openai = new OpenAI({
+  apiKey: '', // defaults to process.env["OPENAI_API_KEY"]
+});
+
+async function embedding() {
+  const embedding = await openai.embeddings.create({input: 'Hello How are you?', model: 'text-embedding-ada-002'});
+  console.log(embedding); // {object: "list", data: […], …}
+}
+
+chatCompletion();
+```
+
+</td>
+</tr>
+<tr>
+<td> Azure OAI </td>
+<td>
+
+```typescript
+import OpenAI from 'openai';
+// The name of your Azure OpenAI Resource.
+// https://learn.microsoft.com/en-us/azure/cognitive-services/openai/how-to/create-resource?pivots=web-portal#create-a-resource
+const resource = '<your resource name>';
+
+// Corresponds to your Model deployment within your OpenAI resource, e.g. my-gpt35-16k-deployment
+// Navigate to the Azure OpenAI Studio to deploy a model.
+const model = '<your model>';
+
+// https://learn.microsoft.com/en-us/azure/ai-services/openai/reference#rest-api-versioning
+const apiVersion = '2023-06-01-preview';
+
+const apiKey = process.env['AZURE_OPENAI_API_KEY'];
+if (!apiKey) {
+  throw new Error('The AZURE_OPENAI_API_KEY environment variable is missing or empty.');
+}
+
+const openai = new OpenAI({
+  apiKey,
+  baseURL: `https://${resource}.openai.azure.com/openai/deployments/${model}`,
+  defaultQuery: { 'api-version': apiVersion },
+  defaultHeaders: { 'api-key': apiKey },
+});
+
+async function embedding() {
+  const embedding = await openai.embeddings.create({input: 'Hello How are you?', model: 'text-embedding-ada-002'});
+  console.log(embedding); // {object: "list", data: […], …}
+}
+
+chatCompletion();
+```
+
+</td>
+</tr>
+</table>
+
+## Audio
+Coming soon
+
+## How to reproduce
+1. Step 1: Dependencies installation
+```
+npm install --save openai typescript
+# or
+yarn add openai
+```
+2. Step 2: Fill `tsconfig.json`
+```json
+{
+  "compilerOptions": {
+    "moduleResolution": "node",
+    "sourceMap": true,
+    "outDir": "dist",
+    "target": "es2020",
+    "lib": ["es2020"],
+    "module": "commonjs",
+  },
+  "lib": ["es2015"]
+}
+```
+3. Step 3: Fill `index.ts` file with code
+3. Step 4: Build with `npx tsc`
+4. Step 5: Run the code with `node dist/index.js`
+5. Step 6: Enjoy!