Node.js Open AI examples (#149)

* feat: added examples for nodejs

* feat: added examples for nodejs

* docs: updated README

* docs: updated README

Author: DaniAkash

.gitignore

@@ -139,3 +139,152 @@ dmypy.json
 # Pytorch checkpoint
 *.pth
 *.pt
+
+# Node lock files since this is a example repo and they can be ignored
+package-lock.json
+yarn.lock
+
+# Created by https://www.toptal.com/developers/gitignore/api/node
+# Edit at https://www.toptal.com/developers/gitignore?templates=node
+
+### Node ###
+# Logs
+logs
+*.log
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+lerna-debug.log*
+.pnpm-debug.log*
+
+# Diagnostic reports (https://nodejs.org/api/report.html)
+report.[0-9]*.[0-9]*.[0-9]*.[0-9]*.json
+
+# Runtime data
+pids
+*.pid
+*.seed
+*.pid.lock
+
+# Directory for instrumented libs generated by jscoverage/JSCover
+lib-cov
+
+# Coverage directory used by tools like istanbul
+coverage
+*.lcov
+
+# nyc test coverage
+.nyc_output
+
+# Grunt intermediate storage (https://gruntjs.com/creating-plugins#storing-task-files)
+.grunt
+
+# Bower dependency directory (https://bower.io/)
+bower_components
+
+# node-waf configuration
+.lock-wscript
+
+# Compiled binary addons (https://nodejs.org/api/addons.html)
+build/Release
+
+# Dependency directories
+node_modules/
+jspm_packages/
+
+# Snowpack dependency directory (https://snowpack.dev/)
+web_modules/
+
+# TypeScript cache
+*.tsbuildinfo
+
+# Optional npm cache directory
+.npm
+
+# Optional eslint cache
+.eslintcache
+
+# Optional stylelint cache
+.stylelintcache
+
+# Microbundle cache
+.rpt2_cache/
+.rts2_cache_cjs/
+.rts2_cache_es/
+.rts2_cache_umd/
+
+# Optional REPL history
+.node_repl_history
+
+# Output of 'npm pack'
+*.tgz
+
+# Yarn Integrity file
+.yarn-integrity
+
+# dotenv environment variable files
+.env
+.env.development.local
+.env.test.local
+.env.production.local
+.env.local
+
+# parcel-bundler cache (https://parceljs.org/)
+.cache
+.parcel-cache
+
+# Next.js build output
+.next
+out
+
+# Nuxt.js build / generate output
+.nuxt
+dist
+
+# Gatsby files
+.cache/
+# Comment in the public line in if your project uses Gatsby and not Next.js
+# https://nextjs.org/blog/next-9-1#public-directory-support
+# public
+
+# vuepress build output
+.vuepress/dist
+
+# vuepress v2.x temp and cache directory
+.temp
+
+# Docusaurus cache and generated files
+.docusaurus
+
+# Serverless directories
+.serverless/
+
+# FuseBox cache
+.fusebox/
+
+# DynamoDB Local files
+.dynamodb/
+
+# TernJS port file
+.tern-port
+
+# Stores VSCode versions used for testing VSCode extensions
+.vscode-test
+
+# yarn v2
+.yarn/cache
+.yarn/unplugged
+.yarn/build-state.yml
+.yarn/install-state.gz
+.pnp.*
+
+### Node Patch ###
+# Serverless Webpack directories
+.webpack/
+
+# Optional stylelint cache
+
+# SvelteKit build / generate output
+.svelte-kit
+
+# End of https://www.toptal.com/developers/gitignore/api/node

README.md

@@ -41,6 +41,8 @@ dataset.upload_dataset(task="text_clf", split="train", module_dir="path_to_imdb_
 | Compute Orchestration      | [CRUD Operations](ComputeOrchestration/crud_operations.ipynb) | Basic Functionalities (create, list, get, delete) of Compute Orchestration Classes - ComputeCluster, Nodepool, Deployment | [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Clarifai/examples/blob/main/ComputeOrchestration/crud_operations.ipynb) |
 | Model Predict  | [Predict](models/model_predict/README.md) | Call predict of any model in a [Python native way](models/model_predict/clarifai_llm.py) with our SDK. See many more examples [here](models/model_predict/) | [Docs for Python/Javascript](https://docs.clarifai.com/compute/models/inference/api) |
 |                | [Using OpenAI Client](models/model_predict/openai_llm.py) | Use the openAI client to call openAI-compatible models in Clarifai. See many more examples [here](models/model_predict/).  | [Docs for Pyhon/Typescript](https://docs.clarifai.com/compute/models/inference/open-ai) |
+|               | [Using OpenAI Client on Node.js](nodejs/openai/getTextResponse.js) | Use the OpenAI node client to call OpenAI-compatible models in Clarifai. See many more examples [here](nodejs/openai/) | [Docs for Typescript](https://docs.clarifai.com/compute/models/inference/open-ai/) |
+|               | [Using Vercel AI SDK on Node.js](nodejs/vercel-ai-sdk/getTextResponse.js) | Use the Vercel AI SDK with OpenAI provider to call OpenAI-compatible models in Clarifai. See many more examples [here](nodejs/vercel-ai-sdk/) | [Docs for Typescript](https://docs.clarifai.com/compute/models/inference/open-ai/) |
 |                | [Using LiteLLM](models/model_predict/openai_llm.py) | Use Litellm to call openAI-compatible models in Clarifai. See many more examples [here](models/model_predict/) |  |
 |                | [Legacy Models](http://docs.clarifai.com/compute/models/inference/api-legacy/) | Call predict of any model not uploaded to compute orchestration with our SDK | [Docs](http://docs.clarifai.com/compute/models/inference/api-legacy/) |
 | Model Upload  | [Model Upload](https://github.com/clarifai/runners-examples) | Upload custom models, MCP tools, or any python function you want. See our new runner examples repo for compute orchestration with many examples covered! |  |

nodejs/openai/README.md

@@ -0,0 +1,39 @@
+# Clarifai Open AI Example
+
+Clarifai provides an OpenAI-compatible API endpoint, which allows you to leverage your existing OpenAI API code and workflows to make inferences with Clarifai models, including those that integrate or wrap OpenAI models.
+
+The built-in compatibility layer converts your OpenAI calls directly into Clarifai API requests, letting you harness Clarifai's diverse models as custom tools in your OpenAI projects.
+
+This simplifies the integration process, as you don't need to rewrite your code specifically for Clarifai's native API structure if you're already familiar with OpenAI's.
+
+## Prerequisites
+
+- A Clarifai account with API access
+- A Clarifai Personal Access Token (PAT)
+
+## Setup
+
+Clone this directory to your local machine using [degit](https://github.com/Rich-Harris/degit)
+
+```bash
+degit clarifai/examples/nodejs/openai
+```
+
+Install the required packages:
+
+```bash
+npm install
+```
+
+Add your Clarifai PAT to the environment variable `CLARIFAI_PAT`
+
+```bash
+export CLARIFAI_PAT=your_pat_here
+```
+
+or use a `.env` file to setup your environment variables.
+
+## Notes
+
+- The example uses Clarifai's GPT-4o model by default, but you can easily switch to other models
+- Make sure your Clarifai PAT has the necessary permissions

nodejs/openai/getStreamingResponse.js

@@ -0,0 +1,23 @@
+import OpenAI from "openai";
+
+// Ensure you have the CLARIFAI_PAT environment variable set with your Clarifai Personal Access Token
+const client = new OpenAI({
+  baseURL: "https://api.clarifai.com/v2/ext/openai/v1",
+  apiKey: process.env.CLARIFAI_PAT,
+});
+
+// Stream response from the model
+const streamingResponse = await client.chat.completions.create({
+  model: "https://clarifai.com/openai/chat-completion/models/gpt-4o",
+  messages: [
+    { role: "system", content: "You are a helpful assistant." },
+    { role: "user", content: "What is photosynthesis?" },
+  ],
+  stream: true,
+});
+
+for await (const part of streamingResponse) {
+  if (part.choices?.[0]?.delta.content) {
+    console.log(part.choices[0].delta.content);
+  }
+}

nodejs/openai/getTextResponse.js

@@ -0,0 +1,18 @@
+import OpenAI from "openai";
+
+// Ensure you have the CLARIFAI_PAT environment variable set with your Clarifai Personal Access Token
+const client = new OpenAI({
+  baseURL: "https://api.clarifai.com/v2/ext/openai/v1",
+  apiKey: process.env.CLARIFAI_PAT,
+});
+
+// Example usage of the OpenAI client with Clarifai's GPT-4o model
+const response = await client.chat.completions.create({
+  model: "https://clarifai.com/openai/chat-completion/models/gpt-4o",
+  messages: [
+    { role: "system", content: "You are a helpful assistant." },
+    { role: "user", content: "What is photosynthesis?" },
+  ],
+});
+
+console.log(response.choices?.[0]?.message.content);

nodejs/openai/package.json

@@ -0,0 +1,16 @@
+{
+  "name": "openai",
+  "version": "1.0.0",
+  "description": "",
+  "main": "index.js",
+  "type": "module",
+  "scripts": {
+    "test": "echo \"Error: no test specified\" && exit 1"
+  },
+  "keywords": [],
+  "author": "",
+  "license": "ISC",
+  "dependencies": {
+    "openai": "^5.0.1"
+  }
+}

nodejs/openai/toolCalling.js

@@ -0,0 +1,41 @@
+import OpenAI from "openai";
+
+// Ensure you have the CLARIFAI_PAT environment variable set with your Clarifai Personal Access Token
+const client = new OpenAI({
+  baseURL: "https://api.clarifai.com/v2/ext/openai/v1",
+  apiKey: process.env.CLARIFAI_PAT,
+});
+
+// Example of using tools with the OpenAI client
+const tools = [
+  {
+    type: "function",
+    function: {
+      name: "get_weather",
+      description: "Get current temperature for a given location.",
+      parameters: {
+        type: "object",
+        properties: {
+          location: {
+            type: "string",
+            description: "City and country e.g. Bogotá, Colombia",
+          },
+        },
+        required: ["location"],
+        additionalProperties: false,
+      },
+      strict: true,
+    },
+  },
+];
+
+const toolCompletion = await client.chat.completions.create({
+  model: "https://clarifai.com/openai/chat-completion/models/gpt-4o",
+  messages: [
+    { role: "system", content: "You are a helpful assistant." },
+    { role: "user", content: "What is the weather in New York?" },
+  ],
+  tools,
+});
+
+console.log(toolCompletion.choices?.[0]?.message.tool_calls);

nodejs/vercel-ai-sdk/README.md

@@ -0,0 +1,41 @@
+# Clarifai Vercel AI SDK Example
+
+Clarifai provides an OpenAI-compatible API endpoint, which allows you to leverage your existing OpenAI API code and workflows to make inferences with Clarifai models, including those that integrate or wrap OpenAI models.
+
+The built-in compatibility layer converts your OpenAI calls directly into Clarifai API requests, letting you harness Clarifai's diverse models as custom tools in your OpenAI projects.
+
+This simplifies the integration process, as you don't need to rewrite your code specifically for Clarifai's native API structure if you're already familiar with OpenAI's.
+
+The [Vercel AI SDK](https://ai-sdk.dev/) provides a convenient way to interact with Clarifai's OpenAI-compatible API. You can leverage the [OpenAI provider](https://ai-sdk.dev/providers/ai-sdk-providers/openai) to interact with Clarifai models.
+
+## Prerequisites
+
+- A Clarifai account with API access
+- A Clarifai Personal Access Token (PAT)
+
+## Setup
+
+Clone this directory to your local machine using [degit](https://github.com/Rich-Harris/degit)
+
+```bash
+degit clarifai/examples/nodejs/vercel-ai-sdk
+```
+
+Install the required packages:
+
+```bash
+npm install
+```
+
+Add your Clarifai PAT to the environment variable `CLARIFAI_PAT`
+
+```bash
+export CLARIFAI_PAT=your_pat_here
+```
+
+or use a `.env` file to setup your environment variables.
+
+## Notes
+
+- The example uses Clarifai's GPT-4o model by default, but you can easily switch to other models
+- Make sure your Clarifai PAT has the necessary permissions

nodejs/vercel-ai-sdk/getStreamingResponse.js

@@ -0,0 +1,23 @@
+import { createOpenAI } from "@ai-sdk/openai";
+import { streamText } from "ai";
+
+const openai = createOpenAI({
+  baseURL: "https://api.clarifai.com/v2/ext/openai/v1",
+  apiKey: process.env.CLARIFAI_PAT,
+});
+
+const model = openai(
+  "https://clarifai.com/openai/chat-completion/models/gpt-4o",
+);
+
+const stream = streamText({
+  model,
+  messages: [
+    { role: "system", content: "You are a helpful assistant." },
+    { role: "user", content: "What is photosynthesis?" },
+  ],
+});
+
+for await (const part of stream.textStream) {
+  console.log(part);
+}

nodejs/vercel-ai-sdk/getTextResponse.js

@@ -0,0 +1,21 @@
+import { createOpenAI } from "@ai-sdk/openai";
+import { generateText } from "ai";
+
+const openai = createOpenAI({
+  baseURL: "https://api.clarifai.com/v2/ext/openai/v1",
+  apiKey: process.env.CLARIFAI_PAT,
+});
+
+const model = openai(
+  "https://clarifai.com/openai/chat-completion/models/gpt-4o",
+);
+
+const { text } = await generateText({
+  model,
+  messages: [
+    { role: "system", content: "You are a helpful assistant." },
+    { role: "user", content: "What is photosynthesis?" },
+  ],
+});
+
+console.log(text);