PaLM API: Chat Quickstart with Node.js

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Overview

This quickstart demonstrates how to use the PaLM API, which gives you access to Google's latest large language models, with the PaLM Node.js SDK specifically for dialog-focused use cases, such as chatbots.

Obtain an API Key

To get started, you'll need to get an API key. Set it as an environment variable:

import os
os.environ["API_KEY"] = "<YOUR API KEY>"

Install the API client

In a new directory, initialize a Node.js project using npm and install the google-auth library:

npm init -y

npm install google-auth-library
 
Wrote to /content/package.json:

{
  "name": "content",
  "version": "1.0.0",
  "main": "index.js",
  "scripts": {
    "test": "echo \"Error: no test specified\" && exit 1"
  },
  "keywords": [],
  "author": "",
  "license": "ISC",
  "dependencies": {
    "@google-ai/generativelanguage": "^1.0.1",
    "google-auth-library": "^9.0.0"
  },
  "devDependencies": {},
  "description": ""
}


+ google-auth-library@9.0.0
updated 1 package and audited 74 packages in 0.905s

3 packages are looking for funding
  run `npm fund` for details

found 0 vulnerabilities
npm WARN content@1.0.0 No description
npm WARN content@1.0.0 No repository field.

Next, install the client library:

npm install @google-ai/generativelanguage
 

+ @google-ai/generativelanguage@1.0.1
updated 1 package and audited 74 packages in 2.274s

3 packages are looking for funding
  run `npm fund` for details

found 0 vulnerabilities
npm WARN content@1.0.0 No description
npm WARN content@1.0.0 No repository field.

Obtain an API key

Follow the instructions on the setup page to create an API key for your app. You will need this API key in the next step.

Generate messages

Create a new file index.js and add the following code, supplying your PaLM API key through the API_KEY environment variable:

%%writefile index.js

const { DiscussServiceClient } = require("@google-ai/generativelanguage");
const { GoogleAuth } = require("google-auth-library");

const MODEL_NAME = "models/chat-bison-001";
const API_KEY = process.env.API_KEY;

const client = new DiscussServiceClient({
  authClient: new GoogleAuth().fromAPIKey(API_KEY),
});

async function main() {
  const result = await client.generateMessage({
    model: MODEL_NAME, // Required. The model to use to generate the result.
    temperature: 0.5, // Optional. Value `0.0` always uses the highest-probability result.
    candidateCount: 1, // Optional. The number of candidate results to generate.
    prompt: {
      // optional, preamble context to prime responses
      context: "Respond to all questions with a rhyming poem.",
      // Optional. Examples for further fine-tuning of responses.
      examples: [
        {
          input: { content: "What is the capital of California?" },
          output: {
            content:
              `If the capital of California is what you seek,
Sacramento is where you ought to peek.`,
          },
        },
      ],
      // Required. Alternating prompt/response messages.
      messages: [{ content: "How tall is the Eiffel Tower?" }],
    },
  });

  console.log(result[0].candidates[0].content);
}

main();

Overwriting index.js

Then run the script:

node index.js
 
The Eiffel Tower is 324 meters tall,
It's a sight to behold, tall and not small.
It's made of iron and weighs 10,100 tons,
It's a wonder of the world, it's a must-see for all.

Continue the conversation

To continue a conversation after an initial prompt message, you need to append the returned candidate message as well as your next prompt:

%%writefile index.js
const { DiscussServiceClient } = require("@google-ai/generativelanguage");
const { GoogleAuth } = require("google-auth-library");

const MODEL_NAME = "models/chat-bison-001";
const API_KEY = process.env.API_KEY;

const client = new DiscussServiceClient({
  authClient: new GoogleAuth().fromAPIKey(API_KEY),
});

async function main() {
  let first = "Tell me a one short animal fact."
  let messages = [{ content: first }];

  const result = await client.generateMessage({
    model: MODEL_NAME,
    prompt: { messages },
  });

  console.log("User:\n\n", first, "\n\n")
  console.log("Palm:\n\n", result[0].candidates[0].content, "\n\n");

  let second = "Oh, where do those live?"

  messages.push({ content: result[0].candidates[0].content });
  messages.push({ content: second });

  const secondResult = await client.generateMessage({
    model: MODEL_NAME,
    prompt: { messages },
  });

  console.log("User:\n\n", second, "\n\n")
  console.log("Palm:\n\n", secondResult[0].candidates[0].content, "\n\n");
}

main();

Overwriting index.js

node index.js
 
User:

 Tell me a one short animal fact. 


Palm:

 The world's smallest mammal is the bumblebee bat, which weighs less than a penny. 


User:

 Oh, where do those live? 


Palm:

 The bumblebee bat is found in the rainforests of Thailand, Myanmar, and Laos. It is a small, nocturnal bat that feeds on insects. The bumblebee bat is the smallest mammal in the world, weighing only about 2 grams. It is about the size of a bumblebee, hence its name. The bumblebee bat is a very important part of the rainforest ecosystem. It helps to control insect populations and pollinate plants.