Merge pull request #15 from mrsteele/feature/client

Feature/client

README.md

@@ -19,14 +19,31 @@ This package was written by an author who actively uses OpenAI and was running i
 npm i openai-tokens
 ```
 
+## Quick Start
+
+If you are looking for all the bells and whistles provided out of the box, it is recommended to use the `client`.
+
+```js
+import { createClient } = from 'openai-tokens'
+
+const client = createClient({
+  key: 'your-openai-key-here',
+  limit: 1000 // Maybe add a limit if you want
+})
+
+const response = await client.gpt('Is this working?')
+console.log(response.content)
+// 'Yes, it seems like we are connected!'
+```
+
 ## Use-Cases
 
 ### Automatically swapping models based on token size
 
 If you have too much content in your request, you can change your model dynamically so you use an appropriate size for each request.
 
 ```js
-const { dynamicWrapper } = require('openai-tokens')
+import { dynamicWrapper } from 'openai-tokens'
 
 const chat = async (messages = []) => {
   const body = await fetch('https://api.openai.com/v1/chat/completions', {
@@ -99,6 +116,122 @@ await fetch('https://api.openai.com/v1/embeddings', {
 
 ## Complete Usage
 
+### createClient
+
+In an effort to streamline all the utilities into a single opinionated service, you can create a `client` that will determine waht is the best model and truncate if needed to fit your needs.
+
+```js
+import { createClient } = from 'openai-tokens'
+
+const client = createClient({
+  // put in your OpenAI key here
+  key: 'your-openai-key-here',
+  // (optional - defaults to 'null') - A limit on the prompts. If `null` it will be the model limit.
+  limit: 1000,
+  // (optional - defaults to `null`) - A buffer on the token count to let GPT respond
+  buffer: 1000,
+  // (optional - defaults below) Pass multiple models for adaptive models based on prompt size
+  gptModels: ['gpt-3.5-turbo', 'gpt-3.5-turbo-16k']
+})
+
+// single
+await client.gpt('Is this working?')
+// '{ content: 'Yes, it seems like we are connected!' }
+
+// multi
+await client.gpt([{
+  role: 'system',
+  content: 'You are a bot'
+}, {
+  role: 'user',
+  content: 'What is your name?!'
+}])
+// '{ content: 'I am a bot using the model gpt-3.5-turbo.' }
+
+// configurable on an individual basis
+await client.gpt({
+  opts: {
+    // this overrides what was on the client in this instance only
+    buffer: 500
+  },
+  messages: [{
+    role: 'system',
+    content: 'You are a bot'
+  }, {
+    role: 'user',
+    content: 'What is your name?!'
+  }]
+})
+// '{ content: 'A bot using 3.5 turbo!' }
+```
+
+#### Options
+
+The client itself can be created and configured with the following options:
+
+* **key** (String) - REQUIRED. This is your key that is provided from OpenAI. Used for all your prompts.
+* **limit** (Int) - The token limit you want to enforce on the messages/input. This is the aggregated results for messages (GPT/Completions), and the individual results for inputs/embeddings which is how they are calculated by OpenAI. Defaults to the model maximum.
+* **buffer** (Int) - The amount of additional restriction you want to apply to the limit. The math equates to `max = limit - buffer`. Defaults to `0`.
+* **json** (Bool) - Automatically returns the response as json. Defaults to `true`.
+* **truncate** (Bool) - Uses some advanced logic to ensure that the prompts fit with the respective models and considers your limits and buffers. Defaults to `true`.
+* **gptModels**: (String[]) - An array of models used for GPT completions. Uses the `validationWrapper` to find the best model to use. Defaults to `['gpt-3.5-turbo', 'gpt-3.5-turbo-4k']`.
+* **embeddingModels**: (String[]) - An array of models used for Embeddings. There is only one at the moment. Defaults to `['ada-embeddings']`.
+
+#### Returns
+
+The client will return two properties:
+
+* **gpt** - Run a GPT completion. Supports a `String`, `Array`, or an `Object` as the argument (see examples below):
+```js
+// String
+await client.gpt('Is this working?')
+
+// Array
+await client.gpt([{
+  role: 'system',
+  content: 'You are a bot'
+}, {
+  role: 'user',
+  content: 'What is your name?!'
+}])
+
+// Object
+await client.gpt({
+  opts: {
+    limit: 500,
+  },
+  messages: [{
+    role: 'system',
+    content: 'You are a bot'
+  }, {
+    role: 'user',
+    content: 'What is your name?!'
+  }]
+})
+```
+* **embed** - Run an Embedding. Supports a `String`, `Array` or an `Object`. See examples below:
+```js
+// String
+await client.embed('Is this working?')
+
+// Array
+await client.embed([
+  'You are a bot',
+  'What is your name?!'
+])
+
+// Object
+await client.embed({
+  opts: {
+    limit: 500,
+  },
+  input: [
+    'You are a bot',
+    'What is your name?!'
+  ]
+})
+```
+
 ### Truncate
 
 You can use the truncate tools to enforce cutoffs of sentences that are too large. This can be automatically detected or you can provide your own limits. The truncation is programmed to break on a word, not in the middle.
@@ -196,7 +329,7 @@ You can pass options to the validate wrapper as seen in the examples above. The
 A dynamic router has been provided for convenience. This allows you to pass multiple models. The module will choose the first valid model, so you can always maintain the smallest possible (and save some money 💰).
 
 ```js
-const { dynamicWrapper } = require('openai-tokens')
+import { dynamicWrapper } = from 'openai-tokens'
 
 const chat = async (messages = []) => {
   const body = await fetch('https://api.openai.com/v1/chat/completions', {
@@ -240,7 +373,7 @@ If you provide a model that is not supported, you will get a console message as
 YES! A good example of this would be using the `dynamicWrapper` and the `truncateWrapper` together like so:
 
 ```js
-const { dynamicWrapper, truncateWrapper } = require('openai-tokens')
+import { dynamicWrapper, truncateWrapper } from 'openai-tokens'
 
 const chat = async (messages = []) => {
   const body = await fetch('https://api.openai.com/v1/chat/completions', {

package.json

@@ -42,6 +42,7 @@
   "author": "Matt Steele <[email protected]>",
   "license": "MIT",
   "dependencies": {
+    "isomorphic-fetch": "^3.0.0",
     "js-tiktoken": "^1.0.7"
   },
   "devDependencies": {