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Langtail’s TypeScript SDK wraps OpenAI’s API client so that it can be used seamlessly with Langtail. You can store the entire prompt in Langtail and reference it by prompt slug and environment. By routing requests through Langtail, you can get logs, metrics, and many more beneifts. For more, check out the GitHub repository.

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Installation

Use NPM or your package manager of choice to install the langtail package: 
npm i langtail

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Usage

Here are the different ways you can use the SDK. To invoke a deployed prompt, you can use lt.prompts.invoke like this:
Invoke a prompt
const deployedPromptCompletion = await lt.prompts.invoke({
  prompt: '<PROMPT_SLUG>', // required
  environment: 'staging',
  variables: {
    about: 'cowboy Bebop',
  },
}) // results in an openAI ChatCompletion
If you call a prompt that isn’t deployed yet, you will get an error thrown an error: 
Error: Failed to fetch prompt: 404 {"error":"Prompt deployment not found"}

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2. Invoke a prompt that’s stored in code

If you’re storing your prompt in your codebase and want to give Langtail a try, use this method. You can use lt.chat.completions.create as a light wrapper over the OpenAI API that still sends logs and metrics to Langtail. For more, see the example in this doc.

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3. Fetch prompt from Langtail and invoke directly (proxyless)

If you’re storing your prompt in Langtail but want to invoke it directly from your code without using Langtail as a proxy, use this method. You can call LangtailPrompts.get to retrieve the contents of the prompt:
Fetch prompt from Langtail
import { LangtailPrompts } from 'langtail'

const lt = new LangtailPrompts({
  apiKey: '<LANGTAIL_API_KEY>',
})

const prompt = await lt.get({
  prompt: '<PROMPT_SLUG>',
  environment: 'preview',
  version: '<PROMPT_VERSION>', // optional
})
The response will return something like this:
Prompt response
{
  "chatInput": {
    "optionalExtra": ""
  },
  "state": {
    "args": {
      "frequency_penalty": 0,
      "jsonmode": false,
      "max_tokens": 800,
      "model": "gpt-3.5-turbo",
      "presence_penalty": 0,
      "stop": [],
      "stream": true,
      "temperature": 0.5,
      "top_p": 1
    },
    "functions": [],
    "template": [
      {
        "content": "I want you to tell me a joke. Topic of the joke: {{topic}}",
        "role": "system"
      }
    ],
    "tools": [],
    "type": "chat"
  }
}
Now you can build the final output:
Build the final output
const openAiBody = lt.build(prompt, {
  stream: true,
  variables: {
    topic: 'iron man',
  },
})
Which returns this object:
OpenAI body
{
  "frequency_penalty": 0,
  "max_tokens": 800,
  "messages": [
    {
      "content": "I want you to tell me a joke. Topic of the joke: iron man",
      "role": "system",
    },
  ],
  "model": "gpt-3.5-turbo",
  "presence_penalty": 0,
  "temperature": 0.5,
  "top_p": 1,
}
Finally, you can directly call the OpenAI SDK with the returned object:
Call OpenAI SDK
import OpenAI from 'openai'

const openai = new OpenAI()

const joke = await openai.chat.completions.create(openAiBody)
Using this method, you’re getting all of the power of Langtail prompts (like variables) and you’re able to send requests directly to OpenAI. This can be helpful if you’re especially sensitive to performance. If you’re taking this route for security reasons, let us know and give you a deeper look into Langtail.

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API reference

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LangtailNode

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Constructor

The constructor accepts an options object with the following properties:
​
apiKey
string
required
The API key for Langtail.
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baseURL
string
The base URL for the Langtail API.
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doNotRecord
boolean
A boolean indicating whether to record the API calls.
​
organization
string
The organization ID.
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project
string
The project ID.
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fetch
Function
The fetch function to use for making HTTP requests. It is passed to openAI client under the hood.

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Properties

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chat
Object
An object containing a completions object with a create method.
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completions
LangtailPrompts
An instance of the LangtailPrompts class.

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Methods

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chat.completions.create

This method accepts two parameters:
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body
Object
required
An object that can be of type ChatCompletionCreateParamsNonStreaming & ILangtailExtraProps, ChatCompletionCreateParamsStreaming & ILangtailExtraProps, ChatCompletionCreateParamsBase & ILangtailExtraProps, or ChatCompletionCreateParams & ILangtailExtraProps.
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options
Core.RequestOptions
OpenAI Core.RequestOptions object (optional).
It returns a promise that resolves to a ChatCompletion or a Stream<ChatCompletionChunk> depending whether you are using streaming or not.
Create a chat completion
const completion = await lt.chat.completions.create({
  messages: [{ role: 'system', content: 'You are a helpful assistant.' }],
  model: 'gpt-3.5-turbo',
})

console.log(completion.choices[0])

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Exceptions

  • Throws an error if the apiKey is not provided in the options object or as an environment variable.

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LangtailPrompts

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Constructor

The constructor accepts an options object with the following properties:
​
apiKey
string
required
The API key for Langtail.
​
baseURL
string
The base URL for the Langtail API.
​
organization
string
The organization ID.
​
project
string
The project ID.
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fetch
Function
The fetch function to use for making HTTP requests. It is passed to openAI client under the hood.

​
Properties

​
apiKey
string
required
The API key for Langtail.
​
baseUrl
string
The base URL for the Langtail API.
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options
Object
An object containing the options for the Langtail API.

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Methods

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invoke

This method accepts:
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params
IRequestParams | IRequestParamsStream
required
An IRequestParams or IRequestParamsStream object.
It returns a promise that resolves to an OpenAIResponseWithHttp or a StreamResponseType depending on whether you use streaming or not.
Invoke a prompt
const deployedPromptCompletion = await lt.prompts.invoke({
  prompt: '<PROMPT_SLUG>', // required
  environment: 'staging',
  variables: {
    about: 'cowboy Bebop',
  },
}) // results in an openAI ChatCompletion

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get

This method accepts one parameter with these fields:
​
prompt
string
required
A string representing the prompt.
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environment
string
An Environment string identifier. Accepts values: "preview" | "staging" | "production". Defaults to production
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version
string
String for version. Necessary for preview environment.
Returns Langtail state defined here:
Fetch prompt from Langtail
import { LangtailPrompts } from 'langtail'

const lt = new LangtailPrompts({
  apiKey: '<LANGTAIL_API_KEY>',
})

const prompt = await lt.get({
  prompt: '<PROMPT_SLUG>',
  environment: 'preview',
  version: '<PROMPT_VERSION>', // optional
})

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build

This method accepts two parameters:
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state
PromptState
required
The state object returned from the get method.
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options
Object
An object containing the options for the Langtail API.
Returns an object that can be passed to the OpenAI SDK:
Build the final output
const openAiBody = lt.build(prompt, {
  stream: true,
  variables: {
    topic: 'iron man',
  },
})

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Exceptions

  • Throws an error if the fetch operation fails.
  • Throws an error if there is no body in the response when streaming is enabled.
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