LangChain

Connect Praxis to LangChain (JS/TS)—chains, memory, and the whole toolkit work as usual; the model side changes one baseURL. This page is verified against Node.

Every step lists its expected result: follow along yourself, or hand this page to an AI assistant that can operate your computer and let it do the install, run, and verification for you.

What you'll accomplish

• Call Praxis models with LangChain's ChatOpenAI and get replies plus usage
• Done when: hello.mjs prints a reply with usage, and stream.mjs prints token by token
• Time needed: 3–5 minutes (excluding the Node.js install)
• Protocol: OpenAI-compatible (/openai/v1)

Prerequisites

Confirm each item before you start:

• A Praxis API key (starting with sk-praxis-). If you don't have one, create it at Console → API Keys: click "Create Key"—the name is required, validity offers 30/60/90 days or permanent, defaulting to 90 days; the success dialog shows the full key with a "Copy Key" button, and after it closes the list shows only a masked value—re-copy the full key any time from the copy icon on its row. Expected: a "Create API Key" dialog appears, and after submitting, a dialog shows the full key with a "Copy Key" button. New accounts ship with $1 of free credit. See Quickstart for the full flow.

• Node.js 18 or newer (check node --version; Bun works too).

• Install the SDK:

  npm install @langchain/openai

  Expected: the install succeeds. An empty directory works—npm generates package.json, package-lock.json, and node_modules there; run npm install langchain when you need chains, prompt templates, or output parsers.

First request

Put the key in an environment variable first (export PRAXIS_API_KEY=sk-praxis-…; PowerShell: $env:PRAXIS_API_KEY="…"), then create hello.mjs:

import { ChatOpenAI } from "@langchain/openai";

const model = new ChatOpenAI({
  model: "deepseek-flash",
  configuration: {
    baseURL: "https://api.deepraxis.com/openai/v1",
    apiKey: process.env.PRAXIS_API_KEY,
  },
});

const res = await model.invoke("Introduce yourself in one sentence");
console.log(res.content);
console.log(res.usage_metadata);

Run it:

node hello.mjs

Expected: a reply prints, followed by the usage object (input_tokens / output_tokens / total_tokens; the reasoning token count sits at output_token_details.reasoning). Note the difference from the official OpenAI SDK: the URL and key live inside the nested configuration object, not at the top level.

Streaming

Create stream.mjs:

import { ChatOpenAI } from "@langchain/openai";

const model = new ChatOpenAI({
  model: "deepseek-flash",
  configuration: {
    baseURL: "https://api.deepraxis.com/openai/v1",
    apiKey: process.env.PRAXIS_API_KEY,
  },
});

const stream = await model.stream("Explain what an API is in two sentences");
for await (const chunk of stream) {
  process.stdout.write(chunk.content);
}
console.log();

Expected: the reply prints token by token, ending with a newline. Streaming support varies by model and its upstream channel; some aren't enabled yet—drop streaming or switch models and retry.

FAQ

Advanced

• Chaining: model.pipe(...) plus prompt templates and output parsers makes a chain—no extra Praxis-side configuration needed
• What did that call cost? LangChain usage carries no price; the OpenAI SDK path returns it directly in usage.cost, or see Console → Usage & Billing
• Switch models: change the model field; deepseek-flash always points at the latest Flash generation

Related recipes

• OpenAI SDK · Anthropic SDK · Vercel AI SDK
• Rather not write code? See Cherry Studio · Claude Code