Working with API

You can use LangDB as a drop-in replacement for OpenAI APIs, making it easy to integrate into existing workflows and libraries such as OpenAI Client SDK.

You can choose from any of the supported models.

Python

from openai import OpenAI

langdb_project_id = "xxxxx"  # LangDB Project ID

client = OpenAI(
    base_url=f"https://api.us-east-1.langdb.ai/{langdb_project_id}/v1",
    api_key="xxxxx" ,           # LangDB token
)
response = client.chat.completions.create(
    model="anthropic/claude-sonnet-4", # Change Model
    messages=[
        {"role": "system", "content": "You are a helpful assistant"},
        {"role": "user", "content": "What are the earnings of Apple in 2022?"},
    ],
)
print("Assistant:", response.choices[0].message)

TypeScript

import { OpenAI } from 'openai';

const langdbProjectId = 'xxxx';  // LangDB Project ID

const client = new OpenAI({
  baseURL: `https://api.us-east-1.langdb.ai/${langdbProjectId}/v1`,
  apiKey:  'xxxx'   // Your LangDB token,
});

const messages = [
  {
    role: 'system',
    content: 'You are a helpful assistant.'
  },
  {
    role: 'user',
    content: 'What are the earnings of Apple in 2022?'
  }
];
async function getAssistantReply() {
  const { choices } = await client.chat.completions.create({
    model: 'gpt-4o-mini',
    messages: messages
  });
  console.log('Assistant:', choices[0].message.content);
}
getAssistantReply();

cURL

curl "https://api.us-east-1.langdb.ai/v1/chat/completions" \
    -H "Content-Type: application/json" \
    -H "Authorization: Bearer $LANGDB_API_KEY" \
    -X "X-Project-Id: $Project_ID" \
    -d '{
        "model": "gpt-4o",
        "messages": [
            {
                "role": "user",
                "content": "Write a haiku about recursion in programming."
            }
        ],
        "temperature": 0.8
    }'

After sending your request, you can see the Traces on the dashboard:

Check out the API reference here.