# 1. Install official SDK: pip install openai
import os
from openai import OpenAI

# Authenticate with either Virtual API Key or User Login JWT
client = OpenAI(
    base_url="http://localhost:3000/v1",
    api_key=os.environ.get("NEXUS_API_KEY", "sk-live-your-virtual-key") # or user session JWT
)

response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[
        {"role": "system", "content": "You are a specialized code consultant."},
        {"role": "user", "content": "Summarize the benefits of dynamic API routing."}
    ],
    stream=True
)

for chunk in response:
    content = chunk.choices[0].delta.content
    if content:
        print(content, end="", flush=True)
print()

// app/api/chat/route.ts
import { OpenAI } from 'openai';

export async function POST(req: Request) {
  const { messages, model = 'gpt-4o-mini' } = await req.json();

  // Extract client's session token from incoming Authorization header,
  // or fall back to server-side virtual key
  const authHeader = req.headers.get('authorization');
  const bearerToken = authHeader ? authHeader.replace(/^Bearer\s+/i, '') : process.env.NEXUS_API_KEY;

  const client = new OpenAI({
    baseURL: process.env.NEXUS_BASE_URL || 'http://localhost:3000/v1',
    apiKey: bearerToken,
  });

  const response = await client.chat.completions.create({
    model,
    messages,
    stream: true,
  });

  // Convert OpenAI streaming response to standard Web ReadableStream
  const stream = new ReadableStream({
    async start(controller) {
      for await (const chunk of response) {
        const text = chunk.choices[0]?.delta?.content || '';
        controller.enqueue(new TextEncoder().encode(text));
      }
      controller.close();
    },
  });

  return new Response(stream, {
    headers: { 'Content-Type': 'text/plain; charset=utf-8' },
  });
}

# Option 1: Authenticate with Virtual API Key (sk-live-...)
curl -X POST http://localhost:3000/v1/chat/completions \
  -H "Authorization: Bearer sk-live-your_virtual_key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-4o-mini",
    "messages": [
      {"role": "user", "content": "Explain quantum superposition in 1 sentence."}
    ]
  }'

# Option 2: Authenticate with User Login Session (Frontend App - No API Key Needed)
curl -X POST http://localhost:3000/v1/chat/completions \
  -H "Authorization: Bearer eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9..." \
  -H "Content-Type: application/json" \
  -d '{
    "model": "claude-3-5-sonnet",
    "messages": [
      {"role": "user", "content": "Provide a high-level summary of Q3 financial earnings."}
    ]
  }'

from langchain_openai import ChatOpenAI
from langchain_core.messages import HumanMessage

# Initialize LangChain with Pikpam Router endpoint
llm = ChatOpenAI(
    base_url="http://localhost:3000/v1",
    api_key="sk-live-your_virtual_key",  # or pass user login JWT session token
    model="gpt-4o-mini",
    temperature=0.7
)

response = llm.invoke([
    HumanMessage(content="What are the key architectural benefits of an API router?")
])

print(response.content)