IBM Granite 3.1 8B

import { streamText } from "ai";
import { createOpenAI } from "@ai-sdk/openai";

const router = createOpenAI({
  apiKey: process.env.ROUTER_API_KEY,
  baseURL: "https://api.megapromoting.com/v1",
});

export async function POST(req: Request) {
  const { messages } = await req.json();
  const result = streamText({
    model: router("granite-3-1-8b"),
    messages,
  });
  return result.toDataStreamResponse();
}

import OpenAI from "openai";

const client = new OpenAI({
  apiKey: process.env.ROUTER_API_KEY,
  baseURL: "https://api.megapromoting.com/v1",   // <— singura linie diferită
});

const r = await client.chat.completions.create({
  model: "granite-3-1-8b",
  messages: [{ role: "user", content: "Salut!" }],
});
console.log(r.choices[0].message.content);

from openai import OpenAI

client = OpenAI(
    api_key=os.environ["ROUTER_API_KEY"],
    base_url="https://api.megapromoting.com/v1",
)

r = client.chat.completions.create(
    model="granite-3-1-8b",
    messages=[{"role": "user", "content": "Salut!"}],
)
print(r.choices[0].message.content)

from langchain_openai import ChatOpenAI

llm = ChatOpenAI(
    model="granite-3-1-8b",
    openai_api_key=os.environ["ROUTER_API_KEY"],
    openai_api_base="https://api.megapromoting.com/v1",
)

resp = llm.invoke("Răspunde în română.")
print(resp.content)

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

const llm = new ChatOpenAI({
  model: "granite-3-1-8b",
  apiKey: process.env.ROUTER_API_KEY,
  configuration: { baseURL: "https://api.megapromoting.com/v1" },
});

const r = await llm.invoke("Răspunde în română.");
console.log(r.content);

from llama_index.llms.openai import OpenAI

llm = OpenAI(
    model="granite-3-1-8b",
    api_key=os.environ["ROUTER_API_KEY"],
    api_base="https://api.megapromoting.com/v1",
)

print(llm.complete("Generează un titlu pentru articol despre AI în Moldova"))

from fastapi import FastAPI
from openai import AsyncOpenAI

app = FastAPI()
client = AsyncOpenAI(
    api_key=os.environ["ROUTER_API_KEY"],
    base_url="https://api.megapromoting.com/v1",
)

@app.post("/chat")
async def chat(prompt: str):
    r = await client.chat.completions.create(
        model="granite-3-1-8b",
        messages=[{"role": "user", "content": prompt}],
    )
    return {"text": r.choices[0].message.content}

"use server";

import OpenAI from "openai";

const client = new OpenAI({
  apiKey: process.env.ROUTER_API_KEY,
  baseURL: "https://api.megapromoting.com/v1",
});

export async function summarize(text: string) {
  const r = await client.chat.completions.create({
    model: "granite-3-1-8b",
    messages: [
      { role: "system", content: "Rezumi text în 3 puncte." },
      { role: "user", content: text },
    ],
  });
  return r.choices[0].message.content;
}