Ejemplos

Todos los ejemplos usan el endpoint compatible con OpenAI en https://api.helmcode.com/v1 — cambia sk-your-key-here por una key de tu panel.

Chat completion

cURL

curl https://api.helmcode.com/v1/chat/completions \
  -H "Authorization: Bearer sk-your-key-here" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen3.6",
    "messages": [{"role": "user", "content": "Explain RAG in one sentence."}]
  }'

Python

from openai import OpenAI

client = OpenAI(base_url="https://api.helmcode.com/v1", api_key="sk-your-key-here")

resp = client.chat.completions.create(
    model="deepseek-v4-flash",
    messages=[{"role": "user", "content": "Explain RAG in one sentence."}],
)
print(resp.choices[0].message.content)

Node.js

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api.helmcode.com/v1",
  apiKey: "sk-your-key-here",
});

const resp = await client.chat.completions.create({
  model: "qwen3.6",
  messages: [{ role: "user", content: "Explain RAG in one sentence." }],
});
console.log(resp.choices[0].message.content);

Streaming

stream = client.chat.completions.create(
    model="qwen3.6",
    messages=[{"role": "user", "content": "Write a haiku about Europe."}],
    stream=True,
)
for chunk in stream:
    print(chunk.choices[0].delta.content or "", end="")

Embeddings

emb = client.embeddings.create(
    model="qwen3-embedding",
    input="Helmcode runs inference in the EU.",
)
print(len(emb.data[0].embedding))  # 4096