1Stack AI Mission Control API Reference

import requests

response = requests.get(
    "https://taas.cloudsigma.com/v1/models",
    headers={"Authorization": "Bearer taas_xxxxxxxxxxxxxxxx"}
)
models = response.json()
for m in models:
    print(m["id"])  # e.g. "claude-sonnet-4"

const response = await fetch(
  "https://taas.cloudsigma.com/v1/models",
  {
    headers: {
      "Authorization": "Bearer taas_xxxxxxxxxxxxxxxx"
    }
  }
);
const models = await response.json();
models.forEach(m => console.log(m.id));

import requests

response = requests.post(
    "https://taas.cloudsigma.com/v1/chat/completions",
    headers={"Authorization": "Bearer taas_xxxxxxxxxxxxxxxx"},
    json={
        "model": "claude-sonnet-4",
        "messages": [
            {"role": "system", "content": "You are a helpful assistant."},
            {"role": "user", "content": "Explain quantum entanglement."}
        ],
        "temperature": 0.7,
        "max_tokens": 512
    }
)
result = response.json()
print(result["choices"][0]["message"]["content"])

const response = await fetch(
  "https://taas.cloudsigma.com/v1/chat/completions",
  {
    method: "POST",
    headers: {
      "Authorization": "Bearer taas_xxxxxxxxxxxxxxxx",
      "Content-Type": "application/json",
    },
    body: JSON.stringify({
      model: "claude-sonnet-4",
      messages: [
        { role: "system", content: "You are a helpful assistant." },
        { role: "user", content: "Explain quantum entanglement." }
      ],
      temperature: 0.7,
      max_tokens: 512,
    }),
  }
);
const data = await response.json();
console.log(data.choices[0].message.content);

import requests

response = requests.post(
    "https://taas.cloudsigma.com/v1/embeddings",
    headers={"Authorization": "Bearer taas_xxxxxxxxxxxxxxxx"},
    json={
        "model": "bge-m3",
        "input": ["Hello world", "How are you?"]
    }
)
data = response.json()
vector = data["data"][0]["embedding"]
print(f"Dimensions: {len(vector)}")

const response = await fetch(
  "https://taas.cloudsigma.com/v1/embeddings",
  {
    method: "POST",
    headers: {
      "Authorization": "Bearer taas_xxxxxxxxxxxxxxxx",
      "Content-Type": "application/json",
    },
    body: JSON.stringify({
      model: "bge-m3",
      input: ["Hello world", "How are you?"],
    }),
  }
);
const data = await response.json();
console.log(`Dims: ${data.data[0].embedding.length}`);

import requests

response = requests.post(
    "https://taas.cloudsigma.com/v1/rerank",
    headers={"Authorization": "Bearer taas_xxxxxxxxxxxxxxxx"},
    json={
        "model": "bge-reranker-v2-m3",
        "query": "What is quantum computing?",
        "documents": [
            "Quantum computing uses qubits to process information.",
            "Classical computers use binary bits.",
            "The weather today is sunny."
        ]
    }
)
results = response.json()["results"]
for r in results:
    print(f"idx={r['index']} score={r['relevance_score']:.4f}")

const response = await fetch(
  "https://taas.cloudsigma.com/v1/rerank",
  {
    method: "POST",
    headers: {
      "Authorization": "Bearer taas_xxxxxxxxxxxxxxxx",
      "Content-Type": "application/json",
    },
    body: JSON.stringify({
      model: "bge-reranker-v2-m3",
      query: "What is quantum computing?",
      documents: [
        "Quantum computing uses qubits to process information.",
        "Classical computers use binary bits.",
        "The weather today is sunny.",
      ],
    }),
  }
);
const { results } = await response.json();

import requests

with open("recording.wav", "rb") as f:
    response = requests.post(
        "https://taas.cloudsigma.com/v1/audio/transcriptions",
        headers={"Authorization": "Bearer taas_xxxxxxxxxxxxxxxx"},
        files={"file": ("recording.wav", f, "audio/wav")},
        data={"model": "whisper"}
    )
result = response.json()
print(result["text"])

const formData = new FormData();
formData.append("file", audioBlob, "recording.wav");
formData.append("model", "whisper");

const response = await fetch(
  "https://taas.cloudsigma.com/v1/audio/transcriptions",
  {
    method: "POST",
    headers: {
      "Authorization": "Bearer taas_xxxxxxxxxxxxxxxx"
    },
    body: formData,
  }
);
const { text } = await response.json();
console.log(text);

import requests

response = requests.post(
    "https://taas.cloudsigma.com/v1/audio/speech",
    headers={"Authorization": "Bearer taas_xxxxxxxxxxxxxxxx"},
    json={
        "model": "kokoro",
        "input": "Welcome to AI Mission Control.",
        "voice": "af_sarah"
    }
)
with open("speech.mp3", "wb") as f:
    f.write(response.content)
print("Saved speech.mp3")

const response = await fetch(
  "https://taas.cloudsigma.com/v1/audio/speech",
  {
    method: "POST",
    headers: {
      "Authorization": "Bearer taas_xxxxxxxxxxxxxxxx",
      "Content-Type": "application/json",
    },
    body: JSON.stringify({
      model: "kokoro",
      input: "Welcome to AI Mission Control.",
      voice: "af_sarah",
    }),
  }
);
const audioBuffer = await response.arrayBuffer();
// Play or save the audio binary

import requests

response = requests.get("https://taas.cloudsigma.com/health")
print(response.json())  # {"status": "ok"}

const response = await fetch(
  "https://taas.cloudsigma.com/health"
);
const data = await response.json();
console.log(data.status); // "ok"