API Documentation

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://alapi.deep.sa/v1"
)

response = client.chat.completions.create(
    model="llama-3.3-70b-versatile",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "What is the capital of Saudi Arabia?"}
    ],
    temperature=0.7,
    max_tokens=1024
)

print(response.choices[0].message.content)

import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: 'YOUR_API_KEY',
  baseURL: 'https://alapi.deep.sa/v1'
});

async function main() {
  const response = await client.chat.completions.create({
    model: 'llama-3.3-70b-versatile',
    messages: [
      { role: 'system', content: 'You are a helpful assistant.' },
      { role: 'user', content: 'What is the capital of Saudi Arabia?' }
    ],
    temperature: 0.7,
    max_tokens: 1024
  });

  console.log(response.choices[0].message.content);
}

main();

curl -X POST "https://alapi.deep.sa/v1/chat/completions" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "llama-3.3-70b-versatile",
    "messages": [
      {"role": "system", "content": "You are a helpful assistant."},
      {"role": "user", "content": "What is the capital of Saudi Arabia?"}
    ],
    "temperature": 0.7,
    "max_tokens": 1024
  }'

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://alapi.deep.sa/v1"
)

stream = client.chat.completions.create(
    model="llama-3.3-70b-versatile",
    messages=[
        {"role": "user", "content": "Write a short poem about coding"}
    ],
    stream=True
)

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

import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: 'YOUR_API_KEY',
  baseURL: 'https://alapi.deep.sa/v1'
});

async function main() {
  const stream = await client.chat.completions.create({
    model: 'llama-3.3-70b-versatile',
    messages: [{ role: 'user', content: 'Write a short poem about coding' }],
    stream: true,
  });

  for await (const chunk of stream) {
    const content = chunk.choices[0]?.delta?.content || '';
    process.stdout.write(content);
  }
}

main();

curl -X POST "https://alapi.deep.sa/v1/chat/completions" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -N \
  -d '{
    "model": "llama-3.3-70b-versatile",
    "messages": [{"role": "user", "content": "Write a short poem about coding"}],
    "stream": true
  }'

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://alapi.deep.sa/v1"
)

models = client.models.list()
for model in models.data:
    print(f"{model.id} ({model.type})")

curl "https://alapi.deep.sa/v1/models" \
  -H "Authorization: Bearer YOUR_API_KEY"

curl -s -X POST "https://alapi.deep.sa/v1/alGuardrail/detect" \
  -H "Authorization: Bearer $ALAPI_KEY" \
  -H "Content-Type: application/json" \
  -d '{"text": "جوالي 0551234567 وايميلي sara@example.sa", "mode": "redact"}'

import os, requests

r = requests.post(
    "https://alapi.deep.sa/v1/alGuardrail/detect",
    headers={"Authorization": f"Bearer {os.environ['ALAPI_KEY']}"},
    json={"text": "جوالي 0551234567 وايميلي sara@example.sa", "mode": "redact"},
)
r.raise_for_status()
print(r.json()["output"])

const r = await fetch("https://alapi.deep.sa/v1/alGuardrail/detect", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.ALAPI_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({ text: "جوالي 0551234567 وايميلي sara@example.sa", mode: "redact" }),
});
const { output } = await r.json();
console.log(output);

curl "https://alapi.deep.sa/v1/ocr/jobs/YOUR_TOKEN_HERE" \
  -H "Authorization: Bearer YOUR_API_KEY"

import requests

API_BASE = "https://alapi.deep.sa/v1"
API_KEY = "YOUR_API_KEY"
token = "YOUR_TOKEN_HERE"

response = requests.get(
    f"{API_BASE}/ocr/jobs/{token}",
    headers={"Authorization": f"Bearer {API_KEY}"},
)
job = response.json()

print(job["status"], job.get("progress", 0))
if job["status"] == "done":
    for page in job["pages"]:
        print(page["text"])

import requests

API_BASE = "https://alapi.deep.sa/v1"
API_KEY = "YOUR_API_KEY"
headers = {"Authorization": f"Bearer {API_KEY}"}

token = "YOUR_TOKEN_HERE"
page_num = 3

response = requests.get(
    f"{API_BASE}/ocr/jobs/{token}/{page_num}",
    headers=headers
)

page = response.json()
print(f"Page {page['page_num']}: {page['status']}")
print(page["text"])

curl "https://alapi.deep.sa/v1/ocr/jobs/YOUR_TOKEN_HERE/3" \
  -H "Authorization: Bearer YOUR_API_KEY"

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://alapi.deep.sa/v1"
)

response = client.embeddings.create(
    model="deep-sa/alEmbedding",
    input="The quick brown fox jumps over the lazy dog"
)

embedding = response.data[0].embedding
print(f"Embedding dimension: {len(embedding)}")

import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: 'YOUR_API_KEY',
  baseURL: 'https://alapi.deep.sa/v1'
});

async function main() {
  const response = await client.embeddings.create({
    model: 'deep-sa/alEmbedding',
    input: 'The quick brown fox jumps over the lazy dog'
  });

  const embedding = response.data[0].embedding;
  console.log(`Embedding dimension: ${embedding.length}`);
}

main();

curl -X POST "https://alapi.deep.sa/v1/embeddings" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "deep-sa/alEmbedding",
    "input": "The quick brown fox jumps over the lazy dog"
  }'