المطوّرون: خمس دقائق إلى أول رمز

# Any OpenAI-compatible SDK works. Two values change.
export IAALGERIE_API_KEY="iaa_live_xxxxxxxxxxxxxxxxxxxx"
export OPENAI_BASE_URL="https://api.iaalgerie.com/v1"

# default model
export DEFAULT_MODEL="qwen3.7-plus"

# pip install openai
import os
from openai import OpenAI

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

response = client.chat.completions.create(
    model="qwen3.7-plus",
    messages=[
        {"role": "system", "content": "Reponds toujours en francais."},
        {"role": "user", "content": "Resume ce contrat en 5 points."},
    ],
    temperature=0.3,
)

print(response.choices[0].message.content)
print("tokens:", response.usage.total_tokens)

// npm install openai
import OpenAI from "openai";

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

const response = await client.chat.completions.create({
  model: "qwen3.7-plus",
  messages: [
    { role: "system", content: "Reponds toujours en francais." },
    { role: "user", content: "Resume ce contrat en 5 points." },
  ],
});

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

curl https://api.iaalgerie.com/v1/chat/completions \
  -H "Authorization: Bearer $IAALGERIE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen3.7-plus",
    "messages": [
      {"role": "system", "content": "Reponds toujours en francais."},
      {"role": "user", "content": "Resume ce contrat en 5 points."}
    ],
    "temperature": 0.3
  }'

OpenAI-compatible  https://api.iaalgerie.com/v1
Anthropic format   https://api.iaalgerie.com/anthropic
Native DashScope   https://api.iaalgerie.com/api/v1

One URL for every model. Our gateway selects the upstream region
for you (Singapore, US Virginia or Beijing) — nothing to configure
on your side.

Authorization: Bearer iaa_live_xxxxxxxxxxxxxxxxxxxx
Content-Type: application/json

curl https://api.iaalgerie.com/v1/chat/completions \
  -H "Authorization: Bearer $IAALGERIE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen3.7-plus",
    "messages": [
      {"role": "system", "content": "Reponds toujours en francais."},
      {"role": "user", "content": "Resume ce contrat en 5 points."}
    ],
    "temperature": 0.3
  }'

stream = client.chat.completions.create(
    model="qwen3.7-plus",
    messages=[{"role": "user", "content": "Ecris un devis pour 3 sites web."}],
    stream=True,
)

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

tools = [{
    "type": "function",
    "function": {
        "name": "get_order_status",
        "description": "Retourne le statut d'une commande algerienne.",
        "parameters": {
            "type": "object",
            "properties": {
                "order_id": {"type": "string"},
                "wilaya": {"type": "string"}
            },
            "required": ["order_id"]
        }
    }
}]

messages = [{"role": "user", "content": "Ou est ma commande CMD-4821 ?"}]

while True:
    reply = client.chat.completions.create(
        model="qwen3.7-plus", messages=messages, tools=tools
    ).choices[0].message

    if not reply.tool_calls:
        print(reply.content)
        break

    messages.append(reply)
    for call in reply.tool_calls:
        args = json.loads(call.function.arguments)
        messages.append({
            "role": "tool",
            "tool_call_id": call.id,
            "content": json.dumps({"status": "en livraison", "wilaya": "Bejaia"}),
        })

from pydantic import BaseModel

class Invoice(BaseModel):
    supplier: str
    nif: str | None
    total_da: float
    currency: str
    due_date: str | None

raw = "FACTURE SARL Exemple, NIF 0998...1620, total 145 000,00 DA, echeance 30/11/2026"

parsed = client.beta.chat.completions.parse(
    model="qwen3.8-flash",
    messages=[
        {"role": "system", "content": "Extract the invoice fields."},
        {"role": "user", "content": raw},
    ],
    response_format=Invoice,
)

invoice = parsed.choices[0].message.parsed
print(invoice.total_da, invoice.currency)   # 145000.0 DA

# Images — synchronous, billed per image
curl -X POST https://api.iaalgerie.com/v1/images/generations \
  -H "Authorization: Bearer $IAALGERIE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "qwen-image-3.0-pro",
       "prompt": "Photo produit d une bouteille d huile d olive",
       "size": "1024x1024", "n": 2}'

# Video — asynchronous: submit, then poll the task
curl -X POST https://api.iaalgerie.com/v1/services/aigc/video-generation/video-synthesis \
  -H "Authorization: Bearer $IAALGERIE_API_KEY" \
  -H "X-DashScope-Async: enable" \
  -H "Content-Type: application/json" \
  -d '{"model": "wan3.0-video",
       "input": {"prompt": "Tramway d Alger au coucher du soleil"},
       "parameters": {"duration": 5, "size": "1280*720"}}'

# -> {"output": {"task_id": "..."}}  then:
curl https://api.iaalgerie.com/v1/tasks/<task_id> \
  -H "Authorization: Bearer $IAALGERIE_API_KEY"

# Speech to text
curl -X POST https://api.iaalgerie.com/v1/audio/transcriptions \
  -H "Authorization: Bearer $IAALGERIE_API_KEY" \
  -F model="qwen-audio-3.1-asr-flash-filetrans" \
  -F file="@reunion.m4a"

# Embeddings: turn your knowledge base into vectors
emb = client.embeddings.create(
    model="text-embedding-v4",
    input=["Politique de retour sous 7 jours", "Frais de livraison Yalidine"],
)
vectors = [d.embedding for d in emb.data]

# Rerank: best candidates first, before the chat call
import dashscope   # pip install dashscope

ranked = dashscope.TextReRank.call(
    model="qwen3-rerank",
    query="Quel est le delai de retour ?",
    documents=["Politique de retour sous 7 jours",
               "Nos horaires d ouverture",
               "Frais de livraison Yalidine"],
    top_n=2,
    return_documents=True,
    api_key=os.environ["IAALGERIE_API_KEY"],
)
print(ranked.output.results[0].document.text)

import time
from openai import APIStatusError

def ask(messages, model="qwen3.7-plus"):
    for attempt in range(5):
        try:
            r = client.chat.completions.create(model=model, messages=messages)
            print("request_id:", r._request_id, "tokens:", r.usage.total_tokens)
            return r
        except APIStatusError as e:
            if e.status_code == 429:      # rate limit
                time.sleep(2 ** attempt)
                continue
            if e.status_code == 402:      # insufficient balance
                raise SystemExit("Top up your IA Algerie balance.")
            if e.status_code >= 500:      # upstream hiccup
                time.sleep(1)
                continue
            raise
    raise RuntimeError("rate limited after 5 attempts")