گفت‌وگو (Chat Completions)

curl https://gisoo.pro/api/v1/chat/completions \
  -H "Authorization: Bearer $GISOO_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-4o-mini",
    "messages": [
      {"role": "system", "content": "You are a support agent for an online bookshop. Reply in Persian, briefly and politely."},
      {"role": "user", "content": "Can I return a book I bought last week?"}
    ],
    "temperature": 0.4,
    "max_tokens": 300
  }'

import os
from openai import OpenAI

client = OpenAI(base_url="https://gisoo.pro/api/v1", api_key=os.environ["GISOO_API_KEY"])

reply = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[
        {"role": "system", "content": "You are a support agent for an online bookshop. Reply in Persian, briefly and politely."},
        {"role": "user", "content": "Can I return a book I bought last week?"},
    ],
    temperature=0.4,
    max_tokens=300,
)

choice = reply.choices[0]
print(choice.message.content)
print(choice.finish_reason, reply.usage.total_tokens)

import OpenAI from "openai";

const client = new OpenAI({ baseURL: "https://gisoo.pro/api/v1", apiKey: process.env.GISOO_API_KEY });

const reply = await client.chat.completions.create({
  model: "gpt-4o-mini",
  messages: [
    { role: "system", content: "You are a support agent for an online bookshop. Reply in Persian, briefly and politely." },
    { role: "user", content: "Can I return a book I bought last week?" },
  ],
  temperature: 0.4,
  max_tokens: 300,
});

console.log(reply.choices[0].message.content);
console.log(reply.choices[0].finish_reason, reply.usage.total_tokens);

<?php
$client = OpenAI::factory()
    ->withBaseUri('https://gisoo.pro/api/v1')
    ->withApiKey(getenv('GISOO_API_KEY'))
    ->make();

$reply = $client->chat()->create([
    'model' => 'gpt-4o-mini',
    'messages' => [
        ['role' => 'system', 'content' => 'You are a support agent for an online bookshop. Reply in Persian, briefly and politely.'],
        ['role' => 'user', 'content' => 'Can I return a book I bought last week?'],
    ],
    'temperature' => 0.4,
    'max_tokens' => 300,
]);

echo $reply->choices[0]->message->content;

reply, err := client.Chat.Completions.New(context.TODO(), openai.ChatCompletionNewParams{
    Model: "gpt-4o-mini",
    Messages: []openai.ChatCompletionMessageParamUnion{
        openai.SystemMessage("You are a support agent for an online bookshop. Reply in Persian, briefly and politely."),
        openai.UserMessage("Can I return a book I bought last week?"),
    },
    Temperature: openai.Float(0.4),
    MaxTokens:   openai.Int(300),
})
if err != nil {
    panic(err)
}
fmt.Println(reply.Choices[0].Message.Content)

ChatClient client = new(
    model: "gpt-4o-mini",
    credential: new ApiKeyCredential(Environment.GetEnvironmentVariable("GISOO_API_KEY")!),
    options: new OpenAIClientOptions { Endpoint = new Uri("https://gisoo.pro/api/v1") });

ChatCompletion reply = client.CompleteChat(
    [
        new SystemChatMessage("You are a support agent for an online bookshop. Reply in Persian, briefly and politely."),
        new UserChatMessage("Can I return a book I bought last week?"),
    ],
    new ChatCompletionOptions { Temperature = 0.4f, MaxOutputTokenCount = 300 });

Console.WriteLine(reply.Content[0].Text);

history = [{"role": "system", "content": "You are a friendly Persian tutor for English learners."}]

def ask(text: str) -> str:
    history.append({"role": "user", "content": text})
    reply = client.chat.completions.create(model="gpt-4o-mini", messages=history, max_tokens=400)
    answer = reply.choices[0].message.content
    history.append({"role": "assistant", "content": answer})  # the model only remembers what you send back
    return answer

print(ask("What does 'take off' mean?"))
print(ask("Give me two example sentences with it."))

{
  "id": "req_7d2e19c0a4b6f8e1d3c5a7b9",
  "object": "chat.completion",
  "created": 1790000000,
  "model": "gpt-4o-mini",
  "choices": [
    {
      "index": 0,
      "message": { "role": "assistant", "content": "…" },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 48,
    "completion_tokens": 72,
    "total_tokens": 120,
    "prompt_tokens_details": { "cached_tokens": 0 },
    "completion_tokens_details": { "reasoning_tokens": 0 }
  }
}

reply = client.chat.completions.create(
    model="gpt-5-mini",
    reasoning_effort="low",          # minimal | low | medium | high
    max_completion_tokens=2000,      # thinking tokens count towards this too
    messages=[{"role": "user", "content": "A train leaves at 14:35 and arrives at 19:10. How long is the trip?"}],
)
print(reply.choices[0].message.content)
print(reply.usage.completion_tokens_details)  # reasoning_tokens is inside