curl -X POST https://ai.bakeli.tech/v1/chat \
  -H "Authorization: Bearer <ta-cle-api>" \
  -H "Content-Type: application/json" \
  -d '{"model":"llama3.2","messages":[{"role":"user","content":"Bonjour !"}]}'

{ "model": "llama3.2", "message": { "role": "assistant", "content": "Bonjour !" }, "done": true }

Authorization: Bearer <API_KEY>

{ "error": "Unauthorized" }

BAKELI_AI_URL=https://ai.bakeli.tech
BAKELI_AI_KEY=ta-cle-api-secrete

{
  "model":   "llama3.2",
  "message": { "role": "assistant", "content": "Docker est..." },
  "done": true
}

curl https://ai.bakeli.tech/v1/models -H "Authorization: Bearer <API_KEY>"

{ "models": [{ "name": "llama3.2:latest", "size": 2019383552 }, ...] }

curl https://ai.bakeli.tech/v1/health

{ "RedTeam": "ok", "ollama": "ok" }

{ "RedTeam": "ok", "ollama": "unreachable" }

BAKELI_AI_URL=https://ai.bakeli.tech
BAKELI_AI_KEY=ta-cle-api

BAKELI_AI_URL = env("BAKELI_AI_URL", default="https://ai.bakeli.tech")
BAKELI_AI_KEY = env("BAKELI_AI_KEY")

import requests
from django.conf import settings

def ask(messages: list, model: str = "llama3.2") -> str:
    """Envoie une conversation, retourne le texte de réponse."""
    resp = requests.post(
        f"{settings.BAKELI_AI_URL}/v1/chat",
        headers={"Authorization": f"Bearer {settings.BAKELI_AI_KEY}"},
        json={"model": model, "messages": messages},
        timeout=120,
    )
    resp.raise_for_status()
    return resp.json()["message"]["content"]

def ask_with_file(prompt: str, filepath: str, model: str = "llama3.2") -> str:
    """Envoie un fichier avec un prompt."""
    with open(filepath, "rb") as f:
        resp = requests.post(
            f"{settings.BAKELI_AI_URL}/v1/chat/file",
            headers={"Authorization": f"Bearer {settings.BAKELI_AI_KEY}"},
            data={"prompt": prompt, "model": model},
            files={"file": f},
            timeout=180,
        )
    return resp.json()["message"]["content"]

from utils.ai_client import ask

def assistant(request):
    historique = request.session.get("chat_history", [])
    historique.append({"role": "user", "content": request.POST.get("message")})
    reponse = ask(historique)
    historique.append({"role": "assistant", "content": reponse})
    request.session["chat_history"] = historique
    return JsonResponse({"reponse": reponse})

BAKELI_AI_URL=https://ai.bakeli.tech
BAKELI_AI_KEY=ta-cle-api

<?php
return [
    'url'     => env('BAKELI_AI_URL', 'https://ai.bakeli.tech'),
    'key'     => env('BAKELI_AI_KEY'),
    'model'   => env('BAKELI_AI_MODEL', 'llama3.2'),
    'timeout' => 120,
];

<?php
namespace App\Services;
use Illuminate\Support\Facades\Http;

class AiService
{
    private string $url, $key, $model;

    public function __construct() {
        $this->url   = config('ai.url');
        $this->key   = config('ai.key');
        $this->model = config('ai.model');
    }

    public function ask(array $messages, string $model = null): string
    {
        return Http::withToken($this->key)
            ->timeout(config('ai.timeout'))
            ->post($this->url . '/v1/chat', [
                'model'    => $model ?? $this->model,
                'messages' => $messages,
            ])->throw()->json('message.content');
    }

    public function askWithFile(string $prompt, string $path, string $model = null): string
    {
        return Http::withToken($this->key)
            ->timeout(180)
            ->attach('file', file_get_contents($path), basename($path))
            ->post($this->url . '/v1/chat/file', [
                'prompt' => $prompt,
                'model'  => $model ?? $this->model,
            ])->throw()->json('message.content');
    }
}

class AssistantController extends Controller
{
    public function __construct(private AiService $ai) {}

    public function chat(Request $request)
    {
        $history   = session('chat_history', []);
        $history[] = ['role' => 'user', 'content' => $request->input('message')];
        $reply     = $this->ai->ask($history);
        $history[] = ['role' => 'assistant', 'content' => $reply];
        session(['chat_history' => $history]);
        return response()->json(['reply' => $reply]);
    }
}

# Côté serveur uniquement (sans NEXT_PUBLIC_)
BAKELI_AI_URL=https://ai.bakeli.tech
BAKELI_AI_KEY=ta-cle-api

import { NextRequest, NextResponse } from 'next/server';

export async function POST(req: NextRequest) {
  const body = await req.json();
  const resp = await fetch(`${process.env.BAKELI_AI_URL}/v1/chat`, {
    method: 'POST',
    headers: {
      'Content-Type':  'application/json',
      'Authorization': `Bearer ${process.env.BAKELI_AI_KEY}`,
    },
    body: JSON.stringify(body),
  });
  return NextResponse.json(await resp.json());
}

import { useState, useCallback } from 'react';

type Message = { role: 'user' | 'assistant'; content: string };

export function useAI(model = 'llama3.2') {
  const [loading, setLoading]   = useState(false);
  const [messages, setMessages] = useState<Message[]>([]);

  const ask = useCallback(async (userMessage: string) => {
    const updated = [...messages, { role: 'user' as const, content: userMessage }];
    setMessages(updated);
    setLoading(true);
    try {
      const res  = await fetch('/api/ai', {
        method: 'POST',
        headers: { 'Content-Type': 'application/json' },
        body: JSON.stringify({ model, messages: updated }),
      });
      const data  = await res.json();
      const reply = data.message.content;
      setMessages(prev => [...prev, { role: 'assistant', content: reply }]);
      return reply;
    } finally { setLoading(false); }
  }, [messages, model]);

  return { ask, loading, messages, reset: () => setMessages([]) };
}

import { useState } from 'react';
import { useAI } from '@/hooks/useAI';

export default function ChatWidget() {
  const { ask, loading, messages } = useAI();
  const [input, setInput] = useState('');

  return (
    <div>
      {messages.map((m, i) => <div key={i}>{m.content}</div>)}
      <input value={input} onChange={e => setInput(e.target.value)} />
      <button onClick={() => { ask(input); setInput(''); }} disabled={loading}>
        {loading ? '...' : 'Envoyer'}
      </button>
    </div>
  );
}

import google.generativeai as genai
genai.configure(api_key="AIza...")
model = genai.GenerativeModel("gemini-pro")
text = model.generate_content("Explique Docker").text

from utils.ai_client import ask
text = ask([{"role": "user", "content": "Explique Docker"}])

curl https://ai.bakeli.tech/v1/health
docker logs -f ai-RedTeam
docker ps | grep -E "ollama|ai-RedTeam"