app.py

from flask import Flask, request, jsonify
import requests
import os
import re

app = Flask(__name__)

# Hugging Face Ayarları
HF_TOKEN = os.getenv("HF_TOKEN")
API_URL = "https://router.huggingface.co/v1/chat/completions"

# ÇALIŞAN ELİT 50 MODEL
MODELLER = [
    "meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8", "deepcogito/cogito-671b-v2.1-FP8",
    "deepseek-ai/DeepSeek-V3.2-Exp", "Qwen/Qwen3.5-397B-A17B", "Qwen/Qwen3-Coder-480B-A35B-Instruct-FP8",
    "meta-llama/Llama-3.3-70B-Instruct", "deepseek-ai/DeepSeek-R1", "google/gemma-3-27b-it",
    "openai/gpt-oss-120b", "Qwen/QwQ-32B", "meta-llama/Llama-4-Scout-17B-16E-Instruct",
    "baidu/ERNIE-4.5-300B-A47B-Base-PT", "moonshotai/Kimi-K2.5", "deepseek-ai/DeepSeek-V3",
    "mistralai/Mistral-Small-2409", "Qwen/Qwen2.5-72B-Instruct", "meta-llama/Llama-3.1-70B-Instruct",
    "CohereLabs/c4ai-command-a-03-2025", "meta-llama/Llama-3.2-3B-Instruct", "google/gemma-3n-E4B-it",
    "Qwen/Qwen3-235B-A22B-Thinking-2507", "CohereLabs/aya-expanse-32b", "meta-llama/Meta-Llama-3-70B-Instruct",
    "allenai/Olmo-3.1-32B-Instruct", "Qwen/Qwen2.5-Coder-32B-Instruct", "mistralai/Mistral-7B-Instruct-v0.2",
    "meta-llama/Llama-3.1-8B-Instruct", "nvidia/NVIDIA-Nemotron-Nano-9B-v2", "Qwen/Qwen3-8B",
    "allenai/Olmo-3.1-32B-Think", "CohereLabs/c4ai-command-r-08-2024", "meta-llama/Llama-3.2-1B-Instruct",
    "Qwen/Qwen3-32B", "google/gemma-2-9b-it", "mistralai/Mistral-Nemo-Instruct-2407",
    "microsoft/Phi-3.5-mini-instruct", "meta-llama/Llama-Guard-3-8B", "Qwen/Qwen2.5-7B-Instruct",
    "allenai/Olmo-3-7B-Instruct", "CohereLabs/c4ai-command-r7b-12-2024", "Qwen/Qwen3-14B",
    "google/gemma-2-2b-it", "meta-llama/Llama-3-8B-Instruct", "Qwen/Qwen2.5-Coder-7B-Instruct",
    "mistralai/Pixtral-12B-2409", "Qwen/Qwen3-Next-80B-A3B-Instruct", "google/gemma-3-4b-it",
    "meta-llama/Llama-3.1-405B-Instruct-FP8", "deepseek-ai/DeepSeek-V2.5", "Qwen/Qwen2.5-1.5B-Instruct"
]

model_sayaci = 0

@app.route("/", methods=["POST"])
def handle_request():
    global model_sayaci
    secilen_model = MODELLER[model_sayaci % len(MODELLER)]
    model_sayaci += 1
    
    try:
        data = request.get_json()
        istatistikler = data.get("istatistikler", "")
        
        headers = {"Authorization": f"Bearer {HF_TOKEN}"}
        payload = {
            "model": secilen_model,
            "messages": [
                {"role": "system", "content": "SADECE 'İsim: Puan' formatında cevap ver. 4.0-10.0 arası."},
                {"role": "user", "content": istatistikler}
            ],
            "max_tokens": 80,
            "temperature": 0.0
        }
        
        response = requests.post(API_URL, headers=headers, json=payload, timeout=25)
        
        if response.status_code == 200:
            cevap = response.json()['choices'][0]['message']['content']
            if "</think>" in cevap: cevap = cevap.split("</think>")[-1]
            cevap = re.sub(r'(?i)(okay|let|here|rating|score|analysis|sure|certainly).*', '', cevap).strip()
            
            return jsonify({
                "model": secilen_model,
                "puanlar": cevap.replace(".", ","),
                "sayac": model_sayaci
            })
        
        return jsonify({"error": f"Model Hatası: {response.status_code}"}), response.status_code
            
    except Exception as e:
        return jsonify({"error": str(e)}), 500

if __name__ == "__main__":
    # HF için PORT 7860 şarttır!
    app.run(host="0.0.0.0", port=7860)