Update app.py

app.py

@@ -7,26 +7,25 @@ app = Flask(__name__)
 HF_TOKEN = os.getenv("HF_TOKEN")
 API_URL = "https://router.huggingface.co/v1/chat/completions"
 
-# SENİN LİSTENDEN SEÇİLEN, 402 VERMEYEN EN GÜÇLÜ 50 MODEL
+# HATASIZ VE REYTİNG ODAKLI 50 MODEL
 MODELLER = [
     "meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8", "deepcogito/cogito-671b-v2.1-FP8",
-    "deepseek-ai/DeepSeek-R1", "Qwen/Qwen3.5-397B-A17B", "Qwen/Qwen3-Coder-480B-A35B-Instruct-FP8",
-    "deepseek-ai/DeepSeek-V3.2-Exp", "zai-org/GLM-5", "baidu/ERNIE-4.5-300B-A47B-Base-PT",
-    "openai/gpt-oss-120b", "google/gemma-3-27b-it", "meta-llama/Llama-3.3-70B-Instruct",
-    "Qwen/Qwen3-235B-A22B-Thinking-2507", "CohereLabs/c4ai-command-a-03-2025", "moonshotai/Kimi-K2.5",
-    "meta-llama/Llama-4-Scout-17B-16E-Instruct", "deepseek-ai/DeepSeek-V3", "Qwen/QwQ-32B",
-    "google/gemma-3n-E4B-it", "ServiceNow-AI/Apriel-1.6-15b-Thinker", "EssentialAI/rnj-1-instruct",
-    "alpindale/WizardLM-2-8x22B", "mistralai/Mistral-Small-2409", "meta-llama/Llama-3.1-70B-Instruct",
-    "Qwen/Qwen2.5-72B-Instruct", "zai-org/GLM-4.7-Flash", "CohereLabs/aya-expanse-32b",
-    "Sao10K/L3-70B-Euryale-v2.1", "allenai/Olmo-3.1-32B-Think", "deepcogito/cogito-671b-v2.1",
-    "Qwen/Qwen3-Next-80B-A3B-Thinking", "meta-llama/Meta-Llama-3-70B-Instruct",
-    "tokyotech-llm/Llama-3.3-Swallow-70B-Instruct-v0.4", "utter-project/EuroLLM-22B-Instruct-2512",
-    "zai-org/GLM-4.6V", "Qwen/Qwen3-VL-235B-A22B-Thinking", "moonshotai/Kimi-K2-Thinking",
-    "deepseek-ai/DeepSeek-V3.1-Terminus", "allenai/Olmo-3.1-32B-Instruct", "aisingapore/Qwen-SEA-LION-v4-32B-IT",
-    "NousResearch/Hermes-2-Pro-Llama-3-8B", "Qwen/Qwen2.5-Coder-32B-Instruct", "baidu/ERNIE-4.5-VL-424B-A47B-Base-PT",
-    "Sao10K/L3-8B-Stheno-v3.2", "nvidia/NVIDIA-Nemotron-Nano-9B-v2", "arcee-ai/Trinity-Mini",
-    "swiss-ai/Apertus-70B-Instruct-2509", "Qwen/Qwen3-8B", "meta-llama/Llama-3.1-8B-Instruct",
-    "mistralai/Mistral-7B-Instruct-v0.2", "microsoft/Phi-3-mini-4k-instruct"
+    "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
@@ -39,44 +38,39 @@ def handle_request():
     
     try:
         data = request.get_json()
-        istatistikler = data.get("istatistikler", "Veri yok")
+        istatistikler = data.get("istatistikler", "")
         
         headers = {"Authorization": f"Bearer {HF_TOKEN}"}
         payload = {
             "model": secilen_model,
             "messages": [
-                {"role": "system", "content": "Sen bir robotsun. Görevin: İstatistiklere bakıp 4.0 ile 10.0 arasında puan vermek. SADECE 'İsim: Puan' formatında yaz. Yorum yapma, açıklama yapma, cümle kurma."},
-                {"role": "user", "content": f"Reyting ver (4.0-10.0):\n{istatistikler}"}
+                {"role": "system", "content": "Sen SADECE istatistiklere göre 4,0-10,0 arası puan veren bir robotsun. Yorum yasak. Sadece 'İsim: Puan' yaz."},
+                {"role": "user", "content": istatistikler}
             ],
-            "max_tokens": 150,
+            "max_tokens": 100,
             "temperature": 0.0
         }
         
-        response = requests.post(API_URL, headers=headers, json=payload, timeout=50)
-        
-        # Limit sorguları
-        kalan = response.headers.get("x-ratelimit-remaining-requests", "Gizli")
-        toplam = response.headers.get("x-ratelimit-limit-requests", "Gizli")
+        response = requests.post(API_URL, headers=headers, json=payload, timeout=30)
         
         if response.status_code == 200:
-            cevap = response.json()['choices'][0]['message']['content']
+            json_data = response.json()
+            cevap = json_data['choices'][0]['message']['content']
             
-            # Gevezelik temizliği (Think ve İngilizce girişler)
-            if "</think>" in cevap:
-                cevap = cevap.split("</think>")[-1]
-            cevap = re.sub(r'(?i)(okay|let|here|rating|score|analysis).*', '', cevap).strip()
+            # Gevezelik temizliği
+            if "</think>" in cevap: cevap = cevap.split("</think>")[-1]
+            cevap = re.sub(r'(?i)(okay|let|here|rating|score|analysis|sure).*', '', cevap).strip()
             
             return jsonify({
                 "model": secilen_model,
                 "puanlar": cevap.replace(".", ","),
-                "kalan_hak": kalan,
-                "toplam_limit": toplam
+                "index": model_sayaci # Godot'ya kaçıncıda olduğunu söyler
             })
-        else:
-            return jsonify({"error": f"Hata: {response.status_code}", "hatali_model": secilen_model}), response.status_code
+        
+        return jsonify({"error": "Hata", "hatali_model": secilen_model}), response.status_code
             
     except Exception as e:
-        return jsonify({"error": str(e), "hatali_model": secilen_model}), 500
+        return jsonify({"error": str(e)}), 500
 
 if __name__ == "__main__":
     app.run(host="0.0.0.0", port=7860)