Update app.py

app.py

@@ -72,29 +72,6 @@ request_timestamps_day = []
 token_counts_day = []
 data_lock = threading.Lock()
 
-def get_credit_summary(api_key):
-    headers = {
-        "Authorization": f"Bearer {api_key}",
-        "Content-Type": "application/json"
-    }
-    max_retries = 3
-
-    for attempt in range(max_retries):
-        try:
-            response = session.get(API_ENDPOINT, headers=headers, timeout=2)
-            response.raise_for_status()
-            data = response.json().get("data", {})
-            total_balance = data.get("totalBalance", 0)
-            logging.info(f"获取额度，API Key：{api_key}，当前额度: {total_balance}")
-            return {"total_balance": float(total_balance)}
-        except requests.exceptions.Timeout as e:
-            logging.error(f"获取额度信息失败，API Key：{api_key}，尝试次数：{attempt+1}/{max_retries}，错误信息：{e} (Timeout)")
-            if attempt >= max_retries - 1:
-                logging.error(f"获取额度信息失败，API Key：{api_key}，所有重试次数均已失败 (Timeout)")
-        except requests.exceptions.RequestException as e:
-            logging.error(f"获取额度信息失败，API Key：{api_key}，错误信息：{e}")
-            return None
-
 def extract_user_content(messages):
     user_content = ""
     for message in messages:
@@ -107,57 +84,10 @@ def extract_user_content(messages):
                         user_content += item.get("text", "") + " "
     return user_content.strip()
 
-def get_siliconflow_data(model_name, data):
-    siliconflow_data = {
-        "model": model_name,
-        "prompt": data.get("prompt") or "",
-    }
-    
-    if model_name == "black-forest-labs/FLUX.1-pro":
-        siliconflow_data.update({
-            "width": max(256, min(1440, (data.get("width", 1024) // 32) * 32)),
-            "height": max(256, min(1440, (data.get("height", 768) // 32) * 32)),
-            "prompt_upsampling": data.get("prompt_upsampling", False),
-            "image_prompt": data.get("image_prompt"),
-            "steps": max(1, min(50, data.get("steps", 20))),
-            "guidance": max(1.5, min(5, data.get("guidance", 3))),
-            "safety_tolerance": max(0, min(6, data.get("safety_tolerance", 2))),
-            "interval": max(1, min(4, data.get("interval", 2))),
-            "output_format": data.get("output_format", "png")
-        })
-        
-        seed = data.get("seed")
-        if isinstance(seed, int) and 0 < seed < 9999999999:
-            siliconflow_data["seed"] = seed
-            
-    else:
-        siliconflow_data.update({
-            "image_size": data.get("image_size", "1024x1024"),
-            "prompt_enhancement": data.get("prompt_enhancement", False)
-        })
-        
-        seed = data.get("seed")
-        if isinstance(seed, int) and 0 < seed < 9999999999:
-            siliconflow_data["seed"] = seed
-            
-        if model_name not in ["black-forest-labs/FLUX.1-schnell", "Pro/black-forest-labs/FLUX.1-schnell"]:
-            siliconflow_data.update({
-                "batch_size": max(1, min(4, data.get("n", 1))),
-                "num_inference_steps": max(1, min(50, data.get("steps", 20))),
-                "guidance_scale": max(0, min(100, data.get("guidance_scale", 7.5))),
-                "negative_prompt": data.get("negative_prompt")
-            })
-    
-    valid_sizes = ["1024x1024", "512x1024", "768x512", "768x1024", "1024x576", "576x1024", "960x1280", "720x1440", "720x1280"]
-    if "image_size" in siliconflow_data and siliconflow_data["image_size"] not in valid_sizes:
-        siliconflow_data["image_size"] = "1024x1024"
-        
-    return siliconflow_data
-
 def refresh_models():
     global models
     
-    models["text"] = get_all_models(key_status["valid"][0])
+    models["text"] = get_all_models(keys_str[0])
 
     for model_type in ["text"]:
         logging.info(f"所有{model_type}模型列表：{models[model_type]}")