Update app.py

app.py

@@ -583,19 +583,49 @@ def handsome_chat_completions():
     
     if model_name in image_models:
         # Handle image generation
+        user_content = ""
+        messages = data.get("messages", [])
+        for message in messages:
+            if message["role"] == "user":
+                if isinstance(message["content"], str):
+                    user_content += message["content"] + " "
+                elif isinstance(message["content"], list):
+                    for item in message["content"]:
+                        if (
+                            isinstance(item, dict) and
+                            item.get("type") == "text"
+                        ):
+                            user_content += (
+                                item.get("text", "") +
+                                " "
+                            )
+        user_content = user_content.strip()
+
         # Map OpenAI-style parameters to SiliconFlow's parameters
         siliconflow_data = {
             "model": model_name,
-            "prompt": data.get("messages", [{}])[0].get("content") if isinstance(data.get("messages"), list) else "",
-            "image_size": data.get("size", "1024x1024"),
-            "batch_size": data.get("n", 1),
-            "num_inference_steps": data.get("steps", 20),
-            "guidance_scale": data.get("guidance_scale", 7.5),
-            "negative_prompt": data.get("negative_prompt"),
-            "seed": data.get("seed"),
-            "prompt_enhancement": False,
+            "prompt": user_content,
+            "image_size": "1024x1024", # Default value
+            "batch_size": 1, # Default value
+            "num_inference_steps": 20, # Default value
+            "guidance_scale": 7.5, # Default value
+            "prompt_enhancement": False, # Default value
         }
-        
+
+        # Override with user's params (if provided)
+        if data.get("size"):
+            siliconflow_data["image_size"] = data.get("size")
+        if data.get("n"):
+            siliconflow_data["batch_size"] = data.get("n")
+        if data.get("steps"):
+            siliconflow_data["num_inference_steps"] = data.get("steps")
+        if data.get("guidance_scale"):
+           siliconflow_data["guidance_scale"] = data.get("guidance_scale")
+        if data.get("negative_prompt"):
+           siliconflow_data["negative_prompt"] = data.get("negative_prompt")
+        if data.get("seed"):
+           siliconflow_data["seed"] = data.get("seed")
+
         # Parameter validation and adjustments
         if siliconflow_data["batch_size"] < 1:
             siliconflow_data["batch_size"] = 1