修改下拉框，并增加新的映射

prompter.py

@@ -737,17 +737,79 @@ class RN_LLMAPI_Pro_Node():
     def __init__(self):
         pass
 
+    def _load_config_json(self):
+        try:
+            cfg_path = os.path.join(os.path.dirname(__file__), "config", "ComfyUI_rn_translator-config.json")
+            with open(cfg_path, "r", encoding="utf-8") as f:
+                return json.load(f)
+        except Exception:
+            return {}
+
+    def _get_model_config(self, display_name):
+        cfg = self._load_config_json()
+        vllm = cfg.get("vllm") or {}
+        llm = cfg.get("llm") or {}
+        v_models = vllm.get("models") or {}
+        l_models = llm.get("models") or {}
+        model_cfg = v_models.get(display_name) or l_models.get(display_name)
+        if isinstance(model_cfg, dict):
+            return {
+                "api_key": model_cfg.get("api_key") or "",
+                "model": model_cfg.get("model") or "",
+                "base_url": model_cfg.get("base_url") or "",
+                "temperature": model_cfg.get("temperature"),
+                "max_tokens": model_cfg.get("max_tokens"),
+                "top_p": model_cfg.get("top_p"),
+            }
+        return None
+
+    def _fallback_model_name(self, display_name):
+        mapping = {
+            "Qwen2.5-32B-Instruct": "Qwen/Qwen2.5-32B-Instruct",
+            "Qwen2.5-72B-Instruct": "Qwen/Qwen2.5-72B-Instruct",
+            "Qwen2.5-VL-32B-Instruct": "Qwen/Qwen2.5-VL-32B-Instruct",
+            "Qwen2.5-Omni-7B": "Qwen/Qwen2.5-Omni-7B",
+            "Qwen3-32B": "Qwen/Qwen3-32B",
+            "Qwen3-Embedding-8B": "Qwen/Qwen3-Embedding-8B",
+            "Qwen3-Reranker-8B": "Qwen/Qwen3-Reranker-8B",
+            "Qwen3-Coder-480B-A35B-Instruct": "Qwen/Qwen3-Coder-480B-A35B-Instruct",
+            "DeepSeek-R1-Distill-Qwen-32B": "deepseek-ai/DeepSeek-R1-Distill-Qwen-32B",
+            "DeepSeek-R1-0528": "deepseek-ai/DeepSeek-R1-0528",
+            "DeepSeek-V3-0324": "deepseek-ai/DeepSeek-V3-0324",
+            "glm-4-9b-chat": "THUDM/glm-4-9b-chat",
+            "GLM-4-32B-0414": "THUDM/GLM-4-32B-0414",
+            "GLM-4.1V-9B-Thinking": "THUDM/GLM-4.1V-9B-Thinking",
+            "GLM-4.6": "THUDM/GLM-4.6",
+            "bge-m3": "BAAI/bge-m3",
+            "bge-reranker-v2-m3": "BAAI/bge-reranker-v2-m3",
+        }
+        if not display_name:
+            return ""
+        if "/" in display_name:
+            return display_name
+        return mapping.get(display_name, display_name)
     @classmethod
     def INPUT_TYPES(cls):
         return {
             "required": {
-                "model": (["default",
-                "doubao-seed-1-6-251015", 
-                "DeepSeek-V3",
-                "Qwen3-235B-A22B-Instruct-2507", 
-                "gemini-2.5-flash", 
-                "gpt-5",
-                "gemini-3-pro-preview"], {"default": "default"}),
+                "model": (["Qwen2.5-32B-Instruct",
+                "Qwen2.5-72B-Instruct", 
+                "Qwen2.5-VL-32B-Instruct",
+                "Qwen2.5-Omni-7B", 
+                "Qwen3-32B",
+                "Qwen3-Embedding-8B", 
+                "Qwen3-Reranker-8B",
+                "Qwen3-Coder-480B-A35B-Instruct",
+                "DeepSeek-R1-Distill-Qwen-32B",
+                "DeepSeek-R1-0528",
+                "DeepSeek-V3-0324",
+                "glm-4-9b-chat",
+                "GLM-4-32B-0414",
+                "GLM-4.1V-9B-Thinking",
+                "GLM-4.6",
+                "bge-m3",
+                "bge-reranker-v2-m3",
+                ], {"default": "Qwen2.5-VL-32B-Instruct"}),
                 "role": ("STRING", {"multiline": True, "default": "You are a helpful assistant"}),
                 "prompt": ("STRING", {"multiline": True, "default": "Hello"}),
                 "temperature": ("FLOAT", {"default": 0.6}),
@@ -765,14 +827,11 @@ class RN_LLMAPI_Pro_Node():
 
     def rn_run_llmapi_pro(self, model, role, prompt, temperature, seed, api_baseurl='', api_key='', ref_image=None):
         cfg = get_config()
-        vllm_cfg = get_vllm_config()
-        if model == "default":
-            model = ""
-        has_visual = (ref_image is not None)
-        selected_cfg = vllm_cfg if has_visual else cfg
-        used_api_baseurl = (api_baseurl or selected_cfg.get("base_url"))
-        used_api_key = (api_key or selected_cfg.get("api_key") or "")
-        used_model = (model or selected_cfg.get("model") or ("qwen25-vl-32b-instruct" if has_visual else "gpt-4o-mini"))
+        model_cfg = self._get_model_config(model) if hasattr(self, "_get_model_config") else None
+        used_api_baseurl = api_baseurl or (model_cfg or {}).get("base_url") or cfg.get("base_url")
+        used_api_key = api_key or (model_cfg or {}).get("api_key") or cfg.get("api_key") or ""
+        base_model = (model_cfg or {}).get("model") or (self._fallback_model_name(model) if hasattr(self, "_fallback_model_name") else model) or model
+        used_model = base_model
         client = OpenAI(api_key=used_api_key, base_url=used_api_baseurl)
         if ref_image is None:
             messages = [
@@ -797,9 +856,12 @@ class RN_LLMAPI_Pro_Node():
                         },
                     ]},
             ]
-        completion = client.chat.completions.create(model=used_model, messages=messages, temperature=temperature)
-        if completion is not None and hasattr(completion, 'choices'):
-            prompt = completion.choices[0].message.content
-        else:
-            prompt = 'Error'
-        return (prompt,)
+        try:
+            completion = client.chat.completions.create(model=used_model, messages=messages, temperature=temperature)
+            if completion is not None and hasattr(completion, 'choices'):
+                result = completion.choices[0].message.content
+            else:
+                result = 'Error: No response from API'
+        except Exception as e:
+            result = f"API调用出错: {str(e)}"
+        return (result,)