nodes/SF-Runnode-ComfyUI_rn_prompter
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修复config获取

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LuQiutian
2025-12-13 19:50:21 +08:00
parent 96b273afd6
commit bfcee65eae
1 changed files with 93 additions and 35 deletions
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prompter.py
+93 -35
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@@ -140,18 +140,17 @@ def get_model_config(model_name):
"""
try:
# 修改配置文件路径为新的配置文件
# config_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), "config",
# 'ComfyUI_rn_translator-config.json')
config_paths = [
os.path.join(os.path.dirname(os.path.realpath(__file__)), "config", 'ComfyUI_rn_translator-config.json'),
os.path.join(os.path.dirname(os.path.realpath(__file__)), "config", 'comfyui_rn_translator-config.json')
]
config_path = None
for path in config_paths:
if os.path.exists(path):
config_path = path
break
with open(config_path, 'r', encoding='utf-8') as f:
config = json.load(f)
@@ -172,30 +171,52 @@ def get_model_config(model_name):
"GLM-4-32B-0414": "ZhipuAI/GLM-4-32B-0414",
"GLM-4.1V-9B-Thinking": "ZhipuAI/GLM-4.1V-9B-Thinking",
"GLM-4.6": "ZhipuAI/GLM-4.6",
"bge-m3": "BAAI/bge-m3",
"bge-reranker-v2-m3": "BAAI/bge-reranker-v2-m3",
"bge-m3": "bge-m3",
"bge-reranker-v2-m3": "bge-reranker-v2-m3",
}
# 获取映射后的模型名称
mapped_name = mapping.get(model_name, model_name)
# 在vllm和llm的providers中查找匹配的配置
for section in ['vllm', 'llm']:
if section in config:
providers = config[section].get('providers', {})
for provider_name, provider_config in providers.items():
if provider_config.get('model') == mapped_name:
# 找到匹配的配置
return {
'api_key': provider_config.get('api_key', ''),
'model': provider_config.get('model', ''),
'base_url': provider_config.get('base_url', ''),
'temperature': provider_config.get('temperature', 0.7),
'max_tokens': provider_config.get('max_tokens', 1000),
'top_p': provider_config.get('top_p', 0.9)
}
# 直接在整个配置中查找匹配的model字段
def find_matching_config(config_dict, target_model):
"""递归查找匹配的配置"""
if isinstance(config_dict, dict):
# 检查当前字典是否有model字段且匹配
if 'model' in config_dict and config_dict['model'] == target_model:
# 找到了匹配的配置
return {
'api_key': config_dict.get('api_key', ''),
'model': config_dict.get('model', ''),
'base_url': config_dict.get('base_url', ''),
'temperature': config_dict.get('temperature', 0.7),
'max_tokens': config_dict.get('max_tokens', 1000),
'top_p': config_dict.get('top_p', 0.9)
}
# 递归查找子字典
for key, value in config_dict.items():
result = find_matching_config(value, target_model)
if result:
return result
elif isinstance(config_dict, list):
# 递归查找列表中的字典
for item in config_dict:
result = find_matching_config(item, target_model)
if result:
return result
return None
# 如果没有找到，返回空字典
# 在整个配置中查找
result = find_matching_config(config, mapped_name)
if result:
print(f"Found config for {model_name} -> {mapped_name}")
return result
print(f"No matching config found for {model_name} -> {mapped_name}")
return {}
except Exception as e:
@@ -203,7 +224,6 @@ def get_model_config(model_name):
return {}
baseurl = get_config().get('base_url', '')
@@ -908,11 +928,44 @@ class RN_LLMAPI_Pro_Node():
# 优先使用传入的api_baseurl和api_key，如果没有则使用配置文件中的
used_api_baseurl = api_baseurl or model_config.get('base_url', '')
used_api_key = api_key or model_config.get('api_key', '')
used_model = model_config.get('model', model) # 如果没有找到配置，使用原始模型名称
used_model = model_config.get('model', '') # 使用配置中的模型名称
# 如果配置中也没有模型名称，使用默认值
# 如果配置中没有模型名称，使用映射后的名称
if not used_model:
used_model = "qwen25-vl-32b-instruct" # 或其他默认值
# 模型名称映射字典
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": "glm-4-9b-chat",
"GLM-4-32B-0414": "ZhipuAI/GLM-4-32B-0414",
"GLM-4.1V-9B-Thinking": "ZhipuAI/GLM-4.1V-9B-Thinking",
"GLM-4.6": "ZhipuAI/GLM-4.6",
"bge-m3": "bge-m3",
"bge-reranker-v2-m3": "bge-reranker-v2-m3",
}
used_model = mapping.get(model, model)
# 如果base_url或api_key为空，使用默认的get_config作为后备
if not used_api_baseurl or not used_api_key:
cfg = get_config()
used_api_baseurl = used_api_baseurl or cfg.get('base_url', '')
used_api_key = used_api_key or cfg.get('api_key', '')
# 最终的检查，确保有base_url
if not used_api_baseurl:
return ("ERROR: No API base URL configured. Please check your configuration.",)
print(f"Using base_url: {used_api_baseurl}")
print(f"Using model: {used_model}")
client = OpenAI(api_key=used_api_key, base_url=used_api_baseurl)
@@ -942,15 +995,20 @@ class RN_LLMAPI_Pro_Node():
]
# 调用API
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'
try:
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: No response from API'
except Exception as e:
print(f"API call error: {e}")
prompt = f'Error: {str(e)}'
return (prompt,)