科林_Cyril Pilgrim
1a15c8d129
Motivation: LLM API calls frequently failed with HTTP 429 and 50x errors, crashing the workflow. Code redundancy existed between different LLM nodes. Non-standard payload fields caused 400 errors with some providers. Implementation: 1. Extracted api_client.py for centralized HTTP handling with smart retries (Retry-After, backoff, jitter) and structured error logging. 2. Implemented graceful degradation to return error text instead of raising exceptions. 3. Cleaned up non-standard OpenAI payload fields. 4. Added input validation to fail fast on empty prompts or API keys. 5. Refactored both openai_compatible.py and llm_translator.py to reuse LLMClient. 6. Handled dual import registration in __init__.py for robust dynamic loading.
102 lines
3.0 KiB
Python
102 lines
3.0 KiB
Python
import json
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import urllib.request
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import urllib.parse
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import sys
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import time
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# 测试用的一个简单 ComfyUI 工作流，只包含我们修改的加载器和处理器
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# 我们需要向本地模型发起请求（因为可能没有 API Key），由于没有Key，它可能会返回 Error，
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# 但为了验证 UI 格式，只要看 error 结构或正常响应是否包含 `ui` 参数。
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# 注意我们手动传入一些测试参数
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workflow = {
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"1": {
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"inputs": {
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"provider": "Custom/自定义",
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"model": "foo",
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"api_key": "YOUR_API_KEY", # 替换为您想要测试的真实 KEY 或者随便乱填以产生报错
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"custom_base_url": "http://example.com"
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},
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"class_type": "LLM_Loader"
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},
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"2": {
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"inputs": {
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"system_prompt": "你是一个AI大模型",
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"prompt": "你好",
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"prep_img": "",
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"temperature": 0.7,
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"seed": 0,
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"llm_config": [
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"1",
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0
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]
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},
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"class_type": "OpenAICompatibleLoader"
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},
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"3": {
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"inputs": {
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"filename_prefix": "ComfyUI",
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"images": [
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"4",
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0
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]
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},
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"class_type": "SaveImage"
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},
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"4": {
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"inputs": {
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"image": "example.png"
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},
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"class_type": "LoadImage"
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}
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}
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def queue_prompt(prompt_workflow):
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p = {"prompt": prompt_workflow}
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data = json.dumps(p).encode('utf-8')
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req = urllib.request.Request("http://127.0.0.1:8188/prompt", data=data)
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return json.loads(urllib.request.urlopen(req).read())
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def get_history(prompt_id):
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with urllib.request.urlopen("http://127.0.0.1:8188/history/{}".format(prompt_id)) as response:
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return json.loads(response.read())
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def test():
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try:
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print("Submitting workflow to ComfyUI...")
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response = queue_prompt(workflow)
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prompt_id = response['prompt_id']
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print(f"Submitted! Prompt ID: {prompt_id}")
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while True:
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history = get_history(prompt_id)
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if prompt_id in history:
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print("\nExecution finished!")
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result = history[prompt_id]
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# Check for UI data in node '2'
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outputs = result.get('outputs', {})
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if '2' in outputs:
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node_2_output = outputs['2']
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if 'ui' in node_2_output:
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print("✅ Success! 'ui' attribute found in response:")
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print(json.dumps(node_2_output['ui'], indent=2, ensure_ascii=False))
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else:
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print("❌ Failed! No 'ui' attribute found in response:")
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print(json.dumps(node_2_output, indent=2, ensure_ascii=False))
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break
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time.sleep(1)
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except urllib.error.HTTPError as e:
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error_body = e.read().decode('utf-8', errors='replace')
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print(f"HTTP Error {e.code}:\n{error_body}")
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except Exception as e:
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print(f"Test failed (is ComfyUI running?): {e}")
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if __name__ == "__main__":
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test()
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