149 lines
7.2 KiB
Python
149 lines
7.2 KiB
Python
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import json, os, re, ssl, time, urllib.request, urllib.error
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from pathlib import Path
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ROOT = Path(__file__).resolve().parent
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SERVER_VERSION = '9.2.5'
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def load_config():
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cfg = {}
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p = Path(os.getenv('AI_CONFIG_PATH') or ROOT/'config.json').expanduser()
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cfg['_config_path'] = str(p)
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cfg['_config_error'] = ''
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if p.exists():
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try:
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raw = p.read_text('utf-8').strip()
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data = json.loads(raw)
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if not isinstance(data, dict):
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raise ValueError('config.json 顶层必须是 JSON 对象')
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cfg.update(data)
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except json.JSONDecodeError as e:
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cfg['_config_error'] = f'config.json JSON 格式错误：第 {e.lineno} 行第 {e.colno} 列：{e.msg}'
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except Exception as e:
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cfg['_config_error'] = f'{type(e).__name__}: {e}'
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else:
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cfg['_config_error'] = 'config.json 不存在'
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cfg['api_base'] = os.getenv('AI_API_BASE', cfg.get('api_base','https://api.bananarouter.com/v1')).rstrip('/')
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cfg['api_key'] = os.getenv('AI_API_KEY', cfg.get('api_key',''))
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cfg['model'] = os.getenv('AI_MODEL', cfg.get('model',''))
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cfg['chat_path'] = str(cfg.get('chat_path','/chat/completions'))
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cfg['models_path'] = str(cfg.get('models_path','/models'))
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try: cfg['temperature'] = float(os.getenv('AI_TEMPERATURE', cfg.get('temperature',0.2)))
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except Exception: cfg['temperature'] = 0.2
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try: cfg['timeout'] = int(os.getenv('AI_TIMEOUT', cfg.get('timeout',120)))
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except Exception: cfg['timeout'] = 120
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try: cfg['retries'] = max(0, int(cfg.get('retries',2)))
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except Exception: cfg['retries'] = 2
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cfg['extra_headers'] = cfg.get('extra_headers',{}) or {}
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cfg['ca_bundle'] = str(cfg.get('ca_bundle','') or '')
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cfg['ssl_verify'] = bool(cfg.get('ssl_verify', True))
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return cfg
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def configured():
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c=load_config()
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key=str(c.get('api_key') or '').strip(); model=str(c.get('model') or '').strip()
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return bool(not c.get('_config_error') and key and model and not key.startswith('YOUR_') and not model.startswith('YOUR_'))
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def _ssl_context(c):
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if not c.get('ssl_verify', True):
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raise RuntimeError('ssl_verify=false 被禁止。V6.2 不允许关闭 HTTPS 证书校验。')
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cafile = c.get('ca_bundle') or ''
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bundled = ROOT/'cacert.pem'
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if not cafile and bundled.exists(): cafile=str(bundled)
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if cafile:
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if not Path(cafile).exists():
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raise RuntimeError(f'ca_bundle 文件不存在：{cafile}')
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ctx=ssl.create_default_context(cafile=cafile)
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else:
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try:
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import certifi
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ctx=ssl.create_default_context(cafile=certifi.where())
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except Exception:
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ctx=ssl.create_default_context()
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try: ctx.minimum_version=ssl.TLSVersion.TLSv1_2
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except Exception: pass
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return ctx
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def _headers(c):
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h={'Content-Type':'application/json','Accept':'application/json','Authorization':'Bearer '+c['api_key'],'User-Agent':'TmallAIProductAnalysis/9.2.5'}
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h.update(c.get('extra_headers',{}))
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return h
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def _join(base,path):
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path='/' + str(path or '').lstrip('/')
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return base.rstrip('/') + path
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def probe_model_api(timeout=15):
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c=load_config()
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if c.get('_config_error'):
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return {'ok':False,'stage':'config','error':c['_config_error']}
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if not c.get('api_key') or not c.get('model'):
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return {'ok':False,'stage':'config','error':'api_key 或 model 为空'}
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try:
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req=urllib.request.Request(_join(c['api_base'],c['models_path']),headers=_headers(c),method='GET')
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with urllib.request.urlopen(req,timeout=min(timeout,c['timeout']),context=_ssl_context(c)) as r:
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obj=json.loads(r.read().decode('utf-8','ignore') or '{}')
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ids=[x.get('id') for x in (obj.get('data') or []) if isinstance(x,dict)]
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return {'ok':True,'stage':'models','http':200,'modelFound':(c['model'] in ids) if ids else None,'model':c['model'],'modelsCount':len(ids)}
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except urllib.error.HTTPError as e:
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body=e.read().decode('utf-8','ignore')
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return {'ok':False,'stage':'models','http':e.code,'error':body[:500] or str(e)}
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except ssl.SSLCertVerificationError as e:
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return {'ok':False,'stage':'ssl','error':f'SSL证书验证失败：{e}. V6.2 已优先使用 certifi；如仍失败，请确认 Python/代理没有替换证书链。'}
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except Exception as e:
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return {'ok':False,'stage':'network','error':str(e)}
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def _parse_json(s):
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if isinstance(s, dict): return s
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s = (s or '').strip()
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s = re.sub(r'^```(?:json)?\s*|\s*```$', '', s, flags=re.I|re.S)
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try: return json.loads(s)
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except Exception:
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a=s.find('{'); b=s.rfind('}')
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if a>=0 and b>a: return json.loads(s[a:b+1])
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raise
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def _do_post(c,payload):
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req=urllib.request.Request(_join(c['api_base'],c['chat_path']),data=json.dumps(payload,ensure_ascii=False).encode('utf-8'),headers=_headers(c),method='POST')
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with urllib.request.urlopen(req,timeout=c['timeout'],context=_ssl_context(c)) as r:
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return json.loads(r.read().decode('utf-8','ignore'))
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def chat_json(system, user, images=None, max_tokens=5000):
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c=load_config()
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if c.get('_config_error'):
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raise RuntimeError(c['_config_error'])
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if not c.get('api_key') or not c.get('model'):
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raise RuntimeError('未配置模型。请复制 config.example.json 为 config.json，并填写 api_key 与 model。')
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content=[{'type':'text','text':user}]
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for url in (images or [])[:12]:
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if isinstance(url,str) and url.startswith(('http://','https://','data:image/')):
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content.append({'type':'image_url','image_url':{'url':url}})
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base_payload={
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'model':c['model'],
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'messages':[{'role':'system','content':system},{'role':'user','content':content if len(content)>1 else user}],
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'temperature':c['temperature'],
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'response_format':{'type':'json_object'},
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'max_tokens':max_tokens
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}
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variants=[base_payload]
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# Some OpenAI-compatible gateways/models reject response_format, temperature, or max_tokens.
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v2=dict(base_payload); v2.pop('response_format',None); variants.append(v2)
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v3=dict(v2); v3.pop('temperature',None); v3['max_completion_tokens']=v3.pop('max_tokens',max_tokens); variants.append(v3)
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last=None
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for attempt in range(c['retries']+1):
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for payload in variants:
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try:
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obj=_do_post(c,payload)
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try: return _parse_json(obj['choices'][0]['message']['content'])
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except Exception as e: raise RuntimeError(f'模型返回无法解析为 JSON: {e}')
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except urllib.error.HTTPError as e:
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body=e.read().decode('utf-8','ignore')
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last=RuntimeError(f'模型接口 HTTP {e.code}: {body[:900]}')
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if e.code not in (400,408,409,429,500,502,503,504): raise last
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except ssl.SSLCertVerificationError as e:
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raise RuntimeError(f'SSL证书验证失败：{e}。V6.2 已使用 certifi CA；请检查本机 Python/代理证书链。')
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except Exception as e:
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last=RuntimeError(f'模型接口调用失败: {e}')
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if attempt<c['retries']:
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time.sleep(min(1.5*(attempt+1),4))
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raise last or RuntimeError('模型接口调用失败')
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