知微
fa45d8aa5f
- health_checklist.json: 192.168.1.122→node122
- ocr_client.py: docstring IP→node122
- docs/market-data-requirements.md: IP→node122
- 所有API调用通过ProxyHandler({})绕过系统代理
Privoxy对node122:18003返回500，直连正常
59 lines
1.9 KiB
Python
59 lines
1.9 KiB
Python
from typing import Any, Dict, Optional
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import orjson
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from litellm.types.videos.utils import encode_character_id_with_provider
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def extract_model_from_target_model_names(target_model_names: Any) -> Optional[str]:
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if isinstance(target_model_names, str):
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target_model_names = [
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m.strip() for m in target_model_names.split(",") if m.strip()
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]
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elif not isinstance(target_model_names, list):
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return None
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return target_model_names[0] if target_model_names else None
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def get_custom_provider_from_data(data: Dict[str, Any]) -> Optional[str]:
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custom_llm_provider = data.get("custom_llm_provider")
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if custom_llm_provider:
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return custom_llm_provider
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extra_body = data.get("extra_body")
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if isinstance(extra_body, str):
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try:
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parsed_extra_body = orjson.loads(extra_body)
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if isinstance(parsed_extra_body, dict):
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extra_body = parsed_extra_body
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except Exception:
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extra_body = None
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if isinstance(extra_body, dict):
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extra_body_custom_llm_provider = extra_body.get("custom_llm_provider")
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if isinstance(extra_body_custom_llm_provider, str):
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return extra_body_custom_llm_provider
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return None
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def encode_character_id_in_response(
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response: Any, custom_llm_provider: str, model_id: Optional[str]
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) -> Any:
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if isinstance(response, dict) and response.get("id"):
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response["id"] = encode_character_id_with_provider(
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character_id=response["id"],
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provider=custom_llm_provider,
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model_id=model_id,
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)
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return response
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character_id = getattr(response, "id", None)
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if isinstance(character_id, str) and character_id:
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response.id = encode_character_id_with_provider(
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character_id=character_id,
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provider=custom_llm_provider,
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model_id=model_id,
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)
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return response
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