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
49 lines
1.8 KiB
Python
49 lines
1.8 KiB
Python
"""Weave (W&B) attribute mapper.
|
|
|
|
Weave consumes OpenInference + a small set of Weave-specific keys (display
|
|
name, thread id, output value). This mapper layers the latter on top of
|
|
OpenInference's vocabulary — compose ``["genai", "openinference", "weave"]``
|
|
to feed a Weave backend.
|
|
"""
|
|
|
|
from typing import Callable
|
|
|
|
from litellm.integrations.otel.mappers.base import AttributeMap, AttrValue, SpanData
|
|
from litellm.integrations.otel.mappers.utils import collect, json_or_none
|
|
from litellm.integrations.otel.model.payloads import LLMCallSpanData
|
|
|
|
|
|
class WeaveMapper:
|
|
"""Maps ``LLMCallSpanData`` to Weave's vendor attributes."""
|
|
|
|
_LLM_CALL_ATTRS: dict[str, Callable[[LLMCallSpanData], AttrValue | None]] = {
|
|
# ``display_name`` has the form ``"{operation} {model}"``. The span
|
|
# name already covers that, but Weave reads this attribute too.
|
|
"weave.display_name": lambda d: (
|
|
f"{d.operation.value} {d.request_model}" if d.request_model else None
|
|
),
|
|
"weave.call_id": lambda d: d.identity.call_id or None,
|
|
}
|
|
|
|
# JSON-payload attributes: each builder returns the serialized blob or None.
|
|
_BLOB_ATTRS: dict[str, Callable[[LLMCallSpanData], AttrValue | None]] = {
|
|
# Weave treats the response choices as the "output" payload.
|
|
"weave.output": lambda d: (
|
|
json_or_none(list(d.choices_out)) if d.choices_out else None
|
|
),
|
|
}
|
|
|
|
def map(self, data: SpanData) -> AttributeMap:
|
|
match data:
|
|
case LLMCallSpanData():
|
|
return self._llm_call(data)
|
|
case _:
|
|
return {}
|
|
|
|
@classmethod
|
|
def _llm_call(cls, data: LLMCallSpanData) -> AttributeMap:
|
|
return {
|
|
**collect(cls._LLM_CALL_ATTRS, data),
|
|
**collect(cls._BLOB_ATTRS, data),
|
|
}
|