56 lines
2.2 KiB
Python
56 lines
2.2 KiB
Python
# NB: These keys are placeholders and subject to change
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class TraceMetadataKey:
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INPUTS = "mlflow.traceInputs"
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OUTPUTS = "mlflow.traceOutputs"
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SOURCE_RUN = "mlflow.sourceRun"
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class TraceTagKey:
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TRACE_NAME = "mlflow.traceName"
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EVAL_REQUEST_ID = "eval.requestId"
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# A set of reserved attribute keys
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class SpanAttributeKey:
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EXPERIMENT_ID = "mlflow.experimentId"
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REQUEST_ID = "mlflow.traceRequestId"
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INPUTS = "mlflow.spanInputs"
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OUTPUTS = "mlflow.spanOutputs"
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SPAN_TYPE = "mlflow.spanType"
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FUNCTION_NAME = "mlflow.spanFunctionName"
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START_TIME_NS = "mlflow.spanStartTimeNs"
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# these attributes are for standardized chat messages and tool definitions
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# in CHAT_MODEL and LLM spans. they are used for rendering the rich chat
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# display in the trace UI, as well as downstream consumers of trace data
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# such as evaluation
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CHAT_MESSAGES = "mlflow.chat.messages"
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CHAT_TOOLS = "mlflow.chat.tools"
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# This attribute is used to populate `intermediate_outputs` property of a trace data
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# representing intermediate outputs of the trace. This attribute is not empty only on
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# the root span of a trace created by the `mlflow.log_trace` API. The `intermediate_outputs`
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# property of the normal trace is generated by the outputs of non-root spans.
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INTERMEDIATE_OUTPUTS = "mlflow.trace.intermediate_outputs"
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# All storage backends are guaranteed to support request_metadata key/value up to 250 characters
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MAX_CHARS_IN_TRACE_INFO_METADATA = 250
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# All storage backends are guaranteed to support tag keys up to 250 characters,
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# values up to 4096 characters
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MAX_CHARS_IN_TRACE_INFO_TAGS_KEY = 250
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MAX_CHARS_IN_TRACE_INFO_TAGS_VALUE = 4096
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TRUNCATION_SUFFIX = "..."
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# Trace request ID must have the prefix "tr-" appended to the OpenTelemetry trace ID
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TRACE_REQUEST_ID_PREFIX = "tr-"
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# Schema version of traces and spans.
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TRACE_SCHEMA_VERSION = 2
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# Key for the trace schema version in the trace. This key is also used in
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# Databricks model serving to be careful when modifying it.
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TRACE_SCHEMA_VERSION_KEY = "mlflow.trace_schema.version"
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STREAM_CHUNK_EVENT_NAME_FORMAT = "mlflow.chunk.item.{index}"
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STREAM_CHUNK_EVENT_VALUE_KEY = "mlflow.chunk.value"
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