wehub-resource-sync
48 lines
1.5 KiB
Python
48 lines
1.5 KiB
Python
from mlflow.mistral.autolog import async_patched_class_call, patched_class_call
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from mlflow.telemetry.events import AutologgingEvent
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from mlflow.telemetry.track import _record_event
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from mlflow.utils.autologging_utils import autologging_integration, safe_patch
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FLAVOR_NAME = "mistral"
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@autologging_integration(FLAVOR_NAME)
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def autolog(
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log_traces: bool = True,
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disable: bool = False,
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silent: bool = False,
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):
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"""
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Enables (or disables) and configures autologging from Mistral AI to MLflow.
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Only synchronous calls to the Text generation API are supported.
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Asynchronous APIs and streaming are not recorded.
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Args:
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log_traces: If ``True``, traces are logged for Mistral AI models.
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If ``False``, no traces are collected during inference. Default to ``True``.
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disable: If ``True``, disables the Mistral AI autologging. Default to ``False``.
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silent: If ``True``, suppress all event logs and warnings from MLflow during Mistral AI
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autologging. If ``False``, show all events and warnings.
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"""
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try:
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from mistralai.client.chat import Chat # mistralai >= 2.0
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except ImportError:
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from mistralai.chat import Chat # mistralai < 2.0
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safe_patch(
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FLAVOR_NAME,
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Chat,
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"complete",
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patched_class_call,
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)
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safe_patch(
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FLAVOR_NAME,
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Chat,
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"complete_async",
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async_patched_class_call,
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)
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_record_event(
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AutologgingEvent, {"flavor": FLAVOR_NAME, "log_traces": log_traces, "disable": disable}
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)
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