repo stringclasses 454
values | file_path stringlengths 5 201 | extension stringclasses 1
value | content stringlengths 8 509k | num_lines int64 3 16.9k | size_bytes int64 8 511k |
|---|---|---|---|---|---|
qutip | qutip/tests/core/data/test_properties.py | .py | import numpy as np
import pytest
import qutip
from qutip import data as _data
from qutip import CoreOptions
from . import conftest
from qutip.core.data.dia import clean_dia
@pytest.fixture(params=[_data.CSR, _data.Dense, _data.Dia], ids=["CSR", "Dense", "Dia"])
def datatype(request):
return request.param
class ... | 257 | 10,244 |
qutip | qutip/tests/core/data/test_convert.py | .py | import numpy as np
import pytest
from scipy import sparse
from qutip import data, CoreOptions
from .test_mathematics import UnaryOpMixin
def test_init_empty_data():
shape = (3, 3)
base_data = data.Data(shape)
assert base_data.shape[0] == shape[0]
assert base_data.shape[1] == shape[1]
@pytest.mark.pa... | 118 | 4,874 |
qutip | qutip/tests/core/data/test_dispatch.py | .py | import pytest
import itertools
import qutip
from qutip.core.data.dispatch import Dispatcher, _constructed_specialisation
import qutip.core.data as _data
class pseudo_dipatched:
def __init__(self, types, output):
if output:
self.output = types[-1]
self.inputs = types[:-1]
el... | 218 | 6,802 |
qutip | qutip/tests/core/data/test_block_operations.py | .py | import pytest
import numpy as np
from qutip.core import data as _data
from qutip.core.data import csr, Dense
from . import conftest
@pytest.mark.parametrize('outtype', _data.to.dtypes)
def test_empty_block_build(outtype):
"""block_build with no blocks should return a zero matrix"""
block_rows = np.array([], d... | 247 | 9,641 |
qutip | qutip/tests/core/data/test_reshape.py | .py | from .test_mathematics import UnaryOpMixin
import pytest
import numpy as np
from qutip import data
from qutip.core.data import CSR, Dense, Dia
class TestSplitColumns(UnaryOpMixin):
def op_numpy(self, matrix):
return [column[:, np.newaxis] for column in matrix.T]
specialisations = [
pytest.par... | 127 | 4,694 |
qutip | qutip/tests/core/data/test_norm.py | .py | from . import test_mathematics as testing
import numpy as np
import scipy.linalg
import pytest
from qutip import data
from qutip.core.data import CSR, Dense, Dia
import numbers
class TestOneNorm(testing.UnaryOpMixin):
def op_numpy(self, matrix):
return scipy.linalg.norm(matrix, 1)
specialisations = [... | 74 | 2,402 |
qutip | qutip/tests/core/data/test_ptrace.py | .py | from . import test_mathematics as testing
import numpy as np
import scipy.linalg
import pytest
from qutip import data
from qutip.core.data import CSR, Dense, Dia
class TestPtrace(testing.UnaryOpMixin):
def op_numpy(self, matrix, dims, sel):
sel.sort()
ndims = len(dims)
dkeep = [dims[x] for... | 110 | 3,571 |
qutip | qutip/tests/core/data/test_mean.py | .py | import pytest
import numpy as np
import qutip
import numbers
from qutip.core.data.mean import mean_csr, mean_dia, mean_dense
from qutip.core.data.mean import mean_abs_csr, mean_abs_dia, mean_abs_dense
from qutip.core.data import CSR, Dia, Dense
from . import test_mathematics as testing
class TestMean(testing.UnaryOp... | 84 | 2,632 |
qutip | qutip/tests/core/data/test_mathematics.py | .py | import itertools
import numpy as np
import pytest
import scipy
import warnings
from qutip.core import data
from qutip.core.data import Data, Dense, CSR, Dia
from qutip.core.data.dense import OrderEfficiencyWarning
from . import conftest
# The ParameterSet is actually a pretty hidden type, so it's easiest to access
#... | 1,247 | 45,538 |
qutip | qutip/tests/core/data/conftest.py | .py | import numpy as np
import scipy.sparse
import qutip
def shuffle_indices_scipy_csr(matrix, gen=None):
"""
Given a scipy CSR matrix or array, shuffle the indices within each row and
return a new object of the same type. This should represent the same
matrix, but in the less efficient, "unsorted" manne... | 139 | 5,014 |
qutip | qutip/tests/piqs/test_piqs.py | .py | """
Tests for Permutational Invariant Quantum solver (PIQS).
"""
import math
import numpy as np
from numpy.testing import (
assert_raises,
assert_array_equal,
assert_array_almost_equal,
assert_almost_equal,
assert_equal,
)
from scipy.sparse import block_diag, coo_matrix
from qutip import Qobj, entro... | 1,575 | 52,275 |
qutip | qutip/legacy/rcsolve.py | .py | """
This module provides exact solvers for a system-bath setup using the
reaction coordinate method.
"""
# Author: Neill Lambert, Anubhav Vardhan
# Contact: nwlambert@gmail.com
__all__ = ['rcsolve']
import warnings
import numpy as np
import scipy.sparse as sp
from numpy import matrix
from numpy import linalg
from ..... | 121 | 3,707 |
qutip | qutip/legacy/__init__.py | .py | import warnings
warnings.warn("Function in legacy are untested.")
del warnings
from .nonmarkov.memorycascade import MemoryCascade
| 6 | 131 |
qutip | qutip/legacy/nonmarkov/memorycascade.py | .py | # @author: Arne L. Grimsmo
# @email1: arne.grimsmo@gmail.com
# @organization: University of Sherbrooke
"""
This module is an implementation of the method introduced in [1], for
solving open quantum systems subject to coherent feedback with a single
discrete time-delay. This method is referred to as the ``memory cascad... | 432 | 12,909 |
qutip | qutip/_mkl/spsolve.py | .py | import sys
import numpy as np
import scipy.sparse as sp
from ctypes import c_int, byref
from numpy.ctypeslib import ndpointer
import time
from qutip.settings import settings as qset
# Load solver functions from mkl_lib
pardiso = qset.mkl_lib.pardiso
pardiso_delete = qset.mkl_lib.pardiso_handle_delete
if sys.maxsize > ... | 407 | 12,901 |
qutip | qutip/_mkl/spmv.py | .py | import numpy as np
from ctypes import POINTER, c_int, c_char, byref
from numpy.ctypeslib import ndpointer
import qutip.settings as qset
zcsrgemv = qset.mkl_lib.mkl_cspblas_zcsrgemv
def mkl_spmv(A, x):
"""
sparse csr_spmv using MKL
"""
m, _ = A.shape
# Pointers to data of the matrix
data = A.d... | 39 | 1,196 |
qutip | qutip/ui/progressbar.py | .py | __all__ = ['BaseProgressBar', 'TextProgressBar',
'EnhancedTextProgressBar', 'TqdmProgressBar',
'HTMLProgressBar', 'progress_bars']
import time
import datetime
import sys
from qutip import settings
class BaseProgressBar(object):
"""
An abstract progress bar with some shared functionality... | 207 | 6,173 |
qutip | qutip/piqs/piqs.py | .py | """Permutational Invariant Quantum Solver (PIQS)
This module calculates the Liouvillian for the dynamics of ensembles of
identical two-level systems (TLS) in the presence of local and collective
processes by exploiting permutational symmetry and using the Dicke basis.
It also allows to characterize nonlinear functions... | 1,920 | 53,204 |
mlflow | bin/install.py | .py | """
Install binary tools for MLflow development.
"""
# ruff: noqa: T201
import argparse
import gzip
import hashlib
import http.client
import platform
import re
import shutil
import subprocess
import tarfile
import tempfile
import time
import urllib.request
from dataclasses import dataclass
from pathlib import Path
fro... | 338 | 12,008 |
mlflow | mlflow/environment_variables.py | .py | """
This module defines environment variables used in MLflow.
MLflow's environment variables adhere to the following naming conventions:
- Public variables: environment variable names begin with `MLFLOW_`
- Internal-use variables: For variables used only internally, names start with `_MLFLOW_`
"""
import os
import war... | 1,705 | 80,170 |
mlflow | mlflow/exceptions.py | .py | import json
import logging
from mlflow.error_classification import ErrorClass, SqlState
from mlflow.protos.databricks_pb2 import (
ABORTED,
ALREADY_EXISTS,
BAD_REQUEST,
CANCELLED,
CUSTOMER_UNAUTHORIZED,
DATA_LOSS,
DEADLINE_EXCEEDED,
ENDPOINT_NOT_FOUND,
INTERNAL_ERROR,
INVALID_PA... | 307 | 11,549 |
mlflow | mlflow/runs.py | .py | """
CLI for runs
"""
import json
import click
import mlflow
from mlflow import MlflowClient
from mlflow.entities import RunStatus, ViewType
from mlflow.environment_variables import MLFLOW_EXPERIMENT_ID, MLFLOW_EXPERIMENT_NAME
from mlflow.exceptions import MlflowException
from mlflow.mcp.decorator import mlflow_mcp
f... | 253 | 8,060 |
mlflow | mlflow/__main__.py | .py | from mlflow.cli import cli
cli.main()
| 4 | 39 |
mlflow | mlflow/__init__.py | .py | """
The ``mlflow`` module provides a high-level "fluent" API for starting and managing MLflow runs.
For example:
.. code:: python
import mlflow
mlflow.start_run()
mlflow.log_param("my", "param")
mlflow.log_metric("score", 100)
mlflow.end_run()
You can also use the context manager syntax like thi... | 451 | 14,048 |
mlflow | mlflow/mismatch.py | .py | from __future__ import annotations
import importlib.metadata
import warnings
def _get_version(package_name: str) -> str | None:
try:
return importlib.metadata.version(package_name)
except importlib.metadata.PackageNotFoundError:
return None
def _check_version_mismatch() -> None:
"""
... | 43 | 1,335 |
mlflow | mlflow/version.py | .py | # Copyright 2018 Databricks, Inc.
import importlib.metadata
import re
VERSION = "3.15.2.dev0"
def is_release_version():
return bool(re.match(r"^\d+\.\d+\.\d+$", VERSION))
def _is_package_installed(package_name: str) -> bool:
try:
importlib.metadata.version(package_name)
return True
exce... | 30 | 974 |
mlflow | mlflow/error_classification.py | .py | """Centralized error classification for MLflow exceptions.
Maps error codes to sqlstate codes and error classes for structured error
classification and observability. Client-side errors use the KAM0x/XXM0x
namespace, while server/CP errors use the KAMCx/XXMCx namespace.
Terminology:
error_code: The existing MLflo... | 198 | 9,094 |
mlflow | mlflow/client.py | .py | """
The ``mlflow.client`` module provides a Python CRUD interface to MLflow Experiments, Runs,
Model Versions, and Registered Models. This is a lower level API that directly translates to MLflow
`REST API <../rest-api.html>`_ calls.
For a higher level API for managing an "active run", use the :py:mod:`mlflow` module.
"... | 13 | 407 |
mlflow | mlflow/db.py | .py | import click
@click.group("db")
def commands():
"""
Commands for managing an MLflow tracking database.
"""
@commands.command()
@click.argument("url")
def upgrade(url):
"""
Upgrade the schema of an MLflow tracking database to the latest supported version.
**IMPORTANT**: Schema migrations can... | 359 | 12,646 |
mlflow | mlflow/experiments.py | .py | import json
import os
import click
import mlflow
from mlflow.entities import ExperimentTag, ViewType
from mlflow.exceptions import MlflowException
from mlflow.mcp.decorator import mlflow_mcp
from mlflow.protos import databricks_pb2
from mlflow.tracing.constant import TraceExperimentTagKey
from mlflow.tracking import ... | 420 | 14,909 |
mlflow | mlflow/webhooks/types.py | .py | """Type definitions for MLflow webhook payloads.
This module contains class definitions for all webhook event payloads
that are sent when various model registry events occur.
"""
from typing import Literal, TypeAlias, TypedDict
from mlflow.entities.webhook import WebhookAction, WebhookEntity, WebhookEvent
class Re... | 590 | 15,358 |
mlflow | mlflow/webhooks/__init__.py | .py | """MLflow webhooks module.
This module provides webhook functionality for MLflow model registry and prompt registry events.
"""
from mlflow.webhooks.constants import WEBHOOK_SIGNATURE_HEADER
from mlflow.webhooks.types import (
ModelVersionAliasCreatedPayload,
ModelVersionAliasDeletedPayload,
ModelVersionC... | 43 | 1,248 |
mlflow | mlflow/webhooks/constants.py | .py | # MLflow webhook headers
WEBHOOK_SIGNATURE_HEADER = "X-MLflow-Signature"
WEBHOOK_TIMESTAMP_HEADER = "X-MLflow-Timestamp"
WEBHOOK_DELIVERY_ID_HEADER = "X-MLflow-Delivery-Id"
# Webhook signature version
WEBHOOK_SIGNATURE_VERSION = "v1"
| 8 | 235 |
mlflow | mlflow/webhooks/delivery.py | .py | """Webhook delivery implementation following Standard Webhooks conventions.
This module implements webhook delivery patterns similar to the Standard Webhooks
specification (https://www.standardwebhooks.com), providing consistent and secure
webhook delivery with HMAC signature verification and timestamp-based replay pr... | 357 | 11,847 |
mlflow | mlflow/webhooks/ssrf.py | .py | """Connection-time SSRF protection for outbound webhook delivery.
``_validate_webhook_url`` resolves the webhook hostname and checks that every
resolved IP is public, but it discards the resolved IP and the subsequent
``requests.post`` re-resolves the hostname independently. That TOCTOU gap lets a
DNS-rebinding attack... | 145 | 5,265 |
mlflow | mlflow/johnsnowlabs/__init__.py | .py | """
The ``mlflow.johnsnowlabs`` module provides an API for logging and loading Spark NLP and NLU models.
This module exports the following flavors:
Johnsnowlabs (native) format
Allows models to be loaded as Spark Transformers for scoring in a Spark session.
Models with this flavor can be loaded as NluPipelines... | 892 | 34,834 |
mlflow | mlflow/spacy/__init__.py | .py | """
The ``mlflow.spacy`` module provides an API for logging and loading spaCy models.
This module exports spacy models with the following flavors:
spaCy (native) format
This is the main flavor that can be loaded back into spaCy.
:py:mod:`mlflow.pyfunc`
Produced for use by generic pyfunc-based deployment tools ... | 380 | 14,045 |
mlflow | mlflow/demo/__init__.py | .py | import logging
import mlflow.demo.generators # noqa: F401
from mlflow.demo.base import DEMO_EXPERIMENT_NAME, DEMO_PROMPT_PREFIX, BaseDemoGenerator, DemoResult
from mlflow.demo.registry import demo_registry
from mlflow.utils.workspace_context import WorkspaceContext, get_request_workspace
_logger = logging.getLogger(... | 49 | 1,799 |
mlflow | mlflow/demo/registry.py | .py | from __future__ import annotations
from typing import TYPE_CHECKING
from mlflow.demo.base import DemoFeature
if TYPE_CHECKING:
from mlflow.demo.base import BaseDemoGenerator
class DemoRegistry:
"""Registry for demo data generators.
Provides registration and lookup of BaseDemoGenerator subclasses by na... | 44 | 1,447 |
mlflow | mlflow/demo/data.py | .py | from __future__ import annotations
import base64
import functools
import math
import struct
import zlib
from dataclasses import dataclass, field
from typing import Any
from mlflow.demo.base import DEMO_PROMPT_PREFIX
from mlflow.entities.issue import IssueSeverity
from mlflow.entities.model_registry import PromptVersi... | 1,234 | 49,213 |
mlflow | mlflow/demo/base.py | .py | import logging
from abc import ABC, abstractmethod
from dataclasses import dataclass
from enum import Enum
from mlflow.tracking._tracking_service.utils import _get_store
_logger = logging.getLogger(__name__)
DEMO_EXPERIMENT_NAME = "MLflow Demo"
DEMO_PROMPT_PREFIX = "mlflow-demo"
class DemoFeature(str, Enum):
"... | 136 | 4,746 |
mlflow | mlflow/demo/generators/judges.py | .py | from __future__ import annotations
import logging
from mlflow.demo.base import (
DEMO_EXPERIMENT_NAME,
DEMO_PROMPT_PREFIX,
BaseDemoGenerator,
DemoFeature,
DemoResult,
)
from mlflow.genai.scorers.registry import delete_scorer, list_scorers
from mlflow.tracking._tracking_service.utils import _get_st... | 145 | 5,916 |
mlflow | mlflow/demo/generators/evaluation.py | .py | from __future__ import annotations
import contextlib
import hashlib
import io
import logging
import os
from collections.abc import Callable
from typing import TYPE_CHECKING, Literal
import mlflow
if TYPE_CHECKING:
from mlflow.genai.datasets import EvaluationDataset
from mlflow.demo.base import (
DEMO_EXPERI... | 404 | 15,123 |
mlflow | mlflow/demo/generators/__init__.py | .py | from mlflow.demo.generators.evaluation import EvaluationDemoGenerator
from mlflow.demo.generators.issues import IssuesDemoGenerator
from mlflow.demo.generators.judges import JudgesDemoGenerator
from mlflow.demo.generators.prompts import PromptsDemoGenerator
from mlflow.demo.generators.review_queues import ReviewQueuesD... | 29 | 1,277 |
mlflow | mlflow/demo/generators/issues.py | .py | from __future__ import annotations
import logging
from typing import Any
import mlflow
from mlflow import MlflowClient
from mlflow.demo.base import (
DEMO_EXPERIMENT_NAME,
BaseDemoGenerator,
DemoFeature,
DemoResult,
)
from mlflow.demo.data import ASSESSMENT_TO_ISSUE, ROOT_CAUSE_EXPLANATIONS
from mlflo... | 233 | 9,592 |
mlflow | mlflow/demo/generators/review_queues.py | .py | from __future__ import annotations
import logging
from typing import Any
import mlflow
from mlflow.demo.base import (
DEMO_EXPERIMENT_NAME,
BaseDemoGenerator,
DemoFeature,
DemoResult,
)
from mlflow.exceptions import MlflowException
from mlflow.genai.label_schemas import InputCategorical, InputPassFail... | 190 | 7,827 |
mlflow | mlflow/demo/generators/traces.py | .py | from __future__ import annotations
import copy
import hashlib
import json
import logging
import random
import re
from dataclasses import dataclass
from datetime import datetime, timedelta, timezone
from typing import Any, Literal
import mlflow
from mlflow.demo.base import (
DEMO_EXPERIMENT_NAME,
DEMO_PROMPT_P... | 894 | 33,742 |
mlflow | mlflow/demo/generators/prompts.py | .py | from __future__ import annotations
import logging
from mlflow.demo.base import (
DEMO_EXPERIMENT_NAME,
DEMO_PROMPT_PREFIX,
BaseDemoGenerator,
DemoFeature,
DemoResult,
)
from mlflow.demo.data import DEMO_PROMPTS, DemoPromptDef
from mlflow.genai.prompts import (
delete_prompt_alias,
register... | 132 | 4,401 |
mlflow | mlflow/gemini/__init__.py | .py | """
The ``mlflow.gemini`` module provides an API for tracing the interaction with Gemini models.
"""
from mlflow.gemini.autolog import (
async_patched_class_call,
patched_class_call,
patched_module_call,
)
from mlflow.telemetry.events import AutologgingEvent
from mlflow.telemetry.track import _record_event... | 99 | 2,967 |
mlflow | mlflow/gemini/chat.py | .py | import json
import logging
from typing import TYPE_CHECKING
from mlflow.types.chat import (
ChatTool,
Function,
FunctionParams,
FunctionToolDefinition,
ParamProperty,
ToolCall,
)
if TYPE_CHECKING:
from google import genai
_logger = logging.getLogger(__name__)
def convert_gemini_func_to_... | 113 | 3,462 |
mlflow | mlflow/gemini/autolog.py | .py | import inspect
import logging
from typing import Any
import mlflow
import mlflow.gemini
from mlflow.entities import SpanType
from mlflow.entities.span import LiveSpan
from mlflow.gemini.chat import (
convert_gemini_func_to_mlflow_chat_tool,
)
from mlflow.tracing.constant import SpanAttributeKey, TokenUsageKey
from... | 328 | 11,809 |
mlflow | mlflow/gemini/genai_semconv_converter.py | .py | import json
from typing import Any
from mlflow.tracing.constant import GenAiSemconvKey
from mlflow.tracing.export.genai_semconv.converter import GenAiSemconvConverter
class GeminiConverter(GenAiSemconvConverter):
def convert_inputs(self, inputs: dict[str, Any]) -> list[dict[str, Any]] | None:
contents = ... | 127 | 4,972 |
mlflow | mlflow/bedrock/utils.py | .py | import logging
from typing import Any, Callable, Sequence
from mlflow.bedrock import FLAVOR_NAME
from mlflow.environment_variables import _MLFLOW_TESTING
from mlflow.tracing.constant import TokenUsageKey
from mlflow.utils.autologging_utils.config import AutoLoggingConfig
_logger = logging.getLogger(__name__)
# Token... | 213 | 8,539 |
mlflow | mlflow/bedrock/__init__.py | .py | import logging
from mlflow.telemetry.events import AutologgingEvent
from mlflow.telemetry.track import _record_event
from mlflow.utils.autologging_utils import autologging_integration, safe_patch
_logger = logging.getLogger(__name__)
FLAVOR_NAME = "bedrock"
@autologging_integration(FLAVOR_NAME)
def autolog(
lo... | 50 | 1,988 |
mlflow | mlflow/bedrock/chat.py | .py | from typing import Any
from mlflow.types.chat import ChatTool, FunctionToolDefinition
def convert_tool_to_mlflow_chat_tool(tool: dict[str, Any]) -> ChatTool:
"""
Convert Bedrock tool definition into MLflow's standard format (OpenAI compatible).
Ref: https://docs.aws.amazon.com/bedrock/latest/APIReferenc... | 27 | 810 |
mlflow | mlflow/bedrock/_autolog.py | .py | import io
import json
import logging
from typing import Any
from botocore.client import BaseClient
from botocore.response import StreamingBody
import mlflow
from mlflow.bedrock import FLAVOR_NAME
from mlflow.bedrock.chat import convert_tool_to_mlflow_chat_tool
from mlflow.bedrock.stream import ConverseStreamWrapper, ... | 240 | 9,147 |
mlflow | mlflow/bedrock/genai_semconv_converter.py | .py | """
Bedrock Converse API message converter for GenAI Semantic Convention export.
Translates Bedrock's Converse API format (content blocks with text, toolUse,
toolResult, image) into the GenAI semconv parts array format.
"""
import base64
import json
from typing import Any
from mlflow.tracing.constant import GenAiSem... | 149 | 5,306 |
mlflow | mlflow/bedrock/stream.py | .py | import json
import logging
from typing import Any
from botocore.eventstream import EventStream
from mlflow.bedrock.utils import (
capture_exception,
parse_complete_token_usage_from_response,
parse_partial_token_usage_from_response,
)
from mlflow.entities.span import LiveSpan
from mlflow.entities.span_even... | 217 | 7,875 |
mlflow | mlflow/strands/__init__.py | .py | import logging
from mlflow.strands.autolog import setup_strands_tracing, teardown_strands_tracing
from mlflow.telemetry.events import AutologgingEvent
from mlflow.telemetry.track import _record_event
from mlflow.utils.autologging_utils import autologging_integration
FLAVOR_NAME = "strands"
_logger = logging.getLogger... | 42 | 1,440 |
mlflow | mlflow/strands/autolog.py | .py | import json
import logging
import threading
from opentelemetry.context import Context
from opentelemetry.sdk.trace import (
ReadableSpan as OTelReadableSpan,
)
from opentelemetry.sdk.trace import (
Span as OTelSpan,
)
from opentelemetry.sdk.trace import (
TracerProvider as SDKTracerProvider,
)
from opentel... | 180 | 7,137 |
mlflow | mlflow/diffusers/__init__.py | .py | """
The ``mlflow.diffusers`` module provides an API for logging and loading diffusion model
LoRA adapters as MLflow Models. This module exports adapter models with
the following flavors:
:py:mod:`mlflow.diffusers`
Adapter weights in safetensors format, with a reference to the base model.
:py:mod:`mlflow.pyfunc`
... | 541 | 20,534 |
mlflow | mlflow/diffusers/wrapper.py | .py | import io
import logging
import threading
from types import MappingProxyType
from typing import Any
import pandas as pd
from mlflow.diffusers import _detect_device
from mlflow.exceptions import MlflowException
_logger = logging.getLogger(__name__)
class _DiffusersAdapterWrapper:
def __init__(
self,
... | 152 | 5,659 |
mlflow | mlflow/tracing/provider.py | .py | """
This module provides a set of functions to manage the global tracer provider for MLflow tracing.
Every tracing operation in MLflow *MUST* be managed through this module, instead of directly
using the OpenTelemetry APIs. This is because MLflow needs to control the initialization of the
tracer provider and ensure th... | 1,107 | 44,109 |
mlflow | mlflow/tracing/destination.py | .py | """
Trace destination classes are DEPRECATED. Use mlflow.entities.trace_location.TraceLocation instead.
"""
from __future__ import annotations
import logging
from contextvars import ContextVar
from dataclasses import dataclass
import mlflow
from mlflow.entities.trace_location import (
MlflowExperimentLocation,
... | 164 | 6,247 |
mlflow | mlflow/tracing/analysis.py | .py | import math
from dataclasses import dataclass
from mlflow.entities._mlflow_object import _MlflowObject
from mlflow.protos.service_pb2 import CalculateTraceFilterCorrelation
@dataclass
class TraceFilterCorrelationResult(_MlflowObject):
"""
Result of calculating correlation between two trace filter conditions.... | 89 | 3,376 |
mlflow | mlflow/tracing/databricks.py | .py | from mlflow.exceptions import MlflowException
from mlflow.utils.uri import is_databricks_uri
def set_databricks_monitoring_sql_warehouse_id(
sql_warehouse_id: str, experiment_id: str | None = None
) -> None:
"""
Set the SQL warehouse ID used for Databricks production monitoring on traces logged to the giv... | 43 | 1,629 |
mlflow | mlflow/tracing/trace_archival_config.py | .py | from __future__ import annotations
import logging
import threading
import time
from dataclasses import dataclass
from pathlib import Path
from typing import Any
import yaml
from mlflow.environment_variables import MLFLOW_TRACE_ARCHIVAL_CONFIG
from mlflow.exceptions import MlflowException
from mlflow.store.tracking.u... | 258 | 8,675 |
mlflow | mlflow/tracing/trace_manager.py | .py | import contextlib
import logging
import threading
from dataclasses import dataclass, field
from typing import Generator, Sequence
from mlflow.entities import LiveSpan, Trace, TraceData, TraceInfo
from mlflow.entities.model_registry import PromptVersion
from mlflow.environment_variables import MLFLOW_TRACE_TIMEOUT_SECO... | 238 | 9,148 |
mlflow | mlflow/tracing/sampling.py | .py | import contextvars
from opentelemetry.sdk.trace.sampling import (
Sampler,
SamplingResult,
TraceIdRatioBased,
)
# Context variable to override the sampling ratio for a specific trace.
# When set, the sampler uses this ratio instead of the default.
_SAMPLING_RATIO_OVERRIDE = contextvars.ContextVar("samplin... | 49 | 1,579 |
mlflow | mlflow/tracing/__init__.py | .py | from mlflow.tracing.config import configure
from mlflow.tracing.context import context
from mlflow.tracing.databricks import set_databricks_monitoring_sql_warehouse_id
from mlflow.tracing.display import disable_notebook_display, enable_notebook_display
from mlflow.tracing.distributed import (
get_tracing_context_he... | 36 | 1,149 |
mlflow | mlflow/tracing/archival.py | .py | _ERROR_MSG = (
"The `databricks-agents` package is required to use databricks trace archival. "
"Please install it with `pip install databricks-agents`."
)
def enable_databricks_trace_archival(
*,
delta_table_fullname: str,
experiment_id: str | None = None,
) -> None:
"""
Enable archiving ... | 71 | 2,086 |
mlflow | mlflow/tracing/assessment.py | .py | from typing import Any
from mlflow.entities.assessment import (
DEFAULT_FEEDBACK_NAME,
Assessment,
AssessmentError,
Expectation,
Feedback,
FeedbackValueType,
IssueReference,
)
from mlflow.entities.assessment_source import AssessmentSource
from mlflow.exceptions import MlflowException
from m... | 482 | 17,212 |
mlflow | mlflow/tracing/client.py | .py | import json
import logging
import time
from collections import defaultdict
from concurrent.futures import ThreadPoolExecutor
from contextlib import nullcontext
from typing import TYPE_CHECKING, Sequence
import mlflow
if TYPE_CHECKING:
from mlflow.genai.label_schemas.label_schemas import (
InputCategorical... | 1,104 | 44,937 |
mlflow | mlflow/tracing/context.py | .py | from __future__ import annotations
import contextlib
from contextvars import ContextVar
from dataclasses import dataclass, field
from typing import Generator
from mlflow.tracing.constant import TraceMetadataKey
@dataclass(frozen=True)
class _UserTraceContext:
"""
Metadata and tags declared via ``mlflow.trac... | 124 | 4,633 |
mlflow | mlflow/tracing/enablement.py | .py | """
Trace enablement functionality for MLflow to enable tracing to Databricks Storage.
"""
import logging
import mlflow
from mlflow.entities.trace_location import UCSchemaLocation
from mlflow.exceptions import MlflowException
from mlflow.utils.uri import is_databricks_uri
from mlflow.version import IS_TRACING_SDK_ONL... | 161 | 5,949 |
mlflow | mlflow/tracing/trace_archival_service.py | .py | from __future__ import annotations
import logging
import random
import threading
import time
from contextlib import nullcontext
from dataclasses import dataclass
from mlflow.entities.workspace import TraceArchivalConfig
from mlflow.environment_variables import (
MLFLOW_ENABLE_WORKSPACES,
)
from mlflow.exceptions ... | 213 | 8,102 |
mlflow | mlflow/tracing/locations.py | .py | from mlflow.entities.trace_location import UnityCatalog
__all__ = ["UnityCatalog"]
| 4 | 84 |
mlflow | mlflow/tracing/constant.py | .py | from enum import Enum
# NB: These keys are placeholders and subject to change
class TraceMetadataKey:
INPUTS = "mlflow.traceInputs"
OUTPUTS = "mlflow.traceOutputs"
SOURCE_RUN = "mlflow.sourceRun"
MODEL_ID = "mlflow.modelId"
# Trace size statistics including total size, number of spans, and max spa... | 397 | 14,432 |
mlflow | mlflow/tracing/fluent.py | .py | from __future__ import annotations
import contextlib
import functools
import importlib
import inspect
import json
import logging
import os
import warnings
from concurrent.futures import ThreadPoolExecutor
from contextvars import ContextVar
from typing import TYPE_CHECKING, Any, Callable, Generator, Literal, ParamSpec,... | 1,975 | 77,248 |
mlflow | mlflow/tracing/config.py | .py | from dataclasses import dataclass, field, replace
from typing import TYPE_CHECKING, Any, Callable
from mlflow.tracing.utils.processor import validate_span_processors
if TYPE_CHECKING:
from mlflow.entities.span import LiveSpan
@dataclass
class TracingConfig:
"""Configuration for MLflow tracing behavior."""
... | 124 | 4,413 |
mlflow | mlflow/tracing/attachments.py | .py | import mimetypes
import uuid
from pathlib import Path
from urllib.parse import parse_qs, urlencode, urlparse
class Attachment:
"""
Represents a binary attachment (image, audio, PDF, etc.) that can be logged
as part of a trace span's inputs or outputs.
When an Attachment is set as a span input/output ... | 74 | 2,437 |
mlflow | mlflow/tracing/export/inference_table.py | .py | import logging
from typing import Any, Sequence
from cachetools import TTLCache
from opentelemetry.sdk.trace import ReadableSpan
from opentelemetry.sdk.trace.export import SpanExporter
from mlflow.entities.model_registry import PromptVersion
from mlflow.entities.trace import Trace
from mlflow.environment_variables im... | 163 | 6,957 |
mlflow | mlflow/tracing/export/utils.py | .py | """
Utility functions for prompt linking in trace exporters.
"""
import logging
import threading
import uuid
from typing import Sequence
from mlflow.entities.model_registry import PromptVersion
from mlflow.tracing.client import TracingClient
_logger = logging.getLogger(__name__)
def try_link_prompts_to_trace(
... | 71 | 2,201 |
mlflow | mlflow/tracing/export/span_batcher.py | .py | import atexit
import logging
import threading
from collections import defaultdict
from queue import Queue
from typing import Callable
from mlflow.entities.span import Span
from mlflow.environment_variables import (
MLFLOW_ASYNC_TRACE_LOGGING_MAX_INTERVAL_MILLIS,
MLFLOW_ASYNC_TRACE_LOGGING_MAX_SPAN_BATCH_SIZE,
... | 123 | 4,682 |
mlflow | mlflow/tracing/export/async_export_queue.py | .py | import atexit
import logging
import threading
import time
from concurrent.futures import FIRST_COMPLETED, ThreadPoolExecutor, wait
from dataclasses import dataclass
from queue import Empty, Queue
from queue import Full as queue_Full
from typing import Any, Callable, Sequence
from mlflow.environment_variables import (
... | 188 | 6,851 |
mlflow | mlflow/tracing/export/uc_table.py | .py | import logging
from typing import Sequence
from opentelemetry.sdk.trace import ReadableSpan
from mlflow.entities.span import Span
from mlflow.entities.trace_info import TraceInfo
from mlflow.environment_variables import MLFLOW_ENABLE_ASYNC_TRACE_LOGGING
from mlflow.tracing.export.mlflow_v3 import MlflowV3SpanExporter... | 76 | 2,863 |
mlflow | mlflow/tracing/export/mlflow_v3.py | .py | import logging
import os
import threading
from collections import defaultdict
from contextlib import nullcontext
from typing import Sequence
from opentelemetry.sdk.trace import ReadableSpan
from opentelemetry.sdk.trace.export import SpanExporter
from mlflow.entities.model_registry import PromptVersion
from mlflow.ent... | 425 | 19,908 |
mlflow | mlflow/tracing/export/genai_semconv/converter.py | .py | """
Abstract base class for format-specific message converters.
Each LLM provider stores inputs/outputs in its own format (e.g. OpenAI, Anthropic).
Converters translate these provider-specific formats into the GenAI Semantic Convention
attributes: gen_ai.input.messages, gen_ai.output.messages, request params, and resp... | 84 | 3,536 |
mlflow | mlflow/tracing/export/genai_semconv/translator.py | .py | """
Core translator for converting MLflow spans to OpenTelemetry GenAI Semantic Convention format.
Phase 1: Universal attributes (model, provider, tokens, span type) normalized across all
autologging integrations.
Phase 2: Format-specific message content (gen_ai.input.messages, gen_ai.output.messages),
request params,... | 223 | 8,446 |
mlflow | mlflow/tracing/display/__init__.py | .py | from mlflow.tracing.display.display_handler import (
IPythonTraceDisplayHandler,
get_notebook_iframe_html,
is_using_tracking_server,
)
__all__ = [
"IPythonTraceDisplayHandler",
"get_display_handler",
"is_using_tracking_server",
"get_notebook_iframe_html",
]
def get_display_handler() -> IP... | 41 | 1,265 |
mlflow | mlflow/tracing/display/display_handler.py | .py | import html
import json
import logging
from typing import TYPE_CHECKING
from urllib.parse import urlencode, urljoin
import mlflow
from mlflow.environment_variables import (
MLFLOW_MAX_TRACES_TO_DISPLAY_IN_NOTEBOOK,
MLFLOW_NOTEBOOK_TRACE_RENDERER_BASE_URL,
)
from mlflow.tracing.constant import TRACE_RENDERER_AS... | 213 | 7,242 |
mlflow | mlflow/tracing/distributed/__init__.py | .py | import logging
from contextlib import contextmanager
from opentelemetry.trace.propagation.tracecontext import TraceContextTextMapPropagator
import mlflow
from mlflow.entities.span import LiveSpan
from mlflow.telemetry.events import TracingContextPropagation
from mlflow.telemetry.track import record_usage_event
from m... | 191 | 7,442 |
mlflow | mlflow/tracing/otel/otel_archival.py | .py | """
Helpers for serializing archived trace spans as OTLP ``TracesData`` protobuf.
"""
from __future__ import annotations
from typing import Any
from google.protobuf.message import DecodeError
from opentelemetry.proto.trace.v1.trace_pb2 import TracesData
from mlflow.entities.span import Span
from mlflow.exceptions i... | 133 | 5,008 |
mlflow | mlflow/tracing/otel/translation/langfuse.py | .py | """
Translation utilities for Langfuse observation attributes.
Maps ``langfuse.observation.*`` attributes to MLflow span semantics so that
spans forwarded from Langfuse via the generic OTEL processor are stored with
correct span types, inputs, and outputs.
"""
from mlflow.entities.span import SpanType
from mlflow.tra... | 30 | 965 |
mlflow | mlflow/tracing/otel/translation/gemini_cli.py | .py | """
Translator for Gemini CLI OTEL spans.
Gemini CLI (google-gemini/gemini-cli) emits OTLP traces using `gen_ai.operation.name`
for span kind (same key as the GenAI semantic conventions), but with its own operation
names that don't match the standard GenAI values. This translator maps those
Gemini-specific names to M... | 157 | 6,446 |
mlflow | mlflow/tracing/otel/translation/genai_semconv.py | .py | """
Translation utilities for GenAI (Generic AI) semantic conventions.
Reference: https://opentelemetry.io/docs/specs/semconv/registry/attributes/gen-ai/
"""
import json
from typing import Any
from mlflow.entities.span import SpanType
from mlflow.tracing.otel.translation.base import OtelSchemaTranslator
class GenA... | 133 | 5,079 |
mlflow | mlflow/tracing/otel/translation/livekit.py | .py | """
Translation utilities for LiveKit Agents semantic conventions.
LiveKit Agents (Python SDK) provides real-time AI voice agents with built-in
OpenTelemetry support. This translator maps LiveKit's span attributes to MLflow's
semantic conventions for optimal visualization.
Reference:
- https://docs.livekit.io/agents/... | 117 | 3,770 |
mlflow | mlflow/tracing/otel/translation/__init__.py | .py | """
Utilities for translating OTEL span attributes to MLflow span format.
This module provides functions to translate span attributes from various
OTEL semantic conventions (OpenInference, Traceloop, GenAI) to MLflow span types.
It uses modular translator classes for each OTEL schema for better organization
and perfor... | 487 | 17,665 |
mlflow | mlflow/tracing/otel/translation/laminar.py | .py | from typing import Any
from mlflow.entities.span import SpanType
from mlflow.tracing.otel.translation.base import OtelSchemaTranslator
class LaminarTranslator(OtelSchemaTranslator):
SPAN_KIND_ATTRIBUTE_KEY = "lmnr.span.type"
SPAN_KIND_TO_MLFLOW_TYPE = {
"LLM": SpanType.LLM,
"TOOL": SpanType.... | 39 | 1,224 |
mlflow | mlflow/tracing/otel/translation/traceloop.py | .py | """
Translation utilities for Traceloop/OpenLLMetry semantic conventions.
Reference: https://github.com/traceloop/openllmetry/
"""
import re
from typing import Any
from mlflow.entities.span import SpanType
from mlflow.tracing.otel.translation.base import OtelSchemaTranslator
class TraceloopTranslator(OtelSchemaTra... | 83 | 3,733 |
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