sample_id stringlengths 21 196 | text stringlengths 105 936k | metadata dict | category stringclasses 6
values |
|---|---|---|---|
mlflow/mlflow:mlflow/genai/judges/tools/get_traces_in_session.py | """
Get traces in session tool for MLflow GenAI judges.
This module provides a tool for retrieving traces from the same session
to enable multi-turn evaluation capabilities.
"""
from mlflow.entities.trace import Trace
from mlflow.exceptions import MlflowException
from mlflow.genai.judges.tools.base import JudgeTool
f... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/genai/judges/tools/get_traces_in_session.py",
"license": "Apache License 2.0",
"lines": 97,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mlflow/mlflow:mlflow/genai/judges/tools/search_traces.py | """
Search traces tool for MLflow GenAI judges.
This module provides a tool for searching and retrieving traces from an MLflow experiment
based on filter criteria, ordering, and result limits. It enables judges to analyze
traces within the same experiment context.
"""
import logging
import mlflow
from mlflow.entitie... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/genai/judges/tools/search_traces.py",
"license": "Apache License 2.0",
"lines": 242,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mlflow/mlflow:tests/genai/judges/test_judge_tool_get_traces_in_session.py | from unittest.mock import MagicMock, patch
import pytest
from mlflow.entities.trace import Trace, TraceData
from mlflow.entities.trace_info import TraceInfo as MlflowTraceInfo
from mlflow.entities.trace_location import TraceLocation
from mlflow.entities.trace_state import TraceState
from mlflow.exceptions import Mlfl... | {
"repo_id": "mlflow/mlflow",
"file_path": "tests/genai/judges/test_judge_tool_get_traces_in_session.py",
"license": "Apache License 2.0",
"lines": 130,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:tests/genai/judges/test_judge_tool_search_traces.py | from unittest import mock
import pytest
from mlflow.entities.assessment import Expectation, Feedback
from mlflow.entities.assessment_error import AssessmentError
from mlflow.entities.assessment_source import AssessmentSource, AssessmentSourceType
from mlflow.entities.span import Span
from mlflow.entities.trace import... | {
"repo_id": "mlflow/mlflow",
"file_path": "tests/genai/judges/test_judge_tool_search_traces.py",
"license": "Apache License 2.0",
"lines": 370,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:tests/tracing/test_otel_loading.py | import uuid
from pathlib import Path
import pytest
from opentelemetry import trace as otel_trace
from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
from opentelemetry.sdk.resources import Resource as OTelSDKResource
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.s... | {
"repo_id": "mlflow/mlflow",
"file_path": "tests/tracing/test_otel_loading.py",
"license": "Apache License 2.0",
"lines": 449,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:tests/genai/scorers/test_scorer_description.py | from unittest.mock import patch
import pytest
from mlflow.genai import scorer
from mlflow.genai.judges import make_judge
from mlflow.genai.judges.instructions_judge import InstructionsJudge
from mlflow.genai.scorers import RelevanceToQuery
@pytest.fixture(autouse=True)
def mock_databricks_runtime():
with patch(... | {
"repo_id": "mlflow/mlflow",
"file_path": "tests/genai/scorers/test_scorer_description.py",
"license": "Apache License 2.0",
"lines": 115,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:tests/pytorch/test_forecasting_model.py | import os
import numpy as np
import pytest
import torch
from lightning.pytorch import Trainer
from pytorch_forecasting import DeepAR, TimeSeriesDataSet
from pytorch_forecasting.data.examples import generate_ar_data
import mlflow
@pytest.fixture
def model_path(tmp_path):
return os.path.join(tmp_path, "model")
... | {
"repo_id": "mlflow/mlflow",
"file_path": "tests/pytorch/test_forecasting_model.py",
"license": "Apache License 2.0",
"lines": 53,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:mlflow/tracing/databricks.py | from mlflow.exceptions import MlflowException
from mlflow.utils.annotations import experimental
from mlflow.utils.uri import is_databricks_uri
@experimental(version="3.5.0")
def set_databricks_monitoring_sql_warehouse_id(
sql_warehouse_id: str, experiment_id: str | None = None
) -> None:
"""
Set the SQL w... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/tracing/databricks.py",
"license": "Apache License 2.0",
"lines": 37,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mlflow/mlflow:tests/tracing/test_databricks.py | from unittest import mock
import pytest
from mlflow.exceptions import MlflowException
from mlflow.tracing.databricks import set_databricks_monitoring_sql_warehouse_id
def test_set_databricks_monitoring_sql_warehouse_id_requires_databricks_tracking_uri():
with mock.patch("mlflow.get_tracking_uri", return_value="... | {
"repo_id": "mlflow/mlflow",
"file_path": "tests/tracing/test_databricks.py",
"license": "Apache License 2.0",
"lines": 43,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:mlflow/genai/judges/prompts/equivalence.py | from mlflow.genai.prompts.utils import format_prompt
# NB: User-facing name for the equivalence assessment.
EQUIVALENCE_FEEDBACK_NAME = "equivalence"
EQUIVALENCE_PROMPT_INSTRUCTIONS = """\
Compare the following actual output against the expected output. You must determine whether they \
are semantically equivalent o... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/genai/judges/prompts/equivalence.py",
"license": "Apache License 2.0",
"lines": 34,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | documentation |
mlflow/mlflow:mlflow/genai/optimize/optimize.py | import logging
import uuid
from concurrent.futures import ThreadPoolExecutor
from contextlib import nullcontext
from typing import TYPE_CHECKING, Any, Callable
import mlflow
from mlflow.entities import Trace
from mlflow.entities.evaluation_dataset import EvaluationDataset as EntityEvaluationDataset
from mlflow.entitie... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/genai/optimize/optimize.py",
"license": "Apache License 2.0",
"lines": 296,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mlflow/mlflow:mlflow/genai/optimize/optimizers/base.py | from abc import ABC, abstractmethod
from typing import Any, Callable
from mlflow.genai.optimize.types import EvaluationResultRecord, PromptOptimizerOutput
from mlflow.utils.annotations import experimental
# The evaluation function that takes candidate prompts as a dict
# (prompt template name -> prompt template) and ... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/genai/optimize/optimizers/base.py",
"license": "Apache License 2.0",
"lines": 34,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | documentation |
mlflow/mlflow:tests/genai/optimize/test_optimize.py | from typing import Any
import pandas as pd
import pytest
import mlflow
from mlflow.entities.model_registry import PromptModelConfig
from mlflow.exceptions import MlflowException
from mlflow.genai.datasets import create_dataset
from mlflow.genai.optimize.optimize import optimize_prompts
from mlflow.genai.optimize.opti... | {
"repo_id": "mlflow/mlflow",
"file_path": "tests/genai/optimize/test_optimize.py",
"license": "Apache License 2.0",
"lines": 398,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:mlflow/tracing/utils/prompt.py | import json
from mlflow.entities.model_registry import PromptVersion
from mlflow.exceptions import MlflowException
from mlflow.tracing.constant import TraceTagKey
# TODO: Remove tag based linking once we migrate to LinkPromptsToTraces endpoint
def update_linked_prompts_tag(current_tag_value: str | None, prompt_versi... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/tracing/utils/prompt.py",
"license": "Apache License 2.0",
"lines": 38,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mlflow/mlflow:tests/tracing/utils/test_prompt.py | import json
import pytest
from mlflow.entities.model_registry import PromptVersion
from mlflow.exceptions import MlflowException
from mlflow.tracing.utils.prompt import update_linked_prompts_tag
def test_update_linked_prompts_tag():
pv1 = PromptVersion(name="test_prompt", version=1, template="Test template")
... | {
"repo_id": "mlflow/mlflow",
"file_path": "tests/tracing/utils/test_prompt.py",
"license": "Apache License 2.0",
"lines": 31,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:dev/clint/src/clint/rules/nested_mock_patch.py | import ast
from clint.resolver import Resolver
from clint.rules.base import Rule
class NestedMockPatch(Rule):
def _message(self) -> str:
return (
"Do not nest `unittest.mock.patch` context managers. "
"Use multiple context managers in a single `with` statement instead: "
... | {
"repo_id": "mlflow/mlflow",
"file_path": "dev/clint/src/clint/rules/nested_mock_patch.py",
"license": "Apache License 2.0",
"lines": 45,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mlflow/mlflow:dev/clint/tests/rules/test_nested_mock_patch.py | from pathlib import Path
from clint.config import Config
from clint.linter import Position, Range, lint_file
from clint.rules.nested_mock_patch import NestedMockPatch
def test_nested_mock_patch_unittest_mock(index_path: Path) -> None:
code = """
import unittest.mock
def test_foo():
with unittest.mock.patch(... | {
"repo_id": "mlflow/mlflow",
"file_path": "dev/clint/tests/rules/test_nested_mock_patch.py",
"license": "Apache License 2.0",
"lines": 161,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:mlflow/cli/scorers.py | import json
from typing import Literal
import click
from mlflow.environment_variables import MLFLOW_EXPERIMENT_ID
from mlflow.genai.judges import make_judge
from mlflow.genai.scorers import get_all_scorers
from mlflow.genai.scorers import list_scorers as list_scorers_api
from mlflow.mcp.decorator import mlflow_mcp
fr... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/cli/scorers.py",
"license": "Apache License 2.0",
"lines": 168,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mlflow/mlflow:tests/cli/test_scorers.py | import json
from typing import Any
from unittest.mock import patch
import pytest
from click.testing import CliRunner
import mlflow
from mlflow.cli.scorers import commands
from mlflow.exceptions import MlflowException
from mlflow.genai.scorers import get_all_scorers, list_scorers, scorer
from mlflow.utils.string_utils... | {
"repo_id": "mlflow/mlflow",
"file_path": "tests/cli/test_scorers.py",
"license": "Apache License 2.0",
"lines": 503,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:dev/clint/src/clint/rules/mock_patch_dict_environ.py | import ast
from clint.resolver import Resolver
from clint.rules.base import Rule
class MockPatchDictEnviron(Rule):
def _message(self) -> str:
return (
"Do not use `mock.patch.dict` to modify `os.environ` in tests; "
"use pytest's monkeypatch fixture (monkeypatch.setenv / monkeypat... | {
"repo_id": "mlflow/mlflow",
"file_path": "dev/clint/src/clint/rules/mock_patch_dict_environ.py",
"license": "Apache License 2.0",
"lines": 36,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mlflow/mlflow:dev/clint/tests/rules/test_mock_patch_dict_environ.py | from pathlib import Path
from clint.config import Config
from clint.linter import Position, Range, lint_file
from clint.rules.mock_patch_dict_environ import MockPatchDictEnviron
def test_mock_patch_dict_environ_with_string_literal(index_path: Path) -> None:
code = """
import os
from unittest import mock
# Bad -... | {
"repo_id": "mlflow/mlflow",
"file_path": "dev/clint/tests/rules/test_mock_patch_dict_environ.py",
"license": "Apache License 2.0",
"lines": 110,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:dev/clint/src/clint/rules/mock_patch_as_decorator.py | import ast
from clint.resolver import Resolver
from clint.rules.base import Rule
class MockPatchAsDecorator(Rule):
def _message(self) -> str:
return (
"Do not use `unittest.mock.patch` as a decorator. "
"Use it as a context manager to avoid patches being active longer than needed ... | {
"repo_id": "mlflow/mlflow",
"file_path": "dev/clint/src/clint/rules/mock_patch_as_decorator.py",
"license": "Apache License 2.0",
"lines": 23,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mlflow/mlflow:dev/clint/tests/rules/test_mock_patch_as_decorator.py | from pathlib import Path
from clint.config import Config
from clint.linter import Position, Range, lint_file
from clint.rules.mock_patch_as_decorator import MockPatchAsDecorator
def test_mock_patch_as_decorator_unittest_mock(index_path: Path) -> None:
code = """
import unittest.mock
@unittest.mock.patch("foo.ba... | {
"repo_id": "mlflow/mlflow",
"file_path": "dev/clint/tests/rules/test_mock_patch_as_decorator.py",
"license": "Apache License 2.0",
"lines": 86,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:mlflow/cli/eval.py | """
CLI commands for evaluating traces with scorers.
"""
import json
from typing import Literal
import click
import pandas as pd
import mlflow
from mlflow.cli.genai_eval_utils import (
extract_assessments_from_results,
format_table_output,
resolve_scorers,
)
from mlflow.entities import Trace
from mlflow.... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/cli/eval.py",
"license": "Apache License 2.0",
"lines": 106,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mlflow/mlflow:tests/cli/test_eval.py | import re
from unittest import mock
import click
import pandas as pd
import pytest
import mlflow
from mlflow.cli.eval import evaluate_traces
from mlflow.entities import Trace, TraceInfo
from mlflow.genai.scorers.base import scorer
def test_evaluate_traces_with_single_trace_table_output():
experiment_id = mlflow... | {
"repo_id": "mlflow/mlflow",
"file_path": "tests/cli/test_eval.py",
"license": "Apache License 2.0",
"lines": 185,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:tests/gateway/providers/test_traffic_route_provider.py | from typing import Any
import pytest
from mlflow.gateway.config import EndpointConfig
from mlflow.gateway.providers.base import TrafficRouteProvider
from tests.gateway.providers.test_openai import (
_run_test_chat,
_run_test_chat_stream,
_run_test_completions,
_run_test_completions_stream,
_run_t... | {
"repo_id": "mlflow/mlflow",
"file_path": "tests/gateway/providers/test_traffic_route_provider.py",
"license": "Apache License 2.0",
"lines": 60,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:mlflow/server/jobs/_job_subproc_entry.py | """
This module is used for launching subprocess to execute the job function.
If the job has timeout setting, or the job has pip requirements dependencies,
or the job has extra environment variables setting,
the job is executed as a subprocess.
"""
import importlib
import json
import logging
import os
import threadin... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/server/jobs/_job_subproc_entry.py",
"license": "Apache License 2.0",
"lines": 63,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mlflow/mlflow:mlflow/genai/optimize/optimizers/gepa_optimizer.py | import json
import logging
import tempfile
from pathlib import Path
from typing import TYPE_CHECKING, Any
import mlflow
from mlflow.exceptions import MlflowException
from mlflow.genai.optimize.optimizers.base import BasePromptOptimizer, _EvalFunc
from mlflow.genai.optimize.types import EvaluationResultRecord, PromptOp... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/genai/optimize/optimizers/gepa_optimizer.py",
"license": "Apache License 2.0",
"lines": 354,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mlflow/mlflow:tests/genai/optimize/optimizers/test_gepa_optimizer.py | import json
import sys
from pathlib import Path
from typing import Any
from unittest.mock import MagicMock, Mock, patch
import pytest
import mlflow
from mlflow.genai.optimize.optimizers.gepa_optimizer import GepaPromptOptimizer
from mlflow.genai.optimize.types import EvaluationResultRecord, PromptOptimizerOutput
@p... | {
"repo_id": "mlflow/mlflow",
"file_path": "tests/genai/optimize/optimizers/test_gepa_optimizer.py",
"license": "Apache License 2.0",
"lines": 560,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:mlflow/store/tracking/databricks_rest_store.py | import base64
import logging
from collections import defaultdict
from datetime import datetime
from typing import Any
from urllib.parse import quote, urlencode
from opentelemetry.proto.collector.trace.v1.trace_service_pb2 import ExportTraceServiceRequest
from pydantic import BaseModel
from mlflow.entities import Asse... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/store/tracking/databricks_rest_store.py",
"license": "Apache License 2.0",
"lines": 957,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mlflow/mlflow:mlflow/tracing/enablement.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.annotations import experimental
from mlflow.utils.uri import is_databricks... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/tracing/enablement.py",
"license": "Apache License 2.0",
"lines": 126,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | documentation |
mlflow/mlflow:mlflow/tracing/export/uc_table.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... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/tracing/export/uc_table.py",
"license": "Apache License 2.0",
"lines": 59,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mlflow/mlflow:mlflow/tracing/processor/uc_table.py | import logging
from opentelemetry.sdk.trace import ReadableSpan as OTelReadableSpan
from opentelemetry.sdk.trace import Span as OTelSpan
from opentelemetry.sdk.trace.export import SpanExporter
from mlflow.entities.trace_info import TraceInfo
from mlflow.entities.trace_location import TraceLocation, UCSchemaLocation, ... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/tracing/processor/uc_table.py",
"license": "Apache License 2.0",
"lines": 82,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mlflow/mlflow:mlflow/utils/databricks_tracing_utils.py | import logging
from google.protobuf.duration_pb2 import Duration
from google.protobuf.timestamp_pb2 import Timestamp
from mlflow.entities import Assessment, Span, Trace, TraceData, TraceInfo
from mlflow.entities.trace_info_v2 import _truncate_request_metadata, _truncate_tags
from mlflow.entities.trace_location import... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/utils/databricks_tracing_utils.py",
"license": "Apache License 2.0",
"lines": 246,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mlflow/mlflow:tests/store/tracking/test_databricks_rest_store.py | import base64
import json
import time
from unittest import mock
import pytest
from google.protobuf.json_format import MessageToDict
from opentelemetry.proto.trace.v1.trace_pb2 import Span as OTelProtoSpan
import mlflow
from mlflow.entities import Span
from mlflow.entities.assessment import (
AssessmentSource,
... | {
"repo_id": "mlflow/mlflow",
"file_path": "tests/store/tracking/test_databricks_rest_store.py",
"license": "Apache License 2.0",
"lines": 1709,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:tests/tracing/export/test_uc_table_exporter.py | import time
from concurrent.futures import ThreadPoolExecutor
from unittest import mock
import pytest
from mlflow.entities.span import Span
from mlflow.tracing.export.uc_table import DatabricksUCTableSpanExporter
from mlflow.tracing.trace_manager import InMemoryTraceManager
from mlflow.tracing.utils import generate_t... | {
"repo_id": "mlflow/mlflow",
"file_path": "tests/tracing/export/test_uc_table_exporter.py",
"license": "Apache License 2.0",
"lines": 214,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:tests/tracing/processor/test_uc_table_processor.py | from unittest import mock
import pytest
import mlflow
import mlflow.tracking.context.default_context
from mlflow.entities.span import LiveSpan
from mlflow.entities.trace_location import TraceLocationType, UCSchemaLocation
from mlflow.entities.trace_state import TraceState
from mlflow.environment_variables import MLFL... | {
"repo_id": "mlflow/mlflow",
"file_path": "tests/tracing/processor/test_uc_table_processor.py",
"license": "Apache License 2.0",
"lines": 138,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:tests/tracing/test_enablement.py | """
Tests for mlflow.tracing.enablement module
"""
from unittest import mock
import pytest
import mlflow
from mlflow.entities.trace_location import UCSchemaLocation
from mlflow.exceptions import MlflowException
from mlflow.tracing.enablement import (
set_experiment_trace_location,
unset_experiment_trace_loca... | {
"repo_id": "mlflow/mlflow",
"file_path": "tests/tracing/test_enablement.py",
"license": "Apache License 2.0",
"lines": 119,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:tests/utils/test_databricks_tracing_utils.py | import json
import pytest
from google.protobuf.timestamp_pb2 import Timestamp
import mlflow
from mlflow.entities import (
AssessmentSource,
Expectation,
Feedback,
Trace,
TraceData,
TraceInfo,
TraceState,
)
from mlflow.entities.trace_location import (
InferenceTableLocation,
MlflowE... | {
"repo_id": "mlflow/mlflow",
"file_path": "tests/utils/test_databricks_tracing_utils.py",
"license": "Apache License 2.0",
"lines": 440,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:dev/clint/src/clint/rules/redundant_test_docstring.py | """Rule to detect redundant docstrings in test functions and classes.
This rule flags ALL single-line docstrings in test functions and classes.
Single-line docstrings in tests rarely provide meaningful context and are
typically redundant. Multi-line docstrings are always allowed as they
generally provide meaningful co... | {
"repo_id": "mlflow/mlflow",
"file_path": "dev/clint/src/clint/rules/redundant_test_docstring.py",
"license": "Apache License 2.0",
"lines": 56,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mlflow/mlflow:dev/clint/tests/rules/test_redundant_test_docstring.py | from pathlib import Path
from clint.config import Config
from clint.linter import lint_file
from clint.rules.redundant_test_docstring import RedundantTestDocstring
def test_redundant_docstrings_are_flagged(index_path: Path) -> None:
code = '''
def test_feature_a():
"""
This test verifies that feature A w... | {
"repo_id": "mlflow/mlflow",
"file_path": "dev/clint/tests/rules/test_redundant_test_docstring.py",
"license": "Apache License 2.0",
"lines": 175,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:mlflow/server/fastapi_security.py | import logging
from http import HTTPStatus
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
from starlette.types import ASGIApp
from mlflow.environment_variables import (
MLFLOW_SERVER_DISABLE_SECURITY_MIDDLEWARE,
MLFLOW_SERVER_X_FRAME_OPTIONS,
)
from mlflow.server.security_utils... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/server/fastapi_security.py",
"license": "Apache License 2.0",
"lines": 151,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mlflow/mlflow:mlflow/server/security.py | import logging
from http import HTTPStatus
from flask import Flask, Response, request
from flask_cors import CORS
from mlflow.environment_variables import (
MLFLOW_SERVER_DISABLE_SECURITY_MIDDLEWARE,
MLFLOW_SERVER_X_FRAME_OPTIONS,
)
from mlflow.server.security_utils import (
CORS_BLOCKED_MSG,
HEALTH_E... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/server/security.py",
"license": "Apache License 2.0",
"lines": 91,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mlflow/mlflow:mlflow/server/security_utils.py | """
Shared security utilities for MLflow server middleware.
This module contains common functions used by both Flask and FastAPI
security implementations.
"""
import fnmatch
from urllib.parse import urlparse
from mlflow.environment_variables import (
MLFLOW_SERVER_ALLOWED_HOSTS,
MLFLOW_SERVER_CORS_ALLOWED_OR... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/server/security_utils.py",
"license": "Apache License 2.0",
"lines": 119,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mlflow/mlflow:tests/server/test_security.py | import pytest
from fastapi import FastAPI
from flask import Flask
from starlette.testclient import TestClient
from werkzeug.test import Client
from mlflow.server import security
from mlflow.server.fastapi_security import init_fastapi_security
from mlflow.server.security_utils import is_allowed_host_header, is_api_endp... | {
"repo_id": "mlflow/mlflow",
"file_path": "tests/server/test_security.py",
"license": "Apache License 2.0",
"lines": 266,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:tests/server/test_security_integration.py | import json
import pytest
from werkzeug.test import Client
@pytest.mark.parametrize(
("host", "origin", "expected_status", "should_block"),
[
("evil.attacker.com:5000", "http://evil.attacker.com:5000", 403, True),
("localhost:5000", None, None, False),
],
)
def test_dns_rebinding_and_cors... | {
"repo_id": "mlflow/mlflow",
"file_path": "tests/server/test_security_integration.py",
"license": "Apache License 2.0",
"lines": 100,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:mlflow/cli/genai_eval_utils.py | """
Utility functions for trace evaluation output formatting.
"""
from dataclasses import dataclass
from typing import Any
import click
import pandas as pd
from mlflow.exceptions import MlflowException
from mlflow.genai.scorers import Scorer, get_all_scorers, get_scorer
from mlflow.tracing.constant import Assessment... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/cli/genai_eval_utils.py",
"license": "Apache License 2.0",
"lines": 213,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mlflow/mlflow:tests/cli/test_genai_eval_utils.py | from unittest import mock
import click
import pandas as pd
import pytest
from mlflow.cli.genai_eval_utils import (
NA_VALUE,
Assessment,
EvalResult,
extract_assessments_from_results,
format_table_output,
resolve_scorers,
)
from mlflow.exceptions import MlflowException
from mlflow.tracing.const... | {
"repo_id": "mlflow/mlflow",
"file_path": "tests/cli/test_genai_eval_utils.py",
"license": "Apache License 2.0",
"lines": 405,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:tests/claude_code/test_autolog.py | import sys
from unittest.mock import MagicMock, patch
import pytest
from claude_agent_sdk.types import AssistantMessage, ResultMessage, TextBlock, UserMessage
import mlflow.anthropic
from mlflow.anthropic.autolog import patched_claude_sdk_init
def test_anthropic_autolog_without_claude_sdk():
sys.modules.pop("cl... | {
"repo_id": "mlflow/mlflow",
"file_path": "tests/claude_code/test_autolog.py",
"license": "Apache License 2.0",
"lines": 125,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:tests/server/jobs/test_utils.py | import os
import pytest
from mlflow.exceptions import MlflowException
from mlflow.server.jobs.utils import _load_function, _validate_function_parameters
pytestmark = pytest.mark.skipif(
os.name == "nt", reason="MLflow job execution is not supported on Windows"
)
def test_validate_function_parameters():
def... | {
"repo_id": "mlflow/mlflow",
"file_path": "tests/server/jobs/test_utils.py",
"license": "Apache License 2.0",
"lines": 96,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:examples/pytorch/HPOExample/hpo_mnist.py | """
Hyperparameter Optimization Example with Pure PyTorch and MLflow
This example demonstrates:
- Using MLflow to track hyperparameter optimization trials
- Parent/child run structure for organizing HPO experiments
- Pure PyTorch training (no Lightning dependencies)
- Simple MNIST classification with configurable hype... | {
"repo_id": "mlflow/mlflow",
"file_path": "examples/pytorch/HPOExample/hpo_mnist.py",
"license": "Apache License 2.0",
"lines": 126,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mlflow/mlflow:mlflow/server/jobs/_huey_consumer.py | """
This module is used for launching Huey consumer
the command is like:
```
export _MLFLOW_HUEY_STORAGE_PATH={huey_store_dir}
export _MLFLOW_HUEY_INSTANCE_KEY={huey_instance_key}
huey_consumer.py mlflow.server.jobs.huey_consumer.huey_instance -w {max_workers}
```
It launches the Huey consumer that polls tasks from ... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/server/jobs/_huey_consumer.py",
"license": "Apache License 2.0",
"lines": 31,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mlflow/mlflow:mlflow/server/jobs/_job_runner.py | """
This module is used for launching the job runner process.
The job runner will:
* enqueue all unfinished huey tasks when MLflow server is down last time.
* Watch the `_MLFLOW_HUEY_STORAGE_PATH` path,
if new files (named like `XXX.mlflow-huey-store`) are created,
it means a new Huey queue is created, then the jo... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/server/jobs/_job_runner.py",
"license": "Apache License 2.0",
"lines": 37,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mlflow/mlflow:tests/webhooks/test_delivery.py | from pathlib import Path
from unittest.mock import patch
import pytest
from mlflow.entities.webhook import Webhook, WebhookAction, WebhookEntity, WebhookEvent
from mlflow.store.model_registry.file_store import FileStore
from mlflow.store.model_registry.sqlalchemy_store import SqlAlchemyStore
from mlflow.webhooks.deli... | {
"repo_id": "mlflow/mlflow",
"file_path": "tests/webhooks/test_delivery.py",
"license": "Apache License 2.0",
"lines": 95,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:mlflow/genai/labeling/databricks_utils.py | """
Databricks utilities for MLflow GenAI labeling functionality.
"""
_ERROR_MSG = (
"The `databricks-agents` package is required to use labeling functionality. "
"Please install it with `pip install databricks-agents`."
)
def get_databricks_review_app(experiment_id: str | None = None):
"""Import databri... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/genai/labeling/databricks_utils.py",
"license": "Apache License 2.0",
"lines": 14,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mlflow/mlflow:mlflow/genai/labeling/stores.py | """
Labeling store functionality for MLflow GenAI.
This module provides store implementations to manage labeling sessions and schemas
"""
import warnings
from abc import ABCMeta, abstractmethod
from typing import TYPE_CHECKING, Any, Callable
from mlflow.entities import Trace
from mlflow.exceptions import MlflowExcep... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/genai/labeling/stores.py",
"license": "Apache License 2.0",
"lines": 409,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mlflow/mlflow:mlflow/genai/judges/tools/get_span_performance_and_timing_report.py | """
Get span timing report tool for MLflow traces.
This tool generates a timing report showing span latencies, execution order,
and concurrency patterns for performance analysis.
"""
from collections import defaultdict
from dataclasses import dataclass
from mlflow.entities.span import Span
from mlflow.entities.trace... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/genai/judges/tools/get_span_performance_and_timing_report.py",
"license": "Apache License 2.0",
"lines": 419,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mlflow/mlflow:tests/genai/judges/test_judge_tool_get_span_performance_and_timing_report.py | from mlflow.entities.span import Span
from mlflow.entities.trace import Trace
from mlflow.entities.trace_data import TraceData
from mlflow.entities.trace_info import TraceInfo
from mlflow.entities.trace_location import TraceLocation
from mlflow.entities.trace_state import TraceState
from mlflow.genai.judges.tools.get_s... | {
"repo_id": "mlflow/mlflow",
"file_path": "tests/genai/judges/test_judge_tool_get_span_performance_and_timing_report.py",
"license": "Apache License 2.0",
"lines": 728,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:tests/langchain/test_responses_agent_langchain.py | import json
from langchain_core.messages import AIMessage, HumanMessage, ToolMessage
from mlflow.types.responses import ResponsesAgentStreamEvent, output_to_responses_items_stream
def test_output_to_responses_items_stream_langchain():
"""
Tests langchain message stream to responses items stream conversion.
... | {
"repo_id": "mlflow/mlflow",
"file_path": "tests/langchain/test_responses_agent_langchain.py",
"license": "Apache License 2.0",
"lines": 395,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:mlflow/server/job_api.py | """
Internal job APIs for UI invocation
"""
import json
from typing import Any
from fastapi import APIRouter, HTTPException
from pydantic import BaseModel
from mlflow.entities._job import Job as JobEntity
from mlflow.entities._job_status import JobStatus
from mlflow.exceptions import MlflowException
job_api_router ... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/server/job_api.py",
"license": "Apache License 2.0",
"lines": 106,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mlflow/mlflow:dev/clint/src/clint/rules/isinstance_union_syntax.py | import ast
from clint.rules.base import Rule
class IsinstanceUnionSyntax(Rule):
def _message(self) -> str:
return (
"Use `isinstance(obj, (X, Y))` instead of `isinstance(obj, X | Y)`. "
"The union syntax with `|` is slower than using a tuple of types."
)
@staticmethod... | {
"repo_id": "mlflow/mlflow",
"file_path": "dev/clint/src/clint/rules/isinstance_union_syntax.py",
"license": "Apache License 2.0",
"lines": 44,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mlflow/mlflow:dev/clint/tests/rules/test_isinstance_union_syntax.py | from pathlib import Path
from clint.config import Config
from clint.linter import Position, Range, lint_file
from clint.rules import IsinstanceUnionSyntax
def test_isinstance_union_syntax(index_path: Path) -> None:
code = """
# Bad - basic union syntax
isinstance(obj, str | int)
isinstance(value, int | str | flo... | {
"repo_id": "mlflow/mlflow",
"file_path": "dev/clint/tests/rules/test_isinstance_union_syntax.py",
"license": "Apache License 2.0",
"lines": 34,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:mlflow/entities/_job.py | import json
from typing import Any
from mlflow.entities._job_status import JobStatus
from mlflow.entities._mlflow_object import _MlflowObject
from mlflow.utils.workspace_utils import resolve_entity_workspace_name
class Job(_MlflowObject):
"""
MLflow entity representing a Job.
"""
def __init__(
... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/entities/_job.py",
"license": "Apache License 2.0",
"lines": 98,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mlflow/mlflow:mlflow/entities/_job_status.py | from enum import Enum
from mlflow.exceptions import MlflowException
from mlflow.protos.jobs_pb2 import JobStatus as ProtoJobStatus
class JobStatus(str, Enum):
"""Enum for status of a Job."""
PENDING = "PENDING"
RUNNING = "RUNNING"
SUCCEEDED = "SUCCEEDED"
FAILED = "FAILED"
TIMEOUT = "TIMEOUT"... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/entities/_job_status.py",
"license": "Apache License 2.0",
"lines": 57,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mlflow/mlflow:mlflow/store/jobs/abstract_store.py | from abc import ABC, abstractmethod
from typing import Any, Iterator
from mlflow.entities._job import Job
from mlflow.entities._job_status import JobStatus
from mlflow.utils.annotations import developer_stable
@developer_stable
class AbstractJobStore(ABC):
"""
Abstract class that defines API interfaces for s... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/store/jobs/abstract_store.py",
"license": "Apache License 2.0",
"lines": 140,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | documentation |
mlflow/mlflow:mlflow/store/jobs/sqlalchemy_store.py | import json
import threading
import uuid
from typing import Any, Iterator
import sqlalchemy
from mlflow.entities._job import Job
from mlflow.entities._job_status import JobStatus
from mlflow.exceptions import MlflowException
from mlflow.protos.databricks_pb2 import RESOURCE_DOES_NOT_EXIST
from mlflow.store.db.utils i... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/store/jobs/sqlalchemy_store.py",
"license": "Apache License 2.0",
"lines": 337,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mlflow/mlflow:dev/check_init_py.py | """
Pre-commit hook to check for missing `__init__.py` files in mlflow and tests directories.
This script ensures that all directories under the mlflow package and tests directory that contain
Python files also have an `__init__.py` file. This prevents `setuptools` from excluding these
directories during package build... | {
"repo_id": "mlflow/mlflow",
"file_path": "dev/check_init_py.py",
"license": "Apache License 2.0",
"lines": 42,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mlflow/mlflow:tests/dev/test_check_init_py.py | import subprocess
import sys
from pathlib import Path
import pytest
def get_check_init_py_script() -> Path:
return Path(__file__).resolve().parents[2] / "dev" / "check_init_py.py"
@pytest.fixture
def temp_git_repo(tmp_path: Path) -> Path:
subprocess.check_call(["git", "init"], cwd=tmp_path)
subprocess.... | {
"repo_id": "mlflow/mlflow",
"file_path": "tests/dev/test_check_init_py.py",
"license": "Apache License 2.0",
"lines": 171,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:dev/clint/tests/test_index.py | from pathlib import Path
from unittest.mock import patch
from clint.index import SymbolIndex
def test_symbol_index_build_basic(tmp_path: Path) -> None:
mlflow_dir = tmp_path / "mlflow"
mlflow_dir.mkdir()
test_file = mlflow_dir / "test.py"
test_file.write_text("def test_function(): pass")
mock_g... | {
"repo_id": "mlflow/mlflow",
"file_path": "dev/clint/tests/test_index.py",
"license": "Apache License 2.0",
"lines": 31,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:dev/clint/src/clint/rules/temp_dir_in_test.py | import ast
from clint.resolver import Resolver
from clint.rules.base import Rule
class TempDirInTest(Rule):
def _message(self) -> str:
return "Do not use `tempfile.TemporaryDirectory` in test directly. Use `tmp_path` fixture (https://docs.pytest.org/en/stable/reference/reference.html#tmp-path)."
@st... | {
"repo_id": "mlflow/mlflow",
"file_path": "dev/clint/src/clint/rules/temp_dir_in_test.py",
"license": "Apache License 2.0",
"lines": 12,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:dev/clint/tests/rules/test_temp_dir_in_test.py | from pathlib import Path
from clint.config import Config
from clint.linter import Position, Range, lint_file
from clint.rules.temp_dir_in_test import TempDirInTest
def test_temp_dir_in_test(index_path: Path) -> None:
code = """
import tempfile
# Bad
def test_func():
tempfile.TemporaryDirectory()
# Good
def... | {
"repo_id": "mlflow/mlflow",
"file_path": "dev/clint/tests/rules/test_temp_dir_in_test.py",
"license": "Apache License 2.0",
"lines": 109,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:dev/clint/src/clint/rules/os_chdir_in_test.py | import ast
from clint.resolver import Resolver
from clint.rules.base import Rule
class OsChdirInTest(Rule):
def _message(self) -> str:
return "Do not use `os.chdir` in test directly. Use `monkeypatch.chdir` (https://docs.pytest.org/en/stable/reference/reference.html#pytest.MonkeyPatch.chdir)."
@stat... | {
"repo_id": "mlflow/mlflow",
"file_path": "dev/clint/src/clint/rules/os_chdir_in_test.py",
"license": "Apache License 2.0",
"lines": 12,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:dev/clint/tests/rules/test_os_chdir_in_test.py | from pathlib import Path
from clint.config import Config
from clint.linter import Position, Range, lint_file
from clint.rules.os_chdir_in_test import OsChdirInTest
def test_os_chdir_in_test(index_path: Path) -> None:
code = """
import os
# Bad
def test_func():
os.chdir("/tmp")
# Good
def non_test_func():
... | {
"repo_id": "mlflow/mlflow",
"file_path": "dev/clint/tests/rules/test_os_chdir_in_test.py",
"license": "Apache License 2.0",
"lines": 83,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:dev/clint/tests/test_resolve_paths.py | from __future__ import annotations
import subprocess
from pathlib import Path
from unittest.mock import patch
import pytest
from clint.utils import ALLOWED_EXTS, _git_ls_files, resolve_paths
@pytest.fixture
def git_repo(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> Path:
"""Create and initialize a git rep... | {
"repo_id": "mlflow/mlflow",
"file_path": "dev/clint/tests/test_resolve_paths.py",
"license": "Apache License 2.0",
"lines": 199,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:dev/clint/tests/test_config.py | import subprocess
from pathlib import Path
from typing import Generator
import pytest
from clint.config import Config
from clint.utils import get_repo_root
@pytest.fixture(autouse=True)
def clear_repo_root_cache() -> Generator[None, None, None]:
"""Clear the get_repo_root cache before each test to avoid cross-te... | {
"repo_id": "mlflow/mlflow",
"file_path": "dev/clint/tests/test_config.py",
"license": "Apache License 2.0",
"lines": 100,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:examples/haystack/tracing.py | import os
from getpass import getpass
from haystack import Pipeline
from haystack.components.builders import ChatPromptBuilder
from haystack.components.generators.chat import OpenAIChatGenerator
from haystack.components.retrievers.in_memory import InMemoryBM25Retriever
from haystack.components.routers import Condition... | {
"repo_id": "mlflow/mlflow",
"file_path": "examples/haystack/tracing.py",
"license": "Apache License 2.0",
"lines": 119,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mlflow/mlflow:mlflow/haystack/autolog.py | import json
import logging
import threading
from typing import Any
from haystack.tracing import OpenTelemetryTracer, enable_tracing
from opentelemetry import trace
from opentelemetry.context import Context
from opentelemetry.sdk.trace import ReadableSpan as OTelReadableSpan
from opentelemetry.sdk.trace import Span as ... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/haystack/autolog.py",
"license": "Apache License 2.0",
"lines": 206,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mlflow/mlflow:tests/haystack/test_haystack_tracing.py | from unittest.mock import patch
from haystack import Document, Pipeline, component
from haystack.components.rankers import LostInTheMiddleRanker
from haystack.components.retrievers import InMemoryBM25Retriever
from haystack.document_stores.in_memory import InMemoryDocumentStore
import mlflow
from mlflow.entities impo... | {
"repo_id": "mlflow/mlflow",
"file_path": "tests/haystack/test_haystack_tracing.py",
"license": "Apache License 2.0",
"lines": 163,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:dev/xtest_viz.py | # /// script
# dependencies = [
# "aiohttp",
# ]
# ///
"""
Script to visualize cross-version test results for MLflow autologging and models.
This script fetches scheduled workflow run results from GitHub Actions and generates
a markdown table showing the test status for different package versions across
different ... | {
"repo_id": "mlflow/mlflow",
"file_path": "dev/xtest_viz.py",
"license": "Apache License 2.0",
"lines": 281,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mlflow/mlflow:mlflow/genai/judges/base.py | from __future__ import annotations
from abc import ABC, abstractmethod
from typing import Any
from pydantic import BaseModel, Field
from mlflow.entities.trace import Trace
from mlflow.genai.judges.constants import (
_RATIONALE_FIELD_DESCRIPTION,
_RESULT_FIELD_DESCRIPTION,
)
from mlflow.genai.judges.utils imp... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/genai/judges/base.py",
"license": "Apache License 2.0",
"lines": 109,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | documentation |
mlflow/mlflow:mlflow/genai/judges/builtin_judges.py | from mlflow.genai.judges.base import Judge
from mlflow.genai.scorers.builtin_scorers import BuiltInScorer
from mlflow.utils.annotations import experimental
@experimental(version="3.4.0")
class BuiltinJudge(BuiltInScorer, Judge):
"""
Base class for built-in AI judge scorers that use LLMs for evaluation.
""... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/genai/judges/builtin_judges.py",
"license": "Apache License 2.0",
"lines": 8,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mlflow/mlflow:mlflow/genai/judges/constants.py | _DATABRICKS_DEFAULT_JUDGE_MODEL = "databricks"
_DATABRICKS_AGENTIC_JUDGE_MODEL = "gpt-oss-120b"
# Use case constants for chat completions
USE_CASE_BUILTIN_JUDGE = "builtin_judge"
USE_CASE_AGENTIC_JUDGE = "agentic_judge"
USE_CASE_CUSTOM_PROMPT_JUDGE = "custom_prompt_judge"
USE_CASE_JUDGE_ALIGNMENT = "judge_alignment"
... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/genai/judges/constants.py",
"license": "Apache License 2.0",
"lines": 101,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mlflow/mlflow:mlflow/genai/judges/instructions_judge/constants.py | """
Constants for the InstructionsJudge module.
This module contains constant values used by the InstructionsJudge class,
including the augmented prompt template for trace-based evaluation.
"""
# Common base prompt for all judge evaluations
JUDGE_BASE_PROMPT = """You are an expert judge tasked with evaluating the per... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/genai/judges/instructions_judge/constants.py",
"license": "Apache License 2.0",
"lines": 51,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | documentation |
mlflow/mlflow:mlflow/genai/judges/make_judge.py | from typing import Any, Literal, get_args, get_origin
from mlflow.genai.judges.base import Judge
from mlflow.genai.judges.instructions_judge import InstructionsJudge
from mlflow.telemetry.events import MakeJudgeEvent
from mlflow.telemetry.track import record_usage_event
from mlflow.utils.annotations import experimenta... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/genai/judges/make_judge.py",
"license": "Apache License 2.0",
"lines": 206,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | documentation |
mlflow/mlflow:mlflow/genai/judges/optimizers/dspy.py | """DSPy-based alignment optimizer implementation."""
import logging
from abc import abstractmethod
from typing import Any, Callable, ClassVar, Collection
from mlflow.entities.assessment import Feedback
from mlflow.entities.trace import Trace
from mlflow.exceptions import MlflowException
from mlflow.genai.judges impor... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/genai/judges/optimizers/dspy.py",
"license": "Apache License 2.0",
"lines": 212,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mlflow/mlflow:mlflow/genai/judges/optimizers/dspy_utils.py | """Utility functions for DSPy-based alignment optimizers."""
import logging
import os
from contextlib import contextmanager
from typing import TYPE_CHECKING, Any, Callable, Iterator, Optional
from mlflow import __version__ as VERSION
from mlflow.entities.assessment_source import AssessmentSourceType
from mlflow.entit... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/genai/judges/optimizers/dspy_utils.py",
"license": "Apache License 2.0",
"lines": 478,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mlflow/mlflow:mlflow/genai/judges/optimizers/simba.py | """SIMBA alignment optimizer implementation."""
import logging
from typing import TYPE_CHECKING, Any, Callable, ClassVar, Collection
from mlflow.genai.judges.optimizers.dspy import DSPyAlignmentOptimizer
from mlflow.genai.judges.optimizers.dspy_utils import (
_check_dspy_installed,
suppress_verbose_logging,
)... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/genai/judges/optimizers/simba.py",
"license": "Apache License 2.0",
"lines": 96,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | documentation |
mlflow/mlflow:mlflow/genai/judges/tools/base.py | """
Base classes for MLflow GenAI tools that can be used by judges.
This module provides the foundational interfaces for tools that judges can use
to enhance their evaluation capabilities.
"""
from abc import ABC, abstractmethod
from typing import Any
from mlflow.entities.trace import Trace
from mlflow.types.llm imp... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/genai/judges/tools/base.py",
"license": "Apache License 2.0",
"lines": 42,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | documentation |
mlflow/mlflow:mlflow/genai/judges/tools/constants.py | """
Constants for MLflow GenAI judge tools.
This module contains constant values used across the judge tools system,
providing a single reference point for tool names and other constants.
"""
from mlflow.utils.annotations import experimental
# Tool names
@experimental(version="3.4.0")
class ToolNames:
"""Regist... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/genai/judges/tools/constants.py",
"license": "Apache License 2.0",
"lines": 18,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mlflow/mlflow:mlflow/genai/judges/tools/get_root_span.py | """
Get root span tool for MLflow GenAI judges.
This module provides a tool for retrieving the root span of a trace,
which contains the top-level inputs and outputs.
"""
from mlflow.entities.trace import Trace
from mlflow.genai.judges.tools.base import JudgeTool
from mlflow.genai.judges.tools.constants import ToolNam... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/genai/judges/tools/get_root_span.py",
"license": "Apache License 2.0",
"lines": 97,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mlflow/mlflow:mlflow/genai/judges/tools/get_span.py | """
Get span tool for MLflow GenAI judges.
This module provides a tool for retrieving a specific span by ID.
"""
import json
from mlflow.entities.trace import Trace
from mlflow.genai.judges.tools.base import JudgeTool
from mlflow.genai.judges.tools.constants import ToolNames
from mlflow.genai.judges.tools.types impo... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/genai/judges/tools/get_span.py",
"license": "Apache License 2.0",
"lines": 118,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mlflow/mlflow:mlflow/genai/judges/tools/get_trace_info.py | """
Get trace info tool for MLflow GenAI judges.
This module provides a tool for retrieving trace metadata including
timing, location, state, and other high-level information.
"""
from mlflow.entities.trace import Trace
from mlflow.entities.trace_info import TraceInfo
from mlflow.genai.judges.tools.base import JudgeT... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/genai/judges/tools/get_trace_info.py",
"license": "Apache License 2.0",
"lines": 52,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mlflow/mlflow:mlflow/genai/judges/tools/list_spans.py | """
Tool definitions for MLflow GenAI judges.
This module provides concrete JudgeTool implementations that judges can use
to analyze traces and extract information during evaluation.
"""
from dataclasses import dataclass
from mlflow.entities.trace import Trace
from mlflow.genai.judges.tools.base import JudgeTool
fro... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/genai/judges/tools/list_spans.py",
"license": "Apache License 2.0",
"lines": 106,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mlflow/mlflow:mlflow/genai/judges/tools/registry.py | """
Tool registry for MLflow GenAI judges.
This module provides a registry system for managing and invoking JudgeTool instances.
"""
import json
import logging
from typing import Any
import mlflow
from mlflow.entities import SpanType, Trace
from mlflow.environment_variables import MLFLOW_GENAI_EVAL_ENABLE_SCORER_TRA... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/genai/judges/tools/registry.py",
"license": "Apache License 2.0",
"lines": 117,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mlflow/mlflow:mlflow/genai/judges/tools/search_trace_regex.py | """
Tool for searching traces using regex patterns.
This module provides functionality to search through entire traces (including
spans, metadata, tags, requests, and responses) using regular expressions
with case-insensitive matching.
"""
import re
from dataclasses import dataclass
from mlflow.entities.trace import... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/genai/judges/tools/search_trace_regex.py",
"license": "Apache License 2.0",
"lines": 148,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_complex |
mlflow/mlflow:mlflow/genai/judges/tools/types.py | """
Shared types for MLflow GenAI judge tools.
This module provides common data structures and types that can be reused
across multiple judge tools for consistent data representation.
"""
from dataclasses import dataclass
from typing import Any
from mlflow.entities.assessment import FeedbackValueType
from mlflow.ent... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/genai/judges/tools/types.py",
"license": "Apache License 2.0",
"lines": 70,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | function_simple |
mlflow/mlflow:mlflow/genai/judges/tools/utils.py | """
Utilities for MLflow GenAI judge tools.
This module contains utility functions and classes used across
different judge tool implementations.
"""
from mlflow.exceptions import MlflowException
from mlflow.protos.databricks_pb2 import INVALID_PARAMETER_VALUE
from mlflow.utils.annotations import experimental
@exper... | {
"repo_id": "mlflow/mlflow",
"file_path": "mlflow/genai/judges/tools/utils.py",
"license": "Apache License 2.0",
"lines": 38,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | documentation |
mlflow/mlflow:tests/genai/judges/optimizers/test_dspy_base.py | from typing import Any, Callable, Collection
from unittest.mock import MagicMock, Mock, patch
import dspy
import litellm
import pytest
from mlflow.entities.trace import Trace
from mlflow.exceptions import MlflowException
from mlflow.genai.judges import make_judge
from mlflow.genai.judges.optimizers.dspy import DSPyAl... | {
"repo_id": "mlflow/mlflow",
"file_path": "tests/genai/judges/optimizers/test_dspy_base.py",
"license": "Apache License 2.0",
"lines": 385,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:tests/genai/judges/optimizers/test_dspy_utils.py | from unittest.mock import MagicMock, Mock, patch
import dspy
import pytest
from mlflow.exceptions import MlflowException
from mlflow.genai.judges.base import JudgeField
from mlflow.genai.judges.optimizers.dspy_utils import (
AgentEvalLM,
agreement_metric,
append_input_fields_section,
construct_dspy_lm... | {
"repo_id": "mlflow/mlflow",
"file_path": "tests/genai/judges/optimizers/test_dspy_utils.py",
"license": "Apache License 2.0",
"lines": 380,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
mlflow/mlflow:tests/genai/judges/optimizers/test_simba.py | from importlib import reload
from unittest.mock import MagicMock, patch
import dspy
import pytest
from mlflow.exceptions import MlflowException
from mlflow.genai.judges.optimizers import SIMBAAlignmentOptimizer
def test_dspy_optimize_no_dspy():
# Since dspy import is now at module level, we need to test this di... | {
"repo_id": "mlflow/mlflow",
"file_path": "tests/genai/judges/optimizers/test_simba.py",
"license": "Apache License 2.0",
"lines": 91,
"canary_id": -1,
"canary_value": "",
"pii_type": "",
"provider": "",
"regex_pattern": "",
"repetition": -1,
"template": ""
} | test |
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