input string | label int64 | category string | sample_id string |
|---|---|---|---|
_screenshot(self, page, **kwargs) -> str:
"""
Take a screenshot of the current page.
Args:
page (Page): The Playwright page object
kwargs: Additional keyword arguments
Returns:
str: The base64-encoded screenshot data
"""
need_scroll =... | 1 | function_simple | unclecode/crawl4ai:crawl4ai/async_crawler_strategy.back.py:AsyncPlaywrightCrawlerStrategy.take_screenshot |
({file_size} bytes)')
# Get file extension for file_type
file_ext = path.suffix.lower().lstrip('.')
# Call direct callbacks first (for click handlers waiting for downloads)
complete_info = {
'guid': guid,
'url': str(path),
'path': str(path),
'file_name': path.name,
'file_size... | 0 | function_complex | browser-use/browser-use:browser_use/browser/watchdogs/downloads_watchdog.py:DownloadsWatchdog._track_download |
_table(self):
"""Create table with vector column if it doesn't exist."""
try:
# Create table with vector stored as list<float> and payload as text (JSON)
query = f"""
CREATE TABLE IF NOT EXISTS {self.keyspace}.{self.collection_name} (
id text P... | 1 | function_simple | mem0ai/mem0:mem0/vector_stores/cassandra.py:CassandraDB._create_table |
_state()
assert isinstance(state, dict)
assert "rl_module" in state
# check that a new env runner can be updated based on an older state
new_runner = env_runner_cls(config=env_runner_config)
try:
# Check the states are not identical
new_state = new_runne... | 0 | test | ray-project/ray:rllib/env/tests/test_env_runner.py:TestEnvRunnerStateManagement.test_get_state_returns_dict |
config to a directory."""
if os.path.isfile(save_directory):
raise AssertionError(f"Provided path ({save_directory}) should be a directory, not a file")
os.makedirs(save_directory, exist_ok=True)
output_path = os.path.join(save_directory, self.config_name)
self.to_json_file... | 1 | function_simple | huggingface/diffusers:src/diffusers/modular_pipelines/mellon_node_utils.py:MellonPipelineConfig.save |
_logger.log_value("simple", 1)
root_logger.log_value("simple", 2)
time.sleep(0.1)
end_time = time.perf_counter()
throughput = 3 / (end_time - start_time)
# Get compiled results
compiled = root_logger.compile()
# Check that values and throughputs are correctly combined
check(compiled[... | 0 | test | ray-project/ray:rllib/utils/metrics/tests/test_metrics_logger.py:test_compile |
format to Gemini function declaration format."""
gemini_tools = []
from crewai.llms.providers.utils.common import safe_tool_conversion
for tool in tools:
name, description, parameters = safe_tool_conversion(tool, "Gemini")
function_declaration = types.FunctionDeclarat... | 0 | function_simple | crewAIInc/crewAI:lib/crewai/src/crewai/llms/providers/gemini/completion.py:GeminiCompletion._convert_tools_for_interference |
Args:
pixel_values: Input pixel values of shape (batch, channels, height, width)
Returns:
Visual embeddings
"""
vit_embeds = self.vision_model(pixel_values=pixel_values)
h = w = int(vit_embeds.shape[1] ** 0.5)
vit_embeds = vit_embeds.reshape(vit_embed... | 1 | function_simple | vllm-project/vllm:vllm/model_executor/models/eagle2_5_vl.py:Eagle2_5_VLForConditionalGeneration.extract_feature |
<html><body>
<div id="unicode">日本語 中文 한국어 العربية 🎉 💻 🚀</div>
<div id="special">& < > " '</div>
</body></html>
"""
async with AsyncWebCrawler() as crawler:
config = CrawlerRunConfig(js_code="document.getElementById('unicode').innerText += ' ✅ Modified'")
... | 1 | test | unclecode/crawl4ai:tests/test_raw_html_edge_cases.py:test_raw_html_with_unicode |
els_should_override_global_labels(self):
"""Test that component-specific labels take precedence over global labels with the same key."""
docs = render_chart(
values={
"airflowVersion": self.AIRFLOW_VERSION,
"labels": {"common_label": "global_value"},
... | 1 | test | apache/airflow:helm-tests/tests/helm_tests/dagprocessor/test_labels_service_account.py:TestDagProcessorServiceAccount.test_component_specific_labels_should_override_global_labels |
("transferOperations/123", IndexError),
("transferOperations/123-", ("123-", "")),
("-transferJobs-job456", IndexError),
("transferOperations/123-transferJobs", ("123-transferJobs", "transferJobs")),
]
for operation_name, expected in test_cases:
... | 1 | test | apache/airflow:providers/google/tests/unit/google/cloud/links/test_cloud_storage_transfer.py:TestCloudStorageTransferLinkHelper.test_extract_parts_with_malformed_operation_names |
test_retrieval_generic_exception_mapping(monkeypatch):
module = _load_dify_retrieval_module(monkeypatch)
_set_request_json(monkeypatch, module, {"knowledge_id": "kb-1", "query": "hello"})
monkeypatch.setattr(module.DocMetadataService, "get_meta_by_kbs", lambda _kb_ids: [])
monkeypatch.setattr(module.Kn... | 1 | test | infiniflow/ragflow:test/testcases/test_http_api/test_dataset_management/test_dify_retrieval_routes_unit.py:test_retrieval_generic_exception_mapping |
"""Test the _search_destination_node method."""
# Mock embedding
mock_embedding = [0.1, 0.2, 0.3]
# Mock the _search_destination_node_cypher method
mock_cypher = "MATCH (n) RETURN n"
mock_params = {"destination_embedding": mock_embedding, "user_id": self.user_id, "threshold": 0... | 1 | test | mem0ai/mem0:tests/memory/test_neptune_memory.py:TestNeptuneMemory.test_search_destination_node |
A decorator that executes the given function in a parallel loop.
"""
def decorator(body):
flat_carries, carry_tree = jax.tree.flatten(carry)
def wrapped(idx, *carries):
if carry is None:
body(idx)
return []
result = body(idx, carry_tree.unflatten(carries))
result, res... | 1 | function_complex | jax-ml/jax:jax/_src/pallas/mosaic/sc_primitives.py:parallel_loop |
/test_main.py": {
"content": [],
"created_at": "2025-01-01T00:00:00",
"modified_at": "2025-01-01T00:00:00",
},
},
}
result = middleware._handle_glob_search(
pattern="**/*.py", path="/", state=state
... | 1 | test | langchain-ai/langchain:libs/partners/anthropic/tests/unit_tests/middleware/test_file_search.py:TestGlobSearch.test_glob_recursive_pattern |
'SessionRegistry', params: dict[str, Any]) -> Any:
"""Handle session management command."""
if action == 'sessions':
sessions = registry.list_sessions()
return {
'sessions': sessions,
'count': len(sessions),
}
elif action == 'close':
if params.get('all'):
# Close all sessions and signal shutdown
... | 0 | function_simple | browser-use/browser-use:browser_use/skill_cli/commands/session.py:handle |
dbo_enabled():
# If DBO is being used, register the hook with the ubatch
# context and call it in dbo_maybe_run_recv_hook instead of
# passing it to the receiver.
dbo_register_recv_hook(hook)
dbo_yield()
... | 1 | function_complex | vllm-project/vllm:vllm/model_executor/layers/fused_moe/modular_kernel.py:FusedMoEModularKernel._prepare |
."""
# Poll for result instead of blocking on thread join
start_time = time.time()
while time.time() - start_time < self.timeout:
if OAuthCallbackHandler.callback_result or OAuthCallbackHandler.callback_error:
break
time.sleep(0.1)
# Signa... | 1 | function_complex | xtekky/gpt4free:g4f/Provider/needs_auth/Antigravity.py:OAuthCallbackServer.wait_for_callback |
text", "value": message["content"]}],
"loss_weight": 1.0 if message["role"] == "assistant" else 0.0,
}
)
return messages
sample = {}
sample["chosen_messages"] = process_message(raw_sample.get("chosen", []))
sample["rejected_messages"] = p... | 1 | function_complex | hiyouga/LlamaFactory:src/llamafactory/v1/plugins/data_plugins/converter.py:pair_converter |
DPOINT": "https://models.inference.ai.azure.com"
}):
# Test DeepSeek model
llm_deepseek = LLM(model="azure/deepseek-chat")
# Endpoint should not be modified for non-OpenAI endpoints
assert llm_deepseek.endpoint == "https://models.inference.ai.azure.com"
assert llm_deepseek.i... | 0 | test | crewAIInc/crewAI:lib/crewai/tests/llms/azure/test_azure.py:test_azure_deepseek_model_support |
shadow_elements.append((idx, element))
# Iframe content elements have IDs starting with "iframe-"
elif elem_id.startswith('iframe-'):
iframe_content_elements.append((idx, element))
# Everything else is regular DOM
else:
regular_elements.append((idx, element))
# Elements without IDs are ... | 0 | test | browser-use/browser-use:tests/ci/browser/test_dom_serializer.py:TestDOMSerializer.test_dom_serializer_with_shadow_dom_and_iframes |
formatted_links.append(
f"{i + 1}. {link.get('text', 'No text')}: {link.get('href', 'No href')}"
)
result = (
"\n".join(formatted_links)
if formatted_links
else "No hyperlinks found on the page"
)
... | 1 | function_simple | run-llama/llama_index:llama-index-integrations/tools/llama-index-tools-aws-bedrock-agentcore/llama_index/tools/aws_bedrock_agentcore/browser/base.py:AgentCoreBrowserToolSpec.extract_hyperlinks |
with mock.patch(
"langextract.providers.gemini.GeminiLanguageModel.infer",
return_value=iter([[mock.Mock(output='{"extractions": []}')]]),
):
with mock.patch(
"langextract.annotation.Annotator.__init__", return_value=None
) as mock_annotator_init:
with... | 1 | test | google/langextract:tests/extract_schema_integration_test.py:ExtractSchemaIntegrationTest.test_extract_explicit_fence_respected |
logger.warning(f"HTTP port out of range: {port}")
elif self._protocol == RequestProtocol.GRPC:
if not (
RAY_SERVE_DIRECT_INGRESS_MIN_GRPC_PORT
<= port
<= RAY_SERVE_DIRECT_INGRESS_MAX_GRPC_PORT
):
logger.warning(f"GRPC ... | 0 | function_complex | ray-project/ray:python/ray/serve/_private/node_port_manager.py:PortAllocator.update_port_if_missing |
Create a client for submitting and interacting with jobs on a remote cluster.
:param address: Either (1) the address of the Ray cluster, or (2) the HTTP address
of the dashboard server on the head node, e.g. "http://<head-node-ip>:8265".
In case (1) it must be specified as an a... | 1 | function_simple | apache/airflow:providers/google/src/airflow/providers/google/cloud/hooks/ray.py:RayJobHook.get_client |
originals = defaultdict(dict)
try:
# Replace all torch funcs by the ones in this file
for module_name in TORCH_MODULES_TO_PATCH:
if module_name in sys.modules:
module = sys.modules[module_name]
for func_name in TORCH_INIT_FUNCTIONS.keys():
... | 0 | function_complex | huggingface/transformers:src/transformers/initialization.py:guard_torch_init_functions |
ml_marker_split_at_fullwidth_pipe(self):
"""The fullwidth pipe character ｜ might be its own token."""
# This is a realistic tokenization: the DSML marker is split at the ｜ chars
model_tokens = [
"Let me help.\n\n",
"<\uff5c", # start of ｜DSML｜
"DSML\uff5c", ... | 0 | test | exo-explore/exo:src/exo/worker/tests/unittests/test_runner/test_dsml_e2e.py:TestE2EEdgeCases.test_dsml_marker_split_at_fullwidth_pipe |
False,
)
except asyncio.TimeoutError:
return (
None,
f"MCP discovery timed out after {MCP_DISCOVERY_TIMEOUT} seconds",
True,
)
except Exception as e:
error_str = str(e).lower()
if "authenticat... | 0 | function_complex | crewAIInc/crewAI:lib/crewai/src/crewai/mcp/tool_resolver.py:MCPToolResolver._attempt_mcp_discovery |
pixels²
Returns:
The input image if valid
Raises:
ValueError: If image is too small or aspect ratio is too extreme
"""
if not isinstance(image, PIL.Image.Image):
raise ValueError(f"Image must be a PIL.Image.Image, got {type(image)}")
width,... | 1 | function_simple | huggingface/diffusers:src/diffusers/pipelines/flux2/image_processor.py:Flux2ImageProcessor.check_image_input |
int_range = IntegerRangeField()
bigint_range = BigIntegerRangeField()
decimal_range = DecimalRangeField()
datetime_range = DateTimeRangeField()
date_range = DateRangeField()
expected_errors = [
self._make_error(field, field.__class__.__name__)
... | 1 | test | django/django:tests/postgres_tests/test_app_installed_check.py:TestPostgresAppInstalledCheck.test_range_fields |
used when generating samples with a pre-trained model. If used, `timesteps`
must be `None`.
device (`str` or `torch.device`, *optional*):
The device to which the timesteps should be moved to. If `None`, the timesteps are not moved.
timesteps (`list[int]`, *optional*):
... | 1 | function_complex | huggingface/diffusers:src/diffusers/pipelines/flux/pipeline_flux_kontext_inpaint.py:retrieve_timesteps |
_version = "1.0.6rc3"
repo_root = "/repo/root"
confirm_prompts: list[str] = []
def fake_confirm_action(prompt: str, **_kwargs) -> bool:
confirm_prompts.append(prompt)
return False
def should_not_be_called(*_args, **_kwargs):
raise AssertionError("This should not have been call... | 1 | test | apache/airflow:dev/breeze/tests/test_release_candidate_command.py:test_remove_old_releases_returns_early_when_user_declines |
"""Delete a file from the local storage.
Args:
flow_id: The identifier for the flow.
file_name: The name of the file to be deleted.
Raises:
FileNotFoundError: If the file does not exist.
"""
file_path = self.data_dir / flow_id / file_name
... | 1 | function_simple | langflow-ai/langflow:src/lfx/src/lfx/services/storage/local.py:LocalStorageService.delete_file |
4#file-reproducer-py
"""
path = Path(__file__).parent.parent.parent / "fixtures/audioflamingo3/expected_results_batched.json"
with open(path, "r", encoding="utf-8") as f:
raw = json.load(f)
exp_ids = torch.tensor(raw["token_ids"])
exp_txt = raw["transcriptions"]
... | 0 | test | huggingface/transformers:tests/models/audioflamingo3/test_modeling_audioflamingo3.py:AudioFlamingo3ForConditionalGenerationIntegrationTest.test_fixture_batched_matches |
ages = AnthropicMessageSerializer._clean_cache_messages(normal_messages)
# Verify only the last cache=True message remains cached
assert not cleaned_messages[0].cache # First user message should be uncached
assert not cleaned_messages[1].cache # First assistant message should be uncached
assert not cleaned_m... | 0 | test | browser-use/browser-use:browser_use/llm/tests/test_anthropic_cache.py:TestAnthropicCache.test_cache_cleaning_last_message_only |
.
"""
sentry.add_tagging(dag_run=dag_run, task_instance=task_instance)
assert mock_sentry_sdk.configure_scope.mock_calls == [
mock.call.__call__(),
mock.call.__call__().__enter__(),
mock.call.__call__().__enter__().set_tag("task_id", TASK_ID),
mock... | 1 | test | apache/airflow:task-sdk/tests/task_sdk/execution_time/test_sentry.py:TestSentryHook.test_add_tagging |
batched_messages,
tokenize=True,
add_generation_prompt=True,
return_dict=True,
return_tensors="pt",
padding=True,
).to(torch_device)
# This model on the hub has `do_sample=True`.
torch.manual_seed(42)
# it should not matte... | 0 | test | huggingface/transformers:tests/models/glm4v/test_modeling_glm4v.py:Glm4vIntegrationTest.test_small_model_integration_test_batch_wo_image_flashatt2 |
ard for a given rank, without re-loading the model."""
model_dir = {
"base": "base_checkpoints",
"sft": "chatsft_checkpoints",
"rl": "chatrl_checkpoints",
}[source]
base_dir = get_base_dir()
checkpoints_dir = os.path.join(base_dir, model_dir)
if model_tag is None:
mod... | 0 | function_simple | karpathy/nanochat:nanochat/checkpoint_manager.py:load_optimizer_state |
Discrete token indices from the VQVAE codebook.
Returns:
special_image_mask (`torch.LongTensor` of shape `(batch_size, seq_len)`):
Mask indicating positions in input ids that will be replaced by actual image tokens.
"""
special_image_mask = input_id... | 0 | function_simple | huggingface/transformers:src/transformers/models/glm_image/modular_glm_image.py:GlmImageModel.get_placeholder_mask |
.object(
AlibabaCloudMySQLVectorStore, "_check_vector_support"
) as mock_check:
with patch.object(
AlibabaCloudMySQLVectorStore, "_create_table_if_not_exists"
) as mock_create_table:
with patch.object(AlibabaCloudMySQLVectorStore, "_connect"):
store = ... | 1 | test | run-llama/llama_index:llama-index-integrations/vector_stores/llama-index-vector-stores-alibabacloud-mysql/tests/test_alibabacloud_mysql.py:test_initialize_without_setup |
_run=args.dry_run)
_create_group_membership_mapper(client, client_uuid, _dry_run=args.dry_run)
_create_permissions(client, client_uuid, teams=[team], include_global_admin=False, _dry_run=args.dry_run)
_ensure_group(client, team, _dry_run=args.dry_run)
_ensure_team_policies(client, client_uuid, team, _dr... | 1 | function_simple | apache/airflow:providers/keycloak/src/airflow/providers/keycloak/auth_manager/cli/commands.py:create_team_command |
= None
) -> bool:
"""Check if the given remote job variable file path is a valid file."""
if remote_job_var_file_path:
sftp_client = ssh_client.open_sftp()
try:
# Get file metadata
file_stat = sftp_client.stat(remote_job_var_file_path)
if file_stat.st_mode:
... | 1 | function_complex | apache/airflow:providers/teradata/src/airflow/providers/teradata/utils/tpt_util.py:is_valid_remote_job_var_file |
args.session}" is running')
return 0
else:
print(f'Server for session "{args.session}" is not running')
return 1
elif args.server_command == 'stop':
if not is_server_running(args.session):
print(f'Server for session "{args.session}" is not running')
return 0
response = send_command(args.session, ... | 0 | function_complex | browser-use/browser-use:browser_use/skill_cli/main.py:handle_server_command |
_dim_size
v_norm = v_norm_sq.sqrt()
second_momentum_buffer.lerp_(v_mean.to(dtype=second_momentum_buffer.dtype), 1 - beta2)
step_size = second_momentum_buffer.clamp_min(1e-10).rsqrt()
scaled_sq_sum = (v_mean * red_dim_size) * step_size.float().square()
v_norm_new = scaled_sq_sum.sum(dim=(-2, -1), kee... | 0 | function_complex | karpathy/nanochat:nanochat/optim.py:muon_step_fused |
num_image_tokens = sum(1 for token_id in inputs["input_ids"][0] if token_id == self.image_token_id)
# Verify we have image tokens (the bug caused 0 tokens)
self.assertGreater(num_image_tokens, 0, "Single-tile image with use_thumbnail=False should have image tokens")
# Verify the numbe... | 0 | test | huggingface/transformers:tests/models/lfm2_vl/test_processing_lfm2_vl.py:Lfm2VlProcessorTest.test_single_tile_image_with_thumbnail_disabled |
)
mock_output1 = TaskOutput(
description="Test task for AI",
raw="Result about AI",
agent="Test Agent",
)
mock_output2 = TaskOutput(
description="Test task for ML",
raw="Result about ML",
agent="Test Agent",
)
... | 0 | test | crewAIInc/crewAI:lib/crewai/tests/crew/test_async_crew.py:TestAsyncCrewKickoffForEach.test_akickoff_for_each_basic |
goal="Complete a simple task",
backstory="You are a test agent.",
llm=openai_llm # Use same instance
)
task = Task(
description="Say hello world",
expected_output="Hello world",
agent=agent,
)
crew = Crew(agents=[agent... | 0 | test | crewAIInc/crewAI:lib/crewai/tests/llms/openai/test_openai.py:test_openai_completion_call_arguments |
"""
if isinstance(self.running_average, torch.Tensor):
shape = tuple(self.running_average.shape)
# Calculate statistics
with torch.no_grad():
stats = {
"mean": self.running_average.mean().item(),
"std": self.runnin... | 1 | function_simple | huggingface/diffusers:src/diffusers/guiders/adaptive_projected_guidance_mix.py:MomentumBuffer.__repr__ |
tmp_path}/test_grayscale_image.png"
image = image.convert("L")
image.save(image_path)
# Convert to gray RGB for comparison
image = image.convert("RGB")
video_path = f"{tmp_path}/test_RGB_video.{ext}"
create_video_from_image(
image_path,
video_path,
num_fra... | 1 | test | vllm-project/vllm:tests/multimodal/media/test_video.py:test_opencv_video_io_colorspace |
command_receiver=co_rx,
is_candidate=True,
)
async with create_task_group() as tg:
with fail_after(2):
tg.start_soon(election.run)
# Send any connection message object; we close quickly to cancel before result creation
await cm_tx.send(ConnectionMessag... | 0 | test | exo-explore/exo:src/exo/shared/tests/test_election.py:test_connection_message_triggers_new_round_broadcast |
apply_router_weight_on_input: bool,
quant_config: FusedMoEQuantConfig,
defer_input_quant: bool = False,
) -> mk.PrepareResultType:
"""
Returns a tuple of:
- quantized + dispatched a.
- Optional quantized + dispatched a1_scales.
- Optional ExpertTokensMetada... | 1 | function_simple | vllm-project/vllm:vllm/model_executor/layers/fused_moe/mori_prepare_finalize.py:MoriPrepareAndFinalize.prepare |
and setup
with a single TPU worker.
"""
actor_name = "test_tpu_single_host"
verify_actor = VerificationActor.options(name=actor_name).remote()
trainer = JaxTrainer(
train_loop_per_worker=train_func,
scaling_config=ScalingConfig(
use_tpu=True,
num_workers=1,
... | 0 | test | ray-project/ray:python/ray/train/v2/tests/test_jax_trainer.py:test_tpu_single_host |
.models.FieldCondition(
key=filter_by,
match=self.qdrant_package.http.models.MatchValue(
value=filter_value
),
)
)
query_vector = (
self.custom_embedding_fn(query)
if self.cus... | 0 | function_complex | crewAIInc/crewAI:lib/crewai-tools/src/crewai_tools/tools/qdrant_vector_search_tool/qdrant_search_tool.py:QdrantVectorSearchTool._run |
_model(
self, state: AgentState[Any], runtime: Runtime[Any]
) -> dict[str, Any] | None: # type: ignore[override]
"""Async version of before_model.
Args:
state: Current agent state containing messages.
runtime: Agent runtime context.
Returns:
Upd... | 1 | function_simple | langchain-ai/langchain:libs/partners/openai/langchain_openai/middleware/openai_moderation.py:OpenAIModerationMiddleware.abefore_model |
_ref_bundler_basic(target, in_bundles, expected_bundles):
# Test that the bundler creates the expected output bundles.
bundler = BlockRefBundler(target)
bundles = _make_ref_bundles(in_bundles)
out_bundles = []
for bundle in bundles:
bundler.add_bundle(bundle)
while bundler.has_bundle... | 0 | test | ray-project/ray:python/ray/data/tests/test_block_ref_bundler.py:test_block_ref_bundler_basic |
message: The raw message received for the unknown task
exc: The exception raised when trying to process the unknown task
**kwargs: Additional context information from Celery
"""
logger.info(
f"Unknown task detected by Celery. Name: {name}, ID: {id}, Exc: {str(ex... | 0 | function_simple | ray-project/ray:python/ray/serve/task_processor.py:CeleryTaskProcessorAdapter._handle_unknown_task |
."""
step_num = step.number if step.number is not None else '?'
memory = step.memory or ''
if verbose:
url = step.url or ''
actions = step.actions or []
# Truncate URL for display
short_url = url[:60] + '...' if len(url) > 60 else url
print(f' [{step_num}] {short_url}')
if memory:
# Truncate memor... | 0 | function_complex | browser-use/browser-use:browser_use/skill_cli/commands/cloud_task.py:_print_step |
test_arun_pipeline() -> None:
pipeline = RayIngestionPipeline(
readers=[
ReaderConfig(
reader=StringIterableReader(),
reader_kwargs={"texts": ["This is a test."]},
)
],
documents=[Document.example()],
transformations=[... | 1 | test | run-llama/llama_index:llama-index-integrations/ingestion/llama-index-ingestion-ray/tests/test_pipeline.py:test_arun_pipeline |
data = {
"name": "Flow to Update",
"data": {},
}
flow_response = await client.post("api/v1/flows/", json=flow_data, headers=logged_in_headers)
assert flow_response.status_code == status.HTTP_201_CREATED
flow_id = flow_response.json()["id"]
# Now try to update the flow with a non-exi... | 1 | test | langflow-ai/langflow:src/backend/tests/unit/api/v1/test_flow_folder_integrity.py:test_update_flow_with_nonexistent_folder_id_assigns_default_folder |
None,
sender_name: str | None = None,
session_id: str | UUID | None = None,
context_id: str | UUID | None = None,
order_by: str | None = "timestamp",
order: str | None = "DESC",
flow_id: UUID | None = None,
limit: int | None = None,
) -> list[Message]:
"""DEPRECATED - Retrieve messages ... | 1 | function_simple | langflow-ai/langflow:src/lfx/src/lfx/memory/stubs.py:get_messages |
chroma.return_value = mock_chroma_inst
mock_chroma_inst.aadd_documents = AsyncMock()
mock_meta.return_value = {"chunks": 5, "size": 100, "source_types": []}
mock_size.return_value = 100
file_name, file_content = sample_text_file
files_data = [(file_name, file_content.encode())]... | 1 | test | langflow-ai/langflow:src/backend/tests/unit/test_knowledge_bases_api.py:TestPerformIngestionTask.test_perform_ingestion_success |
name (str | None): Component name or pattern
collection (str | None): Optional collection to filter by
load_id (str | None): Optional load_id to filter by
Returns:
A single component
Raises:
ValueError: If no components match or multiple components mat... | 1 | function_complex | huggingface/diffusers:src/diffusers/modular_pipelines/components_manager.py:ComponentsManager.get_one |
Args:
tokens (`str` or `list[str]`): One or several token(s) to convert to token id(s).
Returns:
`int` or `list[int]`: The token id or list of token ids.
"""
if isinstance(tokens, str):
one_token = True
tokens = [tokens]
else:
... | 0 | function_simple | huggingface/transformers:src/transformers/tokenization_mistral_common.py:MistralCommonBackend.convert_tokens_to_ids |
agent_id: str, action: str, delegation_id: Optional[str] = None) -> bool:
"""Validate if an agent can perform an action under their delegation"""
if delegation_id:
delegation = self.delegations.get(delegation_id)
if not delegation:
return False
... | 0 | function_complex | Shubhamsaboo/awesome-llm-apps:advanced_ai_agents/multi_agent_apps/multi_agent_trust_layer/multi_agent_trust_layer.py:DelegationManager.validate_action |
int = 96, min_len: int = 5, max_len: int = 100):
"""Create a mock Ray dataset with random text and labels."""
numbers = random.choices(range(min_len, max_len + 1), k=dataset_size)
ray_dataset = ray.data.from_items(numbers)
def map_to_text_and_label(item):
length = item['item']
text = r... | 0 | function_simple | ray-project/ray:doc/source/train/doc_code/random_text_generator.py:create_mock_ray_text_dataset |
if not self.test_attention_slicing:
return
components = self.get_dummy_components()
pipe = self.pipeline_class(**components)
for component in pipe.components.values():
if hasattr(component, "set_default_attn_processor"):
component.set_default_attn_proce... | 1 | test | huggingface/diffusers:tests/pipelines/qwenimage/test_qwenimage_img2img.py:QwenImageImg2ImgPipelineFastTests.test_attention_slicing_forward_pass |
def test_foreign_key_exists_case_sensitive(self, mock_inspect):
"""Test case sensitivity of foreign key name matching."""
mock_inspector = Mock()
mock_inspector.get_foreign_keys.return_value = [{"name": "FK_User_ID", "constrained_columns": ["user_id"]}]
mock_inspect.return_value = mock_i... | 1 | test | langflow-ai/langflow:src/backend/tests/unit/utils/test_migration.py:TestForeignKeyExists.test_foreign_key_exists_case_sensitive |
2-5
start_time = time.time()
print(f'🎯 URL Search: {url}')
print(f"🔍 Looking for: '{query}'")
print(f'📊 Navigation depth: {depth}')
print(f'💰 Estimated cost: {depth}¢')
payload = {'url': url, 'query': query, 'depth': depth}
timeout = aiohttp.ClientTimeout(total=TIMEOUT)
connector = aiohttp.TCPConnector... | 0 | function_simple | browser-use/browser-use:examples/cloud/05_search_api.py:search_url |
for i in range(0, len(query_embeddings), batch_size):
batch_scores: list[torch.Tensor] = []
batch_queries = torch.nn.utils.rnn.pad_sequence(
query_embeddings[i : i + batch_size], batch_first=True, padding_value=0
)
for j in range(0, len(passage_embeddi... | 0 | function_complex | huggingface/transformers:src/transformers/models/colmodernvbert/modular_colmodernvbert.py:ColModernVBertProcessor.score_retrieval |
delegator_identity = self._known_identities.get(delegation.delegator)
if not delegator_identity:
return False
delegation_data = json.dumps(
{
"delegator": delegation.delegator,
"delegatee": delegation.delegatee,
... | 1 | function_complex | run-llama/llama_index:llama-index-integrations/agent/llama-index-agent-agentmesh/llama_index/agent/agentmesh/trust.py:DelegationChain.verify |
from crewai.events.event_bus import crewai_event_bus
from crewai.events.types.flow_events import FlowInputReceivedEvent
events_captured: list[FlowInputReceivedEvent] = []
class MetadataProvider:
def request_input(
self, message: str, flow: Flow[Any], metadata: di... | 0 | test | crewAIInc/crewAI:lib/crewai/tests/test_flow_ask.py:TestAskMetadata.test_ask_metadata_in_received_event |
llm=llm,
prompt=_prompt,
callbacks=callbacks,
**(llm_chain_kwargs or {}),
)
document_prompt = PromptTemplate(
input_variables=["page_content"],
template="Context:\n{page_content}",
)
combine_documents_chain = StuffDocumen... | 1 | function_simple | langchain-ai/langchain:libs/langchain/langchain_classic/chains/retrieval_qa/base.py:BaseRetrievalQA.from_llm |
def test_lt(runner: CliRunner, root_dir: Path, copy_test_files):
result = runner.invoke(
cli,
["fix-pages", "docs/lang/docs/doc.md"],
)
# assert result.exit_code == 1, result.output
fixed_content = (root_dir / "docs" / "lang" / "docs" / "doc.md").read_text("utf-8")
expected_content ... | 1 | test | fastapi/fastapi:scripts/tests/test_translation_fixer/test_markdown_links/test_mkd_links_number_mismatch.py:test_lt |
"""Generate a new CMVK identity with Ed25519 key pair."""
seed = f"{agent_name}:{time.time_ns()}"
did_hash = hashlib.sha256(seed.encode()).hexdigest()[:32]
did = f"did:cmvk:{did_hash}"
private_key_obj = ed25519.Ed25519PrivateKey.generate()
public_key_obj = private_key_obj.pu... | 1 | function_simple | run-llama/llama_index:llama-index-integrations/agent/llama-index-agent-agentmesh/llama_index/agent/agentmesh/identity.py:CMVKIdentity.generate |
1k(self, WebApiAuth, add_document):
chunks_num = 1_000
_, doc_id = add_document
chunk_ids = batch_add_chunks(WebApiAuth, doc_id, chunks_num)
from time import sleep
sleep(1)
res = delete_chunks(WebApiAuth, {"doc_id": doc_id, "chunk_ids": chunk_ids})
assert res["... | 1 | test | infiniflow/ragflow:test/testcases/test_web_api/test_chunk_app/test_rm_chunks.py:TestChunksDeletion.test_delete_1k |
or transport manager for the given tensor transport protocol.
Args:
transport_name: The tensor transport protocol to use for the GPU object.
Returns:
TensorTransportManager: The tensor transport manager for the given tensor transport protocol.
"""
global transport_manager_info
glob... | 0 | function_simple | ray-project/ray:python/ray/experimental/gpu_object_manager/util.py:get_tensor_transport_manager |
--------
Assert that typing did not trigger a rerun or open the clear-cache dialog:
>>> expect_global_hotkeys_not_fired(app, expected_runs=1)
"""
# Rerun hotkey: must not start a script run while we're typing.
expect(app.get_by_test_id("stApp")).to_have_attribute(
"data-test-script-st... | 1 | function_simple | streamlit/streamlit:e2e_playwright/shared/input_utils.py:expect_global_hotkeys_not_fired |
bar(
themed_app: Page, assert_snapshot: ImageCompareFunction
) -> None:
select_subtest(themed_app, "large_logo_w_sidebar_subtest")
expect(themed_app.get_by_test_id("stSidebar")).to_be_visible()
expect(themed_app.get_by_test_id("stSidebarHeader")).to_be_visible()
expect(themed_app.get_by_test_id("st... | 1 | test | streamlit/streamlit:e2e_playwright/st_logo_test.py:test_large_logo_w_sidebar |
# to expiration
now = datetime.now(timezone.utc)
created_at = datetime.fromisoformat(credential_json["created_at"])
expires_in: int = credential_json["expires_in"]
renew_at = created_at + timedelta(seconds=expires_in // 2)
if now <= renew_at:
# cached/current creden... | 1 | function_complex | infiniflow/ragflow:common/data_source/confluence_connector.py:OnyxConfluence._renew_credentials |
httpx.Request("GET", "https://api.example.com/1"),
httpx.Request("POST", "https://api.example.com/2"),
httpx.Request("PUT", "https://api.example.com/3"),
]
for req in requests:
transport.handle_request(req)
# Verify all... | 0 | test | crewAIInc/crewAI:lib/crewai/tests/llms/hooks/test_transport.py:TestTransportIntegration.test_multiple_requests_same_interceptor |
colors = [
self._ensure_visible_color(
raw_colors[i] if i < len(raw_colors) else None,
self.DEFAULT_COLORS[i % len(self.DEFAULT_COLORS)]
)
for i in range(len(labels))
]
# 计算角度
theta... | 1 | function_complex | 666ghj/BettaFish:ReportEngine/renderers/chart_to_svg.py:ChartToSVGConverter._render_polarArea |
ResolverParsingError: If the content within the string cannot be parsed.
ValueError: If the input is invalid or does not contain expected format.
"""
if not input_string or not isinstance(input_string, str):
logging.error("Input string must be a non-empty string.")
raise ValueError("In... | 1 | function_simple | google/langextract:langextract/resolver.py:Resolver.string_to_extraction_data |
':
return ChatOpenAI # type: ignore
elif name == 'ChatAzureOpenAI':
return ChatAzureOpenAI # type: ignore
elif name == 'ChatGoogle':
return ChatGoogle # type: ignore
elif name == 'ChatMistral':
return ChatMistral # type: ignore
elif name == 'ChatOCIRaw':
if not OCI_AVAILABLE:
raise ImportError('O... | 0 | function_complex | browser-use/browser-use:browser_use/llm/models.py:__getattr__ |
as tmpdir:
with open(os.path.join(tmpdir, "build.sh"), "w") as f:
f.write("echo hello")
ctx = make_build_context(
base_dir=tmpdir,
envs={"ZZZ": "last", "AAA": "first"},
post_build_script="build.sh",
)
encoded = encode_build_context(ctx)
... | 0 | test | ray-project/ray:release/ray_release/tests/test_byod_build_context.py:test_encode_build_context |
(
self,
init_overrides: Optional[Dict[str, Any]] = None,
) -> "StatsBase":
"""Returns a new stats object with the same settings as `self`.
Args:
init_overrides: Optional dict of initialization arguments to override. Can be used to change is_root, is_leaf, etc.
R... | 0 | function_simple | ray-project/ray:rllib/utils/metrics/stats/base.py:StatsBase.clone |
: # noqa: S110
pass
crew._task_output_handler.reset()
crew._logging_color = "bold_purple"
# Check for flow input files in baggage context (inherited from parent Flow)
_flow_files = baggage.get_baggage("flow_input_files")
flow_files: dict[str, Any] = _flow_files if isinstance(_flow_fil... | 0 | function_complex | crewAIInc/crewAI:lib/crewai/src/crewai/crews/utils.py:prepare_kickoff |
are included in completion params when set
"""
from crewai.llms.providers.azure.completion import AzureCompletion
with patch.dict(os.environ, {
"AZURE_API_KEY": "test-key",
"AZURE_ENDPOINT": "https://models.inference.ai.azure.com"
}):
llm = LLM(
model="azure/gpt-4",... | 0 | test | crewAIInc/crewAI:lib/crewai/tests/llms/azure/test_azure.py:test_azure_complete_params_include_optional_params |
_labels(self):
"""Test that component-specific labels take precedence over global labels with the same key."""
docs = render_chart(
values={
"statsd": {
"enabled": True,
"labels": {"common_label": "component_value"},
},
... | 1 | test | apache/airflow:helm-tests/tests/helm_tests/statsd/test_labels_deployment.py:TestStatsdDeployment.test_component_specific_labels_should_override_global_labels |
text for wrapping long sentences in english language"
wrapped_text_en, text_height_en = vd.wrap_text(
text=test_text_en,
max_width=300,
font=font_path,
fontsize=30
)
print(wrapped_text_en, text_height_en)
... | 0 | test | harry0703/MoneyPrinterTurbo:test/services/test_video.py:TestVideoService.test_wrap_text |
generation step. Tuple of `torch.FloatTensor` with up to `max_new_tokens` elements (one element for
each generated token), with each tensor of shape `(batch_size, config.vocab_size)`.
attentions (`tuple(tuple(torch.FloatTensor))`, *optional*, returned when `output_attentions=True`):
Tuple (one elem... | 0 | documentation | huggingface/transformers:src/transformers/models/parakeet/modular_parakeet.py:ParakeetGenerateOutput:class_doc |
available_skills)} available skills from API')
# Determine which skills to load
if use_wildcard:
logger.info('Wildcard "*" detected, loading first 100 skills')
skills_to_load = all_available_skills
else:
# Load only the requested skill IDs
skills_to_load = [skill for skill in all_available_ski... | 0 | function_complex | browser-use/browser-use:browser_use/skills/service.py:SkillService.async_init |
text_str = text_val if isinstance(text_val, str) else ("" if text_val is None else str(text_val))
marks_raw = run.get("marks") if isinstance(run.get("marks"), list) else []
marks_filtered: List[Dict[str, Any]] = []
for mark in marks_raw:
... | 1 | function_complex | 666ghj/BettaFish:ReportEngine/nodes/chapter_generation_node.py:ChapterGenerationNode._sanitize_engine_quote_block |
labels (`torch.LongTensor` of shape `(batch_size, sequence_length)`, *optional*):
Labels for computing the masked language modeling loss. Indices should either be in `[0, ...,
config.vocab_size]` or -100 (see `input_ids` docstring). Tokens with indices set to `-100` are ignored
... | 0 | function_simple | huggingface/transformers:src/transformers/models/lfm2_vl/modular_lfm2_vl.py:Lfm2VlForConditionalGeneration.forward |
np.zeros((height, width, 3)),
size=(size["longest_edge"], size["longest_edge"]),
patch_size=patch_size,
)
num_height_tokens = resized_height // self.effective_patch_size
num_width_tokens = resized_width // self.effective_p... | 0 | function_complex | huggingface/transformers:src/transformers/models/lighton_ocr/modular_lighton_ocr.py:LightOnOcrProcessor._get_num_multimodal_tokens |
"release-management",
"prepare-task-sdk-distributions",
"--distribution-format",
"both",
],
cwd=str(self.airflow_repo_root),
check=False,
capture_output=True,
text=True,
)
if result.returncode !... | 1 | function_complex | apache/airflow:dev/breeze/src/airflow_breeze/utils/airflow_release_validator.py:AirflowReleaseValidator.build_packages |
await get_and_cache_all_types_dict(settings_service)
# Check if component type exists in the cache
if (
component_cache.all_types_dict
and "components" in component_cache.all_types_dict
and component_type in component_cache.all_types_dict["components"]
):
# If in lazy mod... | 1 | function_complex | langflow-ai/langflow:src/lfx/src/lfx/interface/components.py:get_type_dict |
return_value=mock_embedding_func,
):
config = {
"embedding_model": {
"provider": "cohere",
"config": {
"model": "embed-english-v3.0",
"api_key": "test-cohere-key",
},
}
}
t... | 0 | test | crewAIInc/crewAI:lib/crewai-tools/tests/tools/test_txt_search_tool_config.py:test_txt_search_tool_with_cohere_config |
_when_valid_keys_exist(self):
"""'default' is skipped in favor of a real match."""
config_keys = [
"default",
"intermediate_4096_numtokens_32",
"intermediate_4096_numtokens_128",
]
input_tensor = torch.randn(64, 8192, dtype=torch.bfloat16, device="cuda... | 1 | test | vllm-project/vllm:tests/kernels/helion/test_silu_mul_fp8.py:TestSiluMulFp8ConfigPicker.test_config_picker_default_ignored_when_valid_keys_exist |
self.logits_indices[:q_len].zero_()
self.output_ids[:q_len].zero_()
# Reset the attributes that are either tensors or dict of tensors
for layer_type in self.cumulative_seqlens_k:
self.max_seqlen_k[layer_type] = 0
if self.attention_mask is not None:
... | 0 | function_simple | huggingface/transformers:src/transformers/generation/continuous_batching/input_outputs.py:ContinuousBatchingIOs._reset_static_tensors |
vector_store: VolcengineMySQLVectorStore, embed_model: ArkEmbedding, question: str
) -> None:
"""Demonstrate async query capabilities."""
print(f"\n=== Async Similarity search for: {question!r} ===")
query_embedding = await embed_model.aget_query_embedding(question)
vs_query = VectorStoreQuery(
... | 1 | function_complex | run-llama/llama_index:llama-index-integrations/vector_stores/llama-index-vector-stores-volcenginemysql/examples/volcengine_mysql_vector_store_demo.py:run_async_query_demo |
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