input string | label int64 | category string | sample_id string |
|---|---|---|---|
sampled_videos = []
sampled_metadata = []
for video, metadata in zip(videos, video_metadata):
indices = sample_indices_fn(metadata=metadata)
metadata.frames_indices = indices
sampled_videos.append(video[indices])
sampled_metadat... | 0 | function_complex | huggingface/transformers:src/transformers/video_processing_utils.py:BaseVideoProcessor._decode_and_sample_videos |
researcher: Agent, simple_task: Task
) -> None:
"""Test basic streaming example from documentation."""
crew = Crew(
agents=[researcher],
tasks=[simple_task],
stream=True,
verbose=False,
)
streaming = crew.kickoff(inputs={"topic": "art... | 0 | test | crewAIInc/crewAI:lib/crewai/tests/test_streaming_integration.py:TestStreamingCrewIntegration.test_basic_crew_streaming_from_docs |
"""
sync_queue: queue.Queue[StreamChunk | None | Exception] = queue.Queue()
async_queue: asyncio.Queue[StreamChunk | None | Exception] | None = None
loop: asyncio.AbstractEventLoop | None = None
if use_async:
async_queue = asyncio.Queue()
loop = asyncio.get_event_loop()
handler = ... | 0 | function_simple | crewAIInc/crewAI:lib/crewai/src/crewai/utilities/streaming.py:create_streaming_state |
sample_weight: Sample weights (currently unused).
training: Whether the model is in training mode.
Returns:
Combined loss tensor.
"""
# Handle case where y_pred is not provided
if y_pred is None:
y_pred = self(x, training=training)
# ... | 1 | function_complex | keras-team/keras:keras/src/distillation/distiller.py:Distiller.compute_loss |
class GangWithBundlesAndChild:
def test_second_worker_blocked(self):
"""The second child actor shouldn't fit in this replica's bundle slice."""
w1 = ChildActor.remote()
w2 = ChildActor.remote()
ready, _ = ray.wait([w2.get_pg.remote()], timeo... | 0 | test | ray-project/ray:python/ray/serve/tests/test_gang_scheduling.py:TestGangChildSpawnPlacementGroup.test_child_actor_gang_pg_bundles_bounded |
returncode=0, stdout="Command output", stderr=""
)
_pytest(Path(), {}, cov=False)
assert mock_subprocess.call_args[0][0] == [
"uv",
"run",
"--no-sync",
"--",
"pytest",
"-q",
"--disable-warnings",
"--disable-pytest-warnings",
]
mock_s... | 1 | test | run-llama/llama_index:llama-dev/tests/test/test_test.py:test__pytest |
# Shift to center of pixel
coords = boxes.view(*boxes.shape[:2], 2, 2)
# add padding point for consistency with the original implementation
coords = torch.nn.functional.pad(coords, (0, 0, 0, 1), mode="constant", value=0)
corner_embedding = self.shared_embedding(coords, (self.input_imag... | 0 | function_simple | huggingface/transformers:src/transformers/models/sam2/modular_sam2.py:Sam2PromptEncoder._embed_boxes |
ate per-model costs on-the-fly
total_model_cost = 0.0
model_prompt_cost = 0.0
model_completion_cost = 0.0
# Calculate costs for this model
for entry in self.usage_history:
if entry.model == model:
cost = await self.calculate_cost(entry.model, entry.usage)
if cost:
model_prom... | 0 | function_complex | browser-use/browser-use:browser_use/tokens/service.py:TokenCost.log_usage_summary |
video_hidden_state.shape[0], dtype=torch.long
)
if padding_mask is not None:
audio_lengths = padding_mask.sum(dim=-1)
else:
audio_lengths = audio_hidden_state.shape[1] * audio_hidden_state.new_ones(
audio_hidden_state.shape[0], dtype=torch... | 0 | function_complex | huggingface/transformers:src/transformers/models/pe_audio_video/modular_pe_audio_video.py:PeAudioVideoEncoderEmbedder._align_video_hidden_state |
ral_tokenizer_does_not_block_event_loop():
expected_tokens = [1, 2, 3]
# Mock the blocking version to sleep
def mocked_apply_chat_template(*_args, **_kwargs):
time.sleep(2)
return expected_tokens
mock_model_config = MockModelConfig(skip_tokenizer_init=True)
mock_tokenizer = Mock(sp... | 1 | test | vllm-project/vllm:tests/renderers/test_mistral.py:test_async_mistral_tokenizer_does_not_block_event_loop |
."""
if not isinstance(filter_obj, MetadataFilter):
raise ValueError(f"Expected MetadataFilter, got {type(filter_obj)}")
key = filter_obj.key
value = filter_obj.value
operator = filter_obj.operator
# Map LlamaIndex operators to S3 Vectors ope... | 1 | function_complex | run-llama/llama_index:llama-index-integrations/vector_stores/llama-index-vector-stores-s3/llama_index/vector_stores/s3/base.py:S3VectorStore._build_filter |
image1 = image2 = Image.new("1", size=(10, 20))
id = uuid.uuid4()
image1.getexif()[Image.ExifTags.Base.ImageID] = id
image2 = Image.open(ASSETS_DIR / "image1.png")
image2.getexif()[Image.ExifTags.Base.ImageID] = "Not a UUID"
image2a = Image.open(ASSETS_DIR / "image1.png")
hasher = MultiModal... | 1 | test | vllm-project/vllm:tests/multimodal/test_hasher.py:test_hash_image_exif_id |
None,
categories: list[str] | None = None,
older_than: datetime | None = None,
metadata_filter: dict[str, Any] | None = None,
record_ids: list[str] | None = None,
) -> int:
"""Delete memories matching criteria.
Returns:
Number of records deleted.
... | 0 | function_simple | crewAIInc/crewAI:lib/crewai/src/crewai/memory/unified_memory.py:Memory.forget |
A JSON string containing the extracted data.
"""
if not self.client:
raise ValueError(
"Tavily client is not initialized. Ensure 'tavily-python' is installed and API key is set."
)
return json.dumps(
self.client.extract(
... | 0 | function_simple | crewAIInc/crewAI:lib/crewai-tools/src/crewai_tools/tools/tavily_extractor_tool/tavily_extractor_tool.py:TavilyExtractorTool._run |
key_net_ver: Bip32KeyNetVersions) -> bool:
"""
Get if the key is public.
Args:
ser_key_bytes (bytes) : Serialized key bytes
key_net_ver (Bip32KeyNetVersions object): Key net versions
Returns:
bool: True if public, fa... | 1 | function_simple | ccxt/ccxt:python/ccxt/static_dependencies/bip/bip32/bip32_key_ser.py:Bip32KeyDeserializer.__GetIfPublic |
pt-oss-safeguard-20b") == "OpenAI"
assert discovery._get_provider_name("qwen/qwen3-32b") == "Alibaba Cloud"
assert discovery._get_provider_name("moonshotai/moonshot-v1") == "Moonshot AI"
assert discovery._get_provider_name("groq/groq-model") == "Groq"
# Models with prefixes
asse... | 1 | test | langflow-ai/langflow:src/backend/tests/unit/groq/test_groq_model_discovery.py:TestGroqModelDiscoverySuccess.test_provider_name_extraction |
�于 .env 配置并融合命令行覆盖项生成最终配置"""
config_overrides: Dict[str, Any] = {}
if args.graphrag_enabled is not None:
config_overrides['GRAPHRAG_ENABLED'] = args.graphrag_enabled
if args.graphrag_max_queries is not None:
if args.graphrag_max_queries <= 0:
logger.warning("GRAPHRAG_MAX_QUERIES... | 1 | function_complex | 666ghj/BettaFish:report_engine_only.py:build_agent_config |
modified=now)
fb.setupPost()
fb.setupNameTable(
{
"familyName": "Occulta",
"styleName": "Regular",
"uniqueFontIdentifier": "OCRmyPDF;Occulta-Regular;2026",
"fullName": "Occulta Regular",
"version": "Version 2.0",
"psName": "Occulta... | 1 | function_simple | ocrmypdf/OCRmyPDF:scripts/generate_glyphless_font.py:create_font |
).to(torch_device),
atol=1e-4,
rtol=1e-4,
)
# test propagate in video frames
frames = []
for sam2_video_output in self.video_model.propagate_in_video_iterator(
inference_session=inference_session,
start_frame_idx=ann_frame_idx,
... | 0 | test | huggingface/transformers:tests/models/edgetam_video/test_modeling_edgetam_video.py:EdgeTamVideoModelIntegrationTest.test_inference_mask_generation_video_multi_points |
and_validation_alias_missing(path: str):
client = TestClient(app)
response = client.post(path)
assert response.status_code == 422
assert response.json() == {
"detail": [
{
"type": "missing",
"loc": [
"body",
"p_v... | 1 | test | fastapi/fastapi:tests/test_request_params/test_form/test_required_str.py:test_required_alias_and_validation_alias_missing |
mock_llm.acall = AsyncMock(
side_effect=[
"<summary>Result A</summary>",
"<summary>Result B</summary>",
]
)
results = asyncio.run(
_asummarize_chunks(
chunks=[chunk_a, chunk_b],
llm=mock_llm,
... | 0 | test | crewAIInc/crewAI:lib/crewai/tests/utilities/test_agent_utils.py:TestParallelSummarization.test_asummarize_chunks_returns_ordered_results |
equal_resolution=False, return_tensors="pil"
)
for video in video_inputs:
self.assertIsInstance(video[0], Image.Image)
video_metadata = self.video_processor_tester.prepare_video_metadata(video_inputs)
encoded_videos = video_processing(
v... | 0 | test | huggingface/transformers:tests/models/glm4v/test_video_processing_glm4v.py:Glm4vVideoProcessingTest.test_call_pil |
"""
This transforms the weights obtained using `convert_gpt_oss.py` to load them into `Mxfp4GptOssExperts`.
"""
PrecisionConfig, FlexCtx, InFlexData = (
triton_kernels_hub.matmul_ogs.PrecisionConfig,
triton_kernels_hub.matmul_ogs.FlexCtx,
triton_kernels_hub.matmul_ogs.InFlexData,
... | 0 | function_complex | huggingface/transformers:src/transformers/integrations/mxfp4.py:swizzle_mxfp4_convertops |
- NUM_RETRIES: 重试次数（可选）
- FALLBACK_MODELS: 备用模型列表（可选）
"""
self.model = config.get("MODEL", "deepseek/deepseek-chat")
self.api_key = config.get("API_KEY") or os.environ.get("AI_API_KEY", "")
self.api_base = config.get("API_BASE", "")
self.temperature = config.get(... | 1 | function_simple | sansan0/TrendRadar:trendradar/ai/client.py:AIClient.__init__ |
color channel (gray_scaled=True) or 3 RGB channels (gray_scaled=False).
"""
super().__init__()
cnn_multiplier = get_cnn_multiplier(model_size, override=cnn_multiplier)
self.gray_scaled = gray_scaled
config = CNNTransposeHeadConfig(
input_dims=[input_size]... | 0 | function_simple | ray-project/ray:rllib/algorithms/dreamerv3/torch/models/components/conv_transpose_atari.py:ConvTransposeAtari.__init__ |
�证器 - 验证 IR 表格数据格式是否正确。
验证规则：
1. 基本结构验证：type, rows 字段
2. 行结构验证：每行必须有 cells 数组
3. 单元格结构验证：每个 cell 必须有 blocks 数组
4. 嵌套 cells 检测：检测错误的嵌套 cells 结构
5. 数据完整性验证：检查空单元格和缺失数� | 1 | documentation | 666ghj/BettaFish:ReportEngine/utils/table_validator.py:TableValidator:class_doc |
m_set_on_agent():
"""
Test that OpenAI is the default provider when no explicit LLM is set on the agent
"""
agent = Agent(
role="Research Assistant",
goal="Find information about the population of Tokyo",
backstory="You are a helpful research assistant.",
llm=LLM(model="g... | 0 | test | crewAIInc/crewAI:lib/crewai/tests/llms/openai/test_openai.py:test_openai_is_default_provider_without_explicit_llm_set_on_agent |
student):
"""Validate that teacher and student have compatible input shapes."""
if not hasattr(teacher, "inputs") or not hasattr(student, "inputs"):
return
teacher_inputs = getattr(teacher, "inputs")
student_inputs = getattr(student, "inputs")
if teacher_inputs is No... | 1 | function_simple | keras-team/keras:keras/src/distillation/distiller.py:Distiller._validate_input_compatibility |
print(f"Function parameters: {params}")
if 'webhook_config' in params:
print(f"✅ process_llm_extraction has webhook_config parameter")
webhook_param = sig.parameters['webhook_config']
if webhook_param.default is None or webhook_param.default == inspect.Parameter.empty:... | 1 | test | unclecode/crawl4ai:test_llm_webhook_feature.py:test_process_llm_extraction_signature |
initialization and basic functionality.
"""
engine_args = AsyncEngineArgs(
model="Qwen/Qwen2.5-0.5B-Instruct",
dtype="auto",
disable_log_stats=False,
enforce_eager=True,
trust_remote_code=True,
enable_prefix_caching=True,
max_model_len=256,
specu... | 0 | test | ray-project/ray:release/llm_tests/serve/test_llm_serve_integration.py:test_engine_metrics_with_spec_decode |
else []
)
for comp in comparisons:
if not (
isinstance(comp.left, ast.Attribute)
and comp.left.attr == "major"
and comp.comparators
and isin... | 1 | function_complex | vllm-project/vllm:tools/pre_commit/generate_attention_backend_docs.py:parse_flash_attn_features |
task_id: The job's task identifier
"""
payload = {
"url": url,
"q": query,
"cache": False,
"webhook_config": {
"webhook_url": webhook_url,
"webhook_data_in_payload": include_data,
# Optional: Add custom headers for authentication
... | 1 | function_simple | unclecode/crawl4ai:docs/examples/docker_webhook_example.py:submit_llm_job_with_webhook |
Disable auth mode
set_auth_mode("disabled")
reset_auth_token_state()
# Create server without auth
server, port = create_sync_test_server(with_auth=False)
try:
# Client without auth
channel = grpc.insecure_channel(f"localhost:{port}")
stub = ... | 0 | test | ray-project/ray:python/ray/tests/authentication/test_sync_grpc_interceptors.py:test_sync_server_without_auth |
_ask_in_start_method(self) -> None:
"""ask() works inside a @start() method, flow completes normally."""
execution_log: list[str] = []
class TestFlow(Flow):
input_provider = MockInputProvider(["AI"])
@start()
def gather(self):
topic = self.as... | 0 | test | crewAIInc/crewAI:lib/crewai/tests/test_flow_ask.py:TestAskBasic.test_ask_in_start_method |
block_ids) >= n_blocks:
return True
# Exit early if even after uninitializing all initialized blocks, there are not enough free blocks
block_to_uninitialize = n_blocks - len(self._uninit_block_ids)
if len(self._init_block_ids) < block_to_uninitialize:
return False
... | 0 | function_simple | huggingface/transformers:src/transformers/generation/continuous_batching/cache_manager.py:BlockManager.has_enough_free_blocks |
podcast_data["title"])
if "date" in podcast_data:
fields.append("date = ?")
params.append(podcast_data["date"])
if "content" in podcast_data and isinstance(podcast_data["content"], dict):
fields.append("content_json = ?")
params.app... | 0 | function_complex | Shubhamsaboo/awesome-llm-apps:advanced_ai_agents/multi_agent_apps/ai_news_and_podcast_agents/beifong/services/podcast_service.py:PodcastService.update_podcast |
_model_len=1024,
enable_lora=True,
max_loras=4,
max_lora_rank=8,
max_num_seqs=2,
max_num_batched_tokens=2048,
compilation_config=vllm.config.CompilationConfig( # Avoid OOM
cudagraph_specialize_lora=False,
),
)
... | 1 | test | vllm-project/vllm:tests/lora/test_gptoss_tp.py:test_gpt_oss_lora |
if req.is_prefill:
kinds["prefill"].append(tup)
elif req.is_extend:
kinds["extend"].append(tup)
elif req.is_decode:
kinds["decode"].append(tup)
parts = []
for kind in ["prefill", "extend", "decode"]:
lst = kinds[kind]
if not lst:
... | 1 | function_complex | vllm-project/vllm:benchmarks/attention_benchmarks/batch_spec.py:format_batch_spec |
dir):
"""Generated SKILL.md should contain valid, parseable YAML frontmatter."""
install_ai_skills(project_dir, "claude")
skill_file = project_dir / ".claude" / "skills" / "speckit-specify" / "SKILL.md"
content = skill_file.read_text()
# Extract and parse frontmatter
as... | 0 | test | github/spec-kit:tests/test_ai_skills.py:TestInstallAiSkills.test_generated_skill_has_parseable_yaml |
for component in pipe.components.values():
if hasattr(component, "set_default_attn_processor"):
component.set_default_attn_processor()
pipe.to(torch_device)
pipe.set_progress_bar_config(disable=None)
generator_device = "cpu"
inputs = self.get_dummy_inputs(g... | 1 | test | huggingface/diffusers:tests/pipelines/qwenimage/test_qwenimage.py:QwenImagePipelineFastTests.test_attention_slicing_forward_pass |
频率和活跃时间）
- "keyword_cooccur": 关键词共现分析（分析关键词同时出现的模式）
topic: 话题关键词（可选，platform_compare模式适用）
date_range: **【对象类型】** 日期范围（可选）
- **格式**: {"start": "YYYY-MM-DD", "end": "YYYY-MM-DD"}
| 1 | function_simple | sansan0/TrendRadar:mcp_server/server.py:analyze_data_insights |
apping functionality since it is implemented in PEFT
and is extensively tested there. The goal of this test is specifically to ensure that
hotswapping with diffusers does not require recompilation.
See https://github.com/huggingface/peft/blob/eaab05e18d51fb4cce20a73c9acd82a00c013b83/tests/test_gpu_examples.py#L4252
fo... | 1 | documentation | huggingface/diffusers:tests/models/testing_utils/lora.py:LoraHotSwappingForModelTesterMixin:class_doc |
": [4, 5, 6], "c": [7, 8, 9]})
parquet_path = tmp_path / "test.parquet"
df.to_parquet(parquet_path, index=False)
# Build pipeline with operations
ds = ray.data.read_parquet(str(parquet_path))
for op_type, *op_args in operations:
if op_type == "select":
... | 0 | test | ray-project/ray:python/ray/data/tests/test_projection_fusion.py:TestProjectionFusion.test_projection_pushdown_into_parquet_read |
type": "flip", "p": 0.5}}),
},
timeout=120,
)
b1 = r1.json()
assert r1.status_code == 200 and any(a["name"] == name for a in b1["assets"])
# Non-matching object -> no match
r2 = http.get(
api_base + "/api/assets",
params={
"include_tags": "unit-tests,mf-o... | 1 | test | Comfy-Org/ComfyUI:tests-unit/assets_test/test_metadata_filters.py:test_meta_list_of_objects_any_of |
test_T5Gemma2_sequence_classification_model(self):
config, input_dict = self.model_tester.prepare_config_and_inputs_for_common()
config.num_labels = 3
input_ids = input_dict["input_ids"]
attention_mask = input_ids.ne(1).to(torch_device)
sequence_labels = ids_tensor([self.model_t... | 0 | test | huggingface/transformers:tests/models/t5gemma2/test_modeling_t5gemma2.py:T5Gemma2ModelTest.test_T5Gemma2_sequence_classification_model |
:
async with websockets.connect(self.uri, additional_headers=headers) as ws:
self.ws = ws # Safe: now created inside this thread + loop
# Create separate tasks for sending and receiving
recv_task = asyncio.create_task(self._recv_loop(ws))
... | 1 | function_simple | run-llama/llama_index:llama-index-integrations/voice_agents/llama-index-voice-agents-openai/llama_index/voice_agents/openai/websocket.py:OpenAIVoiceAgentWebsocket._socket_loop |
(f"{_root}/plugins/convert/writer", [], ['writer_config.py', '__init__.py']), # Too deep
# Wrong name
(f"{_root}/plugins/train", ["model", "trainer"], ['train_defaults.py', '__init__.py'])]
mock_walk = mocker.MagicMock(return_value=dir_tree)
mocker.patch("lib.config.config.os.walk", mock_w... | 1 | test | deepfakes/faceswap:tests/lib/config/config_test.py:test_generate_configs |
"""Download a single file from S3.
Args:
s3_client: Shared boto3 S3 client
bucket: S3 bucket name
key: S3 object key
local_file_path: Local path where file will be saved
Returns:
Tuple of (key, success)
"""
try:
... | 0 | function_simple | ray-project/ray:python/ray/llm/_internal/common/utils/cloud_filesystem/s3_filesystem.py:S3FileSystem._download_single_file |
"nodeAffinity": {
"preferredDuringSchedulingIgnoredDuringExecution": [
{
"weight": 1,
"preference": {
"matchExpressions": [
{"key": "not-me", "operator": "In", "valu... | 1 | test | apache/airflow:helm-tests/tests/helm_tests/airflow_core/test_worker_sets.py:TestWorkerSets.test_overwrite_affinity |
Name="container">
<p>Nested content</p>
</div>
"""
result, path = self._load_from_file(content)
assert isinstance(result, LoaderResult)
assert all(
tag not in result.content
for tag in ["import", "export", "<Component", "<div", "</div>"]
)
assert all(... | 0 | test | crewAIInc/crewAI:lib/crewai-tools/tests/rag/test_mdx_loader.py:TestMDXLoader.test_load_basic_mdx_file |
query = """
INSERT INTO tasks
(name, description, command, task_type, frequency, frequency_unit, enabled, created_at)
VALUES (?, ?, ?, ?, ?, ?, ?, ?)
"""
params = (
name,
description,
command,
... | 0 | function_complex | Shubhamsaboo/awesome-llm-apps:advanced_ai_agents/multi_agent_apps/ai_news_and_podcast_agents/beifong/services/task_service.py:TaskService.create_task |
[str, Any] | None],
label: str = "",
default_repo: str = "",
default_dtype: str = "",
):
"""
Args:
node_specs: Dict mapping node_type to node spec or None.
Node spec has: inputs, model_inputs, outputs, required_inputs, required_model_inputs... | 1 | function_simple | huggingface/diffusers:src/diffusers/modular_pipelines/mellon_node_utils.py:MellonPipelineConfig.__init__ |
canvas_id: str,
tenant_id: str,
runtime_user_id: str,
dsl,
canvas_category=CanvasCategory.Agent,
title="",
):
"""Replace replica content for `/set` under lock."""
replica_key = cls._replica_key(canvas_id, str(tenant_id), str(runtime_user_id))
lock_ke... | 1 | function_simple | infiniflow/ragflow:api/apps/services/canvas_replica_service.py:CanvasReplicaService.replace_for_set |
position_ids=text_position_ids,
)
hidden_states = inputs_embeds
# create position embeddings to be shared across the decoder layers
position_embeddings = self.rotary_emb(hidden_states, position_ids)
for decoder_layer in self.layers[: self.config.num_hidden_layers]:
... | 0 | function_complex | huggingface/transformers:src/transformers/models/ernie4_5_vl_moe/modular_ernie4_5_vl_moe.py:Ernie4_5_VLMoeTextModel.forward |
url: str):
"""Crawl with undetected browser"""
print("\n[Undetected Browser Mode]")
browser_config = BrowserConfig(
headless=False,
verbose=True,
)
# Create undetected adapter and strategy
undetected_adapter = UndetectedAdapter()
crawler_strategy = AsyncPlaywrightCrawler... | 1 | function_simple | unclecode/crawl4ai:docs/examples/undetected_simple_demo.py:crawl_with_undetected_browser |
key(feature: str) -> str:
"""Interactive prompt for API key."""
print(
f"""
╭─────────────────────────────────────────────────────────────╮
│ 🔑 Browser-Use API Key Required │
│ │
│ {feature} requires an API key. ... | 0 | function_simple | browser-use/browser-use:browser_use/skill_cli/api_key.py:prompt_for_api_key |
73, 486, 780, 1136, 254, 983, 138, 386, 800, 1819, 1857],
[1178, 1939, 107, 1605, 582, 1256, 420, 637, 648, 1023, 1809, 978, 1703, 278, 1668, 2044, 1599, 1321, 1670, 1716, 1155, 56, 602, 877, 886, 220, 910, 797, 1028, 1226, 869, 811],
[1432, 1926, 1197, 1687, 540, 1815, 658, 1080, 1162, 192, 31... | 0 | test | huggingface/transformers:tests/models/csm/test_modeling_csm.py:CsmForConditionalGenerationIntegrationTest.test_1b_model_integration_generate |
method="process",
dtype=None,
request_kwargs=dict(x=row["id"]),
),
# Error rows will bypass this postprocess and return raw data with
# __inference_error__ set. Only success rows get resp/id keys.
postprocess=lambda row: dict(
resp=row.get(... | 0 | test | ray-project/ray:python/ray/llm/tests/batch/gpu/processor/test_serve_deployment_proc.py:test_serve_deployment_continue_on_error |
"title": "Fix: A bug",
"url": "https://github.com/test/repo/pull/456",
}
],
}
package_versions = {"pkg1": "0.1.0", "pkg2": "0.2.0"}
today = date.today().strftime("%Y-%m-%d")
expected_text = f"""{CHANGELOG_PLACEHOLDER}
## [{today}]
### pkg1 [0.1.0]
-... | 1 | test | run-llama/llama_index:llama-dev/tests/release/test_changelog.py:test_get_changelog_text |
_model_len"] = 1024
compilation_config = dict(
use_inductor_graph_partition=inductor_graph_partition,
custom_ops=custom_ops.split(","),
pass_config=PassConfig(
enable_qk_norm_rope_fusion=True,
fuse_allreduce_rms=True,
),
)
matches_check = [
"... | 1 | test | vllm-project/vllm:tests/compile/fusions_e2e/test_tp2_ar_rms.py:test_tp2_ar_rms_fusions |
mlx_whisper missing
class _MpsOff:
def is_built(self):
return False
def is_available(self):
return False
class _TorchOff:
class backends:
mps = _MpsOff()
monkeypatch.setitem(sys.modules, "torch", _TorchOff())... | 1 | test | docling-project/docling:tests/test_asr_mlx_whisper.py:TestMlxWhisperIntegration.test_selector_import_errors_force_native |
print(f"✓ Successfully crawled bot detection site")
print(f"✓ With stealth enabled, many detection tests should show as passed")
if result.screenshot:
# Save screenshot for verification
import base64
with open("stealth_detection... | 1 | function_simple | unclecode/crawl4ai:docs/examples/stealth_mode_quick_start.py:example_2_stealth_with_screenshot |
):
"""Test that private network IPv4 addresses are blocked."""
browser_profile = BrowserProfile(block_ip_addresses=True, headless=True, user_data_dir=None)
browser_session = BrowserSession(browser_profile=browser_profile)
event_bus = EventBus()
watchdog = SecurityWatchdog(browser_session=browser_session, even... | 0 | test | browser-use/browser-use:tests/ci/security/test_ip_blocking.py:TestIPv4Blocking.test_block_private_ipv4_networks |
command=Command(
update={
"messages": [
HumanMessage(content="Inner msg", id="inner"),
]
}
),
)
model = GenericFakeChatModel(me... | 1 | test | langchain-ai/langchain:libs/langchain_v1/tests/unit_tests/agents/middleware/core/test_wrap_model_call_state_update.py:TestComposition.test_inner_command_propagated_through_composition |
is not None:
assert not per_act_token_quant
assert not per_out_ch_quant
# TODO(bnell): this is not quite right for activations since first
# dim should be 1.
a_shape = GroupShape(row=block_shape[0], col=block_shape[1])
w_shape = GroupShape(row=block_shape[0], col=block_s... | 1 | function_complex | vllm-project/vllm:vllm/model_executor/layers/fused_moe/config.py:_quant_flags_to_group_shape |
indices:
intermediates.append(x)
if torch.jit.is_scripting() or not stop_early:
stages = self.stages
else:
# max_index is 0-4, stages are 1-4, so we need max_index stages
stages = self.stages[:max_index] if max_index > 0 else []
for feat_idx, sta... | 1 | function_complex | huggingface/pytorch-image-models:timm/models/csatv2.py:CSATv2.forward_intermediates |
" is 72",
"°F",
" and sunny",
".",
]
results = list(parse_deepseek_v32(_simulate_tokens(model_tokens)))
# Step 3: Verify all tokens pass through as GenerationResponse
gen_results = [r for r in results if isinstance(r, GenerationResponse)]
to... | 0 | test | exo-explore/exo:src/exo/worker/tests/unittests/test_runner/test_dsml_e2e.py:TestE2EStandardResponse.test_plain_text_passthrough |
�】创建专用的logger，配置实时写入
# - enqueue=False: 禁用异步队列，立即写入
# - buffering=1: 行缓冲，每条日志立即刷新到文件
# - level="DEBUG": 记录所有级别的日志
# - encoding="utf-8": 明确指定UTF-8编码
# - mode="a": 追加模式，保留历史日志
| 1 | function_complex | 666ghj/BettaFish:ReportEngine/agent.py:ReportAgent._setup_logging |
replace_in_file(compiled_file, "emoji==2.9.0", "emoji==2.10.0")
output_file = Path(
_runfiles.Rlocation(f"{tmpdir}/requirements_compiled.txt")
)
save_file_as(compiled_file, output_file)
manager = _create_test_manager(tmpdir)
manager.compile(
... | 0 | test | ray-project/ray:ci/raydepsets/tests/test_cli.py:TestCli.test_compile_update_package |
_spec: Model specification (for generating engine-specific configs)
Returns:
Initialized engine instance
Raises:
ValueError: If engine type is not supported
ImportError: If required dependencies are not installed
"""
engine_type = options.engine_type
# Generate model_confi... | 1 | function_complex | docling-project/docling:docling/models/inference_engines/vlm/factory.py:create_vlm_engine |
corners.
Args:
num_patches_h (int): Number of patches along the vertical (height) axis.
num_patches_w (int): Number of patches along the horizontal (width) axis.
dtype (torch.dtype): The desired data type of the returned tensor.
Returns:
torch.Tensor: A tensor of shape (height... | 0 | function_simple | huggingface/transformers:src/transformers/models/dinov3_vit/modular_dinov3_vit.py:get_patches_center_coordinates |
"type": "tool_call",
"id": "abc_234",
"name": "another_tool",
"args": {"arg_1": "value_1"},
},
],
response_metadata={
"model_provider": "bedrock",
"model_name": "us.anthropic.claude-sonnet-4-20250514-v1:0",
... | 1 | test | langchain-ai/langchain:libs/core/tests/unit_tests/messages/block_translators/test_bedrock.py:test_convert_to_v1_from_bedrock |
Creating subtasks using LLM...')
# Create subtasks using LLM
subtasks = await create_subtasks(main_task, llm)
print(f'📋 Created {len(subtasks)} subtasks:')
for i, task in enumerate(subtasks, 1):
print(f' {i}. {task}')
print(f'\n🔥 Starting {len(subtasks)} agents in parallel...')
print('🔍 Each agent will ... | 0 | function_simple | browser-use/browser-use:examples/custom-functions/parallel_agents.py:run_parallel_agents |
"""Test get_configured_op returns cached ConfiguredHelionKernel."""
def fake_impl(*args, **kwargs):
return torch.zeros_like(args[0])
def default_picker(args, config_keys):
return "default"
wrapper = HelionKernelWrapper(
raw_kernel_func=sample_kernel,... | 1 | test | vllm-project/vllm:tests/kernels/helion/test_register.py:TestHelionKernelWrapper.test_get_configured_op_returns_cached_kernel |
config": {
"encoding": encoding_type,
},
},
]
config = ServeDeploySchema.parse_obj(config_dict)
client.deploy_apps(config)
wait_for_condition(
lambda: httpx.post("http://localhost:8000/app1").status_code == 200
)
... | 0 | test | ray-project/ray:python/ray/serve/tests/test_deploy_app_2.py:TestDeploywithLoggingConfig.test_deploy_app_with_deployment_logging_config |
2", tn_parent=a)
c = Tag.objects.create(name="C2", tn_parent=b)
d = Tag.objects.create(name="D2", tn_parent=c)
x = Tag.objects.create(name="X2")
y = Tag.objects.create(name="Y2", tn_parent=x)
assert y.parent_pk == x.pk
# Moving X under D would make deepest node Y exceed... | 1 | test | paperless-ngx/paperless-ngx:src/documents/tests/test_tag_hierarchy.py:TestTagHierarchy.test_max_depth_on_move_subtree |
(Page): The Playwright page instance
Returns:
str: Base64-encoded screenshot image
"""
try:
# The page is already loaded, just take the screenshot
screenshot = await page.screenshot(full_page=False)
return base64.b64encode(screenshot).decode("utf... | 1 | function_simple | unclecode/crawl4ai:crawl4ai/async_crawler_strategy.back.py:AsyncPlaywrightCrawlerStrategy.take_screenshot_naive |
processor_dict)
self.assertTrue(hasattr(image_processing, "downsample_factor"))
self.assertTrue(hasattr(image_processing, "min_tiles"))
self.assertTrue(hasattr(image_processing, "max_tiles"))
self.assertTrue(hasattr(image_processing, "use_thumbnail"))
self.ass... | 0 | test | huggingface/transformers:tests/models/lfm2_vl/test_image_processing_lfm2_vl.py:Lfm2VlImageProcessingTest.test_image_processor_properties |
id_from_path,
get_best_access_host,
get_free_port,
is_port_in_use,
)
# Test port functions
assert not is_port_in_use(0) # Port 0 is always available
port = get_free_port(8000)
assert 8000 <= port < 65535
# Test host resolution
assert get_best_access_host("0.0.0.0"... | 1 | test | langflow-ai/langflow:src/lfx/tests/unit/cli/test_serve_simple.py:test_cli_utility_functions |
input_str = "This is a test"
image_input = self.prepare_image_inputs()
# both image and text
inputs = processor(text=input_str, images=image_input)
self.assertListEqual(
list(inputs.keys()),
[
"flattened_patches",
"attention_m... | 0 | test | huggingface/transformers:tests/models/kosmos2_5/test_processor_kosmos2_5.py:Kosmos2_5ProcessorTest.test_model_input_names |
Matters")
print("=" * 70)
print("Before v0.7.7: Docker was just a containerized crawler")
print("After v0.7.7: Complete self-hosting platform with enterprise monitoring")
print("\nYou now have:")
print(" • Full visibility into what's happening inside")
print(" • Real-time operational dashboar... | 1 | function_simple | unclecode/crawl4ai:docs/releases_review/demo_v0.7.7.py:print_summary |
": "arn:aws:iam::123456789012:role/firehose_delivery_role",
"BucketARN": "arn:aws:s3:::kinesis-test",
"Prefix": "airflow/",
"BufferingHints": {"SizeInMBs": 123, "IntervalInSeconds": 124},
"CompressionFormat": "UNCOMPRESSED",
},
)
... | 1 | test | apache/airflow:providers/amazon/tests/unit/amazon/aws/hooks/test_firehose.py:TestFirehoseHook.test_insert_batch_records_kinesis_firehose |
Raises:
Bip44DepthError: If the current depth is not suitable for deriving keys
Bip32KeyError: If the derivation results in an invalid key
"""
if not self.IsLevel(Bip44Levels.CHANGE):
raise Bip44DepthError(
f"Current depth ({self.m_bip32_obj.De... | 1 | function_simple | ccxt/ccxt:python/ccxt/static_dependencies/bip/bip44_base/bip44_base.py:Bip44Base._AddressIndexGeneric |
Args(
model="Qwen/Qwen2.5-0.5B-Instruct",
dtype="auto",
disable_log_stats=False,
enforce_eager=True,
)
engine = AsyncLLM.from_engine_args(
engine_args, stat_loggers=[RayPrometheusStatLogger]
)
for i, prompt in enumerate(["What is the capital of France?", "What i... | 0 | test | ray-project/ray:release/llm_tests/serve/test_llm_serve_integration.py:test_engine_metrics |
lx.data.Extraction(
extraction_class="emotion",
extraction_text="But soft!",
attributes={"feeling": "gentle awe"},
),
lx.data.Extraction(
extraction_class="relationship",
extraction_text="Juliet is th... | 1 | function_simple | google/langextract:examples/ollama/demo_ollama.py:example_romeo_juliet |
list[int],
min_prime_idx: int,
prev_num: int,
max_num: int,
prev_sum: int,
primes_degrees: dict[int, int],
) -> None:
"""
Run over all prime combinations to generate non-prime numbers.
>>> chain = [0] * 3
>>> primes_degrees = {}
>>> multiply(
... chain=chain,
... ... | 1 | function_simple | TheAlgorithms/Python:project_euler/problem_095/sol1.py:multiply |
# Return partial success, or adapt as you see fit
result = {
"success": True,
"info": "Navigation triggered, ignoring context destroyed error",
}
else:
... | 1 | function_complex | unclecode/crawl4ai:crawl4ai/async_crawler_strategy.back.py:AsyncPlaywrightCrawlerStrategy.robust_execute_user_script |
_match.groups()
headers.append(
HeaderPermalinkInfo(
hashes=hashes, line_no=line_no, permalink=permalink, title=title
)
)
elif in_code_block3:
if line.startswith("```"):
count = len(line)... | 1 | function_complex | fastapi/fastapi:scripts/doc_parsing_utils.py:extract_header_permalinks |
sanitize_mcp_name(flow.action_name) if flow.action_name else sanitize_mcp_name(flow.name)
)
name = get_unique_name(base_name, MAX_MCP_TOOL_NAME_LENGTH, existing_names)
description = flow.action_description or (
flow.description i... | 1 | function_complex | langflow-ai/langflow:src/backend/base/langflow/api/v1/mcp_utils.py:handle_list_tools |
],
},
]
formatted_prompt = processor.apply_chat_template([messages], add_generation_prompt=True, tokenize=False)
self.assertEqual(len(formatted_prompt), 1) # batch size=1
out_dict = processor.apply_chat_template(
messages,
add_generation_prom... | 0 | test | huggingface/transformers:tests/models/qwen3_omni_moe/test_processing_qwen3_omni_moe.py:Qwen3OmniMoeProcessorTest.test_chat_template_audio_from_video |
matches in left (id=0, 1)
assert len(result) == 2
_assert_columns_match(result, {"id", "value", "score"})
_assert_scalar_values(result_by_id, {0: {"value": "x"}, 1: {"value": "y"}})
elif join_type == "right_anti":
# Should return right rows that DON'T have matches in left (id=3)
... | 0 | test | ray-project/ray:python/ray/data/tests/test_join.py:test_join_with_unjoinable_non_key_columns |
raction():
"""Demo: Extract structured company data."""
print('\n🏢 Demo 3: Company Information Extraction')
print('-' * 40)
task = """
Go to a financial website and look up information about Apple Inc.
Extract company details including name, stock symbol, market cap,
industry, headquarters, and foundi... | 0 | function_complex | browser-use/browser-use:examples/cloud/03_structured_output.py:demo_company_extraction |
()
with authentication_env_guard():
set_auth_mode("token")
set_env_auth_token(token)
reset_auth_token_state()
# Create server with auth enabled
server, port = create_sync_test_server(with_auth=True)
try:
# Client with auth interceptor via init_grpc_chan... | 0 | test | ray-project/ray:python/ray/tests/authentication/test_sync_grpc_interceptors.py:test_sync_server_and_client_with_valid_token |
block_ids_per_group3, num_tokens3 = metadata.reqs_to_fill[req3.request_id]
# Verify token counts (all tokens except last one)
assert num_tokens1 == block_size * 2 - 1
assert num_tokens2 == block_size * 3 - 1
assert num_tokens3 == block_size * 1 - 1
# Verify block counts for each request
asse... | 1 | test | vllm-project/vllm:tests/v1/kv_connector/unit/test_decode_bench_connector.py:test_decode_bench_connector_concurrent_requests |
6 and 4 tokens
position_ids = torch.tensor([[0, 1, 2, 3, 0, 1, 0, 1, 2, 3], [0, 1, 2, 3, 4, 5, 0, 1, 2, 3]])
causal_mask = create_causal_mask(
config=config,
# we only need batch size, seq_length and dtype here - we don't care about the values of the embeddings
inpu... | 0 | test | huggingface/transformers:tests/utils/test_masking_utils.py:MaskTest.test_packed_sequence_mask_sdpa |
.send.Page.getNavigationHistory(session_id=cdp_session.session_id)
current_index = history['currentIndex']
entries = history['entries']
# Check if we can go back
if current_index <= 0:
self.logger.warning('⚠️ Cannot go back - no previous entry in history')
return
# Navigate to the previous entr... | 0 | function_simple | browser-use/browser-use:browser_use/browser/watchdogs/default_action_watchdog.py:DefaultActionWatchdog.on_GoBackEvent |
return None
register_before_tool_call_hook(before_hook)
register_after_tool_call_hook(after_hook)
try:
agent = Agent(
role="Calculator",
goal="Perform calculations",
backstory="You are a calculator assistant",
... | 0 | test | crewAIInc/crewAI:lib/crewai/tests/hooks/test_tool_hooks.py:TestNativeToolCallingHooksIntegration.test_agent_native_tool_hooks_before_and_after |
, just use the main session
if not self.browser_profile.cross_origin_iframes:
return await self.get_or_create_cdp_session()
# Get complete frame hierarchy
all_frames, target_sessions = await self.get_all_frames()
# Find the requested frame
frame_info = await self.find_frame_target(frame_id, all_frames)
... | 0 | function_simple | browser-use/browser-use:browser_use/browser/session.py:BrowserSession.cdp_client_for_frame |
break
except ConnectionRefusedError:
time.sleep(5)
# Send ping-pong.
send_rllink_message(sock_, {"type": RLlink.PING.name})
msg_type, msg_body = get_rllink_message(sock_)
assert msg_type == RLlink.PONG
# Request config.
send_rllink_message(sock_, {"type": RLlink.GET_... | 0 | function_complex | ray-project/ray:rllib/examples/envs/classes/utils/dummy_external_client.py:_dummy_external_client |
def _reset_chart_validation_stats(self) -> None:
"""重置图表校验统计并清除失败计数标记"""
self.chart_validation_stats = {
'total': 0,
'valid': 0,
'repaired_locally': 0,
'repaired_api': 0,
'failed': 0
}
# 保留失败原因缓存，但重置本次渲染的计数
self._chart_f... | 1 | function_simple | 666ghj/BettaFish:ReportEngine/renderers/html_renderer.py:HTMLRenderer._reset_chart_validation_stats |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.