code stringlengths 66 870k | docstring stringlengths 19 26.7k | func_name stringlengths 1 138 | language stringclasses 1
value | repo stringlengths 7 68 | path stringlengths 5 324 | url stringlengths 46 389 | license stringclasses 7
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|---|---|---|---|---|---|---|---|
def test_on_data_returns_message(mock_message):
"""Test that on_data returns the same IngestControlMessage object it receives."""
result = on_data(mock_message)
assert result is mock_message, "on_data should return the input IngestControlMessage object." | Test that on_data returns the same IngestControlMessage object it receives. | test_on_data_returns_message | python | NVIDIA/nv-ingest | tests/service_tests/modules/injectors/test_task_injector.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/modules/injectors/test_task_injector.py | Apache-2.0 |
def test_process_message_normal(
mock_IngestControlMessage,
mock_ControlMessageTask,
mock_validate_ingest_job,
mock_annotate_cm,
mock_format_trace_id,
):
"""
Test that process_message correctly processes a valid job.
The job dict contains:
- "job_id": identifier
- "job_payloa... |
Test that process_message correctly processes a valid job.
The job dict contains:
- "job_id": identifier
- "job_payload": a list of dicts to be converted to a DataFrame
- "tasks": a list of task dicts (each with optional id, type, task_properties)
- "tracing_options": options that trigg... | test_process_message_normal | python | NVIDIA/nv-ingest | tests/service_tests/modules/sources/test_message_broker_task_source.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/modules/sources/test_message_broker_task_source.py | Apache-2.0 |
def test_fetch_and_process_messages_dict_job(mock_process_message):
"""
Test that when the client returns a job as a dictionary,
fetch_and_process_messages yields a processed control message.
"""
job = {
"job_id": "job_dict",
"job_payload": [{"x": 1}, {"x": 2}],
"tasks": [],
... |
Test that when the client returns a job as a dictionary,
fetch_and_process_messages yields a processed control message.
| test_fetch_and_process_messages_dict_job | python | NVIDIA/nv-ingest | tests/service_tests/modules/sources/test_message_broker_task_source.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/modules/sources/test_message_broker_task_source.py | Apache-2.0 |
def test_fetch_and_process_messages_base_model_job(mock_process_message):
"""
Test that when the client returns a job as a BaseModel with response_code 0,
the job.response is JSON-decoded and processed.
"""
job_dict = {
"job_id": "job_bm",
"job_payload": [{"y": "a"}],
"tasks"... |
Test that when the client returns a job as a BaseModel with response_code 0,
the job.response is JSON-decoded and processed.
| test_fetch_and_process_messages_base_model_job | python | NVIDIA/nv-ingest | tests/service_tests/modules/sources/test_message_broker_task_source.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/modules/sources/test_message_broker_task_source.py | Apache-2.0 |
def test_fetch_and_process_messages_skip_on_nonzero_response_code(mock_process_message):
"""
Test that when the client returns a BaseModel job with a nonzero response_code,
the job is skipped and not processed.
Then a subsequent valid dictionary job is processed.
"""
response_bad = DummyResponse... |
Test that when the client returns a BaseModel job with a nonzero response_code,
the job is skipped and not processed.
Then a subsequent valid dictionary job is processed.
| test_fetch_and_process_messages_skip_on_nonzero_response_code | python | NVIDIA/nv-ingest | tests/service_tests/modules/sources/test_message_broker_task_source.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/modules/sources/test_message_broker_task_source.py | Apache-2.0 |
def test_fetch_and_process_messages_timeout_error():
"""
Test that if client.fetch_message raises a TimeoutError,
fetch_and_process_messages catches it and continues to the next message.
"""
call = [0]
class TimeoutThenValidClient:
def fetch_message(self, task_queue, count, override_fet... |
Test that if client.fetch_message raises a TimeoutError,
fetch_and_process_messages catches it and continues to the next message.
| test_fetch_and_process_messages_timeout_error | python | NVIDIA/nv-ingest | tests/service_tests/modules/sources/test_message_broker_task_source.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/modules/sources/test_message_broker_task_source.py | Apache-2.0 |
def test_fetch_and_process_messages_exception_handling():
"""
Test that if client.fetch_message raises a generic Exception,
fetch_and_process_messages logs the error and continues fetching.
"""
call = [0]
class ExceptionThenValidClient:
def fetch_message(self, task_queue, count, overrid... |
Test that if client.fetch_message raises a generic Exception,
fetch_and_process_messages logs the error and continues fetching.
| test_fetch_and_process_messages_exception_handling | python | NVIDIA/nv-ingest | tests/service_tests/modules/sources/test_message_broker_task_source.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/modules/sources/test_message_broker_task_source.py | Apache-2.0 |
def test_audio_config_schema_valid_grpc():
"""Test AudioConfigSchema with a valid gRPC endpoint."""
config = AudioConfigSchema(audio_endpoints=("grpc://localhost:50051", ""))
assert config.audio_endpoints == ("grpc://localhost:50051", None)
assert config.audio_infer_protocol == "grpc" | Test AudioConfigSchema with a valid gRPC endpoint. | test_audio_config_schema_valid_grpc | python | NVIDIA/nv-ingest | tests/service_tests/schemas/test_audio_extractor_schema.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/schemas/test_audio_extractor_schema.py | Apache-2.0 |
def test_audio_config_schema_valid_http():
"""Test AudioConfigSchema with a valid HTTP endpoint."""
config = AudioConfigSchema(audio_endpoints=("", "http://localhost:8080"))
assert config.audio_endpoints == (None, "http://localhost:8080")
assert config.audio_infer_protocol == "http" | Test AudioConfigSchema with a valid HTTP endpoint. | test_audio_config_schema_valid_http | python | NVIDIA/nv-ingest | tests/service_tests/schemas/test_audio_extractor_schema.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/schemas/test_audio_extractor_schema.py | Apache-2.0 |
def test_audio_config_schema_valid_both_endpoints():
"""Test AudioConfigSchema with both gRPC and HTTP endpoints provided."""
config = AudioConfigSchema(audio_endpoints=("grpc://localhost:50051", "http://localhost:8080"))
assert config.audio_endpoints == ("grpc://localhost:50051", "http://localhost:8080")
... | Test AudioConfigSchema with both gRPC and HTTP endpoints provided. | test_audio_config_schema_valid_both_endpoints | python | NVIDIA/nv-ingest | tests/service_tests/schemas/test_audio_extractor_schema.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/schemas/test_audio_extractor_schema.py | Apache-2.0 |
def test_audio_config_schema_whitespace_endpoints():
"""Test AudioConfigSchema removes whitespace-only values."""
config = AudioConfigSchema(audio_endpoints=(" ", "http://localhost:8080"))
assert config.audio_endpoints == (None, "http://localhost:8080")
assert config.audio_infer_protocol == "http" | Test AudioConfigSchema removes whitespace-only values. | test_audio_config_schema_whitespace_endpoints | python | NVIDIA/nv-ingest | tests/service_tests/schemas/test_audio_extractor_schema.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/schemas/test_audio_extractor_schema.py | Apache-2.0 |
def test_audio_config_schema_default_protocol():
"""Test that the default protocol is inferred correctly."""
config = AudioConfigSchema(audio_endpoints=("grpc://localhost:50051", None))
assert config.audio_infer_protocol == "grpc"
config = AudioConfigSchema(audio_endpoints=(None, "http://localhost:8080... | Test that the default protocol is inferred correctly. | test_audio_config_schema_default_protocol | python | NVIDIA/nv-ingest | tests/service_tests/schemas/test_audio_extractor_schema.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/schemas/test_audio_extractor_schema.py | Apache-2.0 |
def test_audio_extractor_schema_with_audio_config():
"""Test AudioExtractorSchema with an embedded AudioConfigSchema."""
audio_config = AudioConfigSchema(audio_endpoints=("grpc://localhost:50051", ""))
extractor = AudioExtractorSchema(audio_extraction_config=audio_config)
assert extractor.audio_extracti... | Test AudioExtractorSchema with an embedded AudioConfigSchema. | test_audio_extractor_schema_with_audio_config | python | NVIDIA/nv-ingest | tests/service_tests/schemas/test_audio_extractor_schema.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/schemas/test_audio_extractor_schema.py | Apache-2.0 |
def valid_module_config():
"""Returns a valid job payload for testing purposes."""
return {
"raise_on_failure": True,
} | Returns a valid job payload for testing purposes. | valid_module_config | python | NVIDIA/nv-ingest | tests/service_tests/schemas/test_image_dedup_schema.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/schemas/test_image_dedup_schema.py | Apache-2.0 |
def test_task_injection_schema_explicit_value():
"""
Test TaskInjectionSchema with an explicit value for raise_on_failure.
"""
schema = TaskInjectionSchema(raise_on_failure=True)
assert schema.raise_on_failure is True, "raise_on_failure should respect the explicitly provided value." |
Test TaskInjectionSchema with an explicit value for raise_on_failure.
| test_task_injection_schema_explicit_value | python | NVIDIA/nv-ingest | tests/service_tests/schemas/test_injection_schema.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/schemas/test_injection_schema.py | Apache-2.0 |
def test_task_injection_schema_forbids_extra():
"""
Test that TaskInjectionSchema forbids extra fields due to the 'extra = "forbid"' configuration.
"""
with pytest.raises(ValidationError) as excinfo:
TaskInjectionSchema(raise_on_failure=False, unexpected_field="value")
assert "Extra inputs a... |
Test that TaskInjectionSchema forbids extra fields due to the 'extra = "forbid"' configuration.
| test_task_injection_schema_forbids_extra | python | NVIDIA/nv-ingest | tests/service_tests/schemas/test_injection_schema.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/schemas/test_injection_schema.py | Apache-2.0 |
def test_metadata_injector_schema_default():
"""
Test the MetadataInjectorSchema with default values.
"""
schema = MetadataInjectorSchema()
assert schema.raise_on_failure is False, "Default value for raise_on_failure should be False." |
Test the MetadataInjectorSchema with default values.
| test_metadata_injector_schema_default | python | NVIDIA/nv-ingest | tests/service_tests/schemas/test_metadata_injector_schema.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/schemas/test_metadata_injector_schema.py | Apache-2.0 |
def test_metadata_injector_schema_explicit_value():
"""
Test the MetadataInjectorSchema with an explicit value for raise_on_failure.
"""
schema = MetadataInjectorSchema(raise_on_failure=True)
assert schema.raise_on_failure is True, "raise_on_failure should respect the explicitly provided value." |
Test the MetadataInjectorSchema with an explicit value for raise_on_failure.
| test_metadata_injector_schema_explicit_value | python | NVIDIA/nv-ingest | tests/service_tests/schemas/test_metadata_injector_schema.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/schemas/test_metadata_injector_schema.py | Apache-2.0 |
def test_metadata_injector_schema_forbids_extra():
"""
Test that the MetadataInjectorSchema forbids extra fields due to the 'extra = "forbid"' configuration.
"""
with pytest.raises(ValidationError) as excinfo:
MetadataInjectorSchema(raise_on_failure=False, unexpected_field="value")
assert "E... |
Test that the MetadataInjectorSchema forbids extra fields due to the 'extra = "forbid"' configuration.
| test_metadata_injector_schema_forbids_extra | python | NVIDIA/nv-ingest | tests/service_tests/schemas/test_metadata_injector_schema.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/schemas/test_metadata_injector_schema.py | Apache-2.0 |
def test_metadata_injector_schema_raise_on_failure_parametrized(input_value):
"""
Parametrized test for different boolean values of raise_on_failure.
"""
schema = MetadataInjectorSchema(raise_on_failure=input_value)
assert schema.raise_on_failure is input_value, f"raise_on_failure should be {input_v... |
Parametrized test for different boolean values of raise_on_failure.
| test_metadata_injector_schema_raise_on_failure_parametrized | python | NVIDIA/nv-ingest | tests/service_tests/schemas/test_metadata_injector_schema.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/schemas/test_metadata_injector_schema.py | Apache-2.0 |
def test_redis_client_schema_optional_fields(use_ssl, connection_timeout, max_backoff, max_retries):
"""
Parametrized test for RedisClientSchema to check behavior with various combinations of optional fields.
"""
schema = MessageBrokerClientSchema(
broker_params={"use_ssl": use_ssl},
con... |
Parametrized test for RedisClientSchema to check behavior with various combinations of optional fields.
| test_redis_client_schema_optional_fields | python | NVIDIA/nv-ingest | tests/service_tests/schemas/test_redis_client_schema.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/schemas/test_redis_client_schema.py | Apache-2.0 |
def test_redis_client_schema_with_custom_host_and_port():
"""
Test RedisClientSchema instantiation with custom host and port.
"""
custom_host = "custom_redis_host"
custom_port = 1234
schema = MessageBrokerClientSchema(host=custom_host, port=custom_port)
assert schema.host == custom_host
... |
Test RedisClientSchema instantiation with custom host and port.
| test_redis_client_schema_with_custom_host_and_port | python | NVIDIA/nv-ingest | tests/service_tests/schemas/test_redis_client_schema.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/schemas/test_redis_client_schema.py | Apache-2.0 |
def test_redis_task_sink_schema_defaults():
"""
Test RedisTaskSinkSchema with default values, including the default embedded RedisClientSchema.
"""
schema = MessageBrokerTaskSinkSchema()
assert isinstance(
schema.broker_client, MessageBrokerClientSchema
), "redis_client should be an inst... |
Test RedisTaskSinkSchema with default values, including the default embedded RedisClientSchema.
| test_redis_task_sink_schema_defaults | python | NVIDIA/nv-ingest | tests/service_tests/schemas/test_redis_task_sink_schema.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/schemas/test_redis_task_sink_schema.py | Apache-2.0 |
def test_redis_task_sink_schema_custom_values():
"""
Test RedisTaskSinkSchema with custom values for its fields and embedded RedisClientSchema.
"""
custom_redis_client = MessageBrokerClientSchema(host="custom_host", port=12345, broker_params={"use_ssl": True})
schema = MessageBrokerTaskSinkSchema(br... |
Test RedisTaskSinkSchema with custom values for its fields and embedded RedisClientSchema.
| test_redis_task_sink_schema_custom_values | python | NVIDIA/nv-ingest | tests/service_tests/schemas/test_redis_task_sink_schema.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/schemas/test_redis_task_sink_schema.py | Apache-2.0 |
def test_redis_task_source_schema_custom_values():
"""
Test RedisTaskSourceSchema with custom values for its fields.
"""
custom_redis_client = MessageBrokerClientSchema(host="custom_host", port=12345, broker_params={"use_ssl": True})
schema = MessageBrokerTaskSourceSchema(
broker_client=cust... |
Test RedisTaskSourceSchema with custom values for its fields.
| test_redis_task_source_schema_custom_values | python | NVIDIA/nv-ingest | tests/service_tests/schemas/test_redis_task_source_schema.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/schemas/test_redis_task_source_schema.py | Apache-2.0 |
def test_redis_task_source_schema_invalid_progress_engines(progress_engines):
"""
Test RedisTaskSourceSchema with invalid values for progress_engines to ensure validation catches them.
"""
with pytest.raises(ValidationError) as excinfo:
MessageBrokerTaskSourceSchema(progress_engines=progress_eng... |
Test RedisTaskSourceSchema with invalid values for progress_engines to ensure validation catches them.
| test_redis_task_source_schema_invalid_progress_engines | python | NVIDIA/nv-ingest | tests/service_tests/schemas/test_redis_task_source_schema.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/schemas/test_redis_task_source_schema.py | Apache-2.0 |
def test_text_splitter_schema_defaults():
"""
Test the TextSplitterSchema with default values.
"""
schema = TextSplitterSchema()
assert schema.tokenizer is None
assert schema.chunk_size == 1024
assert schema.chunk_overlap == 150
assert schema.raise_on_failure is False |
Test the TextSplitterSchema with default values.
| test_text_splitter_schema_defaults | python | NVIDIA/nv-ingest | tests/service_tests/schemas/test_text_splitter_schema.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/schemas/test_text_splitter_schema.py | Apache-2.0 |
def test_text_splitter_schema_custom_values():
"""
Test the TextSplitterSchema with custom values.
"""
tokenizer = "meta-llama/Llama-3.2-1B"
chunk_size = 500
chunk_overlap = 10
schema = TextSplitterSchema(
tokenizer=tokenizer, chunk_size=chunk_size, chunk_overlap=chunk_overlap, raise... |
Test the TextSplitterSchema with custom values.
| test_text_splitter_schema_custom_values | python | NVIDIA/nv-ingest | tests/service_tests/schemas/test_text_splitter_schema.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/schemas/test_text_splitter_schema.py | Apache-2.0 |
def test_text_splitter_schema_chunk_overlap_validation(chunk_size, chunk_overlap, is_valid):
"""
Parametrized test for validating the chunk_overlap logic in TextSplitterSchema.
"""
if is_valid:
schema = TextSplitterSchema(chunk_size=chunk_size, chunk_overlap=chunk_overlap)
assert schema.... |
Parametrized test for validating the chunk_overlap logic in TextSplitterSchema.
| test_text_splitter_schema_chunk_overlap_validation | python | NVIDIA/nv-ingest | tests/service_tests/schemas/test_text_splitter_schema.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/schemas/test_text_splitter_schema.py | Apache-2.0 |
def test_is_subset_wildcard():
"""Test that the special wildcard '*' matches any value."""
assert _is_subset("anything", "*")
assert _is_subset(123, "*")
assert _is_subset({"a": 1}, "*") | Test that the special wildcard '*' matches any value. | test_is_subset_wildcard | python | NVIDIA/nv-ingest | tests/service_tests/util/flow_control/test_filter_by_task.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/util/flow_control/test_filter_by_task.py | Apache-2.0 |
def test_is_subset_dict_true():
"""Test that a dictionary is a subset when all required keys/values are present."""
superset = {"a": 1, "b": 2, "c": 3}
subset = {"a": 1, "b": 2}
assert _is_subset(superset, subset) | Test that a dictionary is a subset when all required keys/values are present. | test_is_subset_dict_true | python | NVIDIA/nv-ingest | tests/service_tests/util/flow_control/test_filter_by_task.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/util/flow_control/test_filter_by_task.py | Apache-2.0 |
def test_filter_decorator_complex_nested_match():
"""
Test that a complex nested property requirement with regex and list matching is satisfied.
Required task:
("taskComplex", {"nested": {"key": "regex:^start"}, "list": [1, 2]})
Dummy task:
- type: "taskComplex"
- properties: a dict ... |
Test that a complex nested property requirement with regex and list matching is satisfied.
Required task:
("taskComplex", {"nested": {"key": "regex:^start"}, "list": [1, 2]})
Dummy task:
- type: "taskComplex"
- properties: a dict with a nested dict whose 'key' starts with "start"
... | test_filter_decorator_complex_nested_match | python | NVIDIA/nv-ingest | tests/service_tests/util/flow_control/test_filter_by_task.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/util/flow_control/test_filter_by_task.py | Apache-2.0 |
def test_filter_decorator_complex_nested_no_match():
"""
Test that a complex nested property requirement fails when nested values do not match.
Required task:
("taskComplex", {"nested": {"key": "regex:^start"}, "list": [1, 2, 3]})
Dummy task:
- type: "taskComplex"
- properties: a dic... |
Test that a complex nested property requirement fails when nested values do not match.
Required task:
("taskComplex", {"nested": {"key": "regex:^start"}, "list": [1, 2, 3]})
Dummy task:
- type: "taskComplex"
- properties: a dict with a nested dict whose 'key' does not start with "start"... | test_filter_decorator_complex_nested_no_match | python | NVIDIA/nv-ingest | tests/service_tests/util/flow_control/test_filter_by_task.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/util/flow_control/test_filter_by_task.py | Apache-2.0 |
def test_filter_decorator_multiple_required_conditions_match():
"""
Test that multiple property conditions within a single required task tuple are all satisfied.
Required task:
("taskMulti", {"a": 1}, {"b": 2})
Dummy task:
- type: "taskMulti"
- properties: a dict that includes 'a': 1... |
Test that multiple property conditions within a single required task tuple are all satisfied.
Required task:
("taskMulti", {"a": 1}, {"b": 2})
Dummy task:
- type: "taskMulti"
- properties: a dict that includes 'a': 1 and 'b': 2 (along with extra data).
| test_filter_decorator_multiple_required_conditions_match | python | NVIDIA/nv-ingest | tests/service_tests/util/flow_control/test_filter_by_task.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/util/flow_control/test_filter_by_task.py | Apache-2.0 |
def test_filter_decorator_multiple_required_conditions_no_match():
"""
Test that if not all property conditions within a required task tuple are satisfied,
the function is not executed.
Required task:
("taskMulti", {"a": 1}, {"b": 2})
Dummy task:
- type: "taskMulti"
- properties:... |
Test that if not all property conditions within a required task tuple are satisfied,
the function is not executed.
Required task:
("taskMulti", {"a": 1}, {"b": 2})
Dummy task:
- type: "taskMulti"
- properties: a dict that satisfies 'a': 1 but has 'b': 3 (which does not match the req... | test_filter_decorator_multiple_required_conditions_no_match | python | NVIDIA/nv-ingest | tests/service_tests/util/flow_control/test_filter_by_task.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/util/flow_control/test_filter_by_task.py | Apache-2.0 |
def test_filter_decorator_pydantic_properties_match():
"""
Test that the decorator correctly handles Pydantic model instances as task properties.
Required task:
("taskPydantic", {"a": 10, "b": "hello"})
Dummy task:
- type: "taskPydantic"
- properties: a DummyModel instance with value... |
Test that the decorator correctly handles Pydantic model instances as task properties.
Required task:
("taskPydantic", {"a": 10, "b": "hello"})
Dummy task:
- type: "taskPydantic"
- properties: a DummyModel instance with values that satisfy the requirement.
| test_filter_decorator_pydantic_properties_match | python | NVIDIA/nv-ingest | tests/service_tests/util/flow_control/test_filter_by_task.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/util/flow_control/test_filter_by_task.py | Apache-2.0 |
def test_filter_decorator_pydantic_properties_no_match():
"""
Test that a Pydantic model instance does not satisfy the required property criteria if its values differ.
Required task:
("taskPydantic", {"a": 10, "b": "world"})
Dummy task:
- type: "taskPydantic"
- properties: a DummyMod... |
Test that a Pydantic model instance does not satisfy the required property criteria if its values differ.
Required task:
("taskPydantic", {"a": 10, "b": "world"})
Dummy task:
- type: "taskPydantic"
- properties: a DummyModel instance that does not match the required properties.
| test_filter_decorator_pydantic_properties_no_match | python | NVIDIA/nv-ingest | tests/service_tests/util/flow_control/test_filter_by_task.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/util/flow_control/test_filter_by_task.py | Apache-2.0 |
def test_fetch_and_validate_module_config_valid():
"""
Test the function with a valid module configuration.
"""
valid_config = {"name": "Test Name", "age": 30}
mock_builder.get_current_module_config.return_value = valid_config
validated_config = fetch_and_validate_module_config(mock_builder, Sa... |
Test the function with a valid module configuration.
| test_fetch_and_validate_module_config_valid | python | NVIDIA/nv-ingest | tests/service_tests/util/modules/test_config_validator.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/util/modules/test_config_validator.py | Apache-2.0 |
def test_fetch_and_validate_module_config_invalid(mock_logger):
"""
Test the function with an invalid module configuration, ensuring it raises ValueError and logs the error.
"""
invalid_config = {"name": "Test Name"} # Missing required 'age' field
mock_builder.get_current_module_config.return_value... |
Test the function with an invalid module configuration, ensuring it raises ValueError and logs the error.
| test_fetch_and_validate_module_config_invalid | python | NVIDIA/nv-ingest | tests/service_tests/util/modules/test_config_validator.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/util/modules/test_config_validator.py | Apache-2.0 |
def test_fetch_and_validate_module_config_raises_with_no_config():
"""
Test the function when no configuration is provided, ensuring it raises a ValueError.
"""
mock_builder.get_current_module_config.return_value = {}
with pytest.raises(ValueError):
fetch_and_validate_module_config(mock_bui... |
Test the function when no configuration is provided, ensuring it raises a ValueError.
| test_fetch_and_validate_module_config_raises_with_no_config | python | NVIDIA/nv-ingest | tests/service_tests/util/modules/test_config_validator.py | https://github.com/NVIDIA/nv-ingest/blob/master/tests/service_tests/util/modules/test_config_validator.py | Apache-2.0 |
def main():
"""Main entry point for the Anus AI agent"""
parser = argparse.ArgumentParser(description="Anus AI - Autonomous Networked Utility System")
parser.add_argument("--config", type=str, default="config.yaml", help="Path to configuration file")
parser.add_argument("--mode", type=str, default="sing... | Main entry point for the Anus AI agent | main | python | nikmcfly/ANUS | anus/main.py | https://github.com/nikmcfly/ANUS/blob/master/anus/main.py | MIT |
def __init__(self, config_path: str = "config.yaml"):
"""
Initialize an AgentOrchestrator instance.
Args:
config_path: Path to the configuration file.
"""
self.config = self._load_config(config_path)
self.agents: Dict[str, BaseAgent] = {}
self... |
Initialize an AgentOrchestrator instance.
Args:
config_path: Path to the configuration file.
| __init__ | python | nikmcfly/ANUS | anus/core/orchestrator.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/orchestrator.py | MIT |
def execute_task(self, task: str, mode: Optional[str] = None) -> Dict[str, Any]:
"""
Execute a task using an appropriate agent.
Args:
task: The task description to execute.
mode: Execution mode ("single" or "multi"). If None, uses the config default.
... |
Execute a task using an appropriate agent.
Args:
task: The task description to execute.
mode: Execution mode ("single" or "multi"). If None, uses the config default.
Returns:
The execution result.
| execute_task | python | nikmcfly/ANUS | anus/core/orchestrator.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/orchestrator.py | MIT |
def list_agents(self) -> List[Dict[str, Any]]:
"""
List all registered agents.
Returns:
A list of agent descriptions.
"""
agent_list = []
# Add primary agent
agent_list.append({
"id": self.primary_agent.id,
"na... |
List all registered agents.
Returns:
A list of agent descriptions.
| list_agents | python | nikmcfly/ANUS | anus/core/orchestrator.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/orchestrator.py | MIT |
def _load_config(self, config_path: str) -> Dict[str, Any]:
"""
Load configuration from a YAML file.
Args:
config_path: Path to the configuration file.
Returns:
The loaded configuration.
"""
# Default configuration
def... |
Load configuration from a YAML file.
Args:
config_path: Path to the configuration file.
Returns:
The loaded configuration.
| _load_config | python | nikmcfly/ANUS | anus/core/orchestrator.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/orchestrator.py | MIT |
def _merge_configs(self, default: Dict[str, Any], override: Dict[str, Any]) -> Dict[str, Any]:
"""
Merge two configuration dictionaries.
Args:
default: Default configuration.
override: Override configuration.
Returns:
The merged c... |
Merge two configuration dictionaries.
Args:
default: Default configuration.
override: Override configuration.
Returns:
The merged configuration.
| _merge_configs | python | nikmcfly/ANUS | anus/core/orchestrator.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/orchestrator.py | MIT |
def _create_primary_agent(self) -> HybridAgent:
"""
Create the primary agent based on configuration.
Returns:
A HybridAgent instance.
"""
# Get agent config
agent_config = self.config.get("agent", {})
name = agent_config.get("name", "anus")
... |
Create the primary agent based on configuration.
Returns:
A HybridAgent instance.
| _create_primary_agent | python | nikmcfly/ANUS | anus/core/orchestrator.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/orchestrator.py | MIT |
def _create_short_term_memory(self) -> ShortTermMemory:
"""
Create a short-term memory instance based on configuration.
Returns:
A ShortTermMemory instance.
"""
memory_config = self.config.get("memory", {}).get("short_term", {})
capacity = memory_conf... |
Create a short-term memory instance based on configuration.
Returns:
A ShortTermMemory instance.
| _create_short_term_memory | python | nikmcfly/ANUS | anus/core/orchestrator.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/orchestrator.py | MIT |
def _create_long_term_memory(self) -> Optional[LongTermMemory]:
"""
Create a long-term memory instance based on configuration.
Returns:
A LongTermMemory instance, or None if disabled.
"""
memory_config = self.config.get("memory", {}).get("long_term", {})
... |
Create a long-term memory instance based on configuration.
Returns:
A LongTermMemory instance, or None if disabled.
| _create_long_term_memory | python | nikmcfly/ANUS | anus/core/orchestrator.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/orchestrator.py | MIT |
def _create_specialized_agents(self, primary_agent: HybridAgent) -> None:
"""
Create specialized agents for multi-agent mode.
Args:
primary_agent: The primary HybridAgent instance.
"""
# Default specialized agent roles
default_roles = ["researcher", "... |
Create specialized agents for multi-agent mode.
Args:
primary_agent: The primary HybridAgent instance.
| _create_specialized_agents | python | nikmcfly/ANUS | anus/core/orchestrator.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/orchestrator.py | MIT |
def __init__(self, name: Optional[str] = None, **kwargs):
"""
Initialize a BaseAgent instance.
Args:
name: Optional name for the agent. If not provided, a UUID will be generated.
**kwargs: Additional configuration options for the agent.
"""
self.i... |
Initialize a BaseAgent instance.
Args:
name: Optional name for the agent. If not provided, a UUID will be generated.
**kwargs: Additional configuration options for the agent.
| __init__ | python | nikmcfly/ANUS | anus/core/agent/base_agent.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/agent/base_agent.py | MIT |
def log_action(self, action: str, details: Dict[str, Any]) -> None:
"""
Log an action performed by the agent.
Args:
action: The name of the action.
details: Details about the action.
"""
log_entry = {
"timestamp": time.time(),
... |
Log an action performed by the agent.
Args:
action: The name of the action.
details: Details about the action.
| log_action | python | nikmcfly/ANUS | anus/core/agent/base_agent.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/agent/base_agent.py | MIT |
def get_info(self) -> Dict[str, Any]:
"""
Get information about the agent.
Returns:
A dictionary containing agent information.
"""
return {
"id": self.id,
"name": self.name,
"created_at": self.created_at,
"state... |
Get information about the agent.
Returns:
A dictionary containing agent information.
| get_info | python | nikmcfly/ANUS | anus/core/agent/base_agent.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/agent/base_agent.py | MIT |
def __init__(
self,
name: Optional[str] = None,
max_iterations: int = 10,
tools: Optional[List[str]] = None,
**kwargs
):
"""
Initialize a HybridAgent instance.
Args:
name: Optional name for the agent.
max_iterations: Ma... |
Initialize a HybridAgent instance.
Args:
name: Optional name for the agent.
max_iterations: Maximum number of thought-action cycles to perform.
tools: Optional list of tool names to load.
**kwargs: Additional configuration options for the agent.
... | __init__ | python | nikmcfly/ANUS | anus/core/agent/hybrid_agent.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/agent/hybrid_agent.py | MIT |
def _assess_complexity(self, task: str) -> float:
"""
Assess the complexity of a task.
Args:
task: The task description.
Returns:
A complexity score between 0 and 10.
"""
complexity = 0.0
# Check for multiple ... |
Assess the complexity of a task.
Args:
task: The task description.
Returns:
A complexity score between 0 and 10.
| _assess_complexity | python | nikmcfly/ANUS | anus/core/agent/hybrid_agent.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/agent/hybrid_agent.py | MIT |
def execute(self, task: str, **kwargs) -> Dict[str, Any]:
"""
Execute a task using the appropriate mode based on complexity.
Args:
task: The task description to execute.
**kwargs: Additional parameters for task execution.
Returns:
... |
Execute a task using the appropriate mode based on complexity.
Args:
task: The task description to execute.
**kwargs: Additional parameters for task execution.
Returns:
A dictionary containing the execution result and metadata.
| execute | python | nikmcfly/ANUS | anus/core/agent/hybrid_agent.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/agent/hybrid_agent.py | MIT |
def _execute_multi_agent(self, task: str, **kwargs) -> Dict[str, Any]:
"""
Execute a task using multiple specialized agents.
Args:
task: The task description to execute.
**kwargs: Additional parameters for task execution.
Returns:
... |
Execute a task using multiple specialized agents.
Args:
task: The task description to execute.
**kwargs: Additional parameters for task execution.
Returns:
A dictionary containing the aggregated results.
| _execute_multi_agent | python | nikmcfly/ANUS | anus/core/agent/hybrid_agent.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/agent/hybrid_agent.py | MIT |
def __init__(self, name: Optional[str] = None, max_iterations: int = 10, **kwargs):
"""
Initialize a ReactAgent instance.
Args:
name: Optional name for the agent.
max_iterations: Maximum number of thought-action cycles to perform.
**kwargs: Additional... |
Initialize a ReactAgent instance.
Args:
name: Optional name for the agent.
max_iterations: Maximum number of thought-action cycles to perform.
**kwargs: Additional configuration options for the agent.
| __init__ | python | nikmcfly/ANUS | anus/core/agent/react_agent.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/agent/react_agent.py | MIT |
def execute(self, task: str, **kwargs) -> Dict[str, Any]:
"""
Execute a task using the React paradigm.
Args:
task: The task description to execute.
**kwargs: Additional parameters for task execution.
Returns:
A dictionary containi... |
Execute a task using the React paradigm.
Args:
task: The task description to execute.
**kwargs: Additional parameters for task execution.
Returns:
A dictionary containing the execution result and metadata.
| execute | python | nikmcfly/ANUS | anus/core/agent/react_agent.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/agent/react_agent.py | MIT |
def _generate_thought(self, context: Dict[str, Any]) -> str:
"""
Generate a thought based on the current context.
Args:
context: The current execution context.
Returns:
The thought string.
"""
# This should be implemented usin... |
Generate a thought based on the current context.
Args:
context: The current execution context.
Returns:
The thought string.
| _generate_thought | python | nikmcfly/ANUS | anus/core/agent/react_agent.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/agent/react_agent.py | MIT |
def _decide_action(self, context: Dict[str, Any]) -> Tuple[str, Dict[str, Any]]:
"""
Decide on the next action to take.
Args:
context: The current execution context.
Returns:
A tuple of (action_name, action_input).
"""
# This ... |
Decide on the next action to take.
Args:
context: The current execution context.
Returns:
A tuple of (action_name, action_input).
| _decide_action | python | nikmcfly/ANUS | anus/core/agent/react_agent.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/agent/react_agent.py | MIT |
def _execute_action(self, action_name: str, action_input: Dict[str, Any]) -> Dict[str, Any]:
"""
Execute an action and return the observation.
Args:
action_name: The name of the action to execute.
action_input: The input parameters for the action.
... |
Execute an action and return the observation.
Args:
action_name: The name of the action to execute.
action_input: The input parameters for the action.
Returns:
The observation from executing the action.
| _execute_action | python | nikmcfly/ANUS | anus/core/agent/react_agent.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/agent/react_agent.py | MIT |
def _should_terminate(self, context: Dict[str, Any]) -> bool:
"""
Check if execution should terminate.
Args:
context: The current execution context.
Returns:
True if execution should terminate, False otherwise.
"""
# This shou... |
Check if execution should terminate.
Args:
context: The current execution context.
Returns:
True if execution should terminate, False otherwise.
| _should_terminate | python | nikmcfly/ANUS | anus/core/agent/react_agent.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/agent/react_agent.py | MIT |
def _generate_final_answer(self, context: Dict[str, Any]) -> str:
"""
Generate a final answer based on the context.
Args:
context: The current execution context.
Returns:
The final answer string.
"""
# Check if we have any suc... |
Generate a final answer based on the context.
Args:
context: The current execution context.
Returns:
The final answer string.
| _generate_final_answer | python | nikmcfly/ANUS | anus/core/agent/react_agent.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/agent/react_agent.py | MIT |
def __init__(
self,
name: Optional[str] = None,
max_iterations: int = 10,
tools: Optional[List[str]] = None,
**kwargs
):
"""
Initialize a ToolAgent instance.
Args:
name: Optional name for the agent.
max_iterations: M... |
Initialize a ToolAgent instance.
Args:
name: Optional name for the agent.
max_iterations: Maximum number of thought-action cycles to perform.
tools: Optional list of tool names to load.
**kwargs: Additional configuration options for the agent.
... | __init__ | python | nikmcfly/ANUS | anus/core/agent/tool_agent.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/agent/tool_agent.py | MIT |
def load_tool(self, tool_name: str) -> bool:
"""
Load a tool by name.
Args:
tool_name: The name of the tool to load.
Returns:
True if the tool was successfully loaded, False otherwise.
"""
try:
# Dynamically import... |
Load a tool by name.
Args:
tool_name: The name of the tool to load.
Returns:
True if the tool was successfully loaded, False otherwise.
| load_tool | python | nikmcfly/ANUS | anus/core/agent/tool_agent.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/agent/tool_agent.py | MIT |
def _decide_action(self, context: Dict[str, Any]) -> Tuple[str, Dict[str, Any]]:
"""
Decide on the next action to take based on the task.
Args:
context: The current execution context.
Returns:
A tuple of (action_name, action_input).
"... |
Decide on the next action to take based on the task.
Args:
context: The current execution context.
Returns:
A tuple of (action_name, action_input).
| _decide_action | python | nikmcfly/ANUS | anus/core/agent/tool_agent.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/agent/tool_agent.py | MIT |
def _execute_action(self, action_name: str, action_input: Dict[str, Any]) -> Dict[str, Any]:
"""
Execute an action using the appropriate tool.
Args:
action_name: The name of the action/tool to execute.
action_input: The input parameters for the action.
... |
Execute an action using the appropriate tool.
Args:
action_name: The name of the action/tool to execute.
action_input: The input parameters for the action.
Returns:
The observation from executing the action.
| _execute_action | python | nikmcfly/ANUS | anus/core/agent/tool_agent.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/agent/tool_agent.py | MIT |
def list_available_tools(self) -> List[Dict[str, Any]]:
"""
List all available tools.
Returns:
A list of tool information dictionaries.
"""
tool_info = []
for name, tool in self.tools.items():
info = {
"name": name,
... |
List all available tools.
Returns:
A list of tool information dictionaries.
| list_available_tools | python | nikmcfly/ANUS | anus/core/agent/tool_agent.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/agent/tool_agent.py | MIT |
def __init__(
self,
storage_path: Optional[str] = None,
index_in_memory: bool = True,
**kwargs
):
"""
Initialize a LongTermMemory instance.
Args:
storage_path: Path to store memory files. If None, uses a default location.
inde... |
Initialize a LongTermMemory instance.
Args:
storage_path: Path to store memory files. If None, uses a default location.
index_in_memory: Whether to keep an in-memory index for faster searches.
**kwargs: Additional configuration options.
| __init__ | python | nikmcfly/ANUS | anus/core/memory/long_term.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/memory/long_term.py | MIT |
def add(self, item: Dict[str, Any]) -> str:
"""
Add an item to memory and return its identifier.
Args:
item: The item to add to memory.
Returns:
A string identifier for the added item.
"""
# Generate a unique identifier
... |
Add an item to memory and return its identifier.
Args:
item: The item to add to memory.
Returns:
A string identifier for the added item.
| add | python | nikmcfly/ANUS | anus/core/memory/long_term.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/memory/long_term.py | MIT |
def get(self, identifier: str) -> Optional[Dict[str, Any]]:
"""
Retrieve an item from memory by its identifier.
Args:
identifier: The identifier of the item to retrieve.
Returns:
The retrieved item, or None if not found.
"""
#... |
Retrieve an item from memory by its identifier.
Args:
identifier: The identifier of the item to retrieve.
Returns:
The retrieved item, or None if not found.
| get | python | nikmcfly/ANUS | anus/core/memory/long_term.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/memory/long_term.py | MIT |
def update(self, identifier: str, item: Dict[str, Any]) -> bool:
"""
Update an item in memory.
Args:
identifier: The identifier of the item to update.
item: The updated item.
Returns:
True if the update was successful, False other... |
Update an item in memory.
Args:
identifier: The identifier of the item to update.
item: The updated item.
Returns:
True if the update was successful, False otherwise.
| update | python | nikmcfly/ANUS | anus/core/memory/long_term.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/memory/long_term.py | MIT |
def delete(self, identifier: str) -> bool:
"""
Delete an item from memory.
Args:
identifier: The identifier of the item to delete.
Returns:
True if the deletion was successful, False otherwise.
"""
item_path = self._get_item_p... |
Delete an item from memory.
Args:
identifier: The identifier of the item to delete.
Returns:
True if the deletion was successful, False otherwise.
| delete | python | nikmcfly/ANUS | anus/core/memory/long_term.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/memory/long_term.py | MIT |
def get_stats(self) -> Dict[str, Any]:
"""
Get statistics about the memory system.
Returns:
A dictionary containing memory statistics.
"""
# Count the number of items
if self.index_in_memory:
item_count = len(self.index)
else:
... |
Get statistics about the memory system.
Returns:
A dictionary containing memory statistics.
| get_stats | python | nikmcfly/ANUS | anus/core/memory/long_term.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/memory/long_term.py | MIT |
def _save_item(self, identifier: str, item: Dict[str, Any]) -> None:
"""
Save an item to disk.
Args:
identifier: The identifier of the item.
item: The item to save.
"""
item_path = self._get_item_path(identifier)
try:
... |
Save an item to disk.
Args:
identifier: The identifier of the item.
item: The item to save.
| _save_item | python | nikmcfly/ANUS | anus/core/memory/long_term.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/memory/long_term.py | MIT |
def _matches_query(self, item: Dict[str, Any], query: Dict[str, Any]) -> bool:
"""
Check if an item matches a query.
Args:
item: The item to check.
query: The query to match against.
Returns:
True if the item matches the query, Fa... |
Check if an item matches a query.
Args:
item: The item to check.
query: The query to match against.
Returns:
True if the item matches the query, False otherwise.
| _matches_query | python | nikmcfly/ANUS | anus/core/memory/long_term.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/memory/long_term.py | MIT |
def __init__(
self,
capacity: int = 1000,
ttl: int = 3600, # Time to live in seconds
**kwargs
):
"""
Initialize a ShortTermMemory instance.
Args:
capacity: Maximum number of items to store.
ttl: Time to live for items in sec... |
Initialize a ShortTermMemory instance.
Args:
capacity: Maximum number of items to store.
ttl: Time to live for items in seconds.
**kwargs: Additional configuration options.
| __init__ | python | nikmcfly/ANUS | anus/core/memory/short_term.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/memory/short_term.py | MIT |
def add(self, item: Dict[str, Any]) -> str:
"""
Add an item to memory and return its identifier.
If the memory is at capacity, the least recently used item will be evicted.
Args:
item: The item to add to memory.
Returns:
A st... |
Add an item to memory and return its identifier.
If the memory is at capacity, the least recently used item will be evicted.
Args:
item: The item to add to memory.
Returns:
A string identifier for the added item.
| add | python | nikmcfly/ANUS | anus/core/memory/short_term.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/memory/short_term.py | MIT |
def get(self, identifier: str) -> Optional[Dict[str, Any]]:
"""
Retrieve an item from memory by its identifier.
Updates the access time of the item to prevent it from being evicted.
Args:
identifier: The identifier of the item to retrieve.
... |
Retrieve an item from memory by its identifier.
Updates the access time of the item to prevent it from being evicted.
Args:
identifier: The identifier of the item to retrieve.
Returns:
The retrieved item, or None if not found.
... | get | python | nikmcfly/ANUS | anus/core/memory/short_term.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/memory/short_term.py | MIT |
def _prune_expired(self) -> None:
"""
Remove items that have exceeded their time to live.
"""
current_time = time.time()
expired_identifiers = []
for identifier, creation_time in self.creation_times.items():
if current_time - creation_time > self.ttl:... |
Remove items that have exceeded their time to live.
| _prune_expired | python | nikmcfly/ANUS | anus/core/memory/short_term.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/memory/short_term.py | MIT |
def _evict_lru(self) -> None:
"""
Evict the least recently used item from memory.
"""
while self.lru_queue:
_, identifier = heapq.heappop(self.lru_queue)
# Skip if the item has been deleted
if identifier not in self.items:
... |
Evict the least recently used item from memory.
| _evict_lru | python | nikmcfly/ANUS | anus/core/memory/short_term.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/memory/short_term.py | MIT |
def __init__(self, model: BaseModel, **kwargs):
"""
Initialize a TaskPlanner instance.
Args:
model: The language model to use for planning.
**kwargs: Additional configuration options for the planner.
"""
super().__init__(**kwargs)
self.mod... |
Initialize a TaskPlanner instance.
Args:
model: The language model to use for planning.
**kwargs: Additional configuration options for the planner.
| __init__ | python | nikmcfly/ANUS | anus/core/planning/task_planner.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/planning/task_planner.py | MIT |
def create_plan(self, task: str, context: Optional[Dict[str, Any]] = None) -> Dict[str, Any]:
"""
Create a plan for executing a task using the language model.
Args:
task: The task description.
context: Optional context for planning.
Returns:
... |
Create a plan for executing a task using the language model.
Args:
task: The task description.
context: Optional context for planning.
Returns:
A plan dictionary with steps and metadata.
| create_plan | python | nikmcfly/ANUS | anus/core/planning/task_planner.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/planning/task_planner.py | MIT |
def replan(self, plan: Dict[str, Any], feedback: Dict[str, Any]) -> Dict[str, Any]:
"""
Update a plan based on execution feedback.
Args:
plan: The current plan.
feedback: Feedback from execution.
Returns:
The updated plan.
... |
Update a plan based on execution feedback.
Args:
plan: The current plan.
feedback: Feedback from execution.
Returns:
The updated plan.
| replan | python | nikmcfly/ANUS | anus/core/planning/task_planner.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/planning/task_planner.py | MIT |
def get_next_step(self, plan: Dict[str, Any]) -> Optional[Dict[str, Any]]:
"""
Get the next step to execute from a plan.
Args:
plan: The current plan.
Returns:
The next step to execute, or None if the plan is complete.
"""
ste... |
Get the next step to execute from a plan.
Args:
plan: The current plan.
Returns:
The next step to execute, or None if the plan is complete.
| get_next_step | python | nikmcfly/ANUS | anus/core/planning/task_planner.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/planning/task_planner.py | MIT |
def mark_step_complete(self, plan: Dict[str, Any], step_id: str, result: Dict[str, Any]) -> Dict[str, Any]:
"""
Mark a step as complete in a plan.
Args:
plan: The current plan.
step_id: The ID of the completed step.
result: The result of the step exec... |
Mark a step as complete in a plan.
Args:
plan: The current plan.
step_id: The ID of the completed step.
result: The result of the step execution.
Returns:
The updated plan.
| mark_step_complete | python | nikmcfly/ANUS | anus/core/planning/task_planner.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/planning/task_planner.py | MIT |
def _create_planning_prompt(self, task: str, context: Dict[str, Any]) -> str:
"""
Create a prompt for generating a plan.
Args:
task: The task description.
context: Context information.
Returns:
A prompt string.
"""
... |
Create a prompt for generating a plan.
Args:
task: The task description.
context: Context information.
Returns:
A prompt string.
| _create_planning_prompt | python | nikmcfly/ANUS | anus/core/planning/task_planner.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/planning/task_planner.py | MIT |
def _create_replanning_prompt(self, task: str, plan: Dict[str, Any], feedback: Dict[str, Any]) -> str:
"""
Create a prompt for replanning.
Args:
task: The task description.
plan: The current plan.
feedback: Feedback from execution.
... |
Create a prompt for replanning.
Args:
task: The task description.
plan: The current plan.
feedback: Feedback from execution.
Returns:
A prompt string.
| _create_replanning_prompt | python | nikmcfly/ANUS | anus/core/planning/task_planner.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/planning/task_planner.py | MIT |
def _process_plan_data(self, task: str, plan_data: Dict[str, Any]) -> Dict[str, Any]:
"""
Process raw plan data into a structured plan.
Args:
task: The task description.
plan_data: Raw plan data from the model.
Returns:
A structur... |
Process raw plan data into a structured plan.
Args:
task: The task description.
plan_data: Raw plan data from the model.
Returns:
A structured plan dictionary.
| _process_plan_data | python | nikmcfly/ANUS | anus/core/planning/task_planner.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/planning/task_planner.py | MIT |
def _get_remaining_steps(self, plan: Dict[str, Any]) -> List[Dict[str, Any]]:
"""
Get the remaining steps from a plan.
Args:
plan: The current plan.
Returns:
A list of remaining steps.
"""
steps = plan.get("steps", [])
... |
Get the remaining steps from a plan.
Args:
plan: The current plan.
Returns:
A list of remaining steps.
| _get_remaining_steps | python | nikmcfly/ANUS | anus/core/planning/task_planner.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/planning/task_planner.py | MIT |
def _find_executable_step(self, plan: Dict[str, Any]) -> Optional[Dict[str, Any]]:
"""
Find a step that can be executed (all dependencies satisfied).
Args:
plan: The current plan.
Returns:
An executable step, or None if none found.
""... |
Find a step that can be executed (all dependencies satisfied).
Args:
plan: The current plan.
Returns:
An executable step, or None if none found.
| _find_executable_step | python | nikmcfly/ANUS | anus/core/planning/task_planner.py | https://github.com/nikmcfly/ANUS/blob/master/anus/core/planning/task_planner.py | MIT |
def __init__(self, default_model_config: Optional[Dict[str, Any]] = None):
"""
Initialize a ModelRouter instance.
Args:
default_model_config: Configuration for the default model.
"""
self.models: Dict[str, BaseModel] = {}
self.model_classes: Dict[str,... |
Initialize a ModelRouter instance.
Args:
default_model_config: Configuration for the default model.
| __init__ | python | nikmcfly/ANUS | anus/models/model_router.py | https://github.com/nikmcfly/ANUS/blob/master/anus/models/model_router.py | MIT |
def register_model(self, name: str, model: BaseModel) -> None:
"""
Register a model instance.
Args:
name: A unique name for the model.
model: The model instance to register.
"""
self.models[name] = model
logging.info(f"Registered model: {n... |
Register a model instance.
Args:
name: A unique name for the model.
model: The model instance to register.
| register_model | python | nikmcfly/ANUS | anus/models/model_router.py | https://github.com/nikmcfly/ANUS/blob/master/anus/models/model_router.py | MIT |
def register_model_class(self, provider: str, model_class: Type[BaseModel]) -> None:
"""
Register a model class for a provider.
Args:
provider: The model provider name.
model_class: The model class to register.
"""
self.model_classes[provider] = m... |
Register a model class for a provider.
Args:
provider: The model provider name.
model_class: The model class to register.
| register_model_class | python | nikmcfly/ANUS | anus/models/model_router.py | https://github.com/nikmcfly/ANUS/blob/master/anus/models/model_router.py | MIT |
def get_model(self, name_or_config: Union[str, Dict[str, Any]]) -> BaseModel:
"""
Get a model instance by name or create one from config.
Args:
name_or_config: Either a model name or a model configuration dictionary.
Returns:
A model instance... |
Get a model instance by name or create one from config.
Args:
name_or_config: Either a model name or a model configuration dictionary.
Returns:
A model instance.
| get_model | python | nikmcfly/ANUS | anus/models/model_router.py | https://github.com/nikmcfly/ANUS/blob/master/anus/models/model_router.py | MIT |
def get_default_model(self) -> BaseModel:
"""
Get the default model, creating it if necessary.
Returns:
The default model instance.
"""
if self.default_model is None:
self.default_model = self._create_model_from_config(self.default_model_config)
... |
Get the default model, creating it if necessary.
Returns:
The default model instance.
| get_default_model | python | nikmcfly/ANUS | anus/models/model_router.py | https://github.com/nikmcfly/ANUS/blob/master/anus/models/model_router.py | MIT |
def select_model_for_task(self, task: str, requirements: Dict[str, Any] = None) -> BaseModel:
"""
Select an appropriate model for a given task.
Args:
task: The task description.
requirements: Optional requirements for the model.
Returns:
... |
Select an appropriate model for a given task.
Args:
task: The task description.
requirements: Optional requirements for the model.
Returns:
The selected model instance.
| select_model_for_task | python | nikmcfly/ANUS | anus/models/model_router.py | https://github.com/nikmcfly/ANUS/blob/master/anus/models/model_router.py | MIT |
def _create_model_from_config(self, config: Dict[str, Any]) -> BaseModel:
"""
Create a model instance from a configuration dictionary.
Args:
config: The model configuration.
Returns:
A model instance.
"""
# Get the provider
... |
Create a model instance from a configuration dictionary.
Args:
config: The model configuration.
Returns:
A model instance.
| _create_model_from_config | python | nikmcfly/ANUS | anus/models/model_router.py | https://github.com/nikmcfly/ANUS/blob/master/anus/models/model_router.py | MIT |
def list_available_models(self) -> List[Dict[str, Any]]:
"""
List all available models.
Returns:
A list of model information dictionaries.
"""
models_info = []
# Add instantiated models
for name, model in self.models.items():
... |
List all available models.
Returns:
A list of model information dictionaries.
| list_available_models | python | nikmcfly/ANUS | anus/models/model_router.py | https://github.com/nikmcfly/ANUS/blob/master/anus/models/model_router.py | MIT |
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