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SelfInstructPipeline
class SelfInstructPipeline:
- agent (ChatAgent): The agent used to interact and generate instructions.
- seed (str): The path to the human-written instructions.
- num_machine_instructions (int): Number of machine-generated instructions to generate. (default::obj:
5)
- data_output_path (Optional[str]): Path to save the generated data. (default::obj:
./data_output.json)
- human_to_machine_ratio (tuple): Ratio of human to machine tasks used for instruction generation. (default::obj:
(6, 2))
- instruction_filter (InstructionFilter): A filter to validate generated instructions. (default::obj:
None)
- filter_config (Optional[Dict[str, Dict[str, Any]]]): configuration for the filter functions registered in FILE_REGISTRY. (default::obj:
None)
- stop_on_first_failure (bool): If True, stops checking filters after the first failure.
init
def __init__(
self,
agent: ChatAgent,
seed: str,
num_machine_instructions: int = 5,
data_output_path: Optional[str] = './data_output.json',
human_to_machine_ratio: tuple = (6, 2),
instruction_filter: Optional[InstructionFilter] = None,
filter_config: Optional[Dict[str, Dict[str, Any]]] = None,
stop_on_first_failure: bool = False
):
load_seed
def load_seed(self, path: str):
- path (str): Path to the seed file.
sample_human_tasks
def sample_human_tasks(self, count: int):
- count (int): Number of human tasks to sample.
Returns:
List[dict]: A list of sampled human tasks.
sample_machine_tasks
def sample_machine_tasks(self, count: int):
- count (int): Number of machine tasks to sample.
Returns:
List[dict]: A list of sampled machine tasks, with placeholders if
insufficient tasks are available.
generate_machine_instruction
def generate_machine_instruction(self):
identify_instruction
def identify_instruction(self, instruction: str):
- instruction (str): The instruction to classify.
Returns:
bool: True if the instruction is a classification task,
otherwise False.
generate_machine_instances
def generate_machine_instances(self):
generate_machine_instance
def generate_machine_instance(self, instruction: str, classification: bool):
- instruction (str): The instruction to create instances for.
- classification (bool): Whether the instruction is a classification task.
Returns:
List[dict]: A list of generated instances in input-output format.
parse_classification_output
def parse_classification_output(self, generated_text: str):
- generated_text (str): The raw text generated by the agent for classification tasks.
Returns:
List[Dict[str, str]]: A list of dictionaries with ‘input’ and
‘output’ keys.
parse_non_classification_output
def parse_non_classification_output(self, generated_text: str):
- generated_text (str): The raw text generated by the agent for non-classification tasks.
Returns:
List[Dict[str, str]]: A list of dictionaries with ‘input’ and
‘output’ keys.
construct_data
def construct_data(self):
generate
def generate(self, timeout_minutes = 600):
- timeout_minutes (int): Maximum time in minutes to run the generation process before timing out. (default: :obj:
600)
