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Update API docs
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26 changed files with 1397 additions and 32 deletions
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@ -14,7 +14,15 @@ from llama_stack.schema_utils import json_schema_type, webmethod
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class FilteringFunction(Enum):
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"""The type of filtering function."""
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"""The type of filtering function.
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:cvar none: No filtering applied, accept all generated synthetic data
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:cvar random: Random sampling of generated data points
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:cvar top_k: Keep only the top-k highest scoring synthetic data samples
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:cvar top_p: Nucleus-style filtering, keep samples exceeding cumulative score threshold
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:cvar top_k_top_p: Combined top-k and top-p filtering strategy
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:cvar sigmoid: Apply sigmoid function for probability-based filtering
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"""
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none = "none"
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random = "random"
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@ -26,7 +34,12 @@ class FilteringFunction(Enum):
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@json_schema_type
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class SyntheticDataGenerationRequest(BaseModel):
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"""Request to generate synthetic data. A small batch of prompts and a filtering function"""
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"""Request to generate synthetic data. A small batch of prompts and a filtering function
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:param dialogs: List of conversation messages to use as input for synthetic data generation
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:param filtering_function: Type of filtering to apply to generated synthetic data samples
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:param model: (Optional) The identifier of the model to use. The model must be registered with Llama Stack and available via the /models endpoint
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"""
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dialogs: list[Message]
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filtering_function: FilteringFunction = FilteringFunction.none
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@ -35,7 +48,11 @@ class SyntheticDataGenerationRequest(BaseModel):
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@json_schema_type
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class SyntheticDataGenerationResponse(BaseModel):
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"""Response from the synthetic data generation. Batch of (prompt, response, score) tuples that pass the threshold."""
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"""Response from the synthetic data generation. Batch of (prompt, response, score) tuples that pass the threshold.
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:param synthetic_data: List of generated synthetic data samples that passed the filtering criteria
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:param statistics: (Optional) Statistical information about the generation process and filtering results
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"""
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synthetic_data: list[dict[str, Any]]
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statistics: dict[str, Any] | None = None
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@ -48,4 +65,12 @@ class SyntheticDataGeneration(Protocol):
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dialogs: list[Message],
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filtering_function: FilteringFunction = FilteringFunction.none,
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model: str | None = None,
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) -> SyntheticDataGenerationResponse: ...
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) -> SyntheticDataGenerationResponse:
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"""Generate synthetic data based on input dialogs and apply filtering.
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:param dialogs: List of conversation messages to use as input for synthetic data generation
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:param filtering_function: Type of filtering to apply to generated synthetic data samples
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:param model: (Optional) The identifier of the model to use. The model must be registered with Llama Stack and available via the /models endpoint
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:returns: Response containing filtered synthetic data samples and optional statistics
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"""
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...
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