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update doc

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Xi Yan 2025-03-12 23:30:47 -07:00
parent 772339bebf
commit b4d118fc5c
3 changed files with 32 additions and 14 deletions
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26
llama_stack/apis/datasets/datasets.py
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@ -16,17 +16,17 @@ from llama_stack.schema_utils import json_schema_type, register_schema, webmetho
class DatasetPurpose(Enum):
"""
Purpose of the dataset. Each purpose has a required input data schema.
:cvar post-training/messages: The dataset contains messages used for post-training. Examples:
:cvar post-training/messages: The dataset contains messages used for post-training.
{
"messages": [
{"role": "user", "content": "Hello, world!"},
{"role": "assistant", "content": "Hello, world!"},
]
}
:cvar eval/question-answer: The dataset contains a question and answer column.
:cvar eval/messages-answer: The dataset contains a messages column with list of messages and an answer column.
{
"question": [
"messages": [
{"role": "user", "content": "What is the capital of France?"},
],
"answer": "Paris"
@ -34,7 +34,7 @@ class DatasetPurpose(Enum):
"""
post_training_messages = "post-training/messages"
eval_question_answer = "eval/question-answer"
eval_messages_answer = "eval/messages-answer"
# TODO: add more schemas here
@ -153,7 +153,21 @@ class Datasets(Protocol):
:param purpose: The purpose of the dataset. One of
- "post-training/messages": The dataset contains a messages column with list of messages for post-training.
- "eval/question-answer": The dataset contains a question and answer column.
- Example data rows:
{
"messages": [
{"role": "user", "content": "Hello, world!"},
{"role": "assistant", "content": "Hello, world!"},
]
}
- "eval/messages-answer": The dataset contains a messages column with list of messages and an answer column.
- Example data rows:
{
"messages": [
{"role": "user", "content": "What is the capital of France?"},
],
"answer": "Paris"
}
:param source: The data source of the dataset. Examples:
- {
"type": "uri",