Documentation Index
Fetch the complete documentation index at: https://docs.aevyra.ai/llms.txt
Use this file to discover all available pages before exploring further.
Dataset
from aevyra_verdict import Dataset
dataset = Dataset.from_jsonl("data.jsonl")
dataset = Dataset.from_jsonl("data.jsonl", name="my-dataset")
# Explicit format
dataset = Dataset.from_jsonl("sharegpt_data.jsonl", format="sharegpt")
dataset = Dataset.from_jsonl("alpaca_data.jsonl", format="alpaca")
| Parameter | Default | Description |
|---|
path | — | Path to the JSONL file. |
name | filename stem | Display name for the dataset. |
format | "auto" | Input format: "auto", "openai", "sharegpt", or "alpaca". |
dataset = Dataset.from_list([
{"messages": [{"role": "user", "content": "Hello"}], "ideal": "Hi"},
])
# ShareGPT inline
dataset = Dataset.from_list(sharegpt_records, format="sharegpt")
| Parameter | Default | Description |
|---|
items | — | List of records in OpenAI, ShareGPT, or Alpaca format. |
name | "inline" | Display name for the dataset. |
format | "auto" | Input format: "auto", "openai", "sharegpt", or "alpaca". |
### `dataset.filter(**kwargs)`
Return a new dataset containing only conversations where metadata matches all given key-value pairs.
```python
hard = dataset.filter(difficulty="hard")
hard_reasoning = dataset.filter(difficulty="hard", category="reasoning")
dataset.summary()
Return a dict with name, sample count, whether ideals are present, and metadata keys.
{
"name": "data",
"num_conversations": 50,
"has_ideals": True,
"metadata_keys": ["category", "difficulty"]
}
dataset.has_ideals()
Return True if every conversation has an ideal field.
Conversation
Each item in a dataset is a Conversation:
| Property | Type | Description |
|---|
messages | list[Message] | The conversation messages. |
ideal | str | None | The reference answer. |
metadata | dict | Arbitrary metadata. |
prompt_messages | list[dict] | Messages as plain dicts, ready to send to a provider. |
last_user_message | str | None | The last user message in the conversation. |
