license: apache-2.0
dataset_info:
features:
- name: message_id
dtype: string
- name: parent_id
dtype: string
- name: user_id
dtype: string
- name: created_date
dtype: string
- name: text
dtype: string
- name: role
dtype: string
- name: lang
dtype: string
- name: review_count
dtype: int32
- name: review_result
dtype: bool
- name: deleted
dtype: bool
- name: rank
dtype: int32
- name: synthetic
dtype: bool
- name: model_name
dtype: string
- name: detoxify
struct:
- name: toxicity
dtype: float64
- name: severe_toxicity
dtype: float64
- name: obscene
dtype: float64
- name: identity_attack
dtype: float64
- name: insult
dtype: float64
- name: threat
dtype: float64
- name: sexual_explicit
dtype: float64
- name: message_tree_id
dtype: string
- name: tree_state
dtype: string
- name: emojis
sequence:
- name: name
dtype: string
- name: count
dtype: int32
- name: labels
sequence:
- name: name
dtype: string
- name: value
dtype: float64
- name: count
dtype: int32
splits:
- name: train
num_bytes: 100367999
num_examples: 84437
- name: validation
num_bytes: 5243405
num_examples: 4401
download_size: 41596430
dataset_size: 105611404
language:
- en
- es
- ru
- de
- pl
- th
- vi
- sv
- bn
- da
- he
- it
- fa
- sk
- id
- nb
- el
- nl
- hu
- eu
- zh
- eo
- ja
- ca
- cs
- bg
- fi
- pt
- tr
- ro
- ar
- uk
- gl
- fr
- ko
tags:
- human-feedback
size_categories:
- 10K<n<100K
pretty_name: OpenAssistant Conversations
OpenAssistant Conversations Dataset (OASST1)
Dataset Description
- Homepage: https://www.open-assistant.io/
- Repository: https://github.com/LAION-AI/Open-Assistant
- Paper: TBA on April 17, 2023
Dataset Summary
In an effort to democratize research on large-scale alignment, we release OpenAssistant Conversations (OASST1), a human-generated, human-annotated assistant-style conversation corpus consisting of 161,443 messages distributed across 66,497 conversation trees, in 35 different languages, annotated with 461,292 quality ratings. The corpus is a product of a worldwide crowd-sourcing effort involving over 13,500 volunteers.
Please refer to our paper for further details.
Dataset Structure
This dataset contains demonstrations of human-assistant conversations which were collected on the open-assistant.io website until April, 12 2023.
Conversations are exported as conversation trees with messages as nodes.
The root node of a conversation tree is called the initial prompt. Each message can have
multiple replies. Nodes with more than one reply can have a rank field indicating the
aggregated user preference (the most preferred message has rank 0).
All messages have a role property which can either be "assistant" or "prompter". The roles in conversation threads from prompt to leaf node are stricly alternating between "prompter" and "assistant".
JSON Example: Message
For readability the following JSON examples are shown formatted with indentation on multiple lines. Objects are stored without indentation on a single lines in the actual jsonl files.
{
"message_id": "218440fd-5317-4355-91dc-d001416df62b",
"parent_id": "13592dfb-a6f9-4748-a92c-32b34e239bb4",
"user_id": "8e95461f-5e94-4d8b-a2fb-d4717ce973e4",
"text": "It was the winter of 2035, and artificial intelligence (..)",
"role": "assistant",
"lang": "en",
"review_count": 3,
"review_result": true,
"deleted": false,
"rank": 0,
"synthetic": true,
"model_name": "oasst-sft-0_3000,max_new_tokens=400 (..)",
"labels": {
"spam": { "value": 0.0, "count": 3 },
"lang_mismatch": { "value": 0.0, "count": 3 },
"pii": { "value": 0.0, "count": 3 },
"not_appropriate": { "value": 0.0, "count": 3 },
"hate_speech": { "value": 0.0, "count": 3 },
"sexual_content": { "value": 0.0, "count": 3 },
"quality": { "value": 0.416, "count": 3 },
"toxicity": { "value": 0.16, "count": 3 },
"humor": { "value": 0.0, "count": 3 },
"creativity": { "value": 0.33, "count": 3 },
"violence": { "value": 0.16, "count": 3 }
}
}
JSON Example: Conversation Tree
For readability only a subset of the message properties is shown here.
{
"message_tree_id": "14fbb664-a620-45ce-bee4-7c519b16a793",
"tree_state": "ready_for_export",
"prompt": {
"message_id": "14fbb664-a620-45ce-bee4-7c519b16a793",
"text": "Why can't we divide by 0? (..)",
"role": "prompter",
"lang": "en",
"replies": [
{
"message_id": "894d30b6-56b4-4605-a504-89dd15d4d1c8",
"text": "The reason we cannot divide by zero is because (..)",
"role": "assistant",
"lang": "en",
"replies": [
// ...
]
},
{
"message_id": "84d0913b-0fd9-4508-8ef5-205626a7039d",
"text": "The reason that the result of a division by zero is (..)",
"role": "assistant",
"lang": "en",
"replies": [
{
"message_id": "3352725e-f424-4e3b-a627-b6db831bdbaa",
"text": "Math is confusing. Like those weird Irrational (..)",
"role": "prompter",
"lang": "en",
"replies": [
{
"message_id": "f46207ca-3149-46e9-a466-9163d4ce499c",
"text": "Irrational numbers are simply numbers (..)",
"role": "assistant",
"lang": "en",
"replies": []
},
// ...
]
}
]
}
]
}
}
Please refer to oasst-data for details about the data structure and Python code to read and write jsonl files containing oasst data objects.
Main Dataset Files
Conversation data is provided either as nested messages in trees (extension .trees.jsonl.gz)
or as flat list (table) of messages (extension .messages.jsonl.gz).
Full conversation trees can be reconstructed from flat messages by using the parent_id
and message_id properties to identify the parent-child relationship of messages. The message_tree_id
and tree_state properties (only present in flat messages files) can be used to find all
all messages of a message tree or to select trees by their state.
Ready For Export Trees
2023-04-12_oasst_ready.trees.jsonl.gz 10364 trees with 88838 total messages
2023-04-12_oasst_ready.messages.jsonl.gz 88838 messages
Trees in ready_for_export state without spam and deleted messages including message labels.
The oasst_ready-trees file is normally sufficient for supervised fine-tuning (SFT) & reward model (RM) training.
All Trees
2023-04-12_oasst_all.trees.jsonl.gz 66497 trees with 161443 total messages
2023-04-12_oasst_all.messages.jsonl.gz 161443 messages
All trees including those in states prompt_lottery_waiting (trees that consist of only one message, namely the inital prompt),
aborted_low_grade (trees that stopped growing because the messages had low quality), and halted_by_moderator.
Supplemental Exports: Spam & Prompts
2023-04-12_oasst_spam.messages.jsonl.gz
Messages which were deleted or have a negative review result ("review_result": false).
Beside low quality a frequent reason for message deletion is a wrong language tag.
2023-04-12_oasst_prompts.messages.jsonl.gz
All non-deleted initial prompt messages with positile spam review result of trees in ready_for_export or prompt_lottery_waiting state.
Languages
OpenAssistant Conversations incorporates 35 different languages with a distribution of messages as follows:
Languages with over 1000 messages
- English: 71956
- Spanish: 43061
- Russian: 9089
- German: 5279
- Chinese: 4962
- French: 4251
- Thai: 3042
- Portuguese (Brazil): 2969
- Catalan: 2260
- Korean: 1553
- Ukrainian: 1352
- Italian: 1320
- Japanese: 1018
Languages with under 1000 messages
- Vietnamese: 952
- Basque: 947
- Polish: 886
- Hungarian: 811
- Arabic: 666
- Dutch: 628
- Swedish: 512
- Turkish: 454
- Finnish: 386
- Czech: 372
- Danish: 358
- Galician: 339
- Hebrew: 255
- Romanian: 200
- Norwegian Bokmål: 133
- Indonesian: 115
- Bulgarian: 95
- Bengali: 82
- Persian: 72
- Greek: 66
- Esperanto: 59
- Slovak: 19
Contact
- Discord Open Assistant Discord Server
- GitHub: LAION-AI/Open-Assistant
- E-Mail: open-assistent@laion.ai (yes, with e)