

# **CAMEL: Communicative Agents for “Mind” Exploration of Large Scale Language Model Society**
- **Github:** https://github.com/lightaime/camel
- **Website:** https://www.camel-ai.org/
- **Arxiv Paper:** https://arxiv.org/abs/2303.17760

## Dataset Summary

The original AI Society dataset is in English and is composed of 25K conversations between two gpt-3.5-turbo agents. The dataset is obtained by running role-playing for a combination of 50 user roles and 50 assistant roles with each combination running over 10 tasks. 

We provide translated versions of the original English dataset into ten languages: Arabic, Chinese, Korean, Japanese, Hindi, Russian, Spanish, French, German, and Italian in ".zip" format.

The dataset was translated by a prompting gpt-3.5-turbo to translate presented sentences into a particular language. 

**Note:** Sometimes gpt decides not to translate particular keywords such as "Instruction", "Input", and "Solution". Therefore, cleaning might be needed depended on your use case.

## Data Fields

**The data fields for chat format (`ai_society_chat_{language}.zip`) are as follows:**

* `input`: {assistant\_role\_index}\_{user\_role\_index}\_{task\_index}, for example 001_002_003 refers to assistant role 1, user role 2, and task 3 from our text assistant role names, user role names and task text files.
* `role_1`: assistant role
* `role_2`: user role
* `original_task`: the general assigned task for the assistant and user to cooperate on.
* `specified_task`: the task after task specifier, this task is more specific than the original task.
* `message_k`: refers to the k<sup>_th_</sup> message of the conversation.
  *  `role_type`: refers to whether the agent is an assistant or a user.
  *  `role_name`: refers to the assigned assistant/user role.
  *  `role`: refers to the role of the agent during the message for openai api. [usually not needed]
  *  `content`: refers to the content of the message.
* `termination_reason`: refers to the reason of termination of the chat.
* `num_messages`: refers to the total number of messages in the chat.

**Download in python**
```
from huggingface_hub import hf_hub_download
# replace {language} by one of the following: ar, zh, ko, ja, hi, ru, es, fr, de, it
hf_hub_download(repo_id="camel-ai/ai_society_translated", repo_type="dataset", filename="ai_society_chat_{language}.zip",
                local_dir="datasets/", local_dir_use_symlinks=False) 
```

### Citation

```
@misc{li2023camel,
      title={CAMEL: Communicative Agents for "Mind" Exploration of Large Scale Language Model Society}, 
      author={Guohao Li and Hasan Abed Al Kader Hammoud and Hani Itani and Dmitrii Khizbullin and Bernard Ghanem},
      year={2023},
      eprint={2303.17760},
      archivePrefix={arXiv},
      primaryClass={cs.AI}
}
```

## Disclaimer:

This data was synthetically generated by gpt-3.5-turbo and might contain incorrect information. The dataset is there only for research purposes.

---
license: cc-by-nc-4.0
---
task_categories:text-generation language:ar language:zh language:ko language:ja language:hi language:ru language:es language:fr language:de language:it license:cc-by-nc-4.0 instruction-finetuning arxiv:2303.17760 region:us
{"language": ["ar", "zh", "ko", "ja", "hi", "ru", "es", "fr", "de", "it"], "license": "cc-by-nc-4.0", "task_categories": ["text-generation"], "pretty_name": "CAMEL AI Society Translated", "tags": ["instruction-finetuning"], "arxiv": 2303.1776, "extra_gated_prompt": "By using this data, you acknowledge and agree to utilize it solely for research purposes, recognizing that the dataset may contain inaccuracies due to its artificial generation through ChatGPT.", "extra_gated_fields": {"Name": "text", "Email": "text"}, "I will adhere to the terms and conditions of this dataset": "checkbox"}
TAGS
#task_categories-text-generation #language-Arabic #language-Chinese #language-Korean #language-Japanese #language-Hindi #language-Russian #language-Spanish #language-French #language-German #language-Italian #license-cc-by-nc-4.0 #instruction-finetuning #arxiv-2303.17760 #region-us 



# CAMEL: Communicative Agents for “Mind” Exploration of Large Scale Language Model Society
- Github: URL
- Website: URL
- Arxiv Paper: URL

## Dataset Summary

The original AI Society dataset is in English and is composed of 25K conversations between two gpt-3.5-turbo agents. The dataset is obtained by running role-playing for a combination of 50 user roles and 50 assistant roles with each combination running over 10 tasks. 

We provide translated versions of the original English dataset into ten languages: Arabic, Chinese, Korean, Japanese, Hindi, Russian, Spanish, French, German, and Italian in ".zip" format.

The dataset was translated by a prompting gpt-3.5-turbo to translate presented sentences into a particular language. 

Note: Sometimes gpt decides not to translate particular keywords such as "Instruction", "Input", and "Solution". Therefore, cleaning might be needed depended on your use case.

## Data Fields

The data fields for chat format ('ai_society_chat_{language}.zip') are as follows:

* 'input': {assistant\_role\_index}\_{user\_role\_index}\_{task\_index}, for example 001_002_003 refers to assistant role 1, user role 2, and task 3 from our text assistant role names, user role names and task text files.
* 'role_1': assistant role
* 'role_2': user role
* 'original_task': the general assigned task for the assistant and user to cooperate on.
* 'specified_task': the task after task specifier, this task is more specific than the original task.
* 'message_k': refers to the k<sup>_th_</sup> message of the conversation.
  *  'role_type': refers to whether the agent is an assistant or a user.
  *  'role_name': refers to the assigned assistant/user role.
  *  'role': refers to the role of the agent during the message for openai api. [usually not needed]
  *  'content': refers to the content of the message.
* 'termination_reason': refers to the reason of termination of the chat.
* 'num_messages': refers to the total number of messages in the chat.

Download in python


## Disclaimer:

This data was synthetically generated by gpt-3.5-turbo and might contain incorrect information. The dataset is there only for research purposes.

---
license: cc-by-nc-4.0
---
# CAMEL: Communicative Agents for “Mind” Exploration of Large Scale Language Model Society
- Github: URL
- Website: URL
- Arxiv Paper: URL ## Dataset Summary

The original AI Society dataset is in English and is composed of 25K conversations between two gpt-3.5-turbo agents. The dataset is obtained by running role-playing for a combination of 50 user roles and 50 assistant roles with each combination running over 10 tasks. 

We provide translated versions of the original English dataset into ten languages: Arabic, Chinese, Korean, Japanese, Hindi, Russian, Spanish, French, German, and Italian in ".zip" format.

The dataset was translated by a prompting gpt-3.5-turbo to translate presented sentences into a particular language. 

Note: Sometimes gpt decides not to translate particular keywords such as "Instruction", "Input", and "Solution". Therefore, cleaning might be needed depended on your use case. ## Data Fields

The data fields for chat format ('ai_society_chat_{language}.zip') are as follows:

* 'input': {assistant\_role\_index}\_{user\_role\_index}\_{task\_index}, for example 001_002_003 refers to assistant role 1, user role 2, and task 3 from our text assistant role names, user role names and task text files.
* 'role_1': assistant role
* 'role_2': user role
* 'original_task': the general assigned task for the assistant and user to cooperate on.
* 'specified_task': the task after task specifier, this task is more specific than the original task.
* 'message_k': refers to the k<sup>_th_</sup> message of the conversation.
  *  'role_type': refers to whether the agent is an assistant or a user.
  *  'role_name': refers to the assigned assistant/user role.
  *  'role': refers to the role of the agent during the message for openai api. [usually not needed]
  *  'content': refers to the content of the message.
* 'termination_reason': refers to the reason of termination of the chat.
* 'num_messages': refers to the total number of messages in the chat.

Download in python ## Disclaimer:

This data was synthetically generated by gpt-3.5-turbo and might contain incorrect information. The dataset is there only for research purposes.

---
license: cc-by-nc-4.0
---
TAGS
#task_categories-text-generation #language-Arabic #language-Chinese #language-Korean #language-Japanese #language-Hindi #language-Russian #language-Spanish #language-French #language-German #language-Italian #license-cc-by-nc-4.0 #instruction-finetuning #arxiv-2303.17760 #region-us 
 # CAMEL: Communicative Agents for “Mind” Exploration of Large Scale Language Model Society
- Github: URL
- Website: URL
- Arxiv Paper: URL ## Dataset Summary

The original AI Society dataset is in English and is composed of 25K conversations between two gpt-3.5-turbo agents. The dataset is obtained by running role-playing for a combination of 50 user roles and 50 assistant roles with each combination running over 10 tasks. 

We provide translated versions of the original English dataset into ten languages: Arabic, Chinese, Korean, Japanese, Hindi, Russian, Spanish, French, German, and Italian in ".zip" format.

The dataset was translated by a prompting gpt-3.5-turbo to translate presented sentences into a particular language. 

Note: Sometimes gpt decides not to translate particular keywords such as "Instruction", "Input", and "Solution". Therefore, cleaning might be needed depended on your use case. ## Data Fields

The data fields for chat format ('ai_society_chat_{language}.zip') are as follows:

* 'input': {assistant\_role\_index}\_{user\_role\_index}\_{task\_index}, for example 001_002_003 refers to assistant role 1, user role 2, and task 3 from our text assistant role names, user role names and task text files.
* 'role_1': assistant role
* 'role_2': user role
* 'original_task': the general assigned task for the assistant and user to cooperate on.
* 'specified_task': the task after task specifier, this task is more specific than the original task.
* 'message_k': refers to the k<sup>_th_</sup> message of the conversation.
  *  'role_type': refers to whether the agent is an assistant or a user.
  *  'role_name': refers to the assigned assistant/user role.
  *  'role': refers to the role of the agent during the message for openai api. [usually not needed]
  *  'content': refers to the content of the message.
* 'termination_reason': refers to the reason of termination of the chat.
* 'num_messages': refers to the total number of messages in the chat.

Download in python ## Disclaimer:

This data was synthetically generated by gpt-3.5-turbo and might contain incorrect information. The dataset is there only for research purposes.

---
license: cc-by-nc-4.0
---
passage: TAGS
#task_categories-text-generation #language-Arabic #language-Chinese #language-Korean #language-Japanese #language-Hindi #language-Russian #language-Spanish #language-French #language-German #language-Italian #license-cc-by-nc-4.0 #instruction-finetuning #arxiv-2303.17760 #region-us 
# CAMEL: Communicative Agents for “Mind” Exploration of Large Scale Language Model Society
- Github: URL
- Website: URL
- Arxiv Paper: URL## Dataset Summary

The original AI Society dataset is in English and is composed of 25K conversations between two gpt-3.5-turbo agents. The dataset is obtained by running role-playing for a combination of 50 user roles and 50 assistant roles with each combination running over 10 tasks. 

We provide translated versions of the original English dataset into ten languages: Arabic, Chinese, Korean, Japanese, Hindi, Russian, Spanish, French, German, and Italian in ".zip" format.

The dataset was translated by a prompting gpt-3.5-turbo to translate presented sentences into a particular language. 

Note: Sometimes gpt decides not to translate particular keywords such as "Instruction", "Input", and "Solution". Therefore, cleaning might be needed depended on your use case.