# EmoLLM - Large Language Model for Mental Health
[![Contributors][contributors-shield]][contributors-url]
[![Forks][forks-shield]][forks-url]
[![Issues][issues-shield]][issues-url]
[![MIT License][license-shield]][license-url]
[![Stargazers][stars-shield]][stars-url]
EmoLLM
简体中文 | English
Explore the documentation of this project »
View the Demo
·
Report a Bug
·
Propose a New Feature
**EmoLLM** is a series of large language models designed to understand, support and help customers in mental health counseling. It is fine-tuned from the LLM instructions. We really appreciate it if you could give it a star~⭐⭐. The open-sourced configuration is as follows:
| Model | Type |
| :-------------------: | :------: |
| InternLM2_7B_chat | QLORA |
| InternLM2_7B_chat | full fine-tuning |
| InternLM2_1_8B_chat | full fine-tuning |
| InternLM2_20B_chat | LORA |
| Qwen_7b_chat | QLORA |
| Qwen1_5-0_5B-Chat | full fine-tuning |
| Baichuan2_13B_chat | QLORA |
| ChatGLM3_6B | LORA |
| DeepSeek MoE_16B_chat | QLORA |
| Mixtral 8x7B_instruct | QLORA |
| …… | …… |
Everyone is welcome to contribute to this project ~
---
The Model aims to fully understand and promote the mental health of individuals, groups, and society. This model typically includes the following key components:
- Cognitive factors: Involving an individual's thought patterns, belief systems, cognitive biases, and problem-solving abilities. Cognitive factors significantly impact mental health as they affect how individuals interpret and respond to life events.
- Emotional factors: Including emotion regulation, emotional expression, and emotional experiences. Emotional health is a crucial part of mental health, involving how individuals manage and express their emotions and how they recover from negative emotions.
- Behavioral factors: Concerning an individual's behavior patterns, habits, and coping strategies. This includes stress management skills, social skills, and self-efficacy, which is the confidence in one's abilities.
- Social environment: Comprising external factors such as family, work, community, and cultural background, which have direct and indirect impacts on an individual's mental health.
- Physical health: There is a close relationship between physical and mental health. Good physical health can promote mental health and vice versa.
- Psychological resilience: Refers to an individual's ability to recover from adversity and adapt. Those with strong psychological resilience can bounce back from challenges and learn and grow from them.
- Prevention and intervention measures: The Mental Health Grand Model also includes strategies for preventing psychological issues and promoting mental health, such as psychological education, counseling, therapy, and social support systems.
- Assessment and diagnostic tools: Effective promotion of mental health requires scientific tools to assess individuals' psychological states and diagnose potential psychological issues.
### Recent Updates
- 【2024.3.12】 Released on Baidu Flying Pulp Platform [aiwei](https://aistudio.baidu.com/community/app/63335)
- 【2024.3.11】 **EmoLLM V2.0 is greatly improved in all scores compared to EmoLLM V1.0. Surpasses the performance of Role-playing ChatGPT on counseling tasks!**, [Click to experience EmoLLM V2.0](https://openxlab.org.cn/apps/detail/Farewell1/EmoLLMV2.0), update [dataset statistics and details](./datasets/), [Roadmap](./assets/Roadmap_ZH.png)
- 【2024.3.9】 Add concurrency acceleration [QA pair generation](./scripts/qa_generation/), [RAG pipeline](./rag/)
- 【2024.3.3】 [Based on InternLM2-7B-chat full fine-tuned version EmoLLM V2.0 open sourced](https://openxlab.org.cn/models/detail/ajupyter/EmoLLM_internlm2_7b_full), need two A100*80G, update professional evaluation, see [evaluate](./evaluate/), update PaddleOCR-based PDF to txt tool scripts, see [scripts](./scripts/).
- 【2024.2.29】 Updated objective assessment calculations, see [evaluate](./evaluate/) for details. A series of datasets have also been updated, see [datasets](./datasets/) for details.
- 【2024.2.27】 Updated English README and a series of datasets (licking dogs and one-round dialogue)
- 【2024.2.23】The "Gentle Lady Psychologist Ai Wei" based on InternLM2_7B_chat_qlora was launched. [Click here to obtain the model weights](https://openxlab.org.cn/models/detail/ajupyter/EmoLLM_aiwei), [configuration file](xtuner_config/aiwei-internlm2_chat_7b_qlora.py), [online experience link](https://openxlab.org.cn/apps/detail/ajupyter/EmoLLM-aiwei)
- 【2024.2.23】Updated [several fine-tuning configurations](/xtuner_config/), added [data_pro.json](/datasets/data_pro.json) (more quantity, more comprehensive scenarios, richer content) and [aiwei.json](/datasets/aiwei.json) (dedicated to the gentle lady role-play, featuring Emoji expressions), the "Gentle Lady Psychologist Ai Wei" is coming soon.
- 【2024.2.18】 The full fine-tuned version based on Qwen1_5-0_5B-Chat has been [open-sourced](https://www.modelscope.cn/models/aJupyter/EmoLLM_Qwen1_5-0_5B-Chat_full_sft/summary). Friends with limited computational resources can now dive in and explore it.
View More
- 【2024.2.6】 [Open-sourced based on the Qwen1_5-0_5B-Chat full-scale fine-tuned version](https://www.modelscope.cn/models/aJupyter/EmoLLM_Qwen1_5-0_5B-Chat_full_sft/summary), friends with limited computing power can start experimenting~
- 【2024.2.5】 The project has been promoted by the official WeChat account NLP Engineering. Here's the [link](https://mp.weixin.qq.com/s/78lrRl2tlXEKUfElnkVx4A) to the article. Welcome everyone to follow!! 🥳🥳
- 【2024.2.3】 [Project Vedio](https://www.bilibili.com/video/BV1N7421N76X/) at bilibili 😊
- 【2024.1.27】 Complete data construction documentation, fine-tuning guide, deployment guide, Readme, and other related documents 👏
- 【2024.1.25】 EmoLLM V1.0 has deployed online https://openxlab.org.cn/apps/detail/jujimeizuo/EmoLLM 😀
### Roadmap
## Contents
- [EmoLLM - Large Language Model for Mental Health](#emollm---large-language-model-for-mental-health)
- [Recent Updates](#recent-updates)
- [Roadmap](#roadmap)
- [Contents](#contents)
- [Pre-development Configuration Requirements.](#pre-development-configuration-requirements)
- [**User Guide**](#user-guide)
- [File Directory Explanation](#file-directory-explanation)
- [Data Construction](#data-construction)
- [Fine-tuning Guide](#fine-tuning-guide)
- [Deployment Guide](#deployment-guide)
- [RAG (Retrieval Augmented Generation) Pipeline](#rag-retrieval-augmented-generation-pipeline)
- [Frameworks Used](#frameworks-used)
- [How to participate in this project](#how-to-participate-in-this-project)
- [Version control](#version-control)
- [Authors (in no particular order)](#authors-in-no-particular-order)
- [Copyright Notice](#copyright-notice)
- [Acknowledgments](#acknowledgments)
- [Star History](#star-history)
- [🌟 Contributors](#-contributors)
- [Communication group](#communication-group)
###### Pre-development Configuration Requirements.
- A100 40G (specifically for InternLM2_7B_chat + qlora fine-tuning + deepspeed zero2 optimization)
###### **User Guide**
1. Clone the repo
```sh
git clone https://github.com/SmartFlowAI/EmoLLM.git
```
1. Read in sequence or read sections you're interested in:
- [File Directory Explanation](#file-directory-explanation)
- [Data Construction](#data-construction)
- [Fine-tuning Guide](#fine-tuning-guide)
- [Deployment Guide](#deployment-guide)
- View More Details
### File Directory Explanation
```
├─assets: Image Resources
├─datasets: Dataset
├─demo: demo scripts
├─generate_data: Data Generation Guide
│ └─xinghuo
├─scripts: Some Available Tools
└─xtuner_config:Fine-tuning Guide
└─images
```
### Data Construction
- Please read the [Data Construction Guide ](generate_data/tutorial.md)for reference.
- The dataset used for this fine-tuning can be found at [datasets](datasets/data.json)
### Fine-tuning Guide
For details, see the [fine-tuning guide](xtuner_config/README.md)
### Deployment Guide
- Demo deployment: see [deployment guide](./demo/README.md) for details.
- Quantitative deployment based on [LMDeploy](https://github.com/InternLM/lmdeploy/): see [deploy](./deploy/lmdeploy.md)
### RAG (Retrieval Augmented Generation) Pipeline
- See [RAG](./rag/)
Additional Details
### Frameworks Used
- [Xtuner](https://github.com/InternLM/xtuner)
- [Transformers](https://github.com/huggingface/transformers)
- [Pytorch](https://pytorch.org/)
- [LMDeploy](https://github.com/InternLM/lmdeploy/): for quantitative deployment
- [Stremlit](https://streamlit.io/): for building demos
- [DeepSpeed](https://github.com/microsoft/DeepSpeed): for parallel training
- …
#### How to participate in this project
Contributions make the open-source community an excellent place for learning, inspiration, and creation. Any contribution you make is greatly appreciated.
1. Fork the Project
2. Create your Feature Branch (`git checkout -b feature/AmazingFeature`)
3. Commit your Changes (`git commit -m 'Add some AmazingFeature'`)
4. Push to the Branch (`git push origin feature/AmazingFeature`)
5. Open a Pull Request
### Version control
This project uses Git for version control. You can see the currently available versions in the repository.
### Authors (in no particular order)
| Username | School/Organization | Remarks | Contributions |
| :-------: | :-------------------: | :------------------: | :--------: |
| [aJupyter](https://github.com/aJupyter) | Nankai University, Master's student | DataWhale member | Project initiator |
| [jujimeizuo](https://github.com/jujimeizuo) | Jiangnan University, Master's student | | |
| [Smiling-Weeping-zhr](https://github.com/Smiling-Weeping-zhr) | Harbin Institute of Technology (Weihai), Undergraduate student | | |
| [8baby8](https://github.com/8baby8) | PaddlePaddle Pilot Team Regional Director | Wenxin Large Model core developer | |
| [zxazys](https://github.com/zxazys) | Nankai University, Master's student | | |
| [MING-ZCH](https://github.com/MING-ZCH) | Huazhong University of Science and Technology, Undergraduate student | | |
| [JasonLLLLLLLLLLL](https://github.com/JasonLLLLLLLLLLL) | SWUFE (Southwestern University of Finance and Economics) | | |
| [MrCatAI](https://github.com/MrCatAI) | AI Mover | | |
| [ZeyuBa](https://github.com/ZeyuBa) | Institute of Automation, Master's student | | |
| [aiyinyuedejustin](https://github.com/aiyinyuedejustin) | University of Pennsylvania, Master's student | | |
| [Nobody-ML](https://github.com/Nobody-ML) | China University of Petroleum (East China), Undergraduate student | | |
| [chg0901](https://github.com/chg0901) | [MiniSora](https://github.com/mini-sora/minisora) |Maintainer and Admin|Data Cleaning and Docs Translation|
| [Mxoder](https://github.com/Mxoder) | Beihang University, Undergraduate student | | |
| [Anooyman](https://github.com/Anooyman) | Nanjing University of Science and Technology, Master's student | | |
| [Vicky-3021](https://github.com/Vicky-3021) | Xidian University, Master's student (Research Year 0) | | |
| [SantiagoTOP](https://github.com/santiagoTOP) | Taiyuan University of Technology, Master's student | | |
### Copyright Notice
The project is licensed under the MIT License. Please refer to the details
[LICENSE](https://github.com/aJupyter/EmoLLM/blob/master/LICENSE)
### Acknowledgments
- [Sanbu](https://github.com/sanbuphy)
- [Shanghai Artificial Intelligence Laboratory](https://www.shlab.org.cn/)
- [Vanin](https://github.com/vansin)
- [Bloom up (WeChat Official Account Promotion)](https://mp.weixin.qq.com/s/78lrRl2tlXEKUfElnkVx4A)
- Abu (M.A. in Psychology, Peking University)
## Star History
[![Star History Chart](https://api.star-history.com/svg?repos=SmartFlowAI/EmoLLM&type=Date)](https://star-history.com/#SmartFlowAI/EmoLLM&Date)
## 🌟 Contributors
[![EmoLLM contributors](https://contrib.rocks/image?repo=SmartFlowAI/EmoLLM&max=50)](https://github.com/SmartFlowAI/EmoLLM/graphs/contributors)
[your-project-path]: SmartflowAI/EmoLLM
[contributors-shield]: https://img.shields.io/github/contributors/SmartflowAI/EmoLLM.svg?style=flat-square
[contributors-url]: https://github.com/SmartflowAI/EmoLLM/graphs/contributors
[forks-shield]: https://img.shields.io/github/forks/SmartflowAI/EmoLLM.svg?style=flat-square
[forks-url]: https://github.com/SmartflowAI/EmoLLM/network/members
[stars-shield]: https://img.shields.io/github/stars/SmartflowAI/EmoLLM.svg?style=flat-square
[stars-url]: https://github.com/SmartflowAI/EmoLLM/stargazers
[issues-shield]: https://img.shields.io/github/issues/SmartflowAI/EmoLLM.svg?style=flat-square
[issues-url]: https://img.shields.io/github/issues/SmartflowAI/EmoLLM.svg
[license-shield]: https://img.shields.io/github/license/SmartflowAI/EmoLLM.svg?style=flat-square
[license-url]: https://github.com/SmartflowAI/EmoLLM/blob/main/LICENSE
## Communication group
- If it fails, go to the Issue section.