https://github.com/naver-ai/chacha-chatbot
https://github.com/naver-ai/chacha-chatbot
ai chatbot conversational-agents emotion hci
Last synced: 3 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/naver-ai/chacha-chatbot
- Owner: naver-ai
- License: mit
- Created: 2023-07-07T02:31:39.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2025-12-29T04:54:36.000Z (6 months ago)
- Last Synced: 2026-01-01T01:05:06.931Z (6 months ago)
- Topics: ai, chatbot, conversational-agents, emotion, hci
- Language: Python
- Homepage: https://naver-ai.github.io/chacha
- Size: 1.22 MB
- Stars: 41
- Watchers: 0
- Forks: 5
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# ChaCha (CHAtbot for CHildren's emotion Awareness): LLM-Driven Chatbot for Enhancing Emotional Awareness in Children
This repository is a source code of the chatbot implementation presented in the ACM CHI 2024 paper, titled "**ChaCha: Leveraging Large Language Models to Prompt Children to Share Their Emotions about Personal Events**."
> Woosuk Seo, Chanmo Yang, and Young-Ho Kim. 2024.
> ChaCha: Leveraging Large Language Models to Prompt Children to Share Their Emotions about Personal Events.
> In Proceedings of ACM CHI Conference on Human Factors in Computing Systems (CHI'24). To appear.
## Project Website
https://naver-ai.github.io/chacha/
## System Requirements
1. Python 3.11.2 or higher
2. [Poetry](https://python-poetry.org/docs/) - Python project dependency manager
3. NodeJS and NPM - tested on 18.17.0
4. Paid OpenAI API key (ChaCha uses GPT-3.5 and GPT-4 models internally).
## How To Run
### Installation
1. In the root directory, install dependencies using `poetry`.
```shell
> poetry install
```
2. Install frontend Node dependencies
```shell
> cd frontend
> npm install
> cd ..
```
4. Run the setup script and follow the steps. It would help if you prepared the OpenAI API Key ready.
```shell
> poetry run python setup.py
```
### Testing Chatbot on Command Line
3. Run chat.py on the command line:
```shell
> poetry run python chat.py
```
### Testing Chatbot on Web
#### Running in development mode
1. **Run backend server**
```shell
> poetry run python main.py
```
The default port is 8000. You can set `--port` to designate manually.
```shell
> poetry run python main.py --port 3000
```
2. **Run frontend server**
The frontend is implemented with React in TypeScript. The development server is run on [Parcel](https://parceljs.org/).
```shell
> cd frontend
> npm install <-- Run this to install dependencies
> npm run dev
```
Access http://localhost:8888 on web browser.
You can perform the above steps using a shell script:
```shell
> sh ./run-web-dev.sh
```
#### Running in production mode
The backend server can serve the frontend web under the hood via the same port.
To activate this, build the frontend code once:
```shell
> cd frontend
> npm run build
```
Then run the backend server:
```shell
> cd ..
> poetry run python main.py --production --port 80
```
Access http://localhost on web browser.
## Analysis of Chat Logs
### Chat Session Reviewing on Web
A session chat can be reviewed by visiting `[domain]/share/{session_id}`. There, you can also download the chat logs in CSV.
### Log Files
To keep the framework lightweight, ChaCha leverages a file storage instead of a database. The session information and chat messages are stored in `./data/sessions/{session_name}` in real time.
In the session directory, `info.json` maintains the metadata and the global configuration of the current session. For example:
```json
{
"id": "User_001",
"turns": 1,
"response_generator": {
"state_history": [
[
"explore",
null
]
],
"verbose": false,
"payload_memory": {},
"user_name": "John",
"user_age": 12,
"locale": "kr"
}
}
```
In the same location, `dialogue.jsonl` keeps the list of chat messages in a format of [JsonLines](https://jsonlines.org/), where each message is formatted as a single-lined json object.
## Authors of the Code
* Young-Ho Kim (NAVER AI Lab) - Maintainer (yghokim@younghokim.net)
* Woosuk Seo (Intern at NAVER AI Lab, PhD candidate at University of Michigan)
## Acknowledgments
* This work was supported by NAVER AI
Lab through a research internship.
* The conversational flow design of ChaCha is grounded in Woosuk Seo’s dissertation research, which was supported by National Science Foundation CAREER Grant #1942547 (PI: Sun Young Park), advised by Sun
Young Park and Mark S. Ackerman, who are instrumental
in shaping this work.