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https://github.com/samad101/chino
Chino is a terminal-based chatbot based on ChatGPT.
https://github.com/samad101/chino
chatbot langchain openai python rag
Last synced: 15 days ago
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Chino is a terminal-based chatbot based on ChatGPT.
- Host: GitHub
- URL: https://github.com/samad101/chino
- Owner: SAMAD101
- License: mit
- Created: 2023-09-20T11:38:18.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-05-15T11:45:50.000Z (6 months ago)
- Last Synced: 2024-11-02T14:51:51.266Z (16 days ago)
- Topics: chatbot, langchain, openai, python, rag
- Language: Python
- Homepage: https://pypi.org/project/chinoai/
- Size: 1.77 MB
- Stars: 21
- Watchers: 2
- Forks: 4
- Open Issues: 4
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
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README
# Chino 🌸
Chino is a terminal-based chatbot. Powered by OpenAI.
Uses RAG to generate responses based on user-provided documents.
## 🐍 Python Version Support
This project is designed to be compatible with specific versions of Python for optimal performance and stability.
### Supported Python Version
- **Python 3.11.7**
> ❗️ For the best experience and performance, it is recommended to use the version mentioned above.
Before diving into the project, ensure that you have the correct Python version installed. To check the version of Python you currently have, execute the following command in your terminal:
```bash
python --version
```
### 🐍 Installing Python 3.11.7 with `pyenv`
**Protip:** Managing multiple Python versions is a breeze with [pyenv](https://github.com/pyenv/pyenv). It allows you to seamlessly switch between different Python versions without the need to reinstall them.
If you haven't installed `pyenv` yet, follow their [official guide](https://github.com/pyenv/pyenv) to set it up.
Once you have `pyenv` ready, install the recommended Python version by running:
```bash
pyenv install 3.11.7
```
> When you navigate to this project's directory in the future, `pyenv` will automatically select the recommended Python version, thanks to the `.python-version` file in the project root.
## Installation 🛠️
### Install using pip:
```bash
pip install chinoai
```
### Build from source:
- Clone the repository:
```bash
git clone https://github.com/SAMAD101/Chino.git
```
- Navigate to the project Directory:
```bash
cd Chino
```
- Install using:
```bash
pip install .
```
# 📦 Setup for development
### Setting Up the Project for development
#### Contributing to the Project:
> Refer to the [Contributing Guide](CONTRIBUTING.md) for detailed information on how to contribute to this project, including setup instructions for development.
> And also refer to the [Code of Conduct](CODE_OF_CONDUCT.md) for the community guidelines.
- **Fork the Repository**:
Get your own fork/copy of the project from GitHub by clicking the "Fork" button.
- **Clone the forked Repository**
```bash
git clone
```
- **Navigate to the Project Directory**:
```bash
cd Chino
```
- **Install the Project (from source)**:
Use PDM to run the project:
```bash
python3 -m pip install -e .
```
- **Install pre-commit hooks**:
```bash
pre-commit install
```
- **Run the project:**
```bash
chino --help
```
## ⚠️ Note:
You will need an OpenAI API key to make it work. Get your API key from OpenAI website and set it as an environment variable:
```bash
export OPENAI_API_KEY=""
```
## Usage 📖
Commands and options are available by running:
```bash
chino --help
```
For using the Retrieval Augmented Generation (RAG) features, follow these steps:
1. You will need to put your documents in the `~/.local/share/chino/data` directory. If not there, make one.
2. Also,make sure you have a directory: `~/.local/share/chino/chroma`. This directory will contain the OpenAI embeddings (embedding vectors) for the documents.
3. Process the documents and create the embeddings using the following command:
```bash
chino migrate
```
> The directory data and chroma directories will be made more configurable in the future releases.
### Using Query mode:
Once your documents are processed. You can use the query mode to give prompts for the documents [RAG].
Start Chino by running:
```bash
chino start
```
and use `\q:` before your prompt to use it in query mode.