# Fabelous-Ai-Chat
#### Video Demo:  https://youtu.be/A5mtqQLF000
#### Description:

This is my Final Project for CS50P. A implementation of a RAG System using Chroma DB and Ollama for the backend, along with customtkinter for the frontend.


## Features
1. Custom GUI built with customtkinter and standard tkinter user interface.
    - optional `terminal` mode, with nice colors provided by the `termcolor` libary
2. RAG system to retrieve and process files from various sources (CSV, HTML, MD, PDF and Webpages) using ChromaDB.
3. Seamless integration with Ollama API for generating responses based on the input text.
4. Supports both context-based and context-free conversations.
5. Code Highlighting: Either highlighted in red within the `terminal` or displayed in a separate widget using the `GUI`, this improves the readability and understanding of code snippets

## Installation
1. Clone the repository or download the project files from: 
`https://gitea.fabelous.app/fabel/Fabelous-Ai-Chat`
2. Install required dependencies by running:
```bash
pip install -r requirements.txt
```
3. To run this project properly, you will need to ensure that the Python 3 and Tkinter libraries arei nstalled.

- For MacOS users who have installed Python 3 via Homebrew, use the following command in your terminal: 
```bash
brew install python-tk
```
- For Linux users, execute the following command in your terminal:
```bash
apt-get install python3-tk
```

## Configuration

Please note that you need access to an Ollama instance with both embeddings model and chat model to use this interface effectively. Ensure that you have set up your instance accordingly before configuring this application.

To configure the Fabelous-Ai-Chat, run the following command and answer the prompts accordingly:

```bash
python project.py --config
```
If you just want to switch for example from `GUI` to `terminal` version type:
```bash
python project.py -m terminal
```

During configuration, you'll be prompted to enter the following information:

- Mode: `gui` or `terminal`
- Base Ollama URL for the LLM e.g.: `http://localhost:11434`
- Base Ollama URL for embeddings e.g.: `http://localhost:11434`
- The base model name e.g: `mistral`
- The base embeddings model name e.g: `mxbai-embed-large`
- Authentication headers for base and embeddings models (if required) 
    - a Authentication could look like this: `{"Authorization": "Token xzy"}`

After providing this information, your configuration file will be saved in the `config` folder as `config.json`.



## Usage in Terminal Mode
To use the Fabelous-Ai-Chat in terminal mode, run the following command and provide a prompt:
```bash
python project.py -p "Your prompt here"
```
You can also provide an input file/link using the -f option:
```bash
python project.py -p "Your prompt here" -f "path/to/yourfile.csv"
```

## Usage in GUI Mode
To use the Fabelous-Ai-Chat in GUI mode, simply run the following command:
```bash
python project.py
```

## Supported files
You can provide the following files / links as context to Ollama:
- .csv
- .html
- .md
- .pdf
- links (Note that only SSL-secured websites are supported)

## How the Rag is working in the GUI:

The RAG is designed to create conversational agents that leverage external sources for more accurate responses. The `Rag` class in `Rag.py` plays a crucial role in this process. When a user submits a message through the chat interface, the `get_response_from_ollama` method comes into play. This method checks for any context associated with the message and processes it if required.


If necessary, it calls the `receive_data` method of the `Rag` instance to handle new context and fetch relevant data using the `get_file` method. The fetched content is then added to a database, which is not persistent. If you close it, you will lose the data. Following that, the `get_request` method of the Rag instance is called with the user's message as input. It generates a response, utilizing the contents of the Chroma DB for better accuracy, with the selected model from the Ollama instance.
For better results, the last five responses are featured in the context, if no other context is provided.

## Difference to terminal mode:
In `terminal` mode, context is provided through command-line arguments as a single file. This approach has its limitations, as it only allows for a single context file during a conversation, restricting versatility when dealing with diverse contexts.

## License
`Fabelous-Ai-Chat` is made available under the [MIT license](.../.././LICENSE). For more details, please refer to the LICENSE file included in the distribution.

This project uses the models from [Mistral AI](https://mistral.ai/) and [Mixedbread.ai](https://www.mixedbread.ai/) as standard, which are made available under the Apache 2.0 license. For more details, check out there model pages on Ollama:
[Mistral](https://ollama.com/library/mistral) and [mxbai-embed-large](https://ollama.com/library/mxbai-embed-large).
This project also uses [ChromaDB](https://www.trychroma.com/) as the vector database. It is also available under the Apache 2.0 License. For more information checkout it's [GitHub](https://github.com/chroma-core/chroma) Page.