Le Potato

Simple. elegant LLM Chat Inference

Get it working

Open up your terminal (mac/linux) / powershell terminal (window) and navigate to the project directory
First of all to be safe, let's create a virtual environment!
Install on Windows
```
python -m venv .venv
```
Install on Linux / MacOs
```
python3 -m venv .venv
```
Now we need to activate it to be able to use Le Potato without libraries error!
Install on Windows
```
.venv\Scripts\activate.ps1
```
Install on Linux / MacOs
```
source .venv/bin/activate
```
Now we are inside our virtual environment...You will have to install all python libraries to be able to use the web app by using:
Install on Windows
```
pip install .
```
Install on Linux / MacOs
```
pip3 install .
```
While it is installing, you should check and modify the configuration file
There you will find some samplers and other settings to modify to host model...

database/configuration.yaml

Once you are done, you can launch the web server if the libraries are done installing!
Run server on Windows
```
python main.py
```
Run server on Linux / MacOs
```
python3 main.py
```
Once it is all set you can open the website url, by default it is

http://127.0.0.1:1234/

It will look like this:

Here is a demo of a normal chat

  src\frontend\static\images

There you will drop your background you wanted and just rename it toji.jpg to make it easier.

How to use the RAG from the UI?

You need to add -rag followed with your rag query that will be used for the retrieval. (Will not be showed to the model )
Then you add a new line and write down your query for the model.

Example:

-rag Who is the author?
Do you know the author ?

LLM will only see the second line and the rag query will add retrieval results to your query!

Name		Name	Last commit message	Last commit date
Latest commit History 15 Commits
database		database
src		src
README.md		README.md
main.py		main.py
poetry.lock		poetry.lock
pyproject.toml		pyproject.toml