chatbot / README.md
Evan Lesmez
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---
title: lv-recipe-chatbot
emoji: 🫑
colorFrom: green
colorTo: indigo
sdk: gradio
sdk_version: 3.23.0
app_file: app.py
pinned: false
license: unknown
---
# lv-recipe-chatbot
<!-- WARNING: THIS FILE WAS AUTOGENERATED! DO NOT EDIT! -->
This file will become your README and also the index of your
documentation.
## Install
``` sh
pip install lv_recipe_chatbot
```
## How to use
``` python
from dotenv import load_dotenv
load_dotenv()
app.launch_demo()
```
Running on local URL: http://127.0.0.1:7860
To create a public link, set `share=True` in `launch()`.
or
``` sh
python3 app.py
```
## Dev quick-start
`git clone` the repo
``` sh
cd lv-recipe-chatbot
```
Make sure to use the version of python specified in `py_version.txt`
Create a virtual environment.
``` sh
python3 -m venv env
```
Activate the env and install dependencies.
``` sh
source env/bin/activate
pip install -r requirements.txt
pip install -r requirements/dev.txt
```
To make the Jupyter environment, git friendly: `nbdev_install_hooks`
If you want to render documentation locally, you will want to [install
Quarto](https://nbdev.fast.ai/tutorials/tutorial.html#install-quarto).
`nbdev_install_quarto`
Put API secrets in .env
``` sh
cp .env.example .env
```
Edit .env with your secret key(s). Only `OPEN_AI_KEY` is required.
Then start the Gradio demo from within the virtual environment.
``` sh
python3 app.py
```
Preview documentation
``` sh
nbdev_preview
```
## Dependencies
If a new dependency for development is helpful for developers, add it to
`dev.txt`.
If it is a dependency for the app that is imported in source code, add
it to `core.txt`.
Then run:
``` sh
pipreqs --force
```
This will update our `requirements.txt` to include the dependency as it
should be pinned in the environment.
## Development
[quick nbdev tutorial](https://nbdev.fast.ai/tutorials)
Make changes in `/nbs`.
Update the package files with `nbdev_export` then reimport with
`pip install -e '.[dev]'`
Preview doc `nbdev_preview`
Build docs, test and update README `nbdev_prepare`
## Useful links
- [Task Matrix (Formerly Visual
ChatGPT)](https://github.com/microsoft/TaskMatrix)
- [LangChain](https://python.langchain.com/en/latest/index.html)
- [LLM Prompt Engineering](https://www.promptingguide.ai)
- [OpenAI best practices for
prompts](https://help.openai.com/en/articles/6654000-best-practices-for-prompt-engineering-with-openai-api)