使用 Flask 部署 PyTorch聊天机器人_css_python_html_JavaScript_代码_下载

# Chatbot Deployment with Flask and JavaScript In this tutorial we deploy the chatbot I created in [this](https://github.com/python-engineer/pytorch-chatbot) tutorial with Flask and JavaScript. This gives 2 deployment options: - Deploy within Flask app with jinja2 template - Serve only the Flask prediction API. The used html and javascript files can be included in any Frontend application (with only a slight modification) and can run completely separate from the Flask App then. ## Initial Setup: This repo currently contains the starter files. Clone repo and create a virtual environment ``` $ git clone https://github.com/python-engineer/chatbot-deployment.git $ cd chatbot-deployment $ python3 -m venv venv $ . venv/bin/activate ``` Install dependencies ``` $ (venv) pip install Flask torch torchvision nltk ``` Install nltk package ``` $ (venv) python >>> import nltk >>> nltk.download('punkt') ``` Modify `intents.json` with different intents and responses for your Chatbot Run ``` $ (venv) python train.py ``` This will dump data.pth file. And then run the following command to test it in the console. ``` $ (venv) python chat.py ``` Now for deployment follow my tutorial to implement `app.py` and `app.js`. ## Watch the Tutorial [](https://youtu.be/a37BL0stIuM) [https://youtu.be/a37BL0stIuM](https://youtu.be/a37BL0stIuM) ## Note In the video we implement the first approach using jinja2 templates within our Flask app. Only slight modifications are needed to run the frontend separately. I put the final frontend code for a standalone frontend application in the [standalone-frontend](/standalone-frontend) folder. ## Credits: This repo was used for the frontend code: https://github.com/hitchcliff/front-end-chatjs