https://github.com/nmf2/chatbot-api
API for a chatbot created with Chatbot Manager
https://github.com/nmf2/chatbot-api
api-server chatbots flask machine-learning python3
Last synced: 3 months ago
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API for a chatbot created with Chatbot Manager
- Host: GitHub
- URL: https://github.com/nmf2/chatbot-api
- Owner: nmf2
- License: gpl-3.0
- Created: 2018-07-25T17:24:42.000Z (almost 8 years ago)
- Default Branch: master
- Last Pushed: 2018-08-18T20:23:36.000Z (almost 8 years ago)
- Last Synced: 2025-03-21T17:30:56.737Z (over 1 year ago)
- Topics: api-server, chatbots, flask, machine-learning, python3
- Language: Python
- Size: 52.7 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Swagger generated server
## Overview
This server was generated by the [swagger-codegen](https://github.com/swagger-api/swagger-codegen) project. By using the
[OpenAPI-Spec](https://github.com/swagger-api/swagger-core/wiki) from a remote server, you can easily generate a server stub. This
is an example of building a swagger-enabled Flask server.
This example uses the [Connexion](https://github.com/zalando/connexion) library on top of Flask.
## Requirements
Python 3.5.2+
## Usage
To run the server, please execute the following from the root directory:
```
pip3 install -r requirements.txt
python3 -m chatbot_server
```
and open your browser to here:
```
http://localhost:8080/nmf21/chatbotModel/1.0.0/ui/
```
Your Swagger definition lives here:
```
http://localhost:8080/nmf21/chatbotModel/1.0.0/swagger.json
```
To launch the integration tests, use tox:
```
sudo pip install tox
tox
```
## Running with Docker
To run the server on a Docker container, please execute the following from the root directory:
```bash
# building the image
docker build -t chatbot_server .
# starting up a container
docker run -p 8080:8080 chatbot_server
```