https://github.com/chatopera/deep-qa

Question and Answering Model with TensorFlow
https://github.com/chatopera/deep-qa

bot-model deepqa docker python tensorflow

Last synced: 3 months ago
JSON representation

Question and Answering Model with TensorFlow

Host: GitHub
URL: https://github.com/chatopera/deep-qa
Owner: chatopera
License: apache-2.0
Created: 2017-05-19T06:03:16.000Z (about 8 years ago)
Default Branch: master
Last Pushed: 2022-06-21T21:15:39.000Z (almost 3 years ago)
Last Synced: 2024-04-14T20:20:44.070Z (about 1 year ago)
Topics: bot-model, deepqa, docker, python, tensorflow
Language: Python
Homepage:
Size: 9.57 MB
Stars: 32
Watchers: 4
Forks: 7
Open Issues: 8
Metadata Files:
- Readme: README.md
- License: LICENSE

Awesome Lists containing this project

README

# Note, this repo is deprecated.

If you are interested in further enhancements and investigations, just watch *Next* repo.

[https://github.com/Samurais/Neural\_Conversation\_Models](https://github.com/Samurais/Neural_Conversation_Models)

# 自然语言处理推荐入门&工具书

本书由 [deep-qa](https://github.com/chatopera/deep-qa) 作者参与著作。

快速购书链接

[《智能问答与深度学习》](https://item.jd.com/12479014.html) 这本书是服务于准备入门机器学习和自然语言处理的学生和软件工程师的，在理论上介绍了很多原理、算法，同时也提供很多示例程序增加实践性，这些程序被汇总到示例程序代码库，这些程序主要是帮助大家理解原理和算法的，欢迎大家下载和执行。代码库的地址是：

[https://github.com/l11x0m7/book-of-qna-code](https://github.com/l11x0m7/book-of-qna-code)

# Approaching a Chatbot Service
[![Join the chat at https://gitter.im/chatbot-pilots/DeepQA](https://badges.gitter.im/chatbot-pilots/DeepQA.svg)](https://gitter.im/chatbot-pilots/DeepQA?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge) [![Docker Pulls](https://img.shields.io/docker/pulls/samurais/deepqa2.svg?maxAge=2592000)](https://hub.docker.com/r/samurais/deepqa2/) [![Docker Stars](https://img.shields.io/docker/stars/samurais/deepqa2.svg?maxAge=2592000)](https://hub.docker.com/r/samurais/deepqa2/) [![Docker Layers](https://images.microbadger.com/badges/image/samurais/deepqa2.svg)](https://microbadger.com/#/images/samurais/deepqa2)

[![chatoper banner][co-banner-image]][co-url]

[co-banner-image]: https://user-images.githubusercontent.com/3538629/42383104-da925942-8168-11e8-8195-868d5fcec170.png
[co-url]: https://www.chatopera.com

[Part 1: Introduction](http://www.leiphone.com/news/201702/O9PGyImfH1Vq3fxV.html)

[Part 2: Bot Engine](http://www.leiphone.com/news/201702/oY07cF3HVIp7Yo1s.html)

[Part 3: Bot Model](http://www.leiphone.com/news/201702/4OZau7OfcNO0v1u5.html)

> This repository is align with **Part 3: Bot Model**.

Train and serve QA Model with TensorFlow

Tested with TensorFlow#0.11.0rc2, Python#3.5.

[Install Nvidia Drivers, CUDNn, Python, TensorFlow on Ubuntu 16.04](https://gist.github.com/Samurais/e20a8283708d37f1d7c9a709e9332429)

# DeepQA
Inspired and inherited from [DeepQA](https://github.com/Conchylicultor/DeepQA/issues/44).

# Install deps
```
pip install -r requirements.txt
```

# Install TensorFlow
```
export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.11.0rc2-cp35-cp35m-linux_x86_64.whl
pip install —-upgrade $TF_BINARY_URL
```

# Pre-process data
Process data, build vocabulary, word embedding, conversations, etc.
```
cp config.sample.ini config.ini
python deepqa2/dataset/preprocesser.py
```

Sample Corpus http://www.cs.cornell.edu/~cristian/Cornell_Movie-Dialogs_Corpus.html

# Train Model
Train language model with Seq2seq.
```
cp config.sample.ini config.ini # modify keys
python deepqa2/train.py
```

# Serve Model
Provide RESt API to access language model.
```
cd DeepQA2/save/deeplearning.cobra.vulcan.20170127.175256/deepqa2/serve
cp db.sample.sqlite3 db.sqlite3
python manage.py runserver 0.0.0.0:8000
```

Access Service with RESt API
```
POST /api/v1/question HTTP/1.1
Host: 127.0.0.1:8000
Content-Type: application/json
Authorization: Basic YWRtaW46cGFzc3dvcmQxMjM=
Cache-Control: no-cache

{"message": "good to know"}

response
{
"rc": 0,
"msg": "hello"
}
```

# Train with Docker
## Install
* [docker](https://docs.docker.com/engine/installation/linux/ubuntu/)
* [nvidia-docker](https://github.com/NVIDIA/nvidia-docker)
## Train
```
docker pull samurais/deepqa2:latest
cd DeepQA2
./scripts/train_with_docker.sh
```

## Chatopera 云服务

[https://bot.chatopera.com/](https://bot.chatopera.com/)

[Chatopera 云服务](https://bot.chatopera.com)是一站式实现聊天机器人的云服务，按接口调用次数计费。Chatopera 云服务是 [Chatopera 机器人平台](https://docs.chatopera.com/products/chatbot-platform/index.html)的软件即服务实例。在云计算基础上，Chatopera 云服务属于**聊天机器人即服务**的云服务。

Chatopera 机器人平台包括知识库、多轮对话、意图识别和语音识别等组件，标准化聊天机器人开发，支持企业 OA 智能问答、HR 智能问答、智能客服和网络营销等场景。企业 IT 部门、业务部门借助 Chatopera 云服务快速让聊天机器人上线！

展开查看 Chatopera 云服务的产品截图

自定义词典