{"id":26483865,"url":"https://github.com/chatopera/deep-qa","last_synced_at":"2025-03-20T04:58:28.735Z","repository":{"id":37070765,"uuid":"91771056","full_name":"chatopera/deep-qa","owner":"chatopera","description":"Question and Answering Model with 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Note, this repo is deprecated.\n\nIf you are interested in further enhancements and investigations, just watch *Next* repo.\n\n[https://github.com/Samurais/Neural\\_Conversation\\_Models](https://github.com/Samurais/Neural_Conversation_Models)\n\n\n# 自然语言处理推荐入门\u0026工具书\n\n本书由 [deep-qa](https://github.com/chatopera/deep-qa) 作者参与著作。\n\n\u003cp align=\"center\"\u003e\n  \u003cb\u003e快速购书\u003ca href=\"https://item.jd.com/12479014.html\" target=\"_blank\"\u003e链接\u003c/a\u003e\u003c/b\u003e\u003cbr\u003e\n  \u003ca href=\"https://item.jd.com/12479014.html\" target=\"_blank\"\u003e\n  \u003cimg src=\"https://user-images.githubusercontent.com/3538629/48657619-bcd24880-ea6e-11e8-8c4e-8bcb00761942.png\" width=\"400\"\u003e      \n  \u003c/a\u003e\n\u003c/p\u003e\n\n[《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：\n\n[https://github.com/l11x0m7/book-of-qna-code](https://github.com/l11x0m7/book-of-qna-code)\n\n\n# Approaching a Chatbot Service\n[![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\u0026utm_medium=badge\u0026utm_campaign=pr-badge\u0026utm_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)\n\n[![chatoper banner][co-banner-image]][co-url]\n\n[co-banner-image]: https://user-images.githubusercontent.com/3538629/42383104-da925942-8168-11e8-8195-868d5fcec170.png\n[co-url]: https://www.chatopera.com\n\n[Part 1: Introduction](http://www.leiphone.com/news/201702/O9PGyImfH1Vq3fxV.html)\n\n[Part 2: Bot Engine](http://www.leiphone.com/news/201702/oY07cF3HVIp7Yo1s.html)\n\n[Part 3: Bot Model](http://www.leiphone.com/news/201702/4OZau7OfcNO0v1u5.html)\n\n\u003e This repository is align with  **Part 3: Bot Model**.\n\nTrain and serve QA Model with TensorFlow\n\nTested with TensorFlow#0.11.0rc2, Python#3.5.\n\n[Install Nvidia Drivers, CUDNn, Python, TensorFlow on Ubuntu 16.04](https://gist.github.com/Samurais/e20a8283708d37f1d7c9a709e9332429)\n\n# DeepQA\nInspired and inherited from [DeepQA](https://github.com/Conchylicultor/DeepQA/issues/44).\n\n# Install deps\n```\npip install -r requirements.txt\n```\n\n# Install TensorFlow\n```\nexport TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.11.0rc2-cp35-cp35m-linux_x86_64.whl\npip install —-upgrade $TF_BINARY_URL\n```\n\n# Pre-process data\nProcess data, build vocabulary, word embedding, conversations, etc.\n```\ncp config.sample.ini config.ini\npython deepqa2/dataset/preprocesser.py\n```\n\nSample Corpus http://www.cs.cornell.edu/~cristian/Cornell_Movie-Dialogs_Corpus.html\n\n# Train Model\nTrain language model with Seq2seq.\n```\ncp config.sample.ini config.ini # modify keys\npython deepqa2/train.py\n```\n\n# Serve Model\nProvide RESt API to access language model.\n```\ncd DeepQA2/save/deeplearning.cobra.vulcan.20170127.175256/deepqa2/serve\ncp db.sample.sqlite3 db.sqlite3 \npython manage.py runserver 0.0.0.0:8000\n```\n\nAccess Service with RESt API\n```\nPOST /api/v1/question HTTP/1.1\nHost: 127.0.0.1:8000\nContent-Type: application/json\nAuthorization: Basic YWRtaW46cGFzc3dvcmQxMjM=\nCache-Control: no-cache\n\n{\"message\": \"good to know\"}\n\nresponse\n{\n  \"rc\": 0,\n  \"msg\": \"hello\"\n}\n```\n\n# Train with Docker\n## Install \n* [docker](https://docs.docker.com/engine/installation/linux/ubuntu/)\n* [nvidia-docker](https://github.com/NVIDIA/nvidia-docker)\n## Train\n```\ndocker pull samurais/deepqa2:latest\ncd DeepQA2\n./scripts/train_with_docker.sh\n```\n\n\n\n## Chatopera 云服务\n\n[https://bot.chatopera.com/](https://bot.chatopera.com/)\n\n[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。\n\nChatopera 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！\n\n\u003cdetails\u003e\n\u003csummary\u003e展开查看 Chatopera 云服务的产品截图\u003c/summary\u003e\n\u003cp\u003e\n\n\u003cp align=\"center\"\u003e\n  \u003cb\u003e自定义词典\u003c/b\u003e\u003cbr\u003e\n  \u003cimg src=\"https://static-public.chatopera.com/assets/images/64530072-da92d600-d33e-11e9-8656-01c26caff4f9.png\" width=\"800\"\u003e\n\u003c/p\u003e\n\n\u003cp align=\"center\"\u003e\n  \u003cb\u003e自定义词条\u003c/b\u003e\u003cbr\u003e\n  \u003cimg src=\"https://static-public.chatopera.com/assets/images/64530091-e41c3e00-d33e-11e9-9704-c07a2a02b84e.png\" width=\"800\"\u003e\n\u003c/p\u003e\n\n\u003cp align=\"center\"\u003e\n  \u003cb\u003e创建意图\u003c/b\u003e\u003cbr\u003e\n  \u003cimg src=\"https://static-public.chatopera.com/assets/images/64530169-12018280-d33f-11e9-93b4-9db881cf4dd5.png\" width=\"800\"\u003e\n\u003c/p\u003e\n\n\u003cp align=\"center\"\u003e\n  \u003cb\u003e添加说法和槽位\u003c/b\u003e\u003cbr\u003e\n  \u003cimg src=\"https://static-public.chatopera.com/assets/images/64530187-20e83500-d33f-11e9-87ec-a0241e3dac4d.png\" width=\"800\"\u003e\n\u003c/p\u003e\n\n\u003cp align=\"center\"\u003e\n  \u003cb\u003e训练模型\u003c/b\u003e\u003cbr\u003e\n  \u003cimg src=\"https://static-public.chatopera.com/assets/images/64530235-33626e80-d33f-11e9-8d07-fa3ae417fd5d.png\" width=\"800\"\u003e\n\u003c/p\u003e\n\n\u003cp align=\"center\"\u003e\n  \u003cb\u003e测试对话\u003c/b\u003e\u003cbr\u003e\n  \u003cimg src=\"https://static-public.chatopera.com/assets/images/64530253-3d846d00-d33f-11e9-81ea-86e6d47020d8.png\" width=\"800\"\u003e\n\u003c/p\u003e\n\n\u003cp align=\"center\"\u003e\n  \u003cb\u003e机器人画像\u003c/b\u003e\u003cbr\u003e\n  \u003cimg src=\"https://static-public.chatopera.com/assets/images/64530312-6442a380-d33f-11e9-869c-85fb6a835a97.png\" width=\"800\"\u003e\n\u003c/p\u003e\n\n\u003cp align=\"center\"\u003e\n  \u003cb\u003e系统集成\u003c/b\u003e\u003cbr\u003e\n  \u003cimg src=\"https://static-public.chatopera.com/assets/images/64530281-4ecd7980-d33f-11e9-8def-c53251f30138.png\" width=\"800\"\u003e\n\u003c/p\u003e\n\n\u003cp align=\"center\"\u003e\n  \u003cb\u003e聊天历史\u003c/b\u003e\u003cbr\u003e\n  \u003cimg src=\"https://static-public.chatopera.com/assets/images/64530295-5856e180-d33f-11e9-94d4-db50481b2d8e.png\" width=\"800\"\u003e\n\u003c/p\u003e\n\n\u003c/p\u003e\n\u003c/details\u003e\n\n\n\u003cp align=\"center\"\u003e\n  \u003cb\u003e立即使用\u003c/b\u003e\u003cbr\u003e\n  \u003ca href=\"https://bot.chatopera.com\" target=\"_blank\"\u003e\n      \u003cimg src=\"https://static-public.chatopera.com/assets/images/64531083-3199aa80-d341-11e9-86cd-3a3ed860b14b.png\" width=\"800\"\u003e\n  \u003c/a\u003e\n\u003c/p\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchatopera%2Fdeep-qa","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fchatopera%2Fdeep-qa","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchatopera%2Fdeep-qa/lists"}