具有自然语言理解和人工智能 的 python聊天机器人框架_python_代码_下载

<img src="https://i.ibb.co/vLR1wpG/logo.png" width="280"/> [](https://gitter.im/ai-chatbot-framework/Lobby?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge) [](https://travis-ci.com/alfredfrancis/ai-chatbot-framework.svg?branch=master) ### An AI Chatbot framework built in Python Building a chatbot can sound daunting, but it’s totally doable. AI Chatbot Framework is an AI powered conversational dialog interface built in Python. With this tool, it’s easy to create Natural Language conversational scenarios with no coding efforts whatsoever. The smooth UI makes it effortless to create and train conversations to the bot and it continuously gets smarter as it learns from conversations it has with people. AI Chatbot Framework can live on any channel of your choice (such as Messenger, Slack etc.) by integrating it’s API with that platform. You don’t need to be an expert at artificial intelligence to create an awesome chatbot that has AI capabilities. With this boilerplate project you can create an AI powered chatting machine in no time.There may be scores of bugs. So feel free to contribute via pull requests.  ### Installation ### Using docker-compose ```sh docker-compose up -d ``` ### Using Helm ```sh helm dep update helm/ai-chatbot-framework helm upgrade --install --create-namespace -n ai-chatbot-framework ai-chatbot-framework helm/ai-chatbot-framework # port forward for local installation kubectl port-forward --namespace=ai-chatbot-framework service/ingress-nginx-controller 8080:80 ``` ### Using Docker ```sh # pull docker images docker pull alfredfrancis/ai-chatbot-framework_backend:latest docker pull alfredfrancis/ai-chatbot-framework_frontend:latest # start a mongodb server docker run --name mongodb -d mongo:3.6 # start iky backend docker run -d --name=iky_backend --link mongodb:mongodb -e="APPLICATION_ENV=Production" alfredfrancis/ai-chatbot-framework_backend:latest # setup default intents docker exec -it iky_backend python manage.py migrate # start iky gateway with frontend docker run -d --name=iky_gateway --link iky_backend:iky_backend -p 8080:80 alfredfrancis/ai-chatbot-framework_frontend:latest ``` ### without docker * Setup Virtualenv and install python requirements ```sh virtualenv -p python3 venv source venv/bin/activate pip install -r requirements.txt python manage.py migrate python run.py ``` * Production ```sh APPLICATION_ENV="Production" gunicorn -k gevent --bind 0.0.0.0:8080 run:app ``` * Open http://localhost:8080/ #### Update Frontend Dist * Run Development mode ```sh cd frontend npm install ng serve ``` * Take Production build ```sh cd frontend ng build --prod --optimize ``` ### Heroku [](https://heroku.com/deploy) * add your dev/production configurations in config.py ### DB #### Restore You can import some default intents using following steps - goto http://localhost:8080/agent/default/settings - click 'choose file' - choose 'examples/default_intents.json file' - click import ### Screenshots  ---  ---  ---  ### Tutorial Checkout this basic tutorial on youtube, [](https://www.youtube.com/watch?v=S1Fj7WinaBA) Watch tutorial on [Fullfilling your Chatbot Intent with an API Call - Recipe Search Bot](https://www.youtube.com/watch?v=gqO69ojLobQ) ### Todos * Write Unit Tests * Multilingual Intent Classifier * PyCRFSuite to sklearn-crfsuite migration * Support follow up conversations ### Dependencies documentations * [SKLearn documentation](http://scikit-learn.org/) * [CRFsuite documentation](http://www.chokkan.org/software/crfsuite/) * [python CRfSuite](https://python-crfsuite.readthedocs.io/en/latest/) **Free Software, Hell Yeah!** <hr></hr>