ondewo-nlu-client 4.0.0

This library facilitates the interaction between a user and his/her CAI server.

Ondewo NLU Client Python Library

This library facilitates the interaction between a user and a CAI server. It achieves this by providing a higher-level interface mediator.

This higher-level interface mediator is structured around a series of python files generated from protobuf files. These protobuf files specify the details of the interface, and can be used to generate code in 10+ high-level languages. They are found in the ONDEWO NLU API along with the older Google protobufs from Dialogueflow that were used at the start. The ONDEWO PROTO-COMPILER will generate the needed files directly in this library.

Python Installation

You can install the library by installing it directly from the PyPi:

pip install ondewo-nlu-client

Or, you could clone it and install the requirements:

git clone [e-mail]:ondewo/ondewo-nlu-client-python.git
cd ondewo-nlu-client-python
make setup_developer_environment_locally

Repository Structure

.
├── examples                         <----- Helpful for implementation of code
├── ondewo
│   ├── nlu
│   │   ├── convenience
│   │   │   ├── __init__.py
│   │   │   └── shared_request_data.py
│   │   ├── core
│   │   │   ├── __init__.py
│   │   │   ├── services_container.py
│   │   │   └── services_interface.py
│   │   ├── scripts
│   │   │   ├── client_example_script.py
│   │   │   └── __init__.py
│   │   ├── services
│   │   │   ├── agents.py
│   │   │   ├── aiservices.py
│   │   │   ├── contexts.py
│   │   │   ├── entity_types.py
│   │   │   ├── __init__.py
│   │   │   ├── intents.py
│   │   │   ├── operations.py
│   │   │   ├── project_roles.py
│   │   │   ├── project_statistics.py
│   │   │   ├── server_statistics.py
│   │   │   ├── sessions.py
│   │   │   ├── users.py
│   │   │   └── utilities.py
│   │   ├── utils
│   │   │   ├── __init__.py
│   │   │   └── login.py
│   │   ├── agent_pb2_grpc.py
│   │   ├── agent_pb2.py
│   │   ├── agent_pb2.pyi
│   │   ├── aiservices_pb2_grpc.py
│   │   ├── aiservices_pb2.py
│   │   ├── aiservices_pb2.pyi
│   │   ├── ...
│   ├── qa
│   │   ├── core
│   │   │   ├── __init__.py
│   │   │   ├── services_container.py
│   │   │   └── services_interface.py
│   │   ├── services
│   │   │   ├── __init__.py
│   │   │   └── qa.py
│   │   ├── client_config.py
│   │   ├── client.py
│   │   ├── __init__.py
│   │   ├── py.typed
│   │   ├── qa_pb2_grpc.py
│   │   ├── qa_pb2.py
│   │   └── qa_pb2.pyi
│   └── __init__.py
├── ondewo-nlu-api                         <----- @ https://github.com/ondewo/ondewo-nlu-api
├── ondewo-proto-compiler                  <----- @ https://github.com/ondewo/ondewo-proto-compiler
├── CONTRIBUTING.md
├── Dockerfile
├── Dockerfile.utils
├── LICENSE
├── Makefile
├── MANIFEST.in
├── mypy.ini
├── README.md
├── RELEASE.md
├── requirements-dev.txt
├── requirements.txt
├── setup.cfg
└── setup.py

Build

The make build command is dependent on 2 repositories and their speciefied version:

• ondewo-nlu-api -- NLU_API_GIT_BRANCH in Makefile
• ondewo-proto-compiler -- ONDEWO_PROTO_COMPILER_GIT_BRANCH in Makefile

It will generate a _pb2.py, _pb2.pyi and _pb2_grpc.py file for every .proto in the api submodule.

:warning: All Files in the ondewo folder that dont have pb2 in their name are handwritten, and therefor need to be manually adjusted to any changes in the proto-code.

Examples

The /examples folder provides a possible implementation of this library. To run an example, simple execute it like any other python file. To specify the server and credentials, you need to provide an environment file with the following variables:

• host // The hostname of the Server - e.g. 127.0.0.1
• port // Port of the Server - e.g. 6600
• user_name // Username - same as you would use in AIM
• password // Password of the user
• http_token // Token to allow access through
• grpc_cert // gRPC Certificate of the server

Automatic Release Process

The entire process is automated to make development easier. The actual steps are simple:

TODO after Pull Request was merged in:

• Checkout master:

  git checkout master
  

• Pull the new stuff:

  git pull
  

• (If not already, run the setup_developer_environment_locally command):

  make setup_developer_environment_locally
  

• Update the ONDEWO_NLU_VERSION in the Makefile

• Add the new Release Notes in RELEASE.md in the format:

  ## Release ONDEWO NLU Python Client X.X.X       <---- Beginning of Notes
  
     ...<NOTES>...
  
  *****************                      <---- End of Notes
  

• Release:

  make ondewo_release
  

---

The release process can be divided into 6 Steps:

1. build specified version of the ondewo-nlu-api
2. commit and push all changes in code resulting from the build
3. Create and push the release branch e.g. release/1.3.20
4. Create and push the release tag e.g. 1.3.20
5. Create a new Release on GitHub
6. Publish the built dist folder to pypi.org

:warning: The Release Automation checks if the build has created all the proto-code files, but it does not check the code-integrity. Please build and test the generated code prior to starting the release process.