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 git@github.com: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
:
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:
build
specified version of the ondewo-nlu-api
commit and push
all changes in code resulting from the build
- Create and push the
release branch
e.g. release/1.3.20
- Create and push the
release tag
e.g. 1.3.20
- Create a new
Release
on GitHub - 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.