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Caikit Template

GitHub Template with a boilerplate repository which serves an example AI model using caikit.

Repository Layout

├── caikit-template/:                       top-level package directory (will change to your repo name after template is deployed)
│   │── caikit_template/:                   a directory that defines Caikit module(s) that can include algorithm(s) implementation that can train/run an AI model 
│   │   ├── config/:                        a directory that contains the configuration for the module and model input and output
│   │   │   ├── config.yml:                 configuration for the module and model input and output
│   │   ├── data_model/:                    a directory that contains the data format of the Caikit module
│   │   │   ├── hello_world.py:             data class that represents the AI model attributes in code
│   │   │   ├── __init__.py:                makes the hello_world class visible in the project
│   │   ├── modules/:                       a directory that contains the Caikit module of the model
│   │   │   ├── hello_world.py:             a class that bootstraps the AI model in Caikit so it can be served and used (infer/train)
│   │   │   ├── __init__.py:                makes the hello_world class visible in the project
|   |   |── __init__.py:                    makes the data_model and runtime_model packages visible
│   │── demo/:                              a directory which contains code and configuration to test the model
│   │   │── client/:                        a directory which contains artifacts to use (infer and train) the AI model spceified in the `caikit_template` package
|   │   │   ├── config.yml:                 caikit runtime configuration file
│   │   │   ├── infer_model.py:             sample client which calls the Caikit runtime to perform inference on a model it is serving
│   │   │   ├── train_model.py:             sample client which calls the Caikit runtime to perform training on a model it is serving
│   │   │── models/:                        a directory that contains the Caikit metadata of the models and any artifacts required to run the models (usually generated after saving and should not be modified)
│   │   │   ├── hello_world/config.yml:     a metadata that defines the example Caikit model
│   │   │── server/:                        a directory which contains artifacts to start Caikit runtime
|   │   │   ├── config.yml:                 configuration for handling the model by the Caikit runtime
│   │   │   ├── start_runtime.py:           a wrapper to start the Caikit runtime as a gRPC server. The runtime will load the model at startup
|   │   ├── train_data/:                    a directory which contains the training data
|   │   |   ├── sample_data.csv:            sample training dataset to perform training of the model
└── └── requirements.txt:                   specifies library dependencies

Try it out

The repository contains an example AI model that you can infer and train using the steps that follow.

Before Starting

The following tools are required:

Note: Before installing dependencies and to avoid conflicts in your environment, it is advisable to use a virtual environment. The subsection which follows provides an example of a virtual environment, Python venv.

Install the dependencies: pip install -r requirements.txt

(Optional) Setting Up Virtual Environment using Python venv

For (venv), make sure you are in an activated venv when running python in the example commands that follow. Use deactivate if you want to exit the venv.

For example, to create and activate a virtual environment using venv:

python3 -m venv venv
source venv/bin/activate

Starting the Caikit Runtime

In one terminal, start the runtime server:

cd client
python3 start_runtime.py

You should see output similar to the following:

$ python3 start_runtime.py

[...]
{"channel": "MODEL-LOADER", "exception": null, "level": "info", "log_code": "<RUN89713784I>", "message": "Singleton cache: '{}'", "num_indent": 0, "thread_id": 8604329472, "timestamp": "2023-06-09T11:22:12.833744"}
{"channel": "MODEL-SIZER", "exception": null, "level": "info", "log_code": "<RUN62161564I>", "message": "No configured model size multiplier found for model type 'standalone-model' for model 'hello_world'. Using default multiplier '10.000000'", "num_indent": 0, "thread_id": 8604329472, "timestamp": "2023-06-09T11:22:12.834439"}
{"channel": "GP-SERVICR-I", "exception": null, "level": "info", "log_code": "<RUN76773776I>", "message": "Metering is disabled, to enable set `metering.enabled` in config to true", "num_indent": 0, "thread_id": 8604329472, "timestamp": "2023-06-09T11:22:12.834766"}
{"channel": "COM-LIB-INIT", "exception": null, "level": "info", "log_code": "<RUN11997772I>", "message": "Loading service module: caikit_template", "num_indent": 0, "thread_id": 8604329472, "timestamp": "2023-06-09T11:22:12.834905"}
{"channel": "COM-LIB-INIT", "exception": null, "level": "info", "log_code": "<RUN11997772I>", "message": "Loading service module: caikit.interfaces.common", "num_indent": 0, "thread_id": 8604329472, "timestamp": "2023-06-09T11:22:12.834977"}
{"channel": "COM-LIB-INIT", "exception": null, "level": "info", "log_code": "<RUN11997772I>", "message": "Loading service module: caikit.interfaces.runtime", "num_indent": 0, "thread_id": 8604329472, "timestamp": "2023-06-09T11:22:12.835026"}
{"channel": "GP-SERVICR-I", "exception": null, "level": "info", "log_code": "<RUN76773778I>", "message": "Validated Caikit Library CDM successfully", "num_indent": 0, "thread_id": 8604329472, "timestamp": "2023-06-09T11:22:12.835119"}
{"channel": "GP-SERVICR-I", "exception": null, "level": "info", "log_code": "<RUN76884779I>", "message": "Constructed inference service for library: caikit_template, version: unknown", "num_indent": 0, "thread_id": 8604329472, "timestamp": "2023-06-09T11:22:12.836444"}
{"channel": "SERVER-WRAPR", "exception": null, "level": "info", "log_code": "<RUN81194024I>", "message": "Intercepting RPC method /caikit.runtime.Template.TemplateService/HelloWorldTaskPredict", "num_indent": 0, "thread_id": 8604329472, "timestamp": "2023-06-09T11:22:12.836523"}
{"channel": "SERVER-WRAPR", "exception": null, "level": "info", "log_code": "<RUN33333123I>", "message": "Wrapping safe rpc for Predict", "num_indent": 0, "thread_id": 8604329472, "timestamp": "2023-06-09T11:22:12.836663"}
{"channel": "SERVER-WRAPR", "exception": null, "level": "info", "log_code": "<RUN30032825I>", "message": "Re-routing RPC /caikit.runtime.Template.TemplateService/HelloWorldTaskPredict from <function _ServiceBuilder._GenerateNonImplementedMethod.<locals>.<lambda> at 0x7fa470fdb550> to <function CaikitRuntimeServerWrapper.safe_rpc_wrapper.<locals>.safe_rpc_call at 0x7fa470ff55e0>", "num_indent": 0, "thread_id": 8604329472, "timestamp": "2023-06-09T11:22:12.836722"}
[...]
{"channel": "SERVER-WRAPR", "exception": null, "level": "info", "log_code": "<RUN24924908I>", "message": "Interception of service caikit.runtime.Template.TemplateService complete", "num_indent": 0, "thread_id": 8604329472, "timestamp": "2023-06-09T11:22:12.836783"}
{"channel": "COM-LIB-INIT", "exception": null, "level": "info", "log_code": "<RUN11997772I>", "message": "Loading service module: caikit_template", "num_indent": 0, "thread_id": 8604329472, "timestamp": "2023-06-09T11:22:12.836977"}
{"channel": "COM-LIB-INIT", "exception": null, "level": "info", "log_code": "<RUN11997772I>", "message": "Loading service module: caikit.interfaces.common", "num_indent": 0, "thread_id": 8604329472, "timestamp": "2023-06-09T11:22:12.837052"}
{"channel": "COM-LIB-INIT", "exception": null, "level": "info", "log_code": "<RUN11997772I>", "message": "Loading service module: caikit.interfaces.runtime", "num_indent": 0, "thread_id": 8604329472, "timestamp": "2023-06-09T11:22:12.837114"}
{"channel": "COM-LIB-INIT", "exception": null, "level": "info", "log_code": "<RUN11997772I>", "message": "Loading service module: caikit_template", "num_indent": 0, "thread_id": 8604329472, "timestamp": "2023-06-09T11:22:12.837267"}
{"channel": "COM-LIB-INIT", "exception": null, "level": "info", "log_code": "<RUN11997772I>", "message": "Loading service module: caikit.interfaces.common", "num_indent": 0, "thread_id": 8604329472, "timestamp": "2023-06-09T11:22:12.837320"}
{"channel": "COM-LIB-INIT", "exception": null, "level": "info", "log_code": "<RUN11997772I>", "message": "Loading service module: caikit.interfaces.runtime", "num_indent": 0, "thread_id": 8604329472, "timestamp": "2023-06-09T11:22:12.837373"}
{"channel": "GT-SERVICR-I", "exception": null, "level": "info", "log_code": "<RUN76773777I>", "message": "Validated Caikit Library CDM successfully", "num_indent": 0, "thread_id": 8604329472, "timestamp": "2023-06-09T11:22:12.837458"}
{"channel": "GT-SERVICR-I", "exception": null, "level": "info", "log_code": "<RUN76884779I>", "message": "Constructed train service for library: caikit_template, version: unknown", "num_indent": 0, "thread_id": 8604329472, "timestamp": "2023-06-09T11:22:12.838420"}
{"channel": "SERVER-WRAPR", "exception": null, "level": "info", "log_code": "<RUN81194024I>", "message": "Intercepting RPC method /caikit.runtime.Template.TemplateTrainingService/HelloWorldTaskHelloWorldModuleTrain", "num_indent": 0, "thread_id": 8604329472, "timestamp": "2023-06-09T11:22:12.838478"}
{"channel": "SERVER-WRAPR", "exception": null, "level": "info", "log_code": "<RUN33333123I>", "message": "Wrapping safe rpc for Train", "num_indent": 0, "thread_id": 8604329472, "timestamp": "2023-06-09T11:22:12.838572"}
{"channel": "SERVER-WRAPR", "exception": null, "level": "info", "log_code": "<RUN30032825I>", "message": "Re-routing RPC /caikit.runtime.Template.TemplateTrainingService/HelloWorldTaskHelloWorldModuleTrain from <function _ServiceBuilder._GenerateNonImplementedMethod.<locals>.<lambda> at 0x7fa470ff53a0> to <function CaikitRuntimeServerWrapper.safe_rpc_wrapper.<locals>.safe_rpc_call at 0x7fa4602adaf0>", "num_indent": 0, "thread_id": 8604329472, "timestamp": "2023-06-09T11:22:12.838619"}

Inferencing the Served Model

In another terminal, run the client code to infer the model:

cd client
python3 infer_model.py

The client code calls the model and queries for generated text using text passed from the client.

You should see output similar to the following after the word World is passed:

$ python3 infer_model.py

RESPONSE: greeting: "Hello World"

Training the Served Model

In another terminal, run the client code to train the model:

cd client
python3 train_model.py

The client code trains the model with sample data in train_data/ and outputs the trained model to training_output/ by default.

You should see output similar to the following:

$ python3 train_model.py

RESPONSE: training_id: "ace2fd4c-0a50-49ef-b4db-9d9bbe2eefaf"
model_name: "hello_world"