Merge pull request #1676 from gchq/feature/BAI-1545-remove-team-and-t…

…eams-endpoints-from-python-bailo-client Remove team & teams endpoints from python bailo client
gchq · Dec 11, 2024 · ec9591b · ec9591b
2 parents 3ebcd8a + b38b663
commit ec9591b
Show file tree

Hide file tree

Showing 17 changed files with 278 additions and 500 deletions.
diff --git a/backend/docs/README.md b/backend/docs/README.md
@@ -1,6 +1,6 @@
-# Bailo Python Client
+# Bailo Python Client Documentation
 
-A simple Python API Wrapper for Bailo
+The documentation for [a simple Python API Wrapper for Bailo](../../lib/python/README.md)
 
 <br />
 
@@ -9,102 +9,43 @@ A simple Python API Wrapper for Bailo
     <summary>Table of Contents</summary>
     <ol>
         <li>
-            <a href="#key-features">Key Features</a>
-        </li>
-        <li>
-            <a href="#installing">Installing</a>
-        </li>
-        <li>
-            <a href="#getting-started">Getting Started</a>
-        </li>
-        <li>
-            <a href="#development">Development</a>
+            <a href="#documentation">Documentation</a>
             <ul>
-                <li><a href="#install-and-add-precommit">Precommits</a></li>
-                <li><a href="#testing">Testing</a></li>
+                <li>
+                    <a href="#building-locally">Building locally</a>
+                    <ul>
+                        <li><a href="#prerequisites">Prerequisites</a></li>
+                        <li><a href="#building">Building</a></li>
+                    </ul>
+                </li>
             </ul>
         </li>
     </ol>
 </details>
 
 <br />
 
-## Key Features
-
-- Uploading and downloading model binaries
-
-## Installing
-
-**Python 3.8.1 or higher is required**
-
-```bash
-pip install bailo
-```
-
-## Getting Started
-
-```python
-from bailo import Client, Model
-client = Client("http://localhost:8080")
-
-# Create a model
-yolo = Model.create(
-    client=client,
-    name="YoloV4",
-    description="You only look once!",
-    team_id="Uncategorised"
-)
-
-yolo.card_from_schema("minimal-general-v10-beta")
-
-# Create a new release
-my_release = yolo.create_release(version="0.1.0",
-                              notes="Beta")
-
-# Upload a file to the release
-with open("yolo.onnx") as f:
-    my_release.upload("yolo", f)
-```
-
 ## Documentation
 
-Documenation is rendered with Sphinx and served [here](https://gchq.github.io/Bailo/docs/python/index.html).
+Documentation is rendered with Sphinx and served [here](https://gchq.github.io/Bailo/docs/python/index.html).
 
 ### Building locally
 
-From the docs directory run either `make html` or `make.bat` on Windows. This will build it in the backend directory by
-default.
-
-## Development
-
-### Install and add precommit
-
-If already working on Bailo you may be prompted to overwrite Husky. Follow the instructions given by Git CLI.
-
-```bash
-pip install pre-commit
-pre-commit install
-```
-
-### Install the package locally
-
-```bash
-pip install -e .
-```
-
-### Testing
+<!-- prettier-ignore-start -->
+> [!IMPORTANT]
+> Python 3.8.1 or higher is required
+<!-- prettier-ignore-end -->
 
-The package uses Pytest to test packages. Tests can be ran accordingly from within this directory. Tests are split into
-categories sections for automation purposes.
+#### Prerequisites
 
-In order to run integration tests make sure Bailo is running on `https://localhost:8080`:
+From within the `backend/docs` directory:
 
 ```bash
-pytest -m integration
+pip install bailo -r requirements.txt
+apt install -y pandoc
 ```
 
-Run all other tests:
+#### Building
 
-```bash
-pytest
-```
+From the docs directory run either `make html` (Linux & Mac) or `make.bat` (Windows). This will build it in the backend
+directory by default.
diff --git a/backend/docs/notebooks/access_requests_demo.ipynb b/backend/docs/notebooks/access_requests_demo.ipynb
@@ -78,7 +78,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "In this section, we'll create a new access request using the `AccessRequest.create()` classmethod. On the Bailo service, an access request must consist of at least 3 parameters upon creation. These are **model_id**, **schema_id** and **metadata**. Below, we use the `Client()` object created before when instantiating the new `AccessRequest()` object. We'll also need to create a new model on the service, which our access request will be for."
+    "In this section, we will create a new access request using the `AccessRequest.create()` classmethod. On the Bailo service, an access request must consist of at least 3 parameters upon creation. These are **model_id**, **schema_id** and **metadata**. Below, we use the `Client()` object created before when instantiating the new `AccessRequest()` object. We will also need to create a new model on the service, which our access request will be for."
    ]
   },
   {
@@ -87,7 +87,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "model = Model.create(client=client, name=\"YOLOv5\", description=\"YOLOv5 model for object detection.\", team_id=\"uncategorised\")\n",
+    "model = Model.create(client=client, name=\"YOLOv5\", description=\"YOLOv5 model for object detection.\")\n",
     "model_id = model.model_id\n",
     "\n",
     "metadata = {\"overview\": {\"entities\": [\"user\"], \"name\": \"test\", \"endDate\": \"1970-01-01\"}}\n",
@@ -117,7 +117,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "In this section, we'll retrieve our previous access request using the `AccessRequest.from_id()` classmethod. This will create your `AccessRequest()` object as before, but using existing information retrieved from the service."
+    "In this section, we will retrieve our previous access request using the `AccessRequest.from_id()` classmethod. This will create your `AccessRequest()` object as before, but using existing information retrieved from the service."
    ]
   },
   {

diff --git a/backend/docs/notebooks/datacards_demo.ipynb b/backend/docs/notebooks/datacards_demo.ipynb
@@ -74,7 +74,7 @@
     "\n",
     "### Creating and updating the base datacard\n",
     "\n",
-    "In this section, we'll create a new datacard using the `Datacard.create()` classmethod. On the Bailo service, a datacard must consist of at least 4 parameters upon creation. These are **name**, **description**, **visibility** and **team_id**. Below, we use the `Client()` object created before when instantiating the new `Datacard()` object. \n",
+    "In this section, we will create a new datacard using the `Datacard.create()` classmethod. On the Bailo service, a datacard must consist of at least 4 parameters upon creation. These are **name**, **description** and **visibility**. Below, we use the `Client()` object created before when instantiating the new `Datacard()` object. \n",
     "\n",
     "NOTE: This creates the datacard on your Bailo service too! The `datacard_id` is assigned by the backend, and we will use this later to retrieve the datacard. *Like with models on Bailo, the actual datacard has not been populated at this stage.*"
    ]
@@ -85,7 +85,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "datacard = Datacard.create(client=client, name=\"ImageNet\", description=\"ImageNet dataset consisting of images.\", team_id=\"uncategorised\")\n",
+    "datacard = Datacard.create(client=client, name=\"ImageNet\", description=\"ImageNet dataset consisting of images.\")\n",
     "\n",
     "datacard_id = datacard.datacard_id"
    ]
@@ -131,7 +131,7 @@
    "source": [
     "If successful, the above will have created a new datacard, and the `data_card_version` attribute should be set to 1.\n",
     "\n",
-    "Next, we can populate the data using the `update_data_card()` method. This can be used any time you want to make changes, and the backend will create a new datacard version each time. We'll learn how to retrieve datacards later (either the latest, or a specific release).\n",
+    "Next, we can populate the data using the `update_data_card()` method. This can be used any time you want to make changes, and the backend will create a new datacard version each time. We will learn how to retrieve datacards later (either the latest, or a specific release).\n",
     "\n",
     "NOTE: Your datacard must match the schema, otherwise an error will be thrown."
    ]
@@ -170,7 +170,7 @@
     "\n",
     "### Using the .from_id() method\n",
     "\n",
-    "In this section, we'll retrieve our previous datacard using the `Datacard.from_id()` classmethod. This will create your `Datacard()` object as before, but using existing information retrieved from the service."
+    "In this section, we will retrieve our previous datacard using the `Datacard.from_id()` classmethod. This will create your `Datacard()` object as before, but using existing information retrieved from the service."
    ]
   },
   {

diff --git a/backend/docs/notebooks/experiment_tracking_demo.ipynb b/backend/docs/notebooks/experiment_tracking_demo.ipynb
@@ -38,7 +38,7 @@
     "\n",
     "### Connecting with Bailo\n",
     "\n",
-    "In order to create an `Experiment()` object, you'll first need to have a Bailo `Model()` object, and thus a defined `Client()` too. We learned how to do this in a previous notebook, but this time we'll create a new model with a custom schema which supports model metrics. *More on that later...*"
+    "In order to create an `Experiment()` object, you'll first need to have a Bailo `Model()` object, and thus a defined `Client()` too. We learned how to do this in a previous notebook, but this time we will create a new model with a custom schema which supports model metrics. *More on that later...*"
    ]
   },
   {
@@ -69,7 +69,7 @@
     "\n",
     "# Creating a demo model\n",
     "\n",
-    "model = Model.create(client=client, name=\"YOLOv5\", description=\"YOLOv5 model for object detection.\", team_id=\"uncategorised\")"
+    "model = Model.create(client=client, name=\"YOLOv5\", description=\"YOLOv5 model for object detection.\")"
    ]
   },
   {
@@ -79,7 +79,7 @@
    "source": [
     "### Setting up MLFlow Tracking\n",
     "\n",
-    "In order to complete the integration element of this tutorial, we'll need to set up a local instance of MLFlow Tracking, and create a sample experiment run. *This will not contain any actual model training and is only to demonstrate the functionality of Bailo.*\n",
+    "In order to complete the integration element of this tutorial, we will need to set up a local instance of MLFlow Tracking, and create a sample experiment run. *This will not contain any actual model training and is only to demonstrate the functionality of Bailo.*\n",
     "\n",
     "Run `mlflow ui` on the command line. Typically this will run on **localhost:5000** and the UI can be accessed on a browser"
    ]
@@ -156,7 +156,7 @@
     "\n",
     "You can run experiments directly using the Bailo python client as follows.\n",
     "\n",
-    "**NOTE**: This will only work for sequential experiment runs, so if you're running experiments in parallel then it would be better to use **MLFlow Tracking**. We'll learn how to import completed experiments from MLFlow in the next section."
+    "**NOTE**: This will only work for sequential experiment runs, so if you're running experiments in parallel then it would be better to use **MLFlow Tracking**. We will learn how to import completed experiments from MLFlow in the next section."
    ]
   },
   {
@@ -218,7 +218,7 @@
    "source": [
     "## Importing existing experiments from MLFlow into Bailo\n",
     "\n",
-    "As previously mentioned, you can import existing experiments into the `Experiment()` class by using the `Experiment.from_mlflow()` method. You must provide the **MLFlow tracking URI** and the experiment ID. To get the experiement ID, go to the link provided in the cell \"Creating a dummy MLFlow experiment run\". In the details section you will see \"Experiment ID\", copy this ID and add it to the argument **experiment_id**. ![image.png](img/experiment_id.png)"
+    "You can import existing experiments into the `Experiment()` class by using the `Experiment.from_mlflow()` method. You must provide the **MLFlow tracking URI** and the experiment ID. To get the experiment ID, go to the link provided in the cell \"Creating a dummy MLFlow experiment run\". In the details section you will see \"Experiment ID\", copy this ID and add it to the argument **experiment_id**. ![image.png](img/experiment_id.png)"
    ]
   },
   {

diff --git a/backend/docs/notebooks/models_and_releases_demo_pytorch.ipynb b/backend/docs/notebooks/models_and_releases_demo_pytorch.ipynb
@@ -91,7 +91,7 @@
     "\n",
     "### Creating and updating the base model\n",
     "\n",
-    "In this section, we'll create a new model representing ResNet-50 using the `Model.create()` classmethod. On the Bailo service, a model must consist of at least 4 parameters upon creation. These are **name**, **description**, **visibility** and **team_id**. Other attributes like model cards, files, or releases are added later on. Below, we use the `Client()` object created before when instantiating the new `Model()` object. \n",
+    "In this section, we will create a new model representing ResNet-50 using the `Model.create()` classmethod. On the Bailo service, a model must consist of at least 4 parameters upon creation. These are **name**, **description** and **visibility**. Other attributes like model cards, files, or releases are added later on. Below, we use the `Client()` object created before when instantiating the new `Model()` object. \n",
     "\n",
     "NOTE: This creates the model on your Bailo service too! The `model_id` is assigned by the backend, and we will use this later to retrieve the model."
    ]
@@ -102,7 +102,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "model = Model.create(client=client, name=\"ResNet-50\", description=\"ResNet-50 model for image classification.\", team_id=\"uncategorised\")\n",
+    "model = Model.create(client=client, name=\"ResNet-50\", description=\"ResNet-50 model for image classification.\")\n",
     "\n",
     "model_id = model.model_id"
    ]
@@ -151,7 +151,7 @@
     "\n",
     "### Creating and populated a new model card with a template\n",
     "\n",
-    "When creating a model card from a template, we need to use a preexisting model card as our template. First we create a new model, to create the new model card we use the `card_from_template` method and pass our chosen template model's ID. \n",
+    "When creating a model card from a template, we need to use a pre-existing model card as our template. First we create a new model, to create the new model card we use the `card_from_template` method and pass our chosen template model's ID. \n",
     "\n",
     "\n"
    ]
@@ -163,7 +163,7 @@
    "outputs": [],
    "source": [
     "model2 = Model.create(\n",
-    "    client=client, name=\"ResNet-50\", description=\"ResNet-50 model for image classification.\", team_id=\"uncategorised\"\n",
+    "    client=client, name=\"ResNet-50\", description=\"ResNet-50 model for image classification.\"\n",
     ")\n",
     "\n",
     "model2_id = model2.model_id\n",
@@ -180,7 +180,7 @@
    "source": [
     "If successful, the above will have created a new model card, and the `model_card_version` attribute should be set to 1.\n",
     "\n",
-    "Next, we can populate the model card using the `update_model_card()` method. This can be used any time you want to make changes, and the backend will create a new model card version each time. We'll learn how to retrieve model cards later (either the latest, or a specific release).\n",
+    "Next, we can populate the model card using the `update_model_card()` method. This can be used any time you want to make changes, and the backend will create a new model card version each time. We will learn how to retrieve model cards later (either the latest, or a specific release).\n",
     "\n",
     "NOTE: Your model card must match the schema, otherwise an error will be thrown."
    ]
@@ -220,7 +220,7 @@
     "\n",
     "### Using the .from_id() method\n",
     "\n",
-    "In this section, we'll retrieve our previous model using the `Model.from_id()` classmethod. This will create your `Model()` object as before, but using existing information retrieved from the service."
+    "In this section, we will retrieve our previous model using the `Model.from_id()` classmethod. This will create your `Model()` object as before, but using existing information retrieved from the service."
    ]
   },
   {
@@ -337,7 +337,7 @@
    "source": [
     "### Downloading weights from the release\n",
     "\n",
-    "Similarly you can also download specific files from release using the `download()` method. In this case, we'll write them to a new file: **bailo_resnet50_weights.pth**. **NOTE**: `filename` refers to the filename on Bailo, and `path` is the local destination for your download.\n",
+    "You can also download specific files from release using the `download()` method. In this case, we will write them to a new file: **bailo_resnet50_weights.pth**. **NOTE**: `filename` refers to the filename on Bailo, and `path` is the local destination for your download.\n",
     "\n",
     "In addition to this, you can also use the `download_all()` method by providing a local directory path as `path`. By default, this will download all files, but you can provide `include` and `exclude` lists, e.g. `include=[\"*.txt\", \"*.json\"]` to only include TXT or JSON files. "
    ]
@@ -378,7 +378,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "If the message \"**All keys matched successfully**\" is displayed, we have successfully initated our model."
+    "If the message \"**All keys matched successfully**\" is displayed, we have successfully initiated our model."
    ]
   },
   {
@@ -400,7 +400,7 @@
     "* Libraries used for the model (e.g. PyTorch).\n",
     "* Model card search (string to be found in model cards).\n",
     "\n",
-    "In the below example, we'll just search for all models with no filters."
+    "In the below example, we will just search for all models with no filters."
    ]
   },
   {