Fix e2e tutorial solution files and documentation.

code-samples/eventing/bookstore-sample-app/solution/ML-bad-word-filter/.gitignore

@@ -3,3 +3,4 @@
 # generally not be tracked in source control. To instruct the system to track
 # .func in source control, comment the following line (prefix it with '# ').
 /.func
+/.s2i

code-samples/eventing/bookstore-sample-app/solution/ML-bad-word-filter/README.md

@@ -0,0 +1,50 @@
+# Python CloudEvents Function
+
+Welcome to your new Python Function! A minimal Function implementation can
+be found in `./function/func.py`.
+
+For more, run `func --help` or read the [Python Functions doc](https://github.com/knative/func/blob/main/docs/function-templates/python.md)
+
+## Usage
+
+Knative Functions allow for the deployment of your source code directly to a
+Kubernetes cluster with Knative installed.
+
+### Function Structure
+
+Python functions must implement a `new()` method that returns a function
+instance. The function class can optionally implement:
+- `handle()` - Process CloudEvent requests
+- `start()` - Initialize the function with configuration
+- `stop()` - Clean up resources when the function stops
+- `alive()` / `ready()` - Health and readiness checks
+
+See the default implementation in `./function/func.py`
+
+### Running Locally
+
+Use `func run` to test your Function locally before deployment.
+For development environments where Python is installed, it's suggested to use
+the `host` builder as follows:
+
+```bash
+# Run function on the host (outsdie of a container)
+func run --builder=host
+```
+
+### Deploying
+
+Use `func deploy` to deploy your Function to a Knative-enabled cluster:
+
+```bash
+# Deploy with interactive prompts (recommended for first deployment)
+func deploy --registry ghcr.io/myuser
+```
+
+Functions are automatically built, containerized, and pushed to a registry
+before deployment. Subsequent deployments will update the existing function.
+
+## Roadmap
+
+Our project roadmap can be found: https://github.com/orgs/knative/projects/49
+

code-samples/eventing/bookstore-sample-app/solution/ML-bad-word-filter/func.yaml

@@ -1,8 +1,14 @@
+# $schema: https://raw.githubusercontent.com/knative/func/d04ff0a3/schema/func_yaml-schema.json
+# yaml-language-server: $schema=https://raw.githubusercontent.com/knative/func/d04ff0a3/schema/func_yaml-schema.json
 specVersion: 0.36.0
 name: bad-word-filter
 runtime: python
-created: 2024-03-27T23:12:06.178272+08:00
+registry: localhost:5000
+namespace: default
+created: 2025-09-20T18:38:53.634514281+02:00
+invoke: cloudevent
 build:
   builder: s2i
 deploy:
   namespace: default
+  image: localhost:5000/bad-word-filter@sha256:690a4eb5aaae56dfbfabcb8a3f0943a48b97851e2b90ce40397091bb0866655c

code-samples/eventing/bookstore-sample-app/solution/ML-bad-word-filter/function/__init__.py

@@ -0,0 +1 @@
+from .func import new

code-samples/eventing/bookstore-sample-app/solution/ML-bad-word-filter/function/func.py

@@ -0,0 +1,44 @@
+import logging
+from cloudevents.http import CloudEvent
+from profanity_check import predict
+
+def new():
+    return Function()
+
+class Function:
+    async def handle(self, scope, receive, send):
+        """ Handle all HTTP requests to this Function. The incoming CloudEvent is in scope["event"]. """
+        logging.info("Request Received")
+
+        # 1. Extract the CloudEvent from the scope
+        request_event = scope["event"]
+
+        # 2. Extract the data payload from the event, analyze and create CloudEvent
+        response_event = self.inappropriate_language_filter(request_event.data)
+
+        # 3. Send the response
+        logging.info(f"Sending response: {response_event.data}")
+        await send(response_event)
+
+    def create_cloud_event(self, inputText, data):
+        attributes = {
+            "type": "new-review-comment",
+            "source": "book-review-broker",
+            "datacontenttype": "application/json",
+            "badwordfilter": data,
+        }
+
+        # Put the bad word filter result into a dictionary
+        data = {"reviewText": inputText, "badWordResult": data}
+
+        # Create a CloudEvent object
+        return CloudEvent(attributes, data)
+
+    def inappropriate_language_filter(self, text):
+        review_text = text.get("reviewText", "")
+        profanity_result = predict([review_text])
+        result = "good"
+        if profanity_result[0] == 1:
+            result = "bad"
+
+        return self.create_cloud_event(review_text, result)

code-samples/eventing/bookstore-sample-app/solution/ML-bad-word-filter/pyproject.toml

@@ -0,0 +1,27 @@
+[project]
+name = "function"
+description = ""
+version = "0.1.0"
+requires-python = ">=3.9"
+readme = "README.md"
+license = "MIT"
+dependencies = [
+  "httpx",
+  "cloudevents",
+  "pytest",
+  "pytest-asyncio",
+  "alt-profanity-check==1.4.1.post1"
+]
+authors = [
+  { name="Your Name", email="you@example.com"},
+]
+
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+[tool.pytest.ini_options]
+asyncio_mode = "strict"
+asyncio_default_fixture_loop_scope = "function"
+
+

code-samples/eventing/bookstore-sample-app/solution/ML-bad-word-filter/tests/test_func.py

@@ -0,0 +1,50 @@
+"""
+Unit tests for the CloudEvent function implementation.
+Tests both the function health endpoints and its handling of CloudEvents.
+
+Functions are currently served as ASGI applications using hypercorn, so we
+use httpx for testing.  To run the tests using poetry:
+
+poetry run python -m unittest discover
+"""
+import json
+import asyncio
+import pytest
+from cloudevents.http import CloudEvent
+from function import new
+
+
+@pytest.mark.asyncio
+async def test_func():
+    f = new()  # Instantiate Function to Test
+
+    # A test CloudEvent
+    attributes = {
+        "id": "test-id",
+        "type": "com.example.test1",
+        "source": "https://example.com/event-producer",
+    }
+    data = {"message": "test message"}
+    event = CloudEvent(attributes, data)
+
+    invoked = False  # Flag indicating send method was invoked
+
+    # Send
+    # confirms the Functions responds with a CloudEvent which echoes
+    # the data sent.
+    async def send(e):
+        nonlocal invoked
+        invoked = True  # Flag send was invoked
+
+        # Ensure we got a CloudEvent
+        assert isinstance(e, CloudEvent), f"Expected CloudEvent, got {type(e)}"
+
+        # Ensure it echoes the data sent
+        assert e.data == data, f"Expected data {data}, got {e.data}"
+
+    # Invoke the Function
+    scope = {"event": event}  # Add the CloudEvent to the scope
+    await f.handle(scope, {}, send)
+
+    # Assert send was called
+    assert invoked, "Function did not call send"

code-samples/eventing/bookstore-sample-app/solution/ML-sentiment-analysis/.gitignore

@@ -3,3 +3,4 @@
 # generally not be tracked in source control. To instruct the system to track
 # .func in source control, comment the following line (prefix it with '# ').
 /.func
+/.s2i