feat(RHOAIENG-21043): Add protobuf support

Add protobuf support in order to parse ModelMesh payloads

Author: ruivieira

.github/workflows/python-tests.yaml

@@ -0,0 +1,48 @@
+name: Python Tests
+
+on:
+  push:
+    branches: [main]
+  pull_request:
+    branches: [main]
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+    strategy:
+      fail-fast: false
+      matrix:
+        python-version: ["3.11"]
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ matrix.python-version }}
+          cache: "pip"
+
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          python -m pip install uv
+          if [ -f pyproject.toml ]; then
+            uv pip install -e ".[dev,protobuf]"
+          else
+            uv pip install pytest
+          fi
+
+      - name: Generate protobuf stubs
+        run: |
+          bash scripts/generate_protos.sh
+
+      - name: Run tests with pytest
+        run: |
+          pytest tests/ -v --cov=src --cov-report=xml
+
+      - name: Upload coverage to Codecov
+        uses: codecov/codecov-action@v4
+        with:
+          file: ./coverage.xml
+          fail_ci_if_error: false

.sourcery.yaml

@@ -1,2 +0,0 @@
-ignore_branches:
-  - "dependabot/**"

README.md

@@ -1,6 +1,6 @@
 # TrustyAI Service
 
-👋 The TrustyAI Service is intended to a hub for all kinds of Responsible AI workflows, such as 
+👋 The TrustyAI Service is intended to a hub for all kinds of Responsible AI workflows, such as
 explainability, drift, and Large Language Model (LLM) evaluation. Designed as a REST server wrapping
 a core Python library, the TrustyAI service is intended to be a tool that can operate in a local
 environment, a Jupyter Notebook, or in Kubernetes.
@@ -15,7 +15,7 @@ environment, a Jupyter Notebook, or in Kubernetes.
 - Meanshift
 
 ### ⚖️ Fairness ⚖️
-- Statistical Parity Difference 
+- Statistical Parity Difference
 - Disparate Impact Ratio
 - Average Odds Ratio (WIP)
 - Average Predictive Value Difference (WIP)
@@ -52,6 +52,11 @@ podman build -t $IMAGE_NAME .
 podman build -t $IMAGE_NAME --build-arg EXTRAS=eval .
 ````
 
+### Locally (With ModelMesh/Protobuf Support)
+```bash
+uv pip install .[protobuf]
+````
+
 
 ## 🏃Running 🏃‍♀️
 ### Locally
@@ -64,7 +69,50 @@ uv run uvicorn src.main --host 0.0.0.0 --port 8080
 podman run -t $IMAGE_NAME -p 8080:8080 .
 ```
 
+## 🧪 Testing 🧪
+### Running All Tests
+To run all tests in the project:
+```bash
+python -m pytest
+```
+
+Or with more verbose output:
+```bash
+python -m pytest -v
+```
+
+### Running with Coverage
+To run tests with coverage reporting:
+```bash
+python -m pytest --cov=src
+```
+
+---
+## 🔄 Protobuf Support 🔄
+TrustyAI can parse ModelMesh protobuf payloads for model inference data processing.
+
+### Installing Dependencies
+Install the required dependencies for protobuf support:
+```bash
+uv pip install -e ".[protobuf]"
+```
+
+### Generating Protobuf Code
+After installing dependencies, generate Python code from the protobuf definitions:
+
+```bash
+# From the project root
+bash scripts/generate_protos.sh
+```
+
+### Testing Protobuf Functionality
+Run the tests for the protobuf implementation:
+
+```bash
+# From the project root
+python -m pytest tests/service/data/test_modelmesh_parser.py -v
+```
+
 ---
 ## ☎️ API ☎️
 When the service is running, visit `localhost:8080/docs` to see the OpenAPI documentation!
-

pyproject.toml

@@ -2,10 +2,7 @@
 name = "trustyai-service"
 version = "1.0.0rc0"
 description = "TrustyAI Service"
-authors = [
-    { name = "Rui Vieira" },
-    { name = "TrustyAI team" },
-]
+authors = [{ name = "Rui Vieira" }, { name = "TrustyAI team" }]
 requires-python = "~=3.11"
 readme = "README.md"
 dependencies = [
@@ -29,11 +26,8 @@ dev = [
     "pytest-cov>=4.1.0,<5",
     "httpx>=0.25.0,<0.26",
 ]
-eval = [
-    "lm-eval[api]==0.4.4",
-    "fastapi-utils>=0.8.0",
-    "typing-inspect==0.9.0",
-]
+eval = ["lm-eval[api]==0.4.4", "fastapi-utils>=0.8.0", "typing-inspect==0.9.0"]
+protobuf = ["numpy>=1.24.0,<2", "grpcio>=1.62.1,<2", "grpcio-tools>=1.62.1,<2"]
 
 [tool.hatch.build.targets.sdist]
 include = ["src"]

scripts/generate_protos.sh

@@ -0,0 +1,28 @@
+#!/bin/bash
+# Script to generate protobuf stubs
+
+set -e
+
+SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+PROTO_DIR="${SCRIPT_DIR}/../src/proto"
+
+echo "Generating Python protobuf stubs..."
+cd "${PROTO_DIR}"
+
+PROTO_FILES=$(find . -name "*.proto")
+if [ -z "$PROTO_FILES" ]; then
+    echo "No .proto files found in ${PROTO_DIR}"
+    exit 1
+fi
+
+for PROTO_FILE in $PROTO_FILES; do
+    echo "Compiling ${PROTO_FILE}..."
+    protoc --python_out=. --proto_path=. "$PROTO_FILE"
+done
+
+if [ ! -f "__init__.py" ]; then
+    echo "# Generated protobuf package" > "__init__.py"
+    echo "Created __init__.py file"
+fi
+
+echo "Protobuf generation completed successfully!"