FEAT: add Swagger UI to deployed model containers with MLflow signature schema

backend/domain/entities/docker/dockerfile_template.py

@@ -16,6 +16,7 @@ def __init__(self, python_version: str):
         # Set environment variables
         ENV IMAGE_NAME={image_name}
         ENV OTEL_METRICS_EXPORTER_LABELS="project_name={project_name},model_name={model_name},model_version={model_version}"
+        ENV ROOT_PATH=""
 
         # Setup uv
         RUN wget -qO- https://astral.sh/uv/install.sh | sh && which uv || echo "UV installation failed"
@@ -47,7 +48,7 @@ def __init__(self, python_version: str):
         EXPOSE 8000
 
         # Activate conda environment and start the application
-        CMD ["bash", "-c", "uv run opentelemetry-instrument --service_name $IMAGE_NAME uvicorn fast_api_template:app --host 0.0.0.0 --port 8000 --log-level debug"]
+        CMD ["bash", "-c", "uv run opentelemetry-instrument --service_name $IMAGE_NAME uvicorn fast_api_template:app --host 0.0.0.0 --port 8000 --root-path $ROOT_PATH --log-level debug"]
         """
 
     def generate_dockerfile(

backend/domain/entities/docker/fast_api_template.py

@@ -12,31 +12,113 @@
 from opentelemetry.sdk.metrics import MeterProvider
 from opentelemetry.sdk.resources import SERVICE_NAME, Resource
 from prometheus_client import generate_latest
-from pydantic import BaseModel
+from pydantic import BaseModel, create_model
 
 try:
     logger.info("Starting up and loading model...")
     model = mlflow.pyfunc.load_model("/opt/mlflow/")
     logger.info("Model loaded successfully")
 except Exception as e:
     logger.error(f"Error loading model: {e}")
+    model = None
 
 image_name = os.environ["IMAGE_NAME"]
 
 tracer = trace.get_tracer(f"model_platform_{image_name}")
 
-app = FastAPI(reload=True)
+# ---------------------------------------------------------------------------
+# Dynamic schema discovery from MLflow model signature
+# ---------------------------------------------------------------------------
+MLFLOW_TYPE_MAP = {
+    "double": float,
+    "float": float,
+    "long": int,
+    "integer": int,
+    "string": str,
+    "boolean": bool,
+}
+
+DynamicInputs = None
+DynamicOutputs = None
+signature_description = ""
 
+try:
+    if model is not None and hasattr(model, "metadata") and model.metadata and model.metadata.signature:
+        sig = model.metadata.signature
+
+        # Build input schema
+        if sig.inputs and hasattr(sig.inputs, "inputs") and sig.inputs.inputs:
+            fields = {}
+            field_descriptions = []
+            for col in sig.inputs.inputs:
+                col_type_str = str(col.type)
+                py_type = MLFLOW_TYPE_MAP.get(col_type_str, Any)
+                fields[col.name] = (py_type, ...)
+                field_descriptions.append(f"- **{col.name}**: `{col_type_str}`")
+            if fields:
+                DynamicInputs = create_model("ModelInputs", **fields)
+                signature_description = "### Input schema (from MLflow signature)\n" + "\n".join(field_descriptions)
+                logger.info(f"Built dynamic input schema with {len(fields)} fields: {list(fields.keys())}")
+
+        # Build output schema (best-effort, less critical)
+        if sig.outputs and hasattr(sig.outputs, "inputs") and sig.outputs.inputs:
+            out_fields = {}
+            for col in sig.outputs.inputs:
+                col_type_str = str(col.type)
+                py_type = MLFLOW_TYPE_MAP.get(col_type_str, Any)
+                out_fields[col.name] = (py_type, ...)
+            if out_fields:
+                DynamicOutputs = create_model("ModelOutputs", **out_fields)
+                logger.info(f"Built dynamic output schema with {len(out_fields)} fields: {list(out_fields.keys())}")
+
+except Exception as e:
+    logger.warning(f"Could not build dynamic schema from model signature, falling back to generic schema: {e}")
+    DynamicInputs = None
+    DynamicOutputs = None
+    signature_description = ""
+
+# ---------------------------------------------------------------------------
+# Request / Response models (dynamic if signature available, generic fallback)
+# ---------------------------------------------------------------------------
+if DynamicInputs is not None:
+
+    class PredictionRequest(BaseModel):
+        inputs: DynamicInputs
+
+else:
 
-class PredictionRequest(BaseModel):
-    inputs: Dict[str, Any]
+    class PredictionRequest(BaseModel):
+        inputs: Dict[str, Any]
 
 
 class PredictionResponse(BaseModel):
     outputs: Any
 
 
-@app.post("/predict", response_model=PredictionResponse)
+# ---------------------------------------------------------------------------
+# FastAPI application
+# ---------------------------------------------------------------------------
+api_description = f"""Inference API for deployed ML model **{image_name}**.
+
+Accepts JSON payloads or file uploads for prediction.
+
+{signature_description}
+"""
+
+app = FastAPI(
+    title=f"Model API - {image_name}",
+    description=api_description,
+    version="1.0.0",
+    root_path=os.getenv("ROOT_PATH", ""),
+)
+
+
+@app.post(
+    "/predict",
+    response_model=PredictionResponse,
+    summary="Run inference",
+    description="Send input features as JSON or upload a file for prediction.",
+)
 async def predict(request: Request, file: Optional[UploadFile] = File(None)):
     tracer = trace.get_tracer(__name__)
     try:
@@ -58,6 +140,8 @@ async def predict(request: Request, file: Optional[UploadFile] = File(None)):
 
             if isinstance(input_data, dict):
                 input_df = pd.DataFrame([input_data])
+            elif isinstance(input_data, BaseModel):
+                input_df = pd.DataFrame([input_data.model_dump()])
             else:
                 input_df = pd.DataFrame(input_data)
 
@@ -77,18 +161,18 @@ async def predict(request: Request, file: Optional[UploadFile] = File(None)):
         raise HTTPException(status_code=500, detail=str(e))
 
 
-@app.get("/health")
+@app.get("/health", summary="Health check")
 async def health_check():
     return {"status": "healthy"}
 
 
-@app.get("/metrics")
+@app.get("/metrics", summary="Prometheus metrics")
 def metrics_endpoint():
     return Response(content=generate_latest(), media_type="text/plain")
 
 
 FastAPIInstrumentor.instrument_app(app)
-# Check si on devrait mettre le service name lié à k8s
+# Check si on devrait mettre le service name lie a k8s
 resource = Resource.create(attributes={SERVICE_NAME: f"model-platform-{image_name}"})
 
 # Prometheus client

backend/infrastructure/k8s_model_deployment_adapter.py

@@ -80,6 +80,12 @@ def _create_model_service_deployment(self):
                                 image=f"{self.docker_image_name}:latest",
                                 image_pull_policy="IfNotPresent",  # Ajouté pour éviter les erreurs de pull
                                 ports=[client.V1ContainerPort(container_port=self.port)],
+                                env=[
+                                    client.V1EnvVar(
+                                        name="ROOT_PATH",
+                                        value=f"/deploy/{self.namespace}/{self.service_name}",
+                                    ),
+                                ],
                             )
                         ],
                         restart_policy="Always",  # Bonne pratique pour un Deployment

frontend/js/pages/monitoring.js

@@ -248,6 +248,7 @@ const MonitoringPage = (() => {
                           <div class="model-row-version">v${m.version}</div>
                         </div>
                         <div class="model-row-actions">
+                          <a href="${m.deployment_name && m.project ? `http://${window.MP_HOST_NAME || ''}/deploy/${m.project}/${m.deployment_name}/docs` : '#'}" target="_blank" rel="noopener" class="model-row-link${!m.deployment_name ? ' model-row-link-disabled' : ''}" title="Open API Docs (Swagger)"><svg width="14" height="14" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><path d="M14 2H6a2 2 0 0 0-2 2v16a2 2 0 0 0 2 2h12a2 2 0 0 0 2-2V8z"></path><polyline points="14 2 14 8 20 8"></polyline><line x1="16" y1="13" x2="8" y2="13"></line><line x1="16" y1="17" x2="8" y2="17"></line></svg></a>
                           <a href="${m.dashboard_url ? m.dashboard_url + GRAFANA_QUERY_PARAMS : '#'}" target="_blank" rel="noopener" class="model-row-link${!m.dashboard_url ? ' model-row-link-disabled' : ''}" title="Open Grafana dashboard"><svg width="14" height="14" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><path d="M18 13v6a2 2 0 0 1-2 2H5a2 2 0 0 1-2-2V8a2 2 0 0 1 2-2h6"></path><polyline points="15 3 21 3 21 9"></polyline><line x1="10" y1="14" x2="21" y2="3"></line></svg></a>
                         </div>
                       </div>

frontend/js/pages/project-detail.js

@@ -636,6 +636,7 @@ const ProjectDetailPage = (() => {
       const dashUrl     = m.dashboard_url    || buildDashboardUrl(projectName, deployName);
       const deployDate  = m.deployment_date  ? new Date(m.deployment_date).toLocaleDateString() : '—';
       const endpointUrl = buildDashboardUrl(projectName, deployName);
+      const docsUrl     = endpointUrl ? `${endpointUrl}/docs` : '';
 
       return `
         <tr>
@@ -647,6 +648,7 @@ const ProjectDetailPage = (() => {
           <td>${statusBadge(status)}</td>
           <td class="actions">
             <div class="flex gap-2 justify-end">
+              ${docsUrl ? `<a href="${escHtml(docsUrl)}" target="_blank" rel="noopener" class="btn btn-secondary btn-sm">API Docs</a>` : ''}
               ${dashUrl ? `<a href="${escHtml(dashUrl)}" target="_blank" rel="noopener" class="btn btn-secondary btn-sm">Dashboard</a>` : ''}
               <button class="btn btn-danger btn-sm undeploy-btn" data-model="${escHtml(name)}" data-version="${escHtml(String(version))}">Undeploy</button>
             </div>

infrastructure/k8s/nginx-configmap.yaml

@@ -164,6 +164,42 @@ data:
                   proxy_read_timeout 86400;
               }
 
+            location ~ ^/deploy/([^/]+)/([^/]+)/docs$ {
+                  set $project_name $1;
+                  set $deployment_name $2;
+
+                  resolver kube-dns.kube-system.svc.cluster.local valid=10s;
+
+                  proxy_pass http://$deployment_name.$project_name.svc.cluster.local:8000/docs;
+
+                  proxy_set_header Host $host;
+                  proxy_set_header X-Real-IP $remote_addr;
+                  proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
+                  proxy_set_header X-Forwarded-Proto $scheme;
+                  proxy_http_version 1.1;
+                  proxy_set_header Upgrade $http_upgrade;
+                  proxy_set_header Connection "upgrade";
+                  proxy_read_timeout 86400;
+              }
+
+            location ~ ^/deploy/([^/]+)/([^/]+)/openapi\.json$ {
+                  set $project_name $1;
+                  set $deployment_name $2;
+
+                  resolver kube-dns.kube-system.svc.cluster.local valid=10s;
+
+                  proxy_pass http://$deployment_name.$project_name.svc.cluster.local:8000/openapi.json;
+
+                  proxy_set_header Host $host;
+                  proxy_set_header X-Real-IP $remote_addr;
+                  proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
+                  proxy_set_header X-Forwarded-Proto $scheme;
+                  proxy_http_version 1.1;
+                  proxy_set_header Upgrade $http_upgrade;
+                  proxy_set_header Connection "upgrade";
+                  proxy_read_timeout 86400;
+              }
+
             location /prometheus/ {
               resolver kube-dns.kube-system.svc.cluster.local valid=10s;
               proxy_pass http://kube-prometheus-stack-prometheus.monitoring.svc.cluster.local:9090/;