WIP: add integration test tldr

.github/workflows/_flagship-apps.yml

@@ -43,9 +43,10 @@ jobs:
       fail-fast: false
       matrix:
         include:
-          - {app: "flashy", repo: "Lightning-Universe/Flashy-app"}
-          - {app: "muse", repo: "Lightning-Universe/stable-diffusion-deploy"}
-          - {app: "jupyter", repo: "Lightning-Universe/Jupyter-component"}
+          - {app: "flashy", repo: "Lightning-Universe/Flashy-app", requirements: ''}
+          - {app: "muse", repo: "Lightning-Universe/stable-diffusion-deploy", requirements: ''}
+          - {app: "jupyter", repo: "Lightning-Universe/Jupyter-component", requirements: ''}
+          - {app: "tldr", repo: "Lightning-Universe/TLDR-component", requirements: 'tests/requirements.txt'}
 
           # TODO:
           # - Training Studio
@@ -89,6 +90,14 @@ jobs:
 
       - name: Install Lightning package
         run: pip install -e .[cloud,test] -f $TORCH_URL
+
+      - name: Install Repo
+        run: pip install -e ./tests/_flagship-app
+
+      - name: Install Flagship Test Requirements
+        run: pip install -r ./tests/_flagship-app/${{ matrix.requirements }}
+        if: ${{ matrix.requirements }}
+
       - name: List pip dependency
         run: pip --version && pip list
 

tests/integrations_app/flagship/test_tldr.py

@@ -0,0 +1,37 @@
+from time import sleep
+
+from integrations_app.flagship import _PATH_INTEGRATIONS_DIR
+
+from lightning.app.testing.testing import run_app_in_cloud
+
+
+def test_app_in_cloud():
+
+    with run_app_in_cloud(_PATH_INTEGRATIONS_DIR, "dummy_test_app.py") as (
+        _,
+        view_page,
+        fetch_logs,
+        name,
+    ):
+
+        # Validate the logs.
+        has_logs = False
+        while not has_logs:
+            logs = list(fetch_logs("multinode.ws.0"))
+            for log in logs:
+                if "`Trainer.fit` stopped: `max_epochs=2` reached." in log:
+                    has_logs = True
+            sleep(1)
+
+    expected_strings = [
+        # don't include values for actual hardware availability as this may depend on environment.
+        "GPU available: ",
+        "All distributed processes registered.",
+        "674 K    Trainable params\n0         Non - trainable params\n674 K    Total params\n2.699   Total estimated model params size(MB)",
+        "Epoch 0:",
+        "`Trainer.fit` stopped: `max_epochs=2` reached.",
+        "Input text:Input text:\n summarize: ML Ops platforms come in many flavors from platforms that train models",
+    ]
+
+    for curr_str in expected_strings:
+        assert any([curr_str in line for line in logs])