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Dockerfile

@@ -6,19 +6,16 @@ COPY ./requirements.txt /code/requirements.txt
 
 RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
 
-# Set up a new user named "user" with user ID 1000
 RUN useradd -m -u 1000 user
-# Switch to the "user" user
+
 USER user
-# Set home to the user's home directory
+
 ENV HOME=/home/user \
     PATH=/home/user/.local/bin:$PATH
 
-# Set the working directory to the user's home directory
+
 WORKDIR $HOME/app
 
-# Copy the current directory contents into the container at $HOME/app setting the owner to the user
 COPY --chown=user . $HOME/app
 
-
 CMD ["python", "app.py"]

app.py

@@ -1,28 +1,10 @@
 import gradio as gr
-import torch
-import requests
-from torchvision import transforms
-
-model = torch.hub.load("pytorch/vision:v0.6.0", "resnet18", pretrained=True).eval()
-response = requests.get("https://git.io/JJkYN")
-labels = response.text.split("\n")
-
-
-def predict(inp):
-    inp = transforms.ToTensor()(inp).unsqueeze(0)
-    with torch.no_grad():
-        prediction = torch.nn.functional.softmax(model(inp)[0], dim=0)
-        confidences = {labels[i]: float(prediction[i]) for i in range(1000)}
-    return confidences
 
+def greet(name):
+    return "Hello " + name + "!!"
 
 def run():
-    demo = gr.Interface(
-        fn=predict,
-        inputs=gr.inputs.Image(type="pil"),
-        outputs=gr.outputs.Label(num_top_classes=3),
-    )
-
+    demo = gr.Interface(fn=greet, inputs="text", outputs="text")
     demo.launch(server_name="0.0.0.0", server_port=7860)
 
 

requirements.txt

@@ -1,4 +1 @@
-gradio
-torch
-torchvision
-requests
+gradio