Update app.py

app.py

@@ -1,24 +1,30 @@
 import gradio as gr
 
-from transformers import pipeline
-
-pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-en-ru")
-
-
-def translate(text):
-    return pipe(text)[0]["translation_text"]
-
-
-with gr.Blocks() as demo:
-    with gr.Row():
-        with gr.Column():
-            english = gr.Textbox(label="English text")
-            translate_btn = gr.Button(value="Translate")
-        with gr.Column():
-            russian = gr.Textbox(label="Russian Text")
-
-    translate_btn.click(translate, inputs=english, outputs=russian, api_name="translate-to-russian")
-    examples = gr.Examples(examples=["I went to the supermarket yesterday.", "Helen is a good swimmer."],
-                           inputs=[english])
-
-demo.launch()
+# Function to handle the logic of PDF viewing, test solving, and homework uploading
+def process_education(topic, test_solution, homework_file):
+    # Here you would add the logic to display the PDF associated with the chosen topic,
+    # check the test solution, and handle the homework file upload.
+    # This is a placeholder for demonstration purposes.
+    pdf_view = "PDF for topic: " + topic
+    test_result = "Test result based on solution: " + test_solution
+    return pdf_view, test_result
+
+# Create the Gradio interface
+iface = gr.Interface(
+    process_education,
+    [
+        gr.inputs.Dropdown(['Topic 1', 'Topic 2', 'Topic 3'], label="Choose Topic"),
+        gr.inputs.Textbox(lines=2, label="Solve the Test"),
+        gr.inputs.File(label="Upload Homework")
+    ],
+    [
+        gr.outputs.HTML(label="View PDF of Chosen Topic"),
+        gr.outputs.Textbox(label="Your Test Result")
+    ]
+)
+
+# Launch the interface; when deploying to Hugging Face Spaces, this line is not needed
+# iface.launch()
+
+# Save the interface to be deployed on Hugging Face Spaces
+iface.save_to_huggingface_space("YOUR_HUGGINGFACE_USERNAME/YOUR_SPACE_NAME")