mcamargo00 commited on
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5d1f599
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1 Parent(s): 11b5366

Upload app.py

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  1. app.py +8 -6
app.py CHANGED
@@ -415,9 +415,8 @@ def classify_solution_stream(question: str, solution: str, progress=gr.Progress(
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  yield "Runtime error", f"{type(e).__name__}: {e}", "❌ Exception during inference."
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-
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  # Create Gradio interface (streaming UI)
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- with gr.Blocks(title="Math Solution Classifier", theme=gr.themes.Soft(), queue=True) as app:
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  gr.Markdown("# 🧮 Math Solution Classifier")
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  gr.Markdown(
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  "Classify math solutions as **correct**, **conceptually flawed**, or **computationally flawed**. "
@@ -444,8 +443,8 @@ with gr.Blocks(title="Math Solution Classifier", theme=gr.themes.Soft(), queue=T
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  # ---------- Right: outputs ----------
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  with gr.Column(scale=1):
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  classification_output = gr.Textbox(label="Classification", interactive=False)
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- explanation_output = gr.Textbox(label="Explanation", interactive=False, lines=6)
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- status_output = gr.Markdown(value="*(idle)*") # live stage updates
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  # ---------- Examples ----------
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  gr.Examples(
@@ -468,10 +467,10 @@ with gr.Blocks(title="Math Solution Classifier", theme=gr.themes.Soft(), queue=T
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  # ---------- Wiring ----------
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  classify_btn.click(
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- fn=classify_solution_stream, # <- your generator function
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  inputs=[question_input, solution_input],
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  outputs=[classification_output, explanation_output, status_output],
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- show_progress="hidden", # single compact global bar; no per-output bars
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  )
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  # Clear everything
@@ -488,5 +487,8 @@ with gr.Blocks(title="Math Solution Classifier", theme=gr.themes.Soft(), queue=T
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  queue=False,
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  )
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  if __name__ == "__main__":
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  app.launch()
 
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  yield "Runtime error", f"{type(e).__name__}: {e}", "❌ Exception during inference."
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  # Create Gradio interface (streaming UI)
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+ with gr.Blocks(title="Math Solution Classifier", theme=gr.themes.Soft()) as app:
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  gr.Markdown("# 🧮 Math Solution Classifier")
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  gr.Markdown(
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  "Classify math solutions as **correct**, **conceptually flawed**, or **computationally flawed**. "
 
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  # ---------- Right: outputs ----------
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  with gr.Column(scale=1):
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  classification_output = gr.Textbox(label="Classification", interactive=False)
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+ explanation_output = gr.Textbox(label="Explanation", interactive=False, lines=6)
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+ status_output = gr.Markdown(value="*(idle)*") # live stage updates
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  # ---------- Examples ----------
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  gr.Examples(
 
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  # ---------- Wiring ----------
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  classify_btn.click(
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+ fn=classify_solution_stream, # your generator
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  inputs=[question_input, solution_input],
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  outputs=[classification_output, explanation_output, status_output],
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+ show_progress="hidden", # single compact global bar
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  )
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  # Clear everything
 
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  queue=False,
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  )
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+ # Enable queue AFTER building (needed for streaming on Spaces)
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+ app.queue(concurrency_count=1, max_size=16)
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+
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  if __name__ == "__main__":
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  app.launch()