Update app.py

app.py

@@ -250,49 +250,49 @@ with gr.Blocks(title="Jerry • HW Intake (Echo)") as demo:
         norm_df = gr.Dataframe(label="Detected table (normalized)", interactive=False)
         btn2.click(handle_image, inputs=img_in, outputs=[ocr_txt, params_json2, raw_df, norm_df])
 
-    with gr.Tab("Straight‑Line • Solve & Check"):
-    gr.Markdown("Enter params (auto-filled if detected) → build the correct SL schedule → compare to your uploaded table.")
-    with gr.Row():
-        in_cost = gr.Number(label="Cost", value=0.0)
-        in_salv = gr.Number(label="Salvage", value=0.0)
-        in_life = gr.Number(label="Life (years)", value=10, precision=0)
-        in_year = gr.Number(label="Start year", value=2025, precision=0)
-    btn_build = gr.Button("Build expected schedule")
-    expected_df = gr.Dataframe(label="Expected (SL) schedule", interactive=False)
-    btn_check = gr.Button("Check against uploaded table")
-    deltas_df  = gr.Dataframe(label="Differences (student − expected)", interactive=False)
-    coach_txt  = gr.Markdown()
-
-    def fill_from_state(p):
-        # prefill controls when we have parsed params
-        p = p or {}
-        return (
-            p.get("cost", 0.0),
-            p.get("salvage", 0.0),
-            p.get("life", 10),
-            p.get("start_year", pd.Timestamp.now().year),
-        )
-
-    def build_cb(cost, salv, life, year):
-        try:
-            df = build_sl_schedule(float(cost), float(salv), int(life), int(year))
-        except Exception as e:
-            return pd.DataFrame([{"error": str(e)}])
-        return df
-
-    def check_cb(cost, salv, life, year, table):
-        exp = build_sl_schedule(float(cost), float(salv), int(life), int(year))
-        deltas, msg = audit_against_expected(exp, table if isinstance(table, pd.DataFrame) else pd.DataFrame())
-        return deltas, msg
-
-    # Wire up
-    btn_build.click(build_cb, [in_cost, in_salv, in_life, in_year], [expected_df])
-    btn_check.click(check_cb, [in_cost, in_salv, in_life, in_year, last_table], [deltas_df, coach_txt])
-
-    btn1.click(handle_docx, inputs=docx_in,
-           outputs=[header_txt, params_json, table_df, last_params, last_table])
-    btn2.click(handle_image, inputs=img_in,
-           outputs=[ocr_txt, params_json2, raw_df, norm_df, last_params, last_table])
+     with gr.Tab("Straight-Line • Solve & Check"):
+        gr.Markdown("Enter params (auto-filled if detected) → build the correct SL schedule → compare to your uploaded table.")
+        with gr.Row():
+            in_cost = gr.Number(label="Cost", value=0.0)
+            in_salv = gr.Number(label="Salvage", value=0.0)
+            in_life = gr.Number(label="Life (years)", value=10, precision=0)
+            in_year = gr.Number(label="Start year", value=2025, precision=0)
+        btn_build = gr.Button("Build expected schedule")
+        expected_df = gr.Dataframe(label="Expected (SL) schedule", interactive=False)
+        btn_check = gr.Button("Check against uploaded table")
+        deltas_df  = gr.Dataframe(label="Differences (student − expected)", interactive=False)
+        coach_txt  = gr.Markdown()
+
+        def fill_from_state(p):
+            # prefill controls when we have parsed params
+            p = p or {}
+            return (
+                p.get("cost", 0.0),
+                p.get("salvage", 0.0),
+                p.get("life", 10),
+                p.get("start_year", pd.Timestamp.now().year),
+            )
+
+        def build_cb(cost, salv, life, year):
+            try:
+                df = build_sl_schedule(float(cost), float(salv), int(life), int(year))
+            except Exception as e:
+                return pd.DataFrame([{"error": str(e)}])
+            return df
+
+        def check_cb(cost, salv, life, year, table):
+            exp = build_sl_schedule(float(cost), float(salv), int(life), int(year))
+            deltas, msg = audit_against_expected(exp, table if isinstance(table, pd.DataFrame) else pd.DataFrame())
+            return deltas, msg
+
+        # Wire up
+        btn_build.click(build_cb, [in_cost, in_salv, in_life, in_year], [expected_df])
+        btn_check.click(check_cb, [in_cost, in_salv, in_life, in_year, last_table], [deltas_df, coach_txt])
+   
+        
+
+        
+        
 
     # When params state changes, prefill inputs
     last_params.change(lambda p: fill_from_state(p), inputs=last_params,