Update app.py

app.py

@@ -39,15 +39,6 @@ def _coerce_numeric(x):
     try: return float(s)
     except: return pd.NA
 
-# ---- NEW: in‑memory file helpers (no disk writes) ----
-def _csv_bytes(df: pd.DataFrame | None) -> bytes:
-    buf = io.StringIO()
-    (df if df is not None else pd.DataFrame()).to_csv(buf, index=False)
-    return buf.getvalue().encode("utf-8")
-
-def _text_bytes(txt: str | None) -> bytes:
-    return (txt or "").encode("utf-8")
-
 PARAM_PATTERNS = {
     "cost":       r"cost\s*[:=]\s*\$?\s*([\d,]+(?:\.\d+)?)",
     "salvage":    r"salvage\s*[:=]\s*\$?\s*([\d,]+(?:\.\d+)?)",
@@ -250,42 +241,31 @@ def handle_docx(file):
 #   )
 
 def handle_image(img):
-    """OCR → table (raw + normalized) → keep types safe for Gradio."""
-    from PIL import Image as PILImage
-
-    # If nothing uploaded, return safe empties for every output
     if img is None:
-        empty = pd.DataFrame()
-        yr = pd.Timestamp.now().year
-        return ("(no image)", {}, empty, empty, 0.0, 0.0, 10, yr, {}, empty)
+        return "(no image)", {}, pd.DataFrame(), pd.DataFrame(), 0.0, 0.0, 10, pd.Timestamp.now().year, {}, pd.DataFrame()
 
-    # Convert to PIL (handles ndarray vs PIL.Image)
+    from PIL import Image as PILImage
     pil = img if isinstance(img, PILImage.Image) else PILImage.fromarray(img)
 
-    # 1) OCR text
-    ocr_text = _image_to_text(pil) or ""
+    ocr_text = _image_to_text(pil)
+    params = _extract_params(ocr_text or "")
+    df_raw = _table_from_ocr_text(ocr_text or "")
+    df_norm = _normalize_depr_columns(df_raw) if df_raw is not None else pd.DataFrame()
 
-    # 2) Try to pick params out of the OCR text
-    params = _extract_params(ocr_text)
     cost, salv, life, year = _params_tuple(params)
 
-    # 3) Parse a table from OCR text
-    raw = _table_from_ocr_text(ocr_text or "")
-
-    # 🔒 IMPORTANT: never return None to gr.Dataframe
-    raw_df  = raw if isinstance(raw, pd.DataFrame) else pd.DataFrame()
-    norm_df = _normalize_depr_columns(raw_df) if not raw_df.empty else pd.DataFrame()
-
     return (
-        (ocr_text if ocr_text.strip() else "(empty OCR)"),
-        params,          # JSON box
-        raw_df,          # Raw table (always a DataFrame)
-        norm_df,         # Normalized table (always a DataFrame)
-        cost, salv, life, year,  # Autofill numbers
-        params,          # last_params state
-        norm_df          # last_table state (what the checker expects)
+        ocr_text or "(empty OCR)",
+        params,
+        df_raw,                  # raw table shown in OCR tab
+        df_norm,                 # normalized table shown in OCR tab
+        cost, salv, life, year,  # auto-fill numbers
+        params,                  # save params state
+        df_norm                  # 🔹 save normalized table to last_table (same as docx)
     )
 
+
+
 def fill_from_state(p):
     p = p or {}
     return (
@@ -311,7 +291,7 @@ def check_cb(cost, salv, life, year, table_state):
     if not isinstance(table_state, pd.DataFrame) or table_state.empty:
         return pd.DataFrame(), "No student table found to check."
 
-    # re-normalize and coerce here every time
+    # 👇 Gradio returns strings → re-normalize and coerce here every time
     actual = _normalize_depr_columns(table_state)
     for c in ["Year", "Begin BV", "Depreciation", "Accum Dep", "End BV"]:
         actual[c] = pd.to_numeric(actual[c], errors="coerce")
@@ -342,16 +322,7 @@ with gr.Blocks(title="Jerry • HW Intake (Echo)") as demo:
         ocr_txt = gr.Textbox(label="Raw OCR text", lines=12)
         params_json2 = gr.JSON(label="Detected parameters")
         raw_df = gr.Dataframe(label="Raw table guess", interactive=False)
-        # make editable so you can fix numbers
-        norm_df = gr.Dataframe(label="Detected table (normalized)", interactive=True)
-
-        # ---- NEW: in‑memory downloads ----
-        raw_dl  = gr.DownloadButton(label="Download RAW CSV")
-        norm_dl = gr.DownloadButton(label="Download NORMALIZED CSV")
-        txt_dl  = gr.DownloadButton(label="Download OCR TEXT")
-
-        # re‑export after manual edits
-        export_btn = gr.DownloadButton(label="Download EDITED NORMALIZED CSV")
+        norm_df = gr.Dataframe(label="Detected table (normalized)", interactive=False)
 
     # --- Tab 3: Solve & Check ---
     with gr.Tab("Straight-Line • Solve & Check"):
@@ -391,9 +362,6 @@ with gr.Blocks(title="Jerry • HW Intake (Echo)") as demo:
             params_json2,      # json
             raw_df,            # raw table
             norm_df,           # normalized table (tab 2)
-            raw_dl,            # NEW: bytes -> RAW CSV download
-            norm_dl,           # NEW: bytes -> NORMALIZED CSV download
-            txt_dl,            # NEW: bytes -> OCR TEXT download
             in_cost, in_salv, in_life, in_year,   # autofill inputs
             last_params,       # state
             last_table,        # state
@@ -410,12 +378,6 @@ with gr.Blocks(title="Jerry • HW Intake (Echo)") as demo:
     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])
 
-    # ---- NEW: export edited normalized CSV ----
-    def export_current(norm_df_current: pd.DataFrame):
-        return _csv_bytes(norm_df_current if isinstance(norm_df_current, pd.DataFrame) else pd.DataFrame())
-
-    export_btn.click(export_current, inputs=norm_df, outputs=export_btn)
-
     gr.Markdown("— Echo mode finished. When this looks good, we’ll plug in the SL solver + coaching.")
 
 if __name__ == "__main__":