Delete page_files/categorized/Backend/plot_mapping_ui.py

page_files/categorized/Backend/plot_mapping_ui.py

@@ -1,397 +0,0 @@
-"""
-plot_mapping_ui.py
-------------------
-Drop-in replacement for the "Extracted Plots" tab (tab2) in Upload_Data.py.
-
-HOW TO INTEGRATE
-────────────────
-1. Copy plot_property_mapper.py next to upload_backend.py.
-2. In Upload_Data.py, add at the top:
-
-       from plot_mapping_ui import render_plot_mapping_tab
-
-3. Replace the entire `with tab2:` block with:
-
-       with tab2:
-           render_plot_mapping_tab(pdf_path, paper_id)
-
-That's it.  The function reads everything it needs from st.session_state
-(which your existing tab1 code already populates).
-"""
-
-import json
-import os
-
-import cv2
-import numpy as np
-import streamlit as st
-
-from plot_property_mapper import (
-    batch_map_plots,
-    fetch_properties_for_material,
-    save_plot_image_mapping,
-)
-
-# ── tiny helper ───────────────────────────────────────────────────────────────
-
-def _confidence_badge(conf: str) -> str:
-    colors = {"high": "#16a34a", "medium": "#d97706", "low": "#dc2626"}
-    c = colors.get(conf.lower(), "#6b7280")
-    return (
-        f"<span style='background:{c};color:#fff;padding:2px 10px;"
-        f"border-radius:99px;font-size:0.78rem;font-weight:700'>{conf.upper()}</span>"
-    )
-
-
-# ── main render function ───────────────────────────────────────────────────────
-
-def render_plot_mapping_tab(pdf_path: str, paper_id: str):
-    """Render the full Extracted Plots + Property Mapping tab."""
-
-    st.subheader("Extracted Plot Images & Property Mapping")
-
-    # ── session-state keys ────────────────────────────────────────────────────
-    for key, default in [
-        ("pdf_processed",       False),
-        ("image_results",       []),
-        ("mapped_results",      []),
-        ("mapping_done",        False),
-        ("saved_image_mapping", {}),
-        ("pdf_extracted_df",    __import__("pandas").DataFrame()),
-        ("pdf_extracted_meta",  {}),
-    ]:
-        if key not in st.session_state:
-            st.session_state[key] = default
-
-    # ── 1. Extract plots if not done yet ─────────────────────────────────────
-    if not st.session_state.pdf_processed:
-        with st.spinner("Extracting plots from PDF…"):
-            import fitz
-            from upload_backend import extract_images
-
-            doc = fitz.open(pdf_path)
-            st.session_state.image_results = extract_images(doc)
-            doc.close()
-            st.session_state.pdf_processed  = True
-            st.session_state.mapping_done   = False   # reset mapping on new PDF
-
-    image_results = st.session_state.image_results
-
-    if not image_results:
-        st.warning("No plots found in this PDF.")
-        return
-
-    # ── 2. Info bar ───────────────────────────────────────────────────────────
-    has_data = not st.session_state.pdf_extracted_df.empty
-    material_class = st.session_state.get("selected_material_class")   # set below
-
-    if has_data:
-        df = st.session_state.pdf_extracted_df
-        mat_abbr = df.iloc[0]["material_abbreviation"]
-        st.info(
-            f"**{len(image_results)} plots** extracted  |  "
-            f"Material: **{mat_abbr}**  |  "
-            f"{len(df['property_name'].unique())} DB properties available"
-        )
-    else:
-        st.warning(
-            "Extract material data in the **Material Data** tab first "
-            "to enable AI property mapping."
-        )
-
-    st.divider()
-
-    # ── 3. Download buttons (always visible) ──────────────────────────────────
-    from upload_backend import create_zip
-
-    col_img, col_json, col_all = st.columns(3)
-    with col_img:
-        img_zip = create_zip(image_results, include_json=False)
-        st.download_button(
-            "⬇ Download Images",
-            data=img_zip,
-            file_name=f"{paper_id}_images.zip",
-            mime="application/zip",
-            use_container_width=True,
-            key="dl_images",
-        )
-    with col_json:
-        json_data = [
-            {"caption": r["caption"], "page": r["page"],
-             "image_count": len(r["image_data"])}
-            for r in image_results
-        ]
-        st.download_button(
-            "⬇ Download JSON",
-            data=json.dumps(json_data, indent=4),
-            file_name=f"{paper_id}_metadata.json",
-            mime="application/json",
-            use_container_width=True,
-            key="dl_json",
-        )
-    with col_all:
-        full_zip = create_zip(image_results, include_json=True)
-        st.download_button(
-            "⬇ Download All",
-            data=full_zip,
-            file_name=f"{paper_id}_complete.zip",
-            mime="application/zip",
-            use_container_width=True,
-            key="dl_all",
-        )
-
-    st.divider()
-
-    # ── 4. AI mapping panel (only when data is extracted) ────────────────────
-    if has_data:
-        from db import fetch_all  # your existing db module
-
-        df          = st.session_state.pdf_extracted_df
-        mat_abbr    = df.iloc[0]["material_abbreviation"]
-        extracted_json = st.session_state.get("pdf_extracted_meta", {})
-
-        # Material class selector (needed to route to the right table)
-        material_class = st.selectbox(
-            "Material class (for DB lookup)",
-            ["Polymer", "Fiber", "Composite"],
-            index=0,
-            key="selected_material_class",
-            help="Determines which PostgreSQL table to fetch properties from.",
-        )
-
-        run_mapping = st.button(
-            "🤖  Run AI Property Mapping",
-            type="primary",
-            disabled=st.session_state.mapping_done,
-            help="Sends each plot + caption + extracted JSON to Gemini for matching.",
-        )
-
-        if run_mapping:
-            # Fetch DB properties
-            with st.spinner("Fetching properties from PostgreSQL…"):
-                try:
-                    db_properties = fetch_properties_for_material(
-                        mat_abbr, material_class, fetch_all
-                    )
-                except Exception as exc:
-                    st.error(f"DB error: {exc}")
-                    db_properties = []
-
-            if not db_properties:
-                st.warning(
-                    f"No properties found for **{mat_abbr}** in the "
-                    f"**{material_class}** table.  Mapping will use all properties."
-                )
-
-            # Run batch mapping with progress bar
-            progress_bar = st.progress(0, text="Mapping plots…")
-
-            def _update(i, total, caption):
-                pct = int((i / max(total, 1)) * 100)
-                progress_bar.progress(
-                    pct,
-                    text=f"Mapping {i+1}/{total}: {caption[:60]}…",
-                )
-
-            with st.spinner("AI is analysing plots…"):
-                mapped = batch_map_plots(
-                    image_results=image_results,
-                    extracted_json=extracted_json,
-                    db_properties=db_properties,
-                    progress_callback=_update,
-                )
-
-            progress_bar.progress(100, text="Done!")
-            st.session_state.mapped_results = mapped
-            st.session_state.mapping_done   = True
-            st.success(f"✅  Mapped {len(mapped)} plots")
-            st.rerun()
-
-        if st.session_state.mapping_done and st.session_state.mapped_results:
-            st.caption("Mapping complete. Review & confirm each match below.")
-
-    st.divider()
-
-    # ── 5. Plot cards ─────────────────────────────────────────────────────────
-    use_mapped = (
-        has_data
-        and st.session_state.mapping_done
-        and bool(st.session_state.mapped_results)
-    )
-
-    display_list = (
-        st.session_state.mapped_results if use_mapped else image_results
-    )
-
-    for idx, item in enumerate(display_list):
-        caption     = item.get("caption", f"Figure {idx+1}")
-        page        = item.get("page", "?")
-        img_list    = item.get("image_data", [])
-        mapping     = item.get("mapping_result") if use_mapped else None
-
-        with st.container(border=True):
-
-            # — header row —
-            col_cap, col_del = st.columns([0.88, 0.12])
-            col_cap.markdown(f"**Page {page}** — {caption}")
-            if col_del.button("🗑 Delete", key=f"del_group_{idx}"):
-                if use_mapped:
-                    st.session_state.mapped_results.pop(idx)
-                else:
-                    st.session_state.image_results.pop(idx)
-                st.rerun()
-
-            # — AI mapping result banner —
-            if mapping:
-                prop_name  = mapping.get("property_name", "")
-                section    = mapping.get("section", "")
-                confidence = mapping.get("confidence", "low")
-                reasoning  = mapping.get("reasoning", "")
-                db_row     = mapping.get("db_row")
-                candidates = mapping.get("all_candidates", [])
-
-                badge = _confidence_badge(confidence)
-                if prop_name:
-                    st.markdown(
-                        f"🔗 **AI Match:** `{section}` › **{prop_name}** &nbsp; {badge}",
-                        unsafe_allow_html=True,
-                    )
-                    if reasoning:
-                        st.caption(f"💬 {reasoning}")
-
-                    # DB row details
-                    if db_row:
-                        with st.expander("📋 Matched DB row", expanded=False):
-                            col_v, col_u, col_c = st.columns(3)
-                            col_v.metric("Value",    db_row.get("value",        "—"))
-                            col_u.metric("Unit",     db_row.get("unit",         "—"))
-                            col_c.metric("Condition", db_row.get("test_condition", "—"))
-                            if db_row.get("comments"):
-                                st.caption(f"Comments: {db_row['comments']}")
-                            if db_row.get("english"):
-                                st.caption(f"English units: {db_row['english']}")
-
-                    # Alternative candidates
-                    if candidates:
-                        with st.expander("🔄 All candidates", expanded=False):
-                            for c in candidates:
-                                rank = c.get("rank", "?")
-                                cn   = c.get("confidence", "low")
-                                st.markdown(
-                                    f"{rank}. `{c.get('section','?')}` › "
-                                    f"**{c.get('property_name','?')}** "
-                                    f"&nbsp; {_confidence_badge(cn)}",
-                                    unsafe_allow_html=True,
-                                )
-                else:
-                    st.warning("⚠️ AI could not match this plot to any DB property.")
-
-            # — sub-images —
-            for p_idx, img_data in enumerate(img_list):
-                bgr = img_data.get("array")
-                if bgr is None:
-                    continue
-
-                img_key = f"{idx}_{p_idx}_{page}"
-
-                # Show the plot
-                st.image(bgr, channels="BGR", width=420)
-
-                # — mapping controls —
-                if has_data:
-                    df          = st.session_state.pdf_extracted_df
-                    mat_abbr    = df.iloc[0]["material_abbreviation"]
-                    property_list = df["property_name"].unique().tolist()
-
-                    # Pre-select the AI suggestion if available
-                    ai_suggestion = mapping.get("property_name", "") if mapping else ""
-                    default_idx   = 0
-                    options       = ["— Select property —"] + property_list
-                    if ai_suggestion in property_list:
-                        default_idx = property_list.index(ai_suggestion) + 1
-
-                    col_sel, col_sec, col_save, col_rem = st.columns(
-                        [0.42, 0.18, 0.20, 0.20]
-                    )
-
-                    with col_sel:
-                        selected = st.selectbox(
-                            "Property",
-                            options=options,
-                            index=default_idx,
-                            key=f"prop_sel_{img_key}",
-                            label_visibility="collapsed",
-                        )
-
-                    with col_sec:
-                        section_override = st.text_input(
-                            "Section",
-                            value=mapping.get("section", "") if mapping else "",
-                            key=f"sec_{img_key}",
-                            label_visibility="collapsed",
-                            placeholder="Section",
-                        )
-
-                    with col_save:
-                        if st.button("💾 Save", key=f"save_{img_key}"):
-                            if selected and selected != "— Select property —":
-                                filepath = save_plot_image_mapping(
-                                    mat_abbr,
-                                    selected,
-                                    section_override,
-                                    bgr,
-                                    save_dir="images",
-                                )
-                                st.session_state.saved_image_mapping[img_key] = {
-                                    "property":  selected,
-                                    "section":   section_override,
-                                    "caption":   caption,
-                                    "filename":  os.path.basename(filepath),
-                                    "path":      filepath,
-                                }
-                                st.success(f"Saved → `{os.path.basename(filepath)}`")
-                                st.rerun()
-                            else:
-                                st.warning("Select a property first.")
-
-                    with col_rem:
-                        if st.button("✕ Remove", key=f"rem_{img_key}"):
-                            img_list.pop(p_idx)
-                            if not img_list:
-                                if use_mapped:
-                                    st.session_state.mapped_results.pop(idx)
-                                else:
-                                    st.session_state.image_results.pop(idx)
-                            st.rerun()
-
-                    # Saved badge
-                    if img_key in st.session_state.saved_image_mapping:
-                        m = st.session_state.saved_image_mapping[img_key]
-                        st.info(f"✅ Saved as **{m['property']}** → `{m['filename']}`")
-
-                else:
-                    # No data extracted yet — just allow removal
-                    col_msg, col_rem = st.columns([0.80, 0.20])
-                    col_msg.caption(
-                        "Extract material data in the **Material Data** tab to enable mapping."
-                    )
-                    if col_rem.button("✕ Remove", key=f"rem_nodata_{img_key}"):
-                        img_list.pop(p_idx)
-                        if not img_list:
-                            st.session_state.image_results.pop(idx)
-                        st.rerun()
-
-                st.divider()
-
-    # ── 6. Saved-mappings summary ─────────────────────────────────────────────
-    if st.session_state.saved_image_mapping:
-        with st.expander(
-            f"📁 Saved mappings ({len(st.session_state.saved_image_mapping)})",
-            expanded=False,
-        ):
-            for key, info in st.session_state.saved_image_mapping.items():
-                st.markdown(
-                    f"**{info['property']}** &nbsp;›&nbsp; `{info['filename']}`  \n"
-                    f"<small>Caption: {info['caption']}</small>",
-                    unsafe_allow_html=True,
-                )