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@@ -16,19 +16,11 @@ RUN pip install --no-cache-dir -r requirements.txt
 # Notebook execution deps
 RUN pip install --no-cache-dir notebook ipykernel papermill
 
-# Pre-install packages that the notebooks install via !pip install
-# so papermill doesn't waste time or fail on them at runtime:
-#   datacreation.ipynb:  beautifulsoup4 pandas matplotlib seaborn numpy textblob
-#   pythonanalysis.ipynb: pandas matplotlib seaborn numpy textblob faker transformers vaderSentiment
-# Most are already in requirements.txt; add the extras:
-RUN pip install --no-cache-dir textblob faker transformers
+# Pre-install packages the notebooks use via !pip install
+RUN pip install --no-cache-dir textblob faker vaderSentiment
 
 RUN python -m ipykernel install --user --name python3 --display-name "Python 3"
 
-# R deps for notebook execution via papermill (IRkernel)
-RUN R -e "install.packages('IRkernel', repos='https://cloud.r-project.org/')"
-RUN R -e "IRkernel::installspec(user = FALSE)"
-
 EXPOSE 7860
 
 CMD ["python", "app.py"]

README.md

@@ -1,10 +1,11 @@
 ---
-title: RX12WorkshopApp
+title: AIBDM 2026 Workshop App
 emoji: 📊
 colorFrom: blue
-colorTo: red
+colorTo: purple
 sdk: docker
 pinned: false
+short_description: AI-enhanced analytics dashboard for ESCP AIBDM course
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -4,7 +4,7 @@ import json
 import time
 import traceback
 from pathlib import Path
-from typing import Dict, Any, List, Optional, Tuple
+from typing import Dict, Any, List, Tuple
 
 import pandas as pd
 import gradio as gr
@@ -50,7 +50,7 @@ llm_client = (
 # =========================================================
 
 def ensure_dirs():
-    for p in [RUNS_DIR, ART_DIR, PY_FIG_DIR, PY_TAB_DIR, R_FIG_DIR, R_TAB_DIR]:
+    for p in [RUNS_DIR, ART_DIR, PY_FIG_DIR, PY_TAB_DIR]:
         p.mkdir(parents=True, exist_ok=True)
 
 def stamp():
@@ -76,7 +76,7 @@ def artifacts_index() -> Dict[str, Any]:
         "python": {
             "figures": _ls(PY_FIG_DIR, (".png", ".jpg", ".jpeg")),
             "tables": _ls(PY_TAB_DIR, (".csv", ".json")),
-        }
+        },
     }
 
 # =========================================================
@@ -128,16 +128,14 @@ def run_pythonanalysis() -> str:
 def run_full_pipeline() -> str:
     logs = []
     logs.append("=" * 50)
-    logs.append("STEP 1/3: Data Creation (web scraping + synthetic data)")
+    logs.append("STEP 1/2: Data Creation (web scraping + synthetic data)")
     logs.append("=" * 50)
     logs.append(run_datacreation())
     logs.append("")
     logs.append("=" * 50)
-    logs.append("STEP 2/3: Python Analysis (sentiment, ARIMA, dashboard)")
+    logs.append("STEP 2/2: Python Analysis (sentiment, ARIMA, dashboard)")
     logs.append("=" * 50)
     logs.append(run_pythonanalysis())
-    logs.append("")
-    logs.append("=" * 50)
     return "\n".join(logs)
 
 
@@ -149,7 +147,7 @@ def _load_all_figures() -> List[Tuple[str, str]]:
     """Return list of (filepath, caption) for Gallery."""
     items = []
     for p in sorted(PY_FIG_DIR.glob("*.png")):
-        items.append((str(p), f"Python | {p.stem.replace('_', ' ').title()}"))
+        items.append((str(p), p.stem.replace('_', ' ').title()))
     return items
 
 
@@ -170,17 +168,11 @@ def refresh_gallery():
     figures = _load_all_figures()
     idx = artifacts_index()
 
-    # Build table choices
-    table_choices = []
-    for name in idx["python"]["tables"]:
-        table_choices.append(f"{"python"}/{name}")
+    table_choices = list(idx["python"]["tables"])
 
-    # Default: show first table if available
     default_df = pd.DataFrame()
     if table_choices:
-        parts = table_choices[0].split("/", 1)
-        base = PY_TAB_DIR
-        default_df = _load_table_safe(base / parts[1])
+        default_df = _load_table_safe(PY_TAB_DIR / table_choices[0])
 
     return (
         figures if figures else [],
@@ -190,15 +182,11 @@ def refresh_gallery():
 
 
 def on_table_select(choice: str):
-    if not choice or "/" not in choice:
+    if not choice:
         return pd.DataFrame([{"hint": "Select a table above."}])
-    scope, name = choice.split("/", 1)
-    base = {"python": PY_TAB_DIR}.get(scope)
-    if not base:
-        return pd.DataFrame([{"error": f"Unknown scope: {scope}"}])
-    path = base / name
+    path = PY_TAB_DIR / choice
     if not path.exists():
-        return pd.DataFrame([{"error": f"File not found: {path}"}])
+        return pd.DataFrame([{"error": f"File not found: {choice}"}])
     return _load_table_safe(path)
 
 
@@ -217,12 +205,12 @@ def load_kpis() -> Dict[str, Any]:
 
 
 # =========================================================
-# AI DASHBOARD (Tab 3) -- LLM picks what to display
+# AI DASHBOARD -- LLM picks what to display
 # =========================================================
 
 DASHBOARD_SYSTEM = """You are an AI dashboard assistant for a book-sales analytics app.
 The user asks questions or requests about their data. You have access to pre-computed
-artifacts from Python and R analysis pipelines.
+artifacts from a Python analysis pipeline.
 
 AVAILABLE ARTIFACTS (only reference ones that exist):
 {artifacts_json}
@@ -233,7 +221,7 @@ YOUR JOB:
 1. Answer the user's question conversationally using the KPIs and your knowledge of the artifacts.
 2. At the END of your response, output a JSON block (fenced with ```json ... ```) that tells
    the dashboard which artifact to display. The JSON must have this shape:
-   {{"show": "figure"|"table"|"none", "scope": "python"|"r", "filename": "..."}}
+   {{"show": "figure"|"table"|"none", "scope": "python", "filename": "..."}}
 
    - Use "show": "figure" to display a chart image.
    - Use "show": "table" to display a CSV/JSON table.
@@ -242,8 +230,7 @@ YOUR JOB:
 RULES:
 - If the user asks about sales trends or forecasting by title, show sales_trends or arima figures.
 - If the user asks about sentiment, show sentiment figure or sentiment_counts table.
-- If the user asks about R regression, the R notebook focuses on forecasting, show accuracy_table.csv.
-- If the user asks about forecast accuracy or model comparison, show accuracy_table.csv or forecast_compare.png.
+- If the user asks about forecast accuracy or ARIMA, show arima figures.
 - If the user asks about top sellers, show top_titles_by_units_sold.csv.
 - If the user asks a general data question, pick the most relevant artifact.
 - Keep your answer concise (2-4 sentences), then the JSON block.
@@ -318,22 +305,21 @@ def ai_chat(user_msg: str, history: list):
     fig_out = None
     tab_out = None
     show = directive.get("show", "none")
-    scope = directive.get("scope", "")
     fname = directive.get("filename", "")
 
-    if show == "figure" and scope and fname:
-        base = {"python": PY_FIG_DIR, "r": R_FIG_DIR}.get(scope)
-        if base and (base / fname).exists():
-            fig_out = str(base / fname)
+    if show == "figure" and fname:
+        fp = PY_FIG_DIR / fname
+        if fp.exists():
+            fig_out = str(fp)
         else:
-            reply += f"\n\n*(Could not find figure: {scope}/{fname})*"
+            reply += f"\n\n*(Could not find figure: {fname})*"
 
-    if show == "table" and scope and fname:
-        base = {"python": PY_TAB_DIR, "r": R_TAB_DIR}.get(scope)
-        if base and (base / fname).exists():
-            tab_out = _load_table_safe(base / fname)
+    if show == "table" and fname:
+        fp = PY_TAB_DIR / fname
+        if fp.exists():
+            tab_out = _load_table_safe(fp)
         else:
-            reply += f"\n\n*(Could not find table: {scope}/{fname})*"
+            reply += f"\n\n*(Could not find table: {fname})*"
 
     new_history = (history or []) + [
         {"role": "user", "content": user_msg},
@@ -347,7 +333,7 @@ def _keyword_fallback(msg: str, idx: Dict, kpis: Dict) -> Tuple[str, Dict]:
     """Simple keyword matcher when LLM is unavailable."""
     msg_lower = msg.lower()
 
-    if not any(idx[s]["figures"] or idx[s]["tables"] for s in ("python", "r")):
+    if not idx["python"]["figures"] and not idx["python"]["tables"]:
         return (
             "No artifacts found yet. Please run the pipeline first (Tab 1), "
             "then come back here to explore the results.",
@@ -375,47 +361,27 @@ def _keyword_fallback(msg: str, idx: Dict, kpis: Dict) -> Tuple[str, Dict]:
         )
 
     if any(w in msg_lower for w in ["arima", "forecast", "predict"]):
-        if "compar" in msg_lower or "ets" in msg_lower or "accuracy" in msg_lower:
-            if "forecast_compare.png" in idx.get("r", {}).get("figures", []):
-                return (
-                    "Here is the ARIMA+Fourier vs ETS forecast comparison from the R analysis.",
-                    {"show": "figure", "scope": "r", "filename": "forecast_compare.png"},
-                )
         return (
-            f"Here are the ARIMA forecasts for sampled titles from the Python analysis. {kpi_text}",
+            f"Here are the ARIMA forecasts for sampled titles. {kpi_text}",
             {"show": "figure", "scope": "python", "filename": "arima_forecasts_sampled_titles.png"},
         )
 
-    if any(w in msg_lower for w in ["regression", "lm", "coefficient", "price effect", "rating effect"]):
-        return (
-            "The R notebook focuses on forecasting rather than regression. "
-            "Here is the forecast accuracy comparison instead.",
-            {"show": "table", "scope": "r", "filename": "accuracy_table.csv"},
-        )
-
     if any(w in msg_lower for w in ["top", "best sell", "popular", "rank"]):
         return (
             f"Here are the top-selling titles by units sold. {kpi_text}",
             {"show": "table", "scope": "python", "filename": "top_titles_by_units_sold.csv"},
         )
 
-    if any(w in msg_lower for w in ["accuracy", "benchmark", "rmse", "mape"]):
+    if any(w in msg_lower for w in ["price", "pricing", "decision"]):
         return (
-            "Here is the forecast accuracy comparison (ARIMA+Fourier vs ETS) from the R analysis.",
-            {"show": "table", "scope": "r", "filename": "accuracy_table.csv"},
+            f"Here are the pricing decisions. {kpi_text}",
+            {"show": "table", "scope": "python", "filename": "pricing_decisions.csv"},
         )
 
-    if any(w in msg_lower for w in ["r analysis", "r output", "r result"]):
-        if "forecast_compare.png" in idx.get("r", {}).get("figures", []):
-            return (
-                "Here is the main R output: forecast model comparison plot.",
-                {"show": "figure", "scope": "r", "filename": "forecast_compare.png"},
-            )
-
     if any(w in msg_lower for w in ["dashboard", "overview", "summary", "kpi"]):
         return (
             f"Dashboard overview: {kpi_text}\n\nAsk me about sales trends, sentiment, forecasts, "
-            "forecast accuracy, or top sellers to see specific visualizations.",
+            "pricing, or top sellers to see specific visualizations.",
             {"show": "table", "scope": "python", "filename": "df_dashboard.csv"},
         )
 
@@ -423,7 +389,7 @@ def _keyword_fallback(msg: str, idx: Dict, kpis: Dict) -> Tuple[str, Dict]:
     return (
         f"I can show you various analyses. {kpi_text}\n\n"
         "Try asking about: **sales trends**, **sentiment**, **ARIMA forecasts**, "
-        "**forecast accuracy**, **top sellers**, or **dashboard overview**.",
+        "**pricing decisions**, **top sellers**, or **dashboard overview**.",
         {"show": "none"},
     )
 
@@ -439,11 +405,11 @@ def load_css() -> str:
     return css_path.read_text(encoding="utf-8") if css_path.exists() else ""
 
 
-with gr.Blocks(title="RX12 Workshop App") as demo:
+with gr.Blocks(title="AIBDM 2026 Workshop App") as demo:
 
     gr.Markdown(
-        "# RX12 - Intro to Python and R - Workshop App\n"
-        "*The app to integrate the three notebooks in to get a functioning blueprint of the group project's final product*",
+        "# AIBDM 2026 - AI & Big Data Management - Workshop App\n"
+        "*Run notebooks, explore results, and chat with your data*",
         elem_id="escp_title",
     )
 
@@ -451,37 +417,16 @@ with gr.Blocks(title="RX12 Workshop App") as demo:
     # TAB 1 -- Pipeline Runner
     # ===========================================================
     with gr.Tab("Pipeline Runner"):
-        gr.Markdown(
-        )
+        gr.Markdown()
 
         with gr.Row():
             with gr.Column(scale=1):
-                btn_nb1 = gr.Button(
-                    "Step 1: Data Creation",
-                    variant="secondary",
-                )
-                gr.Markdown(
-                )
+                btn_nb1 = gr.Button("Step 1: Data Creation", variant="secondary")
             with gr.Column(scale=1):
-                btn_nb2 = gr.Button(
-                    "Step 2a: Python Analysis",
-                    variant="secondary",
-                )
-                gr.Markdown(
-                )
-            with gr.Column(scale=1):
-                btn_r = gr.Button(
-                    "Step 2b: R Analysis",
-                    variant="secondary",
-                )
-                gr.Markdown(
-                )
+                btn_nb2 = gr.Button("Step 2: Python Analysis", variant="secondary")
 
         with gr.Row():
-            btn_all = gr.Button(
-                "Run All 3 Steps",
-                variant="primary",
-            )
+            btn_all = gr.Button("Run Full Pipeline (Both Steps)", variant="primary")
 
         run_log = gr.Textbox(
             label="Execution Log",
@@ -492,7 +437,6 @@ with gr.Blocks(title="RX12 Workshop App") as demo:
 
         btn_nb1.click(run_datacreation, outputs=[run_log])
         btn_nb2.click(run_pythonanalysis, outputs=[run_log])
-        btn_r.click(run_r, outputs=[run_log])
         btn_all.click(run_full_pipeline, outputs=[run_log])
 
     # ===========================================================
@@ -501,15 +445,14 @@ with gr.Blocks(title="RX12 Workshop App") as demo:
     with gr.Tab("Results Gallery"):
         gr.Markdown(
             "### All generated artifacts\n\n"
-            "After running the pipeline, click **Refresh** to load all figures and tables. "
-            "Figures are shown in the gallery; select a table from the dropdown to inspect it."
+            "After running the pipeline, click **Refresh** to load all figures and tables."
         )
 
         refresh_btn = gr.Button("Refresh Gallery", variant="primary")
 
         gr.Markdown("#### Figures")
         gallery = gr.Gallery(
-            label="All Figures (Python + R)",
+            label="Generated Figures",
             columns=2,
             height=480,
             object_fit="contain",
@@ -559,7 +502,7 @@ with gr.Blocks(title="RX12 Workshop App") as demo:
                 )
                 user_input = gr.Textbox(
                     label="Ask about your data",
-                    placeholder="e.g. Show me sales trends / What drives revenue? / Compare forecast models",
+                    placeholder="e.g. Show me sales trends / What are the top sellers? / Sentiment analysis",
                     lines=1,
                 )
                 gr.Examples(
@@ -567,8 +510,8 @@ with gr.Blocks(title="RX12 Workshop App") as demo:
                         "Show me the sales trends",
                         "What does the sentiment look like?",
                         "Which titles sell the most?",
-                        "Show the forecast accuracy comparison",
-                        "Compare the ARIMA and ETS forecasts",
+                        "Show the ARIMA forecasts",
+                        "What are the pricing decisions?",
                         "Give me a dashboard overview",
                     ],
                     inputs=user_input,
@@ -591,4 +534,4 @@ with gr.Blocks(title="RX12 Workshop App") as demo:
         )
 
 
-demo.launch(css=load_css(), allowed_paths=[str(BASE_DIR)])
+demo.launch(css=load_css(), allowed_paths=[str(BASE_DIR)])

style.css

@@ -1,17 +1,18 @@
-/* --- Target the Gradio app wrapper for backgrounds --- */
+/* ── ESCP Background: top (once) + mid gradient strip (repeats) ── */
+
 gradio-app,
 .gradio-app,
 .main,
 #app,
 [data-testid="app"] {
   background-color: rgb(40,9,109) !important;
-  background-image: 
-    url('https://huggingface.co/spaces/escp/rx12workshoptemplate/resolve/main/background_top.png'),
-    url('https://huggingface.co/spaces/escp/rx12workshoptemplate/resolve/main/background_mid.png') !important;
-  background-position: 
+  background-image:
+    url('https://huggingface.co/spaces/atascioglu/SE21AppTemplate/resolve/main/background_top.png'),
+    url('https://huggingface.co/spaces/atascioglu/SE21AppTemplate/resolve/main/background_mid.png') !important;
+  background-position:
     top center,
     0 913px !important;
-  background-repeat: 
+  background-repeat:
     no-repeat,
     repeat-y !important;
   background-size:
@@ -20,7 +21,6 @@ gradio-app,
   min-height: 100vh !important;
 }
 
-/* --- Fallback on html/body --- */
 html, body {
   background-color: rgb(40,9,109) !important;
   margin: 0 !important;
@@ -28,7 +28,6 @@ html, body {
   min-height: 100vh !important;
 }
 
-/* --- Fixed bottom banner using ::after on body --- */
 body::after {
   content: '' !important;
   position: fixed !important;
@@ -36,7 +35,7 @@ body::after {
   left: 0 !important;
   right: 0 !important;
   height: 130px !important;
-  background-image: url('https://huggingface.co/spaces/escp/rx12workshoptemplate/resolve/main/background_bottom.png') !important;
+  background-image: url('https://huggingface.co/spaces/atascioglu/SE21AppTemplate/resolve/main/background_bottom.png') !important;
   background-size: 100% 100% !important;
   background-repeat: no-repeat !important;
   background-position: bottom center !important;
@@ -44,17 +43,17 @@ body::after {
   z-index: 9999 !important;
 }
 
-/* --- Main container --- */
+/* ── Container: opaque purple so it covers the background image cleanly ── */
 .gradio-container {
   max-width: 1400px !important;
   width: 94vw !important;
   margin: 0 auto !important;
-  padding-top: 220px !important;
+  padding-top: 20px !important;
   padding-bottom: 150px !important;
-  background: transparent !important;
+  background: rgb(40,9,109) !important;
 }
 
-/* --- Title in ESCP gold --- */
+/* ── Title: ESCP gold ── */
 #escp_title h1 {
   color: rgb(242,198,55) !important;
   font-size: 3rem !important;
@@ -63,13 +62,12 @@ body::after {
   margin: 0 0 12px 0 !important;
 }
 
-/* --- Subtitle --- */
 #escp_title p, #escp_title em {
   color: rgba(255,255,255,0.85) !important;
   text-align: center !important;
 }
 
-/* --- Tab bar background --- */
+/* ── Tab bar ── */
 .tabs > .tab-nav,
 .tab-nav,
 div[role="tablist"],
@@ -79,7 +77,6 @@ div[role="tablist"],
   padding: 4px !important;
 }
 
-/* --- ALL tab buttons: force white text --- */
 .tabs > .tab-nav button,
 .tab-nav button,
 div[role="tablist"] button,
@@ -96,7 +93,6 @@ button[role="tab"],
   opacity: 1 !important;
 }
 
-/* --- Selected tab: ESCP gold --- */
 .tabs > .tab-nav button.selected,
 .tab-nav button.selected,
 button[role="tab"][aria-selected="true"],
@@ -107,7 +103,6 @@ div[role="tablist"] button[aria-selected="true"],
   background: rgba(255,255,255,0.12) !important;
 }
 
-/* --- Unselected tabs: ensure visibility --- */
 .tabs > .tab-nav button:not(.selected),
 .tab-nav button:not(.selected),
 button[role="tab"][aria-selected="false"],
@@ -117,7 +112,7 @@ div[role="tablist"] button:not([aria-selected="true"]) {
   opacity: 1 !important;
 }
 
-/* --- White card panels --- */
+/* ── White card panels ── */
 .gradio-container .gr-block,
 .gradio-container .gr-box,
 .gradio-container .gr-panel,
@@ -126,14 +121,13 @@ div[role="tablist"] button:not([aria-selected="true"]) {
   border-radius: 10px !important;
 }
 
-/* --- Tab content area --- */
 .tabitem {
   background: rgba(255,255,255,0.95) !important;
   border-radius: 0 0 10px 10px !important;
   padding: 16px !important;
 }
 
-/* --- Inputs --- */
+/* ── Inputs ── */
 .gradio-container input,
 .gradio-container textarea,
 .gradio-container select {
@@ -142,7 +136,7 @@ div[role="tablist"] button:not([aria-selected="true"]) {
   border-radius: 8px !important;
 }
 
-/* --- Buttons: ESCP purple primary --- */
+/* ── Buttons ── */
 .gradio-container button:not([role="tab"]) {
   font-weight: 600 !important;
   padding: 10px 16px !important;
@@ -169,17 +163,15 @@ button.secondary:hover {
   background-color: rgb(240,238,250) !important;
 }
 
-/* --- Dataframes --- */
+/* ── Dataframes ── */
 [data-testid="dataframe"] {
   background-color: #ffffff !important;
   border-radius: 10px !important;
 }
 
-table {
-  font-size: 0.85rem !important;
-}
+table { font-size: 0.85rem !important; }
 
-/* --- Chatbot (AI Dashboard tab) --- */
+/* ── Chatbot ── */
 .gr-chatbot {
   min-height: 380px !important;
   background-color: #ffffff !important;
@@ -196,19 +188,19 @@ table {
   border-radius: 12px !important;
 }
 
-/* --- Gallery --- */
+/* ── Gallery ── */
 .gallery {
   background: #ffffff !important;
   border-radius: 10px !important;
 }
 
-/* --- Log textbox --- */
+/* ── Log textbox ── */
 textarea {
   font-family: monospace !important;
   font-size: 0.8rem !important;
 }
 
-/* --- Markdown headings inside tabs --- */
+/* ── Headings inside tabs ── */
 .tabitem h3 {
   color: rgb(40,9,109) !important;
   font-weight: 700 !important;
@@ -218,7 +210,7 @@ textarea {
   color: #374151 !important;
 }
 
-/* --- Examples row (AI Dashboard) --- */
+/* ── Examples row ── */
 .examples-row button {
   background: rgb(240,238,250) !important;
   color: rgb(40,9,109) !important;
@@ -231,7 +223,7 @@ textarea {
   background: rgb(232,225,250) !important;
 }
 
-/* --- Header / footer: transparent over banner --- */
+/* ── Header / footer: transparent ── */
 header, header *,
 footer, footer * {
   background: transparent !important;
@@ -245,33 +237,7 @@ header a, header button {
   box-shadow: none !important;
 }
 
-#footer, #footer *,
-[class*="footer"], [class*="footer"] *,
-[class*="chip"], [class*="pill"], [class*="chip"] *, [class*="pill"] * {
-  background: transparent !important;
-  border: none !important;
-  box-shadow: none !important;
-}
-
-[data-testid*="api"], [data-testid*="settings"],
-[id*="api"], [id*="settings"],
-[class*="api"], [class*="settings"],
-[class*="bottom"], [class*="toolbar"], [class*="controls"] {
-  background: transparent !important;
-  box-shadow: none !important;
-}
-
-[data-testid*="api"] *, [data-testid*="settings"] *,
-[id*="api"] *, [id*="settings"] *,
-[class*="api"] *, [class*="settings"] * {
-  background: transparent !important;
-  box-shadow: none !important;
-}
-
-section footer {
-  background: transparent !important;
-}
-
+section footer,
 section footer button,
 section footer a {
   background: transparent !important;
@@ -281,22 +247,11 @@ section footer a {
   color: white !important;
 }
 
-section footer button:hover,
-section footer button:focus,
-section footer a:hover,
-section footer a:focus {
-  background: transparent !important;
-  background-color: transparent !important;
-  box-shadow: none !important;
-}
-
-section footer button,
-section footer button * {
+section footer button *,
+section footer a * {
   background: transparent !important;
   background-color: transparent !important;
-  background-image: none !important;
   box-shadow: none !important;
-  filter: none !important;
 }
 
 section footer button::before,
@@ -308,13 +263,6 @@ section footer button::after {
   filter: none !important;
 }
 
-section footer a,
-section footer a * {
-  background: transparent !important;
-  background-color: transparent !important;
-  box-shadow: none !important;
-}
-
 .gradio-container footer button,
 .gradio-container footer button *,
 .gradio-container .footer button,
@@ -333,4 +281,12 @@ section footer a * {
   background-color: transparent !important;
   background-image: none !important;
   box-shadow: none !important;
-}
+}
+
+/* ── Responsive ── */
+@media (max-width: 768px) {
+  .gradio-container {
+    padding-top: 120px !important;
+    width: 98vw !important;
+  }
+}