Update app.py

app.py

@@ -1,45 +1,41 @@
 import gradio as gr
 import pandas as pd
-import plotly.graph_objects as go
-import plotly.express as px
-
-# -----------------------------
-# Mock Data (replace with live)
-# -----------------------------
 
+# Optional Plotly
+try:
+    import plotly.express as px
+    import plotly.graph_objects as go
+    PLOTLY = True
+except Exception:
+    PLOTLY = False
+
+# ---------------------------
+# Demo FOIA Data
+# ---------------------------
 DATA = pd.DataFrame([
     {
         "title": "MKULTRA Behavioral Experiments",
         "agency": "CIA",
         "date": "1977-08-03",
         "year": 1977,
-        "summary": "CIA behavioral research program involving human subjects.",
-        "entities": ["CIA", "MKULTRA", "Behavioral Research"]
+        "summary": "CIA behavioral research involving human subjects.",
+        "entities": ["CIA", "MKULTRA"]
     },
     {
         "title": "Human Performance Research",
         "agency": "DoD",
         "date": "1975-01-12",
         "year": 1975,
-        "summary": "DoD-funded research on human cognition and stress.",
-        "entities": ["DoD", "Cognition", "Stress"]
-    },
-    {
-        "title": "Signals Intelligence Overview",
-        "agency": "NSA",
-        "date": "1981-04-21",
-        "year": 1981,
-        "summary": "Overview of SIGINT collection policies.",
-        "entities": ["NSA", "SIGINT"]
-    },
+        "summary": "DoD-funded cognition research.",
+        "entities": ["DoD", "Cognition"]
+    }
 ])
 
-AGENCIES = ["CIA", "DoD", "DIA", "FBI", "NRO", "NSA", "Unknown"]
-
-# -----------------------------
-# Search Logic
-# -----------------------------
+AGENCIES = sorted(DATA["agency"].unique().tolist())
 
+# ---------------------------
+# Search
+# ---------------------------
 def run_search(query, agencies):
     df = DATA.copy()
     if query:
@@ -48,75 +44,23 @@ def run_search(query, agencies):
         df = df[df["agency"].isin(agencies)]
     return df[["title", "agency", "date"]]
 
-# -----------------------------
-# Row Click → Preview
-# -----------------------------
-
 def preview_row(evt: gr.SelectData):
     row = DATA.iloc[evt.index]
     return f"""
 ### {row['title']}
-
 **Agency:** {row['agency']}  
 **Date:** {row['date']}
 
 {row['summary']}
 """
 
-# -----------------------------
-# Entity Graph (Plotly)
-# -----------------------------
-
-def entity_graph(filtered_df):
-    nodes = set()
-    edges = []
-
-    for _, row in filtered_df.iterrows():
-        for e in row["entities"]:
-            nodes.add(e)
-            edges.append((row["agency"], e))
-
-    nodes = list(nodes)
-    node_index = {n: i for i, n in enumerate(nodes)}
-
-    x = list(range(len(nodes)))
-    y = [0] * len(nodes)
-
-    edge_x, edge_y = [], []
-    for a, b in edges:
-        if b in node_index:
-            edge_x += [node_index.get(a, 0), node_index[b], None]
-            edge_y += [0, 0, None]
-
-    fig = go.Figure()
-    fig.add_trace(go.Scatter(
-        x=edge_x, y=edge_y,
-        mode="lines",
-        line=dict(color="#334155"),
-        hoverinfo="none"
-    ))
-    fig.add_trace(go.Scatter(
-        x=x, y=y,
-        mode="markers+text",
-        marker=dict(size=18, color="#2563eb"),
-        text=nodes,
-        textposition="bottom center"
-    ))
-
-    fig.update_layout(
-        paper_bgcolor="#020617",
-        plot_bgcolor="#020617",
-        font_color="#e5e7eb",
-        margin=dict(l=20, r=20, t=20, b=20),
-        height=400
-    )
-    return fig
-
-# -----------------------------
-# Coverage Heatmap
-# -----------------------------
-
+# ---------------------------
+# Visuals
+# ---------------------------
 def coverage_heatmap():
+    if not PLOTLY:
+        return None
+
     heat = DATA.groupby(["agency", "year"]).size().reset_index(name="count")
     fig = px.density_heatmap(
         heat,
@@ -125,107 +69,53 @@ def coverage_heatmap():
         z="count",
         color_continuous_scale="Blues"
     )
-    fig.update_layout(
-        paper_bgcolor="#020617",
-        plot_bgcolor="#020617",
-        font_color="#e5e7eb",
-        height=300
-    )
+    fig.update_layout(height=300)
     return fig
 
-# -----------------------------
-# Timeline View
-# -----------------------------
-
-def timeline_view(filtered_df):
-    fig = px.scatter(
-        filtered_df,
-        x="year",
-        y="agency",
-        hover_name="title"
-    )
-    fig.update_traces(marker=dict(size=14, color="#38bdf8"))
-    fig.update_layout(
-        paper_bgcolor="#020617",
-        plot_bgcolor="#020617",
-        font_color="#e5e7eb",
-        height=300
+def entity_graph():
+    if not PLOTLY:
+        return None
+
+    nodes = list(set(sum(DATA["entities"].tolist(), [])))
+    fig = go.Figure(
+        data=go.Scatter(
+            x=list(range(len(nodes))),
+            y=[0]*len(nodes),
+            mode="markers+text",
+            text=nodes
+        )
     )
+    fig.update_layout(height=300)
     return fig
 
-# -----------------------------
+# ---------------------------
 # UI
-# -----------------------------
-
-with gr.Blocks(
-    title="Federal FOIA Intelligence Search",
-    css="static/style.css"
-) as demo:
-
-    gr.Markdown("# 🏛️ Federal FOIA Intelligence Search\n**Public Electronic Reading Rooms Only**")
-
-    with gr.Tabs():
-        with gr.Tab("🔍 Search"):
-            with gr.Row():
-                with gr.Column(scale=2):
-                    with gr.Column(elem_id="card"):
-                        query = gr.Textbox(label="Search query", placeholder="MKULTRA")
-                        agencies = gr.CheckboxGroup(
-                            AGENCIES,
-                            value=["CIA", "DoD", "NRO"],
-                            label="Filter by agency",
-                            elem_id="agency-pills"
-                        )
-                        search_btn = gr.Button("Search", elem_id="search-btn")
-
-                    results = gr.Dataframe(
-                        headers=["Title", "Agency", "Date"],
-                        interactive=False,
-                        elem_id="results-table"
-                    )
-
-                with gr.Column(scale=1):
-                    preview = gr.Markdown("### Document Preview\nSelect a result")
-
-            search_btn.click(
-                run_search,
-                inputs=[query, agencies],
-                outputs=results
-            )
-
-            results.select(preview_row, outputs=preview)
-
-        with gr.Tab("🧠 Entity Graph"):
-            entity_plot = gr.Plot()
-
-        with gr.Tab("📊 Coverage"):
-            heatmap_plot = gr.Plot()
-
-        with gr.Tab("⏱ Timeline"):
-            timeline_plot = gr.Plot()
-
-    # Reactive wiring
-    results.change(
-        lambda df: entity_graph(DATA),
-        inputs=results,
-        outputs=entity_plot
-    )
+# ---------------------------
+with gr.Blocks() as demo:
 
-    results.change(
-        lambda df: timeline_view(DATA),
-        inputs=results,
-        outputs=timeline_plot
-    )
+    gr.Markdown("""
+# 🏛️ Federal FOIA Intelligence Search  
+**Public Electronic Reading Rooms Only**
+""")
 
-    heatmap_plot.render(coverage_heatmap)
+    if not PLOTLY:
+        gr.Markdown("⚠️ Plotly not installed — graphs disabled.")
 
-    with gr.Column(elem_id="provenance"):
-        gr.Markdown("""
-### Dataset Provenance
-- **Sources:** Public FOIA Reading Rooms (CIA, DoD, NSA)
-- **Status:** Previously released, unclassified
-- **Scope:** Demonstration subset
-- **Verification:** No inference beyond document text
-""")
+    with gr.Tab("🔍 Search"):
+        query = gr.Textbox(label="Search query", value="MKULTRA")
+        agencies = gr.CheckboxGroup(AGENCIES, value=AGENCIES)
+        search_btn = gr.Button("Search")
+
+        table = gr.Dataframe(headers=["Title", "Agency", "Date"])
+        preview = gr.Markdown()
+
+        search_btn.click(run_search, [query, agencies], table)
+        table.select(preview_row, preview)
+
+    with gr.Tab("📊 Coverage Heatmap"):
+        gr.Plot(value=coverage_heatmap)
+
+    with gr.Tab("🧠 Entity Graph"):
+        gr.Plot(value=entity_graph)
 
 demo.launch()