Create app.py

app.py

@@ -1,121 +1,41 @@
+import asyncio
 import gradio as gr
-import pandas as pd
+from ingest.registry import get_live_adapters
 
-# Optional Plotly
-try:
-    import plotly.express as px
-    import plotly.graph_objects as go
-    PLOTLY = True
-except Exception:
-    PLOTLY = False
+ADAPTERS = get_live_adapters()
 
-# ---------------------------
-# Demo FOIA Data
-# ---------------------------
-DATA = pd.DataFrame([
-    {
-        "title": "MKULTRA Behavioral Experiments",
-        "agency": "CIA",
-        "date": "1977-08-03",
-        "year": 1977,
-        "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 cognition research.",
-        "entities": ["DoD", "Cognition"]
-    }
-])
+async def live_search(query):
+    tasks = [a.search(query) for a in ADAPTERS]
+    results = await asyncio.gather(*tasks, return_exceptions=True)
 
-AGENCIES = sorted(DATA["agency"].unique().tolist())
+    flat = []
+    for r in results:
+        if isinstance(r, list):
+            flat.extend(r)
 
-# ---------------------------
-# Search
-# ---------------------------
-def run_search(query, agencies):
-    df = DATA.copy()
-    if query:
-        df = df[df["title"].str.contains(query, case=False)]
-    if agencies:
-        df = df[df["agency"].isin(agencies)]
-    return df[["title", "agency", "date"]]
+    return [
+        [x["agency"], x["source"], x["title"], x["url"]]
+        for x in flat
+    ]
 
-def preview_row(evt: gr.SelectData):
-    row = DATA.iloc[evt.index]
-    return f"""
-### {row['title']}
-**Agency:** {row['agency']}  
-**Date:** {row['date']}
+def run_search(query):
+    return asyncio.run(live_search(query))
 
-{row['summary']}
-"""
-
-# ---------------------------
-# Visuals
-# ---------------------------
-def coverage_heatmap():
-    if not PLOTLY:
-        return None
-
-    heat = DATA.groupby(["agency", "year"]).size().reset_index(name="count")
-    fig = px.density_heatmap(
-        heat,
-        x="year",
-        y="agency",
-        z="count",
-        color_continuous_scale="Blues"
-    )
-    fig.update_layout(height=300)
-    return fig
-
-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() as demo:
-
     gr.Markdown("""
 # 🏛️ Federal FOIA Intelligence Search  
-**Public Electronic Reading Rooms Only**
+**Public Electronic Reading Rooms Only**  
+_Live CIA CREST & FBI Vault_
 """)
 
-    if not PLOTLY:
-        gr.Markdown("⚠️ Plotly not installed — graphs disabled.")
-
-    with gr.Tab("🔍 Search"):
-        query = gr.Textbox(label="Search query", value="MKULTRA")
-        agencies = gr.CheckboxGroup(AGENCIES, value=AGENCIES)
-        search_btn = gr.Button("Search")
+    query = gr.Textbox(label="Search FOIA documents")
+    btn = gr.Button("Live 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)
+    table = gr.Dataframe(
+        headers=["Agency", "Source", "Title", "URL"],
+        interactive=False
+    )
 
-    with gr.Tab("🧠 Entity Graph"):
-        gr.Plot(value=entity_graph)
+    btn.click(run_search, query, table)
 
 demo.launch()