Initial MVP Commit: Ingest, Enrich, Dashboard

app.py

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+import streamlit as st
+import pandas as pd
+from db import get_leads, init_db
+import json
+
+st.set_page_config(page_title="TradingTwins Lead Engine", layout="wide")
+
+st.title("🚀 Lead Engine: TradingTwins")
+
+# Metrics
+leads = get_leads()
+df = pd.DataFrame(leads)
+
+if not df.empty:
+    col1, col2, col3 = st.columns(3)
+    col1.metric("Total Leads", len(df))
+    col2.metric("New Today", len(df[df['status'] == 'new']))
+    col3.metric("Action Required", len(df[df['status'] == 'enriched']))
+
+    st.subheader("Latest Inquiries")
+    
+    for index, row in df.iterrows():
+        with st.expander(f"{row['company_name']} - {row['status']}"):
+            c1, c2 = st.columns(2)
+            c1.write(f"**Contact:** {row['contact_name']}")
+            c1.write(f"**Email:** {row['email']}")
+            
+            enrichment = json.loads(row['enrichment_data']) if row['enrichment_data'] else {}
+            
+            if enrichment:
+                c2.success(f"Score: {enrichment.get('score')}")
+                c2.write(f"**Vertical:** {enrichment.get('vertical')}")
+                c2.info(f"💡 {enrichment.get('recommendation')}")
+            
+            if st.button(f"Generate Response for {row['id']}"):
+                st.write("Generating draft... (Simulated)")
+                # Here we would call the LLM
+                draft = f"Hallo {row['contact_name']},\n\ndanke für Ihre Anfrage..."
+                st.text_area("Draft", draft, height=200)
+
+else:
+    st.info("No leads found. Waiting for ingest...")
+
+if st.sidebar.button("Run Ingest (Mock)"):
+    from ingest import ingest_mock_leads
+    init_db()
+    count = ingest_mock_leads()
+    st.sidebar.success(f"Ingested {count} leads.")
+    st.rerun()
+
+if st.sidebar.button("Run Enrichment"):
+    from enrich import run_enrichment
+    run_enrichment()
+    st.sidebar.success("Enrichment complete.")
+    st.rerun()