From 9bd8ae99f6b557e3f248ed299f6c166267fec2cd Mon Sep 17 00:00:00 2001
From: Jarvis <jarvis@moltbot.ai>
Date: Fri, 30 Jan 2026 19:46:17 +0000
Subject: [PATCH] Feat: Improved Dashboard Logging & Unbuffered Output

---
 Dockerfile |  1 +
 app.py     | 76 ++++++++++++++++++++++++++++++++++--------------------
 2 files changed, 49 insertions(+), 28 deletions(-)

diff --git a/Dockerfile b/Dockerfile
index 540ffee..ed452e6 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -6,4 +6,5 @@ COPY . .
 
 RUN pip install streamlit pandas
 
+ENV PYTHONUNBUFFERED=1
 CMD ["streamlit", "run", "app.py", "--server.port=8501", "--server.address=0.0.0.0"]
diff --git a/app.py b/app.py
index cce4dd5..2dbcf78 100644
--- a/app.py
+++ b/app.py
@@ -2,54 +2,74 @@ import streamlit as st
 import pandas as pd
 from db import get_leads, init_db
 import json
+from enrich import run_sync  # Import our sync function
 
 st.set_page_config(page_title="TradingTwins Lead Engine", layout="wide")
 
 st.title("🚀 Lead Engine: TradingTwins")
 
-# Metrics
+# Sidebar Actions
+st.sidebar.header("Actions")
+
+if st.sidebar.button("1. Ingest Emails (Mock)"):
+    from ingest import ingest_mock_leads
+    init_db()
+    count = ingest_mock_leads()
+    st.sidebar.success(f"Ingested {count} new leads.")
+    st.rerun()
+
+if st.sidebar.button("2. Sync to Company Explorer"):
+    with st.spinner("Syncing with Company Explorer API..."):
+        # Capture output for debugging
+        try:
+            # We redirect stdout to capture prints
+            import io
+            from contextlib import redirect_stdout
+            f = io.StringIO()
+            with redirect_stdout(f):
+                run_sync()
+            output = f.getvalue()
+            
+            st.success("Sync finished!")
+            with st.expander("See Process Log", expanded=True):
+                st.code(output)
+                
+        except Exception as e:
+            st.error(f"Sync Failed: {e}")
+
+# Main View
 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']))
+    col2.metric("New / Unsynced", len(df[df['status'] == 'new']))
+    col3.metric("Synced to CE", len(df[df['status'] == 'synced']))
 
-    st.subheader("Latest Inquiries")
+    st.subheader("Lead Pipeline")
     
     for index, row in df.iterrows():
-        with st.expander(f"{row['company_name']} - {row['status']}"):
+        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']}")
+            c1.text(row['raw_body'][:200] + "...")
             
             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)
+                c2.write("--- Integration Status ---")
+                if enrichment.get('ce_id'):
+                    c2.success(f"✅ Linked to Company Explorer (ID: {enrichment['ce_id']})")
+                    c2.write(f"**CE Status:** {enrichment.get('ce_status')}")
+                else:
+                    c2.warning("⚠️ Not yet synced or failed")
+                
+                c2.info(f"Log: {enrichment.get('message')}")
+                
+                if enrichment.get('ce_data'):
+                    c2.json(enrichment['ce_data'])
 
 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()
+    st.info("No leads found. Click 'Ingest Emails' in the sidebar.")