Add Test History with View Report in Database tab

- Add AnalysisResult.from_dict() to reconstruct results from stored JSON
- Add Test History section in Database tab listing all past analyses
- View Report button loads full report inline with back navigation
- Results now persist across Streamlit reruns via session_state

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

app.py

@@ -920,6 +920,16 @@ def render_timeline(result):
 
 def render_database_tab():
     """Render the voiceprint database tab."""
+
+    # If viewing a historical report, show it first with a back button
+    if st.session_state.get('viewing_history') and st.session_state.get('last_result'):
+        if st.button("← Back to Database"):
+            st.session_state['viewing_history'] = False
+            st.session_state['last_result'] = None
+            st.rerun()
+        render_results(st.session_state['last_result'])
+        return
+
     st.markdown("### Voiceprint Database")
 
     analyzer = get_analyzer()
@@ -948,6 +958,46 @@ def render_database_tab():
             st.metric("Recurring", stats['multi_appearance'])
             st.caption("Voices in 2+ tests")
 
+    # ---- Test History ----
+    st.markdown("#### Test History")
+    all_tests = analyzer.db.get_all_tests()
+    if all_tests:
+        for idx, test in enumerate(all_tests):
+            date_str = test.analyzed_at.strftime('%d/%m/%Y %H:%M') if test.analyzed_at else '-'
+            risk_data = ""
+            if test.results_json:
+                try:
+                    import json as _json
+                    rj = _json.loads(test.results_json)
+                    rs = rj.get('risk_score', '-')
+                    rl = rj.get('risk_label', '')
+                    risk_icon = {"LOW": "🟢", "MEDIUM": "🟡", "HIGH": "🔴"}.get(rl, "⚪")
+                    risk_data = f"{risk_icon} {rs}"
+                except Exception:
+                    risk_data = "-"
+
+            tc1, tc2, tc3, tc4 = st.columns([2, 3, 1, 1.5])
+            with tc1:
+                st.write(date_str)
+            with tc2:
+                st.write(test.filename[:40] if test.filename else '-')
+            with tc3:
+                st.write(risk_data)
+            with tc4:
+                if st.button("View Report", key=f"view_test_{test.test_id}_{idx}"):
+                    results = analyzer.db.get_test_results(test.test_id)
+                    if results:
+                        from src.analyzer import AnalysisResult
+                        st.session_state['last_result'] = AnalysisResult.from_dict(results)
+                        st.session_state['viewing_history'] = True
+                        st.rerun()
+    else:
+        st.caption("No tests analyzed yet.")
+    st.divider()
+
+    # ---- Voiceprint Database ----
+    st.markdown("#### Voiceprints")
+
     # Check if clear was requested
     if st.session_state.get('clear_db_search', False):
         st.session_state['clear_db_search'] = False

src/analyzer.py

@@ -181,6 +181,71 @@ class AnalysisResult:
         """Convert to JSON string."""
         return json.dumps(self.to_dict(), indent=2)
 
+    @classmethod
+    def from_dict(cls, d: dict) -> 'AnalysisResult':
+        """Reconstruct an AnalysisResult from a stored dict (e.g. from DB JSON)."""
+        main = None
+        if d.get('main_speaker'):
+            ms = d['main_speaker']
+            main = SpeakerResult(
+                voiceprint_id=ms.get('voiceprint_id', ''),
+                label=ms.get('label', ''),
+                role=ms.get('role', 'main'),
+                total_seconds=ms.get('total_seconds', 0),
+                quality=ms.get('quality', 'Unknown'),
+                is_synthetic=ms.get('is_synthetic', False),
+                synthetic_score=ms.get('synthetic_score', 0),
+                is_playback=ms.get('is_playback', False),
+                playback_score=ms.get('playback_score', 0),
+                playback_indicators=ms.get('playback_indicators'),
+                times_seen=ms.get('times_seen', 1),
+                is_flagged=ms.get('is_flagged', False),
+                segments=ms.get('segments'),
+                clip_path=ms.get('clip_path'),
+            )
+        additional = []
+        for s in d.get('additional_speakers', []):
+            additional.append(SpeakerResult(
+                voiceprint_id=s.get('voiceprint_id', ''),
+                label=s.get('label', ''),
+                role=s.get('role', 'additional'),
+                total_seconds=s.get('total_seconds', 0),
+                quality=s.get('quality', 'Unknown'),
+                is_synthetic=s.get('is_synthetic', False),
+                synthetic_score=s.get('synthetic_score', 0),
+                is_playback=s.get('is_playback', False),
+                playback_score=s.get('playback_score', 0),
+                playback_indicators=s.get('playback_indicators'),
+                times_seen=s.get('times_seen', 1),
+                is_flagged=s.get('is_flagged', False),
+                segments=s.get('segments'),
+                clip_path=s.get('clip_path'),
+            ))
+        return cls(
+            test_id=d.get('test_id', ''),
+            filename=d.get('filename', ''),
+            duration_seconds=d.get('duration_seconds', 0),
+            analyzed_at=d.get('analyzed_at', ''),
+            main_speaker=main,
+            additional_speakers=additional,
+            background_anomalies=d.get('background_anomalies', []),
+            wake_words=d.get('wake_words', []),
+            assistant_responses=d.get('assistant_responses', []),
+            prompt_voice_detected=d.get('prompt_voice_detected', False),
+            prompt_voice_seconds=d.get('prompt_voice_seconds', 0),
+            playback_detected=d.get('playback_detected', False),
+            playback_score=d.get('playback_score', 0),
+            playback_indicators=d.get('playback_indicators'),
+            whisper_detected=d.get('whisper_detected', False),
+            whisper_instances=d.get('whisper_instances'),
+            reading_pattern_detected=d.get('reading_pattern_detected', False),
+            reading_confidence=d.get('reading_confidence', 0),
+            reading_indicators=d.get('reading_indicators'),
+            suspicious_pauses_detected=d.get('suspicious_pauses_detected', False),
+            suspicious_pauses=d.get('suspicious_pauses'),
+            longest_pause=d.get('longest_pause', 0),
+        )
+
 
 class AudioAnalyzer:
     """Main analyzer that orchestrates all phases."""