Simplify logic to extract model info

Author: gabegma

apps/analysis.py

@@ -378,22 +378,38 @@ def _extract_model_details(run_config: dict) -> dict[str, str]:
     model_cfg = run_config.get("pipeline") or run_config.get("model") or {}
     details: dict[str, str] = {}
 
-    # LLM / realtime model
-    llm = model_cfg.get("realtime_model") or model_cfg.get("llm_model") or model_cfg.get("llm") or ""
-    if llm:
-        details["LLM"] = llm
-
-    # STT provider + specific model
-    stt = model_cfg.get("stt_model") or model_cfg.get("stt") or ""
-    if stt:
-        stt_model = (model_cfg.get("stt_params") or {}).get("model")
-        details["STT"] = f"{stt} ({stt_model})" if stt_model else stt
-
-    # TTS provider + specific model
-    tts = model_cfg.get("tts_model") or model_cfg.get("tts") or ""
-    if tts:
-        tts_model = (model_cfg.get("tts_params") or {}).get("model")
-        details["TTS"] = f"{tts} ({tts_model})" if tts_model else tts
+    # Speech-to-speech
+    s2s = model_cfg.get("s2s") or model_cfg.get("realtime_model") or ""
+    if s2s:
+        s2s_params = model_cfg.get("s2s_params") or {}
+        label = s2s_params.get("alias") or s2s_params.get("model") or s2s
+        details["S2S"] = label
+    else:
+        # Audio LLM
+        audio_llm = model_cfg.get("audio_llm") or ""
+        if audio_llm:
+            audio_llm_params = model_cfg.get("audio_llm_params") or {}
+            details["Audio LLM"] = audio_llm_params.get("alias") or audio_llm_params.get("model") or audio_llm
+        else:
+            # Cascade: LLM
+            llm = model_cfg.get("llm") or model_cfg.get("llm_model") or ""
+            if llm:
+                details["LLM"] = llm
+
+        # STT (cascade only, not S2S/AudioLLM)
+        if not audio_llm:
+            stt = model_cfg.get("stt") or model_cfg.get("stt_model") or ""
+            if stt:
+                stt_params = model_cfg.get("stt_params") or {}
+                label = stt_params.get("alias") or stt_params.get("model") or stt
+                details["STT"] = f"{stt} ({label})" if label != stt else stt
+
+        # TTS (cascade and AudioLLM)
+        tts = model_cfg.get("tts") or model_cfg.get("tts_model") or ""
+        if tts:
+            tts_params = model_cfg.get("tts_params") or {}
+            label = tts_params.get("alias") or tts_params.get("model") or tts
+            details["TTS"] = f"{tts} ({label})" if label != tts else tts
 
     # Turn strategy
     turn_strategy = model_cfg.get("turn_strategy")
@@ -619,49 +635,25 @@ def _classify_pipeline_type(run_config: dict) -> str:
 
 def _extract_llm_model_name(run_config: dict) -> str:
     """Extract the primary model name from config."""
-    model_cfg = run_config.get("pipeline") or run_config.get("model") or {}
-    audio_llm_params = model_cfg.get("audio_llm_params") or {}
-    return (
-        model_cfg.get("s2s")
-        or model_cfg.get("realtime_model")
-        or audio_llm_params.get("alias")
-        or audio_llm_params.get("model")
-        or model_cfg.get("llm")
-        or model_cfg.get("llm_model")
-        or "unknown"
+    details = _extract_model_details(run_config)
+    return next(
+        (details[k] for k in ("S2S", "Audio LLM", "LLM") if k in details),
+        "unknown",
     )
 
 
 def _extract_all_models(run_config: dict) -> set[str]:
     """Extract all model names with their role (LLM/STT/TTS) from config."""
-    model_cfg = run_config.get("pipeline") or run_config.get("model") or {}
+    details = _extract_model_details(run_config)
     models: set[str] = set()
-
-    # LLM / S2S / Audio LLM
-    audio_llm_params = model_cfg.get("audio_llm_params") or {}
-    llm = (
-        model_cfg.get("s2s")
-        or model_cfg.get("realtime_model")
-        or audio_llm_params.get("alias")
-        or audio_llm_params.get("model")
-        or model_cfg.get("llm")
-        or model_cfg.get("llm_model")
-    )
-    if llm:
-        models.add(f"{llm} (LLM)")
-
-    # STT
-    stt_params = model_cfg.get("stt_params") or {}
-    stt = stt_params.get("alias") or stt_params.get("model") or model_cfg.get("stt_model") or model_cfg.get("stt") or ""
-    if stt:
-        models.add(f"{stt} (STT)")
-
-    # TTS
-    tts_params = model_cfg.get("tts_params") or {}
-    tts = tts_params.get("alias") or tts_params.get("model") or model_cfg.get("tts_model") or model_cfg.get("tts") or ""
-    if tts:
-        models.add(f"{tts} (TTS)")
-
+    for role in ("S2S", "Audio LLM", "LLM"):
+        if role in details:
+            models.add(f"{details[role]} (LLM)")
+            break
+    if "STT" in details:
+        models.add(f"{details['STT']} (STT)")
+    if "TTS" in details:
+        models.add(f"{details['TTS']} (TTS)")
     return models or {"unknown"}
 
 
@@ -1770,16 +1762,9 @@ def render_conversation_trace_tab(metrics: Optional[RecordMetrics], record_dir:
 
 def _render_sidebar_run_metadata(run_name: str, run_config: dict):
     """Render run metadata in the sidebar."""
-    pipeline = run_config.get("pipeline") or run_config.get("model") or {}
     metadata_parts = [f"**Run:** {run_name}"]
-    if pipeline.get("realtime_model"):
-        metadata_parts.append(f"**Realtime Model:** {pipeline['realtime_model']}")
-    elif pipeline.get("llm_model"):
-        metadata_parts.append(f"**LLM Model:** {pipeline['llm_model']}")
-    if pipeline.get("stt_model"):
-        metadata_parts.append(f"**STT:** {pipeline['stt_model']}")
-    if pipeline.get("tts_model"):
-        metadata_parts.append(f"**TTS:** {pipeline['tts_model']}")
+    for label, value in _extract_model_details(run_config).items():
+        metadata_parts.append(f"**{label}:** {value}")
     if run_config.get("num_trials"):
         metadata_parts.append(f"**Trials:** {run_config['num_trials']}")
     provenance = run_config.get("provenance", {})