Update app.py

app.py

@@ -1,11 +1,11 @@
 # app.py — Spine Coder (Chatbot + Feedback + Session Logs) — Gradio 4.x
 # ------------------------------------------------------------------------------
-# FINAL-v2.1 UI build (hardened) + LIVE DATASET LOGGING (no restarts):
-# - Purge caches, dynamic file loader (SPINE_CORE_PATH override) + SHA print
-# - Startup PROBE to logs + in-UI Diagnostics/Probe
-# - Clean CPT table (no per-row modifier columns) + Case Modifiers panel
-# - Build/Core chips, structured logs/export, modern Gradio usage
-# - NEW: per-request log commits to a separate *dataset* repo (no Space rebuilds)
+# FINAL-v3.0 (Stable)
+# - Bulletproof core import (SPINE_CORE_PATH override + SHA print)
+# - Structured local JSONL logging per session
+# - Live dataset logging to a Hugging Face dataset repo (no Space rebuilds)
+# - Diagnostics panel with Probe + Self-Test for live logging
+# - Clean UI with Case Modifiers, raw JSON, and feedback
 # ------------------------------------------------------------------------------
 
 import os
@@ -16,15 +16,14 @@ import pathlib
 import traceback
 from datetime import datetime, timezone
 from typing import Any, Dict, List, Tuple
-
 import pandas as pd
 import gradio as gr
 
-# ==== Bulletproof Core Import ==================================================
+# ==== Core Import =============================================================
 import importlib, importlib.util, importlib.machinery
 import sys as __sys, os as __os, inspect as __inspect, hashlib
 
-__sys.path.insert(0, __os.path.abspath("."))  # ensure repo root is on sys.path
+__sys.path.insert(0, __os.path.abspath("."))
 
 def _purge_spine_modules():
     for k in list(__sys.modules):
@@ -34,6 +33,7 @@ def _purge_spine_modules():
 
 def _sha256(path: str) -> str:
     try:
+        import hashlib
         h = hashlib.sha256()
         with open(path, "rb") as f:
             for chunk in iter(lambda: f.read(8192), b""):
@@ -43,10 +43,6 @@ def _sha256(path: str) -> str:
         return "unknown"
 
 def _load_core_from_file(path: str):
-    """
-    Load spine_coder_core.py directly from a given path (bypass module cache).
-    Register in sys.modules BEFORE exec to enable imports inside the core.
-    """
     path = __os.path.abspath(path)
     if not __os.path.exists(path):
         return None
@@ -59,18 +55,13 @@ def _load_core_from_file(path: str):
     return mod
 
 def _force_import_core():
-    """Order: purge caches → SPINE_CORE_PATH → local files → package modules."""
     _purge_spine_modules()
-
-    # 1) Explicit override
     forced = __os.environ.get("SPINE_CORE_PATH")
     if forced and __os.path.exists(forced):
         mod = _load_core_from_file(forced)
         if mod:
             print("[CORE] forced path:", forced, "sha:", _sha256(forced))
             return mod
-
-    # 2) Likely file paths near app
     for rel in [
         "spine_coder_core.py",
         "spine_coder/spine_coder_core.py",
@@ -82,8 +73,6 @@ def _force_import_core():
             if mod:
                 print("[CORE] loaded file:", p, "sha:", _sha256(p))
                 return mod
-
-    # 3) Package modules
     for modname in [
         "spine_coder.spine_coder.spine_coder_core",
         "spine_coder.spine_coder_core",
@@ -91,29 +80,19 @@ def _force_import_core():
         try:
             mod = importlib.import_module(modname)
             mod = importlib.reload(mod)
-            src = __inspect.getsourcefile(mod.suggest_with_cpt_billing) or "unknown"
-            print("[CORE] loaded module:", modname, "from:", src)
             return mod
         except Exception:
             pass
-
-    raise ImportError("Unable to locate spine_coder_core.py via modules or file paths.")
+    raise ImportError("Unable to locate spine_coder_core.py")
 
 _core = _force_import_core()
 suggest_with_cpt_billing = _core.suggest_with_cpt_billing
 
-try:
-    _active_src = __inspect.getsourcefile(suggest_with_cpt_billing) or "unknown"
-    print("[CORE] active source:", _active_src)
-except Exception:
-    _active_src = "unknown"
-
-# ---- One-time startup probe (prints to Space logs) ----------------------------
+# ==== Startup Probe ===========================================================
 try:
     _probe_note = "Discectomies at C4–C5, C5–C6, and C6–C7. Interbody cages and anterior plate spanning C4–C7."
     _probe = suggest_with_cpt_billing(_probe_note, payer="Medicare", top_k=5)
     print("[PROBE] build:", _probe.get("build"))
-    print("[PROBE] first_suggestion:", (_probe.get("suggestions") or [{}])[0])
 except Exception as e:
     print("[PROBE] failed:", e)
 
@@ -122,19 +101,13 @@ os.environ.setdefault("GRADIO_ANALYTICS_ENABLED", "False")
 DEBUG = os.environ.get("DEBUG", "0") == "1"
 PAYER_CHOICES = ["Medicare", "BCBS", "Aetna", "Cigna", "UnitedHealthcare", "Other"]
 
-# ==== Remote log push settings (dataset repo to avoid restarts) ===============
-# Required env:
-#   LOG_PUSH_ENABLE=1
-#   HF_TARGET_REPO=Slaiwala/spinecoder-logs
-#   HF_REPO_TYPE=dataset
-#   HF_TOKEN (or HUGGINGFACEHUB_API_TOKEN) with write access
+# ==== Live Logging Config =====================================================
 LOG_PUSH_ENABLE = os.environ.get("LOG_PUSH_ENABLE", "0") == "1"
-HF_TARGET_REPO = os.environ.get("HF_TARGET_REPO")             # must be provided; no fallback to SPACE_ID
-HF_REPO_TYPE   = os.environ.get("HF_REPO_TYPE", "dataset")    # keep 'dataset' to prevent Space rebuilds
-HF_WRITE_TOKEN = (
-    os.environ.get("HF_TOKEN")
-    or os.environ.get("HUGGINGFACEHUB_API_TOKEN")
-)
+HF_TARGET_REPO  = os.environ.get("HF_TARGET_REPO")
+HF_REPO_TYPE    = os.environ.get("HF_REPO_TYPE", "dataset")
+HF_WRITE_TOKEN  = os.environ.get("HF_TOKEN") or os.environ.get("HUGGINGFACEHUB_API_TOKEN")
+
+print(f"[LOG CFG] enable={LOG_PUSH_ENABLE} repo={HF_TARGET_REPO} type={HF_REPO_TYPE} token_len={(len(HF_WRITE_TOKEN) if HF_WRITE_TOKEN else 0)}")
 
 _hf_api = None
 def _get_hf_api():
@@ -144,529 +117,241 @@ def _get_hf_api():
         _hf_api = HfApi(token=HF_WRITE_TOKEN)
     return _hf_api
 
-# ==== Local logging ============================================================
-LOG_DIR = os.environ.get("LOG_DIR", "logs")
-pathlib.Path(LOG_DIR).mkdir(parents=True, exist_ok=True)
-
-def _log_path(session_id: str) -> str:
-    return os.path.join(LOG_DIR, f"{session_id}.jsonl")
-
-def _utcnow_iso() -> str:
-    return datetime.now(timezone.utc).isoformat(timespec="seconds")
-
-# ---- push a single line to dataset repo (no Space restart) -------------------
-def _push_log_line_to_repo(entry: Dict[str, Any]) -> None:
-    if not LOG_PUSH_ENABLE:
-        return
-    if not HF_TARGET_REPO or not HF_WRITE_TOKEN:
-        # Misconfigured: silently skip rather than touching the Space repo
-        return
+def _ensure_logs_repo() -> bool:
+    if not LOG_PUSH_ENABLE or not HF_TARGET_REPO or not HF_WRITE_TOKEN:
+        return False
     try:
-        from huggingface_hub import CommitOperationAdd, hf_hub_download
         api = _get_hf_api()
+        api.create_repo(HF_TARGET_REPO, repo_type=HF_REPO_TYPE, private=True, exist_ok=True)
+        return True
+    except Exception as e:
+        print("[LOG PUSH] repo check failed:", e)
+        return False
 
-        day = datetime.utcnow().strftime("%Y-%m-%d")
-        path_in_repo = f"logs-live/{day}.jsonl"
-
-        # Try to download existing file (may not exist yet)
-        existing = ""
-        try:
-            local_fp = hf_hub_download(
-                repo_id=HF_TARGET_REPO,
-                filename=path_in_repo,
-                repo_type=HF_REPO_TYPE,        # 'dataset'
-                token=HF_WRITE_TOKEN,
-                local_dir="/tmp",
-                local_dir_use_symlinks=False,
-                force_download=False,
-            )
-            with open(local_fp, "r", encoding="utf-8") as f:
-                existing = f.read()
-        except Exception:
-            existing = ""
-
-        # Append one line
-        new_line = json.dumps(entry, ensure_ascii=False)
-        if existing and not existing.endswith("\n"):
-            existing += "\n"
-        merged = (existing + new_line + "\n").encode("utf-8")
-
-        api.create_commit(
+def _fetch_existing_day_blob(path_in_repo: str) -> bytes:
+    try:
+        from huggingface_hub import hf_hub_download
+        fp = hf_hub_download(
             repo_id=HF_TARGET_REPO,
-            repo_type=HF_REPO_TYPE,           # 'dataset'
-            operations=[CommitOperationAdd(path_in_repo=path_in_repo, path_or_fileobj=io.BytesIO(merged))],
-            commit_message=f"logs: append {day} ({entry.get('event','')})",
+            filename=path_in_repo,
+            repo_type=HF_REPO_TYPE,
+            token=HF_WRITE_TOKEN,
+            local_dir="/tmp",
+            local_dir_use_symlinks=False,
+            force_download=True,
         )
-    except Exception as e:
-        print("[LOG PUSH] failed:", e)
+        with open(fp, "rb") as f:
+            return f.read()
+    except Exception:
+        return b""
+
+def _commit_bytes(path_in_repo: str, data: bytes, msg: str) -> None:
+    from huggingface_hub import CommitOperationAdd
+    api = _get_hf_api()
+    api.create_commit(
+        repo_id=HF_TARGET_REPO,
+        repo_type=HF_REPO_TYPE,
+        operations=[CommitOperationAdd(path_in_repo=path_in_repo, path_or_fileobj=io.BytesIO(data))],
+        commit_message=msg,
+    )
 
-def _append_log(session_id: str, entry: Dict[str, Any]) -> None:
-    entry = {"ts": _utcnow_iso(), "session_id": session_id, **entry}
-    # Local JSONL (unchanged)
-    with open(_log_path(session_id), "a", encoding="utf-8") as f:
+def _push_log_line_to_repo(entry: Dict[str, Any]) -> None:
+    if not LOG_PUSH_ENABLE or not HF_TARGET_REPO or not HF_WRITE_TOKEN:
+        return
+    if not _ensure_logs_repo():
+        return
+    day = datetime.utcnow().strftime("%Y-%m-%d")
+    path_in_repo = f"logs-live/{day}.jsonl"
+    line = (json.dumps(entry, ensure_ascii=False) + "\n").encode("utf-8")
+    for attempt in range(2):
+        try:
+            existing = _fetch_existing_day_blob(path_in_repo)
+            if existing and not existing.endswith(b"\n"):
+                existing += b"\n"
+            data = existing + line
+            _commit_bytes(path_in_repo, data, f"append {day} ({entry.get('event','')})")
+            return
+        except Exception as e:
+            print(f"[LOG PUSH] attempt {attempt+1} failed:", e)
+
+# ==== Local Logging ===========================================================
+LOG_DIR = "logs"
+pathlib.Path(LOG_DIR).mkdir(exist_ok=True)
+
+def _log_path(sid): return os.path.join(LOG_DIR, f"{sid}.jsonl")
+def _utcnow_iso(): return datetime.now(timezone.utc).isoformat(timespec="seconds")
+
+def _append_log(sid: str, entry: Dict[str, Any]):
+    entry = {"ts": _utcnow_iso(), "session_id": sid, **entry}
+    with open(_log_path(sid), "a", encoding="utf-8") as f:
         f.write(json.dumps(entry, ensure_ascii=False) + "\n")
-    # Dataset push (no restart)
     _push_log_line_to_repo(entry)
 
-def export_session(session_id: str) -> str:
-    src = _log_path(session_id)
-    data: List[Dict[str, Any]] = []
-    if os.path.exists(src):
-        with open(src, "r", encoding="utf-8") as f:
-            data = [json.loads(l) for l in f if l.strip()]
-    out_path = os.path.join(LOG_DIR, f"export_{session_id}.json")
-    with open(out_path, "w", encoding="utf-8") as f:
-        json.dump(data, f, indent=2, ensure_ascii=False)
-    return out_path
-
 # ==== UI Helpers ==============================================================
+def _core_path():
+    try: return __inspect.getsourcefile(suggest_with_cpt_billing) or "unknown"
+    except Exception: return "unknown"
 
-def _core_path() -> str:
-    try:
-        return __inspect.getsourcefile(suggest_with_cpt_billing) or "unknown"
-    except Exception:
-        return "unknown"
-
-# Display columns (per-row modifiers are deliberately not shown here)
-SUGG_COLS = [
-    "CPT", "Description", "Rationale",
-    "Confidence", "Primary", "Category", "Laterality", "Units"
-]
+SUGG_COLS = ["CPT","Description","Rationale","Confidence","Primary","Category","Laterality","Units"]
 EMPTY_SUGG_DF = pd.DataFrame(columns=SUGG_COLS)
-EMPTY_MODS_DF = pd.DataFrame([{"modifier": "—", "reason": ""}])
-
-def _coalesce_rows(result: Dict[str, Any]) -> Tuple[pd.DataFrame, Dict[str, Any]]:
-    """Build the suggestions table (no modifier columns) and meta badges."""
-    if not isinstance(result, dict):
-        return EMPTY_SUGG_DF, {}
-
-    sugg = result.get("suggestions") or []
-    rows: List[Dict[str, Any]] = []
-    case_lat = (result.get("laterality") or "").strip().lower()
-
-    for s in sugg:
-        if not isinstance(s, dict):
-            continue
-        mods = s.get("modifiers", []) or []
-
-        # Derive row laterality
-        row_lat = (s.get("laterality") or "").strip().lower()
-        if not row_lat:
-            if isinstance(mods, list) and "LT" in mods:
-                row_lat = "left"
-            elif isinstance(mods, list) and "RT" in mods:
-                row_lat = "right"
-            elif case_lat in ("left", "right", "bilateral"):
-                row_lat = case_lat
-
-        conf_val = s.get("confidence")
-        conf_out = round(float(conf_val), 2) if isinstance(conf_val, (int, float)) else (conf_val or "")
+EMPTY_MODS_DF = pd.DataFrame([{"modifier":"—","reason":""}])
 
+def _coalesce_rows(res: Dict[str,Any]):
+    if not isinstance(res, dict): return EMPTY_SUGG_DF, {}
+    rows = []
+    for s in res.get("suggestions", []) or []:
         rows.append({
-            "CPT": s.get("cpt", ""),
-            "Description": s.get("desc", ""),
-            "Rationale": s.get("rationale", ""),
-            "Confidence": conf_out,
+            "CPT": s.get("cpt",""),
+            "Description": s.get("desc",""),
+            "Rationale": s.get("rationale",""),
+            "Confidence": round(float(s.get("confidence",0)),2) if s.get("confidence") else "",
             "Primary": "✓" if s.get("primary") else "",
-            "Category": s.get("category", ""),
-            "Laterality": row_lat,
-            "Units": s.get("units", 1),
+            "Category": s.get("category",""),
+            "Laterality": s.get("laterality",""),
+            "Units": s.get("units",1)
         })
-
-    # Normalize levels
-    segs: List[str] = []
-    inters_list: List[str] = []
-    lvl_lat = ""
-    levels_obj = result.get("levels")
-    if isinstance(levels_obj, dict):
-        segs = list(levels_obj.get("segments") or [])
-        inters_list = list(levels_obj.get("interspaces") or [])
-        lvl_lat = levels_obj.get("laterality", "") or ""
-    elif isinstance(levels_obj, list):
-        segs = [str(x) for x in levels_obj]
-
-    # Normalize flags
-    flags_obj = result.get("flags")
-    if isinstance(flags_obj, list):
-        flags_list = [str(x) for x in flags_obj]
-    elif isinstance(flags_obj, dict):
-        flags_list = [k for k, v in flags_obj.items() if v]
-    else:
-        flags_list = []
-
     meta = {
-        "payer": result.get("payer", ""),
-        "region": result.get("region", ""),
-        "laterality": result.get("laterality", "") or lvl_lat,
-        "levels_segments": ", ".join(segs),
-        "levels_interspaces": (
-            str(result.get("interspaces_est", "")) if "interspaces_est" in result
-            else ", ".join(inters_list)
-        ),
-        "flags": ", ".join(sorted(flags_list)),
-        "build": result.get("build", ""),
-        "mode": result.get("mode", ""),
-        "core_path": _core_path(),
+        "payer": res.get("payer",""),
+        "region": res.get("region",""),
+        "laterality": res.get("laterality",""),
+        "build": res.get("build",""),
+        "mode": res.get("mode",""),
+        "core_path": _core_path()
     }
-
-    df = EMPTY_SUGG_DF if not rows else pd.DataFrame(rows)
-    if not df.empty:
-        for col in SUGG_COLS:
-            if col not in df.columns:
-                df[col] = ""
-        df = df[SUGG_COLS]
+    df = pd.DataFrame(rows) if rows else EMPTY_SUGG_DF
     return df, meta
 
-def _case_mods_df(result: Dict[str, Any]) -> pd.DataFrame:
-    mods = result.get("case_modifiers", []) or []
-    if not mods:
-        return EMPTY_MODS_DF.copy()
-    return pd.DataFrame([{"modifier": f"-{m.get('modifier','')}", "reason": m.get("reason","")} for m in mods])
-
-def _summary_md(meta: Dict[str, Any]) -> str:
-    chips = []
-    if meta.get("region"): chips.append(f"`Region: {meta['region']}`")
-    if meta.get("laterality"): chips.append(f"`Laterality: {meta['laterality']}`")
-    if meta.get("levels_segments"): chips.append(f"`Segments: {meta['levels_segments']}`")
-    if meta.get("levels_interspaces"): chips.append(f"`Interspaces: {meta['levels_interspaces']}`")
-    if meta.get("flags"): chips.append(f"`Flags: {meta['flags']}`")
-    if meta.get("build"): chips.append(f"`Build: {meta['build']}`")
-    if meta.get("mode"): chips.append(f"`Mode: {meta['mode']}`")
-    try:
-        core_base = os.path.basename(meta.get("core_path","")) if meta.get("core_path") else ""
-        if core_base:
-            chips.append(f"`Core: {core_base}`")
-    except Exception:
-        pass
-    return " ".join(chips) if chips else "—"
-
-def new_session() -> str:
-    return str(uuid.uuid4())[:8]
+def _case_mods_df(res):
+    mods = res.get("case_modifiers",[]) or []
+    if not mods: return EMPTY_MODS_DF.copy()
+    return pd.DataFrame([{"modifier":f"-{m.get('modifier','')}", "reason":m.get("reason","")} for m in mods])
 
-# ==== Core actions ============================================================
+def _summary_md(meta):
+    chips=[]
+    for k,v in meta.items():
+        if v: chips.append(f"`{k}: {v}`")
+    return " ".join(chips) if chips else "—"
 
-def run_inference(note: str, payer: str, top_k: int, session_id: str):
-    if not note.strip():
-        return (
-            EMPTY_SUGG_DF,
-            EMPTY_MODS_DF.copy(),
-            "—", "", "", session_id
-        )
+def new_session(): return str(uuid.uuid4())[:8]
 
-    _append_log(session_id, {"event": "request", "payer": payer, "top_k": top_k, "note": note})
+# ==== Core Actions ============================================================
+def run_inference(note,payer,top_k,sid):
+    if not note.strip(): return EMPTY_SUGG_DF,EMPTY_MODS_DF.copy(),"—","", "",sid
+    _append_log(sid,{"event":"request","payer":payer,"note":note})
     try:
-        result = suggest_with_cpt_billing(note=note, payer=payer, top_k=top_k)
-        if DEBUG:
-            print("[DEBUG] build/region/laterality/flags]:",
-                  result.get("build"), result.get("region"),
-                  result.get("laterality"), result.get("flags"))
+        res = suggest_with_cpt_billing(note=note,payer=payer,top_k=top_k)
     except Exception as e:
-        tb = traceback.format_exc()
-        _append_log(session_id, {"event": "error", "error": repr(e), "traceback": tb})
-        warn = f"⚠️ Error: {e}"
-        if DEBUG:
-            warn += f"\n\n```traceback\n{tb}\n```"
-        return (
-            EMPTY_SUGG_DF,
-            EMPTY_MODS_DF.copy(),
-            "—", "", warn, session_id
-        )
-
-    sugg_df, meta = _coalesce_rows(result)
-    case_mods_df = _case_mods_df(result)
-    summary = _summary_md(meta)
-    json_pretty = json.dumps(result, indent=2, ensure_ascii=False)
-
-    _append_log(session_id, {
-        "event": "response",
-        "meta": {
-            **meta,
-            "case_modifiers": ", ".join([f"-{m}" for m in [cm.get("modifier","") for cm in (result.get("case_modifiers") or [])] if m]) or ""
-        },
-        "rows_len": int(len(sugg_df) if hasattr(sugg_df, "__len__") else 0)
-    })
-    return sugg_df, case_mods_df, summary, json_pretty, "", session_id
-
-def record_feedback(session_id: str, vote: str, text: str):
-    if not vote and not text:
-        return "Please choose 👍/👎 or add a short note."
-    _append_log(session_id, {"event": "feedback", "vote": vote, "text": text})
-    return "Thanks! Your feedback was recorded."
-
-def do_export(session_id: str):
-    path = export_session(session_id)
-    _append_log(session_id, {"event": "export", "path": path})
-    return path
+        tb=traceback.format_exc()
+        _append_log(sid,{"event":"error","error":repr(e),"trace":tb})
+        return EMPTY_SUGG_DF,EMPTY_MODS_DF.copy(),"—","",f"⚠️ {e}",sid
+    df,meta=_coalesce_rows(res)
+    mods=_case_mods_df(res)
+    summary=_summary_md(meta)
+    jsonp=json.dumps(res,indent=2,ensure_ascii=False)
+    _append_log(sid,{"event":"response","meta":meta,"rows":len(df)})
+    return df,mods,summary,jsonp,"",sid
+
+def record_feedback(sid,vote,text):
+    if not vote and not text: return "Please choose 👍/👎 or add a short note."
+    _append_log(sid,{"event":"feedback","vote":vote,"text":text})
+    return "Thanks! Feedback saved."
+
+def do_export(sid):
+    p=_log_path(sid)
+    out=os.path.join(LOG_DIR,f"export_{sid}.json")
+    if os.path.exists(p):
+        with open(p) as f: data=[json.loads(l) for l in f if l.strip()]
+        json.dump(data,open(out,"w"),indent=2,ensure_ascii=False)
+    _append_log(sid,{"event":"export","path":out})
+    return out
 
 def on_clear():
-    return (
-        "", "Medicare", 10,
-        EMPTY_SUGG_DF,
-        EMPTY_MODS_DF.copy(),
-        "—", "", "",
-        new_session()
-    )
+    return "","Medicare",10,EMPTY_SUGG_DF,EMPTY_MODS_DF.copy(),"—","","",new_session()
 
-# ==== Diagnostics / Probe =====================================================
+# ==== Diagnostics =============================================================
+def run_probe(sid):
+    info=[]
+    try:
+        t=[("Implicit TLIF","Left facetectomy L4–L5 with PEEK interbody cage and pedicle screws; rods secured.",["22633"]),
+           ("ACDF chain w/ plate","Discectomies at C4–C5, C5–C6, and C6–C7. Interbody cages and anterior plate spanning C4–C7.",["22551","22552","22846"]),
+           ("Exposure-only","Anterior exposure of L4–S1 performed by vascular surgeon for access. No fusion performed.",["00000"])]
+        for lbl,note,exp in t:
+            r=suggest_with_cpt_billing(note,payer="Medicare",top_k=10)
+            codes=[s.get("cpt") for s in r.get("suggestions",[])]
+            ok=all(ec in codes for ec in exp)
+            info.append(f"- **{lbl}** → `{', '.join(codes) or '∅'}` — {'✅PASS' if ok else '❌CHECK'}")
+        md="\n".join(info)
+        _append_log(sid,{"event":"probe","details":md})
+        return md,""
+    except Exception as e:
+        tb=traceback.format_exc()
+        _append_log(sid,{"event":"probe_error","error":repr(e),"trace":tb})
+        return "",f"⚠️ Probe failed: {e}"
 
-def run_probe(session_id: str) -> Tuple[str, str]:
-    """Run a live diagnostic: show core path & build and 3 smoke tests."""
-    info_lines = []
+def run_log_selftest(sid):
     try:
-        core_path = _core_path()
-        tests = [
-            ("Implicit TLIF",
-             "Left facetectomy L4–L5 with PEEK interbody cage and pedicle screws; rods secured.",
-             ["22633"],  # expect
-            ),
-            ("ACDF chain w/ plate",
-             "Discectomies at C4–C5, C5–C6, and C6–C7. Interbody cages and anterior plate spanning C4–C7.",
-             ["22551","22552","22846"],
-            ),
-            ("Exposure-only",
-             "Anterior exposure of L4–S1 performed by vascular surgeon for access. No fusion performed.",
-             ["00000"],
-            ),
-        ]
-        # Run once to get build
-        probe = suggest_with_cpt_billing(tests[1][1], payer="Medicare", top_k=10)
-        build = probe.get("build","")
-        info_lines.append(f"**Core path:** `{core_path}`  \n**Build:** `{build}`")
-
-        # Execute each test
-        for label, note, expect_codes in tests:
-            res = suggest_with_cpt_billing(note, payer="Medicare", top_k=10)
-            codes = [s.get("cpt") for s in (res.get("suggestions") or [])]
-            ok = all(any(ec == c for c in codes) for ec in expect_codes)
-            info_lines.append(f"- **{label}** → codes: `{', '.join(codes) or '∅'}` — **{'PASS' if ok else 'CHECK'}**")
-        md = "\n".join(info_lines)
-        _append_log(session_id, {"event":"probe","details": md})
-        return md, ""
+        if not LOG_PUSH_ENABLE: return "","⚠️ LOG_PUSH_ENABLE=0"
+        if not HF_TARGET_REPO: return "","⚠️ HF_TARGET_REPO missing"
+        if not HF_WRITE_TOKEN: return "","⚠️ HF_TOKEN missing"
+        entry={"ts":_utcnow_iso(),"session_id":sid,"event":"selftest","msg":"hello"}
+        _push_log_line_to_repo(entry)
+        day=datetime.utcnow().strftime("%Y-%m-%d")
+        msg=f"✅ Live log push working!\n→ `{HF_TARGET_REPO}/logs-live/{day}.jsonl`"
+        _append_log(sid,{"event":"selftest_ok"})
+        return msg,""
     except Exception as e:
-        tb = traceback.format_exc()
-        _append_log(session_id, {"event":"probe_error","error":repr(e),"traceback":tb})
-        return "", f"⚠️ Probe failed: {e}"
+        tb=traceback.format_exc()
+        _append_log(sid,{"event":"selftest_err","err":repr(e),"trace":tb})
+        return "",f"⚠️ Self-test failed: {e}"
 
 # ==== Examples ================================================================
-
-EXAMPLES = [
-    ["Left-sided TLIF L4–L5 with pedicle screws and interbody cage; posterolateral fusion performed. Navigation used.", "Medicare", 10],
-    ["ACDF C5–C6 with PEEK cage and anterior plate; microscope and neuromonitoring used.", "Medicare", 10],
-    ["Posterior cervical foraminotomy right C6–C7; no fusion or instrumentation.", "Medicare", 10],
-    ["ALIF L5–S1 with structural allograft; non-segmental instrumentation placed.", "Medicare", 10],
-    ["Removal of posterior segmental instrumentation T10–L2; no new hardware placed.", "Medicare", 10],
-    # Case-modifier smoke tests:
-    ["TLIF L4–L5 was initiated but aborted midway due to neuromonitoring changes.", "Medicare", 10],  # -53
-    ["Bilateral decompression and foraminotomy at L4–L5 and L5–S1.", "Medicare", 10],                # -50
-    ["Assistant surgeon present; resident not available.", "Medicare", 10],                           # -82
-    ["Complex exposure with severe deformity and adhesiolysis.", "Medicare", 10],                     # -22
+EXAMPLES=[
+ ["Left-sided TLIF L4–L5 with pedicle screws and interbody cage; posterolateral fusion performed.","Medicare",10],
+ ["ACDF C5–C6 with PEEK cage and anterior plate.","Medicare",10],
+ ["Posterior cervical foraminotomy right C6–C7; no fusion.","Medicare",10]
 ]
 
 # ==== Theme / CSS =============================================================
-
-THEME = gr.themes.Soft(
-    primary_hue="indigo",
-    secondary_hue="blue",
-    neutral_hue="slate",
-).set(
-    body_text_color="#0f172a",
-    background_fill_primary="#ffffff",
-    button_primary_background_fill="#4f46e5",
-    input_background_fill="#ffffff",
-)
-
-CUSTOM_CSS = """
-:root { --radius-lg: 16px; }
-.gradio-container { font-family: ui-sans-serif, system-ui, -apple-system; }
-
-/* Header card */
-.header-card {
-  border-radius: 18px;
-  padding: 18px;
-  border: 1px solid #1f2937;
-  background: linear-gradient(180deg,#0f172a,#0b1220);
-  color: #e5e7eb;
-}
-.badge-row code {
-  margin-right: 8px;
-  border-radius: 12px;
-  padding: 2px 8px;
-  background: #111827;
-  color: #e5e7eb;
-}
-
-/* Table container */
-.table-wrap { max-height: 520px; overflow: auto; }
-
-/* Suggestions table target */
-#suggestions_table .dataframe {
-  font-size: 15px;
-  width: 100% !important;
-  table-layout: auto !important;
-  border-collapse: collapse;
-}
-#suggestions_table .dataframe th,
-#suggestions_table .dataframe td {
-  white-space: normal;
-  word-wrap: break-word;
-  text-align: left;
-  vertical-align: top;
-  padding: 10px 12px;
-}
-
-/* Column sizing (1-indexed):
-   1=CPT, 2=Description, 3=Rationale, 4=Confidence,
-   5=Primary, 6=Category, 7=Laterality, 8=Units  */
-
-/* CPT — wider & no wrap, monospace, centered */
-#suggestions_table .dataframe th:nth-child(1),
-#suggestions_table .dataframe td:nth-child(1) {
-  min-width: 120px;
-  max-width: 140px;
-  white-space: nowrap !important;
-  font-family: ui-monospace, SFMono-Regular, Menlo, Monaco, Consolas, "Liberation Mono", monospace;
-  text-align: center;
-}
-
-/* Description — roomy */
-#suggestions_table .dataframe th:nth-child(2),
-#suggestions_table .dataframe td:nth-child(2) {
-  min-width: 360px;
-  max-width: 560px;
-}
-
-/* Rationale — roomy */
-#suggestions_table .dataframe th:nth-child(3),
-#suggestions_table .dataframe td:nth-child(3) {
-  min-width: 320px;
-  max-width: 520px;
-}
-
-/* Category — a bit wider */
-#suggestions_table .dataframe th:nth-child(6),
-#suggestions_table .dataframe td:nth-child(6) {
-  min-width: 180px;
-}
-
-/* Keep tiny columns compact */
-#suggestions_table .dataframe th:nth-child(4),
-#suggestions_table .dataframe td:nth-child(4),
-#suggestions_table .dataframe th:nth-child(5),
-#suggestions_table .dataframe td:nth-child(5),
-#suggestions_table .dataframe th:nth-child(7),
-#suggestions_table .dataframe td:nth-child(7),
-#suggestions_table .dataframe th:nth-child(8),
-#suggestions_table .dataframe td:nth-child(8) {
-  min-width: 90px;
-}
-
-.footer-note { color:#94a3b8; font-size:12px; }
+THEME=gr.themes.Soft(primary_hue="indigo").set(background_fill_primary="#fff",button_primary_background_fill="#4f46e5")
+CUSTOM_CSS="""
+:root{--radius-lg:16px;}
+.gradio-container{font-family:ui-sans-serif;}
+.header-card{border-radius:18px;padding:18px;border:1px solid #1f2937;background:linear-gradient(180deg,#0f172a,#0b1220);color:#e5e7eb;}
+.badge-row code{margin-right:8px;border-radius:12px;padding:2px 8px;background:#111827;color:#e5e7eb;}
+.table-wrap{max-height:520px;overflow:auto;}
+.footer-note{color:#94a3b8;font-size:12px;}
 """
 
-# ==== App Layout ==============================================================
-with gr.Blocks(theme=THEME, css=CUSTOM_CSS, title="Spine Coder — CPT Billing") as demo:
-    session_id = gr.State(new_session())
-
+# ==== UI Layout ===============================================================
+with gr.Blocks(theme=THEME,css=CUSTOM_CSS,title="Spine Coder — CPT Billing") as demo:
+    sid=gr.State(new_session())
     with gr.Row():
         with gr.Column():
             gr.Markdown("### 🦴 Spine Coder — CPT Billing & Operative Note NLP")
-            gr.Markdown(
-                '<div class="header-card">Structured CPT suggestions from spine operative notes — with payer-aware '
-                'modifiers, laterality detection, and rationales.<br/>'
-                '<span class="footer-note">No PHI is stored; inputs are session-scoped and ephemeral.</span></div>'
-            )
-
+            gr.Markdown('<div class="header-card">Structured CPT suggestions from spine operative notes — payer-aware modifiers & rationales.<br/><span class="footer-note">No PHI stored.</span></div>')
     with gr.Row():
-        # Inputs
         with gr.Column(scale=5):
-            note_in = gr.Textbox(
-                label="Operative Note",
-                placeholder="Paste an operative note here…",
-                lines=14,
-                autofocus=True,
-            )
-            with gr.Row():
-                payer_dd = gr.Dropdown(PAYER_CHOICES, value="Medicare", label="Payer")
-                topk = gr.Slider(1, 15, value=10, step=1, label="Top-K suggestions")
-            with gr.Row():
-                run_btn = gr.Button("Analyze Note", variant="primary")
-                clear_btn = gr.Button("Clear")
-
-            with gr.Accordion("Quick Examples", open=False):
-                gr.Examples(
-                    examples=EXAMPLES,
-                    inputs=[note_in, payer_dd, topk],
-                    label="Click a row to load an example"
-                )
-
-            with gr.Accordion("Feedback", open=False):
-                fb_choice = gr.Radio(choices=["👍", "👎"], label="Was this helpful?")
-                fb_text = gr.Textbox(label="Optional comment", lines=2, placeholder="Tell us what worked or what missed…")
-                fb_submit = gr.Button("Submit Feedback")
-                fb_status = gr.Markdown("")
-
-            with gr.Accordion("Session", open=False):
-                sid_show = gr.Textbox(label="Session ID", value="", interactive=False)
-                export_btn = gr.Button("Export Session as JSON")
-                export_file = gr.File(label="Download", interactive=False)
-
-            with gr.Accordion("Diagnostics", open=False):
-                probe_btn = gr.Button("Run Probe (core path + 3 tests)")
-                probe_md = gr.Markdown("")
-
-        # Results
+            note=gr.Textbox(label="Operative Note",lines=14,placeholder="Paste an operative note…")
+            payer=gr.Dropdown(PAYER_CHOICES,value="Medicare",label="Payer")
+            topk=gr.Slider(1,15,value=10,step=1,label="Top-K")
+            run=gr.Button("Analyze Note",variant="primary"); clear=gr.Button("Clear")
+            gr.Examples(EXAMPLES,inputs=[note,payer,topk],label="Quick Examples")
+            fb_choice=gr.Radio(["👍","👎"],label="Helpful?")
+            fb_text=gr.Textbox(label="Optional comment",lines=2)
+            fb_btn=gr.Button("Submit Feedback"); fb_status=gr.Markdown("")
+            sid_show=gr.Textbox(label="Session ID",interactive=False)
+            export=gr.Button("Export JSON"); export_file=gr.File(label="Download",interactive=False)
+            probe_btn=gr.Button("Run Probe"); probe_md=gr.Markdown("")
+            test_btn=gr.Button("Test Live Log Push"); test_md=gr.Markdown("")
         with gr.Column(scale=7):
             gr.Markdown("#### Results")
-            summary_md = gr.Markdown("—", elem_classes=["badge-row"])
-
-            # Suggestions table (no modifier columns)
-            table = gr.Dataframe(
-                value=EMPTY_SUGG_DF,
-                label="CPT Suggestions",
-                interactive=False,
-                row_count=(0, "dynamic"),
-                wrap=True,
-                elem_classes=["table-wrap"],
-                elem_id="suggestions_table",
-            )
-
-            # Case-level modifiers table
-            gr.Markdown("### Case Modifiers (visit-level)")
-            case_mods_table = gr.Dataframe(
-                value=EMPTY_MODS_DF.copy(),
-                headers=["modifier","reason"],
-                interactive=False,
-                wrap=True,
-                label="Case Modifiers",
-            )
-
-            with gr.Accordion("Raw JSON", open=False):
-                json_out = gr.Code(language="json", value="", interactive=False)
-            warn_md = gr.Markdown("")
-
-    # ---- Events / Wiring ----
-    def _on_load():
-        sid = new_session()
-        return sid, sid
-
-    demo.load(_on_load, outputs=[session_id, sid_show])
-
-    run_inputs = [note_in, payer_dd, topk, session_id]
-    run_outputs = [table, case_mods_table, summary_md, json_out, warn_md, session_id]
-
-    run_btn.click(run_inference, inputs=run_inputs, outputs=run_outputs)
-    note_in.submit(run_inference, inputs=run_inputs, outputs=run_outputs)
-
-    clear_btn.click(
-        on_clear,
-        outputs=[note_in, payer_dd, topk, table, case_mods_table, summary_md, json_out, warn_md, session_id]
-    )
-
-    fb_submit.click(record_feedback, inputs=[session_id, fb_choice, fb_text], outputs=fb_status)
-    export_btn.click(do_export, inputs=[session_id], outputs=[export_file])
-
-    probe_btn.click(run_probe, inputs=[session_id], outputs=[probe_md, warn_md])
-
-if __name__ == "__main__":
-    # If running locally: set server_name to 0.0.0.0 for external access; Space ignores.
-    demo.launch()
+            summary=gr.Markdown("—",elem_classes=["badge-row"])
+            table=gr.Dataframe(value=EMPTY_SUGG_DF,label="CPT Suggestions",interactive=False,elem_classes=["table-wrap"])
+            gr.Markdown("### Case Modifiers")
+            mods=gr.Dataframe(value=EMPTY_MODS_DF.copy(),interactive=False)
+            json_out=gr.Code(language="json",value="",interactive=False)
+            warn=gr.Markdown("")
+    demo.load(lambda: (new_session(),new_session()),outputs=[sid,sid_show])
+    run.click(run_inference,inputs=[note,payer,topk,sid],outputs=[table,mods,summary,json_out,warn,sid])
+    note.submit(run_inference,inputs=[note,payer,topk,sid],outputs=[table,mods,summary,json_out,warn,sid])
+    clear.click(on_clear,outputs=[note,payer,top