Upload app.py

app.py

@@ -1,5 +1,6 @@
-# app.py — Diag Studio AI Frontend (TR/EN, retries, warm-up, artifacts download)
+# app.py — Diag Studio AI Frontend (TR/EN, retries, warm-up, artifacts, Strict/Full, anomaly gate, adjudication)
 import os
+import io
 import json
 import time
 import requests
@@ -48,6 +49,8 @@ L = {
         "detailed": "Detailed analysis (always on)",
         "use_data_uri": "Send as data:URI (safer for private backends)",
         "model": "Commentary model (OpenAI)",
+        "mode": "Prompt Mode",
+        "mode_help": "Strict groups similar timbres to reduce mislabels; Full uses detailed taxonomy.",
         "analyze": "Analyze",
         "reset": "Reset",
         "result": "Result",
@@ -69,7 +72,11 @@ L = {
         "analyzing": "Analyzing…",
         "lang_help": "Output language for GPT-4o commentary",
         "ok_false": "Request returned a controlled error from backend.",
-        "try_again": "Backend might be waking up or rate-limited. Try Analyze again or increase ‘Max total wait’."
+        "try_again": "Backend might be waking up or rate-limited. Try Analyze again or increase ‘Max total wait’.",
+        "gate": "Anomaly Gate",
+        "taxonomy": "Taxonomy",
+        "applied_rules": "Adjudication rules applied",
+        "confusions": "Common confusion pairs",
     },
     "tr": {
         "title": "Diag Studio AI — Motor Sesi Teşhis",
@@ -84,6 +91,8 @@ L = {
         "detailed": "Ayrıntılı analiz (her zaman açık)",
         "use_data_uri": "data:URI olarak gönder (özel backend için güvenli)",
         "model": "Yorum modeli (OpenAI)",
+        "mode": "Prompt Modu",
+        "mode_help": "Strict benzer tınıları gruplayıp karışmayı azaltır; Full detaylı taksonomi kullanır.",
         "analyze": "Analiz Et",
         "reset": "Sıfırla",
         "result": "Sonuç",
@@ -96,7 +105,7 @@ L = {
         "no_backend": "Bir backend URL girin (örn: http://127.0.0.1:7860)",
         "health_ok": "Backend erişilebilir.",
         "health_fail": "Backend’e erişilemedi.",
-        "upload_hint": "Streamlit varsayılan yükleme sınırı ~200 MB; mp3/wav/ogg kullanın.",
+        "upload_hint": "Streamlit yükleme sınırı ~200 MB; mp3/wav/ogg kullanın.",
         "footer": "İpucu: Dosya yüklemek istemezseniz herkese açık bir ses URL’si de girebilirsiniz.",
         "auto_retry": "429/500/502/503/504 için otomatik yeniden dene",
         "warmup": "Analizden önce backend’i ısıt",
@@ -105,7 +114,11 @@ L = {
         "analyzing": "Analiz ediliyor…",
         "lang_help": "GPT-4o yorum çıktısının dili",
         "ok_false": "Backend kontrollü bir hata döndürdü.",
-        "try_again": "Backend uyanıyor veya sınırlandı. Yeniden Dene’ye basın ya da ‘Azami bekleme’ değerini artırın."
+        "try_again": "Backend uyanıyor veya sınırlandı. Yeniden Dene’ye basın ya da ‘Azami bekleme’ değerini artırın.",
+        "gate": "Arıza Kapısı (Anomaly Gate)",
+        "taxonomy": "Taksonomi",
+        "applied_rules": "Uygulanan adjudication kuralları",
+        "confusions": "Sık karışan çiftler",
     }
 }
 
@@ -114,6 +127,8 @@ if "lang" not in st.session_state:
     st.session_state.lang = "tr"
 if "last_response" not in st.session_state:
     st.session_state.last_response = None
+if "audio_mem" not in st.session_state:
+    st.session_state.audio_mem = None  # keep last uploaded audio bytes for player
 
 # ================= Header =================
 col1, col2 = st.columns([0.6, 0.4])
@@ -135,11 +150,12 @@ api_base = st.text_input(t["backend_url"], value=backend_default)
 
 # ================= Advanced options =================
 with st.expander(t["adv"], expanded=False):
-    # Detailed analysis backend’te zorunlu True; burada yalnızca bilgi amaçlı gösteriyoruz.
     st.checkbox(t["detailed"], value=True, disabled=True)
     use_data_uri = st.checkbox(t["use_data_uri"], value=True)
     openai_model = st.text_input(t["model"], value="gpt-4o")
     prompt_override = st.text_area(t["prompt"], value="", height=120)
+    # NEW: Full/Strict selector
+    mode = st.selectbox(t["mode"], ["FULL", "STRICT"], index=0, help=t["mode_help"])
     auto_retry = st.checkbox(t["auto_retry"], value=True)
     warmup = st.checkbox(t["warmup"], value=True)
     max_wait = st.slider(t["max_wait"], 10, 180, 60, step=10)
@@ -153,6 +169,19 @@ file = st.file_uploader(t["upload"], type=["mp3", "wav", "ogg"])
 st.write(f"**{t['or']}**")
 audio_url = st.text_input(t["paste_url"], value="", placeholder="https://...")
 
+# If a file was uploaded, stash bytes for inline audio preview
+if file is not None:
+    try:
+        b = file.read()
+        st.session_state.audio_mem = (b, file.type or "audio/mpeg")
+        # Reset file pointer for requests
+        file.seek(0)
+    except Exception:
+        st.session_state.audio_mem = None
+
+if st.session_state.audio_mem:
+    st.audio(st.session_state.audio_mem[0], format=st.session_state.audio_mem[1])
+
 # ================= Controls =================
 c1, c2, c3 = st.columns([0.2, 0.2, 0.6])
 go = c1.button(f"▶ {t['analyze']}", type="primary")
@@ -198,13 +227,14 @@ def fetch_bytes(sess: requests.Session, base: str, url: str) -> bytes:
     r.raise_for_status()
     return r.content
 
-def post_analyze(sess: requests.Session, base: str, _file, _audio_url: str, lang: str) -> dict:
+def post_analyze(sess: requests.Session, base: str, _file, _audio_url: str, lang: str, mode: str) -> dict:
     url = f"{base.rstrip('/')}/analyze"
     data = {
         "detailed_analysis": "true",      # backend yine de True’ya sabitliyor
         "use_data_uri": "true" if use_data_uri else "false",
         "openai_model": openai_model or "gpt-4o",
-        "lang": lang,                     # <<< DİL backend’e gidiyor (tr/en)
+        "lang": lang,                     # "tr" | "en"
+        "prompt_mode": mode,              # "FULL" | "STRICT"
     }
     if prompt_override.strip():
         data["prompt"] = prompt_override.strip()
@@ -225,7 +255,6 @@ def post_analyze(sess: requests.Session, base: str, _file, _audio_url: str, lang
         attempts += 1
         try:
             resp = sess.post(url, data=data, files=files, timeout=180)
-            # Başarısız statüleri Retry mekanizması yönetir; yine de raise edelim:
             resp.raise_for_status()
             return resp.json()
         except Exception as e:
@@ -266,7 +295,13 @@ if go:
         if warmup:
             warm_up_backend(sess, api_base, total_budget=min(max_wait, 40))
         with st.spinner(t["analyzing"]):
-            res = post_analyze(sess, api_base, file, audio_url, st.session_state.lang)
+            # streamlit's UploadedFile can be used directly in requests; make sure pointer is at 0
+            if file is not None:
+                try:
+                    file.seek(0)
+                except Exception:
+                    pass
+            res = post_analyze(sess, api_base, file, audio_url, st.session_state.lang, mode)
         st.session_state.last_response = res
 
 # ================= Results =================
@@ -281,40 +316,66 @@ if res:
             st.expander("Debug").code(json.dumps(res["fal_debug"], ensure_ascii=False, indent=2), language="json")
     else:
         st.subheader(t["result"])
+
+        # Anomaly Gate & Taxonomy quick view
+        parsed = res.get("fal_parsed") or {}
+        if isinstance(parsed, dict):
+            gate = parsed.get("anomaly_gate") or {}
+            colg1, colg2, colg3 = st.columns([0.33, 0.33, 0.34])
+            with colg1:
+                st.markdown(f"**{t['gate']}**")
+                is_anom = gate.get("is_anomaly")
+                score = gate.get("score")
+                ev = gate.get("evidence")
+                st.write(f"• is_anomaly: `{is_anom}`")
+                st.write(f"• score: `{score}`")
+                if ev: st.write(f"• evidence: `{ev}`")
+            with colg2:
+                st.markdown(f"**{t['taxonomy']}**")
+                tax = parsed.get("taxonomy_version") or res.get("taxonomy_version")
+                st.write(f"`{tax or '—'}`")
+                pmode = res.get("prompt_mode")
+                if pmode:
+                    st.write(f"mode: `{pmode}`")
+            with colg3:
+                rules = (parsed.get("adjudication") or {}).get("applied_rules") or (res.get("adjudication") or {}).get("applied_rules")
+                st.markdown(f"**{t['applied_rules']}**")
+                if rules:
+                    st.code(json.dumps(rules, ensure_ascii=False, indent=2), language="json")
+                conf_pairs = (parsed.get("notes") or {}).get("confusion_pairs")
+                if conf_pairs:
+                    st.markdown(f"**{t['confusions']}**")
+                    st.code(json.dumps(conf_pairs, ensure_ascii=False, indent=2), language="json")
+
+        # Driver-friendly commentary
         comm = res.get("commentary") or ""
         if comm:
             st.markdown(f"**{t['commentary']}**")
             st.write(comm)
 
-        parsed = res.get("fal_parsed")
+        # Raw parsed JSON
         if parsed:
             st.markdown(f"**{t['json']}**")
             st.json(parsed)
 
+        # Backend artifacts
         st.markdown(f"**{t['backend_artifacts']}**")
         dls = res.get("downloads") or {}
         col_a, col_b, col_c = st.columns(3)
 
-        if dls.get("summary_txt"):
-            try:
-                data = fetch_bytes(sess, api_base, dls["summary_txt"])
-                col_a.download_button(label=t["download_summary"], data=data, file_name="summary.txt")
-            except Exception:
-                col_a.error("summary.txt ✖")
-
-        if dls.get("fal_parsed_json"):
-            try:
-                data = fetch_bytes(sess, api_base, dls["fal_parsed_json"])
-                col_b.download_button(label=t["download_parsed"], data=data, file_name="parsed.json", mime="application/json")
-            except Exception:
-                col_b.error("parsed.json ✖")
+        def fetch_and_button(label: str, key: str, file_name: str, column):
+            if dls.get(key):
+                try:
+                    data = fetch_bytes(sess, api_base, dls[key])
+                    column.download_button(label=label, data=data, file_name=file_name)
+                except Exception:
+                    column.error(f"{file_name} ✖")
+            else:
+                column.write("—")
 
-        if dls.get("fal_raw_txt"):
-            try:
-                data = fetch_bytes(sess, api_base, dls["fal_raw_txt"])
-                col_c.download_button(label=t["download_raw"], data=data, file_name="raw.txt")
-            except Exception:
-                col_c.error("raw.txt ✖")
+        fetch_and_button(t["download_summary"], "summary_txt", "summary.txt", col_a)
+        fetch_and_button(t["download_parsed"], "fal_parsed_json", "parsed.json", col_b)
+        fetch_and_button(t["download_raw"], "fal_raw_txt", "raw.txt", col_c)
 
 # ===== Footer =====
-st.caption("© 2025 Diag Studio AI — Streamlit frontend (TR/EN, retries, warm-up)")
+st.caption("© 2025 Diag Studio AI — Streamlit frontend (TR/EN, retries, warm-up, Strict/Full, anomaly gate, adjudication)")