Update src/streamlit_app.py

src/streamlit_app.py

@@ -49,8 +49,10 @@ st.markdown("""
 st.markdown('<div class="card"><span class="big-font">Speech Threat Detection Dashboard</span> <span class="muted"> — upload audio or paste text </span></div>', unsafe_allow_html=True)
 
 UPLOAD_DIR = Path("/tmp/uploads")
+UPLOAD_DIR.mkdir(parents=True, exist_ok=True)
+
 DB_CSV = Path("/tmp/db.csv")
-UPLOAD_DIR.mkdir(exist_ok=True)
+
 if not DB_CSV.exists():
     pd.DataFrame(columns=["timestamp","filename","mode","transcription","predicted_label","scores"]).to_csv(DB_CSV, index=False)
 
@@ -84,10 +86,10 @@ def save_audio_file(uploaded_file) -> Path:
 def normalize_audio_to_wav(path: Path) -> Path:
     sound = AudioSegment.from_file(path)
     sound = sound.set_frame_rate(16000).set_channels(1).set_sample_width(2)
-    wav_path = path.with_suffix(".wav")
+    #wav_path = path.with_suffix(".wav")
+    wav_path = UPLOAD_DIR / f"{path.stem}.wav"
     sound.export(wav_path, format="wav")
     return wav_path
-
 @st.cache_resource(show_spinner=False)
 def get_asr_pipeline() -> Tuple[str, "Pipeline"]:
     """Load Hugging Face Whisper ASR model"""