Update app.py

app.py

@@ -9,9 +9,11 @@ from datetime import timedelta
 from pyannote.audio import Pipeline
 
 # --- Configuration & Tokens ---
-# You can hardcode your token here or use the Sidebar in the App
-HF_TOKEN = os.environ.get("HF_TOKEN", "REPLACE_WITH_YOUR_HF_TOKEN")
-GEMINI_API_KEY = os.environ.get("GEMINI_API_KEY", "")
+# OPTION 1: Set this as a 'Secret' in Hugging Face Space Settings (Recommended)
+
+# Logic to determine which keys to use
+ENV_HF_TOKEN = os.environ.get("HF_TOKEN", "")
+ENV_GEMINI_KEY = os.environ.get("GEMINI_API_KEY", "")
 
 def format_timecode(seconds, fps=25):
     """Converts seconds to HH:MM:SS:FF for Resolve/Premiere."""
@@ -75,11 +77,16 @@ st.title("Documentary AI: Pipeline")
 
 with st.sidebar:
     st.header("Settings")
-    input_gemini_key = st.text_input("Gemini API Key", type="password", value=GEMINI_API_KEY)
-    input_hf_token = st.text_input("HF Token (Diarization)", type="password", value=HF_TOKEN)
     
-    active_api_key = input_gemini_key if input_gemini_key else GEMINI_API_KEY
-    active_hf_token = input_hf_token if input_hf_token else HF_TOKEN
+    # Determine default values for inputs
+    def_gemini = ENV_GEMINI_KEY if ENV_GEMINI_KEY else HARDCODED_GEMINI_KEY
+    def_hf = ENV_HF_TOKEN if ENV_HF_TOKEN else HARDCODED_HF_TOKEN
+
+    input_gemini_key = st.text_input("Gemini API Key", type="password", value=def_gemini)
+    input_hf_token = st.text_input("HF Token (Diarization)", type="password", value=def_hf)
+    
+    active_api_key = input_gemini_key
+    active_hf_token = input_hf_token
     fps = st.number_input("Timeline FPS", value=25)
 
 uploaded_file = st.file_uploader("Upload Video/Audio Clip", type=["mp4", "m4a", "wav", "mp3", "mov"])
@@ -88,8 +95,8 @@ if uploaded_file:
     # --- Step 1: Technical Processing ---
     if "transcript" not in st.session_state:
         if st.button("Step 1: Transcribe & Diarize"):
-            if not active_hf_token or active_hf_token.startswith("REPLACE"):
-                st.error("Please provide a valid Hugging Face Token.")
+            if not active_hf_token or "PASTE_YOUR_HF_TOKEN" in active_hf_token:
+                st.error("Please provide a valid Hugging Face Token in the sidebar or hardcode it in app.py.")
             else:
                 with st.spinner("Processing... Extracting audio, identifying speakers, and transcribing:"):
                     # Save local temp file