Update app.py

app.py

@@ -0,0 +1,51 @@
+import streamlit as st
+import os
+from pipelines.video_process import extract_audio_ffmpeg, apply_edits
+from pipelines.ai_inference import transcribe_audio, generate_edit_instructions
+# from pipelines.auth_utils import check_auth_status  # If using custom
+import openai
+
+def main():
+    st.title("Smart Edit Assistant 🎬")
+    # Check if user is logged in if using custom auth
+    # user_info = check_auth_status()
+    # if not user_info: 
+    #     st.stop()
+
+    openai_api_key = os.getenv("OPENAI_API_KEY", "")
+    if openai_api_key:
+        openai.api_key = openai_api_key
+    else:
+        st.warning("No OpenAI API key found in environment.")
+
+    uploaded_file = st.file_uploader("Upload your video", type=["mp4", "mov", "mkv"])
+    if uploaded_file is not None:
+        with open("temp_input.mp4", "wb") as f:
+            f.write(uploaded_file.getbuffer())
+
+        st.video("temp_input.mp4")
+        
+        if st.button("Process Video"):
+            with st.spinner("Extracting audio..."):
+                audio_path = extract_audio_ffmpeg("temp_input.mp4", "temp_audio.wav")
+
+            with st.spinner("Transcribing..."):
+                transcript_text = transcribe_audio(audio_path)  # calls either local or API-based Whisper
+
+            st.text_area("Transcript", transcript_text, height=200)
+
+            with st.spinner("Generating edit instructions with GPT..."):
+                edit_instructions = generate_edit_instructions(transcript_text)
+
+            st.write(edit_instructions)
+
+            with st.spinner("Applying edits..."):
+                edited_video_path = apply_edits("temp_input.mp4", edit_instructions)
+            
+            st.success("Done!")
+            st.video(edited_video_path)
+            with open(edited_video_path, "rb") as f_out:
+                st.download_button("Download Edited Video", data=f_out, file_name="edited_result.mp4", mime="video/mp4")
+
+if __name__ == "__main__":
+    main()