Update app.py

app.py

@@ -256,11 +256,11 @@ def speech_to_text(video_file_path, selected_source_lang, whisper_model, num_spe
         raise RuntimeError("Error Running inference with local model", e)
 
 
-def create_transcription_summary(openai_key, prompt, transcript_result_path):
+def create_transcription_summary(openai_key, prompt):
     openai.api_key = openai_key
     system_template = prompt
 
-    with open(transcript_result_path, "r") as file:
+    with open("output/transcript_result.csv", "r") as file:
         transcript_text = file.read()
 
     completion = openai.ChatCompletion.create(
@@ -274,14 +274,6 @@ def create_transcription_summary(openai_key, prompt, transcript_result_path):
     return transcript_summary
 
 
-# def transcription_summary_btn_click_callback():
-#     openai_key = openai_key_in.value
-#     prompt = openai_prompt_in.value
-#     transcript_result_path = "output/transcript_result.csv"
-#     transcript_summary = create_transcription_summary(openai_key, prompt, transcript_result_path)
-#     transcription_summary_out.value = transcript_summary
-
-
 # ---- Gradio Layout -----
 # Inspiration from https://huggingface.co/spaces/RASMUS/Whisper-youtube-crosslingual-subtitles
 video_in = gr.Video(label="Video file", mirror_webcam=False)
@@ -387,7 +379,7 @@ with demo:
                 openai_prompt_in.render()
                 openai_summary_btn = gr.Button("Evaluate and analyze transcription content")
                 openai_summary_btn.click(create_transcription_summary,
-                                         [openai_key_in, openai_prompt_in, "output/transcript_result.csv"],
+                                         [openai_key_in, openai_prompt_in],
                                          [openai_summary_out]
                                          )