version1 completed

requirements.txt

@@ -2,4 +2,5 @@ openai
 opencv-python
 python-dotenv
 gradio
-opencv-python-headless
+opencv-python-headless
+pytest-shutil

src/obs_eval_gradio.py

@@ -2,9 +2,8 @@ import gradio as gr
 import cv2
 import base64
 import openai
-import tempfile
 
-def process_video(video_file, api_key):
+def process_video(video_file, api_key, instruction):
     # Set the OpenAI API key
     openai.api_key = api_key
 
@@ -19,21 +18,11 @@ def process_video(video_file, api_key):
         base64Frames.append(base64.b64encode(buffer).decode("utf-8"))
     video.release()
 
-    # Instruction for narration generation
-    INSTRUCTION = " ".join([
-        "These are frames of a video.",
-        "Create a short voiceover script in the style of a super excited Brazilian sports narrator who is narrating his favorite match.",
-        "He is a big fan of Messi, the player who scores in this clip.",
-        "Use caps and exclamation marks where needed to communicate excitement.",
-        "Only include the narration, your output must be in English.",
-        "When the ball goes into the net, you must scream GOL either once or multiple times."
-    ])
-
     PROMPT_MESSAGES = [
         {
             "role": "user",
             "content": [
-                INSTRUCTION,
+                instruction,
                 *map(lambda x: {"image": x, "resize": 768}, base64Frames[0::10]),
             ],
         },
@@ -44,7 +33,6 @@ def process_video(video_file, api_key):
             model="gpt-4-vision-preview",
             messages=PROMPT_MESSAGES,
             api_key=openai.api_key,
-            headers={"Openai-Version": "2020-11-07"},
             max_tokens=500,
         )
         return result.choices[0].message.content
@@ -56,33 +44,17 @@ def main():
     with gr.Blocks() as app:
         gr.Markdown("## Video Narration Generator")
         with gr.Row():
-            with gr.Column():
-                api_key_input = gr.Textbox(label="Enter your OpenAI API Key")
-                video_upload = gr.File(label="Upload your video")
-                submit_button = gr.Button("Generate Script", elem_id="submit_button")
-            with gr.Column():
-                output_box = gr.Textbox(label="Generated Script", lines=10, interactive=False)
+            with gr.Column(scale=1):
+                api_key_input = gr.Textbox(label="Enter your OpenAI API Key", lines=1)
+                instruction_input = gr.Textbox(label="Enter Narration Instruction", placeholder="Enter your custom instruction here...", lines=5)
+                video_upload = gr.File(label="Upload your video", type="file")
+                submit_button = gr.Button("Generate Script")
+            with gr.Column(scale=1):
+                output_box = gr.Textbox(label="Generated Script", lines=7, interactive=False)
 
-        submit_button.click(fn=process_video, inputs=[video_upload, api_key_input], outputs=output_box)
+        submit_button.click(fn=process_video, inputs=[video_upload, api_key_input, instruction_input], outputs=output_box)
 
     app.launch()
 
 if __name__ == "__main__":
-    main()
-
-# # Define the Gradio app
-# def main():
-#     with gr.Blocks() as app:
-#         gr.Markdown("## Video Narration Generator")
-#         with gr.Row():
-#             video_upload = gr.File(label="Upload your video")
-#             api_key_input = gr.Textbox(label="Enter your OpenAI API Key")
-#             submit_button = gr.Button("Generate Script")
-#         output_box = gr.Textbox(label="Generated Script", lines=10, interactive=False)
-
-#         submit_button.click(fn=process_video, inputs=[video_upload, api_key_input], outputs=output_box)
-
-#     app.launch()
-
-# if __name__ == "__main__":
-#     main()
+    main()