add gradio_app

requirements.txt

@@ -1,3 +1,5 @@
 openai
 opencv-python
-python-dotenv
+python-dotenv
+gradio
+opencv-python-headless

src/obs_eval_gradio.py

@@ -0,0 +1,88 @@
+import gradio as gr
+import cv2
+import base64
+import openai
+import tempfile
+
+def process_video(video_file, api_key):
+    # Set the OpenAI API key
+    openai.api_key = api_key
+
+    # Read and process the video file
+    video = cv2.VideoCapture(video_file.name)
+    base64Frames = []
+    while video.isOpened():
+        success, frame = video.read()
+        if not success:
+            break
+        _, buffer = cv2.imencode(".jpg", frame)
+        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,
+                *map(lambda x: {"image": x, "resize": 768}, base64Frames[0::10]),
+            ],
+        },
+    ]
+
+    try:
+        result = openai.ChatCompletion.create(
+            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
+    except Exception as e:
+        return f"Error: {e}"
+    
+# Define the Gradio app
+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)
+
+        submit_button.click(fn=process_video, inputs=[video_upload, api_key_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()