V1

- Setup basic audio -> text pipeline
- Setup basic app interface

.env

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+REPLICATE_API_TOKEN = r8_2nj6fllJpzdNMAA3vo9pymmfhvqOqf00zGghp

app.py

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+import gradio as gr
+import replicate
+import os
+
+REPLICATE_API_TOKEN = os.getenv("REPLICATE_API_TOKEN")
+
+def process_audio(audio):
+    if audio is None:
+        return "No audio file uploaded."
+    output = replicate.run(
+        "victor-upmeet/whisperx:84d2ad2d6194fe98a17d2b60bef1c7f910c46b2f6fd38996ca457afd9c8abfcb",
+        input={"audio_file": open(audio, "rb")},
+        api_token=REPLICATE_API_TOKEN
+    )
+    segments = output.get("segments") if isinstance(output, dict) else output
+
+    script = " ".join(seg["text"] for seg in segments) if segments else output.get("text", "No transcription found.")
+    return script
+
+with gr.Blocks(theme="monochrome") as demo:
+    gr.Markdown("# AIML430 Lecture Transcription Tool")
+    gr.Markdown("Upload an audio file to begin.")
+    audio_input = gr.Audio(type="filepath", sources=["upload"], label="Audio File")
+    raw_text_output = gr.Textbox(
+        label="Raw Text Output",
+        show_copy_button=True,
+        lines=10
+    )
+    audio_input.change(
+        fn=process_audio,
+        inputs=audio_input,
+        outputs=raw_text_output
+    )
+
+demo.launch()