Create app.py

app.py

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+!pip install gradio
+!pip install transformers
+!pip install pipeline
+import gradio as gr
+from transformers import pipeline
+import requests
+import os
+from IPython.display import FileLink, HTML, display
+import time
+
+
+asr = pipeline("automatic-speech-recognition", model="openai/whisper-base.en")
+
+def download_screenplay(screenplay):
+    filename = "generated_screenplay.txt"
+    with open(filename, "w", encoding="utf-8") as file:
+        file.write(screenplay)
+    display(HTML(f'<a href="{filename}" download>Download Screenplay</a>'))
+
+def speech_to_text(speech):
+    text = asr(speech)["text"]
+    return text
+
+
+PALM_KEY = "AIzaSyArKo4frsgJqoAiuJJ0GVsiIlDAjqD08z4"
+cons = """
+-elaborate everything
+-no repetations
+-add naration
+- 'Close up':
+- 'Medium':
+- 'Wide':
+Begin your narration with these cues, and let the screenplay unfold based on the user's input. We want to experience the heart-pounding excitement of this crucial match, and you are our guide through this thrilling journey.
+"""
+
+def generate_text(prompt, length=500, genre=None):
+  url = "https://generativelanguage.googleapis.com/v1beta3/models/text-bison-001:generateText?key=" + PALM_KEY
+  headers = {
+    "Content-Type": "application/json",
+  }
+  payload = {
+    "prompt": {
+      "text": cons+prompt+f" Genre: {genre} Length: {length} words.",
+    },
+  }
+  response = requests.post(url, headers=headers, json=payload)
+  response.raise_for_status()
+  response_json = response.json()
+  return response_json['candidates'][0]['output']
+
+
+def download_screenplay(screenplay):
+    filename = "generated_screenplay.txt"
+    with open(filename, "w", encoding="utf-8") as file:
+        file.write(screenplay)
+
+def submit_feedback(feedback):
+    feedback_message = "Thank you for your feedback! We appreciate your input."
+    return feedback_message
+
+
+demo = gr.Blocks(
+    css="""
+    .gradio-container {background-color: beige;font-family: Roboto, sans-serif;}footer {visibility: hidden; }
+    .Markdown-body { color: visible;}"""
+)
+
+with demo:
+    gr.Markdown(
+        """
+        <center><b><div style="font-size: 28px; color:#333333">
+        A web based application which generates movie screenplay with the input of voice 
+        </div></b></center>
+        """)
+    with gr.Tab("Audio to screenplay generation"):
+        demo.heading = "Problem statement: Generate a movie screenplay from an audio file."
+        audio_file = gr.Audio(type="filepath")
+        live=True
+        length = gr.Slider(label="Length in words",  step=1)
+        genre = gr.Dropdown(label="Genre", choices=["Action", "Adventure", "Comedy", "Drama", "Fantasy", "Horror", "Mystery", "Sci-Fi", "Thriller"])
+        text = gr.Textbox(label="Speech to Text")
+        generated_screenplay = gr.Textbox(label="Required screenplay")
+
+
+    with gr.Row():
+      b1 = gr.Button("CONVERT")
+      b2 = gr.Button("SCREENPLAY")
+      b3 = gr.Button("DOWNLOAD")
+
+
+    b1.click(speech_to_text, inputs=audio_file, outputs=text)
+    b2.click(generate_text, inputs=[text, length, genre], outputs=[generated_screenplay])
+    b3.click(download_screenplay, inputs=[generated_screenplay])
+
+    feedback = gr.Textbox(label="Feedback", placeholder="Share your feedback here")
+    feedback_button = gr.Button("Submit Feedback")
+    feedback_output = gr.Textbox(label="Feedback Status")
+    feedback_button.click(submit_feedback, inputs=[feedback], outputs=[feedback_output])
+
+
+demo.launch()