Update app.py

app.py

@@ -1,19 +1,50 @@
-import gradio as gr
 import openai
+import gradio as gr
 
-# Set API Key
 openai.api_key = "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"
 
-# Define a function that will use OpenAI's API to transcribe an audio file
-def transcribe_audio(inp):
-    with open(inp.name, 'rb') as file:
-        transcript = openai.Audio.transcribe("whisper-1", file)
+def transcribe(audio):
+    with open(audio, "rb") as audio_file:
+        transcript = openai.Audio.transcribe("whisper-1", audio_file)
     return transcript["text"]
 
-# Define the Gradio interface
-iface = gr.Interface(fn=transcribe_audio, 
-                     inputs=gr.inputs.Audio(source="microphone", type="filepath", label="Record audio"), 
-                     outputs="text")
+def generate_response(transcribed_text):
+    response = openai.Completion.create(
+        engine="text-davinci-003",
+        prompt=transcribed_text,
+        max_tokens=1024,
+        n=1,
+        stop=None,
+        temperature=0.5,
+    )
+    return response.choices[0].text
+
+def run_cmd(command):
+    try:
+        print(command)
+        call(command)
+    except KeyboardInterrupt:
+        print("Process interrupted")
+        sys.exit(1)
+
+def inference(text):
+    cmd = ['tts', '--text', text]
+    run_cmd(cmd)
+    return 'tts_output.wav'
+
+def process_audio_and_respond(audio):
+    text = transcribe(audio)
+    response_text = generate_response(text)
+    output_file = inference(response_text)
+    return output_file
+
+demo = gr.Blocks()
+
+with demo:
+    audio_file = gr.inputs.Audio(source="microphone", type="filepath")
+    button = gr.Button("Uliza Swali")
+    outputs = gr.outputs.Audio(type="filepath", label="Output Audio")
+
+    button.click(fn=process_audio_and_respond, inputs=audio_file, outputs=outputs)
 
-# Launch the interface
-iface.launch()
+demo.launch()