Create app.py

app.py

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+import gradio as gr
+import openai
+import os
+from dotenv import load_dotenv
+from pydub import AudioSegment
+
+load_dotenv()
+
+#accessing openapi Key
+openai.api_key = os.getenv("OPENAI_API_KEY")
+
+audio_messages = [{"role": "system", "content": 'You are an AI assistant expert. Respond to all input in precise, crisp and easy to understand language.'}]
+text_messages = [{"role": "system", "content": 'You are an AI assistant expert. Respond to all input in precise, crisp and easy to understand language.'}]
+global user_text_input, text_output, user_audio_input, audio_output
+
+"""
+It seems like the gr.Audio source is not generating a WAV file, which is required for the openai.Audio.transcribe() method to work. 
+To convert the audio file to WAV format, i have used a library like Pydub.
+"""
+
+def audio_transcribe(audio):
+    global audio_messages
+    audio_message = audio_messages
+
+    #audio processing to whisper API.
+    audio_file = AudioSegment.from_file(audio)
+    audio_file.export("temp.wav", format="wav")
+    final_audio_file = open("temp.wav", "rb")
+    transcript = openai.Audio.transcribe("whisper-1", final_audio_file)
+    os.remove("temp.wav")
+
+    #transcripted input to chatGPT API for chatCompletion 
+    audio_message.append({"role": "user", "content": transcript["text"]}) # type: ignore
+    response = openai.ChatCompletion.create(model="gpt-3.5-turbo", messages=audio_message)
+    system_message = response["choices"][0]["message"] # type: ignore
+    audio_message.append(system_message)
+
+    chat_transcript = ""
+    for message in audio_message:
+        if message['role'] != 'system':
+            chat_transcript += message['role'] + ": " + message['content'] + "\n\n"
+
+    return chat_transcript
+
+def text_transcribe(name):
+    global text_messages
+    text_message = text_messages
+    user_text_input.update("")
+    #transcripted input to chatGPT API
+    text_message.append({"role": "user", "content": name}) # type: ignore
+    response = openai.ChatCompletion.create(model="gpt-3.5-turbo", messages=text_message)
+    system_message = response["choices"][0]["message"] # type: ignore
+    text_message.append(system_message)
+    
+    chat_transcript = ""
+    for message in text_message:
+        if message['role'] != 'system':
+            chat_transcript += message['role'] + ": " + message['content'] + "\n\n"
+    return chat_transcript
+
+title = """<h1 align="center">Your Chat-GPT AI Assistant at your Service!! 😎 </h1>"""
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.HTML(title)
+    with gr.Tab("Audio Input"):
+        with gr.Row():
+            user_audio_input = (gr.Audio(source="microphone", type="filepath", label="Speak Here"))
+            audio_input = user_audio_input
+            audio_output = gr.Textbox(label="AI Response", lines=20, placeholder="AI Response will be displayed here...")
+        with gr.Row():
+            audio_submit_button = gr.Button("Submit")
+    with gr.Tab("Text Input"):
+        with gr.Row():
+            user_text_input = (gr.Textbox(label="Type Here", lines=20, placeholder="Type your message here..."))
+            text_input = user_text_input
+            text_output = gr.Textbox(label="AI Response", lines=20, placeholder="AI Response will be displayed here...")
+        with gr.Row():
+            text_submit_button = gr.Button("Submit")
+    audio_submit_button.click(fn=audio_transcribe, inputs=audio_input, outputs=audio_output)
+    text_submit_button.click(fn=text_transcribe, inputs=text_input, outputs=text_output)
+    
+    gr.Markdown("<center> Made with ❤️ by Tanish Gupta. Credits to 🤗 Spaces for Hosting this App </center>")
+
+demo.launch(share=True)