Download app.py from mgbam/rentbot: direct link, hf CLI and curl.
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https://huggingface.co/spaces/mgbam/rentbot/resolve/6f740bf7e16b91b0071e8fbc68ba0d8a8d69d5e6/app.py
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hf download hf://spaces/mgbam/rentbot@6f740bf7e16b91b0071e8fbc68ba0d8a8d69d5e6/app.py
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curl -L -o app.py https://huggingface.co/spaces/mgbam/rentbot/resolve/6f740bf7e16b91b0071e8fbc68ba0d8a8d69d5e6/app.py
1.54 kB
| import gradio as gr | |
| import os | |
| from utils import init_openai, transcribe_audio, chat_with_gpt | |
| # Load API key | |
| init_openai() | |
| # Define the system prompt for RentBot | |
| SYSTEM_PROMPT = ( | |
| "You are RentBot, a friendly virtual leasing assistant. " | |
| "You answer inquiries about rental listings, schedule showings, and provide clear instructions to potential tenants." | |
| ) | |
| def handle_interaction(audio) -> tuple[str, str]: | |
| """ | |
| Gradio handler: saves incoming audio, transcribes it, then chats with GPT. | |
| Returns the transcript and the bot response. | |
| """ | |
| # Save incoming audio to disk | |
| audio_path = "input.wav" | |
| audio.save(audio_path) | |
| # Transcribe audio -> text | |
| transcript = transcribe_audio(audio_path) | |
| # Generate bot reply | |
| reply = chat_with_gpt(SYSTEM_PROMPT, transcript) | |
| return transcript, reply | |
| def main(): | |
| """ | |
| Launch the Gradio interface. | |
| """ | |
| iface = gr.Interface( | |
| fn=handle_interaction, | |
| inputs=gr.Audio(source="microphone", type="filepath", label="Speak to RentBot"), | |
| outputs=[ | |
| gr.Textbox(label="Transcribed Text"), | |
| gr.Textbox(label="RentBot Reply") | |
| ], | |
| title="RentBot 24/7", | |
| description=( | |
| "An AI virtual receptionist for property managers, " | |
| "built with OpenAI Whisper and GPT-4o-mini." | |
| ), | |
| allow_flagging="never", | |
| analytics_enabled=False | |
| ) | |
| iface.launch(server_name="0.0.0.0", server_port=7860, share=True) | |
| if __name__ == "__main__": | |
| main() |