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import gradio as gr
from transformers import pipeline
import time
ASR_MODEL = "openai/whisper-tiny" # small/medium if you switch to ZeroGPU
ZSC_MODEL = "facebook/bart-large-mnli" # for multilingual use: "MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7"
asr = pipeline("automatic-speech-recognition", model=ASR_MODEL)
zsc = pipeline("zero-shot-classification", model=ZSC_MODEL)
DEFAULT_INTENTS = [
"turn_on_lights","turn_off_lights","volume_up","volume_down",
"start_music","pause_music","set_timer","cancel_timer",
"open_calendar","create_note","start_recording","stop_recording"
]
def tool_turn_on_lights():
return "Lights → ON"
def tool_turn_off_lights():
return "Lights → OFF"
def tool_volume_up():
return "Volume → UP"
def tool_volume_down():
return "Volume → DOWN"
def tool_start_music():
return "Music → PLAY"
def tool_pause_music():
return "Music → PAUSE"
def tool_set_timer():
return "Timer → 5 min (demo)"
def tool_cancel_timer():
return "Timer → CANCELLED"
def tool_open_calendar():
return "Calendar → OPENED"
def tool_create_note(text):
return f"Note saved: '{text[:60]}'"
def tool_start_recording():
return "Recording → STARTED"
def tool_stop_recording():
return "Recording → STOPPED"
TOOLS = {
"turn_on_lights": tool_turn_on_lights,
"turn_off_lights": tool_turn_off_lights,
"volume_up": tool_volume_up,
"volume_down": tool_volume_down,
"start_music": tool_start_music,
"pause_music": tool_pause_music,
"set_timer": tool_set_timer,
"cancel_timer": tool_cancel_timer,
"open_calendar": tool_open_calendar,
"create_note": tool_create_note,
"start_recording": tool_start_recording,
"stop_recording": tool_stop_recording,
}
def parse_intents(custom):
if not custom or not custom.strip():
return DEFAULT_INTENTS
return [t.strip() for t in custom.split(",") if t.strip()]
def agent(audio_path, custom_intents, history):
if not audio_path:
return gr.update(), gr.update(), "No audio.", history
transcript = asr(audio_path)["text"].strip()
if not transcript:
return gr.update(), gr.update(), "No speech detected.", history
intents = parse_intents(custom_intents)
out = zsc(transcript, candidate_labels=intents, multi_label=False)
labels = out["labels"]
scores = out["scores"]
top3 = {labels[i]: float(scores[i]) for i in range(min(3, len(labels)))}
chosen = labels[0]
if chosen == "create_note":
result = TOOLS[chosen](transcript)
else:
result = TOOLS.get(chosen, lambda: f"No tool bound: {chosen}")()
stamp = time.strftime("%H:%M:%S")
history = history + [[f"User: {transcript}", f"Agent: {chosen} → {result}"]]
return top3, chosen, result, history
with gr.Blocks(title="Voice Agent: ASR → Intent → Tools") as demo:
gr.Markdown("# 🎙️ Voice Agent\nSpeak or upload audio → transcript via Whisper → zero-shot intent → tool execution.")
with gr.Row():
audio = gr.Audio(sources=["microphone","upload"], type="filepath", label="Audio")
intents_box = gr.Textbox(label="Intents (comma-separated)", value=", ".join(DEFAULT_INTENTS))
run = gr.Button("Run")
topk = gr.Label(num_top_classes=3, label="Top-k Intents")
chosen = gr.Textbox(label="Chosen Intent")
result = gr.Textbox(label="Action Result")
chat = gr.Chatbot(label="Execution Log")
state = gr.State([])
run.click(agent, inputs=[audio, intents_box, state], outputs=[topk, chosen, result, chat], queue=True)
if __name__ == "__main__":
demo.launch()
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