app.py

import asyncio
import base64
import os
import time
from io import BytesIO

import gradio as gr
import numpy as np
from google import genai
from gradio_webrtc import (
    AsyncAudioVideoStreamHandler,
    WebRTC,
    async_aggregate_bytes_to_16bit,
    VideoEmitType,
    AudioEmitType,
    get_twilio_turn_credentials,
)
from PIL import Image


def encode_audio(data: np.ndarray) -> dict:
    """Encode Audio data to send to the server"""
    return {"mime_type": "audio/pcm", "data": base64.b64encode(data.tobytes()).decode("UTF-8")}


def encode_image(data: np.ndarray) -> dict:
    with BytesIO() as output_bytes:
        pil_image = Image.fromarray(data)
        pil_image.save(output_bytes, "JPEG")
        bytes_data = output_bytes.getvalue()
    base64_str = str(base64.b64encode(bytes_data), "utf-8")
    return {"mime_type": "image/jpeg", "data": base64_str}


class GeminiHandler(AsyncAudioVideoStreamHandler):
    def __init__(
        self, expected_layout="mono", output_sample_rate=24000, output_frame_size=480
    ) -> None:
        super().__init__(
            expected_layout,
            output_sample_rate,
            output_frame_size,
            input_sample_rate=16000,
        )
        self.audio_queue = asyncio.Queue()
        self.video_queue = asyncio.Queue()
        self.quit = asyncio.Event()
        self.session = None
        self.last_frame_time = 0

    def copy(self) -> "GeminiHandler":
        return GeminiHandler(
            expected_layout=self.expected_layout,
            output_sample_rate=self.output_sample_rate,
            output_frame_size=self.output_frame_size,
        )
    
    async def video_receive(self, frame: np.ndarray):
        if self.session:
            # send image every 1 second
            if time.time() - self.last_frame_time > 1:
                self.last_frame_time = time.time()
                await self.session.send(encode_image(frame))
        self.video_queue.put_nowait(frame)
    
    async def video_emit(self) -> VideoEmitType:
        return await self.video_queue.get()

    async def connect(self, api_key: str):
        # with open("prompt.md", "r") as file:
        #     template = file.read()

        # filled_prompt = template.format(
        #     about_company=about_company,
        #     about_role=about_role,
        #     responsibilities=responsibilities,
        #     requirements=requirements,
        #     benefits=benefits,
        #     interview_questions=interview_questions
        # )
    
        if self.session is None:
            client = genai.Client(api_key=api_key, http_options={"api_version": "v1alpha"})
            config = {"response_modalities": ["AUDIO"]}
            async with client.aio.live.connect(
                model="gemini-2.0-flash-exp", config=config
            ) as session:
                self.session = session
                asyncio.create_task(self.receive_audio())
                await self.quit.wait()

    async def generator(self):
        while not self.quit.is_set():
            turn = self.session.receive()
            async for response in turn:
                if data := response.data:
                    yield data
    
    async def receive_audio(self):
        async for audio_response in async_aggregate_bytes_to_16bit(
            self.generator()
        ):
            self.audio_queue.put_nowait(audio_response)

    async def receive(self, frame: tuple[int, np.ndarray]) -> None:
        _, array = frame
        array = array.squeeze()
        audio_message = encode_audio(array)
        if self.session:
            await self.session.send(audio_message)

    async def emit(self) -> AudioEmitType:
        if not self.args_set.is_set():
            await self.wait_for_args()
        if self.session is None:
            asyncio.create_task(self.connect(self.latest_args[1]))
        array = await self.audio_queue.get()
        return (self.output_sample_rate, array)

    def shutdown(self) -> None:
        self.quit.set()
        self.connection = None
        self.args_set.clear()
        self.quit.clear()



css = """
#video-source {max-width: 600px !important; max-height: 600 !important;}
"""

with gr.Blocks(css=css) as demo:
    gr.HTML(
        """
    <div style='display: flex; align-items: center; justify-content: center; gap: 20px'>
        <div style="background-color: var(--block-background-fill); border-radius: 8px">
            <img src="https://www.gstatic.com/lamda/images/gemini_favicon_f069958c85030456e93de685481c559f160ea06b.png" style="width: 100px; height: 100px;">
        </div>
        <div>
            <h1>Gen AI SDK Voice Chat</h1>
            <p>Speak with Gemini using real-time audio + video streaming</p>
            <p>Powered by <a href="https://gradio.app/">Gradio</a> and <a href=https://freddyaboulton.github.io/gradio-webrtc/">WebRTC</a>⚡️</p>
            <p>Get an API Key <a href="https://support.google.com/googleapi/answer/6158862?hl=en">here</a></p>
        </div>
    </div>
    """
    )
    with gr.Row() as api_key_row:
        api_key = gr.Textbox(label="API Key", type="password", placeholder="Enter your API Key", value=os.getenv("GOOGLE_API_KEY"))
    with gr.Row(visible=False) as row:
        with gr.Column():
            webrtc = WebRTC(
                label="Video Chat",
                modality="audio-video",
                mode="send-receive",
                elem_id="video-source",
                rtc_configuration=get_twilio_turn_credentials(),
                icon="https://www.gstatic.com/lamda/images/gemini_favicon_f069958c85030456e93de685481c559f160ea06b.png",
                pulse_color="rgb(35, 157, 225)",
                icon_button_color="rgb(35, 157, 225)",
            )
        with gr.Column():
            about_company = gr.Textbox(label="About company", lines=3, placeholder="Enter details about the company")
            about_role = gr.Textbox(label="About this role", lines=3, placeholder="Enter details about the role")
            responsibilities = gr.Textbox(label="This is what you’ll be doing", lines=4, placeholder="Describe the responsibilities")
            requirements = gr.Textbox(label="What we are looking for", lines=4, placeholder="Describe the requirements")
            benefits = gr.Textbox(label="What we offer", lines=3, placeholder="Describe the benefits offered")
            interview_questions = gr.Textbox(label="Interview questions", lines=4, placeholder="Provide interview questions")
        
        webrtc.stream(
            GeminiHandler(),
            inputs=[webrtc, api_key],
            outputs=[webrtc],
            time_limit=90,
            concurrency_limit=2,
        )
        api_key.submit(
        lambda: (gr.update(visible=False), gr.update(visible=True)),
        None,
        [api_key_row, row],
    )


if __name__ == "__main__":
    demo.launch()