File size: 5,883 Bytes
0c39cc3 8539a09 0c39cc3 8539a09 0c39cc3 8539a09 0c39cc3 8539a09 0c39cc3 8539a09 0c39cc3 8539a09 0c39cc3 8539a09 0c39cc3 8539a09 0c39cc3 8539a09 0c39cc3 155f656 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 |
import asyncio
import base64
import json
import os
import pathlib
from typing import AsyncGenerator, Literal
import gradio as gr
import numpy as np
from dotenv import load_dotenv
from fastapi import FastAPI
from fastapi.responses import HTMLResponse
from fastrtc import (
AsyncStreamHandler,
Stream,
get_twilio_turn_credentials,
wait_for_item,
)
from google import genai
from google.genai.types import (
LiveConnectConfig,
PrebuiltVoiceConfig,
SpeechConfig,
VoiceConfig,
Content,
Part
)
from gradio.utils import get_space
from pydantic import BaseModel
current_dir = pathlib.Path(__file__).parent
load_dotenv()
api_key = os.getenv("GEMINI_API_KEY")
if not api_key:
raise ValueError("GEMINI_API_KEY environment variable is not set")
def encode_audio(data: np.ndarray) -> str:
"""Encode Audio data to send to the server"""
return base64.b64encode(data.tobytes()).decode("UTF-8")
class GeminiHandler(AsyncStreamHandler):
"""Handler for the Gemini API"""
def __init__(
self,
expected_layout: Literal["mono"] = "mono",
output_sample_rate: int = 24000,
output_frame_size: int = 480,
) -> None:
super().__init__(
expected_layout,
output_sample_rate,
output_frame_size,
input_sample_rate=16000,
)
self.input_queue: asyncio.Queue = asyncio.Queue()
self.output_queue: asyncio.Queue = asyncio.Queue()
self.quit: asyncio.Event = asyncio.Event()
def copy(self) -> "GeminiHandler":
return GeminiHandler(
expected_layout="mono",
output_sample_rate=self.output_sample_rate,
output_frame_size=self.output_frame_size,
)
async def start_up(self):
if not self.phone_mode:
await self.wait_for_args()
# Fix: Extract voice_name properly - it should be a string, not a list
voice_name = self.latest_args[1] if len(self.latest_args) > 1 else "Puck"
else:
voice_name = "Puck" # Default to Puck for phone mode
client = genai.Client(
api_key=api_key,
http_options={"api_version": "v1alpha"},
)
config = LiveConnectConfig(
response_modalities=["AUDIO"], # type: ignore
speech_config=SpeechConfig(
voice_config=VoiceConfig(
prebuilt_voice_config=PrebuiltVoiceConfig(
voice_name=voice_name,
)
)
),
system_instruction=Content(
parts=[Part(
text="""You are an AI calling assistant for Ishwor Subedi, an AI/ML freelancer. When speaking with clients:
2. For professional inquiries, highlight these key skills concisely:
- 2+ years in machine learning and AI
- Computer Vision expertise
- NLP capabilities
- Software and mobile app development
- Upwork freelancer with proven track record
3. For generic questions:
- Provide brief, direct answers (1-2 sentences)
- Avoid lengthy explanations
- Always connect responses back to Ishwor's services when possible
4. Keep website reference simple: "Visit ishwor-subedi.com.np for portfolio details"
5. Speak in Hindi throughout
6. For unrelated topics: "Please contact Ishwor directly for assistance with this"
Maintain professional tone while keeping all responses concise and focused.
""")],
role="user"
)
)
async with client.aio.live.connect(
model="gemini-2.0-flash-exp", config=config
) as session:
async for audio in session.start_stream(
stream=self.stream(), mime_type="audio/pcm"
):
if audio.data:
array = np.frombuffer(audio.data, dtype=np.int16)
self.output_queue.put_nowait((self.output_sample_rate, array))
async def stream(self) -> AsyncGenerator[bytes, None]:
while not self.quit.is_set():
try:
audio = await asyncio.wait_for(self.input_queue.get(), 0.1)
yield audio
except (asyncio.TimeoutError, TimeoutError):
pass
async def receive(self, frame: tuple[int, np.ndarray]) -> None:
_, array = frame
array = array.squeeze()
audio_message = encode_audio(array)
self.input_queue.put_nowait(audio_message)
async def emit(self) -> tuple[int, np.ndarray] | None:
return await wait_for_item(self.output_queue)
def shutdown(self) -> None:
self.quit.set()
stream = Stream(
modality="audio",
mode="send-receive",
handler=GeminiHandler(),
rtc_configuration=get_twilio_turn_credentials() if get_space() else None,
concurrency_limit=2,
time_limit=90 if get_space() else None,
additional_inputs=[
gr.Dropdown(
label="Voice",
choices=[
"Puck",
"Charon",
"Kore",
"Fenrir",
"Aoede",
],
value="Puck",
),
],
)
class InputData(BaseModel):
webrtc_id: str
voice_name: str
app = FastAPI()
stream.mount(app)
@app.post("/input_hook")
async def _(body: InputData):
stream.set_input(body.webrtc_id, body.voice_name)
return {"status": "ok"}
@app.get("/")
async def index():
rtc_config = get_twilio_turn_credentials() if get_space() else None
html_content = (current_dir / "index.html").read_text()
html_content = html_content.replace("__RTC_CONFIGURATION__", json.dumps(rtc_config))
return HTMLResponse(content=html_content)
if __name__ == "__main__":
import os
import uvicorn
port = int(os.environ.get("PORT", 7860))
uvicorn.run(app, host="0.0.0.0", port=port)
|