Build on TNSOR Speech AI

from openai import OpenAI

# 1-Line Drop-in replacement for OpenAI or Deepgram
client = OpenAI(
    base_url="https://tnsor.ksverse.in/v1",  # TNSOR Global Anycast Edge
    api_key="tn_live_8f9c4a2b"              # Your scoped API Key
)

audio_file = open("customer_support_call.mp3", "rb")

transcription = client.audio.transcriptions.create(
    model="whisper-1",
    file=audio_file,
    response_format="json"
)

# Returns accurate transcript at $0.0014/min (67% cheaper)
print(transcription.text)

import asyncio
import websockets
import json

async def stream_live_speech():
    uri = "wss://api.tnsor.io/v1/listen?key=tn_live_8f9c4a2b&encoding=linear16&sample_rate=16000"

    async with websockets.connect(uri) as ws:
        print("Connected to TNSOR Live Streamer (TTFT < 200ms)")

        # Stream continuous 100ms audio slices (3200 bytes per slice)
        with open("mic_input.pcm", "rb") as f:
            while chunk := f.read(3200):
                await ws.send(chunk)
                response = await ws.recv()
                data = json.loads(response)

                if data.get("is_final"):
                    print("Locked Sentence:", data["text"])
                else:
                    print("Streaming Token:", data["text"], end="\r")

asyncio.run(stream_live_speech())