add all

.env

@@ -0,0 +1 @@
+TRITON_URL=192.168.130.14:3089

.env.example

@@ -0,0 +1 @@
+TRITON_URL=****

.gitignore

@@ -0,0 +1,3 @@
+/data
+.venv
+__pycache__

Dockerfile

@@ -0,0 +1,23 @@
+FROM python:3.12-slim
+
+# Set environment variables
+ENV DEBIAN_FRONTEND=noninteractive \
+    PYTHONUNBUFFERED=1 \
+    PYTHONDONTWRITEBYTECODE=1
+
+# Copy requirements file
+COPY requirements.txt /app/requirements.txt
+
+# Install requirements
+RUN pip install --no-deps git+https://git.d.aiengines.ir/bi/asr_triton_client.git@05c8f7a88d3ff41d82591b6beb41bab86d81d421
+RUN pip install --no-cache-dir -r /app/requirements.txt
+
+# Set working directory and copy app
+WORKDIR /app
+COPY . /app
+
+# Expose necessary ports
+EXPOSE 8000
+
+# Command to run the script
+CMD ["uvicorn", "src.main:app", "--host", "0.0.0.0", "--port", "8000"]

README.md

@@ -0,0 +1,27 @@
+## ASR SERVICE
+
+### A FASTAPI client for receieving audio data from font and sending audio to a Triton ASR service using SSE or WebSocket streaming. It yields real-time transcription results as JSON-like events.
+
+
+## How to run
+
+### SET ENVIRONMENT
+
+    1-create a file .env and set TRITON_URL
+
+### 1-DEVELOPMENT
+#### Run the system : Uvicorn and Fastapi
+	.venv/bin/uvicorn src.main:app  --host 0.0.0.0 --port 8000
+
+### 2-DEPLOYMENT
+#### Docker Build
+    docker build -t asr_client:latest --build-arg DEBIAN_FRONTEND=noninteractive .
+
+
+#### Docker Run
+    docker run -d --gpus all --network host --restart unless-stopped asr_client:latest
+
+
+
+there was a problem in installing ast_client package : 
+ pip couldnot find a versaion for perf-analyzer==2.59.1 : so i removed it

config/base.py

@@ -0,0 +1,7 @@
+from dotenv import load_dotenv
+import os
+
+load_dotenv()
+
+TRITON_URL = os.getenv("TRITON_URL")
+MIN_CHUNK_SIZE = 90000

requirements.txt

@@ -0,0 +1,30 @@
+fastapi==0.116.1
+uvicorn==0.35.0
+aiohappyeyeballs==2.6.1
+aiohttp==3.13.0
+aiosignal==1.4.0
+async-timeout==5.0.1
+attrs==25.4.0
+Brotli==1.1.0
+certifi==2025.10.5
+frozenlist==1.8.0
+gevent==25.9.1
+geventhttpclient==2.3.4
+greenlet==3.2.4
+grpcio==1.67.1
+idna==3.11
+multidict==6.7.0
+numpy==2.2.6
+packaging==25.0
+propcache==0.4.1
+protobuf==5.29.5
+pydub==0.25.1
+python-dotenv==1.1.1
+python-rapidjson==1.21
+tritonclient==2.61.0
+typing_extensions==4.15.0
+urllib3==2.5.0
+websockets==15.0.1
+yarl==1.22.0
+zope.event==6.0
+zope.interface==8.0.1

src/main.py

@@ -0,0 +1,30 @@
+from fastapi import FastAPI, WebSocket
+import asyncio
+from asr.service import TritonGrpcClient
+import json
+
+from config.base import TRITON_URL, MIN_CHUNK_SIZE  
+
+
+app = FastAPI()
+client = TritonGrpcClient(TRITON_URL)
+
+
+@app.websocket("/asr")
+async def websocket_endpoint(ws: WebSocket):
+    print("Starting ASR service")
+    await ws.accept()
+
+    audio_buffer = bytearray()
+
+    try:
+        while True:
+            data = await ws.receive_bytes()
+            audio_buffer.extend(data)
+
+            async for s in client.event_stream_from_bytes(raw=bytes(audio_buffer), filename="stream.webm"):
+                await ws.send_text(json.dumps(s, ensure_ascii=False))
+
+    except Exception as e:
+        print("WebSocket error:", e)
+        await ws.close()

test/test.js

@@ -0,0 +1,16 @@
+const ws = new WebSocket("ws://localhost:8000/asr");
+
+ws.onmessage = (event) => {
+    console.log("ASR Result:", event.data);
+};
+
+async function startStreaming() {
+    const stream = await navigator.mediaDevices.getUserMedia({ audio: true });
+    const recorder = new MediaRecorder(stream, { mimeType: "audio/webm" });
+
+    recorder.ondataavailable = (event) => {
+        ws.send(event.data); // send audio chunks to backend
+    };
+
+    recorder.start(500); // send audio every 250 ms
+}

test/test.py

@@ -0,0 +1,27 @@
+import asyncio
+import websockets
+import json
+
+AUDIO_FILE = "./khabar_1_5.wav"  # Replace with your audio file path
+WS_URL = "ws://127.0.0.1:8000/asr"
+
+async def send_audio():
+    async with websockets.connect(WS_URL) as ws:
+        print("Connected to ASR WebSocket")
+
+        # Read the audio file in chunks
+        with open(AUDIO_FILE, "rb") as f:
+            chunk_size = 21920
+            while chunk := f.read(chunk_size):
+                await ws.send(chunk)
+                
+        try:
+            while True:
+                message = await ws.recv()
+                data = json.loads(message)
+                print("Received:", data)
+        except websockets.exceptions.ConnectionClosed:
+            print("WebSocket closed by server")
+
+# Run the async client
+asyncio.run(send_audio())