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Agent Real Time Coaching

1. Prerequisites​

Before you start, ensure you have the following:

2. Clone the repository​

Use the git clone command to clone the PIOPIY python from our TeleCMI github repository

git clone https://github.com/telecmi/piopiy_python_example.git

Next, navigate to the ai_customer_support directory:

cd ai_customer_support

3. Intsall the piopiy venv package​

Once inside the project directory, install the required venv packages

python -m venv venv
source venv/bin/activate  # On Windows, use `venv\Scripts\activate`
pip install -r requirements.txt

4. Export data from terminal​

For testing purposes, we use Deepgram and ElevenLabs for text-to-speech. You can use either of the accounts to test it, or alternatively, you can use any text-to-speech service.

DG_API_KEY: We use text-to-speech as Deepgram. You can create the trial account and export API key from terminal.

EL_API_KEY: We use text-to-speech as ElevenLabs. You can create the trial account and export API key from terminal.

GROQ_API_KEY: We use LLM as Groq. You can create the trial account and export API key from terminal.

export DG_API_KEY=8a3aebba4cdc1001xxxxxxxxxxxxxxxxxxxxx
export EL_API_KEY=aebba4cdc1001xxxxxxxxxxxxxxxxxxxxx
export GROQ_API_KEY=gsk_caXklhYxxxxxxxxxxxxxxxxxxxxxx

5. WebSocket Code​

Here is the code to create and run the WebSocket server:

import asyncio
import websockets
from piopiy import StreamAction
from asr.deepgram import stream_audio
#from tts.deepgram import set_wss
from tts.elevenlabs import set_wss

global wss
async def handle_client(websocket, path):
    print("Client connected")
    print(f"conn-{id(websocket)}")
    set_wss(websocket)
    try:
        async for message in websocket:
            if isinstance(message, bytes):
                a =10
                # print(f"Received binary message of {len(message)} bytes")
                # await websocket.send(message)  # Echoing the binary message back
                stream_audio(message)
            else:
                print("Received non-binary message:", message)
              
    except websockets.exceptions.ConnectionClosed as e:
        print(f"Connection closed: {e.code} - {e.reason}")
    finally:
        print("Client disconnected")
     


def send_tts_audio(audio_stream_base64):
    # Send the audio stream to the WebSocket
    print(audio_stream_base64)
 


async def main():
    server = await websockets.serve(handle_client, "localhost", 8765)
    print("WebSocket server started at ws://localhost:8765")
    await server.wait_closed()

if __name__ == "__main__":
    asyncio.run(main())

6. Running the WebSocket code​

Run the server with the following command:

python websocket_server.py

7. Exposing the WebSocket Server using ngrok​

To expose your local WebSocket server to the internet, use ngrok to create a public TCP URL:

  1. Start ngrok on port 8080 with the following command:
ngrok tcp 8080
  1. Copy the ngrok TCP URL, which will look something like tcp://0.tcp.ngrok.io

8. Using the ngrok TCP URL​

Once you have the ngrok TCP URL, you can replace "WEBSOCKET_URL" in PIOPIY Code. For example:

ws://0.tcp.ngrok.io:xxxxx

9. Code​

from flask import Flask, request, jsonify
from piopiy import Action
app = Flask(__name__)
@app.route("/python/inbound", methods=["POST"])
def inbound_call():
    action = Action()
    action.stream("WEBSOCKET_URL",{ "listen_mode":"caller", "voice_quality": "8000", "stream_on_answer": True })
    action.call("AGENT_NUMBER", "PIOPIY_NUMBER",{ "duration": 300, "timeout": 20, "loop": 2 })
    return jsonify(action.PCMO())
if __name__ == "__main__":
    app.run(port=3001, debug=True)

10. Configure the call parameters​

Replace the value in the Basic Call code with your actual values for

11. Run the Code​

Execute the code using python:

python agent_assist.py

12. Create a public URL using ngrok​

To expose your local server to the internet, use ngrok to create a public URL:

ngrok http 3001

13. Configure Piopiy dashboard​

Log in to your Piopiy dashboard and paste the ngrok URL into the "Answer URL" input field. Ensure that the endpoint is set correctly to handle inbound calls.

https://customer.to.delivey.agent.ngrok.io/inbound

Copy the URL provided by ngrok. This URL will look something like https://customer.to.delivey.agent.ngrok.io.

capacity

14. Response​

Below is the following sample call response.

{
  "data": { "status": 'progress' },
  "status": 'progress',
  "request_id": 'X0uoi5LT5vCMOG6CZGEdMMYD5RL9raaEFa1p1IQ9EVm',
  "cmi_code": 200
}