Sqweya AI Python Backend

Welcome to the Python backend repository for Sqweya AI. This demo showcases how we plan to integrate our Large Language Model (LLM) with Retell, an AI Conversational API platform.

This repository currently uses the OpenAI endpoint and will soon switch to the Azure OpenAI endpoint. Contributions are welcome to improve the stability and performance of this demo.

Steps to Run Locally

1. Install dependencies:

pip3 install -r requirements.txt

2. Fill out the API keys in .env.

3. Use ngrok to expose the port to the public network:

ngrok http 8080

4. Start the websocket server:

uvicorn server:app --reload --port=8080

You will receive a forwarding address like https://dc14-2601-645-c57f-8670-9986-5662-2c9a-adbd.ngrok-free.app. Take the IP address, prepend it with wss, append with /llm-websocket path, and use it in the Retell dashboard to create a new agent. The agent you create should connect with your localhost.

The custom LLM URL would look like wss://dc14-2601-645-c57f-8670-9986-5662-2c9a-adbd.ngrok-free.app/llm-websocket.

Future implementations: Place and Receive Phone Calls via Twilio

The twilio_server.py contains helper functions to utilize Twilio features for phone calls. Follow these steps:

1. Uncomment Twilio client initialization and listen_twilio_voice_webhook(agent_id_path) in server.py to set up Twilio voice webhook.

2. Put your ngrok IP address into .env (e.g., https://dc14-2601-645-c57f-8670-9986-5662-2c9a-adbd.ngrok-free.app).

3. (optional) Call create_phone_number to get a new number and associate it with an agent ID.

4. (optional) Call register_phone_agent to register your Twilio number and associate it with an agent ID.

5. (optional) Call delete_phone_number to release a number from your Twilio pool.

6. (optional) Call transfer_call to transfer an ongoing call to a destination number.

7. (optional) Call end_call to end an ongoing call.

8. Call create_phone_call to start a call with caller & callee number and your agent ID.

Running in Production

To run in production, plug into Microsoft Azure OpenAI service(to provide the LLM service), fetch changes from this repo and then push your code to Github. Then deploy the code in a cloud environment(Azure or GCP), and use that IP to create an agent in the Retell dashboard.