Openai twilio protgresql help pls

[avielmizele29]

Hello,

I’m working on an integration between Twilio and OpenAI’s Realtime API, and I need some help with a specific requirement. Instead of hardcoding the system message (SM) in the script, I want to dynamically retrieve it from a PostgreSQL database based on the caller’s number.

Here’s what I want to achieve:

1. A central webhook script is deployed on all my Twilio numbers.
2. When an inbound call is received, the script extracts the caller’s number.
3. Using this number, the script queries our PostgreSQL database to fetch the associated system message.
4. The retrieved system message (formatted as a JSON object with at least "role": "system" and "content": "...") is then sent to OpenAI’s Realtime API to initialize the session.
5. After that, the dialogue continues normally until the call ends.

Could you please provide guidance or a solution to implement this approach? Let me know if you need any further details.

Thank you very much! @jochenschultz

[jochenschultz]

Welcome to the community.

Of course I can provide a solution for that. For business inquiries you can send me a mail - an agent will send you a mail with a price - after the checkout process another agent will send you a link to a form that will ask for details where another agent creates the solution and deploys it - it may ask for more details for that)

[avielmizele29]

what is your email and how many time

[jochenschultz]

Please take a moment and imagine what the world would be like if that workflow would exist

anyways here is a response from chatgpt that might help you out:

Twilio & OpenAI Realtime API Integration with PostgreSQL (Node.js)

1. Set Up Your Environment

• Node.js: Ensure you have Node.js (version 18 or later) installed.
• Twilio Account: Sign up for a Twilio account and obtain your Account SID and Auth Token.
• Twilio Phone Number: Purchase a Twilio phone number with voice capabilities.
• OpenAI Account: Sign up for an OpenAI account and obtain an API key with Realtime API access.
• PostgreSQL Database: Set up a PostgreSQL database containing a table that maps caller numbers to system messages.
• ngrok: Install ngrok to expose your local server to the internet for testing purposes.

2. Initialize the Project

Create a new directory for your project and initialize it:

mkdir twilio-openai-integration
cd twilio-openai-integration
npm init -y
npm pkg set type="module"

3. Install Required Dependencies

npm install express pg twilio axios dotenv body-parser

• express: Web framework for handling HTTP requests.
• pg: PostgreSQL client for Node.js.
• twilio: Twilio helper library for Node.js.
• axios: Promise-based HTTP client for making API requests.
• dotenv: Module to load environment variables from a .env file.
• body-parser: Middleware to parse incoming request bodies.

4. Configure Environment Variables

Create a .env file in the root of your project and add the following variables:

TWILIO_ACCOUNT_SID=your_twilio_account_sid
TWILIO_AUTH_TOKEN=your_twilio_auth_token
TWILIO_PHONE_NUMBER=your_twilio_phone_number
OPENAI_API_KEY=your_openai_api_key
DB_HOST=your_db_host
DB_PORT=your_db_port
DB_USER=your_db_user
DB_PASSWORD=your_db_password
DB_NAME=your_db_name

5. Set Up the PostgreSQL Database

Ensure your PostgreSQL database has a table named caller_config with the following structure:

CREATE TABLE caller_config (
    caller_number VARCHAR(15) PRIMARY KEY,
    system_message JSONB
);

Insert sample data into the table:

INSERT INTO caller_config (caller_number, system_message) VALUES
('+1234567890', '{"role": "system", "content": "Welcome, valued customer."}'),
('+1987654321', '{"role": "system", "content": "Hello! How can I assist you today?"}');

6. Develop the Application

Create an index.js file and add the following code:

import express from 'express';
import bodyParser from 'body-parser';
import { Client } from 'pg';
import axios from 'axios';
import dotenv from 'dotenv';

dotenv.config();

const app = express();
app.use(bodyParser.urlencoded({ extended: false }));
app.use(bodyParser.json());

const dbClient = new Client({
    host: process.env.DB_HOST,
    port: process.env.DB_PORT,
    user: process.env.DB_USER,
    password: process.env.DB_PASSWORD,
    database: process.env.DB_NAME,
});

dbClient.connect();

app.post('/webhook', async (req, res) => {
    const callerNumber = req.body.From;
    if (!callerNumber) {
        return res.status(400).send('Caller number is missing.');
    }

    try {
        const query = 'SELECT system_message FROM caller_config WHERE caller_number = $1';
        const result = await dbClient.query(query, [callerNumber]);

        let systemMessage;
        if (result.rows.length > 0) {
            systemMessage = result.rows[0].system_message;
        } else {
            systemMessage = { role: 'system', content: 'Default system message.' };
        }

        const openaiResponse = await axios.post(
            'https://api.openai.com/v1/realtime/session',
            {
                messages: [systemMessage],
            },
            {
                headers: {
                    'Content-Type': 'application/json',
                    Authorization: `Bearer ${process.env.OPENAI_API_KEY}`,
                },
            }
        );

        // Handle the OpenAI response as needed

        res.status(200).send('Call processing initiated.');
    } catch (error) {
        console.error('Error:', error);
        res.status(500).send('Internal Server Error');
    }
});

const PORT = process.env.PORT || 3000;
app.listen(PORT, () => {
    console.log(`Server is running on port ${PORT}`);
});

7. Expose the Server Using ngrok

Start your server:

node index.js

In a separate terminal, start ngrok to expose your local server:

ngrok http 3000

Note the HTTPS URL provided by ngrok (e.g., https://abcd1234.ngrok.io).

8. Configure Twilio Webhook

In the Twilio Console, navigate to your phone number settings and set the “A CALL COMES IN” webhook to your ngrok URL followed by /webhook (e.g., https://abcd1234.ngrok.io/webhook).

9. Test the Integration

Make a call to your Twilio phone number from a number listed in your caller_config table. The application will:

1. Receive the incoming call via the /webhook endpoint.
2. Extract the caller’s number.
3. Query the PostgreSQL database for the corresponding system message.
4. Initialize a session with OpenAI’s Realtime API using the retrieved system message.
5. Continue handling the call as needed.

---

[avielmizele29]

I’m coding in Python—what should I do? Also, I understand that we shouldn’t format the audio inputs for OpenAI. Could you please confirm this? i want to use the code of twilio and openai just to get the system message from protgresql chatgpt code bad

[jochenschultz]

Take this complete text:

# Twilio & OpenAI Realtime API Integration with PostgreSQL (Node.js)

## 1. Set Up Your Environment

- **Node.js**: Ensure you have Node.js (version 18 or later) installed.
- **Twilio Account**: Sign up for a [Twilio account](https://www.twilio.com/try-twilio) and obtain your Account SID and Auth Token.
- **Twilio Phone Number**: Purchase a Twilio phone number with voice capabilities.
- **OpenAI Account**: Sign up for an [OpenAI account](https://platform.openai.com/signup) and obtain an API key with Realtime API access.
- **PostgreSQL Database**: Set up a PostgreSQL database containing a table that maps caller numbers to system messages.
- **ngrok**: Install [ngrok](https://ngrok.com/) to expose your local server to the internet for testing purposes.

## 2. Initialize the Project

Create a new directory for your project and initialize it:

~~~bash
mkdir twilio-openai-integration
cd twilio-openai-integration
npm init -y
npm pkg set type="module"
~~~

## 3. Install Required Dependencies

~~~bash
npm install express pg twilio axios dotenv body-parser
~~~

- `express`: Web framework for handling HTTP requests.
- `pg`: PostgreSQL client for Node.js.
- `twilio`: Twilio helper library for Node.js.
- `axios`: Promise-based HTTP client for making API requests.
- `dotenv`: Module to load environment variables from a `.env` file.
- `body-parser`: Middleware to parse incoming request bodies.

## 4. Configure Environment Variables

Create a `.env` file in the root of your project and add the following variables:

~~~plaintext
TWILIO_ACCOUNT_SID=your_twilio_account_sid
TWILIO_AUTH_TOKEN=your_twilio_auth_token
TWILIO_PHONE_NUMBER=your_twilio_phone_number
OPENAI_API_KEY=your_openai_api_key
DB_HOST=your_db_host
DB_PORT=your_db_port
DB_USER=your_db_user
DB_PASSWORD=your_db_password
DB_NAME=your_db_name
~~~

## 5. Set Up the PostgreSQL Database

Ensure your PostgreSQL database has a table named `caller_config` with the following structure:

~~~sql
CREATE TABLE caller_config (
    caller_number VARCHAR(15) PRIMARY KEY,
    system_message JSONB
);
~~~

Insert sample data into the table:

~~~sql
INSERT INTO caller_config (caller_number, system_message) VALUES
('+1234567890', '{"role": "system", "content": "Welcome, valued customer."}'),
('+1987654321', '{"role": "system", "content": "Hello! How can I assist you today?"}');
~~~

## 6. Develop the Application

Create an `index.js` file and add the following code:

~~~javascript
import express from 'express';
import bodyParser from 'body-parser';
import { Client } from 'pg';
import axios from 'axios';
import dotenv from 'dotenv';

dotenv.config();

const app = express();
app.use(bodyParser.urlencoded({ extended: false }));
app.use(bodyParser.json());

const dbClient = new Client({
    host: process.env.DB_HOST,
    port: process.env.DB_PORT,
    user: process.env.DB_USER,
    password: process.env.DB_PASSWORD,
    database: process.env.DB_NAME,
});

dbClient.connect();

app.post('/webhook', async (req, res) => {
    const callerNumber = req.body.From;
    if (!callerNumber) {
        return res.status(400).send('Caller number is missing.');
    }

    try {
        const query = 'SELECT system_message FROM caller_config WHERE caller_number = $1';
        const result = await dbClient.query(query, [callerNumber]);

        let systemMessage;
        if (result.rows.length > 0) {
            systemMessage = result.rows[0].system_message;
        } else {
            systemMessage = { role: 'system', content: 'Default system message.' };
        }

        const openaiResponse = await axios.post(
            'https://api.openai.com/v1/realtime/session',
            {
                messages: [systemMessage],
            },
            {
                headers: {
                    'Content-Type': 'application/json',
                    Authorization: `Bearer ${process.env.OPENAI_API_KEY}`,
                },
            }
        );

        // Handle the OpenAI response as needed

        res.status(200).send('Call processing initiated.');
    } catch (error) {
        console.error('Error:', error);
        res.status(500).send('Internal Server Error');
    }
});

const PORT = process.env.PORT || 3000;
app.listen(PORT, () => {
    console.log(`Server is running on port ${PORT}`);
});
~~~

## 7. Expose the Server Using ngrok

Start your server:

~~~bash
node index.js
~~~

In a separate terminal, start ngrok to expose your local server:

~~~bash
ngrok http 3000
~~~

Note the HTTPS URL provided by ngrok (e.g., `https://abcd1234.ngrok.io`).

## 8. Configure Twilio Webhook

In the [Twilio Console](https://www.twilio.com/console), navigate to your phone number settings and set the "A CALL COMES IN" webhook to your ngrok URL followed by `/webhook` (e.g., `https://abcd1234.ngrok.io/webhook`).

## 9. Test the Integration

Make a call to your Twilio phone number from a number listed in your `caller_config` table. The application will:

1. Receive the incoming call via the `/webhook` endpoint.
2. Extract the caller's number.
3. Query the PostgreSQL database for the corresponding system message.
4. Initialize a session with OpenAI's Realtime API using the retrieved system message.
5. Continue handling the call as needed.

and ask chatgpt to translate that to python