ai24support-openai-assistants-api

This is a proof-of-concept (POC) of a customer support automation service built using OpenAI Assistants API.

Setup Local Development Steps

• Install Dependencies
• Configuration
• Run the App
• Call the Completion API

Install Dependencies

npm ci

Configuration

1. Create an OpenAI assistant by running the following script (assuming that your are in the root of the project). Please add your OPENAI_API_KEY (get it at https://platform.openai.com/api-keys)

node scripts/createOpenAiAssistant.js

After this expect to see a new assistant in your OpenAI Assistants dashboard. In consode or in the dashboard copy the assistant ID (e.g. asst_vh5EBWjfrcj0imtwocWe8lIY).

2. Copy the contents of .env.example file to .env file and update the variables:

• CUSTOMER_CONFIGS is an array of objects like { "x-customer-id": "test-customer", "x-api-key": "secret", "OPENAI_API_KEY": "secret", "OPENAI_ORG": "secret", "OPENAI_ASSISTANT_ID": "secret" }:
  • x-customer-id is a random UUID which you need to generate once and which will serve as the ID of your customer. This value must be sent as the header key x-customer-id in the requests to [POST] /api/v1/assistant/complete endpoint
  • x-api-key - some password to protect the endpoint for this customer (header x-api-key)
  • OPENAI_API_KEY and OPENAI_ORG - please find those at https://platform.openai.com/api-keys
  • OPENAI_ASSISTANT_ID - the ID of your OpenAI assistant (see step 1 above)
• POSTGRESQL_CONNECTION_STRING - a string to connect to your Postgresql DB, e.g. postgres://postgres.bwghlfwqsbwaxnafsysc:YourPassword@aws-0-us-west-1.pooler.supabase.com:6543/postgres (example from https://supabase.com/).

Note that several customers can be added to CUSTOMER_CONFIGS, each with their own OpenAI credentials and assistant.

Run the App

npm run start:local

Call the Completion API

curl --location 'localhost:3000/api/v1/assistant/complete' \
--header 'x-api-key: secret' \
--header 'x-customer-id: 74a2aeb0-6963-4eb2-b458-e62877fcc152' \
--header 'Content-Type: application/json' \
--data '{
    "userId": "44e2ef2c-89a3-4428-9373-2d18d2e2113f",
    "query": "Is it possible to return something I bought on clearance in the store?""
}'

Notes:

• x-customer-id and x-api-key must coincide with the values stored in .env
• userId must be a UUID. Each user gets their own thread with the bot, in which all the messages are processed (so consider the possible effect of the previous conversation turns on the current question). Pass a new userId to start conversation from scratch.

Please also see https://github.com/IuriiD/ai24support-openai-pinecone-rag for comparison how the same task can be solved using "custom" retrieval augmented generation (RAG) setup (OpenAI Embeddings and Chat Completion API + Pinecone vector DB).