liboai VS apisix-docker

Imagine you have an AI-powered personal alerting chat assistant that interacts using up-to-date data. Whether it's a big move in the stock market that affects your investments, any significant change on your shared SharePoint documents, or discounts on Amazon you were waiting for, the application is designed to keep you informed and alert you about any significant changes based on the criteria you set in advance using your natural language. In this post, we will learn how to build a full-stack event-driven weather alert chat application in Python using pretty cool tools: Streamlit, NATS, and OpenAI. The app can collect real-time weather information, understand your criteria for alerts using AI, and deliver these alerts to the user interface.

1.OpenAI API

OpenAI Account – make an OpenAI Account here

Their big advantage is that they can quickly deal with data they’ve never seen before and scale. NVIDIA and Open AI are currently leading providers of such technologies. Read more.

You need an API key https://openai.com/api

To run ChatGPT, you need access to OpenAI’s API3, which provides a cloud-based platform for interacting with various models, including ChatGPT. You can sign up for an account and request access to the API here: https://openai.com/api/

To get started, go to OpenAI and create an account. After that, click on your profile on the top right corner, and select view API keys.

As far as I know the ChatGPT API isn’t public yet. However you can use the GPT3 version from OpenAI which do have an API you can connect to. The Davinci-003 text model is pretty damn good. https://openai.com/api/ for more info

GPT-3: GPT-3 is an advanced language generation model developed by OpenAI. It is capable of generating high-quality human-like text with a high degree of coherence and coherence. The model has been trained on a vast corpus of text, making it capable of generating text across a range of topics. GPT-3 can be used for a variety of content creation tasks such as blog posts, articles, and social media updates. One of the most significant advantages of using GPT-3 is that it can save a significant amount of time when creating content. The model can generate text much faster than a human writer, and the output can be used as a starting point for further refinement.

This project leverages existing the pre-defined Docker Compose configuration file to set up, deploy, and run APISIX, etcd, Prometheus, and other services with a single command. First, clone the apisix-docker repo on GitHub, open it in your favorite editor, navigate to the example folder, and start the project by simply running docker compose up command in a terminal from the project root folder.

We will leverage the existing file-proxy demo project on GitHub. It has a quite similar structure to the existing Apisix docker example repo, only we removed unnecessary files to keep the demo simple. The project has 3 folders, docker-compose.yml, and sample openapi.yaml files.

git clone https://github.com/apache/apisix-docker.git

This first thing you clone the apisix-docker project repo from GitHub:

Apache APISIX Apache APISIX is an open source, dynamic, real-time, high-performance cloud native API gateway. APISIX provides rich traffic management features such as load balancing, dynamic upstream, canary release, circuit breaking, authentication, observability, and more. Official website https://apisix.apache.org/ GitHub projects APISIX (the core): https://github.com/apache/apisix GitHub - apache/apisix: The Cloud-Native API Gateway GitHub - apache/apisix-dashboard: Dashboard for Apache APISIX GitHub - apache/apisix-website: Apache APISIX Website GitHub - apache/apisix-docker: the docker for Apache APISIX GitHub - apache/apisix-go-plugin-runner: Go Plugin Runner for APISIX GitHub - apache/apisix-java-plugin-runner: APISIX Plugin Runner in Java GitHub - apache/apisix-python-plugin-runner: Apache APISIX Python plugin runner GitHub - apache/apisix-helm-chart: Apache APISIX Helm Chart GitHub - apache/apisix-ingress-controller: ingress controller for K8s

We made use of Apache APISIX docker compose repo where we deployed several components in one run and we demonstrated how the API Gateway can be used to manage sample ASP.NET Core application to retrieve product data using Product microservice's API. Also, you learned how to enable limit-count plugin for the API endpoint. There are many other built-in plugins available in Apache APISIX, you can check them on Plugin Hub page. Basically, APISIX can be a lightweight middleware API Gateway regardless of which programming language, frameworks, tools, or platforms you are developing a microservice or application.

In this demo, we are using Apache APISIX Docker repo and it contains an example docker-compose.yaml file and with other config files that makes straightforward to start APISIX using docker compose. We try out this example:

APISIX uses etcd to save and synchronize configuration. Before installing APISIX, you need to install etcd on your machine. It would be installed automatically if you choose the Apache APISIX Docker compose mode, you will learn more about on the next blog post Use Docker Compose to deploy containerized APISIX to AWS ECS.

The apisix-security-java-spring project makes use of the similar example APISIX docker compose template.

✔️ Create an Azure resource group. ✔️ Configure Azure Container Instances. ✔️ Create a Azure context for Docker to offload Apisix and etcd containers execution to ACI. ✔️ Get Apache APISIX example source code for Docker from GitHub. ✔️ Modify Docker compose file there. ✔️ Setup volumes in Azure Storage Account with Azure File Share. ✔️ Add APISIX config files to Azure File Share. ✔️ Bring up APISIX in Azure Container Instances. ✔️ Verify APISIX running. ✔️ Cleanup after you finish.