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https://github.com/thomassuedbroecker/simple-openai-fastapi-server

This code example is a FastAPI server that contains multiple API endpoints for interacting with an OpenAI model.
https://github.com/thomassuedbroecker/simple-openai-fastapi-server

bash curl fastapi openai python

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This code example is a FastAPI server that contains multiple API endpoints for interacting with an OpenAI model.

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# Simple OpenAI FastAPI server



This code example is a [`FastAPI`](https://fastapi.tiangolo.com/) server that contains multiple API endpoints for interacting with an [`OpenAI`](https://openai.com/) model. 



* [Related blog post](https://suedbroecker.net/2023/11/23/how-to-create-a-fastapi-server-to-use-openai-models/)



## The objective is to provide three main endpoints



* One endpoint is to send a simple text to Open AI and return the result.

* One endpoint to send a preconfigured prompt to Open AI. The preconfigured prompt contains a context and a question as parameters. These parameters will be replaced by the provided values of the endpoint invocation and sent to Open AI. The response will be provided as the return value of the endpoint.

* One endpoint is to upload a file and question as parameters for Open AI.

 

## Overview



* It uses [`HTTPBasic authentication`](https://en.wikipedia.org/wiki/Basic_access_authentication) for security. 

* It defines endpoints for `health status`, fetching simple text from [`OpenAI`](https://openai.com/), fetching text with a prompt from `OpenAI`, and uploading a file as context for the question to get a response from `OpenAI`. 

The code also includes `OpenAPI` configuration for the `Swagger UI`. 

* It uses custom modules for environment variables, response and payload definition, and AI access. 

* Finally, it runs the FastAPI application using [`uvicorn`](https://www.uvicorn.org/) on localhost port 8080.



_Clone the project to your local computer:_



```sh

git clone https://github.com/thomassuedbroecker/simple-openai-server-fastapi.git

```



![](/images/2023-11-22_fastapi-01.gif)



_Note:_ 



  * You can find additional information, on how to create a pipeline in the related project: “How to use and set up `Watsonx.ai` in the simple pipeline project”: https://github.com/thomassuedbroecker/simple-qa-pipeline. We reuse code and concepts from that pipeline project.

  * You can also use the Online editor (github.**dev**) to edit files: `https://github.dev/thomassuedbroecker/simple-openai-server-fastapi`.



_Content_



* [1. Setup of the Windows Machine](#1-setup-windows-machine)

* [2. Setup of the Python environment](#2-setup-the-python-environment)

* [3. Configure and start the `simple-openai-server` FastAPI server](#3-configure-and-start-the-simple-openai-server-fastapi-server)

* [4. Get your own OpenAI access](#4-get-your-own-openai-access)



## 1. Setup of the Windows Machine



### 1.1 Install Python



Please follow the link for the installation [Download Python for Windows](https://www.python.org/downloads/windows/).

_Note:_ Additional resources, how to [Set virtual environment for Python](https://suedbroecker.net/2023/05/23/set-a-virtual-environment-for-python/).



### 1.2 Install virtual environment



Follow the steps in [set up a virtual environment for Python](https://suedbroecker.net/2023/05/23/set-a-virtual-environment-for-python/)



_Note:_ To add the `path variable` please open in your Windows search bar `Edit environment variables for your account`.

 

### 1.3 Ensure you can use PowerShell on Windows



Please follow the link for the installation oder verification [Learn Microsoft Powershell](https://learn.microsoft.com/en-us/powershell/scripting/windows-powershell/starting-windows-powershell?view=powershell-7.3)



### 1.4 Install VSCode



Please follow the link for the installation of [`VSCode`](https://code.visualstudio.com/)



### 1.5 Install GitBash



Please follow the link for the installation of [`How to install GitBash`](https://www.educative.io/answers/how-to-install-git-bash-in-windows)



## 2. Setup of the Python environment



### 2.1 Create a virtual Python environment



* Windows with GitBash terminal.



```sh

cd code

python3.10 -m venv env3.10

source ./env3.10/Scripts/activate

```



* Mac and Linux terminal.



```sh

cd code

python3.10 -m venv env3.10

source ./env3.10/bin/activate

```



### 2.2. Install the needed Python libraries 



```sh

# Linux

#source ./env3.10/bin/activate 

# Windows

source ./env3.10/Scripts/activate 

python3 -m pip install --upgrade pip

python3 -m pip install "fastapi[all]"

python3 -m pip install requests

python3 -m pip install pydantic

python3 -m pip install openai

python3 -m pip install typing

python3 -m pip install beautifulsoup4

python3 -m pip install --upgrade openai

python3 -m pip freeze > requirements.txt 

```



## 3. Configure and start the `simple-openai-server` FastAPI server



### 3.1 Create the environment file



* Set a new user and password.



```sh

cat .env_template > .env

```

* Content



```sh

# APP

export APP_USER=admin

export APP_APIKEY=admin



# OpenAI

export OPENAI_KEY=YOUR_KEY

export OPENAI_MODEL=gpt-3.5-turbo-1106

export PROMPT="Document:\n\n<>\n\nQuestion:\n\n<>\n\nAnswer:\n\n"

```



### 3.2 Start the `simple-openai-server` FastAPI server



* Windows 



```sh

cd code

source ./env3.10/Scripts/activate 

source .env

python3 simple-openai-server.py

```



* Linux



```sh

cd code

source ./env3.10/bin/activate 

source .env

python3 simple-openai-server.py

```



### 3.3 Open a browser and enter the following URL



```sh

http://localhost:8080/docs

```



### 3.4 Invoke FastAPI server endpoints by using the curl commands



* Access FastAPIserver `/`



```sh

export URL=http://localhost:8080

curl -X GET \

  "${URL}/" \

  -H "Content-Type: application/json" 

```



* Using REST GET to invoke the `health` endpoint



```sh

export URL=http://localhost:8080

export USER=admin

export PASSWORD=thomas

export REST_API_PATH=health

curl -u ${USER}:${PASSWORD} -X GET "${URL}/${REST_API_PATH}"

```



* Using REST POST to invoke the `get_openai_text_with_prompt` endpoint.



```sh

export URL=http://localhost:8080

export USER=admin

export PASSWORD=thomas

export CONTEXT="My name is Thomas."

export QUESTION="What is my name?"

export REST_API_PATH=get_openai_text_with_prompt



curl -u ${USER}:${PASSWORD} -X POST "${URL}/${REST_API_PATH}/" -H "Content-Type: application/json" -d "{\"context\":\"${CONTEXT}\",\"question\":\"${QUESTION}\"}"

```



## 4. Get your own OpenAI access



### 4.1 Register your account



_Note:_ Keep in mind `OpenAI` has a kind of prepaid model.



* [OpenAI](https://openai.com/blog/openai-api)

* [OpenAI Pricing](https://openai.com/pricing)



## 5. Additional notes



* [Files](https://fastapi.tiangolo.com/tutorial/request-files/)