openai-files-api

OpenAI-driven File Manager and Summarizer

This is a simple API to upload files into and interact with files from OpenAI's GPT engine. The API is built using Flask and uses the OpenAI Python library to interact with the OpenAI API.

Most of the tasks are automated via Taskfile used by Task - a task runner / build tool that aims to be simpler and easier to use than, for example, GNU Make.

Installation

1. Clone the repository using git clone or download the repository as a zip file and extract it
2. Install support for the Taskfile, details can be found here
3. Install the required packages using pip install -r requirements.txt or run task install
4. Modify environment variables in the Taskfile.yaml file

• OPENAI_API_KEY - Your OpenAI API key
• AUTH_TOKEN - The token to be used for authentication

Configuration

The configuration file is located at config.yaml and contains the following options:

server:
  bind: 0.0.0.0
  port: 5000
  uploads: .uploads

cors:
  origins: "*"
  methods: [ "GET", "POST", "DELETE" ]
  allow_headers: [ "Content-Type", "Authorization" ]

openai:
  model: gpt-4-turbo-preview

• server - The server configuration section
  • bind - The IP address to bind the server to
  • port - The port to bind the server to
  • uploads - The directory to store the uploaded files
• cors - The CORS configuration section, used to configure the CORS policy for the server
  • origins - The allowed origins
  • methods - The allowed methods
  • allow_headers - The allowed headers
• openai - The OpenAI configuration section
  • model - The model to use for the OpenAI API

You can also override bind and port using environment variables BIND and PORT respectively. Environment variables have higher priority than the configuration file.

Usage

To start the server, run task start. The server will start on the IP address and port specified in the configuration.

To stop the server, press Ctrl+C in the terminal.

Generating Systemd Service File

To generate a systemd service file, run task generate-unit-file. The service file will be generated in the current directory. The name of the service file will be openai-files-api.service and can be overridden using the DEPLOYMENT_SERVICE_NAME variable in Taskfile.yaml.

Deploying the Server

To deploy the server, run task deploy-to-remote. This will generate a systemd service file and copy it to the /etc/systemd/system on remote machine. The service will be enabled and started. During deployment Task will copy the config.yaml, code and Taskfile.yaml to the remote machine.

To deploy to the remote machine, you need to modify the DEPLOYMENT_ENDPOINT and DEPLOYMENT_USERNAME variables in the Taskfile.yaml file.

You can also build a Docker image using task docker-build. You can override the image name using the DOCKER_TAG variable.

API Endpoints

The API has the following endpoints:

• GET /api - The root endpoint, returns a welcome message in JSON format
• POST /api/files - Upload a file to the server
• GET /api/files - List all the files on the server
• GET /api/files/<file_id> - Get the details of a file
• GET /api/files/<file_id>/summarize - Summarize the file using the OpenAI API
• DELETE /api/files/<file_id> - Delete the file from the server

For the supported file types and the request and response formats, please refer to the OpenAPI documentation at https://platform.openai.com/docs/assistants/tools/supported-files.

Summarizing a File

To summarize a file, you can use the GET /api/files/<file_id>/summarize endpoint. This endpoint is used to retrieve a summary of the text content from a specified file identified by its unique file_id.

Request

• Method: POST
• URL: /api/files/<file_id>/summarize

Request Body

The request body should be a JSON object with the following optional fields:

1. user_input (string, default: "Summarize the text from the given file"):

   • Specifies the user input for the summarization process. If not provided, a default message will be used.

2. instructions (string, default: "You are a helpful assistant."):

   • Provides instructions for the summarization task. If not provided, a default message will be used.

3. model (string, default: "gpt-4-0125-preview"):

   • Specifies the model to be used for summarization. If not provided, the default model specified in the server configuration will be used.

Response

• Success: Returns a summary of the text content from the specified file.
• Error: Returns an error message if an unexpected error occurs during the summarization process.

Example Request

{
  "user_input": "Please summarize the main points of the document.",
  "instructions": "Focus on key ideas and provide a concise summary.",
  "model": "gpt-4-0125-preview"
}