FastAPI Concept Identification API

This FastAPI application provides an API endpoint to identify unknown concepts in a given text, based on a list of known concepts. It integrates with the OpenAI API to analyze text and generate responses. A development mode is also available, which returns a static response for testing purposes.

Features

• Identify Unknown Concepts: Extract unknown concepts from text by comparing them against a list of known concepts.
• Match Concepts to Ontologies: Extract unknown concepts from text by comparing them against a list of known concepts.
• Create Definitions for Concepts: Extract unknown concepts from text by comparing them against a list of known concepts.
• Create Synonyms for Concepts: Extract unknown concepts from text by comparing them against a list of known concepts.
• Full Unknown Concepts Pipeline: Extract unknown concepts from text by comparing them against a list of known concepts. Provide synonyms, definitions, and fitting ontologies for all of them.
• Development Mode: Easily test the API with a static response by enabling development mode via a query parameter.

Installation

1. Clone the repository:

   git clone https://github.com/biodivportal/unknown_concepts_api.git
   cd unknown_concepts_api
   

2. Install the dependencies:

   pip install -r requirements.txt
   

3. Set up the OpenAI API key:

   Ensure you have a credentials_private.json file in the root directory with your OpenAI API key:

   {
     "api_key": "your_openai_api_key"
   }
   

Usage: Running the Application

Start the FastAPI application using Uvicorn:

uvicorn main:app --reload

API Endpoint

• URL: /identify_unknown_concepts/
• Method: POST
• Request Body: JSON object containing:
  • text (string): The input text to analyze.
  • known_concepts (list of strings): A list of known concepts to exclude.
• Query Parameter: dev_mode (boolean, optional): Set to true to enable development mode, which returns a static response.

Example Request

Here is an example of how to make a request to the API:

curl -X POST "http://127.0.0.1:8001/identify_unknown_concepts/?dev_mode=true" \
-H "Content-Type: application/json" \
-d '{
  "text": "There is for example genetic variability, species diversity, ecosystem diversity and phylogenetic diversity. Diversity is not distributed evenly on Earth.",
  "known_concepts": ["concept1", "concept2"]
}'

Development Mode

Enable development mode by setting the dev_mode query parameter to true. In this mode, the API returns a static response for testing purposes:

{
  "unknownConcepts": [
    {
      "originalLabel": "staticConcept",
      "synonym": "staticSynonym",
      "links": {
        "ontology": "staticOntologyLink"
      },
      "id": "1234",
      "suggested_description": "This is a static description for development mode."
    }
  ]
}

Example Request

Here is an example of how to make a request to the API:

curl -X POST "http://127.0.0.1:8001/identify_unknown_concepts/?dev_mode=true" \
-H "Content-Type: application/json" \
-d '{
  "text": "This is an example text.",
  "known_concepts": ["concept1", "concept2"]
}'

Docker Usage

You can also run this FastAPI application inside a Docker container.

Building the Docker Image

1. Make sure you have Docker installed on your machine.

2. Build the Docker image using the following command:

   docker build -t fastapi-app .

Running the Docker Container

   docker run -p 8001:8001 fastapi-app

This command starts the Docker container and maps port 8001 of the container to port 8000 on your local machine. You can then access the FastAPI application at http://localhost:8001.