Address Parser API using spaCy and FastAPI

This project provides a simple API to parse raw Indian addresses into structured JSON objects. It uses pydantic-settings for configuration management and includes request logging.

Project Structure

.
├── address_parser_model/   <-- This is the spacy model
├── .env                    <-- Your environment configuration file
├── api.py                  <-- The FastAPI application
└── requirements.txt        <-- Python dependencies

Setup Instructions

1. Set up a Virtual Environment (Recommended)

# Create the virtual environment
python -m venv venv

# Activate it
# On Windows:
venv\Scripts\activate
# On macOS/Linux:
source venv/bin/activate

2. Install Dependencies

Install all the required libraries from your updated requirements.txt file.

pip install -r requirements.txt

How to Use

Step 1: Run the FastAPI Server

Start the API server using uvicorn.

uvicorn api:app --reload

When you run the server, you will now see log messages in your console, including the model loading status and details for each request you make.

Example Log Output:

INFO:     Uvicorn running on [http://127.0.0.1:8000](http://127.0.0.1:8000) (Press CTRL+C to quit)
INFO:     Started reloader process [28789] using StatReload
INFO:     Started server process [28791]
INFO:     Waiting for application startup.
2023-10-27 12:30:00,123 - INFO - Loading model from address_parser_model...
2023-10-27 12:30:01,456 - INFO - Model loaded successfully.
INFO:     Application startup complete.

Step 3: Test the API

Go to the interactive documentation at http://127.0.0.1:8000/docs to test the API. When you send a request, check your terminal to see the new log messages for that request.