app.py

from flask import Flask, render_template, request, jsonify
import pandas as pd
from llm import load_astrollama_model, get_backstory_for_image
from main import search_object, load_data
from query import process_question


app = Flask(__name__)

windows_path = r"C:\Users\Anaki\OneDrive\Desktop\codingprojects\jwst\JWST-Project\Copy of Dataset - Sheet1 (1).csv"
wsl_path = '/mnt/c' + windows_path[2:].replace('\\', '/')

data = load_data(wsl_path)
tokenizer, model = load_astrollama_model


# Route for searching objects
@app.route('/')
def index():
    return render_template('index.html')

def search():
    object_name = request.json.get('object_name')
    constellation = request.json.get('Constellation')
    distance_range = request.json.get('object_name')
    
    results = search_object(data, object_name, constellation, distance_range)

    return jsonify(results.to_dict())

# Route for getting a backstory for an image
@app.route('/backstory', methods=['POST'])
def backstory():
    image_data = request.json  # Expecting image data (e.g., from frontend)
    backstory = get_backstory_for_image(image_data, tokenizer, model)
    return jsonify({"backstory": backstory})

# Route for processing NLP queries
@app.route('/query', methods=['POST'])
def query():
    question = request.json.get('question')
    result = process_question(question, data)
    return jsonify({"result": result})

if __name__ == '__main__':
    app.run(debug=True)