from flask import Flask, request
import numpy as np
from .salience import extract, AVAILABLE_MODELS
import json

app = Flask(__name__)

with open('./transcript.txt', 'r') as file:
    source_text = file.read().strip()

@app.route("/models")
def models_view():
    return json.dumps(list(AVAILABLE_MODELS.keys()))

@app.route("/salience")
def salience_view():
    model_name = request.args.get('model', 'all-mpnet-base-v2')

    # Validate model name
    if model_name not in AVAILABLE_MODELS:
        return json.dumps({'error': f'Invalid model: {model_name}'}), 400

    sentence_ranges, adjacency = extract(source_text, model_name)

    return json.dumps({
        'source': source_text,
        'intervals': sentence_ranges,
        'adjacency': np.nan_to_num(adjacency.numpy()).tolist(),
        'model': model_name,
    })