from flask import Flask, jsonify, request
from flask_cors import CORS, cross_origin
from get_blocks import get_top_k_blocks
from chat import talk_to_robot
import dataclasses
import os
import openai
import pickle
import requests

if os.path.exists('.env'):
    from dotenv import load_dotenv
    load_dotenv()

app = Flask(__name__)
cors = CORS(app)
app.config['CORS_HEADERS'] = 'Content-Type'


# -------------------------------- general setup -------------------------------



OPENAI_API_KEY = os.environ.get('OPENAI_API_KEY')
openai.api_key = OPENAI_API_KEY

print('Downloading dataset...')

url = os.environ.get('DATASET_URL')
if url is None:
    print('No dataset url provided.')
    exit()

dataset_dict_bytes = requests.get(url).content
print('Unpacking dataset...')
dataset_dict = pickle.loads(dataset_dict_bytes)
print('Done!')



# ------------------------------- semantic search ------------------------------


@app.route('/semantic', methods=['POST'])
@cross_origin()
def semantic():
    query = request.json['query']
    return jsonify([dataclasses.asdict(block) for block in get_top_k_blocks(dataset_dict, query)])


# ------------------------------------ chat ------------------------------------


@app.route('/chat', methods=['POST'])
@cross_origin()
def chat():
    query = request.json['query']
    response, context = talk_to_robot(dataset_dict, query)
    return jsonify({'response': response, 'citations': [{'title': block.title, 'author': block.author, 'date': block.date, 'url': block.url} for block in context]})

# ------------------------------------------------------------------------------

if __name__ == '__main__': app.run(debug=True, port=3000)