# Copyright 2018 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

# [START gae_python37_render_template]
import datetime
from flask import g
import os
import googleapiclient.discovery
from utils import *
from google.cloud import storage
from google import cloud
import json
from flask import Flask, render_template, request, abort
from flask import Response
import requests
import pdb
import sys
import gpt2.src.encoder as encoder

# App Info
phrases = [" You attack", " You use", " You tell", " You go"]
prompts = [
    "You enter a dungeon with your trusty sword and shield. You are searching for the evil necromancer who killed your family. You've heard that he resides at the bottom of the dungeon, guarded by legions of the undead. You enter the first door and see"]
continuing_prompts = [
    "You are in a dungeon with your sword and shield. You are on a quest to defeat the necromancer. This dungeon is full of zombie and skeletons."]
app = Flask(__name__)

# Encoder Info
encoder_path = 'gpt2/models/117M'
enc = encoder.get_encoder(encoder_path)

# Model/Cache Info
project = "ai-adventure"
model = "generator_v1"
version = "version2"
os.environ['GOOGLE_APPLICATION_CREDENTIALS'] = "./AI-Adventure-2bb65e3a4e2f.json"
storage_client = storage.Client()
bucket = storage_client.get_bucket("dungeon-cache")


def predict(context_tokens):
    service = googleapiclient.discovery.build('ml', 'v1')
    name = 'projects/{}/models/{}'.format(project, model)
    instance = context_tokens

    if version is not None:
        name += '/versions/{}'.format(version)

    response = service.projects().predict(
        name=name,
        body={'instances': [{'context': instance}]}
    ).execute()

    if 'error' in response:
        raise RuntimeError(response['error'])

    return response['predictions']


def generate(prompt):
    while (True):
        context_tokens = enc.encode(prompt)
        try:
            pred = predict(context_tokens)
            pred = pred[0]["output"][len(context_tokens):]
            output = enc.decode(pred)
            return output
        except:
            print("generate request failed, trying again")
            continue


def generate_story_block(prompt):
    block = generate(prompt)
    block = cut_trailing_sentence(block)
    block = story_replace(block)

    return block


def generate_action_result(prompt, phrase):
    action = phrase + generate(prompt + phrase)
    action_result = cut_trailing_sentence(action)
    action_result = story_replace(action_result)

    action = first_sentence(action)

    return action, action_result


@app.route('/')
def root():
    seed = -1
    data = {'seed': seed}
    return render_template('index.html', data=data)


@app.route('/<seed>')
def rootseed(seed):
    if seed == "":
        seed = -1
    else:
        seed = int(seed)
    data = {'seed': seed}
    return render_template('index.html', data=data)


@app.route('/index.html')
def index():
    data = {'seed': -1}
    return render_template('index.html', data=data)


@app.route('/about.html')
def about():
    return render_template('about.html')


def cache_file(seed, prompt_num, choices, response, tag):
    blob_file_name = "prompt" + str(prompt_num) + "/seed" + str(seed) + "/" + tag
    for action in choices:
        blob_file_name = blob_file_name + str(action)
    blob = bucket.blob(blob_file_name)

    blob.upload_from_string(response)

    print("File ", blob_file_name, " cached")


def retrieve_from_cache(seed, prompt_num, choices, tag):
    blob_file_name = "prompt" + str(prompt_num) + "/seed" + str(seed) + "/" + tag

    for action in choices:
        blob_file_name = blob_file_name + str(action)

    blob = bucket.blob(blob_file_name)

    if blob.exists(storage_client):
        result = blob.download_as_string().decode("utf-8")
        print(blob_file_name, " found in cache")
    else:
        result = None
        print(blob_file_name, " not found in cache")

    return result


@app.route('/generate', methods=['POST'])
def story_request():
    print("****Generating Story****")
    seed = request.form["seed"]
    prompt_num = int(request.form["prompt_num"])
    gen_actions = request.form["actions"]

    if int(seed) < 0 or int(seed) > 100:
        print("Invalid seed: " + seed)
        abort(404)

    if gen_actions == "true":

        # prompt = request.form["prompt"]
        choices = json.loads(request.form["choices"])
        print("Getting response for seed ", seed, " prompt_num ", prompt_num, " and choices ", choices)

        action_results = retrieve_from_cache(seed, prompt_num, choices, "choices")

        if action_results is not None:
            response = action_results
        else:
            last_action_result = request.form["last_action_result"]
            prompt = continuing_prompts[prompt_num] + last_action_result
            print("\n\nAction prompt is \n ", prompt)
            action_results = [generate_action_result(prompt, phrase) for phrase in phrases]
            response = json.dumps(action_results)
            cache_file(seed, prompt_num, choices, response, "choices")
    else:

        print("Getting response for seed ", seed, " prompt_num ", prompt_num)
        result = retrieve_from_cache(seed, prompt_num, [], "story")

        if result is not None:
            response = result
        else:
            prompt = prompts[prompt_num]
            response = generate_story_block(prompt)
            cache_file(seed, prompt_num, [], response, "story")

    print("\nGenerated response is: \n", response)
    print("")

    return response


def generate_cache():
    start_seed = int(sys.argv[1])
    end_seed = int(sys.argv[2])

    # Generate story sections
    prompt_num = 0
    action_queue = []
    prompt = prompts[prompt_num]
    for seed in range(start_seed, end_seed):
        result = retrieve_from_cache(seed, prompt_num, [], "story")
        if result is not None:
            response = result
        else:
            prompt = prompts[prompt_num]
            # print("\n Story prompt is ", prompt)
            response = generate_story_block(prompt)
            # print("\n Story response is ", response)
            cache_file(seed, prompt_num, [], response, "story")

        action_queue.append([seed, 0, [], response])

    while (True):

        next_gen = action_queue.pop(0)
        seed = next_gen[0]
        prompt_num = next_gen[1]
        choices = next_gen[2]
        last_action_result = next_gen[3]

        action_results = retrieve_from_cache(seed, prompt_num, choices, "choices")

        if action_results is not None:
            response = action_results

        else:
            if len(choices) is 0:
                prompt = prompts[prompt_num] + last_action_result
            else:
                prompt = continuing_prompts[prompt_num] + last_action_result
            # print("\n\n Action prompt is \n ", prompt)
            action_results = [generate_action_result(prompt, phrase) for phrase in phrases]
            response = json.dumps(action_results)

            # print("\n\n Action
            cache_file(seed, prompt_num, choices, response, "choices")

        un_jsoned = json.loads(response)
        for j in range(4):
            new_choices = choices[:]
            new_choices.append(j)
            action_queue.append([seed, 0, new_choices, un_jsoned[j][1]])


if __name__ == '__main__':
    if (len(sys.argv) > 1):
        generate_cache()
    else:
        app.run(host='0.0.0.0', port=8080)

# [START gae_python37_render_template]