Как я могу сделать пакеты Python, такие как tennflow, который служит чат-ботом с Flask для работы с Wamp Apache?

Question

Я пытаюсь развернуть мой флеш-чат на сервере Wamp с помощью mod_wsgi. Я могу запустить простое приложение фляги на Wamp. Но когда я пытаюсь запустить мой чат-бот с флягой AI, который использует пакеты Python, такие как tenorflow, numpy, tflearn и т. Д., Wamp не загрузит его. Я тестировал приложение фляги локально без каких-либо проблем. Но это не работает на Apache Wamp. Также он не может загрузить файл JSON.

Вот код колбы Chatbot

from flask import Flask, render_template, request
import nltk
from nltk.stem.lancaster import LancasterStemmer
stemmer = LancasterStemmer()

import numpy
import random
import tensorflow
import tflearn
import pickle

import json

app = Flask(__name__)

with open('intents.json') as file:
    data = json.load(file)

try:
    with open("data.pickle", "rb") as f:
        words, labels, training, output = pickle.load(f)
except:
    words = []
    labels = []
    docs_x = []
    docs_y = []

    for intent in data["intents"]:
        for pattern in intent["patterns"]:
            wrds = nltk.word_tokenize(pattern)
            words.extend(wrds)
            docs_x.append(wrds)
            docs_y.append(intent["tag"])

        if intent["tag"] not in labels:
            labels.append(intent["tag"])

    words = [stemmer.stem(w.lower()) for w in words if w != "?"]
    words = sorted(list(set(words)))

    labels = sorted(labels)

    training = []
    output = []

    out_empty = [0 for _ in range(len(labels))]

    for x, doc in enumerate(docs_x):
        bag = []

        wrds = [stemmer.stem(w.lower()) for w in doc]

        for w in words:
            if w in wrds:
                bag.append(1)
            else:
                bag.append(0)

        output_row = out_empty[:]
        output_row[labels.index(docs_y[x])] = 1

        training.append(bag)
        output.append(output_row)


    training = numpy.array(training)
    output = numpy.array(output)

    with open("data.pickle", "wb") as f:
        pickle.dump((words, labels, training, output), f)

tensorflow.reset_default_graph()

net = tflearn.input_data(shape=[None, len(training[0])])
net = tflearn.fully_connected(net, 8)
net = tflearn.fully_connected(net, 8)
net = tflearn.fully_connected(net, len(output[0]), activation="softmax")
net = tflearn.regression(net)

model = tflearn.DNN(net)

try:
    model.load("model.tflearn")
except:
    model.fit(training, output, n_epoch=1000, batch_size=8, show_metric=True)
    model.save("model.tflearn")

def bag_of_words(s, words):
    bag = [0 for _ in range(len(words))]

    s_words = nltk.word_tokenize(s)
    s_words = [stemmer.stem(word.lower()) for word in s_words]

    for se in s_words:
        for i, w in enumerate(words):
            if w == se:
                bag[i] = 1

    return numpy.array(bag)



@app.route("/")
def home():
    return render_template("index.html")

@app.route("/get")
def chat():
    userText = request.args.get('msg')
    while True:
            results = model.predict([bag_of_words(userText, words)])[0]
            results_index = numpy.argmax(results)
            tag = labels[results_index]

            if results[results_index] > 0.7:
                for tg in data["intents"]:
                    if tg['tag'] == tag:
                      responses = tg['responses']

                responce= random.choice(responses)
                return responce
            else:
                return("i didn't understand. try something else. ")


if __name__ == "__main__":
    app.run()

И вот как я настроил apache

LoadFile "c:/users/juliana thayil/appdata/local/programs/python/python36/python36.dll"
LoadModule wsgi_module "c:/users/juliana thayil/appdata/local/programs/python/python36/lib/site-packages/mod_wsgi/server/mod_wsgi.cp36-win_amd64.pyd"
WSGIPythonHome "c:/users/juliana thayil/appdata/local/programs/python/python36"
WSGIPythonPath "C:/wamp64/www/miniproject"

<VirtualHost *:80>
    ServerName localhost
    DocumentRoot c:/wamp64/www
    WSGIScriptAlias /miniproject c:/wamp64/www/miniproject/web.wsgi
    <Directory c:/wamp64/www/miniproject>
         require all granted
    </Directory>

</VirtualHost>