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| import nltk | |
| nltk.download('punkt') | |
| from nltk.stem.lancaster import LancasterStemmer | |
| import numpy as np | |
| import tflearn | |
| import tensorflow | |
| import random | |
| import json | |
| import pandas as pd | |
| import pickle | |
| import gradio as gr | |
| from tensorflow.python.util.nest import is_sequence_or_composite | |
| stemmer = LancasterStemmer() | |
| with open("intents.json") as file: | |
| data = json.load(file) | |
| with open("data.pickle", "rb") as f: | |
| words, labels, training, output = pickle.load(f) | |
| 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) | |
| model.load("MentalHealthChatBotmodel.tflearn") | |
| # print('model loaded successfully') | |
| 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 np.array(bag) | |
| def chat(message, history): | |
| history = history or [] | |
| message = message.lower() | |
| results = model.predict([bag_of_words(message, words)]) | |
| results_index = np.argmax(results) | |
| tag = labels[results_index] | |
| for tg in data["intents"]: | |
| if tg['tag'] == tag: | |
| responses = tg['responses'] | |
| # print(random.choice(responses)) | |
| response = random.choice(responses) | |
| history.append((message, response)) | |
| return history, history | |
| chatbot = gr.Chatbot(label="Chat") | |
| css = """ | |
| footer {display:none !important} | |
| .output-markdown{display:none !important} | |
| .gr-button-primary { | |
| z-index: 14; | |
| height: 43px; | |
| width: 130px; | |
| left: 0px; | |
| top: 0px; | |
| padding: 0px; | |
| cursor: pointer !important; | |
| background: none rgb(17, 20, 45) !important; | |
| border: none !important; | |
| text-align: center !important; | |
| font-family: Poppins !important; | |
| font-size: 14px !important; | |
| font-weight: 500 !important; | |
| color: rgb(255, 255, 255) !important; | |
| line-height: 1 !important; | |
| border-radius: 12px !important; | |
| transition: box-shadow 200ms ease 0s, background 200ms ease 0s !important; | |
| box-shadow: none !important; | |
| } | |
| .gr-button-primary:hover{ | |
| z-index: 14; | |
| height: 43px; | |
| width: 130px; | |
| left: 0px; | |
| top: 0px; | |
| padding: 0px; | |
| cursor: pointer !important; | |
| background: none rgb(37, 56, 133) !important; | |
| border: none !important; | |
| text-align: center !important; | |
| font-family: Poppins !important; | |
| font-size: 14px !important; | |
| font-weight: 500 !important; | |
| color: rgb(255, 255, 255) !important; | |
| line-height: 1 !important; | |
| border-radius: 12px !important; | |
| transition: box-shadow 200ms ease 0s, background 200ms ease 0s !important; | |
| box-shadow: rgb(0 0 0 / 23%) 0px 1px 7px 0px !important; | |
| } | |
| .hover\:bg-orange-50:hover { | |
| --tw-bg-opacity: 1 !important; | |
| background-color: rgb(229,225,255) !important; | |
| } | |
| div[data-testid="user"] { | |
| background-color: #253885 !important; | |
| } | |
| .h-\[40vh\]{ | |
| height: 70vh !important; | |
| } | |
| """ | |
| demo = gr.Interface( | |
| chat, | |
| [gr.Textbox(lines=1, label="Message"), "state"], | |
| [chatbot, "state"], | |
| allow_flagging="never", | |
| title="Mental Health Bot | Data Science Dojo", | |
| css=css | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch() |