| | import nltk |
| | nltk.download('punkt') |
| |
|
| | import nltk |
| | 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 |
| |
|
| | 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") |
| | |
| |
|
| |
|
| | 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'] |
| |
|
| | |
| | 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() |
