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Update app.py
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app.py
CHANGED
@@ -18,19 +18,19 @@ nltk.download('punkt')
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# Initialize the stemmer
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stemmer = LancasterStemmer()
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# Load intents.json
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try:
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with open("intents.json") as file:
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data = json.load(file)
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except FileNotFoundError:
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raise FileNotFoundError("Error: 'intents.json' file not found
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# Load preprocessed data from pickle
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try:
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with open("data.pickle", "rb") as f:
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words, labels, training, output = pickle.load(f)
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except FileNotFoundError:
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raise FileNotFoundError("Error: 'data.pickle' file not found
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# Build the model structure
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net = tflearn.input_data(shape=[None, len(training[0])])
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@@ -39,12 +39,12 @@ net = tflearn.fully_connected(net, 8)
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net = tflearn.fully_connected(net, len(output[0]), activation="softmax")
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net = tflearn.regression(net)
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# Load the trained model
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model = tflearn.DNN(net)
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try:
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model.load("MentalHealthChatBotmodel.tflearn")
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except FileNotFoundError:
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raise FileNotFoundError("Error: Trained model file 'MentalHealthChatBotmodel.tflearn' not found.")
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# Function to process user input into a bag-of-words format
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def bag_of_words(s, words):
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@@ -150,7 +150,7 @@ def provide_suggestions(emotion):
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return suggestions
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# Google Places API to get nearby wellness professionals
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api_key = "
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def get_places_data(query, location, radius, api_key, next_page_token=None):
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url = "https://maps.googleapis.com/maps/api/place/textsearch/json"
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@@ -221,21 +221,3 @@ iface = gr.Interface(
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inputs=[
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gr.Textbox(label="Enter your message", placeholder="How are you feeling today?"),
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gr.Textbox(label="Enter your location (e.g., Hawaii, Oahu)", placeholder="Your location"),
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gr.State() # One state input
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],
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outputs=[
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gr.Chatbot(label="Chat History"),
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gr.Textbox(label="Sentiment Analysis"),
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gr.Textbox(label="Detected Emotion"),
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gr.Dataframe(label="Suggestions & Resources"),
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gr.Dataframe(label="Nearby Wellness Professionals"), # Display results as a table
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gr.State() # One state output
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],
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allow_flagging="never",
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title="Mental Wellbeing App with AI Assistance",
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description="This app provides a mental health chatbot, sentiment analysis, emotion detection, and wellness professional search functionality.",
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)
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# Launch Gradio interface
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if __name__ == "__main__":
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iface.launch(debug=True, share=True) # Set share=True to create a public link
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# Initialize the stemmer
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stemmer = LancasterStemmer()
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# Load intents.json (directly in the app directory)
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try:
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with open("intents.json") as file:
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data = json.load(file)
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except FileNotFoundError:
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raise FileNotFoundError("Error: 'intents.json' file not found in the app directory.")
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# Load preprocessed data from pickle (directly in the app directory)
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try:
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with open("data.pickle", "rb") as f:
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words, labels, training, output = pickle.load(f)
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except FileNotFoundError:
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raise FileNotFoundError("Error: 'data.pickle' file not found in the app directory.")
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# Build the model structure
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net = tflearn.input_data(shape=[None, len(training[0])])
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net = tflearn.fully_connected(net, len(output[0]), activation="softmax")
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net = tflearn.regression(net)
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# Load the trained model (directly in the app directory)
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model = tflearn.DNN(net)
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try:
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model.load("MentalHealthChatBotmodel.tflearn")
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except FileNotFoundError:
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raise FileNotFoundError("Error: Trained model file 'MentalHealthChatBotmodel.tflearn' not found in the app directory.")
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# Function to process user input into a bag-of-words format
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def bag_of_words(s, words):
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return suggestions
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# Google Places API to get nearby wellness professionals
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api_key = "YOUR_GOOGLE_API_KEY" # Replace with your actual API key
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def get_places_data(query, location, radius, api_key, next_page_token=None):
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url = "https://maps.googleapis.com/maps/api/place/textsearch/json"
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inputs=[
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gr.Textbox(label="Enter your message", placeholder="How are you feeling today?"),
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gr.Textbox(label="Enter your location (e.g., Hawaii, Oahu)", placeholder="Your location"),
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