| import gradio as gr | |
| import random | |
| from PIL import Image | |
| from funcs import detect_emotions, cosine_distance, generate_triggers_img, get_doc_response_emotions, summarize_and_recommend | |
| with gr.Blocks() as demo: | |
| gr.Markdown("""# Your Intimate Personal Therapist | |
| ## Your Personal AI Therapist. Start chatting... Once you finish chatting, click "Generate Session Notes & Recommendations" button and wait for few seconds for them to appear""") | |
| therapy_session_conversation = gr.State([]) | |
| img_paths = ['2.jpg','3.jpeg','4.jpeg','5.jpeg','6.jpeg'] | |
| img_path = random.choice(img_paths) | |
| img_1 = Image.open(img_path) | |
| img_path = '7.jpg' | |
| img_2 = Image.open(img_path) | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| image = gr.Image(type='pil', label ='Your Personal Therapy Assistant', value=img_1, interactive=False) | |
| emotions = gr.Image(value=img_2, label='Top 5 Emotion Triggers') | |
| summary_notes = gr.Textbox(label="Summary Notes of the Session", visible=False) | |
| with gr.Column(scale=2): | |
| chatbox = gr.Chatbot(label="Therapy Session Conversation",value =[[None, 'Therapist: Hello, What can I do for you?']], height=300) | |
| user_input = gr.Textbox(placeholder="Enter your message here...", label="User") | |
| submit_button = gr.Button("Submit") | |
| submit_button.click(get_doc_response_emotions, [user_input, chatbox], [user_input, chatbox, emotions]) | |
| user_input.submit(get_doc_response_emotions, [user_input, chatbox], [user_input, chatbox, emotions]) | |
| recommendations = gr.Textbox(label="Recommended Actions", visible = False) | |
| def summarize_and_recommend_process(tcs): | |
| sn, r, cb = summarize_and_recommend(tcs) | |
| return gr.update(visible=True, value=sn), gr.update(visible=True, value=r), gr.update(visible=True, value=cb) | |
| process_button = gr.Button("Generate Session Notes & Recommendations") | |
| clear = gr.ClearButton(components=[user_input, chatbox, emotions, summary_notes, recommendations], value="Clear console") | |
| process_button.click(summarize_and_recommend_process, inputs=[chatbox], outputs=[summary_notes, recommendations, chatbox]) | |
| demo.launch(debug=True, share=True) |