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| import gradio as gr | |
| import numpy as np | |
| from transformers import pipeline | |
| from sentence_transformers import SentenceTransformer | |
| # ------------------------------------------------------------------------ | |
| # Load smaller, valid models | |
| # ------------------------------------------------------------------------ | |
| # Zero-shot NLI classifier (≈120 MB) | |
| intent_classifier = pipeline( | |
| "zero-shot-classification", | |
| model="valhalla/distilbart-mnli-12-1" | |
| ) | |
| # Lightweight sentence‐embedding model (≈60 MB) | |
| model = SentenceTransformer("paraphrase-MiniLM-L3-v2") | |
| # ------------------------------------------------------------------------ | |
| # Define intent labels | |
| # ------------------------------------------------------------------------ | |
| intents = [ | |
| "schedule appointment", | |
| "clinic hours", | |
| "insurance inquiry", | |
| "test results", | |
| "appointment cancellation", | |
| "prescription refill", | |
| "covid protocols", | |
| "update personal info", | |
| "services offered", | |
| "telehealth availability", | |
| "contact support" | |
| ] | |
| # ------------------------------------------------------------------------ | |
| # Updated FAQ data and corresponding intent tags | |
| # ------------------------------------------------------------------------ | |
| faq_data = { | |
| "questions": [ | |
| "How do I schedule an appointment?", | |
| "Can I book an appointment online?", | |
| "What is the process to make a doctor's appointment?", | |
| "What are your clinic hours?", | |
| "Are you open on weekends?", | |
| "When does the clinic open and close?", | |
| "Do you accept my insurance?", | |
| "Which insurance plans do you accept?", | |
| "Can I use my insurance for treatment?", | |
| "How can I get my test results?", | |
| "When will my lab results be ready?", | |
| "How do I access my blood test results?", | |
| "How do I cancel or reschedule my appointment?", | |
| "Can I change my appointment time?", | |
| "What is the cancellation policy?", | |
| "How do I refill my prescription?", | |
| "Can I get a refill for my medication online?", | |
| "What is the process to renew my prescription?", | |
| "What COVID-19 protocols are in place?", | |
| "Do I need to wear a mask to my appointment?", | |
| "How is your clinic handling COVID-19 safety?", | |
| "How do I update my personal information?", | |
| "Can I change my address or phone number online?", | |
| "Where do I update my contact details?", | |
| "What services do you offer?", | |
| "Do you provide pediatric care?", | |
| "What types of medical services are available?", | |
| "Are telehealth visits available?", | |
| "Can I book a virtual doctor visit?", | |
| "Do you offer video consultations?", | |
| "How can I contact customer service?", | |
| "What is your support phone number?", | |
| "Who do I talk to for more help?" | |
| ], | |
| "answers": [ | |
| "You can schedule an appointment by calling our clinic or using our online booking system.", | |
| "Yes, appointments can be booked online via our website or patient portal.", | |
| "To make a doctor's appointment, call our front desk or use the online scheduler.", | |
| "Our clinic is open Monday to Friday from 8 AM to 6 PM, and Saturdays from 9 AM to 1 PM.", | |
| "Yes, we are open on Saturdays from 9 AM to 1 PM but closed on Sundays.", | |
| "We open at 8 AM and close at 6 PM on weekdays.", | |
| "We accept most major insurance providers. Please contact us to verify your coverage.", | |
| "Our clinic accepts a variety of insurance plans including Aetna, Blue Cross, and United Healthcare.", | |
| "Yes, your insurance can be used for most treatments at our clinic.", | |
| "Test results are usually available within 3-5 business days and can be accessed through your patient portal.", | |
| "Lab results are typically ready within 3-5 days after testing.", | |
| "You can view your blood test results online through the patient portal.", | |
| "To cancel or reschedule, please call us at least 24 hours before your appointment or use the patient portal.", | |
| "You can change your appointment time by contacting our front desk.", | |
| "Our cancellation policy requires 24-hour notice to avoid fees.", | |
| "You can request prescription refills by contacting our pharmacy or through the patient portal.", | |
| "Refills can be requested online via your patient account.", | |
| "To renew your prescription, contact your doctor or use the online refill service.", | |
| "We follow all recommended COVID-19 safety protocols, including mask mandates and social distancing.", | |
| "Masks are required for all visitors during appointments.", | |
| "Our clinic enforces strict COVID-19 guidelines to ensure patient safety.", | |
| "You can update your personal information by logging into your patient account or contacting our front desk.", | |
| "Changes to your address or phone number can be made online.", | |
| "Please update your contact details through the patient portal or by calling us.", | |
| "Our services include primary care, pediatrics, lab testing, immunizations, and wellness checkups.", | |
| "Yes, we offer pediatric care as part of our services.", | |
| "We provide a wide range of medical services including preventive care and diagnostics.", | |
| "Telehealth visits are available for many of our services.", | |
| "You can book a virtual doctor visit online through our patient portal.", | |
| "Video consultations are offered for appropriate medical concerns.", | |
| "You can contact customer service via phone at 1-800-123-4567 or email support@clinic.com.", | |
| "Our support phone number is 1-800-123-4567.", | |
| "For more help, please contact our support team by phone or email." | |
| ] | |
| } | |
| intent_tags = [ | |
| "schedule appointment", "schedule appointment", "schedule appointment", | |
| "clinic hours", "clinic hours", "clinic hours", | |
| "insurance inquiry", "insurance inquiry", "insurance inquiry", | |
| "test results", "test results", "test results", | |
| "appointment cancellation", "appointment cancellation", "appointment cancellation", | |
| "prescription refill", "prescription refill", "prescription refill", | |
| "covid protocols", "covid protocols", "covid protocols", | |
| "update personal info", "update personal info", "update personal info", | |
| "services offered", "services offered", "services offered", | |
| "telehealth availability", "telehealth availability", "telehealth availability", | |
| "contact support", "contact support", "contact support" | |
| ] | |
| # ------------------------------------------------------------------------ | |
| # Precompute embeddings for all FAQ questions once | |
| # ------------------------------------------------------------------------ | |
| faq_embeddings = model.encode(faq_data["questions"]) | |
| def chatbot_response(user_question, threshold_intent=0.2, threshold_faq=0.3): | |
| """ | |
| Two‐stage matching: | |
| 1) Zero‐shot intent classification. If confidence < threshold_intent, | |
| do a direct cosine‐similarity search across all FAQs. | |
| 2) Otherwise, filter FAQs by predicted intent, then cosine‐similarity | |
| among that subset. If score < threshold_faq, return fallback. | |
| """ | |
| # 1) Encode the user question | |
| user_emb = model.encode([user_question])[0] | |
| # 2) Intent prediction | |
| intent_result = intent_classifier(user_question, candidate_labels=intents) | |
| predicted_intent = intent_result["labels"][0] | |
| intent_confidence = intent_result["scores"][0] | |
| # 3) If low confidence, match across all FAQs | |
| if intent_confidence < threshold_intent: | |
| cos_sims = np.dot(faq_embeddings, user_emb) / ( | |
| np.linalg.norm(faq_embeddings, axis=1) * np.linalg.norm(user_emb) | |
| ) | |
| best_idx = np.argmax(cos_sims) | |
| if cos_sims[best_idx] >= threshold_faq: | |
| return faq_data["answers"][best_idx] | |
| return "Sorry, I didn't understand your question. Please try rephrasing." | |
| # 4) Otherwise, filter by that intent | |
| indices = [i for i, tag in enumerate(intent_tags) if tag == predicted_intent] | |
| if not indices: | |
| return "Sorry, I don't have an answer for that topic yet." | |
| filtered_embs = faq_embeddings[indices] | |
| cos_sims = np.dot(filtered_embs, user_emb) / ( | |
| np.linalg.norm(filtered_embs, axis=1) * np.linalg.norm(user_emb) | |
| ) | |
| best_idx_within = np.argmax(cos_sims) | |
| if cos_sims[best_idx_within] < threshold_faq: | |
| return "Sorry, I couldn't find a good match for your question." | |
| return faq_data["answers"][indices[best_idx_within]] | |
| # ------------------------------------------------------------------------ | |
| # Gradio interface | |
| # ------------------------------------------------------------------------ | |
| def respond(user_input): | |
| return chatbot_response(user_input) | |
| iface = gr.Interface( | |
| fn=respond, | |
| inputs=gr.Textbox(lines=2, placeholder="Ask a health-related question..."), | |
| outputs="text", | |
| title="Healthcare Support Chatbot", | |
| description="Ask about appointments, test results, COVID protocols, telehealth, and more." | |
| ) | |
| if __name__ == "__main__": | |
| iface.launch() | |