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import os |
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import streamlit as st |
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import pandas as pd |
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from datasets import load_from_disk |
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from transformers import AutoTokenizer, TFAutoModel |
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from dotenv import load_dotenv |
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load_dotenv() |
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Drugs = ['Amitriptyline', 'Ambien', 'Aripiprazole', 'Actos', 'Aubra', |
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'Amphetamine / dextroamphetamine', 'Afrezza', |
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'Aluminum chloride hexahydrate', 'Acetaminophen / hydrocodone', |
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'Aviane', 'Aldesleukin', 'Acamprosate', 'Azathioprine', |
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'Adapalene / benzoyl peroxide', |
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'Acetaminophen / butalbital / caffeine', 'Accutane', |
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'Ayr Saline Nasal', 'Asenapine', 'Adipex-P', 'Augmentin', 'Apri', |
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'Alesse', 'Aspirin / carisoprodol', 'Azelaic acid', 'Azithromycin', |
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'Alpha 1-proteinase inhibitor', 'Abilify', 'Amlodipine', |
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'Arimidex', 'Acetaminophen / codeine', 'Advair Diskus', |
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'Alprazolam', 'Alcaftadine', |
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'Acetaminophen / dexbrompheniramine / pseudoephedrine', 'AndroGel', |
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'Avinza', 'Ativan', 'Atomoxetine', 'Alphagan P', 'Apremilast', |
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'Advair HFA', 'Anastrozole', 'Azor', 'Azelastine / fluticasone', |
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'Amerge', 'Avonex Pen', 'Acetaminophen / oxycodone', |
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'Abacavir / dolutegravir / lamivudine', 'Adderall', 'Atorvastatin', |
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'Aptensio XR', |
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'Acetaminophen / dichloralphenazone / isometheptene mucate', |
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'Acyclovir', 'Armodafinil', 'Adderall XR', |
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'Antipyrine / benzocaine', 'Aczone', 'Amoxicillin / clavulanate', |
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'Adalimumab', 'Aranesp', 'Ammonium lactate / halobetasol', |
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'Atenolol', 'Avelox', 'Azithromycin Dose Pack', 'Adapalene', |
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'Amoxicillin', 'Acetaminophen / aspirin / caffeine', 'Azelastine', |
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'Albuterol', 'Amethyst', 'Asacol', 'Aleve', 'Alprostadil', |
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'Astelin', 'Atropine / hyoscyamine / phenobarbital / scopolamine','Ascorbic acid', 'Asthmanefrin', 'Allegra-D 12 Hour', 'Amikacin', |
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'Arixtra', 'Apokyn', 'AbobotulinumtoxinA', 'Axid', 'Accolate', |
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'Adoxa', 'Aspirin / caffeine', 'Aliskiren / hydrochlorothiazide', |
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'Afinitor', 'Acetaminophen / phenylephrine', 'Atacand', |
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'Allergy DN PE','Bactrim', 'Belviq', 'Blisovi Fe 1 / 20', |
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'Benzoyl peroxide / clindamycin', 'BuSpar', 'Bupropion', |
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'Bacitracin / neomycin / polymyxin b', 'Brisdelle', 'Beyaz', |
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'Buprenorphine / naloxone', 'Benzonatate', 'Bisacodyl', 'Buprenex', |
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'Benzoyl peroxide / erythromycin', 'Budeprion SR', |
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'Bupropion / naltrexone', 'Belsomra', 'Bevacizumab', |
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'Barium sulfate', 'Bismuth subsalicylate', 'Brovana', 'Buspirone', |
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'Bronkaid', 'Benzocaine', 'Butrans', 'Bunavail', 'Benicar', |
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'Benadryl Allergy', 'Benadryl', 'Biotin', 'Bromfed DM', |
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'Breo Ellipta', 'Biaxin', 'Botox', 'Buprenorphine', |
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'Benzoic acid / salicylic acid', 'Brimonidine / timolol', |
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'Beclomethasone', 'Bydureon', 'Bonine', 'Brilinta', 'Bactrim DS', |
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'Brexpiprazole', 'Baclofen', 'Benazepril', 'Biaxin XL', 'Basaglar', |
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'Bismuth subcitrate potassium / metronidazole / tetracycline', |
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'Belbuca', 'Bromocriptine', 'Budesonide / formoterol', |
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'Blisovi 24 Fe', 'Bystolic', 'Banzel', 'Balacet', 'Balsalazide', |
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'Benlysta', 'Belimumab', 'Byetta', |
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'Bisoprolol / hydrochlorothiazide', 'Butorphanol', 'Boniva', |
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'Briviact', 'Brimonidine', 'Biafine', 'Betaseron', |
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'Benazepril / hydrochlorothiazide', 'Benzoyl peroxide / sulfur', |
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'Bisacodyl / polyethylene glycol 3350 / potassium chloride / sodium bicarbonate / sodium chloride', |
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'Balsam peru / castor oil / trypsin', |
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'Betamethasone / calcipotriene', 'Budeprion XL', 'Benicar HCT', |
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'Bepotastine', 'Bentyl', 'Brompheniramine', 'Benzaclin', |
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'Bisoprolol', 'Budesonide', 'Bontril Slow Release', 'Bepreve','Berinert', 'Benzoyl peroxide', 'Belladonna / opium', |
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'Butabarbital', 'Bioflavonoids / zinc glycinate', 'Brodalumab', |
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'Bicillin L-A', 'Bimatoprost', 'Benztropine', 'Bethanechol', |
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'Bupivacaine', 'Bosutinib', 'Bismuth subgallate', 'BenzEFoam', |
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'Brivaracetam', 'Blistex','Contrave', 'Cyclafem 1 / 35', 'Copper', 'Chantix', |
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'Ciprofloxacin', 'Cyclosporine', 'Clonazepam', 'Ciclopirox', |
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'Campral', 'Cryselle', 'Clindamycin', 'Clonidine', 'Celecoxib', |
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'Caffeine', 'Clarithromycin', 'Clomiphene', 'Clotrimazole', |
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'Celexa', 'Codeine / guaifenesin', 'Cefuroxime', 'Cymbalta', |
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'Canagliflozin', 'Citalopram', 'Corticotropin', 'Cefdinir', |
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'Carvedilol', 'Chlordiazepoxide', 'CellCept', |
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'Cobicistat / elvitegravir / emtricitabine / tenofovir alafenamide', |
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'Chateal', 'Cyclobenzaprine', 'Cialis', 'Cholestyramine', 'Cozaar', |
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'Catapres', 'Carbidopa / levodopa', 'Carisoprodol', |
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'Citric acid / magnesium oxide / sodium picosulfate', 'Cetirizine', |
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'Cambia', 'Clindamycin / tretinoin', 'Crestor', 'Copaxone', |
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'Chlorpheniramine / hydrocodone / pseudoephedrine', |
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'Cobicistat / elvitegravir / emtricitabine / tenofovir', |
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'Cogentin', 'Cosentyx', 'Cipro', 'Cytomel', 'Camrese', 'Clomid', |
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'Celebrex', 'Colesevelam', 'Clozapine', 'Cutivate', 'Cyred', |
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'Concerta', 'Chlorpheniramine / hydrocodone', 'Claravis', |
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'Cyanocobalamin', 'Clopidogrel', 'Cyproheptadine', |
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'Chlordiazepoxide / clidinium', 'Carbamazepine', 'Crisaborole', |
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'Colchicine', 'Ciprofloxacin / dexamethasone', 'Clomipramine', |
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'Cabergoline', 'Carac', 'Cephalexin', 'Cariprazine', 'Correctol', |
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'Celestone', 'Creon', 'Clobetasol', 'Colazal', 'Chlorzoxazone', |
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'Cenestin', 'Casodex', 'Cinryze', 'Claritin-D', 'Chlorhexidine', |
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'Complera', 'Cervidil', 'Cefixime', 'Coreg', 'Camila', |
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'Clorazepate', 'Cevimeline', 'Cosopt', 'Chondroitin / glucosamine','Citrate of Magnesia', 'Coricidin HBP Cold & Flu', 'Cefditoren', |
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'Ceftibuten', 'Cyclessa', 'Cortef', 'Calcium acetate', 'Cyclizine', |
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'Coagulation factor ix', 'Colace', 'Carmol 20', 'Calan SR', |
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'Cyklokapron', 'Coal tar', 'Cobicistat / darunavir', 'Calamine', |
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'CoQ10','Duloxetine', 'Depakote', 'Drospirenone / estradiol', |
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'Depo-Provera', 'Desyrel', 'Desvenlafaxine', |
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'Drospirenone / ethinyl estradiol', 'Doxylamine / pyridoxine', |
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'Demerol', 'Dextromethorphan', 'Diazepam', 'Diphenhydramine', |
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'Denosumab', 'Dulaglutide', 'Drysol', 'Divalproex sodium', |
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'Doxycycline', 'Desogestrel / ethinyl estradiol', 'Duofilm', |
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'Dicyclomine', 'Dexmethylphenidate', 'Diltiazem', 'Dapsone', |
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'Dalfampridine', 'Dilantin', 'Dienogest / estradiol', 'Diclofenac', |
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'Donnatal', 'Depakote ER', 'Donepezil', 'Dulcolax', 'Dulera', |
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'Dapagliflozin', 'Duexis', 'Differin', 'Doxepin', 'Docosanol', |
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'Diclegis', 'Desloratadine', |
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'Drospirenone / ethinyl estradiol / levomefolate calcium', 'Duac', |
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'Deplin', 'Doryx', 'Dilaudid', 'Dimenhydrinate', 'Delsym', |
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'Denavir', 'D.H.E. 45', 'Disulfiram', 'Droperidol', 'Dasatinib', |
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'Dextrostat', 'Dymista', 'Dextroamphetamine', 'DDAVP Rhinal Tube', |
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'Dabigatran', 'Dasabuvir / ombitasvir / paritaprevir / ritonavir', |
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'Dextromethorphan / guaifenesin', 'Diflucan', 'Debrox', |
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'Diphenhydramine / naproxen', 'Daklinza', 'Daliresp', |
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'Dihydroergotamine', 'Dinoprostone', 'Dermal filler', 'Doxylamine', |
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'Daytrana', 'Diprivan', 'Dexlansoprazole', 'Dovonex', 'Doral', |
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'Desquam-X Wash', 'Dexilant', 'Dofetilide', 'Diovan HCT', 'Detrol', |
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"Dimetapp Children's Cold & Cough", 'Delatestryl', 'Desipramine', |
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'Daclatasvir', 'Depo-Testosterone', 'Dulcolax Laxative', |
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'Dexamethasone', 'Dimethyl fumarate', 'Dronabinol', 'Duragesic', |
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'Dexedrine', 'Dupixent', 'Dramamine','Daypro', 'Dyazide', 'Deltasone', 'Depo-Medrol', |
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'Dapagliflozin / metformin', 'Dilaudid-HP', 'Doxorubicin', |
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'Deoxycholic acid', |
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'Dextromethorphan / phenylephrine / pyrilamine', |
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'Diphenhydramine / ibuprofen', 'Divigel', 'Dermatop'] |
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model_ckpt = "sentence-transformers/multi-qa-mpnet-base-dot-v1" |
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tokenizer = AutoTokenizer.from_pretrained(model_ckpt) |
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model = TFAutoModel.from_pretrained(model_ckpt, from_pt=True) |
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def cls_pooling(model_output): |
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return model_output.last_hidden_state[:, 0] |
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def get_embeddings(text_list): |
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encoded_input = tokenizer( |
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text_list, padding=True, truncation=True, return_tensors="tf" |
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) |
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encoded_input = {k: v for k, v in encoded_input.items()} |
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model_output = model(**encoded_input) |
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return cls_pooling(model_output) |
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embeddings_dataset = load_from_disk("data") |
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embeddings_dataset.add_faiss_index(column="embeddings") |
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def recommendations(question): |
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question_embedding = get_embeddings([question]).numpy() |
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scores, samples = embeddings_dataset.get_nearest_examples( |
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"embeddings", question_embedding, k=5 |
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) |
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samples_df = pd.DataFrame.from_dict(samples) |
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samples_df["scores"] = scores |
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samples_df.sort_values("scores", ascending=False, inplace=True,ignore_index=True) |
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return samples_df[['drugName', 'review', 'scores']] |
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st.title("Drug Recommendation System") |
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st.markdown( |
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""" |
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<style> |
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#MainMenu {visibility: hidden;} |
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footer {visibility: hidden;} |
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</style> |
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""", |
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unsafe_allow_html=True |
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) |
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st.sidebar.title("Choose or Enter a Question:") |
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selection_type = st.sidebar.radio("Select type:", ("Select Default", "Enter Custom")) |
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if selection_type == "Select Default": |
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selected_question = st.sidebar.selectbox("Select a question", Drugs) |
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if st.sidebar.button("Show Recommendations"): |
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recommendation_result = recommendations(selected_question) |
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st.header(f"Top 5 Recommended Drugs for '{selected_question}':") |
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st.table(recommendation_result) |
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else: |
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default_question = "I've acne problem" |
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custom_question = st.sidebar.text_input("Enter your question:", default_question) |
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if st.sidebar.button("Get Recommendations"): |
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if custom_question: |
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custom_recommendation_result = recommendations(custom_question) |
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st.header("Top 5 Recommended Drugs for Your Question:") |
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st.table(custom_recommendation_result) |
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else: |
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st.warning("Please enter a question to get recommendations.") |
