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| from transformers import pipeline | |
| import wikipedia | |
| import random | |
| import gradio as gr | |
| import csv | |
| model_name = "deepset/electra-base-squad2" | |
| nlp = pipeline('question-answering', model=model_name, tokenizer=model_name) | |
| # dataset save ------------------------------------ | |
| import huggingface_hub | |
| import os | |
| from huggingface_hub import Repository, hf_hub_download, upload_file | |
| from datetime import datetime | |
| # created new dataset as awacke1/MindfulStory.csv | |
| DATASET_REPO_URL = "https://huggingface.co/datasets/awacke1/WikipediaSearch" | |
| DATASET_REPO_ID = "awacke1/WikipediaSearch" | |
| DATA_FILENAME = "WikipediaSearch.csv" | |
| DATA_FILE = os.path.join("data", DATA_FILENAME) | |
| HF_TOKEN = os.environ.get("HF_TOKEN") | |
| # Download dataset repo using hub download | |
| try: | |
| hf_hub_download( | |
| repo_id=DATASET_REPO_ID, | |
| filename=DATA_FILENAME, | |
| cache_dir=DATA_DIRNAME, | |
| force_filename=DATA_FILENAME | |
| ) | |
| except: | |
| print("file not found") | |
| def AIMemory(title: str, story: str): | |
| if title and story: | |
| with open(DATA_FILE, "a") as csvfile: | |
| writer = csv.DictWriter(csvfile, fieldnames=["title", "story", "time"]) | |
| writer.writerow({"title": title, "story": story, "time": str(datetime.now())}) | |
| commit_url = repo.push_to_hub() | |
| return "" | |
| # Set up cloned dataset from repo for operations | |
| repo = Repository( | |
| local_dir="data", clone_from=DATASET_REPO_URL, use_auth_token=HF_TOKEN | |
| ) | |
| # dataset save ------------------------------------ | |
| def get_wiki_article(topic): | |
| topic=topic | |
| try: | |
| search = wikipedia.search(topic, results = 1)[0] | |
| except wikipedia.DisambiguationError as e: | |
| choices = [x for x in e.options if ('disambiguation' not in x) and ('All pages' not in x) and (x!=topic)] | |
| search = random.choice(choices) | |
| try: | |
| p = wikipedia.page(search) | |
| print(p) | |
| except wikipedia.exceptions.DisambiguationError as e: | |
| print("disambiguation error") | |
| choices = [x for x in e.options if ('disambiguation' not in x) and ('All pages' not in x) and (x!=topic)] | |
| print(choices) | |
| s = random.choice(choices) | |
| p = wikipedia.page(s) | |
| saved = AIMemory(p.content, p.url) | |
| return p.content, p.url | |
| def get_answer(topic, question): | |
| w_art, w_url=get_wiki_article(topic) | |
| print(topic) | |
| print(question) | |
| print(w_art) | |
| qa = {'question': question, 'context': w_art} | |
| res = nlp(qa) | |
| saved = AIMemory(res['answer'], w_url) | |
| return res['answer'], w_url, {'confidence':res['score']} | |
| inputs = [ | |
| gr.inputs.Textbox(lines=2, label="Topic"), | |
| gr.inputs.Textbox(lines=2, label="Question") | |
| ] | |
| outputs = [ | |
| gr.outputs.Textbox(type='str',label="Answer"), | |
| gr.outputs.Textbox(type='str',label="Wikipedia Reference Article"), | |
| gr.outputs.Label(type="confidences",label="Confidence in answer (assuming the correct wikipedia article)"), | |
| ] | |
| title = "AI Wikipedia Search" | |
| description = 'Contextual Question and Answer' | |
| article = '' | |
| examples = [ | |
| ['Health and fitness', 'What is the DSM-IV?'], | |
| ['Technology and applied sciences', 'List of military strategies and concepts?'], | |
| ['Culture and the arts', 'What films are considered the best?'], | |
| ['Health and fitness', 'What are the types of psychotherapies?'], | |
| ['Health and fitness', 'What are macronutrients?'], | |
| ['Health and fitness', 'What are micronutrients?'], | |
| ['Health and fitness', 'What are Nootropics?'], | |
| ['Health and fitness', 'What is the timeline of psychology?'], | |
| ['Cicero', 'What quotes did Marcus Tullius Cicero make?'], | |
| ['Alzheimers', 'What causes alzheimers?'], | |
| ['Neuropathy', 'With neuropathy and neuro-muskoskeletal issues, and what are the treatments available?'], | |
| ['Chemotherapy', 'What are possible care options for patients in chemotherapy?'], | |
| ['Health', 'What is mindfulness and how does it affect health?'], | |
| ['Medicine', 'In medicine what is the Hippocratic Oath?'], | |
| ['Insurance', 'What is Medicare?'], | |
| ['Financial Services', 'Does Medicaid offer financial assistance?'], | |
| ['Ontology', 'Why is an anthology different than ontology?'], | |
| ['Taxonomy', 'What is a biology taxonomy?'], | |
| ['Pharmacy', 'What does a pharmacist do?'] | |
| ] | |
| gr.Interface(get_answer, inputs, outputs, title=title, description=description, examples=examples, | |
| article="Saved dataset: https://huggingface.co/datasets/awacke1/WikipediaSearch stores search and the result url. List of topics is at https://en.wikipedia.org/wiki/Wikipedia:Contents/Lists and wikipedia library docs are here: https://pypi.org/project/wikipedia/", | |
| flagging_options=["strongly related","related", "neutral", "unrelated", "strongly unrelated"]).launch(debug=True,share=False,enable_queue=False) |