import json
import requests
import re
from relbert import RelBERT
import gradio as gr

model = RelBERT(model='relbert/relbert-roberta-large')


def get_example():
    url = "https://huggingface.co/datasets/relbert/analogy_questions/raw/main/dataset/sat/test.jsonl"
    r = requests.get(url)
    example = [json.loads(i) for i in r.content.decode().split('\n') if len(i) > 0]
    return example


def cosine_similarity(a, b, zero_vector_mask: float = -100):
    norm_a = sum(map(lambda x: x * x, a)) ** 0.5
    norm_b = sum(map(lambda x: x * x, b)) ** 0.5
    if norm_b * norm_a == 0:
        return zero_vector_mask
    return sum(map(lambda x: x[0] * x[1], zip(a, b)))/(norm_a * norm_b)


def clean(text):
    text = re.sub(r"\A\s+", "", text)
    text = re.sub(r"\s+\Z", "", text)
    return text


def greet(
        query,
        candidate_1,
        candidate_2,
        candidate_3,
        candidate_4,
        candidate_5,
        candidate_6):
    query = [clean(i) for i in query.split(',')]
    # validate query
    if len(query) == 0:
        raise ValueError(f'ERROR: query is empty {query}')
    if len(query) == 1:
        raise ValueError(f'ERROR: query contains single word {query}')
    if len(query) > 2:
        raise ValueError(f'ERROR: query contains more than two word {query}')

    pairs = []
    pairs_id = []
    for n, i in enumerate([
        candidate_1,
        candidate_2,
        candidate_3,
        candidate_4,
        candidate_5,
        candidate_6
    ]):
        if i == '':
            continue
        candidate = [clean(x) for x in i.split(',')]
        if len(candidate) == 1:
            raise ValueError(f'ERROR: candidate {n + 1} contains single word {candidate}')
        if len(candidate) > 2:
            raise ValueError(f'ERROR: candidate {n + 1} contains more than two word {candidate}')
        pairs.append(candidate)
        pairs_id.append(n+1)
    if len(pairs_id) < 2:
        raise ValueError(f'ERROR: please specify at least two candidates: {pairs}')
    vectors = model.get_embedding(pairs+[query])
    vector_q = vectors.pop(-1)
    sims = []
    for v in vectors:
        sims.append(cosine_similarity(v, vector_q))
    output = {f'candidate {i}: [{p[0]}, {p[1]}]': s for i, s, p in zip(pairs_id, sims, pairs)}
    return output


examples = get_example()[:15]
examples = [[','.join(i['stem'])] + [','.join(c) for c in i['choice'] + [''] * (6 - len(i['choice']))] for i in examples]
demo = gr.Interface(
    fn=greet,
    inputs=[
        gr.Textbox(lines=1, placeholder="Query Word Pair (separate by comma)"),
        gr.Textbox(lines=1, placeholder="Candidate Word Pair 1 (separate by comma)"),
        gr.Textbox(lines=1, placeholder="Candidate Word Pair 2 (separate by comma)"),
        gr.Textbox(lines=1, placeholder="Candidate Word Pair 3 (separate by comma)"),
        gr.Textbox(lines=1, placeholder="Candidate Word Pair 4 (separate by comma)"),
        gr.Textbox(lines=1, placeholder="Candidate Word Pair 5 (separate by comma)"),
        gr.Textbox(lines=1, placeholder="Candidate Word Pair 6 (separate by comma)"),
        ],
    outputs="label",
    examples=examples
)
demo.launch(show_error=True)