"""Calibration requests in Prism's own input format, built from multilingual Wikipedia passages (11 languages).
Disjoint from the evaluation suite (different texts and question wording)."""
import json
import random

LANG_NAMES = {"en": "English", "hi": "Hindi", "bn": "Bengali", "ta": "Tamil", "te": "Telugu", "mr": "Marathi",
              "gu": "Gujarati", "kn": "Kannada", "ml": "Malayalam", "or": "Odia", "pa": "Punjabi"}

QUESTIONS = [
    lambda r, l: {"type": "choice", "instructions": "What is the main subject area of this text?",
                  "criteria": {"history": "history and past events", "science": "science and technology",
                               "geography": "places and geography", "people": "a biography of a person",
                               "culture": "arts, religion, culture", "politics": "government and politics",
                               "sports": None, "other": None}},
    lambda r, l: {"type": "choice", "instructions": "In which language is the passage written?",
                  "criteria": dict(r.sample(sorted(LANG_NAMES.items()), 4) + [(l, LANG_NAMES[l])])},
    lambda r, l: {"type": "yes_no", "instructions": "Does the passage mention a specific year or date?"},
    lambda r, l: {"type": "yes_no", "instructions": "Is this passage about a living person?"},
    lambda r, l: {"type": "yes_no", "instructions": "Would this text be suitable for a children's encyclopedia?"},
    lambda r, l: {"type": "yes_no", "instructions": "Does the text contain a factual error?"},
    lambda r, l: {"type": "score", "instructions": "How technical is the language of this passage?",
                  "criteria": ["very simple", "simple", "moderate", "technical", "highly specialised"]},
    lambda r, l: {"type": "score", "instructions": "How well written is this text?",
                  "criteria": {"poor": "many errors", "fair": "some problems", "good": "clear", "great": "excellent prose"}},
    lambda r, l: {"type": "score", "instructions": "How likely is a general reader to find this interesting?",
                  "criteria": ["0", "1", "2", "3", "4", "5", "6", "7", "8", "9", "10"]},
    lambda r, l: {"type": "choice", "instructions": "Which audience is this text written for?",
                  "criteria": {"general": "general public", "student": "students", "expert": "domain experts"}},
    lambda r, l: {"type": "choice", "instructions": "What tone does the passage have?",
                  "criteria": {"neutral": None, "positive": None, "negative": None, "promotional": "advertising"}},
    lambda r, l: {"type": "yes_no", "instructions": "किया यह पाठ किसी स्थान के बारे में है?" if l != "en" else
                  "Is this text about a place?"},
    lambda r, l: {"type": "choice", "instructions": "If a user submitted this as a support ticket, which queue fits best?",
                  "criteria": {"billing": "payments and refunds", "tech": "technical issue", "spam": "not a real ticket",
                               "general": "general enquiry"}},
    lambda r, l: {"type": "score", "instructions": "How urgent would it be to act on this information?",
                  "criteria": ["not urgent", "low", "medium", "high", "critical"]},
]


def make_requests(wiki_path, seed=0, n_per_lang=400):
    wiki = json.load(open(wiki_path))
    r = random.Random(seed)
    reqs = []
    for lang, texts in wiki.items():
        for t in texts[:n_per_lang]:
            u = r.random()
            n_chars = r.randint(150, 900) if u < 0.55 else (r.randint(900, 3500) if u < 0.95 else r.randint(3500, 12000))
            start = r.randint(0, max(0, len(t) - n_chars)) if len(t) > n_chars else 0
            passage = t[start:start + n_chars]
            if r.random() < 0.25:
                state = {"source": "encyclopedia", "lang": lang, "text": passage}
            else:
                state = passage
            qs = {}
            for i, qi in enumerate(r.sample(range(len(QUESTIONS)), r.randint(1, 4))):
                qs[f"q{i}"] = QUESTIONS[qi](r, lang)
            reqs.append((state, qs))
    r.shuffle(reqs)
    return reqs