#!/usr/bin/env python
"""PALIMPSESTE — Train fluid conversation model with expanded corpus.

Combines killer_corpus + conversation_corpus + trivia for maximum breadth.
"""
import json, sys, time, os
sys.path.insert(0, '.')
sys.path.insert(0, 'examples')

from palimseste.lm import PalimpsesteForCausalLM, PalimpsesteConfig
from palimseste.hf import HFPalimpsesteLM
from palimseste.bpe import BPETokenizer
from killer_corpus import get_killer_corpus
from conversation_corpus import get_conversation_corpus

# Load ALL data
pairs = list(get_killer_corpus())
pairs.extend(list(get_conversation_corpus()))

try:
    with open('trivia_qa_pairs.json') as f:
        trivia = json.load(f)
    pairs.extend([(item['q'].lower(), item['a'].lower()) for item in trivia[:3000]])
    print(f'Loaded {len(trivia[:3000])} trivia pairs', flush=True)
except FileNotFoundError:
    pass

print(f'Total pairs: {len(pairs)}', flush=True)

# Config
cfg = PalimpsesteConfig(
    D=20_000,
    context_window=256,
    kernel_radius=400,
    kernel_min_weight=1e-6,
    temperature=0.0,
)
print(f'Config: D={cfg.D} ctx={cfg.context_window} temp={cfg.temperature}', flush=True)

lm = PalimpsesteForCausalLM(config=cfg)

# BPE tokenizer
print('Training BPE tokenizer...', flush=True)
full_text = ' '.join(q + ' ' + a for q, a in pairs)
bpe = BPETokenizer(encoder=lm.encoder, vocab_size=2000)
bpe.train(full_text, verbose=False)
lm.attach_tokenizer(bpe)
print(f'BPE vocab: {bpe.vocab_size_actual}', flush=True)

# Train
print('Training...', flush=True)
t0 = time.perf_counter()
n = lm.train_on_qa_pairs(pairs, verbose=False)
dt = time.perf_counter() - t0
print(f'Trained: {n:,} tokens in {dt:.0f}s ({n/dt:.0f} tok/s)', flush=True)
print(f'|M| = {len(lm.mem):,}', flush=True)

# Test — conversation, creative, code, summarization
print('\n=== FLUID CONVERSATION TESTS ===', flush=True)
tests = [
    # Core Q/A
    'who are you',
    'what is python',
    # Conversation flow
    'that is interesting',
    'tell me more',
    'thanks for the help',
    # Creative writing
    'write a poem about the sea',
    'write a haiku',
    'describe a sunset',
    # Code
    'write a python function to reverse a string',
    'how to read a file in python',
    # Summarization
    'summarize this: python is a high-level programming language known for its clear syntax and large standard library. it supports multiple paradigms including object-oriented and functional programming.',
    # Opinions
    'why is python popular',
    'what is the best programming language',
    # Emotional
    'i am sad',
    'you are amazing',
]
for q in tests:
    t0 = time.perf_counter()
    r = lm.respond(q, max_new_tokens=200)
    dt = time.perf_counter() - t0
    print(f'  [{dt:.1f}s] {q}', flush=True)
    print(f'        -> {r}', flush=True)

# Save
print('\nSaving...', flush=True)
hf = HFPalimpsesteLM(config=lm.config)
hf.mem = lm.mem; hf.phi = lm.phi; hf.encoder = lm.encoder
hf.tokenizer = lm.tokenizer; hf._self_hv = lm._self_hv; hf._token_bits_cache = None
hf.save_pretrained('./palimpseste-max', tune_lsh=False)
sz = os.path.getsize('./palimpseste-max/palimpseste_memory.bin')
print(f'Saved: {sz/1024/1024:.0f} MB', flush=True)
print('DONE', flush=True)