#!/usr/bin/env python3
"""
Human-in-the-loop labeling tool for real-world crypto samples.
Creates high-quality labeled dataset for LoRA retraining.
"""

import json
import sys
from pathlib import Path
from datetime import datetime

SAMPLE_FILE = Path("/mnt/dolphinng5_predict/sentiment_engine/data/real_world_samples.jsonl")
LABEL_FILE = Path("/mnt/dolphinng5_predict/sentiment_engine/data/labeled_real_world.jsonl")

SENTIMENT_LABELS = {
    'b': 'Bearish',
    'r': 'Bullish',  # 'r' for bullish (green/up)
    'n': 'Neutral',
}

EMOTION_LABELS = {
    'g': 'greed',
    'f': 'fear', 
    'j': 'joy',
    'a': 'anger',
    's': 'sadness',
    'n': 'neutral',
}

def load_samples():
    samples = []
    with open(SAMPLE_FILE) as f:
        for line in f:
            samples.append(json.loads(line.strip()))
    return samples

def load_existing_labels():
    labeled = set()
    if LABEL_FILE.exists():
        with open(LABEL_FILE) as f:
            for line in f:
                item = json.loads(line.strip())
                labeled.add(item.get('text', '')[:100])  # Use first 100 chars as key
    return labeled

def save_label(item, sentiment, emotions, confidence, notes=''):
    record = {
        **item,
        'labels': {
            'sentiment': sentiment,
            'emotions': emotions,
            'confidence': confidence,
        },
        'human_labeled': True,
        'labeled_at': datetime.now().isoformat(),
        'notes': notes,
    }
    with open(LABEL_FILE, 'a') as f:
        f.write(json.dumps(record) + '\n')

def clear_screen():
    print('\033[2J\033[H', end='')

def print_header(idx, total, item):
    clear_screen()
    print('=' * 70)
    print(f'LABELING: {idx+1}/{total}  |  Source: {item["source_id"]}')
    print('=' * 70)
    print(f'\nTITLE: {item["title"]}')
    print(f'\nTEXT: {item["text"][:400]}...')
    print(f'\nURL: {item["url"]}')
    print()

def get_sentiment():
    print('SENTIMENT:')
    print('  [B] Bearish  -  [R] Bullish  -  [N] Neutral')
    while True:
        choice = input('  Choice [B/R/N]: ').strip().lower()
        if choice in SENTIMENT_LABELS:
            return SENTIMENT_LABELS[choice]
        print('  Invalid. Use B, R, or N')

def get_emotions():
    print('\nEMOTIONS (multi-select, comma-separated):')
    print('  [G] Greed  [F] Fear  [J] Joy  [A] Anger  [S] Sadness  [N] Neutral')
    while True:
        choice = input('  Emotions [G,F,J,A,S,N]: ').strip().lower()
        if not choice:
            return []
        selected = []
        for c in choice.replace(' ', '').split(','):
            if c in EMOTION_LABELS:
                selected.append(EMOTION_LABELS[c])
        if selected:
            return selected
        print('  Invalid. Use G,F,J,A,S,N')

def get_confidence():
    while True:
        try:
            conf = float(input('\nConfidence [0.0-1.0]: ').strip())
            if 0 <= conf <= 1:
                return conf
            print('  Must be between 0 and 1')
        except ValueError:
            print('  Invalid number')

def main():
    samples = load_samples()
    labeled_keys = load_existing_labels()
    
    # Filter unlabeled
    unlabeled = []
    for item in samples:
        key = item['text'][:100]
        if key not in labeled_keys:
            unlabeled.append(item)
    
    print(f'Total: {len(samples)} | Already labeled: {len(samples)-len(unlabeled)} | Remaining: {len(unlabeled)}')
    if not unlabeled:
        print('All samples labeled!')
        return
    
    input('Press Enter to start labeling...')
    
    for idx, item in enumerate(unlabeled):
        print_header(idx, len(unlabeled), item)
        
        sentiment = get_sentiment()
        emotions = get_emotions()
        confidence = get_confidence()
        notes = input('\nNotes (optional): ').strip()
        
        save_label(item, sentiment, emotions, confidence, notes)
        print(f'\n✅ Saved as {sentiment} | {emotions} | conf={confidence}')
        input('Press Enter for next...')
    
    print('\n🎉 All samples labeled!')
    print(f'Labels saved to: {LABEL_FILE}')

if __name__ == '__main__':
    main()