#!/usr/bin/env python3
"""Generate short (3-6 word) standalone semantic examples for targeted patterns."""
import json
import requests
import os
import sys

sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from config import OLLAMA_URL, OLLAMA_MODEL

RAW_DIR = "data/raw"

def generate(lang_code, lang_name, topic, patterns, num_rounds=50):
    filepath = os.path.join(RAW_DIR, f"{lang_code}_short_semantic.jsonl")
    count = 0
    
    for i in range(num_rounds):
        prompt = (
            f"Generate 5 very short {lang_name} SEMANTIC queries (3-6 words only). "
            f"Topic: {topic}\n\n"
            f"Required patterns:\n{patterns}\n\n"
            f"OUTPUT RULES:\n"
            f"- Each query MUST be 3-6 words only\n"
            f"- No greetings, no commands, no chit-chat\n"
            f"- Self-contained semantic content (personal fact or preference)\n"
            f"- Use different names/items/professions each time\n"
            f"- Vary the sentence structure\n"
            f"- Output ONLY 5 lines of valid JSONL, nothing else\n"
            f'Format: {{"text": "<query>", "language": "{lang_code}", "label": "SEMANTIC"}}'
        )
        
        try:
            resp = requests.post(OLLAMA_URL, json={
                "model": OLLAMA_MODEL,
                "messages": [{"role": "user", "content": prompt}],
                "stream": False,
                "options": {"temperature": 0.9, "num_predict": 1024}
            }, timeout=60)
            
            content = resp.json()["message"]["content"]
            added = 0
            
            with open(filepath, "a") as f:
                for line in content.strip().split("\n"):
                    line = line.strip()
                    if not line or line.startswith("```"):
                        continue
                    try:
                        obj = json.loads(line)
                        text = obj.get("text", "")
                        word_count = len(text.split())
                        if (obj.get("label") == "SEMANTIC" 
                            and obj.get("language") == lang_code
                            and 3 <= word_count <= 7
                            and len(text) < 80):
                            f.write(json.dumps(obj, ensure_ascii=False) + "\n")
                            added += 1
                    except:
                        pass
            
            count += added
            
        except Exception as e:
            pass
        
        sys.stdout.write(f"\r  {lang_name}: round {i+1}/{num_rounds}, {count} total   ")
        sys.stdout.flush()
    
    print(f"\n  Done: {count} examples -> {filepath}")
    return count

if __name__ == "__main__":
    os.makedirs(RAW_DIR, exist_ok=True)
    
    print("Generating short Hindi SEMANTIC queries...")
    generate("hi", "Hindi", 
        "Personal identity, preferences, and relationships",
        '- "mera naam X hai" (Amit, Priya, Vikram, Sunita, Arjun, Kavita, etc.)\n'
        '- "mujhe X pasand/nahi pasand hai" (food, activities, etc.)\n'
        '- "main X hoon" (doctor, teacher, engineer, artist, student, lawyer)\n'
        '- "meri X Y hai" (family, possessions)\n'
        '- "mera X Y hai" (possessions, attributes)\n'
        '- "mujhe X se allergy hai"\n'
        '- "meri umar X hai"\n'
        'Output 3-6 word Hindi Devanagari sentences ONLY.',
        num_rounds=80)
    
    print("\nGenerating short English SEMANTIC queries...")
    generate("en", "English",
        "Personal identity, preferences, and relationships",
        '- "my name is X"\n'
        '- "I am a X" (doctor, teacher, engineer, artist, etc.)\n'
        '- "I love/like/hate/enjoy X"\n'
        '- "my favorite X is Y"\n'
        '- "I prefer X over Y"\n'
        '- "my X is a Y" (family relationships)\n'
        '- "I work as a X"\n'
        '- "I live in X"\n'
        'Output 3-6 word English sentences ONLY.',
        num_rounds=80)

    print("\nDone!")