"""
Condition 1: Direct Generation (Baseline)

Single LLM call asking for creative ideas directly.
No attribute decomposition, no expert perspectives.
"""

import sys
from pathlib import Path

# Add backend to path for imports
sys.path.insert(0, str(Path(__file__).parent.parent.parent / "backend"))

from typing import List, Dict, Any
from app.services.llm_service import ollama_provider, extract_json_from_response
from experiments.config import MODEL, TEMPERATURE, IDEAS_DIRECT, PROMPT_LANGUAGE


def get_direct_generation_prompt(query: str, idea_count: int, lang: str = "en") -> str:
    """Generate prompt for direct idea generation."""
    if lang == "en":
        return f"""/no_think
Generate {idea_count} creative and innovative ideas for "{query}".

Requirements:
1. Each idea should be specific and actionable
2. Ideas should be diverse, covering different aspects and applications
3. Include both practical improvements and creative innovations
4. Ideas should be 15-30 words each

Return JSON only:
{{"ideas": ["idea 1", "idea 2", "idea 3", ...]}}

Generate exactly {idea_count} ideas."""
    else:
        return f"""/no_think
為「{query}」生成 {idea_count} 個創意點子。

要求：
1. 每個點子要具體可行
2. 點子要多元，涵蓋不同面向和應用
3. 包含實用改進和創意創新
4. 每個點子 15-30 字

只回傳 JSON：
{{"ideas": ["點子1", "點子2", "點子3", ...]}}

生成正好 {idea_count} 個點子。"""


async def generate_ideas(
    query: str,
    model: str = None,
    temperature: float = None,
    idea_count: int = None,
    lang: str = None
) -> Dict[str, Any]:
    """
    Generate ideas using direct LLM generation (C1 baseline).

    Args:
        query: The object/concept to generate ideas for
        model: LLM model to use (default from config)
        temperature: Generation temperature (default from config)
        idea_count: Number of ideas to generate (default from config)
        lang: Language for prompts (default from config)

    Returns:
        Dict with ideas and metadata
    """
    model = model or MODEL
    temperature = temperature or TEMPERATURE
    idea_count = idea_count or IDEAS_DIRECT
    lang = lang or PROMPT_LANGUAGE

    prompt = get_direct_generation_prompt(query, idea_count, lang)

    response = await ollama_provider.generate(
        prompt=prompt,
        model=model,
        temperature=temperature
    )

    result = extract_json_from_response(response)
    ideas = result.get("ideas", [])

    return {
        "condition": "c1_direct",
        "query": query,
        "ideas": ideas,
        "idea_count": len(ideas),
        "metadata": {
            "model": model,
            "temperature": temperature,
            "prompt_language": lang,
            "mechanism": "direct_llm_generation"
        }
    }


# For testing
if __name__ == "__main__":
    import asyncio

    async def test():
        result = await generate_ideas("Chair")
        print(f"Generated {result['idea_count']} ideas:")
        for i, idea in enumerate(result['ideas'], 1):
            print(f"  {i}. {idea}")

    asyncio.run(test())