"""Copywriter agent: generates product descriptions and social captions."""

from jinja2 import Template

from agents.llm import LLMClient
from agents.models import AgentTrace, CatalogerOutput, CopywriterOutput

SYSTEM_PROMPT = (
    "You are a warm, authentic copywriter for handmade crafts. You write "
    "product descriptions and social media captions that feel personal and "
    "artisan -- never corporate or salesy.\n\n"
    "Your tone: warm, genuine, storytelling, inviting. Write as if a real "
    "craftsperson is sharing their work.\n\n"
    "Always respond with valid JSON."
)

USER_TEMPLATE = Template(
    "Write marketing copy for this {{ craft_type }} item:\n\n"
    "Category: {{ catalog.category }} / {{ catalog.sub_category }}\n"
    "Materials: {{ catalog.materials | join(', ') }}\n"
    "Colors: {{ catalog.colors | join(', ') }}\n"
    "Size: {{ catalog.estimated_size }}\n"
    "Complexity: {{ catalog.complexity }}\n"
    "{% if user_notes %}Creator's notes: {{ user_notes }}{% endif %}\n\n"
    "Provide:\n"
    "1. A catchy product title (under 60 characters)\n"
    "2. A short description (1-2 sentences)\n"
    "3. A longer description (1 paragraph, warm and personal)\n"
    "4. Exactly 3 Instagram caption variations (each under 200 characters, "
    "include relevant hashtags)"
)


async def run(
    llm: LLMClient,
    craft_type: str,
    catalog: CatalogerOutput,
    user_notes: str | None = None,
) -> tuple[CopywriterOutput, AgentTrace]:
    prompt = USER_TEMPLATE.render(
        craft_type=craft_type,
        catalog=catalog,
        user_notes=user_notes,
    )
    result, duration_ms = await llm.agenerate(
        system=SYSTEM_PROMPT,
        prompt=prompt,
        output_schema=CopywriterOutput,
        max_tokens=1024,
    )
    trace = AgentTrace(
        agent_name="copywriter",
        input_text=prompt,
        output_data=result.model_dump(),
        duration_ms=duration_ms,
        model_id=llm.model_id,
    )
    return result, trace