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PromptEngineer — enriches user prompts with heritage style keywords.
SDXL-aware: builds long prompts (~75-150 tokens) that exploit SDXL's
two-encoder architecture (G+XL text encoders). Negative prompts are
also style-aware.
"""
from __future__ import annotations
import logging
from typing import List
from .base import AgentClient, AgentResponse
from config.styles import StyleSpec
log = logging.getLogger(__name__)
SYSTEM_PROMPT = """You are an expert prompt engineer for Stable Diffusion XL, specialized in Indian heritage art.
Your task: take a user's plain description and enrich it with concrete visual keywords
for the chosen heritage style. Aim for 60-120 words. Be specific about:
- Composition (perspective, framing)
- Color palette (named pigments, not hex codes)
- Linework and brushwork quality
- Iconographic motifs authentic to the style
- Border / frame treatment
- Negative prompt should list things to avoid (modern, photographic, 3D, etc.)
Output STRICT JSON:
{"prompt": "<enriched prompt 60-120 words>",
"negative_prompt": "<negative prompt 20-40 words>",
"style_summary": "<3-word summary>"}"""
class PromptEngineer:
def __init__(self, client: AgentClient | None = None) -> None:
self.client = client or AgentClient(temperature=0.6, max_tokens=900)
def enrich(self, user_prompt: str, style: StyleSpec) -> AgentResponse:
"""Return enriched prompt + negative + summary."""
if self.client.enabled:
user_msg = (
f"User prompt: {user_prompt!r}\n"
f"Style: {style.id} ({style.display_name})\n"
f"Style region: {style.region}\n"
f"Authentic motifs: {', '.join(style.cultural_keywords)}\n"
f"Reference palette: {', '.join(style.palette)}"
)
resp = self.client.chat(system_prompt=SYSTEM_PROMPT, user_prompt=user_msg)
if resp.ok:
resp.content = self._extract_prompt_text(resp.content, user_prompt, style)
return resp
# Heuristic fallback
return AgentResponse(
content=self._heuristic_enrich(user_prompt, style),
model=self.client.model,
ok=True,
error="heuristic_fallback",
)
@staticmethod
def _extract_prompt_text(raw: str, user_prompt: str, style: StyleSpec) -> str:
"""Parse agent JSON; if parsing fails, return a heuristic fallback."""
import json, re
try:
data = json.loads(raw)
return data.get("prompt", raw)
except Exception:
m = re.search(r'"prompt"\s*:\s*"([^"]+)"', raw)
if m:
return m.group(1).replace("\\n", " ").replace('\\"', '"')
return PromptEngineer._heuristic_enrich(user_prompt, style)
@staticmethod
def build_negative(style: StyleSpec, extra: List[str] | None = None) -> str:
"""Compose the negative prompt for a style."""
base = list(style.negative_tags)
# SDXL-universal negatives
universal = [
"low quality", "jpeg artifacts", "watermark", "signature",
"text", "logo", "cropped", "out of frame", "duplicate",
"extra limbs", "deformed", "blurry",
]
parts = base + universal
if extra:
parts.extend(extra)
return ", ".join(parts)
@staticmethod
def _heuristic_enrich(user_prompt: str, style: StyleSpec) -> str:
tags = ", ".join(style.prompt_tags)
return (
f"{user_prompt.strip().rstrip('.')}, {tags}, "
"intricate detail, traditional composition, "
"museum-quality heritage artwork, high resolution"
)
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