"""Single prompt execution entry. Templates live in the DB; LLM egress only via Privacy Gateway.""" from __future__ import annotations from typing import Any import placeholder_mvp # noqa: F401 import placeholder_system # noqa: F401 registers system keys import privacy_placeholders from db import get_db, row_to_dict from entitlements import EntitlementError, check_feature_access, increment_feature_usage from placeholders import PlaceholderError, resolve_template from privacy_gateway import GatewayRequest, PrivacyGatewayError, complete, last_trace, public_trace class EngineError(Exception): def __init__(self, code: str, message: str, status_code: int = 400): super().__init__(message) self.code = code self.message = message self.status_code = status_code def load_active_prompt(slug: str) -> dict: with get_db() as conn: row = row_to_dict( conn.execute( "SELECT * FROM ai_prompts WHERE slug = ? AND active = 1", (slug,), ).fetchone() ) if not row: raise EngineError("prompt_missing", f"Prompt fehlt oder ist inaktiv: {slug}", 404) return row def preview_prompt(prompt: dict, context: dict[str, Any] | None = None) -> dict: template = prompt.get("template") or "" if prompt.get("prompt_type") != "base": raise EngineError("prompt_type_not_ready", "Pipeline- und Workflow-Typen sind vorbereitet, aber noch ohne Executor-Stufen.") try: rendered = resolve_template(template, context or {}) privacy_tokens = privacy_placeholders.validate_tokens(template) except PlaceholderError as exc: raise EngineError(exc.code, exc.message) from exc return { "prompt_id": prompt["id"], "slug": prompt["slug"], "rendered": rendered, "privacy_tokens": privacy_tokens, "llm": False, } def user_source_text(dialogue_context: str) -> str: parts = [] for line in (dialogue_context or "").splitlines(): if line.startswith("user:"): parts.append(line[5:].lstrip()) return "\n".join(parts) def execute_prompt(prompt: dict, profile_id: str, purpose: str, data_class: str, context: dict[str, Any] | None = None) -> dict: preview = preview_prompt(prompt, context) feature_id = prompt.get("required_feature") or "ai_calls" try: check_feature_access(profile_id, feature_id) except EntitlementError as exc: raise EngineError(exc.code, exc.message, exc.status_code) from exc try: ctx = context or {} source_text = user_source_text(ctx.get("dialogue_context") or "") extras = [] if purpose == "journal_generate": extras = [part for part in (ctx.get("existing_text"), ctx.get("writing_profile")) if part] elif purpose == "profile_review": source_text = ctx.get("source_text") or "" extras = [part for part in (ctx.get("review_package"),) if part] if extras: source_text = "\n".join(part for part in (source_text, *extras) if part) elif not source_text: source_text = "\n".join( part for part in (ctx.get("existing_text"), ctx.get("writing_profile")) if part ) result = complete( GatewayRequest( prompt_id=prompt["id"], purpose=purpose, data_class=data_class, profile_id=profile_id, payload={ "rendered": preview["rendered"], "source_text": source_text, "privacy_tokens": preview["privacy_tokens"], "prompt_slug": prompt.get("slug"), }, ) ) except PrivacyGatewayError as exc: raise EngineError(exc.code, exc.message, exc.status_code) from exc increment_feature_usage(profile_id, feature_id) return { **preview, "llm": True, "content": result.content, "provider": result.provider, "trace": public_trace(last_trace()), }