114 lines
4.3 KiB
Python
114 lines
4.3 KiB
Python
"""Build a structured action plan from a natural-language prompt (or JSON bulk)."""
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from __future__ import annotations
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import json
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from core.db import SessionLocal
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from apps.ai_core.ollama_client import get_llm
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from apps.ai_core.tools import describe_for_prompt, get_tool, validate_args
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from apps.catalog.models import Category, Product
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SYSTEM_PROMPT = """You are an admin assistant for an e-commerce shop.
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You help the operator perform tasks by producing a STRUCTURED PLAN of tool calls.
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You MUST NEVER execute anything. You only propose cards that the operator confirms.
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Output format (STRICT):
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Reply with ONLY a JSON object of the shape {"cards": [ ... ]}.
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Each card: {"tool": "<tool-name>", "args": {...}, "missing": [], "preview": "German summary", "notes": ""}.
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Rules:
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- Only use tools from the provided TOOL CATALOG. If no tool applies, return {"cards": []}.
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- NEVER emit a single card that aggregates multiple items.
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If the user provides JSON with multiple items (bulk) → produce ONE card per item.
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If the user asks to change something about ALL or MULTIPLE existing products/categories
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→ produce ONE card per matching item from the SHOP STATE snapshot, with its exact id.
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Examples:
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"setze alle preise auf 1" on 3 products → 3 cards, each {"tool":"catalog.product.update","args":{"id":<real id>,"price":1},...}
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NOT one card with id=null or "all".
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- Numbers must be numbers in JSON (not strings). Omit optional fields instead of sending null.
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- Stay concise in "preview".
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"""
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def _shop_state_snapshot() -> dict:
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"""Compact snapshot of current shop state for the planner. Keep it small."""
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db = SessionLocal()
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try:
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products = [
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{"id": p.id, "sku": p.sku, "name_de": (p.name or {}).get("de", ""), "price": float(p.price)}
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for p in db.query(Product).order_by(Product.id).all()
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]
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categories = [
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{"id": c.id, "slug": c.slug, "name_de": (c.name or {}).get("de", "")}
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for c in db.query(Category).order_by(Category.id).all()
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]
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return {"products": products, "categories": categories}
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finally:
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db.close()
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def build_plan(user_prompt: str) -> list[dict]:
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tools = describe_for_prompt(role="admin")
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state = _shop_state_snapshot()
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user_msg = (
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f"TOOL CATALOG (JSON):\n{json.dumps(tools, ensure_ascii=False)}\n\n"
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f"SHOP STATE (current products & categories):\n{json.dumps(state, ensure_ascii=False)}\n\n"
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f"USER REQUEST:\n{user_prompt}\n\n"
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"Reply with ONLY the JSON object described in the rules."
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)
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try:
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result = get_llm().chat_json(SYSTEM_PROMPT, user_msg)
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except Exception as e: # noqa: BLE001
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return [
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{
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"tool": "_error",
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"args": {},
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"missing": [],
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"preview": f"Planer-Fehler: {e}",
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"notes": "LLM antwortete nicht verwertbar. Prompt umformulieren.",
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}
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]
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if isinstance(result, list):
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cards = result
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elif isinstance(result, dict) and isinstance(result.get("cards"), list):
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cards = result["cards"]
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else:
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cards = []
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# Validate and annotate
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clean: list[dict] = []
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for card in cards:
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if not isinstance(card, dict):
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continue
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name = card.get("tool", "")
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args = card.get("args") or {}
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spec = get_tool(name)
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if spec:
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# Trust only server-side required-field validation, not LLM-supplied missing
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missing = validate_args(spec, args)
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clean.append(
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{
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"tool": name,
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"args": args,
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"missing": missing,
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"preview": card.get("preview", ""),
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"notes": card.get("notes", ""),
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"schema": spec.args_schema,
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}
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)
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else:
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clean.append(
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{
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"tool": name,
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"args": args,
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"missing": list(card.get("missing") or []),
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"preview": card.get("preview", f"Unbekanntes Tool: {name}"),
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"notes": "tool not in catalog",
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"schema": {"type": "object", "properties": {}},
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}
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)
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return clean
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