rebase
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Mikan
301
app/engine/world_builder.py
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301
app/engine/world_builder.py
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"""World Builder — generates a new world from a preset or form, then intro scene.
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Flow (see §9.1 of TDD):
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1. Receive template (preset or form).
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2. Generate schemas + environment_schema + rules + time_schema.
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3. Generate initial environment (player + current_location + plot_rails).
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4. Generate initial entities (locations, NPCs, items).
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5. Generate intro scene + suggested actions.
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6. Mark world status='ready'.
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"""
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from __future__ import annotations
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import json
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import uuid
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from typing import Any
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.core.llm import LlmClient, MockLlmClient
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from app.core.logging import get_logger
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from app.core.state_validator import validate_world
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from app.core.time_utils import summarize_schemas
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from app.engine.sse import SseEmitter
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from app.engine.tools.base import ToolContext, get_registry
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from app.models import World, WorldPreset
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from app.prompts.registry import get_prompt
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_logger = get_logger(__name__)
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async def run_world_builder(
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*,
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db: AsyncSession,
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world: World,
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player_name: str,
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notes: str | None,
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llm: LlmClient | MockLlmClient,
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sse: SseEmitter,
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preset: WorldPreset | None = None,
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) -> None:
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"""Run the full world_builder flow for a draft world.
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Emits SSE events and updates the world row in place. On error, emits `error`
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and returns (the world stays in status='draft').
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"""
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try:
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# ---- Step 1: Generate schemas / rules / time_schema / environment_schema
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await sse.emit("step", {"step": "generating_schema", "message": "Generating world schema..."})
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schema_prompt = get_prompt("world_builder_schema", "en").format(
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mode="preset" if preset else "form",
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form_data=json.dumps({}, ensure_ascii=False),
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preset_name=preset.name if preset else "",
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player_name=player_name,
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language=world.language,
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notes=notes or "",
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)
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# If we have a preset, use its schemas directly instead of calling LLM
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if preset and preset.schemas:
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world.schemas = preset.schemas
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world.environment_schema = preset.environment_schema
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world.rules = preset.rules
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world.time_schema = preset.time_schema
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world.environment = dict(preset.environment_initial)
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else:
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resp = await llm.complete(
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stage="world_builder_schema",
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messages=[{"role": "system", "content": schema_prompt}],
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temperature=0.5,
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max_tokens=4096,
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world_id=world.id,
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session=db,
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)
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try:
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content = resp["message"].get("content", "")
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# Strip markdown fences if present
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content = _strip_code_fence(content)
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schema_data = json.loads(content)
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except (json.JSONDecodeError, KeyError) as e:
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await sse.error("schema_generation_failed", f"Invalid JSON from LLM: {e}")
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return
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world.schemas = schema_data.get("schemas", [])
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world.environment_schema = schema_data.get("environment_schema", [])
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world.rules = schema_data.get("rules", [])
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world.time_schema = schema_data.get("time_schema", {"hours_in_day": 24, "initial_date": "day_1_hour_8"})
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world.environment = schema_data.get("environment_initial", {})
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# Ensure player name is set
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env = dict(world.environment or {})
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if isinstance(env.get("player"), dict):
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env["player"]["name"] = player_name
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else:
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env["player"] = {"name": player_name}
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world.environment = env
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await db.commit()
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await sse.emit("world_schema_generated", {
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"schemas": world.schemas, "environment_schema": world.environment_schema,
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})
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# ---- Step 2: Generate environment (skip if preset provided one)
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if not preset or not preset.environment_initial:
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await sse.emit("step", {"step": "generating_environment", "message": "Generating environment..."})
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env_prompt = get_prompt("world_builder_env", "en").format(
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world_name=world.name,
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world_description=world.description or "",
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language=world.language,
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rules="\n".join(f"- {r}" for r in (world.rules or [])),
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schemas_summary=summarize_schemas(world.schemas or []),
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environment_schema_json=json.dumps(world.environment_schema, ensure_ascii=False, indent=2),
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player_name=player_name,
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)
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resp = await llm.complete(
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stage="world_builder_env",
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messages=[{"role": "system", "content": env_prompt}],
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temperature=0.6,
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max_tokens=2048,
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world_id=world.id,
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session=db,
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)
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try:
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content = _strip_code_fence(resp["message"].get("content", ""))
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env_data = json.loads(content)
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env_data.setdefault("player", {}).setdefault("name", player_name)
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world.environment = env_data
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except (json.JSONDecodeError, KeyError) as e:
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await sse.error("env_generation_failed", f"Invalid env JSON: {e}")
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return
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await db.commit()
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await sse.emit("environment_generated", {"environment": world.environment})
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# Validate world
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ok, errors = validate_world({
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"name": world.name, "language": world.language,
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"schemas": world.schemas, "environment_schema": world.environment_schema,
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"environment": world.environment, "plot_rails": world.plot_rails,
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"current_time": world.current_time,
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})
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if not ok:
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await sse.error("world_invalid", "World validation failed", details=errors)
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return
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# ---- Step 3: Generate entities via tool-calling loop
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await sse.emit("step", {"step": "generating_entities", "message": "Generating entities..."})
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await _run_tool_loop(
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db=db, world=world, llm=llm, sse=sse,
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stage="world_builder_entities",
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system_prompt=get_prompt("world_builder_entities", "en").format(
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world_name=world.name,
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world_description=world.description or "",
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language=world.language,
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schemas_summary=summarize_schemas(world.schemas or []),
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environment_json=json.dumps(world.environment, ensure_ascii=False, indent=2),
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max_substeps=12,
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),
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terminal_tool="submit_plan",
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max_substeps=12,
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settings={}, # world_builder uses fixed defaults
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)
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await db.commit()
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await sse.emit("entities_generated", {"world_id": str(world.id)})
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# ---- Step 4: Generate intro scene
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await sse.emit("step", {"step": "generating_intro", "message": "Generating intro scene..."})
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from sqlalchemy import select
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from app.models import Entity
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entities = (
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await db.execute(
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select(Entity).where(
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Entity.world_id == world.id, Entity.deleted_at.is_(None)
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)
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)
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).scalars().all()
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entities_summary = "\n".join(
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f"- {e.entity_type}: {e.name}" for e in entities[:20]
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)
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intro_prompt = get_prompt("intro_scene", "en").format(
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world_name=world.name,
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world_description=world.description or "",
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language=world.language,
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current_time=world.current_time,
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environment_json=json.dumps(world.environment, ensure_ascii=False, indent=2),
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plot_rails_json=json.dumps(world.plot_rails, ensure_ascii=False, indent=2),
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entities_summary=entities_summary,
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)
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# Phase 2: scene_text + delta_time
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scene_result = await _run_tool_loop(
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db=db, world=world, llm=llm, sse=sse,
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stage="intro_scene",
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system_prompt=intro_prompt,
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terminal_tool="submit_step",
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max_substeps=3,
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settings={},
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)
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scene_text = ""
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delta_time = "hours_1"
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if scene_result and scene_result.get("ok"):
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scene_text = scene_result.get("data", {}).get("scene_text", "")
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delta_time = scene_result.get("data", {}).get("delta_time", "hours_1")
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world.intro_scene = scene_text
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from app.core.time_utils import advance_time
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world.current_time = advance_time(world.current_time, delta_time, world.time_schema)
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await db.commit()
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await sse.emit("intro_scene_complete", {
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"text": scene_text, "delta_time": delta_time, "current_time": world.current_time,
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})
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# Mark ready
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world.status = "ready"
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await db.commit()
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await sse.done({"world_id": str(world.id), "status": "ready"})
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except Exception as e: # noqa: BLE001
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_logger.exception("world_builder_failed", world_id=str(world.id), error=str(e))
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await sse.error("internal_error", str(e))
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def _strip_code_fence(text: str) -> str:
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"""Remove ```json ... ``` fences if present."""
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s = text.strip()
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if s.startswith("```"):
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# Remove first line (``` or ```json)
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s = s.split("\n", 1)[1] if "\n" in s else s
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if s.endswith("```"):
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s = s[:-3]
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return s.strip()
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async def _run_tool_loop(
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*,
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db: AsyncSession,
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world: World,
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llm: LlmClient | MockLlmClient,
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sse: SseEmitter,
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stage: str,
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system_prompt: str,
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terminal_tool: str,
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max_substeps: int,
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settings: dict[str, Any],
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) -> dict[str, Any] | None:
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"""Generic tool-calling loop. Returns the result of the terminal tool call."""
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registry = get_registry()
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ctx = ToolContext(
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db=db, world=world, stage=stage,
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sse_emitter=sse.emit,
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)
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messages: list[dict[str, Any]] = [
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{"role": "system", "content": system_prompt},
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{"role": "user", "content": f"Begin {stage}."},
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]
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tools = registry.to_openai_format(stage)
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last_terminal_result: dict[str, Any] | None = None
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for substep in range(max_substeps):
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await sse.emit("llm_call_start", {"stage": stage, "model": getattr(llm, "_model", "mock")})
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resp = await llm.complete(
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stage=stage,
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messages=messages,
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tools=tools,
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temperature=0.7,
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max_tokens=2048,
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world_id=world.id,
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session=db,
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)
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await sse.emit("llm_call_end", {
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"stage": stage, "latency_ms": resp.get("latency_ms", 0),
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"tokens": (resp.get("prompt_tokens") or 0) + (resp.get("completion_tokens") or 0),
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})
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msg = resp.get("message", {})
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tool_calls = msg.get("tool_calls") or []
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if not tool_calls:
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# No tool calls — append assistant message and ask again
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messages.append({"role": "assistant", "content": msg.get("content", "")})
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messages.append({
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"role": "user",
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"content": "You must call a tool. Available terminal tool: " + terminal_tool,
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})
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continue
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messages.append(msg)
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for tc in tool_calls:
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fn = tc.get("function", {})
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tname = fn.get("name", "")
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try:
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targs = json.loads(fn.get("arguments") or "{}")
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except json.JSONDecodeError:
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targs = {}
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result = await registry.execute(tname, targs, ctx)
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# Tool result as a tool message
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messages.append({
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"role": "tool",
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"tool_call_id": tc.get("id", ""),
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"name": tname,
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"content": json.dumps(result.to_dict(), ensure_ascii=False),
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})
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if tname == terminal_tool:
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last_terminal_result = result.to_dict()
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return last_terminal_result
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# If we exhausted substeps without terminal, return None
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return last_terminal_result
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