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Dejvino
2026-06-30 20:03:53 +02:00
parent e9a1187f34
commit 545d3bcac0
20 changed files with 1633 additions and 1686 deletions
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pre-commit.sh
+30 -12
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@@ -1,15 +1,33 @@
#!/bin/bash
ERRORS=$(python3 -c "import os; [f for f in os.listdir('./tools') if f.endswith('.py') and os.path.getsize(os.path.join('./tools', f)) > 2048]")
if [ -z "$ERRORS" ]; then
echo "Compiling tools/*.py..."
if python3 -m compileall tools/*.py; then
echo "OK"
else
echo "Compilation failed"
exit 1
fi
else
echo "You need to refactor this:"
echo "$ERRORS"
THRESHOLD=30000 # bytes — flag files over ~30 KB
# Check all .py files in tools/ and tools/engine_lib/
OVERSIZED=$(python3 -c "
import os
threshold = $THRESHOLD
dirs = ['./tools', './tools/engine_lib']
for d in dirs:
if not os.path.isdir(d):
continue
for f in sorted(os.listdir(d)):
if not f.endswith('.py'):
continue
path = os.path.join(d, f)
size = os.path.getsize(path)
if size > threshold:
print(f'{path} ({size} bytes)')
")
if [ -n "$OVERSIZED" ]; then
echo "Oversized files (>${THRESHOLD} bytes) — consider refactoring:"
echo "$OVERSIZED"
exit 1
fi
echo "Compiling tools/*.py and tools/engine_lib/*.py..."
if python3 -m compileall tools/*.py tools/engine_lib/*.py; then
echo "OK"
else
echo "Compilation failed"
exit 1
fi
tools/engine.py
+58 -850
View File
@@ -2,249 +2,86 @@
"""
engine.py — The Chaos Game Engine
Owns the LLM interaction, prompt assembly, response parsing, and game state
persistence. The TUI (run.py) calls this module — they do not depend on each
other, only on the shared session/ file layout.
Split into sub-modules: paths, models, prompts, state, tools_handler, llm.
Thin coordinator that owns the GameEngine class. All heavy lifting is
delegated to sub-modules: paths, models, prompts, config, context,
state, tools_handler, llm, validation, parsing, strategies.
"""
from __future__ import annotations
import json
import re
import sys
from collections import Counter
from datetime import datetime
from pathlib import Path
from typing import Iterator, Optional
from paths import (
CHAR_PATH, WORLD_PATH, BOOK_PATH, CONFIG_PATH, LOG_DIR,
)
from models import GenerationResult, TurnResult
from prompts import SYSTEM_PROMPT, PROSE_PROMPT
import state # read_file, read_recent_log, read_recent_book, truncate_world, append_llm_log
from tools_handler import (
execute_tool, describe_tool_action, describe_change,
parse_changes_block, extract_tool_calls,
)
from llm import set_llm_env, call_llm
from engine_lib.paths import CONFIG_PATH
from engine_lib.models import GenerationResult, TurnResult
from engine_lib import config
from engine_lib import strategies
# ── Game Engine ────────────────────────────────────────────────────────────
class GameEngine:
"""Owns the LLM interaction and game state persistence."""
"""Owns configuration and delegates generation to standalone strategies."""
def __init__(self, session_dir: str | Path | None = None):
from paths import SESSION_DIR
from engine_lib.paths import SESSION_DIR
self.session_dir = Path(session_dir) if session_dir else SESSION_DIR
self.config: dict = {}
self._load_config()
self.config = config.load_config(CONFIG_PATH)
# ── Config ──────────────────────────────────────────────────────────
def _load_config(self) -> None:
if not CONFIG_PATH.exists():
print(
"No session/config.json found. Creating default.\n"
"Edit the model field (e.g. 'ollama/llama3.1', 'openai/gpt-4', "
"'anthropic/claude-sonnet-4-20250514') and set api_key if needed.",
file=sys.stderr,
)
self.config = {
"llm": {
"model": "ollama/llama3.1",
"api_key": None,
"api_base": None,
"temperature": 0.8,
"max_tokens": 300,
}
}
self._save_config()
else:
raw = CONFIG_PATH.read_text()
self.config = json.loads(raw)
llm = self.config.get("llm", {})
if not llm.get("api_key"):
llm["api_key"] = None
def _save_config(self) -> None:
CONFIG_PATH.parent.mkdir(parents=True, exist_ok=True)
CONFIG_PATH.write_text(json.dumps(self.config, indent=2) + "\n")
# ── Config accessors ────────────────────────────────────────────────
@property
def model(self) -> str:
return self.config.get("llm", {}).get("model", "ollama/llama3.1")
return config.get_model(self.config)
@property
def api_key(self) -> str | None:
return self.config.get("llm", {}).get("api_key")
return config.get_api_key(self.config)
@property
def api_base(self) -> str | None:
return self.config.get("llm", {}).get("api_base")
return config.get_api_base(self.config)
@property
def temperature(self) -> float:
return self.config.get("llm", {}).get("temperature", 0.8)
return config.get_temperature(self.config)
@property
def max_tokens(self) -> int:
return self.config.get("llm", {}).get("max_tokens", 512)
return config.get_max_tokens(self.config)
@property
def timeout(self) -> int:
return self.config.get("llm", {}).get("timeout", 120)
return config.get_timeout(self.config)
# ── Context Assembly ────────────────────────────────────────────────
def build_system_prompt(self) -> str:
"""Assemble the system prompt with current game state."""
char = state.read_file(CHAR_PATH) or "*No character sheet.*"
world = state.truncate_world(state.read_file(WORLD_PATH) or "") or "*No world state.*"
log = state.read_recent_log()
story = state.read_recent_book()
return SYSTEM_PROMPT.substitute(
character=char, world=world, log=log, story=story
)
def build_user_message(
self,
player_action: str | None = None,
last_prompt: str | None = None,
**kwargs: str | None,
) -> str:
"""Build the user message for this turn's LLM call."""
if kwargs:
raise TypeError(
f"build_user_message() got unexpected keyword arguments: "
f"{set(kwargs)}. Did you mean 'last_prompt' instead of one of these?"
)
parts = []
if last_prompt:
parts.append(f"## Situation\n{last_prompt}")
if player_action:
parts.append(f"## Player's Request\n{player_action}")
has_existing_story = bool(
state.read_file(BOOK_PATH).strip()
) if not last_prompt else True
if not player_action and not last_prompt:
if has_existing_story:
raise RuntimeError(f"User action is required for every turn.")
else:
parts.append(
"## Instructions\n"
"This is a new story. Welcome the player and guide them through the game setup."
)
else:
parts.append(
"## Instructions\n"
"Advance the story based on the player's request. "
"All state is shown above — write the outcome directly."
)
return "\n\n".join(parts)
# ── LLM Call ────────────────────────────────────────────────────────
# ── Generation (delegated) ──────────────────────────────────────────
def generate(
self,
player_action: str | None = None,
last_narrative: str | None = None,
) -> GenerationResult:
"""
Synchronous generation. Calls the LLM, parses the response,
and returns a GenerationResult.
"""
system = self.build_system_prompt()
user = self.build_user_message(
player_action=player_action, last_prompt=last_narrative
return strategies.generate(
player_action=player_action,
last_narrative=last_narrative,
model=self.model,
temperature=self.temperature,
timeout=self.timeout,
max_tokens=self.max_tokens,
api_key=self.api_key,
api_base=self.api_base,
)
messages = [
{"role": "system", "content": system},
{"role": "user", "content": user},
]
try:
import litellm
except ImportError:
return GenerationResult(
narrative="",
error="litellm is not installed. Run: pip install litellm",
)
set_llm_env(self.model, self.api_key, self.api_base)
try:
response = litellm.completion(
model=self.model,
messages=messages,
temperature=self.temperature,
stream=False,
timeout=self.timeout,
)
text = response.choices[0].message.content or ""
except Exception as e:
return GenerationResult(
narrative="",
error=f"LLM call failed: {e}",
)
return self.parse_response(text)
def generate_stream(
self,
player_action: str | None = None,
last_narrative: str | None = None,
) -> Iterator[str]:
"""
Streaming generator. Yields text chunks as they arrive from the LLM.
On completion, the final yield is the FULL text (for parsing).
"""
system = self.build_system_prompt()
user = self.build_user_message(
player_action=player_action, last_prompt=last_narrative
def generate_stream(self, player_action=None, last_narrative=None):
yield from strategies.generate_stream(
player_action=player_action,
last_narrative=last_narrative,
model=self.model,
temperature=self.temperature,
timeout=self.timeout,
max_tokens=self.max_tokens,
api_key=self.api_key,
api_base=self.api_base,
)
messages = [
{"role": "system", "content": system},
{"role": "user", "content": user},
]
try:
import litellm
except ImportError:
yield json.dumps({
"error": "litellm is not installed. Run: pip install litellm"
})
return
set_llm_env(self.model, self.api_key, self.api_base)
try:
response = litellm.completion(
model=self.model,
messages=messages,
temperature=self.temperature,
stream=True,
timeout=self.timeout,
)
full_text = ""
for chunk in response:
delta = chunk.choices[0].delta.content or ""
if delta:
full_text += delta
yield full_text
yield full_text
except Exception as e:
yield json.dumps({"error": f"LLM call failed: {e}"})
# ──── Three-phase generation ────────────────────────────────────────
def generate_with_tools(
self,
player_action: str | None = None,
@@ -254,301 +91,20 @@ class GameEngine:
on_player_roll: callable = None,
on_debug: callable = None,
) -> TurnResult:
"""
Three-phase generation:
1. **Prose** — LLM writes the full book_log from context + player action.
2. **Summarize** — LLM condenses the book_log into one log line.
3. **Extract** — LLM reads the book_log and outputs tool calls for state changes.
"""
set_llm_env(self.model, self.api_key, self.api_base)
import random
datetime_now = datetime.now()
state.append_llm_log(f"\n{'='*60}")
state.append_llm_log(f"=== Turn — {datetime_now.strftime('%Y-%m-%d %H:%M:%S')} ===")
state.append_llm_log(f"{'='*60}")
if player_action:
state.append_llm_log(f"Player: {player_action}")
elif last_prompt:
state.append_llm_log(f"Resume from: {last_prompt[:120]}")
die_roll = random.randint(1, 6)
state.append_llm_log(f"Dice: {die_roll} (1d6)")
book_log = None
changes_block = ""
log_entry = None
user_prompt = self._auto_prompt("")
ambience = None
debug_info = ""
changes = []
for outer_attempt in range(3):
# ── Phase 1: Prose ────────────────────────────────────────────
if on_action:
on_action(f"Phase 1/3: writing story (dice={die_roll})")
if on_debug:
on_debug("phase", {"phase": 1, "name": "prose", "status": "start", "dice": die_roll, "outer_attempt": outer_attempt + 1})
system = PROSE_PROMPT.substitute(
character=state.read_file(CHAR_PATH) or "*No character sheet.*",
world=state.truncate_world(state.read_file(WORLD_PATH) or "") or "*No world state.*",
log=state.read_recent_log(),
story=state.read_recent_book(),
)
user = self.build_user_message(
player_action=player_action,
last_prompt=last_prompt,
)
user += f"\n\n*A die is cast: **{die_roll}** (1d6).*"
text = call_llm([
{"role": "system", "content": system},
{"role": "user", "content": user},
], model=self.model, temperature=self.temperature, timeout=self.timeout,
max_tokens=1024, label=f"Prose attempt {outer_attempt + 1}", on_debug=on_debug)
if not text or not text.strip():
if on_debug:
on_debug("phase", {"phase": 1, "status": "empty", "attempt": outer_attempt + 1})
continue
raw = text.strip()
changes_block = ""
if "### Changes" in raw:
parts = raw.split("### Changes", 1)
book_log = parts[0].strip()
changes_block = "### Changes" + parts[1]
else:
book_log = raw
if on_debug:
preview = book_log[:150].replace("\n", "\\n")
on_debug("phase", {"phase": 1, "status": "done", "chars": len(book_log), "changes": bool(changes_block), "preview": preview})
# ── Validation ────────────────────────────────────────────────
if on_debug:
on_debug("phase", {"phase": 1, "name": "validation", "status": "start"})
valid, reason = self._validate_narrative(book_log, on_debug=on_debug)
if not valid:
if on_debug:
on_debug("phase", {"phase": 1, "status": "validation_failed", "reason": reason, "outer_attempt": outer_attempt + 1})
book_log = None
continue
# ── Phase 2: Summarize ────────────────────────────────────────
if on_action:
on_action("Phase 2/3: summarizing story")
if on_debug:
on_debug("phase", {"phase": 2, "name": "summarize", "status": "start"})
log_context = state.read_recent_log()
log_entry = None
for p2_attempt in range(2):
context = book_log
if changes_block:
context += f"\n\n{changes_block}"
text = call_llm([
{"role": "user", "content":
f"Given the session log so far, summarize the new story in one line. "
f"Focus on who was involved (character and NPC names):\n\n"
f"## Session Log\n{log_context}\n\n"
f"## New Story\n{context}"}
], model=self.model, temperature=self.temperature, timeout=self.timeout,
max_tokens=self.max_tokens, label=f"Summarize attempt {p2_attempt + 1}", on_debug=on_debug)
if text and text.strip():
log_entry = text.strip().split("\n")[0][:300]
if on_debug:
on_debug("phase", {"phase": 2, "status": "done", "summary": log_entry})
break
if not log_entry:
log_entry = book_log.split("\n")[0][:120]
if on_debug:
on_debug("phase", {"phase": 2, "status": "fallback", "summary": log_entry})
# ── Phase 3: Extract state changes ────────────────────────────
if on_action:
on_action("Phase 3/3: extracting state changes")
if on_debug:
on_debug("phase", {"phase": 3, "name": "extract", "status": "start"})
user_prompt = self._auto_prompt(book_log)
ambience = None
phase3_errors = []
changes = []
# Step 1: Parse ### Changes block directly
if changes_block.strip():
for tc in parse_changes_block(changes_block):
name = tc["tool"]
args = tc.get("args", {})
if name == "finalize_turn":
continue
result = execute_tool(name, args)
if result.startswith("**Error:") or result.startswith("Tool error") or result.startswith("Unknown"):
phase3_errors.append(f"{name}: {result}")
else:
desc = describe_change(name, args)
if desc:
changes.append(desc)
# Step 2: LLM Phase 3 for finalize_turn + any extra changes
previous_attempt = None
phase3_ok = False
for p3_attempt in range(5):
current_char = state.read_file(CHAR_PATH) or "*No character.*"
current_world = state.truncate_world(state.read_file(WORLD_PATH) or "") or "*No world.*"
phase3_prompt = (
f"## Current Character\n{current_char}\n\n"
f"## Current World\n{current_world}\n\n"
f"## Story\n{book_log}\n\n"
)
if changes_block.strip():
phase3_prompt += (
f"## Changes already applied\n{changes_block}\n\n"
f"Output the finalize_turn tool to end the turn. "
f"Add extra tool calls if you spot changes the list above missed.\n\n"
)
else:
phase3_prompt += (
f"Read the story and compare with current state. Output tool calls for any changes:\n\n"
)
phase3_prompt += (
f"Output ```tool blocks for changes only. Examples:\n\n"
)
if previous_attempt:
phase3_prompt += (
f"--- PREVIOUS ATTEMPT (had errors) ---\n"
f"{previous_attempt['output']}\n\n"
f"--- FEEDBACK ---\n"
f"{previous_attempt['feedback']}\n\n"
f"Fix the issues above. Output corrected tool calls only.\n\n"
)
text = call_llm([
{"role": "user", "content": phase3_prompt +
f"```tool\n{{\"tool\": \"modify_vitals\", \"args\": {{\"current_hp\": 5, \"cash\": 45}}}}\n```\n"
f"```tool\n{{\"tool\": \"modify_traits\", \"args\": {{\"dex\": 15}}}}\n```\n"
f"```tool\n{{\"tool\": \"add_to_inventory\", \"args\": {{\"item\": \"Silver key\"}}}}\n```\n"
f"```tool\n{{\"tool\": \"remove_from_inventory\", \"args\": {{\"item\": \"Torches (10)\"}}}}\n```\n"
f"```tool\n{{\"tool\": \"replace_gear\", \"args\": {{\"before\": \"Mace (1d6+1)\", \"after\": \"Mace (1d6+2, sharpened)\"}}}}\n```\n"
f"```tool\n{{\"tool\": \"add_note\", \"args\": {{\"note\": \"Found a hidden passage under the temple\"}}}}\n```\n"
f"```tool\n{{\"tool\": \"replace_note\", \"args\": {{\"before\": \"Old note text\", \"after\": \"New note text\"}}}}\n```\n"
f"```tool\n{{\"tool\": \"world_update\", \"args\": {{\"content\": \"# The World\\n\\n...full new world state...\"}}}}\n```\n"
f"```tool\n{{\"tool\": \"journal_update\", \"args\": {{\"add\": [\"Investigate the mine\"], \"done\": [\"Defeat the demon\"]}}}}\n```\n"
f"```tool\n{{\"tool\": \"finalize_turn\", \"args\": {{\"user_prompt\": \"What do you do?\", \"ambience\": \"dungeon\"}}}}\n```\n\n"
f"Only output tools for things that actually changed. Omit unchanged fields."}
], model=self.model, temperature=self.temperature, timeout=self.timeout,
max_tokens=self.max_tokens, label=f"Extract attempt {p3_attempt + 1}", on_debug=on_debug)
if not text or not text.strip():
if on_debug:
on_debug("phase", {"phase": 3, "status": "empty", "attempt": p3_attempt + 1})
continue
tool_calls_list = extract_tool_calls(
text, round_num=p3_attempt + 1, on_debug=on_debug
)
if on_debug and tool_calls_list:
names = [tc.get("tool", "?") for tc in tool_calls_list if tc.get("tool") != "finalize_turn"]
fin = any(tc.get("tool") == "finalize_turn" for tc in tool_calls_list)
on_debug("phase", {"phase": 3, "status": "tools_found", "tools": names, "has_finalize": fin})
errors = []
attempt_changes = []
for tc in tool_calls_list:
name = tc.get("tool", "?")
args = tc.get("args", {})
if name == "finalize_turn":
if args.get("user_prompt"):
user_prompt = args["user_prompt"]
if args.get("ambience"):
ambience = args["ambience"]
continue
if on_action:
on_action(f"State: {describe_tool_action(name, args)}")
if on_debug:
on_debug("tool_call", {"round": p3_attempt + 1, "tool": name, "args": args})
if name == "player_roll" and on_player_roll:
dice = args.get("dice", "1d6")
reason = args.get("reason", "a check")
roll_val = on_player_roll(dice, reason)
result = f"Player rolled {dice} for '{reason}': {roll_val}"
else:
result = execute_tool(name, args)
if result.startswith("**Error:") or result.startswith("Tool error") or result.startswith("Unknown"):
errors.append(f"{name}: {result}")
else:
desc = describe_change(name, args)
if desc:
attempt_changes.append(desc)
if on_debug:
on_debug("tool_result", {"round": p3_attempt + 1, "tool": name, "result": result})
if not errors:
phase3_ok = True
debug_info = ""
changes.extend(attempt_changes)
if on_debug:
on_debug("phase", {"phase": 3, "status": "done", "applied": len([tc for tc in tool_calls_list if tc.get("tool") != "finalize_turn"])})
break
phase3_errors = errors
debug_info = "; ".join(errors)
if on_debug:
on_debug("phase", {"phase": 3, "status": "errors", "errors": errors, "attempt": p3_attempt + 1})
feedback_lines = ["The previous tool calls had errors:"]
for e in errors:
feedback_lines.append(f"- {e}")
feedback_lines.append("")
feedback_lines.append("Fix ALL issues above. Use correct tool names, valid JSON, and reasonable values.")
previous_attempt = {"output": text, "feedback": "\n".join(feedback_lines)}
if phase3_ok:
break
if on_debug:
on_debug("phase", {"phase": 3, "status": "exhausted", "errors": phase3_errors})
on_debug("phase", {"phase": 1, "status": "retry_after_phase3_failure", "outer_attempt": outer_attempt + 1})
book_log = None
if not book_log:
return TurnResult(error="Generation failed after exhausting all retries")
# ── Finalize ──────────────────────────────────────────────────────
if on_action:
on_action("Turn complete")
if on_debug:
on_debug("phase_done", {
"book_log_chars": len(book_log),
"log_entry": log_entry,
"user_prompt": user_prompt,
"ambience": ambience,
"extract_errors": debug_info or None,
})
state.append_llm_log(
f"\n--- FINAL ---\n"
f"book_log: {book_log[:200]}\n"
f"log_entry: {log_entry}\n"
f"user_prompt: {user_prompt}\n"
f"ambience: {ambience}\n"
return strategies.generate_with_tools(
player_action=player_action,
last_prompt=last_prompt,
on_thought=on_thought,
on_action=on_action,
on_player_roll=on_player_roll,
on_debug=on_debug,
model=self.model,
temperature=self.temperature,
timeout=self.timeout,
max_tokens=self.max_tokens,
api_key=self.api_key,
api_base=self.api_base,
)
return TurnResult(
book_log=book_log,
log_entry=log_entry,
user_prompt=user_prompt,
ambience=ambience,
debug_info=debug_info,
changes=changes,
)
# ──── Single-call generation ─────────────────────────────────────────
def generate_with_tools_single(
self,
@@ -559,368 +115,20 @@ class GameEngine:
on_player_roll: callable = None,
on_debug: callable = None,
) -> TurnResult:
"""
Single-call generation using tools.
Uses a single LLM call with all tools available — LLM outputs
narrative + tool blocks in one go. No retry loop.
"""
datetime_now = datetime.now()
state.append_llm_log(f"\n{'='*60}")
state.append_llm_log(f"=== Turn — {datetime_now.strftime('%Y-%m-%d %H:%M:%S')} ===")
state.append_llm_log(f"{'='*60}")
if player_action:
state.append_llm_log(f"Player: {player_action}")
elif last_prompt:
state.append_llm_log(f"Resume from: {last_prompt[:120]}")
strategy_name = "tools"
if on_action:
on_action(f"LLM: {self.model} | temp={self.temperature} | tokens={self.max_tokens} | strategy={strategy_name}")
if on_debug:
on_debug("config", {"model": self.model, "temperature": self.temperature, "max_tokens": self.max_tokens, "strategy": strategy_name})
import random
die_roll = random.randint(1, 6)
state.append_llm_log(f"Dice: {die_roll} (1d6)")
system = """You are an RPG dungeon master. The player just took an action.
Output ONLY ```tool blocks — no prose, no reasoning, no explanation outside tool blocks. Every piece of output must be in a tool block.
Use these tools to perform every action. Wrap each in its own ```tool block:
```tool
{"tool": "narrative", "args": {"text": "The full vivid narrative prose goes here."}}
```
```tool
{"tool": "modify_vitals", "args": {"current_hp": 5, "cash": 45}}
```
```tool
{"tool": "modify_traits", "args": {"dex": 15}}
```
```tool
{"tool": "add_to_inventory", "args": {"item": "Silver key"}}
```
```tool
{"tool": "remove_from_inventory", "args": {"item": "Torches (10)"}}
```
```tool
{"tool": "replace_gear", "args": {"before": "Mace (1d6+1)", "after": "Mace (1d6+2, sharpened)"}}
```
```tool
{"tool": "add_note", "args": {"note": "Found a hidden passage under the temple"}}
```
```tool
{"tool": "replace_note", "args": {"before": "Old note text", "after": "New note text"}}
```
```tool
{"tool": "world_update", "args": {"content": "# The World\n\n...full new world state..."}}
```
```tool
{"tool": "journal_update", "args": {"add": ["Investigate the mine"], "done": ["Defeat the demon"]}}
```
```tool
{"tool": "finalize_turn", "args": {"user_prompt": "What do you do?", "ambience": "dungeon"}}
```
"""
system += PROSE_PROMPT.substitute(
character=state.read_file(CHAR_PATH) or "*No character sheet.*",
world=state.truncate_world(state.read_file(WORLD_PATH) or "") or "*No world state.*",
log=state.read_recent_log(),
story=state.read_recent_book(),
)
user = self.build_user_message(
return strategies.generate_with_tools_single(
player_action=player_action,
last_prompt=last_prompt,
)
user += f"\n\n*A die is cast: **{die_roll}** (1d6).*"
start_time = datetime.now()
set_llm_env(self.model, self.api_key, self.api_base)
state.append_llm_log(f"\n[TOOL] Single call — {len(system)} chars system, {len(user)} chars user")
state.append_llm_log(f"System preview: {system.split(chr(10))[0][:80]}...")
state.append_llm_log(f"User preview: {user.split(chr(10))[0][:80]}...")
text = call_llm(
[{"role": "system", "content": system},
{"role": "user", "content": user}],
model=self.model, temperature=self.temperature, timeout=self.timeout,
max_tokens=4096, label="Single tool call", on_debug=on_debug,
)
total_elapsed = (datetime.now() - start_time).total_seconds() * 1000
if text:
state.append_llm_log(f"\n[TOOL] got {len(text)} chars in {total_elapsed:.1f}ms")
if not text or not text.strip():
return TurnResult(error="Single tool call returned empty response")
raw = text.strip()
book_log = ""
log_entry = None
user_prompt = self._auto_prompt("")
ambience = None
tool_calls = []
changes = []
phase3_errors = []
tool_pattern = r"```tool\s*\n?(.*?)\n?```"
matches = re.findall(tool_pattern, text, re.DOTALL)
if matches:
for block in matches:
block = block.strip()
try:
tc = json.loads(block)
tool_calls.append(tc)
name = tc.get("tool", "unknown")
args = tc.get("args", {})
state.append_llm_log(f"\n[EXTRACT] {name}: {json.dumps(args)[:100]}")
if name == "narrative":
book_log = args.get("text", book_log)
elif name == "finalize_turn":
if args.get("user_prompt"):
user_prompt = args["user_prompt"]
if args.get("ambience"):
ambience = args["ambience"]
except json.JSONDecodeError as e:
state.append_llm_log(f"\n[EXTRACT] bad JSON: {e}")
continue
log_entry = None
if book_log:
clean = re.sub(r'\s+', ' ', book_log).strip()
first_sentence = re.split(r'(?<=[.!?])\s+', clean)
if first_sentence:
log_entry = first_sentence[0].strip()[:200]
else:
log_entry = clean[:200]
state.append_llm_log(f"\n[SUMMARY] \"{log_entry}\"")
extr_start = datetime.now()
for tc in tool_calls:
name = tc.get("tool", "unknown")
args = tc.get("args", {})
if name in ("finalize_turn", "narrative"):
continue
result = execute_tool(name, args)
if result.startswith("**Error:") or result.startswith("Tool error") or result.startswith("Unknown"):
phase3_errors.append(f"{name}: {result}")
else:
desc = describe_change(name, args)
if desc:
changes.append(desc)
apply_elapsed = (datetime.now() - extr_start).total_seconds() * 1000
state.append_llm_log(f"\n[APPLY] {len(changes)} changes in {apply_elapsed:.1f}ms")
else:
state.append_llm_log(f"\n[TOOL] no tool blocks found")
elapsed = (datetime.now() - start_time).total_seconds() * 1000
if on_action:
on_action("Turn complete")
if on_debug:
applied = len([tc for tc in tool_calls if tc.get("tool") != "finalize_turn"])
on_debug("phase_done", {
"book_log_chars": len(book_log),
"log_entry": log_entry,
"user_prompt": user_prompt,
"ambience": ambience,
"extract_errors": phase3_errors or None,
"total_elapsed_ms": elapsed,
"tool_calls_count": len(tool_calls),
"applied_changes_count": applied,
"tool_call_results": tool_calls,
})
self._log_turn_details(
player_action=player_action or last_prompt or "",
last_prompt=last_prompt or "",
strategy_name=strategy_name,
die_roll=die_roll,
on_thought=on_thought,
on_action=on_action,
on_player_roll=on_player_roll,
on_debug=on_debug,
model=self.model,
temperature=self.temperature,
timeout=self.timeout,
max_tokens=self.max_tokens,
book_log=book_log,
log_entry=log_entry or "",
ambience=ambience,
tool_calls=tool_calls,
on_debug=on_debug,
api_key=self.api_key,
api_base=self.api_base,
)
return TurnResult(
book_log=book_log,
log_entry=log_entry,
user_prompt=user_prompt,
ambience=ambience,
debug_info="; ".join(phase3_errors) if phase3_errors else "",
changes=changes,
)
# ── Helpers ─────────────────────────────────────────────────────────
@staticmethod
def _auto_prompt(book_log: str) -> str:
"""Fallback player prompt."""
return "**What do you do?**"
def _validate_narrative(self, book_log: str, *, on_debug: callable = None) -> tuple[bool, str]:
"""Check if book_log is acceptable narrative. Returns (ok, reason)."""
lines = book_log.strip().split("\n")
if not lines:
return False, "Empty narrative"
common = Counter(lines).most_common(1)
if common and common[0][1] >= 5:
return False, f"Repetition: '{common[0][0][:60]}' ×{common[0][1]}"
mech_lines = [l for l in lines if re.match(
r'^\*\*(?:Roll|Damage|Success|Failure|Check|Save|Hit|Miss|'
r'Strenght|Dexterity|Willpower|STR|DEX|WIL|'
r'(?:[A-Z][a-z]+(?: \(\w+\))?:))',
l
)]
if mech_lines:
ratio = len(mech_lines) / len(lines)
if ratio > 0.3:
return False, f"Game mechanics dominate ({len(mech_lines)}/{len(lines)} lines)"
if re.search(r'```(?:tool|json)', book_log):
return False, "Contains unprocessed tool blocks"
prose = re.sub(r'[*_#>`~\-\d]', '', book_log).strip()
if len(prose) < 50:
return False, "Too short to be meaningful"
text = call_llm([
{"role": "user", "content":
f"Rate this RPG narrative quality 1-5.\n"
f"1 = unreadable (spam, repetition, pure mechanics, garbled)\n"
f"2 = poor (mostly mechanics, little story)\n"
f"3 = acceptable (some narrative but rough)\n"
f"4 = good (solid prose, minor issues)\n"
f"5 = excellent (vivid, engaging)\n"
f"Reply with ONLY a single digit 1-5.\n\n"
f"{book_log[:600]}"}
], model=self.model, temperature=self.temperature, timeout=self.timeout,
max_tokens=2, label="Narrative validation", on_debug=on_debug)
if text and text.strip().isdigit():
score = int(text.strip())
if score < 3:
return False, f"Quality score: {score}/5"
return True, ""
# ── Response Parsing ────────────────────────────────────────────────
@staticmethod
def parse_response(text: str) -> GenerationResult:
"""
Parse a full LLM response into a GenerationResult.
Extracts the JSON block and splits narrative from it.
"""
if text.startswith('{"error":'):
try:
err = json.loads(text).get("error", "Unknown error")
except json.JSONDecodeError:
err = "Unknown error"
return GenerationResult(narrative="", error=err)
json_pattern = r"```json\s*\n?(.*?)\n?```"
matches = re.findall(json_pattern, text, re.DOTALL)
narrative = text
data = {}
if matches:
json_str = matches[-1].strip()
narrative = text[: text.rfind("```json")]
narrative_lines = []
for line in narrative.splitlines():
if not line.lstrip().startswith('book_log:'):
narrative_lines.append(line)
narrative = "\n".join(narrative_lines).strip()
try:
data = json.loads(json_str)
except json.JSONDecodeError:
pass
else:
text_stripped = text.strip()
if text_stripped.startswith("{") and text_stripped.endswith("}"):
try:
data = json.loads(text_stripped)
narrative = data.get("narrative", "")
except json.JSONDecodeError:
pass
return GenerationResult(
narrative=narrative or text,
choices=data.get("choices", []),
log_entry=data.get("log_entry"),
ambience=data.get("ambience"),
character_updates=data.get("character_updates"),
world_updates=data.get("world_updates"),
journal_add=data.get("journal_add", []),
journal_done=data.get("journal_done", []),
)
# ── Logging ─────────────────────────────────────────────────────────
def _log_turn_details(
self,
player_action: str,
last_prompt: str,
strategy_name: str,
die_roll: int,
model: str,
temperature: float,
max_tokens: int,
book_log: str,
log_entry: str,
ambience: Optional[str],
tool_calls: list,
on_debug,
) -> None:
"""Write structured turn summary to llm.log and fire TUI debug event."""
ts = datetime.now().isoformat()
output_chars = len(book_log)
output_words = len(book_log.split()) if book_log else 0
applied = len([tc for tc in tool_calls if tc.get("tool") != "finalize_turn"])
state.append_llm_log("")
state.append_llm_log(f"┌─ Turn Details — {ts}")
state.append_llm_log(f"├─ Input: {player_action}")
state.append_llm_log(f"├─ Last Prompt: {last_prompt}")
state.append_llm_log(f"├─ Strategy: {strategy_name}")
state.append_llm_log(f"├─ Dice: {die_roll} (1d6)")
state.append_llm_log(f"├─ Model: {model} | Temp: {temperature} | Tokens: {max_tokens}")
state.append_llm_log(f"├─ Output: {output_chars} chars ({output_words} words)")
state.append_llm_log(f"├─ Log Entry: {log_entry}")
state.append_llm_log(f"├─ Ambience: {ambience or 'None'}")
tools_preview = ", ".join(tc.get("tool", "?") for tc in tool_calls)
state.append_llm_log(f"├─ Tool Calls: {len(tool_calls)} ({tools_preview})")
state.append_llm_log(
"└─────────────────────────────────────────────────────────────────────────────────────────┘"
)
if on_debug:
on_debug("turn_details", {
"timestamp": ts,
"model": model,
"temperature": temperature,
"max_tokens": max_tokens,
"strategy_name": strategy_name,
"die_roll": die_roll,
"player_action": player_action,
"book_log_chars": output_chars,
"book_log_words": output_words,
"ambience": ambience,
"tool_calls_count": len(tool_calls),
"applied_changes_count": applied,
"tool_call_results": tool_calls,
})
# ── CLI entry point (for testing) ─────────────────────────────────────────
tools/engine_lib/__init__.py
View File
tools/engine_lib/config.py
+74
View File
@@ -0,0 +1,74 @@
#!/usr/bin/env python3
"""
config.py — LLM configuration loading and accessors for The Chaos engine.
"""
from __future__ import annotations
import json
import sys
from pathlib import Path
from .paths import CONFIG_PATH
DEFAULT_CONFIG: dict = {
"llm": {
"model": "ollama/llama3.1",
"api_key": None,
"api_base": None,
"temperature": 0.8,
"max_tokens": 300,
}
}
def load_config(path: Path = CONFIG_PATH) -> dict:
"""Load config from path, creating default if missing. Returns config dict."""
if not path.exists():
print(
"No session/config.json found. Creating default.\n"
"Edit the model field (e.g. 'ollama/llama3.1', 'openai/gpt-4', "
"'anthropic/claude-sonnet-4-20250514') and set api_key if needed.",
file=sys.stderr,
)
cfg = dict(DEFAULT_CONFIG)
save_config(cfg, path)
return cfg
raw = path.read_text()
cfg = json.loads(raw)
llm = cfg.get("llm", {})
if not llm.get("api_key"):
llm["api_key"] = None
return cfg
def save_config(config: dict, path: Path = CONFIG_PATH) -> None:
"""Save config dict to path."""
path.parent.mkdir(parents=True, exist_ok=True)
path.write_text(json.dumps(config, indent=2) + "\n")
# ── Accessors ──────────────────────────────────────────────────────────────
def get_model(config: dict) -> str:
return config.get("llm", {}).get("model", "ollama/llama3.1")
def get_api_key(config: dict) -> str | None:
return config.get("llm", {}).get("api_key")
def get_api_base(config: dict) -> str | None:
return config.get("llm", {}).get("api_base")
def get_temperature(config: dict) -> float:
return config.get("llm", {}).get("temperature", 0.8)
def get_max_tokens(config: dict) -> int:
return config.get("llm", {}).get("max_tokens", 512)
def get_timeout(config: dict) -> int:
return config.get("llm", {}).get("timeout", 120)
tools/engine_lib/context.py
+74
View File
@@ -0,0 +1,74 @@
#!/usr/bin/env python3
"""
context.py — System prompt and user message assembly for The Chaos engine.
All functions are standalone — no dependency on GameEngine.
"""
from __future__ import annotations
from .paths import CHAR_PATH, WORLD_PATH, BOOK_PATH
from .prompts import SYSTEM_PROMPT
from . import state
def build_system_prompt() -> str:
"""Assemble the system prompt with current game state."""
char = state.read_file(CHAR_PATH) or "*No character sheet.*"
world = state.truncate_world(state.read_file(WORLD_PATH) or "") or "*No world state.*"
log = state.read_recent_log()
story = state.read_recent_book()
return SYSTEM_PROMPT.substitute(
character=char, world=world, log=log, story=story
)
def build_prose_prompt() -> str:
"""Assemble the prose-generation prompt with current game state."""
from .prompts import PROSE_PROMPT
char = state.read_file(CHAR_PATH) or "*No character sheet.*"
world = state.truncate_world(state.read_file(WORLD_PATH) or "") or "*No world state.*"
log = state.read_recent_log()
story = state.read_recent_book()
return PROSE_PROMPT.substitute(
character=char, world=world, log=log, story=story
)
def build_user_message(
player_action: str | None = None,
last_prompt: str | None = None,
**kwargs: str | None,
) -> str:
"""Build the user message for this turn's LLM call."""
if kwargs:
raise TypeError(
f"build_user_message() got unexpected keyword arguments: "
f"{set(kwargs)}. Did you mean 'last_prompt' instead of one of these?"
)
parts = []
if last_prompt:
parts.append(f"## Situation\n{last_prompt}")
if player_action:
parts.append(f"## Player's Request\n{player_action}")
has_existing_story = bool(
state.read_file(BOOK_PATH).strip()
) if not last_prompt else True
if not player_action and not last_prompt:
if has_existing_story:
raise RuntimeError("User action is required for every turn.")
else:
parts.append(
"## Instructions\n"
"This is a new story. Welcome the player and guide them through the game setup."
)
else:
parts.append(
"## Instructions\n"
"Advance the story based on the player's request. "
"All state is shown above — write the outcome directly."
)
return "\n\n".join(parts)
tools/llm.py → tools/engine_lib/llm.py
+1 -1
View File
@@ -10,7 +10,7 @@ from __future__ import annotations
import os
from state import append_llm_log
from .state import append_llm_log
def set_llm_env(model: str, api_key: str | None, api_base: str | None) -> None:
tools/models.py → tools/engine_lib/models.py
View File
tools/engine_lib/parsing.py
+121
View File
@@ -0,0 +1,121 @@
#!/usr/bin/env python3
"""
parsing.py — LLM response parsing and turn logging for The Chaos engine.
Standalone functions — no dependency on GameEngine.
"""
from __future__ import annotations
import json
import re
from datetime import datetime
from typing import Optional
from .models import GenerationResult
from . import state
def parse_response(text: str) -> GenerationResult:
"""
Parse a full LLM response into a GenerationResult.
Extracts the JSON block and splits narrative from it.
"""
if text.startswith('{"error":'):
try:
err = json.loads(text).get("error", "Unknown error")
except json.JSONDecodeError:
err = "Unknown error"
return GenerationResult(narrative="", error=err)
json_pattern = r"```json\s*\n?(.*?)\n?```"
matches = re.findall(json_pattern, text, re.DOTALL)
narrative = text
data = {}
if matches:
json_str = matches[-1].strip()
narrative = text[: text.rfind("```json")]
narrative_lines = []
for line in narrative.splitlines():
if not line.lstrip().startswith('book_log:'):
narrative_lines.append(line)
narrative = "\n".join(narrative_lines).strip()
try:
data = json.loads(json_str)
except json.JSONDecodeError:
pass
else:
text_stripped = text.strip()
if text_stripped.startswith("{") and text_stripped.endswith("}"):
try:
data = json.loads(text_stripped)
narrative = data.get("narrative", "")
except json.JSONDecodeError:
pass
return GenerationResult(
narrative=narrative or text,
choices=data.get("choices", []),
log_entry=data.get("log_entry"),
ambience=data.get("ambience"),
character_updates=data.get("character_updates"),
world_updates=data.get("world_updates"),
journal_add=data.get("journal_add", []),
journal_done=data.get("journal_done", []),
)
def log_turn_details(
player_action: str,
last_prompt: str,
strategy_name: str,
die_roll: int,
model: str,
temperature: float,
max_tokens: int,
book_log: str,
log_entry: str,
ambience: Optional[str],
tool_calls: list,
on_debug=None,
) -> None:
"""Write structured turn summary to llm.log and fire TUI debug event."""
ts = datetime.now().isoformat()
output_chars = len(book_log)
output_words = len(book_log.split()) if book_log else 0
applied = len([tc for tc in tool_calls if tc.get("tool") != "finalize_turn"])
state.append_llm_log("")
state.append_llm_log(f"┌─ Turn Details — {ts}")
state.append_llm_log(f"├─ Input: {player_action}")
state.append_llm_log(f"├─ Last Prompt: {last_prompt}")
state.append_llm_log(f"├─ Strategy: {strategy_name}")
state.append_llm_log(f"├─ Dice: {die_roll} (1d6)")
state.append_llm_log(f"├─ Model: {model} | Temp: {temperature} | Tokens: {max_tokens}")
state.append_llm_log(f"├─ Output: {output_chars} chars ({output_words} words)")
state.append_llm_log(f"├─ Log Entry: {log_entry}")
state.append_llm_log(f"├─ Ambience: {ambience or 'None'}")
tools_preview = ", ".join(tc.get("tool", "?") for tc in tool_calls)
state.append_llm_log(f"├─ Tool Calls: {len(tool_calls)} ({tools_preview})")
state.append_llm_log(
"└─────────────────────────────────────────────────────────────────────────────────────────┘"
)
if on_debug:
on_debug("turn_details", {
"timestamp": ts,
"model": model,
"temperature": temperature,
"max_tokens": max_tokens,
"strategy_name": strategy_name,
"die_roll": die_roll,
"player_action": player_action,
"book_log_chars": output_chars,
"book_log_words": output_words,
"ambience": ambience,
"tool_calls_count": len(tool_calls),
"applied_changes_count": applied,
"tool_call_results": tool_calls,
})
tools/config_paths.py → tools/engine_lib/paths.py
+1 -3
View File
@@ -1,8 +1,6 @@
#!/usr/bin/env python3
"""
config_paths.py — Path constants for The Chaos game engine.
Shared by engine.py, run.py, and all sub-modules.
paths.py — Path constants for The Chaos game engine.
"""
from __future__ import annotations
tools/prompts.py → tools/engine_lib/prompts.py
View File
tools/state.py → tools/engine_lib/state.py
+2 -2
View File
@@ -13,12 +13,12 @@ import sys
from datetime import date, datetime, timedelta
from pathlib import Path
from paths import (
from .paths import (
CHAR_PATH, WORLD_PATH, BOOK_PATH, JOURNAL_PATH, AMBIENCE_PATH,
LOG_DIR, LLM_LOG_PATH, AMBIENCE_OPTIONS_PATH, CHANGES_PATH,
AUDIO_DIR, TODAY,
)
from models import TurnResult
from .models import TurnResult
def read_file(path: Path) -> str:
tools/engine_lib/strategies.py
+657
View File
@@ -0,0 +1,657 @@
#!/usr/bin/env python3
"""
strategies.py — Generation strategies for The Chaos engine.
Contains the three-phase conversational approach and the single-call
tool-based approach. All functions are standalone — no dependency on
GameEngine (config values and callbacks are passed explicitly).
"""
from __future__ import annotations
import json
import random
import re
from datetime import datetime
from typing import Iterator
from .models import GenerationResult, TurnResult
from .prompts import PROSE_PROMPT
from .llm import set_llm_env, call_llm
from .tools_handler import (
execute_tool, describe_tool_action, describe_change,
parse_changes_block, extract_tool_calls,
)
from .context import build_system_prompt, build_user_message, build_prose_prompt
from .validation import auto_prompt, validate_narrative
from .parsing import parse_response, log_turn_details
from . import state
# ── Synchronous (legacy) ───────────────────────────────────────────────────
def generate(
player_action: str | None = None,
last_narrative: str | None = None,
*,
model: str,
temperature: float,
timeout: int,
max_tokens: int,
api_key: str | None = None,
api_base: str | None = None,
) -> GenerationResult:
"""
Synchronous generation. Calls the LLM, parses the response,
and returns a GenerationResult.
"""
system = build_system_prompt()
user = build_user_message(
player_action=player_action, last_prompt=last_narrative
)
messages = [
{"role": "system", "content": system},
{"role": "user", "content": user},
]
try:
import litellm
except ImportError:
return GenerationResult(
narrative="",
error="litellm is not installed. Run: pip install litellm",
)
set_llm_env(model, api_key, api_base)
try:
response = litellm.completion(
model=model,
messages=messages,
temperature=temperature,
stream=False,
timeout=timeout,
)
text = response.choices[0].message.content or ""
except Exception as e:
return GenerationResult(
narrative="",
error=f"LLM call failed: {e}",
)
return parse_response(text)
# ── Streaming (legacy) ─────────────────────────────────────────────────────
def generate_stream(
player_action: str | None = None,
last_narrative: str | None = None,
*,
model: str,
temperature: float,
timeout: int,
max_tokens: int,
api_key: str | None = None,
api_base: str | None = None,
) -> Iterator[str]:
"""
Streaming generator. Yields text chunks as they arrive from the LLM.
On completion, the final yield is the FULL text (for parsing).
"""
system = build_system_prompt()
user = build_user_message(
player_action=player_action, last_prompt=last_narrative
)
messages = [
{"role": "system", "content": system},
{"role": "user", "content": user},
]
try:
import litellm
except ImportError:
yield json.dumps({
"error": "litellm is not installed. Run: pip install litellm"
})
return
set_llm_env(model, api_key, api_base)
try:
response = litellm.completion(
model=model,
messages=messages,
temperature=temperature,
stream=True,
timeout=timeout,
)
full_text = ""
for chunk in response:
delta = chunk.choices[0].delta.content or ""
if delta:
full_text += delta
yield full_text
yield full_text
except Exception as e:
yield json.dumps({"error": f"LLM call failed: {e}"})
# ── Three-phase generation ─────────────────────────────────────────────────
def generate_with_tools(
player_action: str | None = None,
last_prompt: str | None = None,
on_thought: callable = None,
on_action: callable = None,
on_player_roll: callable = None,
on_debug: callable = None,
*,
model: str,
temperature: float,
timeout: int,
max_tokens: int,
api_key: str | None = None,
api_base: str | None = None,
) -> TurnResult:
"""
Three-phase generation:
1. **Prose** — LLM writes the full book_log from context + player action.
2. **Summarize** — LLM condenses the book_log into one log line.
3. **Extract** — LLM reads the book_log and outputs tool calls for state changes.
"""
set_llm_env(model, api_key, api_base)
datetime_now = datetime.now()
state.append_llm_log(f"\n{'='*60}")
state.append_llm_log(f"=== Turn — {datetime_now.strftime('%Y-%m-%d %H:%M:%S')} ===")
state.append_llm_log(f"{'='*60}")
if player_action:
state.append_llm_log(f"Player: {player_action}")
elif last_prompt:
state.append_llm_log(f"Resume from: {last_prompt[:120]}")
die_roll = random.randint(1, 6)
state.append_llm_log(f"Dice: {die_roll} (1d6)")
book_log = None
changes_block = ""
log_entry = None
user_prompt = auto_prompt("")
ambience = None
debug_info = ""
changes: list[str] = []
for outer_attempt in range(3):
# ── Phase 1: Prose ────────────────────────────────────────────────
if on_action:
on_action(f"Phase 1/3: writing story (dice={die_roll})")
if on_debug:
on_debug("phase", {"phase": 1, "name": "prose", "status": "start", "dice": die_roll, "outer_attempt": outer_attempt + 1})
system = build_prose_prompt()
user = build_user_message(
player_action=player_action,
last_prompt=last_prompt,
)
user += f"\n\n*A die is cast: **{die_roll}** (1d6).*"
text = call_llm([
{"role": "system", "content": system},
{"role": "user", "content": user},
], model=model, temperature=temperature, timeout=timeout,
max_tokens=1024, label=f"Prose attempt {outer_attempt + 1}", on_debug=on_debug)
if not text or not text.strip():
if on_debug:
on_debug("phase", {"phase": 1, "status": "empty", "attempt": outer_attempt + 1})
continue
raw = text.strip()
changes_block = ""
if "### Changes" in raw:
parts = raw.split("### Changes", 1)
book_log = parts[0].strip()
changes_block = "### Changes" + parts[1]
else:
book_log = raw
if on_debug:
preview = book_log[:150].replace("\n", "\\n")
on_debug("phase", {"phase": 1, "status": "done", "chars": len(book_log), "changes": bool(changes_block), "preview": preview})
# ── Validation ────────────────────────────────────────────────────
if on_debug:
on_debug("phase", {"phase": 1, "name": "validation", "status": "start"})
valid, reason = validate_narrative(book_log, model=model, temperature=temperature, timeout=timeout, on_debug=on_debug)
if not valid:
if on_debug:
on_debug("phase", {"phase": 1, "status": "validation_failed", "reason": reason, "outer_attempt": outer_attempt + 1})
book_log = None
continue
# ── Phase 2: Summarize ────────────────────────────────────────────
if on_action:
on_action("Phase 2/3: summarizing story")
if on_debug:
on_debug("phase", {"phase": 2, "name": "summarize", "status": "start"})
log_context = state.read_recent_log()
log_entry = None
for p2_attempt in range(2):
context = book_log
if changes_block:
context += f"\n\n{changes_block}"
text = call_llm([
{"role": "user", "content":
f"Given the session log so far, summarize the new story in one line. "
f"Focus on who was involved (character and NPC names):\n\n"
f"## Session Log\n{log_context}\n\n"
f"## New Story\n{context}"}
], model=model, temperature=temperature, timeout=timeout,
max_tokens=max_tokens, label=f"Summarize attempt {p2_attempt + 1}", on_debug=on_debug)
if text and text.strip():
log_entry = text.strip().split("\n")[0][:300]
if on_debug:
on_debug("phase", {"phase": 2, "status": "done", "summary": log_entry})
break
if not log_entry:
log_entry = book_log.split("\n")[0][:120]
if on_debug:
on_debug("phase", {"phase": 2, "status": "fallback", "summary": log_entry})
# ── Phase 3: Extract state changes ────────────────────────────────
if on_action:
on_action("Phase 3/3: extracting state changes")
if on_debug:
on_debug("phase", {"phase": 3, "name": "extract", "status": "start"})
user_prompt = auto_prompt(book_log)
ambience = None
phase3_errors = []
changes = []
# Step 1: Parse ### Changes block directly
if changes_block.strip():
for tc in parse_changes_block(changes_block):
name = tc["tool"]
args = tc.get("args", {})
if name == "finalize_turn":
continue
result = execute_tool(name, args)
if result.startswith("**Error:") or result.startswith("Tool error") or result.startswith("Unknown"):
phase3_errors.append(f"{name}: {result}")
else:
desc = describe_change(name, args)
if desc:
changes.append(desc)
# Step 2: LLM Phase 3 for finalize_turn + any extra changes
previous_attempt = None
phase3_ok = False
for p3_attempt in range(5):
from paths import CHAR_PATH, WORLD_PATH
current_char = state.read_file(CHAR_PATH) or "*No character.*"
current_world = state.truncate_world(state.read_file(WORLD_PATH) or "") or "*No world.*"
phase3_prompt = (
f"## Current Character\n{current_char}\n\n"
f"## Current World\n{current_world}\n\n"
f"## Story\n{book_log}\n\n"
)
if changes_block.strip():
phase3_prompt += (
f"## Changes already applied\n{changes_block}\n\n"
f"Output the finalize_turn tool to end the turn. "
f"Add extra tool calls if you spot changes the list above missed.\n\n"
)
else:
phase3_prompt += (
f"Read the story and compare with current state. Output tool calls for any changes:\n\n"
)
phase3_prompt += (
f"Output ```tool blocks for changes only. Examples:\n\n"
)
if previous_attempt:
phase3_prompt += (
f"--- PREVIOUS ATTEMPT (had errors) ---\n"
f"{previous_attempt['output']}\n\n"
f"--- FEEDBACK ---\n"
f"{previous_attempt['feedback']}\n\n"
f"Fix the issues above. Output corrected tool calls only.\n\n"
)
text = call_llm([
{"role": "user", "content": phase3_prompt +
f"```tool\n{{\"tool\": \"modify_vitals\", \"args\": {{\"current_hp\": 5, \"cash\": 45}}}}\n```\n"
f"```tool\n{{\"tool\": \"modify_traits\", \"args\": {{\"dex\": 15}}}}\n```\n"
f"```tool\n{{\"tool\": \"add_to_inventory\", \"args\": {{\"item\": \"Silver key\"}}}}\n```\n"
f"```tool\n{{\"tool\": \"remove_from_inventory\", \"args\": {{\"item\": \"Torches (10)\"}}}}\n```\n"
f"```tool\n{{\"tool\": \"replace_gear\", \"args\": {{\"before\": \"Mace (1d6+1)\", \"after\": \"Mace (1d6+2, sharpened)\"}}}}\n```\n"
f"```tool\n{{\"tool\": \"add_note\", \"args\": {{\"note\": \"Found a hidden passage under the temple\"}}}}\n```\n"
f"```tool\n{{\"tool\": \"replace_note\", \"args\": {{\"before\": \"Old note text\", \"after\": \"New note text\"}}}}\n```\n"
f"```tool\n{{\"tool\": \"world_update\", \"args\": {{\"content\": \"# The World\\n\\n...full new world state...\"}}}}\n```\n"
f"```tool\n{{\"tool\": \"journal_update\", \"args\": {{\"add\": [\"Investigate the mine\"], \"done\": [\"Defeat the demon\"]}}}}\n```\n"
f"```tool\n{{\"tool\": \"finalize_turn\", \"args\": {{\"user_prompt\": \"What do you do?\", \"ambience\": \"dungeon\"}}}}\n```\n\n"
f"Only output tools for things that actually changed. Omit unchanged fields."}
], model=model, temperature=temperature, timeout=timeout,
max_tokens=max_tokens, label=f"Extract attempt {p3_attempt + 1}", on_debug=on_debug)
if not text or not text.strip():
if on_debug:
on_debug("phase", {"phase": 3, "status": "empty", "attempt": p3_attempt + 1})
continue
tool_calls_list = extract_tool_calls(
text, round_num=p3_attempt + 1, on_debug=on_debug
)
if on_debug and tool_calls_list:
names = [tc.get("tool", "?") for tc in tool_calls_list if tc.get("tool") != "finalize_turn"]
fin = any(tc.get("tool") == "finalize_turn" for tc in tool_calls_list)
on_debug("phase", {"phase": 3, "status": "tools_found", "tools": names, "has_finalize": fin})
errors: list[str] = []
attempt_changes: list[str] = []
for tc in tool_calls_list:
name = tc.get("tool", "?")
args = tc.get("args", {})
if name == "finalize_turn":
if args.get("user_prompt"):
user_prompt = args["user_prompt"]
if args.get("ambience"):
ambience = args["ambience"]
continue
if on_action:
on_action(f"State: {describe_tool_action(name, args)}")
if on_debug:
on_debug("tool_call", {"round": p3_attempt + 1, "tool": name, "args": args})
if name == "player_roll" and on_player_roll:
dice = args.get("dice", "1d6")
reason = args.get("reason", "a check")
roll_val = on_player_roll(dice, reason)
result = f"Player rolled {dice} for '{reason}': {roll_val}"
else:
result = execute_tool(name, args)
if result.startswith("**Error:") or result.startswith("Tool error") or result.startswith("Unknown"):
errors.append(f"{name}: {result}")
else:
desc = describe_change(name, args)
if desc:
attempt_changes.append(desc)
if on_debug:
on_debug("tool_result", {"round": p3_attempt + 1, "tool": name, "result": result})
if not errors:
phase3_ok = True
debug_info = ""
changes.extend(attempt_changes)
if on_debug:
on_debug("phase", {"phase": 3, "status": "done", "applied": len([tc for tc in tool_calls_list if tc.get("tool") != "finalize_turn"])})
break
phase3_errors = errors
debug_info = "; ".join(errors)
if on_debug:
on_debug("phase", {"phase": 3, "status": "errors", "errors": errors, "attempt": p3_attempt + 1})
feedback_lines = ["The previous tool calls had errors:"]
for e in errors:
feedback_lines.append(f"- {e}")
feedback_lines.append("")
feedback_lines.append("Fix ALL issues above. Use correct tool names, valid JSON, and reasonable values.")
previous_attempt = {"output": text, "feedback": "\n".join(feedback_lines)}
if phase3_ok:
break
if on_debug:
on_debug("phase", {"phase": 3, "status": "exhausted", "errors": phase3_errors})
on_debug("phase", {"phase": 1, "status": "retry_after_phase3_failure", "outer_attempt": outer_attempt + 1})
book_log = None
if not book_log:
return TurnResult(error="Generation failed after exhausting all retries")
if on_action:
on_action("Turn complete")
if on_debug:
on_debug("phase_done", {
"book_log_chars": len(book_log),
"log_entry": log_entry,
"user_prompt": user_prompt,
"ambience": ambience,
"extract_errors": debug_info or None,
})
state.append_llm_log(
f"\n--- FINAL ---\n"
f"book_log: {book_log[:200]}\n"
f"log_entry: {log_entry}\n"
f"user_prompt: {user_prompt}\n"
f"ambience: {ambience}\n"
)
return TurnResult(
book_log=book_log,
log_entry=log_entry,
user_prompt=user_prompt,
ambience=ambience,
debug_info=debug_info,
changes=changes,
)
# ── Single-call generation ─────────────────────────────────────────────────
def generate_with_tools_single(
player_action: str | None = None,
last_prompt: str | None = None,
on_thought: callable = None,
on_action: callable = None,
on_player_roll: callable = None,
on_debug: callable = None,
*,
model: str,
temperature: float,
timeout: int,
max_tokens: int,
api_key: str | None = None,
api_base: str | None = None,
) -> TurnResult:
"""
Single-call generation using tools.
Uses a single LLM call with all tools available — LLM outputs
narrative + tool blocks in one go. No retry loop.
"""
datetime_now = datetime.now()
state.append_llm_log(f"\n{'='*60}")
state.append_llm_log(f"=== Turn — {datetime_now.strftime('%Y-%m-%d %H:%M:%S')} ===")
state.append_llm_log(f"{'='*60}")
if player_action:
state.append_llm_log(f"Player: {player_action}")
elif last_prompt:
state.append_llm_log(f"Resume from: {last_prompt[:120]}")
strategy_name = "tools"
if on_action:
on_action(f"LLM: {model} | temp={temperature} | tokens={max_tokens} | strategy={strategy_name}")
if on_debug:
on_debug("config", {"model": model, "temperature": temperature, "max_tokens": max_tokens, "strategy": strategy_name})
die_roll = random.randint(1, 6)
state.append_llm_log(f"Dice: {die_roll} (1d6)")
system = """You are an RPG dungeon master. The player just took an action.
Output ONLY ```tool blocks — no prose, no reasoning, no explanation outside tool blocks. Every piece of output must be in a tool block.
Use these tools to perform every action. Wrap each in its own ```tool block:
```tool
{"tool": "narrative", "args": {"text": "The full vivid narrative prose goes here."}}
```
```tool
{"tool": "modify_vitals", "args": {"current_hp": 5, "cash": 45}}
```
```tool
{"tool": "modify_traits", "args": {"dex": 15}}
```
```tool
{"tool": "add_to_inventory", "args": {"item": "Silver key"}}
```
```tool
{"tool": "remove_from_inventory", "args": {"item": "Torches (10)"}}
```
```tool
{"tool": "replace_gear", "args": {"before": "Mace (1d6+1)", "after": "Mace (1d6+2, sharpened)"}}
```
```tool
{"tool": "add_note", "args": {"note": "Found a hidden passage under the temple"}}
```
```tool
{"tool": "replace_note", "args": {"before": "Old note text", "after": "New note text"}}
```
```tool
{"tool": "world_update", "args": {"content": "# The World\n\n...full new world state..."}}
```
```tool
{"tool": "journal_update", "args": {"add": ["Investigate the mine"], "done": ["Defeat the demon"]}}
```
```tool
{"tool": "finalize_turn", "args": {"user_prompt": "What do you do?", "ambience": "dungeon"}}
```
"""
system += build_prose_prompt()
user = build_user_message(
player_action=player_action,
last_prompt=last_prompt,
)
user += f"\n\n*A die is cast: **{die_roll}** (1d6).*"
start_time = datetime.now()
set_llm_env(model, api_key, api_base)
state.append_llm_log(f"\n[TOOL] Single call — {len(system)} chars system, {len(user)} chars user")
state.append_llm_log(f"System preview: {system.split(chr(10))[0][:80]}...")
state.append_llm_log(f"User preview: {user.split(chr(10))[0][:80]}...")
text = call_llm(
[{"role": "system", "content": system},
{"role": "user", "content": user}],
model=model, temperature=temperature, timeout=timeout,
max_tokens=4096, label="Single tool call", on_debug=on_debug,
)
total_elapsed = (datetime.now() - start_time).total_seconds() * 1000
if text:
state.append_llm_log(f"\n[TOOL] got {len(text)} chars in {total_elapsed:.1f}ms")
if not text or not text.strip():
return TurnResult(error="Single tool call returned empty response")
raw = text.strip()
book_log = ""
log_entry = None
user_prompt = auto_prompt("")
ambience = None
tool_calls = []
changes: list[str] = []
phase3_errors: list[str] = []
tool_pattern = r"```tool\s*\n?(.*?)\n?```"
matches = re.findall(tool_pattern, text, re.DOTALL)
if matches:
for block in matches:
block = block.strip()
try:
tc = json.loads(block)
tool_calls.append(tc)
name = tc.get("tool", "unknown")
args = tc.get("args", {})
state.append_llm_log(f"\n[EXTRACT] {name}: {json.dumps(args)[:100]}")
if name == "narrative":
book_log = args.get("text", book_log)
elif name == "finalize_turn":
if args.get("user_prompt"):
user_prompt = args["user_prompt"]
if args.get("ambience"):
ambience = args["ambience"]
except json.JSONDecodeError as e:
state.append_llm_log(f"\n[EXTRACT] bad JSON: {e}")
continue
log_entry = None
if book_log:
clean = re.sub(r'\s+', ' ', book_log).strip()
first_sentence = re.split(r'(?<=[.!?])\s+', clean)
if first_sentence:
log_entry = first_sentence[0].strip()[:200]
else:
log_entry = clean[:200]
state.append_llm_log(f"\n[SUMMARY] \"{log_entry}\"")
extr_start = datetime.now()
for tc in tool_calls:
name = tc.get("tool", "unknown")
args = tc.get("args", {})
if name in ("finalize_turn", "narrative"):
continue
result = execute_tool(name, args)
if result.startswith("**Error:") or result.startswith("Tool error") or result.startswith("Unknown"):
phase3_errors.append(f"{name}: {result}")
else:
desc = describe_change(name, args)
if desc:
changes.append(desc)
apply_elapsed = (datetime.now() - extr_start).total_seconds() * 1000
state.append_llm_log(f"\n[APPLY] {len(changes)} changes in {apply_elapsed:.1f}ms")
else:
state.append_llm_log(f"\n[TOOL] no tool blocks found")
elapsed = (datetime.now() - start_time).total_seconds() * 1000
if on_action:
on_action("Turn complete")
if on_debug:
applied = len([tc for tc in tool_calls if tc.get("tool") != "finalize_turn"])
on_debug("phase_done", {
"book_log_chars": len(book_log),
"log_entry": log_entry,
"user_prompt": user_prompt,
"ambience": ambience,
"extract_errors": phase3_errors or None,
"total_elapsed_ms": elapsed,
"tool_calls_count": len(tool_calls),
"applied_changes_count": applied,
"tool_call_results": tool_calls,
})
log_turn_details(
player_action=player_action or last_prompt or "",
last_prompt=last_prompt or "",
strategy_name=strategy_name,
die_roll=die_roll,
model=model,
temperature=temperature,
max_tokens=max_tokens,
book_log=book_log,
log_entry=log_entry or "",
ambience=ambience,
tool_calls=tool_calls,
on_debug=on_debug,
)
return TurnResult(
book_log=book_log,
log_entry=log_entry,
user_prompt=user_prompt,
ambience=ambience,
debug_info="; ".join(phase3_errors) if phase3_errors else "",
changes=changes,
)
tools/tools_handler.py → tools/engine_lib/tools_handler.py
+2 -2
View File
@@ -12,8 +12,8 @@ import json
import random
import re
from paths import CHAR_PATH, WORLD_PATH, LOG_DIR, TODAY
from state import read_file, validate_update_size, update_journal, append_llm_log
from .paths import CHAR_PATH, WORLD_PATH, LOG_DIR, TODAY
from .state import read_file, validate_update_size, update_journal, append_llm_log
# ── Tool Registry ───────────────────────────────────────────────────────────
tools/engine_lib/validation.py
+74
View File
@@ -0,0 +1,74 @@
#!/usr/bin/env python3
"""
validation.py — Narrative quality validation for The Chaos engine.
Standalone functions — no dependency on GameEngine.
"""
from __future__ import annotations
import re
from collections import Counter
from .llm import call_llm
def auto_prompt(book_log: str = "") -> str:
"""Fallback player prompt."""
return "**What do you do?**"
def validate_narrative(
book_log: str,
*,
model: str,
temperature: float,
timeout: int,
on_debug: callable = None,
) -> tuple[bool, str]:
"""Check if book_log is acceptable narrative. Returns (ok, reason)."""
lines = book_log.strip().split("\n")
if not lines:
return False, "Empty narrative"
common = Counter(lines).most_common(1)
if common and common[0][1] >= 5:
return False, f"Repetition: '{common[0][0][:60]}' ×{common[0][1]}"
mech_lines = [l for l in lines if re.match(
r'^\*\*(?:Roll|Damage|Success|Failure|Check|Save|Hit|Miss|'
r'Strenght|Dexterity|Willpower|STR|DEX|WIL|'
r'(?:[A-Z][a-z]+(?: \(\w+\))?:))',
l
)]
if mech_lines:
ratio = len(mech_lines) / len(lines)
if ratio > 0.3:
return False, f"Game mechanics dominate ({len(mech_lines)}/{len(lines)} lines)"
if re.search(r'```(?:tool|json)', book_log):
return False, "Contains unprocessed tool blocks"
prose = re.sub(r'[*_#>`~\-\d]', '', book_log).strip()
if len(prose) < 50:
return False, "Too short to be meaningful"
text = call_llm([
{"role": "user", "content":
f"Rate this RPG narrative quality 1-5.\n"
f"1 = unreadable (spam, repetition, pure mechanics, garbled)\n"
f"2 = poor (mostly mechanics, little story)\n"
f"3 = acceptable (some narrative but rough)\n"
f"4 = good (solid prose, minor issues)\n"
f"5 = excellent (vivid, engaging)\n"
f"Reply with ONLY a single digit 1-5.\n\n"
f"{book_log[:600]}"}
], model=model, temperature=temperature, timeout=timeout,
max_tokens=2, label="Narrative validation", on_debug=on_debug)
if text and text.strip().isdigit():
score = int(text.strip())
if score < 3:
return False, f"Quality score: {score}/5"
return True, ""
tools/run.py
+138 -804
View File
File diff suppressed because it is too large Load Diff
tools/run_ambience.py
+97
View File
@@ -0,0 +1,97 @@
import os
import random
from run_utils import AMBIENCE_PATH, AMBIENCE_OPTIONS_PATH, AUDIO_DIR, parse_ambience_options
try:
import miniaudio
HAS_AUDIO = True
except ImportError:
HAS_AUDIO = False
class AmbiencePlayer:
def __init__(self):
self.current_ambience = 'silence'
self._last_mtime = 0
self._options = {}
self._device = None
self._stream = None
self._muted = False
self.load_options()
@property
def available(self):
return HAS_AUDIO
@property
def ambience_name(self):
return self.current_ambience
@property
def is_muted(self):
return self._muted
def toggle_mute(self):
self._muted = not self._muted
if self._muted:
self._stop()
else:
self._load_current()
def load_options(self):
self._options = parse_ambience_options()
def _stop(self):
if self._device:
try:
self._device.close()
except Exception:
pass
self._device = None
self._stream = None
def poll(self):
if not HAS_AUDIO:
return
try:
mtime = os.path.getmtime(AMBIENCE_PATH)
except OSError:
return
if mtime == self._last_mtime:
return
self._last_mtime = mtime
try:
name = AMBIENCE_PATH.read_text().strip().lower()
except OSError:
return
self.current_ambience = name
self._stop()
if not self._muted and name != 'silence' and name in self._options:
self._play_current()
def _switch_to(self, name):
if name == self.current_ambience:
return
self.current_ambience = name
self._stop()
if self._muted or name == 'silence' or name not in self._options:
return
self._play_current()
def _play_current(self):
tracks = self._options.get(self.current_ambience, [])
valid = [t for t in tracks if t.exists()]
if not valid:
return
track = random.choice(valid)
try:
self._stream = miniaudio.stream_file(str(track))
self._device = miniaudio.PlaybackDevice()
self._device.start(self._stream)
except Exception:
self.current_ambience = None
self._stop()
def _load_current(self):
if self.current_ambience and self.current_ambience != 'silence':
self._play_current()
tools/run_utils.py
+125
View File
@@ -0,0 +1,125 @@
from pathlib import Path
from datetime import date
BASE = Path(__file__).resolve().parent.parent
SESSION = BASE / 'session'
LOG_DIR = SESSION / 'log'
CHAR_PATH = SESSION / 'character.md'
WORLD_PATH = SESSION / 'world.md'
JOURNAL_PATH = SESSION / 'journal.md'
AMBIENCE_PATH = SESSION / 'ambience.md'
AMBIENCE_OPTIONS_PATH = SESSION / 'ambience_options.md'
BOOK_PATH = SESSION / 'book.md'
LAST_PROMPT_PATH = SESSION / 'last_prompt.md'
CHANGES_PATH = SESSION / 'changes.md'
SETTINGS_PATH = SESSION / 'settings.json'
AUDIO_DIR = SESSION / 'audio'
TODAY = date.today().isoformat()
LOG_PATH = LOG_DIR / f'{TODAY}.md'
REFRESH_SECS = 2
def ensure_log():
LOG_DIR.mkdir(parents=True, exist_ok=True)
if not LOG_PATH.exists():
LOG_PATH.write_text(f"# Session Log — {TODAY}\n\n")
_populate_if_empty()
def _populate_if_empty():
content = LOG_PATH.read_text().strip()
if content and len(content.splitlines()) > 2:
return
def clear_llm_log():
from engine_lib.paths import LLM_LOG_PATH
LLM_LOG_PATH.parent.mkdir(parents=True, exist_ok=True)
LLM_LOG_PATH.write_text("")
def read_todo():
if not JOURNAL_PATH.exists():
return ["—— No journal yet ——"]
lines = JOURNAL_PATH.read_text().splitlines()
in_todo = False
todo = []
for l in lines:
if l.strip().lstrip("#").strip().startswith("TODO"):
in_todo = True
continue
if l.strip().startswith("#") and in_todo:
break
if in_todo and l.strip():
todo.append(l.strip().lstrip("- "))
return todo or ["—— All done! ——"]
def read_log_tail(n=200):
if not LOG_PATH.exists():
return []
lines = LOG_PATH.read_text().splitlines()
return [l for l in lines if l.strip() and not l.startswith("#")][-n:]
def status_summary():
if not CHAR_PATH.exists():
return "no character"
lines = CHAR_PATH.read_text().splitlines()
name = "?"
health = "?"
for l in lines:
if l.startswith('**Name:**'):
name = l.split(':', 1)[1].strip().strip('_').strip('*')
if l.startswith('**Current Health:**'):
h = l.split(':', 1)[1].strip().strip('_').strip('*')
if h:
health = h
if l.startswith('**Max Health:**'):
m = l.split(':', 1)[1].strip().strip('_').strip('*')
if m and health == '?':
health = m
return f"{name} ❤ {health}"
def log_count():
return len(read_log_tail())
def load_book_pages():
if not BOOK_PATH.exists() or not BOOK_PATH.read_text().strip():
return ["*The story has not begun.*"]
text = BOOK_PATH.read_text().strip()
turns = text.split('\n## ')
pages = []
for i, t in enumerate(turns):
pages.append(t if i == 0 else '## ' + t)
return pages or ["*The story has not begun.*"]
def parse_ambience_options():
if not AMBIENCE_OPTIONS_PATH.exists():
return {}
options = {}
lines = AMBIENCE_OPTIONS_PATH.read_text().splitlines()
in_table = False
for line in lines:
s = line.strip()
if not s.startswith('|') or not s.endswith('|'):
in_table = False
continue
parts = [p.strip() for p in s.split('|')]
parts = [p for p in parts if p]
if len(parts) < 2:
continue
if not in_table:
in_table = True
continue
if all(c in '-:| ' for c in s):
continue
name = parts[0].lower()
files = [f.strip() for f in parts[1].split(',') if f.strip()]
paths = [AUDIO_DIR / f for f in files]
options[name] = paths
return options
tools/run_widgets.py
+157
View File
@@ -0,0 +1,157 @@
from __future__ import annotations
from textual.app import ComposeResult
from textual.containers import Vertical
from textual.screen import Screen
from textual.widgets import Button, Input, Static
from rich.markdown import Markdown as RichMarkdown
from run_utils import (
CHAR_PATH, TODAY, REFRESH_SECS,
clear_llm_log, ensure_log, read_todo, read_log_tail,
status_summary, log_count,
)
from run_ambience import HAS_AUDIO
# module-level ref filled by ChaosTUI
app_ambience_player: object | None = None
class RollModal(Screen):
CSS = """
RollModal {
align: center middle;
background: rgba(0, 0, 0, 0.75);
}
#roll-dialog {
width: 44;
height: auto;
padding: 2 3;
background: #2a2a3a;
border: thick #e0ad4c;
}
#roll-title {
text-style: bold;
color: #ffd93d;
text-align: center;
height: 3;
}
#roll-reason {
color: #c0b090;
text-align: center;
height: 3;
}
#roll-input {
margin: 1 0;
}
#roll-submit {
width: 100%;
}
#roll-hint {
color: #888888;
text-align: center;
height: 1;
}
"""
def __init__(self, dice: str, reason: str) -> None:
super().__init__()
self.dice = dice
self.reason = reason
def compose(self) -> ComposeResult:
with Vertical(id="roll-dialog"):
yield Static(f"[bold]🎲 ROLL {self.dice}[/bold]", id="roll-title")
yield Static(f"Reason: {self.reason}", id="roll-reason")
yield Input(placeholder="Enter the number you rolled...", id="roll-input")
yield Button("Submit", id="roll-submit", variant="primary")
yield Static("(or press Enter)", id="roll-hint")
def on_input_submitted(self, event: Input.Submitted) -> None:
self._submit(event.value)
def on_button_pressed(self, event: Button.Pressed) -> None:
if event.button.id == "roll-submit":
self._submit(self.query_one("#roll-input", Input).value)
def _submit(self, value: str) -> None:
val = value.strip()
if val:
self.dismiss(val)
class AutoStatic(Static):
def load(self):
raise NotImplementedError
def on_mount(self):
clear_llm_log()
ensure_log()
self.load()
self.set_interval(REFRESH_SECS, self.load)
class TodoPane(AutoStatic):
def load(self):
items = read_todo()
self.update("\n".join(f" ☐ {i}" for i in items))
class TranscriptPane(AutoStatic):
def load(self):
lines = read_log_tail()
display = "\n".join(lines[-80:])
if lines:
display += "\n\n>>--- NOW --->"
self.update(display)
self.call_after_refresh(self._scroll_bottom)
def _scroll_bottom(self):
if self.parent and hasattr(self.parent, 'scroll_end'):
self.parent.scroll_end(animate=False)
class DebugPane(Static):
MAX_LINES = 200
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self._lines: list[str] = []
def append(self, text: str) -> None:
self._lines.append(text)
if len(self._lines) > self.MAX_LINES:
self._lines.pop(0)
self.update("\n".join(self._lines[-100:]))
self.call_after_refresh(self._scroll_bottom)
def _scroll_bottom(self):
if self.parent and hasattr(self.parent, 'scroll_end'):
self.parent.scroll_end(animate=False)
def clear(self) -> None:
self._lines.clear()
self.update("")
class CharPane(AutoStatic):
def load(self):
if not CHAR_PATH.exists():
self.update("*No character sheet*")
return
self.update(RichMarkdown(CHAR_PATH.read_text().strip()))
class StatusBar(AutoStatic):
def load(self):
char = status_summary()
count = log_count()
todo = len(read_todo())
music = ""
if not HAS_AUDIO:
music = " │ ♫ (install miniaudio)"
elif app_ambience_player:
name = app_ambience_player.ambience_name
music = f" │ ♫ {name}"
self.update(f"{char} │ {count} entries │ {todo} todo │ {TODAY}{music}")
tools/test_imports.py
+11 -6
View File
@@ -7,12 +7,17 @@ import ast
MODULES = [
'engine.py',
'config_paths.py',
'models.py',
'prompts.py',
'state.py',
'tools_handler.py',
'llm.py',
'engine_lib/paths.py',
'engine_lib/models.py',
'engine_lib/prompts.py',
'engine_lib/config.py',
'engine_lib/context.py',
'engine_lib/state.py',
'engine_lib/tools_handler.py',
'engine_lib/llm.py',
'engine_lib/validation.py',
'engine_lib/parsing.py',
'engine_lib/strategies.py',
]
def check_missing_imports():
tools/test_runtime.py
+11 -6
View File
@@ -22,12 +22,17 @@ def test_engine_import():
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
modules_to_test = [
('paths', ['BASE_DIR', 'SESSION_DIR', 'CHAR_PATH', 'LLM_LOG_PATH']),
('models', ['GenerationResult', 'TurnResult']),
('prompts', ['SYSTEM_PROMPT', 'PROSE_PROMPT']),
('state', ['read_file', 'apply_state', 'append_log', 'append_llm_log']),
('tools_handler', ['execute_tool', 'extract_tool_calls', 'TOOL_REGISTRY']),
('llm', ['call_llm', 'set_llm_env']),
('engine_lib.paths', ['BASE_DIR', 'SESSION_DIR', 'CHAR_PATH', 'LLM_LOG_PATH']),
('engine_lib.models', ['GenerationResult', 'TurnResult']),
('engine_lib.prompts', ['SYSTEM_PROMPT', 'PROSE_PROMPT']),
('engine_lib.config', ['load_config', 'save_config', 'get_model']),
('engine_lib.context', ['build_system_prompt', 'build_user_message', 'build_prose_prompt']),
('engine_lib.state', ['read_file', 'apply_state', 'append_log', 'append_llm_log']),
('engine_lib.tools_handler', ['execute_tool', 'extract_tool_calls', 'TOOL_REGISTRY']),
('engine_lib.llm', ['call_llm', 'set_llm_env']),
('engine_lib.validation', ['validate_narrative', 'auto_prompt']),
('engine_lib.parsing', ['parse_response', 'log_turn_details']),
('engine_lib.strategies', ['generate_with_tools', 'generate_with_tools_single']),
('engine', ['GameEngine']),
]