AI_Diplomacy/ai_diplomacy/diary_logic.py

104 lines
4 KiB
Python

# ai_diplomacy/diary_logic.py
import logging
import re
from typing import TYPE_CHECKING, Optional
from .utils import run_llm_and_log, log_llm_response, load_prompt
if TYPE_CHECKING:
from diplomacy import Game
from .agent import DiplomacyAgent
logger = logging.getLogger(__name__)
async def run_diary_consolidation(
agent: "DiplomacyAgent",
game: "Game",
log_file_path: str,
entries_to_keep_unsummarized: int = 6,
prompts_dir: Optional[str] = None,
):
"""
Consolidate older diary entries while keeping recent ones.
This is the logic moved from the DiplomacyAgent class.
"""
logger.info(f"[{agent.power_name}] CONSOLIDATION START — {len(agent.full_private_diary)} total full entries")
full_entries = [e for e in agent.full_private_diary if not e.startswith("[CONSOLIDATED HISTORY]")]
if len(full_entries) <= entries_to_keep_unsummarized:
agent.private_diary = list(agent.full_private_diary)
logger.info(f"[{agent.power_name}] ≤ {entries_to_keep_unsummarized} full entries — skipping consolidation")
return
boundary_entry = full_entries[-entries_to_keep_unsummarized]
match = re.search(r"\[[SFWRAB]\s*(\d{4})", boundary_entry)
if not match:
logger.error(f"[{agent.power_name}] Could not parse year from boundary entry; aborting consolidation")
agent.private_diary = list(agent.full_private_diary)
return
cutoff_year = int(match.group(1))
logger.info(f"[{agent.power_name}] Cut-off year for consolidation: {cutoff_year}")
def _entry_year(entry: str) -> int | None:
m = re.search(r"\[[SFWRAB]\s*(\d{4})", entry)
return int(m.group(1)) if m else None
entries_to_summarize = [e for e in full_entries if (_entry_year(e) is not None and _entry_year(e) < cutoff_year)]
entries_to_keep = [e for e in full_entries if (_entry_year(e) is None or _entry_year(e) >= cutoff_year)]
logger.info(f"[{agent.power_name}] Summarising {len(entries_to_summarize)} entries; keeping {len(entries_to_keep)} recent entries verbatim")
if not entries_to_summarize:
agent.private_diary = list(agent.full_private_diary)
logger.warning(f"[{agent.power_name}] No eligible entries to summarise; context diary left unchanged")
return
prompt_template = load_prompt("diary_consolidation_prompt.txt", prompts_dir=prompts_dir)
if not prompt_template:
logger.error(f"[{agent.power_name}] diary_consolidation_prompt.txt missing — aborting")
return
prompt = prompt_template.format(
power_name=agent.power_name,
full_diary_text="\n\n".join(entries_to_summarize),
)
raw_response = ""
success_flag = "FALSE"
consolidation_client = None
try:
consolidation_client = agent.client
raw_response = await run_llm_and_log(
client=consolidation_client,
prompt=prompt,
power_name=agent.power_name,
phase=game.current_short_phase,
response_type="diary_consolidation",
)
consolidated_text = raw_response.strip() if raw_response else ""
if not consolidated_text:
raise ValueError("LLM returned empty summary")
new_summary_entry = f"[CONSOLIDATED HISTORY] {consolidated_text}"
agent.private_diary = [new_summary_entry] + entries_to_keep
success_flag = "TRUE"
logger.info(f"[{agent.power_name}] Consolidation complete — {len(agent.private_diary)} context entries now")
except Exception as exc:
logger.error(f"[{agent.power_name}] Diary consolidation failed: {exc}", exc_info=True)
finally:
log_llm_response(
log_file_path=log_file_path,
model_name=(consolidation_client.model_name if consolidation_client is not None else agent.client.model_name),
power_name=agent.power_name,
phase=game.current_short_phase,
response_type="diary_consolidation",
raw_input_prompt=prompt,
raw_response=raw_response,
success=success_flag,
)