refactor(agent): move internal prompts into packaged templates
This commit is contained in:
Xubin Ren
+489
-184
@@ -1,9 +1,10 @@
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"""Memory system for persistent agent memory."""
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"""Memory system: pure file I/O store, lightweight Consolidator, and Dream processor."""
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from __future__ import annotations
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import asyncio
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import json
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import re
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import weakref
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from datetime import datetime
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from pathlib import Path
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@@ -12,94 +13,307 @@ from typing import TYPE_CHECKING, Any, Callable
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from loguru import logger
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from nanobot.utils.prompt_templates import render_template
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from nanobot.utils.helpers import ensure_dir, estimate_message_tokens, estimate_prompt_tokens_chain
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from nanobot.utils.helpers import ensure_dir, estimate_message_tokens, estimate_prompt_tokens_chain, strip_think
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from nanobot.agent.runner import AgentRunSpec, AgentRunner
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from nanobot.agent.tools.registry import ToolRegistry
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from nanobot.utils.gitstore import GitStore
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if TYPE_CHECKING:
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from nanobot.providers.base import LLMProvider
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from nanobot.session.manager import Session, SessionManager
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_SAVE_MEMORY_TOOL = [
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{
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"type": "function",
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"function": {
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"name": "save_memory",
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"description": "Save the memory consolidation result to persistent storage.",
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"parameters": {
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"type": "object",
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"properties": {
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"history_entry": {
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"type": "string",
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"description": "A paragraph summarizing key events/decisions/topics. "
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"Start with [YYYY-MM-DD HH:MM]. Include detail useful for grep search.",
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},
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"memory_update": {
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"type": "string",
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"description": "Full updated long-term memory as markdown. Include all existing "
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"facts plus new ones. Return unchanged if nothing new.",
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},
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},
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"required": ["history_entry", "memory_update"],
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},
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},
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}
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]
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def _ensure_text(value: Any) -> str:
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"""Normalize tool-call payload values to text for file storage."""
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return value if isinstance(value, str) else json.dumps(value, ensure_ascii=False)
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def _normalize_save_memory_args(args: Any) -> dict[str, Any] | None:
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"""Normalize provider tool-call arguments to the expected dict shape."""
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if isinstance(args, str):
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args = json.loads(args)
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if isinstance(args, list):
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return args[0] if args and isinstance(args[0], dict) else None
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return args if isinstance(args, dict) else None
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_TOOL_CHOICE_ERROR_MARKERS = (
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"tool_choice",
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"toolchoice",
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"does not support",
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'should be ["none", "auto"]',
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)
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def _is_tool_choice_unsupported(content: str | None) -> bool:
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"""Detect provider errors caused by forced tool_choice being unsupported."""
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text = (content or "").lower()
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return any(m in text for m in _TOOL_CHOICE_ERROR_MARKERS)
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# ---------------------------------------------------------------------------
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# MemoryStore — pure file I/O layer
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# ---------------------------------------------------------------------------
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class MemoryStore:
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"""Two-layer memory: MEMORY.md (long-term facts) + HISTORY.md (grep-searchable log)."""
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"""Pure file I/O for memory files: MEMORY.md, history.jsonl, SOUL.md, USER.md."""
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_MAX_FAILURES_BEFORE_RAW_ARCHIVE = 3
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_DEFAULT_MAX_HISTORY = 1000
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_LEGACY_ENTRY_START_RE = re.compile(r"^\[(\d{4}-\d{2}-\d{2}[^\]]*)\]\s*")
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_LEGACY_TIMESTAMP_RE = re.compile(r"^\[(\d{4}-\d{2}-\d{2} \d{2}:\d{2})\]\s*")
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_LEGACY_RAW_MESSAGE_RE = re.compile(
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r"^\[\d{4}-\d{2}-\d{2}[^\]]*\]\s+[A-Z][A-Z0-9_]*(?:\s+\[tools:\s*[^\]]+\])?:"
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)
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def __init__(self, workspace: Path):
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def __init__(self, workspace: Path, max_history_entries: int = _DEFAULT_MAX_HISTORY):
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self.workspace = workspace
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self.max_history_entries = max_history_entries
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self.memory_dir = ensure_dir(workspace / "memory")
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self.memory_file = self.memory_dir / "MEMORY.md"
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self.history_file = self.memory_dir / "HISTORY.md"
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self._consecutive_failures = 0
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self.history_file = self.memory_dir / "history.jsonl"
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self.legacy_history_file = self.memory_dir / "HISTORY.md"
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self.soul_file = workspace / "SOUL.md"
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self.user_file = workspace / "USER.md"
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self._cursor_file = self.memory_dir / ".cursor"
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self._dream_cursor_file = self.memory_dir / ".dream_cursor"
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self._git = GitStore(workspace, tracked_files=[
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"SOUL.md", "USER.md", "memory/MEMORY.md",
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])
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self._maybe_migrate_legacy_history()
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def read_long_term(self) -> str:
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if self.memory_file.exists():
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return self.memory_file.read_text(encoding="utf-8")
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return ""
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@property
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def git(self) -> GitStore:
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return self._git
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def write_long_term(self, content: str) -> None:
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# -- generic helpers -----------------------------------------------------
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@staticmethod
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def read_file(path: Path) -> str:
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try:
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return path.read_text(encoding="utf-8")
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except FileNotFoundError:
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return ""
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def _maybe_migrate_legacy_history(self) -> None:
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"""One-time upgrade from legacy HISTORY.md to history.jsonl.
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The migration is best-effort and prioritizes preserving as much content
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as possible over perfect parsing.
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"""
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if not self.legacy_history_file.exists():
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return
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if self.history_file.exists() and self.history_file.stat().st_size > 0:
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return
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try:
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legacy_text = self.legacy_history_file.read_text(
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encoding="utf-8",
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errors="replace",
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)
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except OSError:
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logger.exception("Failed to read legacy HISTORY.md for migration")
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return
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entries = self._parse_legacy_history(legacy_text)
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try:
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if entries:
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self._write_entries(entries)
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last_cursor = entries[-1]["cursor"]
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self._cursor_file.write_text(str(last_cursor), encoding="utf-8")
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# Default to "already processed" so upgrades do not replay the
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# user's entire historical archive into Dream on first start.
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self._dream_cursor_file.write_text(str(last_cursor), encoding="utf-8")
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backup_path = self._next_legacy_backup_path()
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self.legacy_history_file.replace(backup_path)
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logger.info(
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"Migrated legacy HISTORY.md to history.jsonl ({} entries)",
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len(entries),
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)
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except Exception:
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logger.exception("Failed to migrate legacy HISTORY.md")
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def _parse_legacy_history(self, text: str) -> list[dict[str, Any]]:
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normalized = text.replace("\r\n", "\n").replace("\r", "\n").strip()
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if not normalized:
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return []
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fallback_timestamp = self._legacy_fallback_timestamp()
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entries: list[dict[str, Any]] = []
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chunks = self._split_legacy_history_chunks(normalized)
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for cursor, chunk in enumerate(chunks, start=1):
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timestamp = fallback_timestamp
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content = chunk
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match = self._LEGACY_TIMESTAMP_RE.match(chunk)
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if match:
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timestamp = match.group(1)
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remainder = chunk[match.end():].lstrip()
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if remainder:
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content = remainder
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entries.append({
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"cursor": cursor,
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"timestamp": timestamp,
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"content": content,
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})
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return entries
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def _split_legacy_history_chunks(self, text: str) -> list[str]:
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lines = text.split("\n")
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chunks: list[str] = []
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current: list[str] = []
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saw_blank_separator = False
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for line in lines:
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if saw_blank_separator and line.strip() and current:
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chunks.append("\n".join(current).strip())
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current = [line]
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saw_blank_separator = False
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continue
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if self._should_start_new_legacy_chunk(line, current):
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chunks.append("\n".join(current).strip())
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current = [line]
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saw_blank_separator = False
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continue
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current.append(line)
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saw_blank_separator = not line.strip()
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if current:
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chunks.append("\n".join(current).strip())
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return [chunk for chunk in chunks if chunk]
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def _should_start_new_legacy_chunk(self, line: str, current: list[str]) -> bool:
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if not current:
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return False
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if not self._LEGACY_ENTRY_START_RE.match(line):
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return False
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if self._is_raw_legacy_chunk(current) and self._LEGACY_RAW_MESSAGE_RE.match(line):
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return False
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return True
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def _is_raw_legacy_chunk(self, lines: list[str]) -> bool:
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first_nonempty = next((line for line in lines if line.strip()), "")
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match = self._LEGACY_TIMESTAMP_RE.match(first_nonempty)
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if not match:
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return False
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return first_nonempty[match.end():].lstrip().startswith("[RAW]")
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def _legacy_fallback_timestamp(self) -> str:
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try:
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return datetime.fromtimestamp(
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self.legacy_history_file.stat().st_mtime,
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).strftime("%Y-%m-%d %H:%M")
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except OSError:
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return datetime.now().strftime("%Y-%m-%d %H:%M")
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def _next_legacy_backup_path(self) -> Path:
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candidate = self.memory_dir / "HISTORY.md.bak"
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suffix = 2
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while candidate.exists():
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candidate = self.memory_dir / f"HISTORY.md.bak.{suffix}"
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suffix += 1
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return candidate
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# -- MEMORY.md (long-term facts) -----------------------------------------
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def read_memory(self) -> str:
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return self.read_file(self.memory_file)
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def write_memory(self, content: str) -> None:
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self.memory_file.write_text(content, encoding="utf-8")
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def append_history(self, entry: str) -> None:
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with open(self.history_file, "a", encoding="utf-8") as f:
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f.write(entry.rstrip() + "\n\n")
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# -- SOUL.md -------------------------------------------------------------
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def read_soul(self) -> str:
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return self.read_file(self.soul_file)
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def write_soul(self, content: str) -> None:
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self.soul_file.write_text(content, encoding="utf-8")
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# -- USER.md -------------------------------------------------------------
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def read_user(self) -> str:
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return self.read_file(self.user_file)
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def write_user(self, content: str) -> None:
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self.user_file.write_text(content, encoding="utf-8")
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# -- context injection (used by context.py) ------------------------------
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def get_memory_context(self) -> str:
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long_term = self.read_long_term()
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long_term = self.read_memory()
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return f"## Long-term Memory\n{long_term}" if long_term else ""
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# -- history.jsonl — append-only, JSONL format ---------------------------
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def append_history(self, entry: str) -> int:
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"""Append *entry* to history.jsonl and return its auto-incrementing cursor."""
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cursor = self._next_cursor()
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ts = datetime.now().strftime("%Y-%m-%d %H:%M")
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record = {"cursor": cursor, "timestamp": ts, "content": strip_think(entry.rstrip()) or entry.rstrip()}
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with open(self.history_file, "a", encoding="utf-8") as f:
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f.write(json.dumps(record, ensure_ascii=False) + "\n")
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self._cursor_file.write_text(str(cursor), encoding="utf-8")
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return cursor
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def _next_cursor(self) -> int:
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"""Read the current cursor counter and return next value."""
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if self._cursor_file.exists():
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try:
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return int(self._cursor_file.read_text(encoding="utf-8").strip()) + 1
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except (ValueError, OSError):
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pass
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# Fallback: read last line's cursor from the JSONL file.
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last = self._read_last_entry()
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if last:
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return last["cursor"] + 1
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return 1
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def read_unprocessed_history(self, since_cursor: int) -> list[dict[str, Any]]:
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"""Return history entries with cursor > *since_cursor*."""
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return [e for e in self._read_entries() if e["cursor"] > since_cursor]
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def compact_history(self) -> None:
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"""Drop oldest entries if the file exceeds *max_history_entries*."""
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if self.max_history_entries <= 0:
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return
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entries = self._read_entries()
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if len(entries) <= self.max_history_entries:
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return
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kept = entries[-self.max_history_entries:]
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self._write_entries(kept)
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# -- JSONL helpers -------------------------------------------------------
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def _read_entries(self) -> list[dict[str, Any]]:
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"""Read all entries from history.jsonl."""
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entries: list[dict[str, Any]] = []
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try:
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with open(self.history_file, "r", encoding="utf-8") as f:
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for line in f:
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line = line.strip()
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if line:
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try:
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entries.append(json.loads(line))
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except json.JSONDecodeError:
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continue
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except FileNotFoundError:
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pass
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return entries
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def _read_last_entry(self) -> dict[str, Any] | None:
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"""Read the last entry from the JSONL file efficiently."""
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try:
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with open(self.history_file, "rb") as f:
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f.seek(0, 2)
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size = f.tell()
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if size == 0:
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return None
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read_size = min(size, 4096)
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f.seek(size - read_size)
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data = f.read().decode("utf-8")
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lines = [l for l in data.split("\n") if l.strip()]
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if not lines:
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return None
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return json.loads(lines[-1])
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except (FileNotFoundError, json.JSONDecodeError):
|
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return None
|
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def _write_entries(self, entries: list[dict[str, Any]]) -> None:
|
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"""Overwrite history.jsonl with the given entries."""
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with open(self.history_file, "w", encoding="utf-8") as f:
|
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for entry in entries:
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f.write(json.dumps(entry, ensure_ascii=False) + "\n")
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# -- dream cursor --------------------------------------------------------
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def get_last_dream_cursor(self) -> int:
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if self._dream_cursor_file.exists():
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try:
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return int(self._dream_cursor_file.read_text(encoding="utf-8").strip())
|
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except (ValueError, OSError):
|
||||
pass
|
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return 0
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|
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def set_last_dream_cursor(self, cursor: int) -> None:
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self._dream_cursor_file.write_text(str(cursor), encoding="utf-8")
|
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# -- message formatting utility ------------------------------------------
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@staticmethod
|
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def _format_messages(messages: list[dict]) -> str:
|
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lines = []
|
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@@ -112,106 +326,10 @@ class MemoryStore:
|
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)
|
||||
return "\n".join(lines)
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async def consolidate(
|
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self,
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messages: list[dict],
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provider: LLMProvider,
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model: str,
|
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) -> bool:
|
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"""Consolidate the provided message chunk into MEMORY.md + HISTORY.md."""
|
||||
if not messages:
|
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return True
|
||||
|
||||
current_memory = self.read_long_term()
|
||||
prompt = render_template(
|
||||
"agent/memory_consolidate.md",
|
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part="user",
|
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current_memory=current_memory or "(empty)",
|
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conversation=self._format_messages(messages),
|
||||
)
|
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|
||||
chat_messages = [
|
||||
{"role": "system", "content": render_template("agent/memory_consolidate.md", part="system")},
|
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{"role": "user", "content": prompt},
|
||||
]
|
||||
|
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try:
|
||||
forced = {"type": "function", "function": {"name": "save_memory"}}
|
||||
response = await provider.chat_with_retry(
|
||||
messages=chat_messages,
|
||||
tools=_SAVE_MEMORY_TOOL,
|
||||
model=model,
|
||||
tool_choice=forced,
|
||||
)
|
||||
|
||||
if response.finish_reason == "error" and _is_tool_choice_unsupported(
|
||||
response.content
|
||||
):
|
||||
logger.warning("Forced tool_choice unsupported, retrying with auto")
|
||||
response = await provider.chat_with_retry(
|
||||
messages=chat_messages,
|
||||
tools=_SAVE_MEMORY_TOOL,
|
||||
model=model,
|
||||
tool_choice="auto",
|
||||
)
|
||||
|
||||
if not response.has_tool_calls:
|
||||
logger.warning(
|
||||
"Memory consolidation: LLM did not call save_memory "
|
||||
"(finish_reason={}, content_len={}, content_preview={})",
|
||||
response.finish_reason,
|
||||
len(response.content or ""),
|
||||
(response.content or "")[:200],
|
||||
)
|
||||
return self._fail_or_raw_archive(messages)
|
||||
|
||||
args = _normalize_save_memory_args(response.tool_calls[0].arguments)
|
||||
if args is None:
|
||||
logger.warning("Memory consolidation: unexpected save_memory arguments")
|
||||
return self._fail_or_raw_archive(messages)
|
||||
|
||||
if "history_entry" not in args or "memory_update" not in args:
|
||||
logger.warning("Memory consolidation: save_memory payload missing required fields")
|
||||
return self._fail_or_raw_archive(messages)
|
||||
|
||||
entry = args["history_entry"]
|
||||
update = args["memory_update"]
|
||||
|
||||
if entry is None or update is None:
|
||||
logger.warning("Memory consolidation: save_memory payload contains null required fields")
|
||||
return self._fail_or_raw_archive(messages)
|
||||
|
||||
entry = _ensure_text(entry).strip()
|
||||
if not entry:
|
||||
logger.warning("Memory consolidation: history_entry is empty after normalization")
|
||||
return self._fail_or_raw_archive(messages)
|
||||
|
||||
self.append_history(entry)
|
||||
update = _ensure_text(update)
|
||||
if update != current_memory:
|
||||
self.write_long_term(update)
|
||||
|
||||
self._consecutive_failures = 0
|
||||
logger.info("Memory consolidation done for {} messages", len(messages))
|
||||
return True
|
||||
except Exception:
|
||||
logger.exception("Memory consolidation failed")
|
||||
return self._fail_or_raw_archive(messages)
|
||||
|
||||
def _fail_or_raw_archive(self, messages: list[dict]) -> bool:
|
||||
"""Increment failure count; after threshold, raw-archive messages and return True."""
|
||||
self._consecutive_failures += 1
|
||||
if self._consecutive_failures < self._MAX_FAILURES_BEFORE_RAW_ARCHIVE:
|
||||
return False
|
||||
self._raw_archive(messages)
|
||||
self._consecutive_failures = 0
|
||||
return True
|
||||
|
||||
def _raw_archive(self, messages: list[dict]) -> None:
|
||||
"""Fallback: dump raw messages to HISTORY.md without LLM summarization."""
|
||||
ts = datetime.now().strftime("%Y-%m-%d %H:%M")
|
||||
def raw_archive(self, messages: list[dict]) -> None:
|
||||
"""Fallback: dump raw messages to history.jsonl without LLM summarization."""
|
||||
self.append_history(
|
||||
f"[{ts}] [RAW] {len(messages)} messages\n"
|
||||
f"[RAW] {len(messages)} messages\n"
|
||||
f"{self._format_messages(messages)}"
|
||||
)
|
||||
logger.warning(
|
||||
@@ -219,8 +337,14 @@ class MemoryStore:
|
||||
)
|
||||
|
||||
|
||||
class MemoryConsolidator:
|
||||
"""Owns consolidation policy, locking, and session offset updates."""
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Consolidator — lightweight token-budget triggered consolidation
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
class Consolidator:
|
||||
"""Lightweight consolidation: summarizes evicted messages into history.jsonl."""
|
||||
|
||||
_MAX_CONSOLIDATION_ROUNDS = 5
|
||||
|
||||
@@ -228,7 +352,7 @@ class MemoryConsolidator:
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
workspace: Path,
|
||||
store: MemoryStore,
|
||||
provider: LLMProvider,
|
||||
model: str,
|
||||
sessions: SessionManager,
|
||||
@@ -237,7 +361,7 @@ class MemoryConsolidator:
|
||||
get_tool_definitions: Callable[[], list[dict[str, Any]]],
|
||||
max_completion_tokens: int = 4096,
|
||||
):
|
||||
self.store = MemoryStore(workspace)
|
||||
self.store = store
|
||||
self.provider = provider
|
||||
self.model = model
|
||||
self.sessions = sessions
|
||||
@@ -245,16 +369,14 @@ class MemoryConsolidator:
|
||||
self.max_completion_tokens = max_completion_tokens
|
||||
self._build_messages = build_messages
|
||||
self._get_tool_definitions = get_tool_definitions
|
||||
self._locks: weakref.WeakValueDictionary[str, asyncio.Lock] = weakref.WeakValueDictionary()
|
||||
self._locks: weakref.WeakValueDictionary[str, asyncio.Lock] = (
|
||||
weakref.WeakValueDictionary()
|
||||
)
|
||||
|
||||
def get_lock(self, session_key: str) -> asyncio.Lock:
|
||||
"""Return the shared consolidation lock for one session."""
|
||||
return self._locks.setdefault(session_key, asyncio.Lock())
|
||||
|
||||
async def consolidate_messages(self, messages: list[dict[str, object]]) -> bool:
|
||||
"""Archive a selected message chunk into persistent memory."""
|
||||
return await self.store.consolidate(messages, self.provider, self.model)
|
||||
|
||||
def pick_consolidation_boundary(
|
||||
self,
|
||||
session: Session,
|
||||
@@ -294,14 +416,37 @@ class MemoryConsolidator:
|
||||
self._get_tool_definitions(),
|
||||
)
|
||||
|
||||
async def archive_messages(self, messages: list[dict[str, object]]) -> bool:
|
||||
"""Archive messages with guaranteed persistence (retries until raw-dump fallback)."""
|
||||
async def archive(self, messages: list[dict]) -> bool:
|
||||
"""Summarize messages via LLM and append to history.jsonl.
|
||||
|
||||
Returns True on success (or degraded success), False if nothing to do.
|
||||
"""
|
||||
if not messages:
|
||||
return False
|
||||
try:
|
||||
formatted = MemoryStore._format_messages(messages)
|
||||
response = await self.provider.chat_with_retry(
|
||||
model=self.model,
|
||||
messages=[
|
||||
{
|
||||
"role": "system",
|
||||
"content": render_template(
|
||||
"agent/consolidator_archive.md",
|
||||
strip=True,
|
||||
),
|
||||
},
|
||||
{"role": "user", "content": formatted},
|
||||
],
|
||||
tools=None,
|
||||
tool_choice=None,
|
||||
)
|
||||
summary = response.content or "[no summary]"
|
||||
self.store.append_history(summary)
|
||||
return True
|
||||
except Exception:
|
||||
logger.warning("Consolidation LLM call failed, raw-dumping to history")
|
||||
self.store.raw_archive(messages)
|
||||
return True
|
||||
for _ in range(self.store._MAX_FAILURES_BEFORE_RAW_ARCHIVE):
|
||||
if await self.consolidate_messages(messages):
|
||||
return True
|
||||
return True
|
||||
|
||||
async def maybe_consolidate_by_tokens(self, session: Session) -> None:
|
||||
"""Loop: archive old messages until prompt fits within safe budget.
|
||||
@@ -356,7 +501,7 @@ class MemoryConsolidator:
|
||||
source,
|
||||
len(chunk),
|
||||
)
|
||||
if not await self.consolidate_messages(chunk):
|
||||
if not await self.archive(chunk):
|
||||
return
|
||||
session.last_consolidated = end_idx
|
||||
self.sessions.save(session)
|
||||
@@ -364,3 +509,163 @@ class MemoryConsolidator:
|
||||
estimated, source = self.estimate_session_prompt_tokens(session)
|
||||
if estimated <= 0:
|
||||
return
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Dream — heavyweight cron-scheduled memory consolidation
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
class Dream:
|
||||
"""Two-phase memory processor: analyze history.jsonl, then edit files via AgentRunner.
|
||||
|
||||
Phase 1 produces an analysis summary (plain LLM call).
|
||||
Phase 2 delegates to AgentRunner with read_file / edit_file tools so the
|
||||
LLM can make targeted, incremental edits instead of replacing entire files.
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
store: MemoryStore,
|
||||
provider: LLMProvider,
|
||||
model: str,
|
||||
max_batch_size: int = 20,
|
||||
max_iterations: int = 10,
|
||||
max_tool_result_chars: int = 16_000,
|
||||
):
|
||||
self.store = store
|
||||
self.provider = provider
|
||||
self.model = model
|
||||
self.max_batch_size = max_batch_size
|
||||
self.max_iterations = max_iterations
|
||||
self.max_tool_result_chars = max_tool_result_chars
|
||||
self._runner = AgentRunner(provider)
|
||||
self._tools = self._build_tools()
|
||||
|
||||
# -- tool registry -------------------------------------------------------
|
||||
|
||||
def _build_tools(self) -> ToolRegistry:
|
||||
"""Build a minimal tool registry for the Dream agent."""
|
||||
from nanobot.agent.tools.filesystem import EditFileTool, ReadFileTool
|
||||
|
||||
tools = ToolRegistry()
|
||||
workspace = self.store.workspace
|
||||
tools.register(ReadFileTool(workspace=workspace, allowed_dir=workspace))
|
||||
tools.register(EditFileTool(workspace=workspace, allowed_dir=workspace))
|
||||
return tools
|
||||
|
||||
# -- main entry ----------------------------------------------------------
|
||||
|
||||
async def run(self) -> bool:
|
||||
"""Process unprocessed history entries. Returns True if work was done."""
|
||||
last_cursor = self.store.get_last_dream_cursor()
|
||||
entries = self.store.read_unprocessed_history(since_cursor=last_cursor)
|
||||
if not entries:
|
||||
return False
|
||||
|
||||
batch = entries[: self.max_batch_size]
|
||||
logger.info(
|
||||
"Dream: processing {} entries (cursor {}→{}), batch={}",
|
||||
len(entries), last_cursor, batch[-1]["cursor"], len(batch),
|
||||
)
|
||||
|
||||
# Build history text for LLM
|
||||
history_text = "\n".join(
|
||||
f"[{e['timestamp']}] {e['content']}" for e in batch
|
||||
)
|
||||
|
||||
# Current file contents
|
||||
current_memory = self.store.read_memory() or "(empty)"
|
||||
current_soul = self.store.read_soul() or "(empty)"
|
||||
current_user = self.store.read_user() or "(empty)"
|
||||
file_context = (
|
||||
f"## Current MEMORY.md\n{current_memory}\n\n"
|
||||
f"## Current SOUL.md\n{current_soul}\n\n"
|
||||
f"## Current USER.md\n{current_user}"
|
||||
)
|
||||
|
||||
# Phase 1: Analyze
|
||||
phase1_prompt = (
|
||||
f"## Conversation History\n{history_text}\n\n{file_context}"
|
||||
)
|
||||
|
||||
try:
|
||||
phase1_response = await self.provider.chat_with_retry(
|
||||
model=self.model,
|
||||
messages=[
|
||||
{
|
||||
"role": "system",
|
||||
"content": render_template("agent/dream_phase1.md", strip=True),
|
||||
},
|
||||
{"role": "user", "content": phase1_prompt},
|
||||
],
|
||||
tools=None,
|
||||
tool_choice=None,
|
||||
)
|
||||
analysis = phase1_response.content or ""
|
||||
logger.debug("Dream Phase 1 complete ({} chars)", len(analysis))
|
||||
except Exception:
|
||||
logger.exception("Dream Phase 1 failed")
|
||||
return False
|
||||
|
||||
# Phase 2: Delegate to AgentRunner with read_file / edit_file
|
||||
phase2_prompt = f"## Analysis Result\n{analysis}\n\n{file_context}"
|
||||
|
||||
tools = self._tools
|
||||
messages: list[dict[str, Any]] = [
|
||||
{
|
||||
"role": "system",
|
||||
"content": render_template("agent/dream_phase2.md", strip=True),
|
||||
},
|
||||
{"role": "user", "content": phase2_prompt},
|
||||
]
|
||||
|
||||
try:
|
||||
result = await self._runner.run(AgentRunSpec(
|
||||
initial_messages=messages,
|
||||
tools=tools,
|
||||
model=self.model,
|
||||
max_iterations=self.max_iterations,
|
||||
max_tool_result_chars=self.max_tool_result_chars,
|
||||
fail_on_tool_error=True,
|
||||
))
|
||||
logger.debug(
|
||||
"Dream Phase 2 complete: stop_reason={}, tool_events={}",
|
||||
result.stop_reason, len(result.tool_events),
|
||||
)
|
||||
except Exception:
|
||||
logger.exception("Dream Phase 2 failed")
|
||||
result = None
|
||||
|
||||
# Build changelog from tool events
|
||||
changelog: list[str] = []
|
||||
if result and result.tool_events:
|
||||
for event in result.tool_events:
|
||||
if event["status"] == "ok":
|
||||
changelog.append(f"{event['name']}: {event['detail']}")
|
||||
|
||||
# Advance cursor — always, to avoid re-processing Phase 1
|
||||
new_cursor = batch[-1]["cursor"]
|
||||
self.store.set_last_dream_cursor(new_cursor)
|
||||
self.store.compact_history()
|
||||
|
||||
if result and result.stop_reason == "completed":
|
||||
logger.info(
|
||||
"Dream done: {} change(s), cursor advanced to {}",
|
||||
len(changelog), new_cursor,
|
||||
)
|
||||
else:
|
||||
reason = result.stop_reason if result else "exception"
|
||||
logger.warning(
|
||||
"Dream incomplete ({}): cursor advanced to {}",
|
||||
reason, new_cursor,
|
||||
)
|
||||
|
||||
# Git auto-commit (only when there are actual changes)
|
||||
if changelog and self.store.git.is_initialized():
|
||||
ts = batch[-1]["timestamp"]
|
||||
sha = self.store.git.auto_commit(f"dream: {ts}, {len(changelog)} change(s)")
|
||||
if sha:
|
||||
logger.info("Dream commit: {}", sha)
|
||||
|
||||
return True
|
||||
|
||||
Reference in New Issue
Block a user