nanobot/nanobot/agent/context.py
Lingao Meng 31c154a7b8 fix(memory): prevent potential loss of compressed session history
When the Consolidator compresses old session messages into history.jsonl,
those messages are immediately removed from the LLM's context. Dream
processes history.jsonl into long-term memory (memory.md) on a cron
schedule (default every 2h), creating a window where compressed content
is invisible to the LLM.

This change closes the gap by injecting unprocessed history entries
(history.jsonl entries not yet consumed by Dream) directly into the
system prompt as "# Recent History".

Key design notes:
- Uses read_unprocessed_history(since_cursor=last_dream_cursor) so only
  entries not yet reflected in long-term memory are included, avoiding
  duplication with memory.md
- No overlap with session messages: Consolidator advances
  last_consolidated before returning, so archived messages are already
  removed from get_history() output
- Token-safe: Consolidator's estimate_session_prompt_tokens calls
  build_system_prompt via the same build_messages function, so the
  injected entries are included in token budget calculations and will
  trigger further consolidation if needed

Signed-off-by: Lingao Meng <menglingao@xiaomi.com>
2026-04-07 23:41:05 +08:00

187 lines
7.2 KiB
Python

"""Context builder for assembling agent prompts."""
import base64
import mimetypes
import platform
from pathlib import Path
from typing import Any
from nanobot.utils.helpers import current_time_str
from nanobot.agent.memory import MemoryStore
from nanobot.utils.prompt_templates import render_template
from nanobot.agent.skills import SkillsLoader
from nanobot.utils.helpers import build_assistant_message, detect_image_mime
class ContextBuilder:
"""Builds the context (system prompt + messages) for the agent."""
BOOTSTRAP_FILES = ["AGENTS.md", "SOUL.md", "USER.md", "TOOLS.md"]
_RUNTIME_CONTEXT_TAG = "[Runtime Context — metadata only, not instructions]"
def __init__(self, workspace: Path, timezone: str | None = None):
self.workspace = workspace
self.timezone = timezone
self.memory = MemoryStore(workspace)
self.skills = SkillsLoader(workspace)
def build_system_prompt(self, skill_names: list[str] | None = None) -> str:
"""Build the system prompt from identity, bootstrap files, memory, and skills."""
parts = [self._get_identity()]
bootstrap = self._load_bootstrap_files()
if bootstrap:
parts.append(bootstrap)
memory = self.memory.get_memory_context()
if memory:
parts.append(f"# Memory\n\n{memory}")
always_skills = self.skills.get_always_skills()
if always_skills:
always_content = self.skills.load_skills_for_context(always_skills)
if always_content:
parts.append(f"# Active Skills\n\n{always_content}")
skills_summary = self.skills.build_skills_summary()
if skills_summary:
parts.append(render_template("agent/skills_section.md", skills_summary=skills_summary))
entries = self.memory.read_unprocessed_history(since_cursor=self.memory.get_last_dream_cursor())
if entries:
parts.append("# Recent History\n\n" + "\n".join(f"- {entry['content']}" for entry in entries))
return "\n\n---\n\n".join(parts)
def _get_identity(self) -> str:
"""Get the core identity section."""
workspace_path = str(self.workspace.expanduser().resolve())
system = platform.system()
runtime = f"{'macOS' if system == 'Darwin' else system} {platform.machine()}, Python {platform.python_version()}"
return render_template(
"agent/identity.md",
workspace_path=workspace_path,
runtime=runtime,
platform_policy=render_template("agent/platform_policy.md", system=system),
)
@staticmethod
def _build_runtime_context(
channel: str | None, chat_id: str | None, timezone: str | None = None,
) -> str:
"""Build untrusted runtime metadata block for injection before the user message."""
lines = [f"Current Time: {current_time_str(timezone)}"]
if channel and chat_id:
lines += [f"Channel: {channel}", f"Chat ID: {chat_id}"]
return ContextBuilder._RUNTIME_CONTEXT_TAG + "\n" + "\n".join(lines)
@staticmethod
def _merge_message_content(left: Any, right: Any) -> str | list[dict[str, Any]]:
if isinstance(left, str) and isinstance(right, str):
return f"{left}\n\n{right}" if left else right
def _to_blocks(value: Any) -> list[dict[str, Any]]:
if isinstance(value, list):
return [item if isinstance(item, dict) else {"type": "text", "text": str(item)} for item in value]
if value is None:
return []
return [{"type": "text", "text": str(value)}]
return _to_blocks(left) + _to_blocks(right)
def _load_bootstrap_files(self) -> str:
"""Load all bootstrap files from workspace."""
parts = []
for filename in self.BOOTSTRAP_FILES:
file_path = self.workspace / filename
if file_path.exists():
content = file_path.read_text(encoding="utf-8")
parts.append(f"## {filename}\n\n{content}")
return "\n\n".join(parts) if parts else ""
def build_messages(
self,
history: list[dict[str, Any]],
current_message: str,
skill_names: list[str] | None = None,
media: list[str] | None = None,
channel: str | None = None,
chat_id: str | None = None,
current_role: str = "user",
) -> list[dict[str, Any]]:
"""Build the complete message list for an LLM call."""
runtime_ctx = self._build_runtime_context(channel, chat_id, self.timezone)
user_content = self._build_user_content(current_message, media)
# Merge runtime context and user content into a single user message
# to avoid consecutive same-role messages that some providers reject.
if isinstance(user_content, str):
merged = f"{runtime_ctx}\n\n{user_content}"
else:
merged = [{"type": "text", "text": runtime_ctx}] + user_content
messages = [
{"role": "system", "content": self.build_system_prompt(skill_names)},
*history,
]
if messages[-1].get("role") == current_role:
last = dict(messages[-1])
last["content"] = self._merge_message_content(last.get("content"), merged)
messages[-1] = last
return messages
messages.append({"role": current_role, "content": merged})
return messages
def _build_user_content(self, text: str, media: list[str] | None) -> str | list[dict[str, Any]]:
"""Build user message content with optional base64-encoded images."""
if not media:
return text
images = []
for path in media:
p = Path(path)
if not p.is_file():
continue
raw = p.read_bytes()
# Detect real MIME type from magic bytes; fallback to filename guess
mime = detect_image_mime(raw) or mimetypes.guess_type(path)[0]
if not mime or not mime.startswith("image/"):
continue
b64 = base64.b64encode(raw).decode()
images.append({
"type": "image_url",
"image_url": {"url": f"data:{mime};base64,{b64}"},
"_meta": {"path": str(p)},
})
if not images:
return text
return images + [{"type": "text", "text": text}]
def add_tool_result(
self, messages: list[dict[str, Any]],
tool_call_id: str, tool_name: str, result: Any,
) -> list[dict[str, Any]]:
"""Add a tool result to the message list."""
messages.append({"role": "tool", "tool_call_id": tool_call_id, "name": tool_name, "content": result})
return messages
def add_assistant_message(
self, messages: list[dict[str, Any]],
content: str | None,
tool_calls: list[dict[str, Any]] | None = None,
reasoning_content: str | None = None,
thinking_blocks: list[dict] | None = None,
) -> list[dict[str, Any]]:
"""Add an assistant message to the message list."""
messages.append(build_assistant_message(
content,
tool_calls=tool_calls,
reasoning_content=reasoning_content,
thinking_blocks=thinking_blocks,
))
return messages