nanobot/nanobot/agent/context.py
Jack Lu d436a1d678 feat: integrate Jinja2 templating for agent responses and memory consolidation
- Added Jinja2 template support for various agent responses, including identity, skills, and memory consolidation.
- Introduced new templates for evaluating notifications, handling subagent announcements, and managing platform policies.
- Updated the agent context and memory modules to utilize the new templating system for improved readability and maintainability.
- Added a new dependency on Jinja2 in pyproject.toml.
2026-04-04 14:18:22 +08:00

183 lines
7.0 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))
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