feat: load operator instructions from agents/*.md into the reply prompt
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Drop Markdown files into an agents/ folder and their contents are appended to
the main reply LLM's system prompt, so an operator can extend the assistant's
rules/tone without code changes. Files are concatenated in filename order
(use 00-, 10- prefixes to control ordering) and re-read once per turn, so edits
apply on the next reply with no rebuild/restart. Fail-open: a missing, empty,
or unreadable folder yields no instructions and never breaks a reply.

- load_agent_instructions() in system_prompt.py (AGENTS_DIR env, default
  /app/agents); reads *.md only, skips blanks, ignores non-dir paths
- engine.py appends it alongside the existing settings-UI llm_instructions,
  under the same "Additional instructions from the operator:" framing
- docker-compose.yml bind-mounts ./agents:/app/agents:ro and sets AGENTS_DIR
- agents/example.md.sample starter template (.sample is not loaded)
- tests cover ordering, md-only filtering, blank-skip, env/arg resolution,
  and fail-open paths
- README, .env.example, docs/llm_contexts.md updated

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
This commit is contained in:
javis-bot
2026-06-23 00:57:54 +09:00
parent 677bfcd2a9
commit 2f000ac6c8
8 changed files with 156 additions and 1 deletions

View File

@@ -9,7 +9,11 @@ import os
from typing import Optional, TYPE_CHECKING
from ..utils.redact import redact
from ..system_prompt import build_system_prompt, reply_language_directive
from ..system_prompt import (
build_system_prompt,
load_agent_instructions,
reply_language_directive,
)
from ..tools.registry import run_tool_with_retries, generate_tools_description, generate_tools_json_schema, BUILTIN_TOOLS
from ..tools.builtin.stop import STOP_SIGNAL
from ..debug import debug_log
@@ -1702,6 +1706,10 @@ def run_reply_engine(db: "Database", cfg, tts: Optional[Any],
# the directive used the config value made the two contradict each other.
_output_language = _resolve_output_language()
_persona_prompt = build_system_prompt(_assistant_name, _output_language)
# File-based operator instructions: every *.md in AGENTS_DIR (default
# /app/agents, bind-mounted from ./agents). Read once per turn so edits in
# the folder apply on the next reply without a restart; fail-open to "".
_agent_instructions = load_agent_instructions()
def _build_initial_system_message() -> str:
guidance = [_persona_prompt.strip()]
@@ -1810,6 +1818,12 @@ def run_reply_engine(db: "Database", cfg, tts: Optional[Any],
if _user_instructions:
guidance.append("Additional instructions from the operator:\n" + _user_instructions)
# File-based operator instructions: the concatenated agents/*.md content
# resolved once above. Same framing/placement as the settings-UI field
# so both are treated as authoritative operator guidance.
if _agent_instructions:
guidance.append("Additional instructions from the operator:\n" + _agent_instructions)
# Recency reinforcement: repeat the language lock at the very END too.
# In a ~5k-token prompt the front-placed rule gets "lost in the middle";
# bigger models (qwen2.5:7b) otherwise leak Chinese/Cyrillic mid-reply.