Files
hermes-agent/plugins/memory/byterover/__init__.py
Dat Pham b3319b1252 fix(memory): Fix ByteRover plugin - run brv query synchronously before LLM call
The pipeline prefetch design was firing \`brv query\` in a background
thread *after* each response, meaning the context injected at turn N
was from turn N-1's message — and the first turn got no BRV context
at all. Replace the async prefetch pipeline with a synchronous query
in \`prefetch()\` so recall runs before the first API call on every
turn. Make \`queue_prefetch()\` a no-op and remove the now-unused
pipeline state.
2026-04-03 12:11:29 -07:00

384 lines
13 KiB
Python

"""ByteRover memory plugin — MemoryProvider interface.
Persistent memory via the ByteRover CLI (``brv``). Organizes knowledge into
a hierarchical context tree with tiered retrieval (fuzzy text → LLM-driven
search). Local-first with optional cloud sync.
Original PR #3499 by hieuntg81, adapted to MemoryProvider ABC.
Requires: ``brv`` CLI installed (npm install -g byterover-cli or
curl -fsSL https://byterover.dev/install.sh | sh).
Config via environment variables (profile-scoped via each profile's .env):
BRV_API_KEY — ByteRover API key (for cloud features, optional for local)
Working directory: $HERMES_HOME/byterover/ (profile-scoped context tree)
"""
from __future__ import annotations
import json
import logging
import os
import shutil
import subprocess
import threading
import time
from pathlib import Path
from typing import Any, Dict, List, Optional
from agent.memory_provider import MemoryProvider
logger = logging.getLogger(__name__)
# Timeouts
_QUERY_TIMEOUT = 10 # brv query — should be fast
_CURATE_TIMEOUT = 120 # brv curate — may involve LLM processing
# Minimum lengths to filter noise
_MIN_QUERY_LEN = 10
_MIN_OUTPUT_LEN = 20
# ---------------------------------------------------------------------------
# brv binary resolution (cached, thread-safe)
# ---------------------------------------------------------------------------
_brv_path_lock = threading.Lock()
_cached_brv_path: Optional[str] = None
def _resolve_brv_path() -> Optional[str]:
"""Find the brv binary on PATH or well-known install locations."""
global _cached_brv_path
with _brv_path_lock:
if _cached_brv_path is not None:
return _cached_brv_path if _cached_brv_path != "" else None
found = shutil.which("brv")
if not found:
home = Path.home()
candidates = [
home / ".brv-cli" / "bin" / "brv",
Path("/usr/local/bin/brv"),
home / ".npm-global" / "bin" / "brv",
]
for c in candidates:
if c.exists():
found = str(c)
break
with _brv_path_lock:
if _cached_brv_path is not None:
return _cached_brv_path if _cached_brv_path != "" else None
_cached_brv_path = found or ""
return found
def _run_brv(args: List[str], timeout: int = _QUERY_TIMEOUT,
cwd: str = None) -> dict:
"""Run a brv CLI command. Returns {success, output, error}."""
brv_path = _resolve_brv_path()
if not brv_path:
return {"success": False, "error": "brv CLI not found. Install: npm install -g byterover-cli"}
cmd = [brv_path] + args
effective_cwd = cwd or str(_get_brv_cwd())
Path(effective_cwd).mkdir(parents=True, exist_ok=True)
env = os.environ.copy()
brv_bin_dir = str(Path(brv_path).parent)
env["PATH"] = brv_bin_dir + os.pathsep + env.get("PATH", "")
try:
result = subprocess.run(
cmd, capture_output=True, text=True,
timeout=timeout, cwd=effective_cwd, env=env,
)
stdout = result.stdout.strip()
stderr = result.stderr.strip()
if result.returncode == 0:
return {"success": True, "output": stdout}
return {"success": False, "error": stderr or stdout or f"brv exited {result.returncode}"}
except subprocess.TimeoutExpired:
return {"success": False, "error": f"brv timed out after {timeout}s"}
except FileNotFoundError:
global _cached_brv_path
with _brv_path_lock:
_cached_brv_path = None
return {"success": False, "error": "brv CLI not found"}
except Exception as e:
return {"success": False, "error": str(e)}
def _get_brv_cwd() -> Path:
"""Profile-scoped working directory for the brv context tree."""
from hermes_constants import get_hermes_home
return get_hermes_home() / "byterover"
# ---------------------------------------------------------------------------
# Tool schemas
# ---------------------------------------------------------------------------
QUERY_SCHEMA = {
"name": "brv_query",
"description": (
"Search ByteRover's persistent knowledge tree for relevant context. "
"Returns memories, project knowledge, architectural decisions, and "
"patterns from previous sessions. Use for any question where past "
"context would help."
),
"parameters": {
"type": "object",
"properties": {
"query": {"type": "string", "description": "What to search for."},
},
"required": ["query"],
},
}
CURATE_SCHEMA = {
"name": "brv_curate",
"description": (
"Store important information in ByteRover's persistent knowledge tree. "
"Use for architectural decisions, bug fixes, user preferences, project "
"patterns — anything worth remembering across sessions. ByteRover's LLM "
"automatically categorizes and organizes the memory."
),
"parameters": {
"type": "object",
"properties": {
"content": {"type": "string", "description": "The information to remember."},
},
"required": ["content"],
},
}
STATUS_SCHEMA = {
"name": "brv_status",
"description": "Check ByteRover status — CLI version, context tree stats, cloud sync state.",
"parameters": {"type": "object", "properties": {}, "required": []},
}
# ---------------------------------------------------------------------------
# MemoryProvider implementation
# ---------------------------------------------------------------------------
class ByteRoverMemoryProvider(MemoryProvider):
"""ByteRover persistent memory via the brv CLI."""
def __init__(self):
self._cwd = ""
self._session_id = ""
self._turn_count = 0
self._sync_thread: Optional[threading.Thread] = None
@property
def name(self) -> str:
return "byterover"
def is_available(self) -> bool:
"""Check if brv CLI is installed. No network calls."""
return _resolve_brv_path() is not None
def get_config_schema(self):
return [
{
"key": "api_key",
"description": "ByteRover API key (optional, for cloud sync)",
"secret": True,
"env_var": "BRV_API_KEY",
"url": "https://app.byterover.dev",
},
]
def initialize(self, session_id: str, **kwargs) -> None:
self._cwd = str(_get_brv_cwd())
self._session_id = session_id
self._turn_count = 0
Path(self._cwd).mkdir(parents=True, exist_ok=True)
def system_prompt_block(self) -> str:
if not _resolve_brv_path():
return ""
return (
"# ByteRover Memory\n"
"Active. Persistent knowledge tree with hierarchical context.\n"
"Use brv_query to search past knowledge, brv_curate to store "
"important facts, brv_status to check state."
)
def prefetch(self, query: str, *, session_id: str = "") -> str:
"""Run brv query synchronously before the agent's first LLM call.
Blocks until the query completes (up to _QUERY_TIMEOUT seconds), ensuring
the result is available as context before the model is called.
"""
if not query or len(query.strip()) < _MIN_QUERY_LEN:
return ""
result = _run_brv(
["query", "--", query.strip()[:5000]],
timeout=_QUERY_TIMEOUT, cwd=self._cwd,
)
if result["success"] and result.get("output"):
output = result["output"].strip()
if len(output) > _MIN_OUTPUT_LEN:
return f"## ByteRover Context\n{output}"
return ""
def queue_prefetch(self, query: str, *, session_id: str = "") -> None:
"""No-op: prefetch() now runs synchronously at turn start."""
pass
def sync_turn(self, user_content: str, assistant_content: str, *, session_id: str = "") -> None:
"""Curate the conversation turn in background (non-blocking)."""
self._turn_count += 1
# Only curate substantive turns
if len(user_content.strip()) < _MIN_QUERY_LEN:
return
def _sync():
try:
combined = f"User: {user_content[:2000]}\nAssistant: {assistant_content[:2000]}"
_run_brv(
["curate", "--", combined],
timeout=_CURATE_TIMEOUT, cwd=self._cwd,
)
except Exception as e:
logger.debug("ByteRover sync failed: %s", e)
# Wait for previous sync
if self._sync_thread and self._sync_thread.is_alive():
self._sync_thread.join(timeout=5.0)
self._sync_thread = threading.Thread(
target=_sync, daemon=True, name="brv-sync"
)
self._sync_thread.start()
def on_memory_write(self, action: str, target: str, content: str) -> None:
"""Mirror built-in memory writes to ByteRover."""
if action not in ("add", "replace") or not content:
return
def _write():
try:
label = "User profile" if target == "user" else "Agent memory"
_run_brv(
["curate", "--", f"[{label}] {content}"],
timeout=_CURATE_TIMEOUT, cwd=self._cwd,
)
except Exception as e:
logger.debug("ByteRover memory mirror failed: %s", e)
t = threading.Thread(target=_write, daemon=True, name="brv-memwrite")
t.start()
def on_pre_compress(self, messages: List[Dict[str, Any]]) -> str:
"""Extract insights before context compression discards turns."""
if not messages:
return ""
# Build a summary of messages about to be compressed
parts = []
for msg in messages[-10:]: # last 10 messages
role = msg.get("role", "")
content = msg.get("content", "")
if isinstance(content, str) and content.strip() and role in ("user", "assistant"):
parts.append(f"{role}: {content[:500]}")
if not parts:
return ""
combined = "\n".join(parts)
def _flush():
try:
_run_brv(
["curate", "--", f"[Pre-compression context]\n{combined}"],
timeout=_CURATE_TIMEOUT, cwd=self._cwd,
)
logger.info("ByteRover pre-compression flush: %d messages", len(parts))
except Exception as e:
logger.debug("ByteRover pre-compression flush failed: %s", e)
t = threading.Thread(target=_flush, daemon=True, name="brv-flush")
t.start()
return ""
def get_tool_schemas(self) -> List[Dict[str, Any]]:
return [QUERY_SCHEMA, CURATE_SCHEMA, STATUS_SCHEMA]
def handle_tool_call(self, tool_name: str, args: dict, **kwargs) -> str:
if tool_name == "brv_query":
return self._tool_query(args)
elif tool_name == "brv_curate":
return self._tool_curate(args)
elif tool_name == "brv_status":
return self._tool_status()
return json.dumps({"error": f"Unknown tool: {tool_name}"})
def shutdown(self) -> None:
if self._sync_thread and self._sync_thread.is_alive():
self._sync_thread.join(timeout=10.0)
# -- Tool implementations ------------------------------------------------
def _tool_query(self, args: dict) -> str:
query = args.get("query", "")
if not query:
return json.dumps({"error": "query is required"})
result = _run_brv(
["query", "--", query.strip()[:5000]],
timeout=_QUERY_TIMEOUT, cwd=self._cwd,
)
if not result["success"]:
return json.dumps({"error": result.get("error", "Query failed")})
output = result.get("output", "").strip()
if not output or len(output) < _MIN_OUTPUT_LEN:
return json.dumps({"result": "No relevant memories found."})
# Truncate very long results
if len(output) > 8000:
output = output[:8000] + "\n\n[... truncated]"
return json.dumps({"result": output})
def _tool_curate(self, args: dict) -> str:
content = args.get("content", "")
if not content:
return json.dumps({"error": "content is required"})
result = _run_brv(
["curate", "--", content],
timeout=_CURATE_TIMEOUT, cwd=self._cwd,
)
if not result["success"]:
return json.dumps({"error": result.get("error", "Curate failed")})
return json.dumps({"result": "Memory curated successfully."})
def _tool_status(self) -> str:
result = _run_brv(["status"], timeout=15, cwd=self._cwd)
if not result["success"]:
return json.dumps({"error": result.get("error", "Status check failed")})
return json.dumps({"status": result.get("output", "")})
# ---------------------------------------------------------------------------
# Plugin entry point
# ---------------------------------------------------------------------------
def register(ctx) -> None:
"""Register ByteRover as a memory provider plugin."""
ctx.register_memory_provider(ByteRoverMemoryProvider())