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"""
helix_state.py β In-Process Graph State Manager
βββββββββββββββββββββββββββββββββββββββββββββββ
Implements the same graph API that HelixDB would expose via Python bindings,
but runs entirely in-process (zero network, zero daemon, ~0 MB overhead).
Why not Redis?
Redis requires a separate daemon process (~200 MB RAM) and TCP round-trips.
This module stores the same data as a Python dict-of-dicts with O(1) node
lookup and O(k) edge traversal where k = number of edges per node.
Why not flat dicts in backend.py?
A graph model lets us express relationships that flat dicts cannot:
Project β HAS_TASK β Task
Task β USES_FILE β File
File β HAD_BUG β Bug
Bug β FIXED_BY β Snippet (in Second Brain)
This powers the Bell Curve apex prompt: we can query "What file is this
task working on?" and load exactly that file β nothing more.
Drop-in swap: When HelixDB ships stable Python bindings, replace this
file with: from helixdb import HelixDB as HelixStateDB
The public API (add_node, add_edge, get_node, get_neighbors, update_node,
remove_node, query_path) is kept identical to the planned HelixDB SDK.
"""
import time
import logging
import threading
from typing import Any, Dict, List, Optional, Tuple
logger = logging.getLogger("helix_state")
class HelixStateDB:
"""
In-process graph database.
Graph model:
Nodes: { node_type: { node_id: { **properties } } }
Edges: { (src_type, src_id, edge_label, dst_type, dst_id): { **properties } }
Thread-safe for concurrent FastAPI request handlers.
"""
def __init__(self):
self._nodes: Dict[str, Dict[str, Dict[str, Any]]] = {}
self._edges: Dict[Tuple, Dict[str, Any]] = {}
self._lock = threading.RLock()
logger.info("[HelixState] In-process graph database initialised.")
# ββ Node Operations βββββββββββββββββββββββββββββββββββββββββββββββββββββββ
def add_node(self, node_type: str, node_id: str, **props) -> bool:
"""Insert or replace a node. Returns True on success."""
with self._lock:
if node_type not in self._nodes:
self._nodes[node_type] = {}
self._nodes[node_type][node_id] = {
**props,
"_created_at": time.time(),
"_updated_at": time.time(),
}
logger.debug("[HelixState] add_node(%s, %s)", node_type, node_id)
return True
def update_node(self, node_type: str, node_id: str, **props) -> bool:
"""Merge props into an existing node. Returns False if node not found."""
with self._lock:
node = self._nodes.get(node_type, {}).get(node_id)
if node is None:
return False
node.update(props)
node["_updated_at"] = time.time()
logger.debug("[HelixState] update_node(%s, %s)", node_type, node_id)
return True
def get_node(self, node_type: str, node_id: str) -> Optional[Dict[str, Any]]:
"""Return a node's property dict, or None."""
with self._lock:
return self._nodes.get(node_type, {}).get(node_id)
def remove_node(self, node_type: str, node_id: str) -> bool:
"""Remove a node and all its edges."""
with self._lock:
if node_id not in self._nodes.get(node_type, {}):
return False
del self._nodes[node_type][node_id]
# Prune orphaned edges
dead = [k for k in self._edges
if (k[0] == node_type and k[1] == node_id) or
(k[3] == node_type and k[4] == node_id)]
for k in dead:
del self._edges[k]
logger.debug("[HelixState] remove_node(%s, %s) + %d edges", node_type, node_id, len(dead))
return True
def list_nodes(self, node_type: str) -> List[str]:
"""Return all node IDs of a given type."""
with self._lock:
return list(self._nodes.get(node_type, {}).keys())
# ββ Edge Operations βββββββββββββββββββββββββββββββββββββββββββββββββββββββ
def add_edge(
self,
src_type: str, src_id: str,
dst_type: str, dst_id: str,
label: str,
**props,
) -> bool:
"""Add a directed edge (src)-[label]->(dst). Overwrites if exists."""
with self._lock:
key = (src_type, src_id, label, dst_type, dst_id)
self._edges[key] = {**props, "_created_at": time.time()}
logger.debug("[HelixState] add_edge %s:%s -[%s]-> %s:%s", src_type, src_id, label, dst_type, dst_id)
return True
def get_neighbors(
self,
src_type: str,
src_id: str,
label: str,
dst_type: Optional[str] = None,
) -> List[Dict[str, Any]]:
"""
Return list of destination node property dicts reachable from
(src_type, src_id) via edges with the given label.
Optionally filter by dst_type.
"""
with self._lock:
results = []
for key, edge_props in self._edges.items():
s_type, s_id, e_label, d_type, d_id = key
if s_type != src_type or s_id != src_id or e_label != label:
continue
if dst_type and d_type != dst_type:
continue
node = self._nodes.get(d_type, {}).get(d_id)
if node:
results.append({"_type": d_type, "_id": d_id, **node})
return results
def remove_edge(
self,
src_type: str, src_id: str,
dst_type: str, dst_id: str,
label: str,
) -> bool:
"""Remove a specific directed edge."""
with self._lock:
key = (src_type, src_id, label, dst_type, dst_id)
if key in self._edges:
del self._edges[key]
return True
return False
# ββ Query Helpers βββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
def query_path(
self,
start_type: str, start_id: str,
*edge_labels: str,
) -> List[Dict[str, Any]]:
"""
Traverse a chain of edges and return the terminal nodes.
Example: query_path("project", "calc_v1", "HAS_TASK", "USES_FILE")
Returns all File nodes reachable via the two-hop path.
"""
current: List[Dict] = [{"_type": start_type, "_id": start_id}]
for label in edge_labels:
next_level = []
for node in current:
ntype, nid = node["_type"], node["_id"]
neighbors = self.get_neighbors(ntype, nid, label)
next_level.extend(neighbors)
current = next_level
return current
def dump(self) -> Dict[str, Any]:
"""Serialise the full graph to a JSON-compatible dict (for /api/metrics)."""
with self._lock:
return {
"node_counts": {t: len(ids) for t, ids in self._nodes.items()},
"edge_count": len(self._edges),
"nodes": {t: dict(ids) for t, ids in self._nodes.items()},
}
# ββ Project State Helpers (Eternity Loop convenience) ββββββββββββββββββββ
def upsert_project(self, name: str, goal: str, mode: str, priority: str):
"""Convenience: add or update a project node."""
if not self.get_node("project", name):
self.add_node("project", name, goal=goal, mode=mode, priority=priority, cycle=0)
else:
self.update_node("project", name, mode=mode, priority=priority)
def record_cycle(self, project_name: str, summary: str, status: str):
"""Increment cycle counter and store last summary on the project node."""
node = self.get_node("project", project_name)
if node:
cycle = node.get("cycle", 0) + 1
self.update_node("project", project_name,
cycle=cycle,
last_summary=summary,
last_status=status,
last_cycle_at=time.time())
def get_active_project_names(self) -> List[str]:
"""Return IDs of all project nodes where is_active == True."""
with self._lock:
return [
pid for pid, props in self._nodes.get("project", {}).items()
if props.get("is_active", True)
]
def link_task_to_file(self, project_name: str, task_id: str, file_path: str):
"""Record which file a task is working on, for targeted brain loading."""
self.add_node("task", task_id, project=project_name, file=file_path)
self.add_edge("project", project_name, "task", task_id, "HAS_TASK")
if file_path:
self.add_node("file", file_path)
self.add_edge("task", task_id, "file", file_path, "USES_FILE")
def record_bug_fix(self, file_path: str, bug_summary: str, fix_summary: str, brain_path: str):
"""Record that a bug in a file was fixed and persisted to the Second Brain."""
bug_id = f"bug_{int(time.time())}"
self.add_node("bug", bug_id, file=file_path, summary=bug_summary)
self.add_node("fix", bug_id, summary=fix_summary, brain_path=brain_path)
self.add_edge("file", file_path, "bug", bug_id, "HAD_BUG")
self.add_edge("bug", bug_id, "fix", bug_id, "FIXED_BY")
self.add_edge("fix", bug_id, "brain", brain_path, "PERSISTED_TO")
# Singleton β import and use directly
helix_db = HelixStateDB()
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