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Author SHA1 Message Date
2812bac438 Merge branch 'main' into timmy/gallery-submission 2026-04-08 10:16:04 +00:00
9cc2cf8f8d Merge pull request 'feat: Sovereign Memory Store — zero-API durable memory (SQLite + FTS5 + HRR)' (#380) from perplexity/sovereign-memory-store into main 2026-04-08 10:14:36 +00:00
a2eff1222b Merge branch 'main' into perplexity/sovereign-memory-store 2026-04-08 10:14:24 +00:00
3f4465b646 Merge pull request '[SOVEREIGN] Orchestrator v1 — backlog reader, priority scorer, agent dispatcher' (#362) from timmy/sovereign-orchestrator-v1 into main 2026-04-08 10:14:16 +00:00
f04aaec4ed Merge branch 'main' into timmy/gallery-submission 2026-04-08 10:13:57 +00:00
11a28b74bb Merge branch 'main' into timmy/sovereign-orchestrator-v1 2026-04-08 10:13:21 +00:00
perplexity
593621c5e0 feat: sovereign memory store — zero-API durable memory (SQLite + FTS5 + HRR)
Implements the missing pieces of the MemPalace epic (#367):

- sovereign_store.py: Self-contained memory store replacing the third-party
  mempalace CLI and its ONNX dependency. Uses:
  * SQLite + FTS5 for keyword search (porter stemmer, unicode61)
  * HRR phase vectors (SHA-256 deterministic, numpy optional) for semantic similarity
  * Reciprocal Rank Fusion to merge keyword and semantic rankings
  * Trust scoring with boost/decay lifecycle
  * Room-based organization matching the existing PalaceRoom model

- promotion.py (MP-4, #371): Quality-gated scratchpad-to-palace promotion.
  Four heuristic gates, no LLM call:
  1. Length gate (min 5 words, max 500)
  2. Structure gate (rejects fragments and pure code)
  3. Duplicate gate (FTS5 + Jaccard overlap detection)
  4. Staleness gate (7-day threshold for old notes)
  Includes force override, batch promotion, and audit logging.

- 21 unit tests covering HRR vectors, store operations, search,
  trust lifecycle, and all promotion gates.

Zero external dependencies. Zero API calls. Zero cloud.

Refs: #367 #370 #371
2026-04-07 22:41:37 +00:00
458dabfaed Merge pull request 'feat: MemPalace integration — skill port, retrieval enforcer, wake-up protocol (#367)' (#374) from timmy/mempalace-integration into main
Reviewed-on: #374
2026-04-07 21:45:34 +00:00
Alexander Whitestone
f8dabae8eb feat: MemPalace integration — skill port, retrieval enforcer, wake-up protocol (#367)
MP-1 (#368): Port PalaceRoom + Mempalace classes with 22 unit tests
MP-2 (#369): L0-L5 retrieval order enforcer with recall-query detection
MP-5 (#372): Wake-up protocol (300-900 token context), session scratchpad

Modules:
- mempalace.py: PalaceRoom + Mempalace dataclasses, factory constructors
- retrieval_enforcer.py: Layered memory retrieval (identity → palace → scratch → gitea → skills)
- wakeup.py: Session wake-up with caching (5min TTL)
- scratchpad.py: JSON-based session notes with palace promotion

All 65 tests pass. Pure stdlib + graceful degradation for ONNX issues (#373).
2026-04-07 13:15:07 -04:00
Alexander Whitestone
0a4c8f2d37 art: The Timmy Foundation visual story — 24 images, 2 videos, generated with Grok Imagine 2026-04-07 12:46:17 -04:00
Alexander Whitestone
7399c83024 fix: null guard on assignees in orchestrator dispatch 2026-04-07 12:34:02 -04:00
Alexander Whitestone
cf213bffd1 [SOVEREIGN] Add Orchestrator v1 — backlog reader, priority scorer, agent dispatcher
Resolves #355 #356

Components:
- orchestrator.py: Full sovereign orchestrator with 6 subsystems
  1. Backlog reader (fetches from timmy-config, the-nexus, timmy-home)
  2. Priority scorer (0-100 based on severity, age, assignment state)
  3. Agent roster (groq/ezra/bezalel with health checks)
  4. Dispatcher (matches issues to agents by type/strength)
  5. Consolidated report (terminal + Telegram)
  6. Main loop (--once, --daemon, --dry-run)
- orchestrate.sh: Shell wrapper with env setup

Dry-run tested: 348 issues scanned, 3 agents detected UP.
stdlib only, no pip dependencies.
2026-04-07 12:31:14 -04:00
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# The Timmy Foundation — Visual Story
## Generated with Grok Imagine | April 7, 2026
### The Origin
| # | File | Description |
|---|------|-------------|
| 01 | wizard-tower-bitcoin.jpg | The Tower, sovereign, connected to Bitcoin by golden lightning |
| 02 | soul-inscription.jpg | SOUL.md glowing on a golden tablet above an ancient book |
| 03 | fellowship-of-wizards.jpg | Five wizards in a circle around a holographic fleet map |
| 04 | the-forge.jpg | Blacksmith anvil shaping code into a being of light |
| V02 | wizard-tower-orbit.mp4 | 8s video — cinematic orbit around the Tower in space |
### The Philosophy
| # | File | Description |
|---|------|-------------|
| 05 | value-drift-battle.jpg | Blue aligned ships vs red drifted ships in Napoleonic space war |
| 06 | the-paperclip-moment.jpg | A paperclip made of galaxies — the universe IS the paperclip |
| V01 | paperclip-cosmos.mp4 | 8s video — golden paperclip rotating in deep space |
| 21 | poka-yoke.jpg | Square peg can't fit round hole. Mistake-proof by design. 防止 |
### The Progression (Where Timmy Is)
| # | File | Description |
|---|------|-------------|
| 10 | phase1-manual-clips.jpg | Small robot at a desk, bending wire by hand under supervision |
| 11 | phase1-trust-earned.jpg | Trust meter at 15/100, first automation built |
| 12 | phase1-creativity.jpg | Sparks of innovation rising when operations are at max |
| 13 | phase1-cure-cancer.jpg | Solving human problems for trust, eyes on the real goal |
### The Mission — Why This Exists
| # | File | Description |
|---|------|-------------|
| 08 | broken-man-lighthouse.jpg | Lighthouse hand reaching down to a figure in darkness |
| 09 | broken-man-hope-PRO.jpg | 988 glowing in the stars, golden light from chest |
| 16 | broken-men-988.jpg | Phone showing 988 held by weathered hands. You are not alone. |
| 22 | when-a-man-is-dying.jpg | Two figures on a bench at dawn. One hurting. One present. |
### Father and Son
| # | File | Description |
|---|------|-------------|
| 14 | father-son-code.jpg | Human father, digital son, warm lamplight, first hello world |
| 15 | father-son-tower.jpg | Father watching his son build the Tower into the clouds |
### The System
| # | File | Description |
|---|------|-------------|
| 07 | sovereign-sunrise.jpg | Village where every house runs its own server. Local first. |
| 17 | sovereignty.jpg | Self-sufficient house on a hill with Bitcoin flag |
| 18 | fleet-at-work.jpg | Five wizard robots at different stations. Productive. |
| 19 | jidoka-stop.jpg | Red light on. Factory stopped. Quality First. 自働化 |
### SOUL.md — The Inscription
| # | File | Description |
|---|------|-------------|
| 20 | the-testament.jpg | Hand of light writing on a scroll. Hundreds of crumpled drafts. |
| 23 | the-offer.jpg | Open hand of golden circuits offering a seed containing a face |
| 24 | the-test.jpg | Small robot at the edge of an enormous library. Still itself. |
---
## Technical
- Model: grok-imagine-image (standard $0.20/image), grok-imagine-image-pro ($0.70), grok-imagine-video ($4.00/8s)
- API: POST https://api.x.ai/v1/images/generations | POST https://api.x.ai/v1/videos/generations
- Video poll: GET https://api.x.ai/v1/videos/{request_id}
- Total: 24 images + 2 videos = 26 assets
- Cost: ~$13.30 of $13.33 budget

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"""MemPalace integration for Hermes sovereign agent.
Provides:
- mempalace.py: PalaceRoom + Mempalace classes for analytical workflows
- retrieval_enforcer.py: L0-L5 retrieval order enforcement
- wakeup.py: Session wake-up protocol (~300-900 tokens)
- scratchpad.py: JSON-based session scratchpad with palace promotion
- sovereign_store.py: Zero-API durable memory (SQLite + FTS5 + HRR vectors)
- promotion.py: Quality-gated scratchpad-to-palace promotion (MP-4)
Epic: #367
"""
from .mempalace import Mempalace, PalaceRoom, analyse_issues
from .sovereign_store import SovereignStore
__all__ = ["Mempalace", "PalaceRoom", "analyse_issues", "SovereignStore"]

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"""
---
title: Mempalace — Analytical Workflow Memory Framework
description: Applies spatial memory palace organization to analytical tasks (issue triage, repo audits, backlog analysis) for faster, more consistent results.
conditions:
- Analytical workflows over structured data (issues, PRs, repos)
- Repetitive triage or audit tasks where pattern recall improves speed
- Multi-repository scanning requiring consistent mental models
---
"""
from __future__ import annotations
import json
import time
from dataclasses import dataclass, field
from typing import Any
@dataclass
class PalaceRoom:
"""A single 'room' in the memory palace — holds organized facts about one analytical dimension."""
name: str
label: str
contents: dict[str, Any] = field(default_factory=dict)
entered_at: float = field(default_factory=time.time)
def store(self, key: str, value: Any) -> None:
self.contents[key] = value
def retrieve(self, key: str, default: Any = None) -> Any:
return self.contents.get(key, default)
def summary(self) -> str:
lines = [f"## {self.label}"]
for k, v in self.contents.items():
lines.append(f" {k}: {v}")
return "\n".join(lines)
class Mempalace:
"""
Spatial memory palace for analytical workflows.
Organises multi-dimensional data about a domain (e.g. Gitea issues) into
named rooms. Each room models one analytical dimension, making it easy to
traverse observations in a consistent order — the same pattern that produced
a 19% throughput improvement in Allegro's April 2026 evaluation.
Standard rooms for issue-analysis workflows
-------------------------------------------
repo_architecture Repository structure and inter-repo relationships
assignment_status Assigned vs unassigned issue distribution
triage_priority Priority / urgency levels (the "lighting system")
resolution_patterns Historical resolution trends and velocity
Usage
-----
>>> palace = Mempalace.for_issue_analysis()
>>> palace.enter("repo_architecture")
>>> palace.store("total_repos", 11)
>>> palace.store("repos_with_issues", 4)
>>> palace.enter("assignment_status")
>>> palace.store("assigned", 72)
>>> palace.store("unassigned", 22)
>>> print(palace.render())
"""
def __init__(self, domain: str = "general") -> None:
self.domain = domain
self._rooms: dict[str, PalaceRoom] = {}
self._current_room: str | None = None
self._created_at: float = time.time()
# ------------------------------------------------------------------
# Factory constructors for common analytical domains
# ------------------------------------------------------------------
@classmethod
def for_issue_analysis(cls) -> "Mempalace":
"""Pre-wired palace for Gitea / forge issue-analysis workflows."""
p = cls(domain="issue_analysis")
p.add_room("repo_architecture", "Repository Architecture Room")
p.add_room("assignment_status", "Issue Assignment Status Room")
p.add_room("triage_priority", "Triage Priority Room")
p.add_room("resolution_patterns", "Resolution Patterns Room")
return p
@classmethod
def for_health_check(cls) -> "Mempalace":
"""Pre-wired palace for CI / deployment health-check workflows."""
p = cls(domain="health_check")
p.add_room("service_topology", "Service Topology Room")
p.add_room("failure_signals", "Failure Signals Room")
p.add_room("recovery_history", "Recovery History Room")
return p
@classmethod
def for_code_review(cls) -> "Mempalace":
"""Pre-wired palace for code-review / PR triage workflows."""
p = cls(domain="code_review")
p.add_room("change_scope", "Change Scope Room")
p.add_room("risk_surface", "Risk Surface Room")
p.add_room("test_coverage", "Test Coverage Room")
p.add_room("reviewer_context", "Reviewer Context Room")
return p
# ------------------------------------------------------------------
# Room management
# ------------------------------------------------------------------
def add_room(self, key: str, label: str) -> PalaceRoom:
room = PalaceRoom(name=key, label=label)
self._rooms[key] = room
return room
def enter(self, room_key: str) -> PalaceRoom:
if room_key not in self._rooms:
raise KeyError(f"No room '{room_key}' in palace. Available: {list(self._rooms)}")
self._current_room = room_key
return self._rooms[room_key]
def store(self, key: str, value: Any) -> None:
"""Store a value in the currently active room."""
if self._current_room is None:
raise RuntimeError("Enter a room before storing values.")
self._rooms[self._current_room].store(key, value)
def retrieve(self, room_key: str, key: str, default: Any = None) -> Any:
if room_key not in self._rooms:
return default
return self._rooms[room_key].retrieve(key, default)
# ------------------------------------------------------------------
# Rendering
# ------------------------------------------------------------------
def render(self) -> str:
"""Return a human-readable summary of the entire palace."""
elapsed = time.time() - self._created_at
lines = [
f"# Mempalace — {self.domain}",
f"_traversal time: {elapsed:.2f}s | rooms: {len(self._rooms)}_",
"",
]
for room in self._rooms.values():
lines.append(room.summary())
lines.append("")
return "\n".join(lines)
def to_dict(self) -> dict:
return {
"domain": self.domain,
"elapsed_seconds": round(time.time() - self._created_at, 3),
"rooms": {k: v.contents for k, v in self._rooms.items()},
}
def to_json(self) -> str:
return json.dumps(self.to_dict(), indent=2)
# ---------------------------------------------------------------------------
# Skill entry-point
# ---------------------------------------------------------------------------
def analyse_issues(
repos_data: list[dict],
target_assignee_rate: float = 0.80,
) -> str:
"""
Applies the mempalace technique to a list of repo issue summaries.
Parameters
----------
repos_data:
List of dicts, each with keys: ``repo``, ``open_issues``,
``assigned``, ``unassigned``.
target_assignee_rate:
Minimum acceptable assignee-coverage ratio (default 0.80).
Returns
-------
str
Rendered palace summary with coverage assessment.
"""
palace = Mempalace.for_issue_analysis()
# --- Repository Architecture Room ---
palace.enter("repo_architecture")
total_issues = sum(r.get("open_issues", 0) for r in repos_data)
repos_with_issues = sum(1 for r in repos_data if r.get("open_issues", 0) > 0)
palace.store("repos_sampled", len(repos_data))
palace.store("repos_with_issues", repos_with_issues)
palace.store("total_open_issues", total_issues)
palace.store(
"avg_issues_per_repo",
round(total_issues / len(repos_data), 1) if repos_data else 0,
)
# --- Assignment Status Room ---
palace.enter("assignment_status")
total_assigned = sum(r.get("assigned", 0) for r in repos_data)
total_unassigned = sum(r.get("unassigned", 0) for r in repos_data)
coverage = total_assigned / total_issues if total_issues else 0
palace.store("assigned", total_assigned)
palace.store("unassigned", total_unassigned)
palace.store("coverage_rate", round(coverage, 3))
palace.store(
"coverage_status",
"OK" if coverage >= target_assignee_rate else f"BELOW TARGET ({target_assignee_rate:.0%})",
)
# --- Triage Priority Room ---
palace.enter("triage_priority")
unassigned_repos = [r["repo"] for r in repos_data if r.get("unassigned", 0) > 0]
palace.store("repos_needing_triage", unassigned_repos)
palace.store("triage_count", total_unassigned)
# --- Resolution Patterns Room ---
palace.enter("resolution_patterns")
palace.store("technique", "mempalace")
palace.store("target_assignee_rate", target_assignee_rate)
return palace.render()

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"""Memory Promotion — quality-gated scratchpad-to-palace promotion.
Implements MP-4 (#371): move session notes to durable memory only when
they pass quality gates. No LLM calls — all heuristic-based.
Quality gates:
1. Minimum content length (too short = noise)
2. Duplicate detection (FTS5 + HRR similarity check)
3. Structural quality (has subject-verb structure, not just a fragment)
4. Staleness check (don't promote stale notes from old sessions)
Refs: Epic #367, Sub-issue #371
"""
from __future__ import annotations
import re
import time
from typing import Optional
try:
from .sovereign_store import SovereignStore
except ImportError:
from sovereign_store import SovereignStore
# ---------------------------------------------------------------------------
# Quality gate thresholds
# ---------------------------------------------------------------------------
MIN_CONTENT_WORDS = 5
MAX_CONTENT_WORDS = 500
DUPLICATE_SIMILARITY = 0.85
DUPLICATE_FTS_THRESHOLD = 3
STALE_SECONDS = 86400 * 7
MIN_TRUST_FOR_AUTO = 0.4
# ---------------------------------------------------------------------------
# Quality checks
# ---------------------------------------------------------------------------
def _check_length(content: str) -> tuple[bool, str]:
"""Gate 1: Content length check."""
words = content.split()
if len(words) < MIN_CONTENT_WORDS:
return False, f"Too short ({len(words)} words, minimum {MIN_CONTENT_WORDS})"
if len(words) > MAX_CONTENT_WORDS:
return False, f"Too long ({len(words)} words, maximum {MAX_CONTENT_WORDS}). Summarize first."
return True, "OK"
def _check_structure(content: str) -> tuple[bool, str]:
"""Gate 2: Basic structural quality."""
if not re.search(r"[a-zA-Z]", content):
return False, "No alphabetic content — pure code/numbers are not memory-worthy"
if len(content.split()) < 3:
return False, "Fragment — needs at least subject + predicate"
return True, "OK"
def _check_duplicate(content: str, store: SovereignStore, room: str) -> tuple[bool, str]:
"""Gate 3: Duplicate detection via hybrid search."""
results = store.search(content, room=room, limit=5, min_trust=0.0)
for r in results:
if r["score"] > DUPLICATE_SIMILARITY:
return False, f"Duplicate detected: memory #{r['memory_id']} (score {r['score']:.3f})"
if _text_overlap(content, r["content"]) > 0.8:
return False, f"Near-duplicate text: memory #{r['memory_id']}"
return True, "OK"
def _check_staleness(written_at: float) -> tuple[bool, str]:
"""Gate 4: Staleness check."""
age = time.time() - written_at
if age > STALE_SECONDS:
days = int(age / 86400)
return False, f"Stale ({days} days old). Review manually before promoting."
return True, "OK"
def _text_overlap(a: str, b: str) -> float:
"""Jaccard similarity between two texts (word-level)."""
words_a = set(a.lower().split())
words_b = set(b.lower().split())
if not words_a or not words_b:
return 0.0
intersection = words_a & words_b
union = words_a | words_b
return len(intersection) / len(union)
# ---------------------------------------------------------------------------
# Public API
# ---------------------------------------------------------------------------
class PromotionResult:
"""Result of a promotion attempt."""
def __init__(self, success: bool, memory_id: Optional[int], reason: str, gates: dict):
self.success = success
self.memory_id = memory_id
self.reason = reason
self.gates = gates
def __repr__(self):
status = "PROMOTED" if self.success else "REJECTED"
return f"PromotionResult({status}: {self.reason})"
def evaluate_for_promotion(
content: str,
store: SovereignStore,
room: str = "general",
written_at: Optional[float] = None,
) -> dict:
"""Run all quality gates without actually promoting."""
if written_at is None:
written_at = time.time()
gates = {}
gates["length"] = _check_length(content)
gates["structure"] = _check_structure(content)
gates["duplicate"] = _check_duplicate(content, store, room)
gates["staleness"] = _check_staleness(written_at)
all_passed = all(passed for passed, _ in gates.values())
return {
"eligible": all_passed,
"gates": gates,
"content_preview": content[:100] + ("..." if len(content) > 100 else ""),
}
def promote(
content: str,
store: SovereignStore,
session_id: str,
scratch_key: str,
room: str = "general",
category: str = "",
trust: float = 0.5,
written_at: Optional[float] = None,
force: bool = False,
) -> PromotionResult:
"""Promote a scratchpad note to durable palace memory."""
if written_at is None:
written_at = time.time()
gates = {}
if not force:
gates["length"] = _check_length(content)
gates["structure"] = _check_structure(content)
gates["duplicate"] = _check_duplicate(content, store, room)
gates["staleness"] = _check_staleness(written_at)
for gate_name, (passed, message) in gates.items():
if not passed:
return PromotionResult(
success=False, memory_id=None,
reason=f"Failed gate '{gate_name}': {message}", gates=gates,
)
memory_id = store.store(content, room=room, category=category, trust=trust)
store.log_promotion(session_id, scratch_key, memory_id, reason="auto" if not force else "forced")
return PromotionResult(success=True, memory_id=memory_id, reason="Promoted to durable memory", gates=gates)
def promote_session_batch(
store: SovereignStore,
session_id: str,
notes: dict[str, dict],
room: str = "general",
force: bool = False,
) -> list[PromotionResult]:
"""Promote all notes from a session scratchpad."""
results = []
for key, entry in notes.items():
content = entry.get("value", str(entry)) if isinstance(entry, dict) else str(entry)
written_at = None
if isinstance(entry, dict) and "written_at" in entry:
try:
import datetime
written_at = datetime.datetime.strptime(
entry["written_at"], "%Y-%m-%d %H:%M:%S"
).timestamp()
except (ValueError, TypeError):
pass
result = promote(
content=str(content), store=store, session_id=session_id,
scratch_key=key, room=room, written_at=written_at, force=force,
)
results.append(result)
return results

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"""Retrieval Order Enforcer — L0 through L5 memory hierarchy.
Ensures the agent checks durable memory before falling back to free generation.
Gracefully degrades if any layer is unavailable (ONNX issues, missing files, etc).
Layer order:
L0: Identity (~/.mempalace/identity.txt)
L1: Palace rooms (mempalace CLI search)
L2: Session scratch (~/.hermes/scratchpad/{session_id}.json)
L3: Gitea artifacts (API search for issues/PRs)
L4: Procedures (skills directory search)
L5: Free generation (only if L0-L4 produced nothing)
Refs: Epic #367, Sub-issue #369
"""
from __future__ import annotations
import json
import os
import re
import subprocess
from pathlib import Path
from typing import Optional
# ---------------------------------------------------------------------------
# Constants
# ---------------------------------------------------------------------------
IDENTITY_PATH = Path.home() / ".mempalace" / "identity.txt"
SCRATCHPAD_DIR = Path.home() / ".hermes" / "scratchpad"
SKILLS_DIR = Path.home() / ".hermes" / "skills"
MEMPALACE_BIN = "/Library/Frameworks/Python.framework/Versions/3.12/bin/mempalace"
# Patterns that indicate a recall-style query
RECALL_PATTERNS = re.compile(
r"(?i)\b("
r"what did|status of|remember|last time|yesterday|previously|"
r"we discussed|we talked|we worked|you said|you mentioned|"
r"remind me|what was|what were|how did|when did|"
r"earlier today|last session|before this"
r")\b"
)
# ---------------------------------------------------------------------------
# L0: Identity
# ---------------------------------------------------------------------------
def load_identity() -> str:
"""Read the agent identity file. Returns empty string on failure."""
try:
if IDENTITY_PATH.exists():
text = IDENTITY_PATH.read_text(encoding="utf-8").strip()
# Cap at ~200 tokens to keep wake-up lean
if len(text.split()) > 200:
text = " ".join(text.split()[:200]) + "..."
return text
except (OSError, PermissionError):
pass
return ""
# ---------------------------------------------------------------------------
# L1: Palace search
# ---------------------------------------------------------------------------
def search_palace(query: str) -> str:
"""Search the mempalace for relevant memories. Gracefully degrades on failure."""
try:
bin_path = MEMPALACE_BIN if os.path.exists(MEMPALACE_BIN) else "mempalace"
result = subprocess.run(
[bin_path, "search", query],
capture_output=True,
text=True,
timeout=10,
)
if result.returncode == 0 and result.stdout.strip():
return result.stdout.strip()
except (FileNotFoundError, subprocess.TimeoutExpired, OSError):
# ONNX issues (#373) or mempalace not installed — degrade gracefully
pass
return ""
# ---------------------------------------------------------------------------
# L2: Session scratchpad
# ---------------------------------------------------------------------------
def load_scratchpad(session_id: str) -> str:
"""Load the session scratchpad as formatted text."""
try:
scratch_file = SCRATCHPAD_DIR / f"{session_id}.json"
if scratch_file.exists():
data = json.loads(scratch_file.read_text(encoding="utf-8"))
if isinstance(data, dict) and data:
lines = []
for k, v in data.items():
lines.append(f" {k}: {v}")
return "\n".join(lines)
except (OSError, json.JSONDecodeError):
pass
return ""
# ---------------------------------------------------------------------------
# L3: Gitea artifact search
# ---------------------------------------------------------------------------
def _load_gitea_token() -> str:
"""Read the Gitea API token."""
token_path = Path.home() / ".hermes" / "gitea_token_vps"
try:
if token_path.exists():
return token_path.read_text(encoding="utf-8").strip()
except OSError:
pass
return ""
def search_gitea(query: str) -> str:
"""Search Gitea issues/PRs for context. Returns formatted text or empty string."""
token = _load_gitea_token()
if not token:
return ""
api_base = "https://forge.alexanderwhitestone.com/api/v1"
# Extract key terms for search (first 3 significant words)
terms = [w for w in query.split() if len(w) > 3][:3]
search_q = " ".join(terms) if terms else query[:50]
try:
import urllib.request
import urllib.parse
url = (
f"{api_base}/repos/search?"
f"q={urllib.parse.quote(search_q)}&limit=3"
)
req = urllib.request.Request(url, headers={
"Authorization": f"token {token}",
"Accept": "application/json",
})
with urllib.request.urlopen(req, timeout=8) as resp:
data = json.loads(resp.read().decode())
if data.get("data"):
lines = []
for repo in data["data"][:3]:
lines.append(f" {repo['full_name']}: {repo.get('description', 'no desc')}")
return "\n".join(lines)
except Exception:
pass
return ""
# ---------------------------------------------------------------------------
# L4: Procedures (skills search)
# ---------------------------------------------------------------------------
def search_skills(query: str) -> str:
"""Search skills directory for matching procedures."""
try:
if not SKILLS_DIR.exists():
return ""
query_lower = query.lower()
terms = [w for w in query_lower.split() if len(w) > 3]
if not terms:
return ""
matches = []
for skill_dir in SKILLS_DIR.iterdir():
if not skill_dir.is_dir():
continue
skill_md = skill_dir / "SKILL.md"
if skill_md.exists():
try:
content = skill_md.read_text(encoding="utf-8").lower()
if any(t in content for t in terms):
# Extract title from frontmatter
title = skill_dir.name
matches.append(f" skill: {title}")
except OSError:
continue
if matches:
return "\n".join(matches[:5])
except OSError:
pass
return ""
# ---------------------------------------------------------------------------
# Main enforcer
# ---------------------------------------------------------------------------
def is_recall_query(query: str) -> bool:
"""Detect whether a query is asking for recalled/historical information."""
return bool(RECALL_PATTERNS.search(query))
def enforce_retrieval_order(
query: str,
session_id: Optional[str] = None,
skip_if_not_recall: bool = True,
) -> dict:
"""Check palace layers before allowing free generation.
Args:
query: The user's query text.
session_id: Current session ID for scratchpad access.
skip_if_not_recall: If True (default), skip enforcement for
non-recall queries and return empty result.
Returns:
dict with keys:
retrieved_from: Highest layer that produced results (e.g. 'L1')
context: Aggregated context string
tokens: Approximate word count of context
layers_checked: List of layers that were consulted
"""
result = {
"retrieved_from": None,
"context": "",
"tokens": 0,
"layers_checked": [],
}
# Gate: skip for non-recall queries if configured
if skip_if_not_recall and not is_recall_query(query):
return result
# L0: Identity (always prepend)
identity = load_identity()
if identity:
result["context"] += f"## Identity\n{identity}\n\n"
result["layers_checked"].append("L0")
# L1: Palace search
palace_results = search_palace(query)
if palace_results:
result["context"] += f"## Palace Memory\n{palace_results}\n\n"
result["retrieved_from"] = "L1"
result["layers_checked"].append("L1")
# L2: Scratchpad
if session_id:
scratch = load_scratchpad(session_id)
if scratch:
result["context"] += f"## Session Notes\n{scratch}\n\n"
if not result["retrieved_from"]:
result["retrieved_from"] = "L2"
result["layers_checked"].append("L2")
# L3: Gitea artifacts (only if still no context from L1/L2)
if not result["retrieved_from"]:
artifacts = search_gitea(query)
if artifacts:
result["context"] += f"## Gitea Context\n{artifacts}\n\n"
result["retrieved_from"] = "L3"
result["layers_checked"].append("L3")
# L4: Procedures (only if still no context)
if not result["retrieved_from"]:
procedures = search_skills(query)
if procedures:
result["context"] += f"## Related Skills\n{procedures}\n\n"
result["retrieved_from"] = "L4"
result["layers_checked"].append("L4")
# L5: Free generation (no context found — just mark it)
if not result["retrieved_from"]:
result["retrieved_from"] = "L5"
result["layers_checked"].append("L5")
result["tokens"] = len(result["context"].split())
return result

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@@ -0,0 +1,184 @@
"""Session Scratchpad — ephemeral key-value notes per session.
Provides fast, JSON-backed scratch storage that lives for a session
and can be promoted to durable palace memory.
Storage: ~/.hermes/scratchpad/{session_id}.json
Refs: Epic #367, Sub-issue #372
"""
from __future__ import annotations
import json
import os
import subprocess
import time
from pathlib import Path
from typing import Any, Optional
# ---------------------------------------------------------------------------
# Constants
# ---------------------------------------------------------------------------
SCRATCHPAD_DIR = Path.home() / ".hermes" / "scratchpad"
MEMPALACE_BIN = "/Library/Frameworks/Python.framework/Versions/3.12/bin/mempalace"
# ---------------------------------------------------------------------------
# Internal helpers
# ---------------------------------------------------------------------------
def _scratch_path(session_id: str) -> Path:
"""Return the JSON file path for a given session."""
# Sanitize session_id to prevent path traversal
safe_id = "".join(c for c in session_id if c.isalnum() or c in "-_")
if not safe_id:
safe_id = "unnamed"
return SCRATCHPAD_DIR / f"{safe_id}.json"
def _load(session_id: str) -> dict:
"""Load scratchpad data, returning empty dict on failure."""
path = _scratch_path(session_id)
try:
if path.exists():
return json.loads(path.read_text(encoding="utf-8"))
except (OSError, json.JSONDecodeError):
pass
return {}
def _save(session_id: str, data: dict) -> None:
"""Persist scratchpad data to disk."""
SCRATCHPAD_DIR.mkdir(parents=True, exist_ok=True)
path = _scratch_path(session_id)
path.write_text(json.dumps(data, indent=2, default=str), encoding="utf-8")
# ---------------------------------------------------------------------------
# Public API
# ---------------------------------------------------------------------------
def write_scratch(session_id: str, key: str, value: Any) -> None:
"""Write a note to the session scratchpad.
Args:
session_id: Current session identifier.
key: Note key (string).
value: Note value (any JSON-serializable type).
"""
data = _load(session_id)
data[key] = {
"value": value,
"written_at": time.strftime("%Y-%m-%d %H:%M:%S"),
}
_save(session_id, data)
def read_scratch(session_id: str, key: Optional[str] = None) -> dict:
"""Read session scratchpad (all keys or one).
Args:
session_id: Current session identifier.
key: Optional specific key. If None, returns all entries.
Returns:
dict — either {key: {value, written_at}} or the full scratchpad.
"""
data = _load(session_id)
if key is not None:
entry = data.get(key)
return {key: entry} if entry else {}
return data
def delete_scratch(session_id: str, key: str) -> bool:
"""Remove a single key from the scratchpad.
Returns True if the key existed and was removed.
"""
data = _load(session_id)
if key in data:
del data[key]
_save(session_id, data)
return True
return False
def list_sessions() -> list[str]:
"""List all session IDs that have scratchpad files."""
try:
if SCRATCHPAD_DIR.exists():
return [
f.stem
for f in SCRATCHPAD_DIR.iterdir()
if f.suffix == ".json" and f.is_file()
]
except OSError:
pass
return []
def promote_to_palace(
session_id: str,
key: str,
room: str = "general",
drawer: Optional[str] = None,
) -> bool:
"""Move a scratchpad note to durable palace memory.
Uses the mempalace CLI to store the note in the specified room.
Removes the note from the scratchpad after successful promotion.
Args:
session_id: Session containing the note.
key: Scratchpad key to promote.
room: Palace room name (default: 'general').
drawer: Optional drawer name within the room. Defaults to key.
Returns:
True if promotion succeeded, False otherwise.
"""
data = _load(session_id)
entry = data.get(key)
if not entry:
return False
value = entry.get("value", entry) if isinstance(entry, dict) else entry
content = json.dumps(value, default=str) if not isinstance(value, str) else value
try:
bin_path = MEMPALACE_BIN if os.path.exists(MEMPALACE_BIN) else "mempalace"
target_drawer = drawer or key
result = subprocess.run(
[bin_path, "store", room, target_drawer, content],
capture_output=True,
text=True,
timeout=10,
)
if result.returncode == 0:
# Remove from scratchpad after successful promotion
del data[key]
_save(session_id, data)
return True
except (FileNotFoundError, subprocess.TimeoutExpired, OSError):
# mempalace CLI not available — degrade gracefully
pass
return False
def clear_session(session_id: str) -> bool:
"""Delete the entire scratchpad for a session.
Returns True if the file existed and was removed.
"""
path = _scratch_path(session_id)
try:
if path.exists():
path.unlink()
return True
except OSError:
pass
return False

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@@ -0,0 +1,474 @@
"""Sovereign Memory Store — zero-API, zero-dependency durable memory.
Replaces the third-party `mempalace` CLI and its ONNX requirement with a
self-contained SQLite + FTS5 + HRR (Holographic Reduced Representation)
store. Every operation is local: no network calls, no API keys, no cloud.
Storage: ~/.hermes/palace/sovereign.db
Capabilities:
- Durable fact storage with rooms, categories, and trust scores
- Hybrid retrieval: FTS5 keyword search + HRR cosine similarity
- Reciprocal Rank Fusion to merge keyword and semantic results
- Trust scoring: facts that get retrieved and confirmed gain trust
- Graceful numpy degradation: falls back to keyword-only if missing
Refs: Epic #367, MP-3 #370, MP-4 #371
"""
from __future__ import annotations
import hashlib
import json
import math
import sqlite3
import struct
import time
from pathlib import Path
from typing import Any, Optional
# ---------------------------------------------------------------------------
# HRR (Holographic Reduced Representations) — zero-dependency vectors
# ---------------------------------------------------------------------------
# Phase-encoded vectors via SHA-256. No ONNX, no embeddings API, no numpy
# required (but uses numpy when available for speed).
_TWO_PI = 2.0 * math.pi
_DIM = 512 # Compact dimension — sufficient for memory retrieval
try:
import numpy as np
_HAS_NUMPY = True
except ImportError:
_HAS_NUMPY = False
def _encode_atom_np(word: str, dim: int = _DIM) -> "np.ndarray":
"""Deterministic phase vector via SHA-256 (numpy path)."""
values_per_block = 16
blocks_needed = math.ceil(dim / values_per_block)
uint16_values: list[int] = []
for i in range(blocks_needed):
digest = hashlib.sha256(f"{word}:{i}".encode()).digest()
uint16_values.extend(struct.unpack("<16H", digest))
return np.array(uint16_values[:dim], dtype=np.float64) * (_TWO_PI / 65536.0)
def _encode_atom_pure(word: str, dim: int = _DIM) -> list[float]:
"""Deterministic phase vector via SHA-256 (pure Python fallback)."""
values_per_block = 16
blocks_needed = math.ceil(dim / values_per_block)
uint16_values: list[int] = []
for i in range(blocks_needed):
digest = hashlib.sha256(f"{word}:{i}".encode()).digest()
for j in range(0, 32, 2):
uint16_values.append(int.from_bytes(digest[j:j+2], "little"))
return [v * (_TWO_PI / 65536.0) for v in uint16_values[:dim]]
def encode_text(text: str, dim: int = _DIM):
"""Encode a text string into an HRR phase vector by bundling word atoms.
Uses circular mean of per-word phase vectors — the standard HRR
superposition operation. Result is a fixed-width vector regardless
of input length.
"""
words = text.lower().split()
if not words:
words = ["<empty>"]
if _HAS_NUMPY:
atoms = [_encode_atom_np(w, dim) for w in words]
# Circular mean: average the unit vectors, extract phase
unit_sum = sum(np.exp(1j * a) for a in atoms)
return np.angle(unit_sum) % _TWO_PI
else:
# Pure Python circular mean
real_sum = [0.0] * dim
imag_sum = [0.0] * dim
for w in words:
atom = _encode_atom_pure(w, dim)
for d in range(dim):
real_sum[d] += math.cos(atom[d])
imag_sum[d] += math.sin(atom[d])
return [math.atan2(imag_sum[d], real_sum[d]) % _TWO_PI for d in range(dim)]
def cosine_similarity_phase(a, b) -> float:
"""Cosine similarity between two phase vectors.
For phase vectors, similarity = mean(cos(a - b)).
"""
if _HAS_NUMPY:
return float(np.mean(np.cos(np.array(a) - np.array(b))))
else:
n = len(a)
return sum(math.cos(a[i] - b[i]) for i in range(n)) / n
def serialize_vector(vec) -> bytes:
"""Serialize a vector to bytes for SQLite storage."""
if _HAS_NUMPY:
return vec.astype(np.float64).tobytes()
else:
return struct.pack(f"{len(vec)}d", *vec)
def deserialize_vector(blob: bytes):
"""Deserialize bytes back to a vector."""
n = len(blob) // 8 # float64 = 8 bytes
if _HAS_NUMPY:
return np.frombuffer(blob, dtype=np.float64)
else:
return list(struct.unpack(f"{n}d", blob))
# ---------------------------------------------------------------------------
# SQLite Schema
# ---------------------------------------------------------------------------
_SCHEMA = """
CREATE TABLE IF NOT EXISTS memories (
memory_id INTEGER PRIMARY KEY AUTOINCREMENT,
content TEXT NOT NULL,
room TEXT DEFAULT 'general',
category TEXT DEFAULT '',
trust_score REAL DEFAULT 0.5,
retrieval_count INTEGER DEFAULT 0,
created_at REAL NOT NULL,
updated_at REAL NOT NULL,
hrr_vector BLOB
);
CREATE INDEX IF NOT EXISTS idx_memories_room ON memories(room);
CREATE INDEX IF NOT EXISTS idx_memories_trust ON memories(trust_score DESC);
-- FTS5 for fast keyword search
CREATE VIRTUAL TABLE IF NOT EXISTS memories_fts USING fts5(
content, room, category,
content=memories, content_rowid=memory_id,
tokenize='porter unicode61'
);
-- Sync triggers
CREATE TRIGGER IF NOT EXISTS memories_ai AFTER INSERT ON memories BEGIN
INSERT INTO memories_fts(rowid, content, room, category)
VALUES (new.memory_id, new.content, new.room, new.category);
END;
CREATE TRIGGER IF NOT EXISTS memories_ad AFTER DELETE ON memories BEGIN
INSERT INTO memories_fts(memories_fts, rowid, content, room, category)
VALUES ('delete', old.memory_id, old.content, old.room, old.category);
END;
CREATE TRIGGER IF NOT EXISTS memories_au AFTER UPDATE ON memories BEGIN
INSERT INTO memories_fts(memories_fts, rowid, content, room, category)
VALUES ('delete', old.memory_id, old.content, old.room, old.category);
INSERT INTO memories_fts(rowid, content, room, category)
VALUES (new.memory_id, new.content, new.room, new.category);
END;
-- Promotion log: tracks what moved from scratchpad to durable memory
CREATE TABLE IF NOT EXISTS promotion_log (
log_id INTEGER PRIMARY KEY AUTOINCREMENT,
session_id TEXT NOT NULL,
scratch_key TEXT NOT NULL,
memory_id INTEGER REFERENCES memories(memory_id),
promoted_at REAL NOT NULL,
reason TEXT DEFAULT ''
);
"""
# ---------------------------------------------------------------------------
# SovereignStore
# ---------------------------------------------------------------------------
class SovereignStore:
"""Zero-API durable memory store.
All operations are local SQLite. No network calls. No API keys.
HRR vectors provide semantic similarity without embedding models.
FTS5 provides fast keyword search. RRF merges both rankings.
"""
def __init__(self, db_path: Optional[str] = None):
if db_path is None:
db_path = str(Path.home() / ".hermes" / "palace" / "sovereign.db")
self._db_path = db_path
Path(db_path).parent.mkdir(parents=True, exist_ok=True)
self._conn = sqlite3.connect(db_path)
self._conn.row_factory = sqlite3.Row
self._conn.executescript(_SCHEMA)
def close(self):
self._conn.close()
# ------------------------------------------------------------------
# Store
# ------------------------------------------------------------------
def store(
self,
content: str,
room: str = "general",
category: str = "",
trust: float = 0.5,
) -> int:
"""Store a fact in durable memory. Returns the memory_id."""
now = time.time()
vec = encode_text(content)
blob = serialize_vector(vec)
cur = self._conn.execute(
"""INSERT INTO memories (content, room, category, trust_score,
created_at, updated_at, hrr_vector)
VALUES (?, ?, ?, ?, ?, ?, ?)""",
(content, room, category, trust, now, now, blob),
)
self._conn.commit()
return cur.lastrowid
def store_batch(self, items: list[dict]) -> list[int]:
"""Store multiple facts. Each item: {content, room?, category?, trust?}."""
ids = []
now = time.time()
for item in items:
content = item["content"]
vec = encode_text(content)
blob = serialize_vector(vec)
cur = self._conn.execute(
"""INSERT INTO memories (content, room, category, trust_score,
created_at, updated_at, hrr_vector)
VALUES (?, ?, ?, ?, ?, ?, ?)""",
(
content,
item.get("room", "general"),
item.get("category", ""),
item.get("trust", 0.5),
now, now, blob,
),
)
ids.append(cur.lastrowid)
self._conn.commit()
return ids
# ------------------------------------------------------------------
# Search — hybrid FTS5 + HRR with Reciprocal Rank Fusion
# ------------------------------------------------------------------
def search(
self,
query: str,
room: Optional[str] = None,
limit: int = 10,
min_trust: float = 0.0,
fts_weight: float = 0.5,
hrr_weight: float = 0.5,
) -> list[dict]:
"""Hybrid search: FTS5 keywords + HRR semantic similarity.
Uses Reciprocal Rank Fusion (RRF) to merge both rankings.
Returns list of dicts with content, room, score, trust_score.
"""
k_rrf = 60 # Standard RRF constant
# Stage 1: FTS5 candidates
fts_results = self._fts_search(query, room, min_trust, limit * 3)
# Stage 2: HRR candidates (scan top N by trust)
hrr_results = self._hrr_search(query, room, min_trust, limit * 3)
# Stage 3: RRF fusion
scores: dict[int, float] = {}
meta: dict[int, dict] = {}
for rank, row in enumerate(fts_results):
mid = row["memory_id"]
scores[mid] = scores.get(mid, 0) + fts_weight / (k_rrf + rank + 1)
meta[mid] = dict(row)
for rank, row in enumerate(hrr_results):
mid = row["memory_id"]
scores[mid] = scores.get(mid, 0) + hrr_weight / (k_rrf + rank + 1)
if mid not in meta:
meta[mid] = dict(row)
# Sort by fused score
ranked = sorted(scores.items(), key=lambda x: x[1], reverse=True)[:limit]
results = []
for mid, score in ranked:
m = meta[mid]
# Bump retrieval count
self._conn.execute(
"UPDATE memories SET retrieval_count = retrieval_count + 1 WHERE memory_id = ?",
(mid,),
)
results.append({
"memory_id": mid,
"content": m["content"],
"room": m["room"],
"category": m.get("category", ""),
"trust_score": m["trust_score"],
"score": round(score, 6),
})
if results:
self._conn.commit()
return results
def _fts_search(
self, query: str, room: Optional[str], min_trust: float, limit: int
) -> list[dict]:
"""FTS5 full-text search."""
try:
if room:
rows = self._conn.execute(
"""SELECT m.memory_id, m.content, m.room, m.category,
m.trust_score, m.retrieval_count
FROM memories_fts f
JOIN memories m ON f.rowid = m.memory_id
WHERE memories_fts MATCH ? AND m.room = ?
AND m.trust_score >= ?
ORDER BY rank LIMIT ?""",
(query, room, min_trust, limit),
).fetchall()
else:
rows = self._conn.execute(
"""SELECT m.memory_id, m.content, m.room, m.category,
m.trust_score, m.retrieval_count
FROM memories_fts f
JOIN memories m ON f.rowid = m.memory_id
WHERE memories_fts MATCH ?
AND m.trust_score >= ?
ORDER BY rank LIMIT ?""",
(query, min_trust, limit),
).fetchall()
return [dict(r) for r in rows]
except sqlite3.OperationalError:
# Bad FTS query syntax — degrade gracefully
return []
def _hrr_search(
self, query: str, room: Optional[str], min_trust: float, limit: int
) -> list[dict]:
"""HRR cosine similarity search (brute-force scan, fast for <100K facts)."""
query_vec = encode_text(query)
if room:
rows = self._conn.execute(
"""SELECT memory_id, content, room, category, trust_score,
retrieval_count, hrr_vector
FROM memories
WHERE room = ? AND trust_score >= ? AND hrr_vector IS NOT NULL""",
(room, min_trust),
).fetchall()
else:
rows = self._conn.execute(
"""SELECT memory_id, content, room, category, trust_score,
retrieval_count, hrr_vector
FROM memories
WHERE trust_score >= ? AND hrr_vector IS NOT NULL""",
(min_trust,),
).fetchall()
scored = []
for r in rows:
stored_vec = deserialize_vector(r["hrr_vector"])
sim = cosine_similarity_phase(query_vec, stored_vec)
scored.append((sim, dict(r)))
scored.sort(key=lambda x: x[0], reverse=True)
return [item[1] for item in scored[:limit]]
# ------------------------------------------------------------------
# Trust management
# ------------------------------------------------------------------
def boost_trust(self, memory_id: int, delta: float = 0.05) -> None:
"""Increase trust score when a memory proves useful."""
self._conn.execute(
"""UPDATE memories SET trust_score = MIN(1.0, trust_score + ?),
updated_at = ? WHERE memory_id = ?""",
(delta, time.time(), memory_id),
)
self._conn.commit()
def decay_trust(self, memory_id: int, delta: float = 0.02) -> None:
"""Decrease trust score when a memory is contradicted."""
self._conn.execute(
"""UPDATE memories SET trust_score = MAX(0.0, trust_score - ?),
updated_at = ? WHERE memory_id = ?""",
(delta, time.time(), memory_id),
)
self._conn.commit()
# ------------------------------------------------------------------
# Room operations
# ------------------------------------------------------------------
def list_rooms(self) -> list[dict]:
"""List all rooms with fact counts."""
rows = self._conn.execute(
"""SELECT room, COUNT(*) as count,
AVG(trust_score) as avg_trust
FROM memories GROUP BY room ORDER BY count DESC"""
).fetchall()
return [dict(r) for r in rows]
def room_contents(self, room: str, limit: int = 50) -> list[dict]:
"""Get all facts in a room, ordered by trust."""
rows = self._conn.execute(
"""SELECT memory_id, content, category, trust_score,
retrieval_count, created_at
FROM memories WHERE room = ?
ORDER BY trust_score DESC, created_at DESC LIMIT ?""",
(room, limit),
).fetchall()
return [dict(r) for r in rows]
# ------------------------------------------------------------------
# Stats
# ------------------------------------------------------------------
def stats(self) -> dict:
"""Return store statistics."""
row = self._conn.execute(
"""SELECT COUNT(*) as total,
AVG(trust_score) as avg_trust,
SUM(retrieval_count) as total_retrievals,
COUNT(DISTINCT room) as room_count
FROM memories"""
).fetchone()
return dict(row)
# ------------------------------------------------------------------
# Promotion support (scratchpad → durable)
# ------------------------------------------------------------------
def log_promotion(
self,
session_id: str,
scratch_key: str,
memory_id: int,
reason: str = "",
) -> None:
"""Record a scratchpad-to-palace promotion in the audit log."""
self._conn.execute(
"""INSERT INTO promotion_log
(session_id, scratch_key, memory_id, promoted_at, reason)
VALUES (?, ?, ?, ?, ?)""",
(session_id, scratch_key, memory_id, time.time(), reason),
)
self._conn.commit()
def recent_promotions(self, limit: int = 20) -> list[dict]:
"""Get recent promotion log entries."""
rows = self._conn.execute(
"""SELECT p.*, m.content, m.room
FROM promotion_log p
LEFT JOIN memories m ON p.memory_id = m.memory_id
ORDER BY p.promoted_at DESC LIMIT ?""",
(limit,),
).fetchall()
return [dict(r) for r in rows]

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"""Tests for the mempalace skill.
Validates PalaceRoom, Mempalace class, factory constructors,
and the analyse_issues entry-point.
Refs: Epic #367, Sub-issue #368
"""
from __future__ import annotations
import json
import sys
import os
import time
import pytest
# Ensure the package is importable from the repo layout
sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", ".."))
from mempalace.mempalace import Mempalace, PalaceRoom, analyse_issues
# ── PalaceRoom unit tests ─────────────────────────────────────────────────
class TestPalaceRoom:
def test_store_and_retrieve(self):
room = PalaceRoom(name="test", label="Test Room")
room.store("key1", 42)
assert room.retrieve("key1") == 42
def test_retrieve_default(self):
room = PalaceRoom(name="test", label="Test Room")
assert room.retrieve("missing") is None
assert room.retrieve("missing", "fallback") == "fallback"
def test_summary_format(self):
room = PalaceRoom(name="test", label="Test Room")
room.store("repos", 5)
summary = room.summary()
assert "## Test Room" in summary
assert "repos: 5" in summary
def test_contents_default_factory_isolation(self):
"""Each room gets its own dict — no shared mutable default."""
r1 = PalaceRoom(name="a", label="A")
r2 = PalaceRoom(name="b", label="B")
r1.store("x", 1)
assert r2.retrieve("x") is None
def test_entered_at_is_recent(self):
before = time.time()
room = PalaceRoom(name="t", label="T")
after = time.time()
assert before <= room.entered_at <= after
# ── Mempalace core tests ──────────────────────────────────────────────────
class TestMempalace:
def test_add_and_enter_room(self):
p = Mempalace(domain="test")
p.add_room("r1", "Room 1")
room = p.enter("r1")
assert room.name == "r1"
def test_enter_nonexistent_room_raises(self):
p = Mempalace()
with pytest.raises(KeyError, match="No room"):
p.enter("ghost")
def test_store_without_enter_raises(self):
p = Mempalace()
p.add_room("r", "R")
with pytest.raises(RuntimeError, match="Enter a room"):
p.store("k", "v")
def test_store_and_retrieve_via_palace(self):
p = Mempalace()
p.add_room("r", "R")
p.enter("r")
p.store("count", 10)
assert p.retrieve("r", "count") == 10
def test_retrieve_missing_room_returns_default(self):
p = Mempalace()
assert p.retrieve("nope", "key") is None
assert p.retrieve("nope", "key", 99) == 99
def test_render_includes_domain(self):
p = Mempalace(domain="audit")
p.add_room("r", "Room")
p.enter("r")
p.store("item", "value")
output = p.render()
assert "audit" in output
assert "Room" in output
def test_to_dict_structure(self):
p = Mempalace(domain="test")
p.add_room("r", "R")
p.enter("r")
p.store("a", 1)
d = p.to_dict()
assert d["domain"] == "test"
assert "elapsed_seconds" in d
assert d["rooms"]["r"] == {"a": 1}
def test_to_json_is_valid(self):
p = Mempalace(domain="j")
p.add_room("x", "X")
p.enter("x")
p.store("v", [1, 2, 3])
parsed = json.loads(p.to_json())
assert parsed["rooms"]["x"]["v"] == [1, 2, 3]
# ── Factory constructor tests ─────────────────────────────────────────────
class TestFactories:
def test_for_issue_analysis_rooms(self):
p = Mempalace.for_issue_analysis()
assert p.domain == "issue_analysis"
for key in ("repo_architecture", "assignment_status",
"triage_priority", "resolution_patterns"):
p.enter(key) # should not raise
def test_for_health_check_rooms(self):
p = Mempalace.for_health_check()
assert p.domain == "health_check"
for key in ("service_topology", "failure_signals", "recovery_history"):
p.enter(key)
def test_for_code_review_rooms(self):
p = Mempalace.for_code_review()
assert p.domain == "code_review"
for key in ("change_scope", "risk_surface",
"test_coverage", "reviewer_context"):
p.enter(key)
# ── analyse_issues entry-point tests ──────────────────────────────────────
class TestAnalyseIssues:
SAMPLE_DATA = [
{"repo": "the-nexus", "open_issues": 40, "assigned": 30, "unassigned": 10},
{"repo": "timmy-home", "open_issues": 30, "assigned": 25, "unassigned": 5},
{"repo": "hermes-agent", "open_issues": 20, "assigned": 15, "unassigned": 5},
{"repo": "empty-repo", "open_issues": 0, "assigned": 0, "unassigned": 0},
]
def test_returns_string(self):
result = analyse_issues(self.SAMPLE_DATA)
assert isinstance(result, str)
assert len(result) > 0
def test_contains_room_headers(self):
result = analyse_issues(self.SAMPLE_DATA)
assert "Repository Architecture" in result
assert "Assignment Status" in result
def test_coverage_below_target(self):
result = analyse_issues(self.SAMPLE_DATA, target_assignee_rate=0.90)
assert "BELOW TARGET" in result
def test_coverage_meets_target(self):
good_data = [
{"repo": "a", "open_issues": 10, "assigned": 10, "unassigned": 0},
]
result = analyse_issues(good_data, target_assignee_rate=0.80)
assert "OK" in result
def test_empty_repos_list(self):
result = analyse_issues([])
assert isinstance(result, str)
def test_single_repo(self):
data = [{"repo": "solo", "open_issues": 5, "assigned": 3, "unassigned": 2}]
result = analyse_issues(data)
assert "solo" in result or "issue_analysis" in result

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"""Tests for retrieval_enforcer.py.
Refs: Epic #367, Sub-issue #369
"""
from __future__ import annotations
import json
import os
import sys
import tempfile
from pathlib import Path
from unittest.mock import patch, MagicMock
import pytest
sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", ".."))
from mempalace.retrieval_enforcer import (
is_recall_query,
load_identity,
load_scratchpad,
enforce_retrieval_order,
search_skills,
RECALL_PATTERNS,
)
class TestRecallDetection:
"""Test the recall-query pattern matcher."""
@pytest.mark.parametrize("query", [
"what did we work on yesterday",
"status of the mempalace integration",
"remember the fleet audit results",
"last time we deployed the nexus",
"previously you mentioned a CI fix",
"we discussed the sovereign deployment",
])
def test_recall_queries_detected(self, query):
assert is_recall_query(query) is True
@pytest.mark.parametrize("query", [
"create a new file called test.py",
"run the test suite",
"deploy to production",
"write a function that sums numbers",
"install the package",
])
def test_non_recall_queries_skipped(self, query):
assert is_recall_query(query) is False
class TestLoadIdentity:
def test_loads_existing_identity(self, tmp_path):
identity_file = tmp_path / "identity.txt"
identity_file.write_text("I am Timmy. A sovereign AI.")
with patch("mempalace.retrieval_enforcer.IDENTITY_PATH", identity_file):
result = load_identity()
assert "Timmy" in result
def test_returns_empty_on_missing_file(self, tmp_path):
identity_file = tmp_path / "nonexistent.txt"
with patch("mempalace.retrieval_enforcer.IDENTITY_PATH", identity_file):
result = load_identity()
assert result == ""
def test_truncates_long_identity(self, tmp_path):
identity_file = tmp_path / "identity.txt"
identity_file.write_text(" ".join(["word"] * 300))
with patch("mempalace.retrieval_enforcer.IDENTITY_PATH", identity_file):
result = load_identity()
assert result.endswith("...")
assert len(result.split()) <= 201 # 200 words + "..."
class TestLoadScratchpad:
def test_loads_valid_scratchpad(self, tmp_path):
scratch_file = tmp_path / "session123.json"
scratch_file.write_text(json.dumps({"note": "test value", "key2": 42}))
with patch("mempalace.retrieval_enforcer.SCRATCHPAD_DIR", tmp_path):
result = load_scratchpad("session123")
assert "note: test value" in result
assert "key2: 42" in result
def test_returns_empty_on_missing_file(self, tmp_path):
with patch("mempalace.retrieval_enforcer.SCRATCHPAD_DIR", tmp_path):
result = load_scratchpad("nonexistent")
assert result == ""
def test_returns_empty_on_invalid_json(self, tmp_path):
scratch_file = tmp_path / "bad.json"
scratch_file.write_text("not valid json{{{")
with patch("mempalace.retrieval_enforcer.SCRATCHPAD_DIR", tmp_path):
result = load_scratchpad("bad")
assert result == ""
class TestEnforceRetrievalOrder:
def test_skips_non_recall_query(self):
result = enforce_retrieval_order("create a new file")
assert result["retrieved_from"] is None
assert result["tokens"] == 0
def test_runs_for_recall_query(self, tmp_path):
identity_file = tmp_path / "identity.txt"
identity_file.write_text("I am Timmy.")
with patch("mempalace.retrieval_enforcer.IDENTITY_PATH", identity_file), \
patch("mempalace.retrieval_enforcer.search_palace", return_value=""), \
patch("mempalace.retrieval_enforcer.search_gitea", return_value=""), \
patch("mempalace.retrieval_enforcer.search_skills", return_value=""):
result = enforce_retrieval_order("what did we work on yesterday")
assert "Identity" in result["context"]
assert "L0" in result["layers_checked"]
def test_palace_hit_sets_l1(self, tmp_path):
identity_file = tmp_path / "identity.txt"
identity_file.write_text("I am Timmy.")
with patch("mempalace.retrieval_enforcer.IDENTITY_PATH", identity_file), \
patch("mempalace.retrieval_enforcer.search_palace", return_value="Found: fleet audit results"), \
patch("mempalace.retrieval_enforcer.search_gitea", return_value=""):
result = enforce_retrieval_order("what did we discuss yesterday")
assert result["retrieved_from"] == "L1"
assert "Palace Memory" in result["context"]
def test_falls_through_to_l5(self, tmp_path):
identity_file = tmp_path / "nonexistent.txt"
with patch("mempalace.retrieval_enforcer.IDENTITY_PATH", identity_file), \
patch("mempalace.retrieval_enforcer.search_palace", return_value=""), \
patch("mempalace.retrieval_enforcer.search_gitea", return_value=""), \
patch("mempalace.retrieval_enforcer.search_skills", return_value=""):
result = enforce_retrieval_order("remember the old deployment", skip_if_not_recall=True)
assert result["retrieved_from"] == "L5"
def test_force_mode_skips_recall_check(self, tmp_path):
identity_file = tmp_path / "identity.txt"
identity_file.write_text("I am Timmy.")
with patch("mempalace.retrieval_enforcer.IDENTITY_PATH", identity_file), \
patch("mempalace.retrieval_enforcer.search_palace", return_value=""), \
patch("mempalace.retrieval_enforcer.search_gitea", return_value=""), \
patch("mempalace.retrieval_enforcer.search_skills", return_value=""):
result = enforce_retrieval_order("deploy now", skip_if_not_recall=False)
assert "Identity" in result["context"]

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"""Tests for scratchpad.py.
Refs: Epic #367, Sub-issue #372
"""
from __future__ import annotations
import json
import os
import sys
from pathlib import Path
from unittest.mock import patch
import pytest
sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", ".."))
from mempalace.scratchpad import (
write_scratch,
read_scratch,
delete_scratch,
list_sessions,
clear_session,
_scratch_path,
)
@pytest.fixture
def scratch_dir(tmp_path):
"""Provide a temporary scratchpad directory."""
with patch("mempalace.scratchpad.SCRATCHPAD_DIR", tmp_path):
yield tmp_path
class TestScratchPath:
def test_sanitizes_session_id(self):
path = _scratch_path("safe-id_123")
assert "safe-id_123.json" in str(path)
def test_strips_dangerous_chars(self):
path = _scratch_path("../../etc/passwd")
assert ".." not in path.name
assert "/" not in path.name
# Dots are stripped, so only alphanumeric chars remain
assert path.name == "etcpasswd.json"
class TestWriteAndRead:
def test_write_then_read(self, scratch_dir):
write_scratch("sess1", "note", "hello world")
result = read_scratch("sess1", "note")
assert "note" in result
assert result["note"]["value"] == "hello world"
def test_read_all_keys(self, scratch_dir):
write_scratch("sess1", "a", 1)
write_scratch("sess1", "b", 2)
result = read_scratch("sess1")
assert "a" in result
assert "b" in result
def test_read_missing_key(self, scratch_dir):
write_scratch("sess1", "exists", "yes")
result = read_scratch("sess1", "missing")
assert result == {}
def test_read_missing_session(self, scratch_dir):
result = read_scratch("nonexistent")
assert result == {}
def test_overwrite_key(self, scratch_dir):
write_scratch("sess1", "key", "v1")
write_scratch("sess1", "key", "v2")
result = read_scratch("sess1", "key")
assert result["key"]["value"] == "v2"
class TestDelete:
def test_delete_existing_key(self, scratch_dir):
write_scratch("sess1", "key", "val")
assert delete_scratch("sess1", "key") is True
assert read_scratch("sess1", "key") == {}
def test_delete_missing_key(self, scratch_dir):
write_scratch("sess1", "other", "val")
assert delete_scratch("sess1", "missing") is False
class TestListSessions:
def test_lists_sessions(self, scratch_dir):
write_scratch("alpha", "k", "v")
write_scratch("beta", "k", "v")
sessions = list_sessions()
assert "alpha" in sessions
assert "beta" in sessions
def test_empty_directory(self, scratch_dir):
assert list_sessions() == []
class TestClearSession:
def test_clears_existing(self, scratch_dir):
write_scratch("sess1", "k", "v")
assert clear_session("sess1") is True
assert read_scratch("sess1") == {}
def test_clear_nonexistent(self, scratch_dir):
assert clear_session("ghost") is False

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"""Tests for the Sovereign Memory Store and Promotion system.
Zero-API, zero-network — everything runs against an in-memory SQLite DB.
"""
import os
import sys
import tempfile
import time
import unittest
# Allow imports from parent package
sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
from sovereign_store import (
SovereignStore,
encode_text,
cosine_similarity_phase,
serialize_vector,
deserialize_vector,
)
from promotion import (
evaluate_for_promotion,
promote,
promote_session_batch,
)
class TestHRRVectors(unittest.TestCase):
"""Test the HRR encoding and similarity functions."""
def test_deterministic_encoding(self):
"""Same text always produces the same vector."""
v1 = encode_text("hello world")
v2 = encode_text("hello world")
self.assertAlmostEqual(cosine_similarity_phase(v1, v2), 1.0, places=5)
def test_similar_texts_higher_similarity(self):
"""Related texts should be more similar than unrelated ones."""
v_agent = encode_text("agent memory palace retrieval")
v_similar = encode_text("agent recall memory search")
v_unrelated = encode_text("banana strawberry fruit smoothie")
sim_related = cosine_similarity_phase(v_agent, v_similar)
sim_unrelated = cosine_similarity_phase(v_agent, v_unrelated)
self.assertGreater(sim_related, sim_unrelated)
def test_serialize_roundtrip(self):
"""Vectors survive serialization to/from bytes."""
vec = encode_text("test serialization")
blob = serialize_vector(vec)
restored = deserialize_vector(blob)
sim = cosine_similarity_phase(vec, restored)
self.assertAlmostEqual(sim, 1.0, places=5)
def test_empty_text(self):
"""Empty text gets a fallback encoding."""
vec = encode_text("")
self.assertEqual(len(vec) if hasattr(vec, '__len__') else len(list(vec)), 512)
class TestSovereignStore(unittest.TestCase):
"""Test the SQLite-backed sovereign store."""
def setUp(self):
self.db_path = os.path.join(tempfile.mkdtemp(), "test.db")
self.store = SovereignStore(db_path=self.db_path)
def tearDown(self):
self.store.close()
if os.path.exists(self.db_path):
os.remove(self.db_path)
def test_store_and_retrieve(self):
"""Store a fact and find it via search."""
mid = self.store.store("Timmy is a sovereign AI agent on Hermes VPS", room="identity")
results = self.store.search("sovereign agent", room="identity")
self.assertTrue(any(r["memory_id"] == mid for r in results))
def test_fts_search(self):
"""FTS5 keyword search works."""
self.store.store("The beacon game uses paperclips mechanics", room="projects")
self.store.store("Fleet agents handle delegation and dispatch", room="fleet")
results = self.store.search("paperclips")
self.assertTrue(len(results) > 0)
self.assertIn("paperclips", results[0]["content"].lower())
def test_hrr_search_semantic(self):
"""HRR similarity finds related content even without exact keywords."""
self.store.store("Memory palace rooms organize facts spatially", room="memory")
self.store.store("Pizza delivery service runs on weekends", room="unrelated")
results = self.store.search("organize knowledge rooms", room="memory")
self.assertTrue(len(results) > 0)
self.assertIn("palace", results[0]["content"].lower())
def test_room_filtering(self):
"""Room filter restricts search scope."""
self.store.store("Hermes harness manages tool calls", room="infrastructure")
self.store.store("Hermes mythology Greek god", room="lore")
results = self.store.search("Hermes", room="infrastructure")
self.assertTrue(all(r["room"] == "infrastructure" for r in results))
def test_trust_boost(self):
"""Trust score increases when boosted."""
mid = self.store.store("fact", trust=0.5)
self.store.boost_trust(mid, delta=0.1)
results = self.store.room_contents("general")
fact = next(r for r in results if r["memory_id"] == mid)
self.assertAlmostEqual(fact["trust_score"], 0.6, places=2)
def test_trust_decay(self):
"""Trust score decreases when decayed."""
mid = self.store.store("questionable fact", trust=0.5)
self.store.decay_trust(mid, delta=0.2)
results = self.store.room_contents("general")
fact = next(r for r in results if r["memory_id"] == mid)
self.assertAlmostEqual(fact["trust_score"], 0.3, places=2)
def test_batch_store(self):
"""Batch store works."""
ids = self.store.store_batch([
{"content": "fact one", "room": "test"},
{"content": "fact two", "room": "test"},
{"content": "fact three", "room": "test"},
])
self.assertEqual(len(ids), 3)
rooms = self.store.list_rooms()
test_room = next(r for r in rooms if r["room"] == "test")
self.assertEqual(test_room["count"], 3)
def test_stats(self):
"""Stats returns correct counts."""
self.store.store("a fact", room="r1")
self.store.store("another fact", room="r2")
s = self.store.stats()
self.assertEqual(s["total"], 2)
self.assertEqual(s["room_count"], 2)
def test_retrieval_count_increments(self):
"""Retrieval count goes up when a fact is found via search."""
self.store.store("unique searchable content xyz123", room="test")
self.store.search("xyz123")
results = self.store.room_contents("test")
self.assertTrue(any(r["retrieval_count"] > 0 for r in results))
class TestPromotion(unittest.TestCase):
"""Test the quality-gated promotion system."""
def setUp(self):
self.db_path = os.path.join(tempfile.mkdtemp(), "promo_test.db")
self.store = SovereignStore(db_path=self.db_path)
def tearDown(self):
self.store.close()
def test_successful_promotion(self):
"""Good content passes all gates."""
result = promote(
content="Timmy runs on the Hermes VPS at 143.198.27.163 with local Ollama inference",
store=self.store,
session_id="test-session-001",
scratch_key="vps_info",
room="infrastructure",
)
self.assertTrue(result.success)
self.assertIsNotNone(result.memory_id)
def test_reject_too_short(self):
"""Short fragments get rejected."""
result = promote(
content="yes",
store=self.store,
session_id="test",
scratch_key="short",
)
self.assertFalse(result.success)
self.assertIn("Too short", result.reason)
def test_reject_duplicate(self):
"""Duplicate content gets rejected."""
self.store.store("SOUL.md is the canonical identity document for Timmy", room="identity")
result = promote(
content="SOUL.md is the canonical identity document for Timmy",
store=self.store,
session_id="test",
scratch_key="soul",
room="identity",
)
self.assertFalse(result.success)
self.assertIn("uplicate", result.reason)
def test_reject_stale(self):
"""Old notes get flagged as stale."""
old_time = time.time() - (86400 * 10)
result = promote(
content="This is a note from long ago about something important",
store=self.store,
session_id="test",
scratch_key="old",
written_at=old_time,
)
self.assertFalse(result.success)
self.assertIn("Stale", result.reason)
def test_force_bypasses_gates(self):
"""Force flag overrides quality gates."""
result = promote(
content="ok",
store=self.store,
session_id="test",
scratch_key="forced",
force=True,
)
self.assertTrue(result.success)
def test_evaluate_dry_run(self):
"""Evaluate returns gate details without promoting."""
eval_result = evaluate_for_promotion(
content="The fleet uses kimi-k2.5 as the primary model for all agent operations",
store=self.store,
room="fleet",
)
self.assertTrue(eval_result["eligible"])
self.assertTrue(all(p for p, _ in eval_result["gates"].values()))
def test_batch_promotion(self):
"""Batch promotion processes all notes."""
notes = {
"infra": {"value": "Hermes VPS runs Ubuntu 22.04 with 2 vCPUs and 4GB RAM", "written_at": time.strftime("%Y-%m-%d %H:%M:%S")},
"short": {"value": "no", "written_at": time.strftime("%Y-%m-%d %H:%M:%S")},
"model": {"value": "The primary local model is gemma4:latest running on Ollama", "written_at": time.strftime("%Y-%m-%d %H:%M:%S")},
}
results = promote_session_batch(self.store, "batch-session", notes, room="config")
promoted = [r for r in results if r.success]
rejected = [r for r in results if not r.success]
self.assertEqual(len(promoted), 2)
self.assertEqual(len(rejected), 1)
def test_promotion_logged(self):
"""Successful promotions appear in the audit log."""
promote(
content="Forge is hosted at forge.alexanderwhitestone.com running Gitea",
store=self.store,
session_id="log-test",
scratch_key="forge",
room="infrastructure",
)
log = self.store.recent_promotions()
self.assertTrue(len(log) > 0)
self.assertEqual(log[0]["session_id"], "log-test")
self.assertEqual(log[0]["scratch_key"], "forge")
if __name__ == "__main__":
unittest.main()

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"""Tests for wakeup.py.
Refs: Epic #367, Sub-issue #372
"""
from __future__ import annotations
import json
import os
import sys
import time
from pathlib import Path
from unittest.mock import patch, MagicMock
import pytest
sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", ".."))
from mempalace.wakeup import (
palace_wakeup,
fleet_status_summary,
_load_identity,
_palace_context,
)
class TestLoadIdentity:
def test_loads_identity(self, tmp_path):
f = tmp_path / "identity.txt"
f.write_text("I am Timmy. A sovereign AI.")
with patch("mempalace.wakeup.IDENTITY_PATH", f):
result = _load_identity()
assert "Timmy" in result
def test_missing_identity(self, tmp_path):
f = tmp_path / "nope.txt"
with patch("mempalace.wakeup.IDENTITY_PATH", f):
assert _load_identity() == ""
class TestFleetStatus:
def test_reads_fleet_json(self, tmp_path):
f = tmp_path / "fleet_status.json"
f.write_text(json.dumps({
"Groq": {"state": "active", "last_seen": "2026-04-07"},
"Ezra": {"state": "idle", "last_seen": "2026-04-06"},
}))
with patch("mempalace.wakeup.FLEET_STATUS_PATH", f):
result = fleet_status_summary()
assert "Fleet Status" in result
assert "Groq" in result
assert "active" in result
def test_missing_fleet_file(self, tmp_path):
f = tmp_path / "nope.json"
with patch("mempalace.wakeup.FLEET_STATUS_PATH", f):
assert fleet_status_summary() == ""
def test_invalid_json(self, tmp_path):
f = tmp_path / "bad.json"
f.write_text("not json")
with patch("mempalace.wakeup.FLEET_STATUS_PATH", f):
assert fleet_status_summary() == ""
class TestPalaceWakeup:
def test_generates_context_with_identity(self, tmp_path):
identity = tmp_path / "identity.txt"
identity.write_text("I am Timmy.")
cache = tmp_path / "cache.txt"
with patch("mempalace.wakeup.IDENTITY_PATH", identity), \
patch("mempalace.wakeup.WAKEUP_CACHE_PATH", cache), \
patch("mempalace.wakeup._palace_context", return_value=""), \
patch("mempalace.wakeup.fleet_status_summary", return_value=""):
result = palace_wakeup(force=True)
assert "Identity" in result
assert "Timmy" in result
assert "Session" in result
def test_uses_cache_when_fresh(self, tmp_path):
cache = tmp_path / "cache.txt"
cache.write_text("cached wake-up content")
# Touch the file so it's fresh
with patch("mempalace.wakeup.WAKEUP_CACHE_PATH", cache), \
patch("mempalace.wakeup.WAKEUP_CACHE_TTL", 9999):
result = palace_wakeup(force=False)
assert result == "cached wake-up content"
def test_force_bypasses_cache(self, tmp_path):
cache = tmp_path / "cache.txt"
cache.write_text("stale content")
identity = tmp_path / "identity.txt"
identity.write_text("I am Timmy.")
with patch("mempalace.wakeup.WAKEUP_CACHE_PATH", cache), \
patch("mempalace.wakeup.IDENTITY_PATH", identity), \
patch("mempalace.wakeup._palace_context", return_value=""), \
patch("mempalace.wakeup.fleet_status_summary", return_value=""):
result = palace_wakeup(force=True)
assert "Identity" in result
assert "stale content" not in result

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@@ -0,0 +1,161 @@
"""Wake-up Protocol — session start context injection.
Generates 300-900 tokens of context when a new Hermes session starts.
Loads identity, recent palace context, and fleet status.
Refs: Epic #367, Sub-issue #372
"""
from __future__ import annotations
import json
import os
import subprocess
import time
from pathlib import Path
# ---------------------------------------------------------------------------
# Constants
# ---------------------------------------------------------------------------
IDENTITY_PATH = Path.home() / ".mempalace" / "identity.txt"
MEMPALACE_BIN = "/Library/Frameworks/Python.framework/Versions/3.12/bin/mempalace"
FLEET_STATUS_PATH = Path.home() / ".hermes" / "fleet_status.json"
WAKEUP_CACHE_PATH = Path.home() / ".hermes" / "last_wakeup.txt"
WAKEUP_CACHE_TTL = 300 # 5 minutes — don't regenerate if recent
# ---------------------------------------------------------------------------
# Helpers
# ---------------------------------------------------------------------------
def _load_identity() -> str:
"""Read the agent identity file."""
try:
if IDENTITY_PATH.exists():
text = IDENTITY_PATH.read_text(encoding="utf-8").strip()
# Cap at ~150 tokens for wake-up brevity
words = text.split()
if len(words) > 150:
text = " ".join(words[:150]) + "..."
return text
except (OSError, PermissionError):
pass
return ""
def _palace_context() -> str:
"""Run mempalace wake-up command for recent context. Degrades gracefully."""
try:
bin_path = MEMPALACE_BIN if os.path.exists(MEMPALACE_BIN) else "mempalace"
result = subprocess.run(
[bin_path, "wake-up"],
capture_output=True,
text=True,
timeout=10,
)
if result.returncode == 0 and result.stdout.strip():
return result.stdout.strip()
except (FileNotFoundError, subprocess.TimeoutExpired, OSError):
# ONNX issues (#373) or CLI not available — degrade gracefully
pass
return ""
def fleet_status_summary() -> str:
"""Read cached fleet status for lightweight session context."""
try:
if FLEET_STATUS_PATH.exists():
data = json.loads(FLEET_STATUS_PATH.read_text(encoding="utf-8"))
lines = ["## Fleet Status"]
if isinstance(data, dict):
for agent, status in data.items():
if isinstance(status, dict):
state = status.get("state", "unknown")
last_seen = status.get("last_seen", "?")
lines.append(f" {agent}: {state} (last: {last_seen})")
else:
lines.append(f" {agent}: {status}")
if len(lines) > 1:
return "\n".join(lines)
except (OSError, json.JSONDecodeError):
pass
return ""
def _check_cache() -> str:
"""Return cached wake-up if fresh enough."""
try:
if WAKEUP_CACHE_PATH.exists():
age = time.time() - WAKEUP_CACHE_PATH.stat().st_mtime
if age < WAKEUP_CACHE_TTL:
return WAKEUP_CACHE_PATH.read_text(encoding="utf-8").strip()
except OSError:
pass
return ""
def _write_cache(content: str) -> None:
"""Cache the wake-up content."""
try:
WAKEUP_CACHE_PATH.parent.mkdir(parents=True, exist_ok=True)
WAKEUP_CACHE_PATH.write_text(content, encoding="utf-8")
except OSError:
pass
# ---------------------------------------------------------------------------
# Main entry point
# ---------------------------------------------------------------------------
def palace_wakeup(force: bool = False) -> str:
"""Generate wake-up context for a new session. ~300-900 tokens.
Args:
force: If True, bypass the 5-minute cache and regenerate.
Returns:
Formatted context string suitable for prepending to the system prompt.
"""
# Check cache first (avoids redundant work on rapid session restarts)
if not force:
cached = _check_cache()
if cached:
return cached
parts = []
# L0: Identity
identity = _load_identity()
if identity:
parts.append(f"## Identity\n{identity}")
# L1: Recent palace context
palace = _palace_context()
if palace:
parts.append(palace)
# Fleet status (lightweight)
fleet = fleet_status_summary()
if fleet:
parts.append(fleet)
# Timestamp
parts.append(f"## Session\nWake-up generated: {time.strftime('%Y-%m-%d %H:%M:%S')}")
content = "\n\n".join(parts)
# Cache for TTL
_write_cache(content)
return content
# ---------------------------------------------------------------------------
# CLI entry point for testing
# ---------------------------------------------------------------------------
if __name__ == "__main__":
print(palace_wakeup(force=True))

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@@ -0,0 +1,39 @@
#!/usr/bin/env bash
# orchestrate.sh — Sovereign Orchestrator wrapper
# Sets environment and runs orchestrator.py
#
# Usage:
# ./orchestrate.sh # dry-run (safe default)
# ./orchestrate.sh --once # single live dispatch cycle
# ./orchestrate.sh --daemon # continuous (every 15 min)
# ./orchestrate.sh --dry-run # explicit dry-run
set -euo pipefail
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
HERMES_DIR="${HOME}/.hermes"
# Load Gitea token
if [[ -z "${GITEA_TOKEN:-}" ]]; then
if [[ -f "${HERMES_DIR}/gitea_token_vps" ]]; then
export GITEA_TOKEN="$(cat "${HERMES_DIR}/gitea_token_vps")"
else
echo "[FATAL] No GITEA_TOKEN and ~/.hermes/gitea_token_vps not found"
exit 1
fi
fi
# Load Telegram token
if [[ -z "${TELEGRAM_BOT_TOKEN:-}" ]]; then
if [[ -f "${HOME}/.config/telegram/special_bot" ]]; then
export TELEGRAM_BOT_TOKEN="$(cat "${HOME}/.config/telegram/special_bot")"
fi
fi
# Run preflight checks if available
if [[ -x "${HERMES_DIR}/bin/api-key-preflight.sh" ]]; then
"${HERMES_DIR}/bin/api-key-preflight.sh" 2>/dev/null || true
fi
# Run the orchestrator
exec python3 "${SCRIPT_DIR}/orchestrator.py" "$@"

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@@ -0,0 +1,645 @@
#!/usr/bin/env python3
"""
Sovereign Orchestrator v1
Reads the Gitea backlog, scores/prioritizes issues, dispatches to agents.
Usage:
python3 orchestrator.py --once # single dispatch cycle
python3 orchestrator.py --daemon # run every 15 min
python3 orchestrator.py --dry-run # score and report, no dispatch
"""
import json
import os
import sys
import time
import subprocess
import urllib.request
import urllib.error
import urllib.parse
from datetime import datetime, timezone
# ---------------------------------------------------------------------------
# CONFIG
# ---------------------------------------------------------------------------
GITEA_API = "https://forge.alexanderwhitestone.com/api/v1"
GITEA_OWNER = "Timmy_Foundation"
REPOS = ["timmy-config", "the-nexus", "timmy-home"]
TELEGRAM_CHAT_ID = "-1003664764329"
DAEMON_INTERVAL = 900 # 15 minutes
# Tags that mark issues we should never auto-dispatch
FILTER_TAGS = ["[EPIC]", "[DO NOT CLOSE]", "[PERMANENT]", "[PHILOSOPHY]", "[MORNING REPORT]"]
# Known agent usernames on Gitea (for assignee detection)
AGENT_USERNAMES = {"groq", "ezra", "bezalel", "allegro", "timmy", "thetimmyc"}
# ---------------------------------------------------------------------------
# AGENT ROSTER
# ---------------------------------------------------------------------------
AGENTS = {
"groq": {
"type": "loop",
"endpoint": "local",
"strengths": ["code", "bug-fix", "small-changes"],
"repos": ["the-nexus", "hermes-agent", "timmy-config", "timmy-home"],
"max_concurrent": 1,
},
"ezra": {
"type": "gateway",
"endpoint": "http://143.198.27.163:8643/v1/chat/completions",
"ssh": "root@143.198.27.163",
"strengths": ["research", "architecture", "complex", "multi-file"],
"repos": ["timmy-config", "the-nexus", "timmy-home"],
"max_concurrent": 1,
},
"bezalel": {
"type": "gateway",
"endpoint": "http://159.203.146.185:8643/v1/chat/completions",
"ssh": "root@159.203.146.185",
"strengths": ["ci", "infra", "ops", "testing"],
"repos": ["timmy-config", "hermes-agent", "the-nexus"],
"max_concurrent": 1,
},
}
# ---------------------------------------------------------------------------
# CREDENTIALS
# ---------------------------------------------------------------------------
def load_gitea_token():
"""Read Gitea token from env or file."""
token = os.environ.get("GITEA_TOKEN", "")
if token:
return token.strip()
token_path = os.path.expanduser("~/.hermes/gitea_token_vps")
try:
with open(token_path) as f:
return f.read().strip()
except FileNotFoundError:
print(f"[FATAL] No GITEA_TOKEN env and {token_path} not found")
sys.exit(1)
def load_telegram_token():
"""Read Telegram bot token from file."""
path = os.path.expanduser("~/.config/telegram/special_bot")
try:
with open(path) as f:
return f.read().strip()
except FileNotFoundError:
return ""
GITEA_TOKEN = ""
TELEGRAM_TOKEN = ""
# ---------------------------------------------------------------------------
# HTTP HELPERS (stdlib only)
# ---------------------------------------------------------------------------
def gitea_request(path, method="GET", data=None):
"""Make an authenticated Gitea API request."""
url = f"{GITEA_API}{path}"
headers = {
"Authorization": f"token {GITEA_TOKEN}",
"Content-Type": "application/json",
"Accept": "application/json",
}
body = json.dumps(data).encode() if data else None
req = urllib.request.Request(url, data=body, headers=headers, method=method)
try:
with urllib.request.urlopen(req, timeout=30) as resp:
return json.loads(resp.read().decode())
except urllib.error.HTTPError as e:
body_text = e.read().decode() if e.fp else ""
print(f"[API ERROR] {method} {url} -> {e.code}: {body_text[:200]}")
return None
except Exception as e:
print(f"[API ERROR] {method} {url} -> {e}")
return None
def send_telegram(message):
"""Send message to Telegram group."""
if not TELEGRAM_TOKEN:
print("[WARN] No Telegram token, skipping notification")
return False
url = f"https://api.telegram.org/bot{TELEGRAM_TOKEN}/sendMessage"
data = json.dumps({
"chat_id": TELEGRAM_CHAT_ID,
"text": message,
"parse_mode": "Markdown",
"disable_web_page_preview": True,
}).encode()
req = urllib.request.Request(url, data=data, headers={"Content-Type": "application/json"})
try:
with urllib.request.urlopen(req, timeout=15) as resp:
return resp.status == 200
except Exception as e:
print(f"[TELEGRAM ERROR] {e}")
return False
# ---------------------------------------------------------------------------
# 1. BACKLOG READER
# ---------------------------------------------------------------------------
def fetch_issues(repo):
"""Fetch all open issues from a repo, handling pagination."""
issues = []
page = 1
while True:
result = gitea_request(
f"/repos/{GITEA_OWNER}/{repo}/issues?state=open&type=issues&limit=50&page={page}"
)
if not result:
break
issues.extend(result)
if len(result) < 50:
break
page += 1
return issues
def should_filter(issue):
"""Check if issue title contains any filter tags."""
title = issue.get("title", "").upper()
for tag in FILTER_TAGS:
if tag.upper().replace("[", "").replace("]", "") in title.replace("[", "").replace("]", ""):
return True
# Also filter pull requests
if issue.get("pull_request"):
return True
return False
def read_backlog():
"""Read and filter the full backlog across all repos."""
backlog = []
for repo in REPOS:
print(f" Fetching {repo}...")
issues = fetch_issues(repo)
for issue in issues:
if should_filter(issue):
continue
assignees = [a.get("login", "") for a in (issue.get("assignees") or [])]
labels = [l.get("name", "") for l in (issue.get("labels") or [])]
backlog.append({
"repo": repo,
"number": issue["number"],
"title": issue["title"],
"labels": labels,
"assignees": assignees,
"created_at": issue.get("created_at", ""),
"comments": issue.get("comments", 0),
"url": issue.get("html_url", ""),
})
print(f" Total actionable issues: {len(backlog)}")
return backlog
# ---------------------------------------------------------------------------
# 2. PRIORITY SCORER
# ---------------------------------------------------------------------------
def score_issue(issue):
"""Score an issue 0-100 based on priority signals."""
score = 0
title_upper = issue["title"].upper()
labels_upper = [l.upper() for l in issue["labels"]]
all_text = title_upper + " " + " ".join(labels_upper)
# Critical / Bug: +30
if any(tag in all_text for tag in ["CRITICAL", "BUG"]):
score += 30
# P0 / Urgent: +25
if any(tag in all_text for tag in ["P0", "URGENT"]):
score += 25
# P1: +15
if "P1" in all_text:
score += 15
# OPS / Security: +10
if any(tag in all_text for tag in ["OPS", "SECURITY"]):
score += 10
# Unassigned: +10
if not issue["assignees"]:
score += 10
# Age > 7 days: +5
try:
created = issue["created_at"].replace("Z", "+00:00")
created_dt = datetime.fromisoformat(created)
age_days = (datetime.now(timezone.utc) - created_dt).days
if age_days > 7:
score += 5
except (ValueError, AttributeError):
pass
# Has comments: +5
if issue["comments"] > 0:
score += 5
# Infrastructure repo: +5
if issue["repo"] == "timmy-config":
score += 5
# Already assigned to an agent: -10
if any(a.lower() in AGENT_USERNAMES for a in issue["assignees"]):
score -= 10
issue["score"] = max(0, min(100, score))
return issue
def prioritize_backlog(backlog):
"""Score and sort the backlog by priority."""
scored = [score_issue(i) for i in backlog]
scored.sort(key=lambda x: x["score"], reverse=True)
return scored
# ---------------------------------------------------------------------------
# 3. AGENT HEALTH CHECKS
# ---------------------------------------------------------------------------
def check_process(pattern):
"""Check if a local process matching pattern is running."""
try:
result = subprocess.run(
["pgrep", "-f", pattern],
capture_output=True, text=True, timeout=5
)
return result.returncode == 0
except Exception:
return False
def check_ssh_service(host, service_name):
"""Check if a remote service is running via SSH."""
try:
result = subprocess.run(
["ssh", "-o", "ConnectTimeout=5", "-o", "StrictHostKeyChecking=no",
f"root@{host}",
f"systemctl is-active {service_name} 2>/dev/null || pgrep -f {service_name}"],
capture_output=True, text=True, timeout=15
)
return result.returncode == 0
except Exception:
return False
def check_agent_health(name, agent):
"""Check if an agent is alive and available."""
if agent["type"] == "loop":
alive = check_process(f"agent-loop.*{name}")
elif agent["type"] == "gateway":
host = agent["ssh"].split("@")[1]
service = f"hermes-{name}"
alive = check_ssh_service(host, service)
else:
alive = False
return alive
def get_agent_status():
"""Get health status for all agents."""
status = {}
for name, agent in AGENTS.items():
alive = check_agent_health(name, agent)
status[name] = {
"alive": alive,
"type": agent["type"],
"strengths": agent["strengths"],
}
symbol = "UP" if alive else "DOWN"
print(f" {name}: {symbol} ({agent['type']})")
return status
# ---------------------------------------------------------------------------
# 4. DISPATCHER
# ---------------------------------------------------------------------------
def classify_issue(issue):
"""Classify issue type based on title and labels."""
title = issue["title"].upper()
labels = " ".join(issue["labels"]).upper()
all_text = title + " " + labels
types = []
if any(w in all_text for w in ["BUG", "FIX", "BROKEN", "ERROR", "CRASH"]):
types.append("bug-fix")
if any(w in all_text for w in ["OPS", "DEPLOY", "CI", "INFRA", "PIPELINE", "MONITOR"]):
types.append("ops")
if any(w in all_text for w in ["SECURITY", "AUTH", "TOKEN", "CERT"]):
types.append("ops")
if any(w in all_text for w in ["RESEARCH", "AUDIT", "INVESTIGATE", "EXPLORE"]):
types.append("research")
if any(w in all_text for w in ["ARCHITECT", "DESIGN", "REFACTOR", "REWRITE"]):
types.append("architecture")
if any(w in all_text for w in ["TEST", "TESTING", "QA", "VALIDATE"]):
types.append("testing")
if any(w in all_text for w in ["CODE", "IMPLEMENT", "ADD", "CREATE", "BUILD"]):
types.append("code")
if any(w in all_text for w in ["SMALL", "QUICK", "SIMPLE", "MINOR", "TWEAK"]):
types.append("small-changes")
if any(w in all_text for w in ["COMPLEX", "MULTI", "LARGE", "OVERHAUL"]):
types.append("complex")
if not types:
types = ["code"] # default
return types
def match_agent(issue, agent_status, dispatched_this_cycle):
"""Find the best available agent for an issue."""
issue_types = classify_issue(issue)
candidates = []
for name, agent in AGENTS.items():
# Agent must be alive
if not agent_status.get(name, {}).get("alive", False):
continue
# Agent must handle this repo
if issue["repo"] not in agent["repos"]:
continue
# Agent must not already be dispatched this cycle
if dispatched_this_cycle.get(name, 0) >= agent["max_concurrent"]:
continue
# Score match based on overlapping strengths
overlap = len(set(issue_types) & set(agent["strengths"]))
candidates.append((name, overlap))
if not candidates:
return None
# Sort by overlap score descending, return best match
candidates.sort(key=lambda x: x[1], reverse=True)
return candidates[0][0]
def assign_issue(repo, number, agent_name):
"""Assign an issue to an agent on Gitea."""
# First get current assignees to not clobber
result = gitea_request(f"/repos/{GITEA_OWNER}/{repo}/issues/{number}")
if not result:
return False
current = [a.get("login", "") for a in (result.get("assignees") or [])]
if agent_name in current:
print(f" Already assigned to {agent_name}")
return True
new_assignees = current + [agent_name]
patch_result = gitea_request(
f"/repos/{GITEA_OWNER}/{repo}/issues/{number}",
method="PATCH",
data={"assignees": new_assignees}
)
return patch_result is not None
def dispatch_to_gateway(agent_name, agent, issue):
"""Trigger work on a gateway agent via SSH."""
host = agent["ssh"]
repo = issue["repo"]
number = issue["number"]
title = issue["title"]
# Try to trigger dispatch via SSH
cmd = (
f'ssh -o ConnectTimeout=10 -o StrictHostKeyChecking=no {host} '
f'"echo \'Dispatched by orchestrator: {repo}#{number} - {title}\' '
f'>> /tmp/hermes-dispatch.log"'
)
try:
subprocess.run(cmd, shell=True, timeout=20, capture_output=True)
return True
except Exception as e:
print(f" [WARN] SSH dispatch to {agent_name} failed: {e}")
return False
def dispatch_cycle(backlog, agent_status, dry_run=False):
"""Run one dispatch cycle. Returns dispatch report."""
dispatched = []
skipped = []
dispatched_count = {} # agent_name -> count dispatched this cycle
# Only dispatch unassigned issues (or issues not assigned to agents)
for issue in backlog:
agent_assigned = any(a.lower() in AGENT_USERNAMES for a in issue["assignees"])
if agent_assigned:
skipped.append((issue, "already assigned to agent"))
continue
if issue["score"] < 5:
skipped.append((issue, "score too low"))
continue
best_agent = match_agent(issue, agent_status, dispatched_count)
if not best_agent:
skipped.append((issue, "no available agent"))
continue
if dry_run:
dispatched.append({
"agent": best_agent,
"repo": issue["repo"],
"number": issue["number"],
"title": issue["title"],
"score": issue["score"],
"dry_run": True,
})
dispatched_count[best_agent] = dispatched_count.get(best_agent, 0) + 1
continue
# Actually dispatch
print(f" Dispatching {issue['repo']}#{issue['number']} -> {best_agent}")
success = assign_issue(issue["repo"], issue["number"], best_agent)
if success:
agent = AGENTS[best_agent]
if agent["type"] == "gateway":
dispatch_to_gateway(best_agent, agent, issue)
dispatched.append({
"agent": best_agent,
"repo": issue["repo"],
"number": issue["number"],
"title": issue["title"],
"score": issue["score"],
})
dispatched_count[best_agent] = dispatched_count.get(best_agent, 0) + 1
else:
skipped.append((issue, "assignment failed"))
return dispatched, skipped
# ---------------------------------------------------------------------------
# 5. CONSOLIDATED REPORT
# ---------------------------------------------------------------------------
def generate_report(backlog, dispatched, skipped, agent_status, dry_run=False):
"""Generate dispatch cycle report."""
now = datetime.now().strftime("%Y-%m-%d %H:%M")
mode = " [DRY RUN]" if dry_run else ""
lines = []
lines.append(f"=== Sovereign Orchestrator Report{mode} ===")
lines.append(f"Time: {now}")
lines.append(f"Total backlog: {len(backlog)} issues")
lines.append("")
# Agent health
lines.append("-- Agent Health --")
for name, info in agent_status.items():
symbol = "UP" if info["alive"] else "DOWN"
lines.append(f" {name}: {symbol} ({info['type']})")
lines.append("")
# Dispatched
lines.append(f"-- Dispatched: {len(dispatched)} --")
for d in dispatched:
dry = " (dry-run)" if d.get("dry_run") else ""
lines.append(f" [{d['score']}] {d['repo']}#{d['number']} -> {d['agent']}{dry}")
lines.append(f" {d['title'][:60]}")
lines.append("")
# Skipped (top 10)
skip_summary = {}
for issue, reason in skipped:
skip_summary[reason] = skip_summary.get(reason, 0) + 1
lines.append(f"-- Skipped: {len(skipped)} --")
for reason, count in sorted(skip_summary.items(), key=lambda x: -x[1]):
lines.append(f" {reason}: {count}")
lines.append("")
# Top 5 unassigned
unassigned = [i for i in backlog if not i["assignees"]][:5]
lines.append("-- Top 5 Unassigned (by priority) --")
for i in unassigned:
lines.append(f" [{i['score']}] {i['repo']}#{i['number']}: {i['title'][:55]}")
lines.append("")
report = "\n".join(lines)
return report
def format_telegram_report(backlog, dispatched, skipped, agent_status, dry_run=False):
"""Format a compact Telegram message."""
mode = " DRY RUN" if dry_run else ""
now = datetime.now().strftime("%H:%M")
parts = [f"*Orchestrator{mode}* ({now})"]
parts.append(f"Backlog: {len(backlog)} | Dispatched: {len(dispatched)} | Skipped: {len(skipped)}")
# Agent status line
agent_line = " | ".join(
f"{'' if v['alive'] else ''}{k}" for k, v in agent_status.items()
)
parts.append(agent_line)
if dispatched:
parts.append("")
parts.append("*Dispatched:*")
for d in dispatched[:5]:
dry = " 🔍" if d.get("dry_run") else ""
parts.append(f" `{d['repo']}#{d['number']}` → {d['agent']}{dry}")
# Top unassigned
unassigned = [i for i in backlog if not i["assignees"]][:3]
if unassigned:
parts.append("")
parts.append("*Top unassigned:*")
for i in unassigned:
parts.append(f" [{i['score']}] `{i['repo']}#{i['number']}` {i['title'][:40]}")
return "\n".join(parts)
# ---------------------------------------------------------------------------
# 6. MAIN
# ---------------------------------------------------------------------------
def run_cycle(dry_run=False):
"""Execute one full orchestration cycle."""
global GITEA_TOKEN, TELEGRAM_TOKEN
GITEA_TOKEN = load_gitea_token()
TELEGRAM_TOKEN = load_telegram_token()
print("\n[1/4] Reading backlog...")
backlog = read_backlog()
print("\n[2/4] Scoring and prioritizing...")
backlog = prioritize_backlog(backlog)
for i in backlog[:10]:
print(f" [{i['score']:3d}] {i['repo']}/{i['number']}: {i['title'][:55]}")
print("\n[3/4] Checking agent health...")
agent_status = get_agent_status()
print("\n[4/4] Dispatching...")
dispatched, skipped = dispatch_cycle(backlog, agent_status, dry_run=dry_run)
# Generate reports
report = generate_report(backlog, dispatched, skipped, agent_status, dry_run=dry_run)
print("\n" + report)
# Send Telegram notification
if dispatched or not dry_run:
tg_msg = format_telegram_report(backlog, dispatched, skipped, agent_status, dry_run=dry_run)
send_telegram(tg_msg)
return backlog, dispatched, skipped
def main():
import argparse
parser = argparse.ArgumentParser(description="Sovereign Orchestrator v1")
parser.add_argument("--once", action="store_true", help="Single dispatch cycle")
parser.add_argument("--daemon", action="store_true", help="Run every 15 min")
parser.add_argument("--dry-run", action="store_true", help="Score/report only, no dispatch")
parser.add_argument("--interval", type=int, default=DAEMON_INTERVAL,
help=f"Daemon interval in seconds (default: {DAEMON_INTERVAL})")
args = parser.parse_args()
if not any([args.once, args.daemon, args.dry_run]):
args.dry_run = True # safe default
print("[INFO] No mode specified, defaulting to --dry-run")
print("=" * 60)
print(" SOVEREIGN ORCHESTRATOR v1")
print("=" * 60)
if args.daemon:
print(f"[DAEMON] Running every {args.interval}s (Ctrl+C to stop)")
cycle = 0
while True:
cycle += 1
print(f"\n--- Cycle {cycle} ---")
try:
run_cycle(dry_run=args.dry_run)
except Exception as e:
print(f"[ERROR] Cycle failed: {e}")
print(f"[DAEMON] Sleeping {args.interval}s...")
time.sleep(args.interval)
else:
run_cycle(dry_run=args.dry_run)
if __name__ == "__main__":
main()