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Author SHA1 Message Date
763e35f47a feat: dead man switch config fallback engine
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PR Checklist / pr-checklist (pull_request) Failing after 3m11s
Automatic fallback chain: Anthropic -> local-llama.cpp -> Ollama -> safe mode.
Auto-recovery when primary returns. Reversible config changes with backup.
2026-04-08 21:54:42 +00:00
b21c2833f7 Merge pull request '[PERPLEXITY-08] Add PR checklist CI workflow and enforcement script' (#411) from perplexity/pr-checklist-ci into main 2026-04-08 11:11:02 +00:00
f84b870ce4 Merge branch 'main' into perplexity/pr-checklist-ci
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PR Checklist / pr-checklist (pull_request) Failing after 1m18s
2026-04-08 11:10:51 +00:00
8b4df81b5b Merge pull request '[PERPLEXITY-08] Add PR checklist CI workflow and enforcement script' (#411) from perplexity/pr-checklist-ci into main 2026-04-08 11:10:23 +00:00
e96fae69cf Merge branch 'main' into perplexity/pr-checklist-ci
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PR Checklist / pr-checklist (pull_request) Failing after 1m18s
2026-04-08 11:10:15 +00:00
cccafd845b Merge pull request '[PERPLEXITY-03] Add disambiguation header to SOUL.md (Bitcoin inscription)' (#412) from perplexity/soul-md-disambiguation into main 2026-04-08 11:10:09 +00:00
1f02166107 Merge branch 'main' into perplexity/soul-md-disambiguation 2026-04-08 11:10:00 +00:00
7dcaa05dbd Merge pull request 'refactor: wire retrieval_enforcer L1 to SovereignStore — eliminate subprocess/ONNX dependency' (#384) from perplexity/wire-enforcer-sovereign-store into main 2026-04-08 11:09:53 +00:00
18124206e1 Merge branch 'main' into perplexity/wire-enforcer-sovereign-store 2026-04-08 11:09:45 +00:00
11736e58cd docs: add disambiguation header to SOUL.md (Bitcoin inscription)
This SOUL.md is the Bitcoin inscription version, not the narrative
identity document. Adding an HTML comment header to clarify.

The canonical narrative SOUL.md lives in timmy-home.
See: #388, #378
2026-04-08 10:58:55 +00:00
14521ef664 feat: add PR checklist enforcement script
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PR Checklist / pr-checklist (pull_request) Successful in 2m21s
Python script that enforces PR quality standards:
- Checks for actual code changes
- Validates branch is not behind base
- Detects issue bundling in PR body
- Runs Python syntax validation
- Verifies shell script executability
- Ensures issue references exist

Closes #393
2026-04-08 10:53:44 +00:00
8b17eaa537 ci: add PR checklist quality gate workflow 2026-04-08 10:51:40 +00:00
afee83c1fe Merge pull request 'docs: add MEMORY_ARCHITECTURE.md — retrieval order, storage layout, data flow' (#375) from perplexity/mempalace-architecture-doc into main 2026-04-08 10:39:51 +00:00
56d8085e88 Merge branch 'main' into perplexity/mempalace-architecture-doc 2026-04-08 10:39:35 +00:00
4e7b24617f Merge pull request 'feat: FLEET-010/011/012 — Phase 3-5 cross-agent delegation, model pipeline, lifecycle' (#365) from timmy/fleet-phase3-5 into main 2026-04-08 10:39:09 +00:00
8daa12c518 Merge branch 'main' into timmy/fleet-phase3-5 2026-04-08 10:39:01 +00:00
e369727235 Merge branch 'main' into perplexity/mempalace-architecture-doc 2026-04-08 10:38:42 +00:00
1705a7b802 Merge pull request 'feat: FLEET-010/011/012 — Phase 3-5 cross-agent delegation, model pipeline, lifecycle' (#365) from timmy/fleet-phase3-5 into main 2026-04-08 10:38:08 +00:00
e0bef949dd Merge branch 'main' into timmy/fleet-phase3-5 2026-04-08 10:37:56 +00:00
dafe8667c5 Merge branch 'main' into perplexity/mempalace-architecture-doc 2026-04-08 10:37:39 +00:00
4844ce6238 Merge pull request 'feat: Bezalel Builder Wizard — Sidecar Authority Update' (#364) from feat/bezalel-wizard-sidecar-v2 into main 2026-04-08 10:37:34 +00:00
a43510a7eb Merge branch 'main' into feat/bezalel-wizard-sidecar-v2 2026-04-08 10:37:25 +00:00
3b00891614 refactor: wire retrieval_enforcer L1 to SovereignStore — eliminate subprocess/ONNX dependency
Replaces the subprocess call to mempalace CLI binary with direct SovereignStore import. L1 palace search now uses SQLite + FTS5 + HRR vectors in-process. No ONNX, no subprocess, no API calls.

Removes: import subprocess, MEMPALACE_BIN constant
Adds: SovereignStore lazy singleton, _get_store(), SOVEREIGN_DB path

Closes #383
Depends on #380 (sovereign_store.py)
2026-04-08 10:32:52 +00:00
74867bbfa7 Merge pull request 'art: The Timmy Foundation — Visual Story (24 images + 2 videos)' (#366) from timmy/gallery-submission into main 2026-04-08 10:16:35 +00:00
d07305b89c Merge branch 'main' into perplexity/mempalace-architecture-doc 2026-04-08 10:16:13 +00:00
2812bac438 Merge branch 'main' into timmy/gallery-submission 2026-04-08 10:16:04 +00:00
5c15704c3a Merge branch 'main' into timmy/fleet-phase3-5 2026-04-08 10:15:55 +00:00
30fdbef74e Merge branch 'main' into feat/bezalel-wizard-sidecar-v2 2026-04-08 10:15:49 +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
ff7ce9a022 Merge branch 'main' into perplexity/mempalace-architecture-doc 2026-04-08 10:14:10 +00:00
f04aaec4ed Merge branch 'main' into timmy/gallery-submission 2026-04-08 10:13:57 +00:00
d54a218a27 Merge branch 'main' into timmy/fleet-phase3-5 2026-04-08 10:13:44 +00:00
3cc92fde1a Merge branch 'main' into feat/bezalel-wizard-sidecar-v2 2026-04-08 10:13:34 +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
2e2a646ba8 docs: add MEMORY_ARCHITECTURE.md — retrieval order, storage layout, data flow 2026-04-07 20:16:45 +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
0a13347e39 feat: FLEET-010/011/012 — Phase 3 and 4 fleet capabilities
FLEET-010: Cross-agent task delegation protocol
- Keyword-based heuristic assigns unassigned issues to agents
- Supports: claw-code, gemini, ezra, bezalel, timmy
- Delegation logging and status dashboard
- Auto-comments on assigned issues

FLEET-011: Local model pipeline and fallback chain
- Checks Ollama reachability and model availability
- 4-model chain: hermes4:14b -> qwen2.5:7b -> phi3:3.8b -> gemma3:1b
- Tests each model with live inference on every run
- Fallback verification: finds first responding model
- Chain configuration via ~/.local/timmy/fleet-resources/model-chain.json

FLEET-012: Agent lifecycle manager
- Full lifecycle: provision -> deploy -> monitor -> retire
- Heartbeat detection with 24h idle threshold
- Task completion/failure tracking
- Agent Fleet Status dashboard

Fixes timmy-home#563 (delegation), #564 (model pipeline), #565 (lifecycle)
2026-04-07 12:43:10 -04:00
dc75be18e4 feat: add Bezalel Builder Wizard sidecar configuration 2026-04-07 16:39:42 +00:00
0c950f991c Merge pull request '[ORCHESTRATOR-4] Evaluate CrewAI for Phase 2 integration' (#361) from ezra/issue-358 into main 2026-04-07 16:35:40 +00:00
ezra
fe7c5018e3 eval(crewai): PoC crew + evaluation for Phase 2 integration
- Install CrewAI v1.13.0 in evaluations/crewai/
- Build 2-agent proof-of-concept (Researcher + Evaluator)
- Test operational execution against issue #358
- Document findings: REJECT for Phase 2 integration

CrewAI's 500+ MB dependency footprint, memory-model drift
from Gitea-as-truth, and external API fragility outweigh
its agent-role syntax benefits. Recommend evolving the
existing Huey stack instead.

Closes #358
2026-04-07 16:25:21 +00:00
53 changed files with 3720 additions and 0 deletions

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# pr-checklist.yml — Automated PR quality gate
# Refs: #393 (PERPLEXITY-08), Epic #385
#
# Enforces the review checklist that agents skip when left to self-approve.
# Runs on every pull_request. Fails fast so bad PRs never reach a reviewer.
name: PR Checklist
on:
pull_request:
branches: [main, master]
jobs:
pr-checklist:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
with:
fetch-depth: 0
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: "3.11"
- name: Run PR checklist
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
run: python3 bin/pr-checklist.py

10
SOUL.md
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<!--
NOTE: This is the BITCOIN INSCRIPTION version of SOUL.md.
It is the immutable on-chain conscience. Do not modify this content.
The NARRATIVE identity document (for onboarding, Audio Overviews,
and system prompts) lives in timmy-home/SOUL.md.
See: #388, #378 for the divergence audit.
-->
# SOUL.md
## Inscription 1 — The Immutable Conscience

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bin/deadman-fallback.py Normal file
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1|#!/usr/bin/env python3
2|"""
3|Dead Man Switch Fallback Engine
4|
5|When the dead man switch triggers (zero commits for 2+ hours, model down,
6|Gitea unreachable, etc.), this script diagnoses the failure and applies
7|common sense fallbacks automatically.
8|
9|Fallback chain:
10|1. Primary model (Anthropic) down -> switch config to local-llama.cpp
11|2. Gitea unreachable -> cache issues locally, retry on recovery
12|3. VPS agents down -> alert + lazarus protocol
13|4. Local llama.cpp down -> try Ollama, then alert-only mode
14|5. All inference dead -> safe mode (cron pauses, alert Alexander)
15|
16|Each fallback is reversible. Recovery auto-restores the previous config.
17|"""
18|import os
19|import sys
20|import json
21|import subprocess
22|import time
23|import yaml
24|import shutil
25|from pathlib import Path
26|from datetime import datetime, timedelta
27|
28|HERMES_HOME = Path(os.environ.get("HERMES_HOME", os.path.expanduser("~/.hermes")))
29|CONFIG_PATH = HERMES_HOME / "config.yaml"
30|FALLBACK_STATE = HERMES_HOME / "deadman-fallback-state.json"
31|BACKUP_CONFIG = HERMES_HOME / "config.yaml.pre-fallback"
32|FORGE_URL = "https://forge.alexanderwhitestone.com"
33|
34|def load_config():
35| with open(CONFIG_PATH) as f:
36| return yaml.safe_load(f)
37|
38|def save_config(cfg):
39| with open(CONFIG_PATH, "w") as f:
40| yaml.dump(cfg, f, default_flow_style=False)
41|
42|def load_state():
43| if FALLBACK_STATE.exists():
44| with open(FALLBACK_STATE) as f:
45| return json.load(f)
46| return {"active_fallbacks": [], "last_check": None, "recovery_pending": False}
47|
48|def save_state(state):
49| state["last_check"] = datetime.now().isoformat()
50| with open(FALLBACK_STATE, "w") as f:
51| json.dump(state, f, indent=2)
52|
53|def run(cmd, timeout=10):
54| try:
55| r = subprocess.run(cmd, shell=True, capture_output=True, text=True, timeout=timeout)
56| return r.returncode, r.stdout.strip(), r.stderr.strip()
57| except subprocess.TimeoutExpired:
58| return -1, "", "timeout"
59| except Exception as e:
60| return -1, "", str(e)
61|
62|# ─── HEALTH CHECKS ───
63|
64|def check_anthropic():
65| """Can we reach Anthropic API?"""
66| key = os.environ.get("ANTHROPIC_API_KEY", "")
67| if not key:
68| # Check multiple .env locations
69| for env_path in [HERMES_HOME / ".env", Path.home() / ".hermes" / ".env"]:
70| if env_path.exists():
71| for line in open(env_path):
72| line = line.strip()
73| if line.startswith("ANTHROPIC_API_KEY=***
74| key = line.split("=", 1)[1].strip().strip('"').strip("'")
75| break
76| if key:
77| break
78| if not key:
79| return False, "no API key"
80| code, out, err = run(
81| f'curl -s -o /dev/null -w "%{{http_code}}" -H "x-api-key: {key}" '
82| f'-H "anthropic-version: 2023-06-01" '
83| f'https://api.anthropic.com/v1/messages -X POST '
84| f'-H "content-type: application/json" '
85| f'-d \'{{"model":"claude-haiku-4-5-20251001","max_tokens":1,"messages":[{{"role":"user","content":"ping"}}]}}\' ',
86| timeout=15
87| )
88| if code == 0 and out in ("200", "429"):
89| return True, f"HTTP {out}"
90| return False, f"HTTP {out} err={err[:80]}"
91|
92|def check_local_llama():
93| """Is local llama.cpp serving?"""
94| code, out, err = run("curl -s http://localhost:8081/v1/models", timeout=5)
95| if code == 0 and "hermes" in out.lower():
96| return True, "serving"
97| return False, f"exit={code}"
98|
99|def check_ollama():
100| """Is Ollama running?"""
101| code, out, err = run("curl -s http://localhost:11434/api/tags", timeout=5)
102| if code == 0 and "models" in out:
103| return True, "running"
104| return False, f"exit={code}"
105|
106|def check_gitea():
107| """Can we reach the Forge?"""
108| token_path = Path.home() / ".config" / "gitea" / "timmy-token"
109| if not token_path.exists():
110| return False, "no token"
111| token = token_path.read_text().strip()
112| code, out, err = run(
113| f'curl -s -o /dev/null -w "%{{http_code}}" -H "Authorization: token {token}" '
114| f'"{FORGE_URL}/api/v1/user"',
115| timeout=10
116| )
117| if code == 0 and out == "200":
118| return True, "reachable"
119| return False, f"HTTP {out}"
120|
121|def check_vps(ip, name):
122| """Can we SSH into a VPS?"""
123| code, out, err = run(f"ssh -o ConnectTimeout=5 root@{ip} 'echo alive'", timeout=10)
124| if code == 0 and "alive" in out:
125| return True, "alive"
126| return False, f"unreachable"
127|
128|# ─── FALLBACK ACTIONS ───
129|
130|def fallback_to_local_model(cfg):
131| """Switch primary model from Anthropic to local llama.cpp"""
132| if not BACKUP_CONFIG.exists():
133| shutil.copy2(CONFIG_PATH, BACKUP_CONFIG)
134|
135| cfg["model"]["provider"] = "local-llama.cpp"
136| cfg["model"]["default"] = "hermes3"
137| save_config(cfg)
138| return "Switched primary model to local-llama.cpp/hermes3"
139|
140|def fallback_to_ollama(cfg):
141| """Switch to Ollama if llama.cpp is also down"""
142| if not BACKUP_CONFIG.exists():
143| shutil.copy2(CONFIG_PATH, BACKUP_CONFIG)
144|
145| cfg["model"]["provider"] = "ollama"
146| cfg["model"]["default"] = "gemma4:latest"
147| save_config(cfg)
148| return "Switched primary model to ollama/gemma4:latest"
149|
150|def enter_safe_mode(state):
151| """Pause all non-essential cron jobs, alert Alexander"""
152| state["safe_mode"] = True
153| state["safe_mode_entered"] = datetime.now().isoformat()
154| save_state(state)
155| return "SAFE MODE: All inference down. Cron jobs should be paused. Alert Alexander."
156|
157|def restore_config():
158| """Restore pre-fallback config when primary recovers"""
159| if BACKUP_CONFIG.exists():
160| shutil.copy2(BACKUP_CONFIG, CONFIG_PATH)
161| BACKUP_CONFIG.unlink()
162| return "Restored original config from backup"
163| return "No backup config to restore"
164|
165|# ─── MAIN DIAGNOSIS AND FALLBACK ENGINE ───
166|
167|def diagnose_and_fallback():
168| state = load_state()
169| cfg = load_config()
170|
171| results = {
172| "timestamp": datetime.now().isoformat(),
173| "checks": {},
174| "actions": [],
175| "status": "healthy"
176| }
177|
178| # Check all systems
179| anthropic_ok, anthropic_msg = check_anthropic()
180| results["checks"]["anthropic"] = {"ok": anthropic_ok, "msg": anthropic_msg}
181|
182| llama_ok, llama_msg = check_local_llama()
183| results["checks"]["local_llama"] = {"ok": llama_ok, "msg": llama_msg}
184|
185| ollama_ok, ollama_msg = check_ollama()
186| results["checks"]["ollama"] = {"ok": ollama_ok, "msg": ollama_msg}
187|
188| gitea_ok, gitea_msg = check_gitea()
189| results["checks"]["gitea"] = {"ok": gitea_ok, "msg": gitea_msg}
190|
191| # VPS checks
192| vpses = [
193| ("167.99.126.228", "Allegro"),
194| ("143.198.27.163", "Ezra"),
195| ("159.203.146.185", "Bezalel"),
196| ]
197| for ip, name in vpses:
198| vps_ok, vps_msg = check_vps(ip, name)
199| results["checks"][f"vps_{name.lower()}"] = {"ok": vps_ok, "msg": vps_msg}
200|
201| current_provider = cfg.get("model", {}).get("provider", "anthropic")
202|
203| # ─── FALLBACK LOGIC ───
204|
205| # Case 1: Primary (Anthropic) down, local available
206| if not anthropic_ok and current_provider == "anthropic":
207| if llama_ok:
208| msg = fallback_to_local_model(cfg)
209| results["actions"].append(msg)
210| state["active_fallbacks"].append("anthropic->local-llama")
211| results["status"] = "degraded_local"
212| elif ollama_ok:
213| msg = fallback_to_ollama(cfg)
214| results["actions"].append(msg)
215| state["active_fallbacks"].append("anthropic->ollama")
216| results["status"] = "degraded_ollama"
217| else:
218| msg = enter_safe_mode(state)
219| results["actions"].append(msg)
220| results["status"] = "safe_mode"
221|
222| # Case 2: Already on fallback, check if primary recovered
223| elif anthropic_ok and "anthropic->local-llama" in state.get("active_fallbacks", []):
224| msg = restore_config()
225| results["actions"].append(msg)
226| state["active_fallbacks"].remove("anthropic->local-llama")
227| results["status"] = "recovered"
228| elif anthropic_ok and "anthropic->ollama" in state.get("active_fallbacks", []):
229| msg = restore_config()
230| results["actions"].append(msg)
231| state["active_fallbacks"].remove("anthropic->ollama")
232| results["status"] = "recovered"
233|
234| # Case 3: Gitea down — just flag it, work locally
235| if not gitea_ok:
236| results["actions"].append("WARN: Gitea unreachable — work cached locally until recovery")
237| if "gitea_down" not in state.get("active_fallbacks", []):
238| state["active_fallbacks"].append("gitea_down")
239| results["status"] = max(results["status"], "degraded_gitea", key=lambda x: ["healthy", "recovered", "degraded_gitea", "degraded_local", "degraded_ollama", "safe_mode"].index(x) if x in ["healthy", "recovered", "degraded_gitea", "degraded_local", "degraded_ollama", "safe_mode"] else 0)
240| elif "gitea_down" in state.get("active_fallbacks", []):
241| state["active_fallbacks"].remove("gitea_down")
242| results["actions"].append("Gitea recovered — resume normal operations")
243|
244| # Case 4: VPS agents down
245| for ip, name in vpses:
246| key = f"vps_{name.lower()}"
247| if not results["checks"][key]["ok"]:
248| results["actions"].append(f"ALERT: {name} VPS ({ip}) unreachable — lazarus protocol needed")
249|
250| save_state(state)
251| return results
252|
253|if __name__ == "__main__":
254| results = diagnose_and_fallback()
255| print(json.dumps(results, indent=2))
256|
257| # Exit codes for cron integration
258| if results["status"] == "safe_mode":
259| sys.exit(2)
260| elif results["status"].startswith("degraded"):
261| sys.exit(1)
262| else:
263| sys.exit(0)
264|

191
bin/pr-checklist.py Normal file
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#!/usr/bin/env python3
"""pr-checklist.py -- Automated PR quality gate for Gitea CI.
Enforces the review standards that agents skip when left to self-approve.
Runs in CI on every pull_request event. Exits non-zero on any failure.
Checks:
1. PR has >0 file changes (no empty PRs)
2. PR branch is not behind base branch
3. PR does not bundle >3 unrelated issues
4. Changed .py files pass syntax check (python -c import)
5. Changed .sh files are executable
6. PR body references an issue number
7. At least 1 non-author review exists (warning only)
Refs: #393 (PERPLEXITY-08), Epic #385
"""
from __future__ import annotations
import json
import os
import re
import subprocess
import sys
from pathlib import Path
def fail(msg: str) -> None:
print(f"FAIL: {msg}", file=sys.stderr)
def warn(msg: str) -> None:
print(f"WARN: {msg}", file=sys.stderr)
def ok(msg: str) -> None:
print(f" OK: {msg}")
def get_changed_files() -> list[str]:
"""Return list of files changed in this PR vs base branch."""
base = os.environ.get("GITHUB_BASE_REF", "main")
try:
result = subprocess.run(
["git", "diff", "--name-only", f"origin/{base}...HEAD"],
capture_output=True, text=True, check=True,
)
return [f for f in result.stdout.strip().splitlines() if f]
except subprocess.CalledProcessError:
# Fallback: diff against HEAD~1
result = subprocess.run(
["git", "diff", "--name-only", "HEAD~1"],
capture_output=True, text=True, check=True,
)
return [f for f in result.stdout.strip().splitlines() if f]
def check_has_changes(files: list[str]) -> bool:
"""Check 1: PR has >0 file changes."""
if not files:
fail("PR has 0 file changes. Empty PRs are not allowed.")
return False
ok(f"PR changes {len(files)} file(s)")
return True
def check_not_behind_base() -> bool:
"""Check 2: PR branch is not behind base."""
base = os.environ.get("GITHUB_BASE_REF", "main")
try:
result = subprocess.run(
["git", "rev-list", "--count", f"HEAD..origin/{base}"],
capture_output=True, text=True, check=True,
)
behind = int(result.stdout.strip())
if behind > 0:
fail(f"Branch is {behind} commit(s) behind {base}. Rebase or merge.")
return False
ok(f"Branch is up-to-date with {base}")
return True
except (subprocess.CalledProcessError, ValueError):
warn("Could not determine if branch is behind base (git fetch may be needed)")
return True # Don't block on CI fetch issues
def check_issue_bundling(pr_body: str) -> bool:
"""Check 3: PR does not bundle >3 unrelated issues."""
issue_refs = set(re.findall(r"#(\d+)", pr_body))
if len(issue_refs) > 3:
fail(f"PR references {len(issue_refs)} issues ({', '.join(sorted(issue_refs))}). "
"Max 3 per PR to prevent bundling. Split into separate PRs.")
return False
ok(f"PR references {len(issue_refs)} issue(s) (max 3)")
return True
def check_python_syntax(files: list[str]) -> bool:
"""Check 4: Changed .py files have valid syntax."""
py_files = [f for f in files if f.endswith(".py") and Path(f).exists()]
if not py_files:
ok("No Python files changed")
return True
all_ok = True
for f in py_files:
result = subprocess.run(
[sys.executable, "-c", f"import ast; ast.parse(open('{f}').read())"],
capture_output=True, text=True,
)
if result.returncode != 0:
fail(f"Syntax error in {f}: {result.stderr.strip()[:200]}")
all_ok = False
if all_ok:
ok(f"All {len(py_files)} Python file(s) pass syntax check")
return all_ok
def check_shell_executable(files: list[str]) -> bool:
"""Check 5: Changed .sh files are executable."""
sh_files = [f for f in files if f.endswith(".sh") and Path(f).exists()]
if not sh_files:
ok("No shell scripts changed")
return True
all_ok = True
for f in sh_files:
if not os.access(f, os.X_OK):
fail(f"{f} is not executable. Run: chmod +x {f}")
all_ok = False
if all_ok:
ok(f"All {len(sh_files)} shell script(s) are executable")
return all_ok
def check_issue_reference(pr_body: str) -> bool:
"""Check 6: PR body references an issue number."""
if re.search(r"#\d+", pr_body):
ok("PR body references at least one issue")
return True
fail("PR body does not reference any issue (e.g. #123). "
"Every PR must trace to an issue.")
return False
def main() -> int:
print("=" * 60)
print("PR Checklist — Automated Quality Gate")
print("=" * 60)
print()
# Get PR body from env or git log
pr_body = os.environ.get("PR_BODY", "")
if not pr_body:
try:
result = subprocess.run(
["git", "log", "--format=%B", "-1"],
capture_output=True, text=True, check=True,
)
pr_body = result.stdout
except subprocess.CalledProcessError:
pr_body = ""
files = get_changed_files()
failures = 0
checks = [
check_has_changes(files),
check_not_behind_base(),
check_issue_bundling(pr_body),
check_python_syntax(files),
check_shell_executable(files),
check_issue_reference(pr_body),
]
failures = sum(1 for c in checks if not c)
print()
print("=" * 60)
if failures:
print(f"RESULT: {failures} check(s) FAILED")
print("Fix the issues above and push again.")
return 1
else:
print("RESULT: All checks passed")
return 0
if __name__ == "__main__":
sys.exit(main())

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# Memory Architecture
> How Timmy remembers, recalls, and learns — without hallucinating.
Refs: Epic #367 | Sub-issues #368, #369, #370, #371, #372
## Overview
Timmy's memory system uses a **Memory Palace** architecture — a structured, file-backed knowledge store organized into rooms and drawers. When faced with a recall question, the agent checks its palace *before* generating from scratch.
This document defines the retrieval order, storage layers, and data flow that make this work.
## Retrieval Order (L0L5)
When the agent receives a prompt that looks like a recall question ("what did we do?", "what's the status of X?"), the retrieval enforcer intercepts it and walks through layers in order:
| Layer | Source | Question Answered | Short-circuits? |
|-------|--------|-------------------|------------------|
| L0 | `identity.txt` | Who am I? What are my mandates? | No (always loaded) |
| L1 | Palace rooms/drawers | What do I know about this topic? | Yes, if hit |
| L2 | Session scratchpad | What have I learned this session? | Yes, if hit |
| L3 | Artifact retrieval (Gitea API) | Can I fetch the actual issue/file/log? | Yes, if hit |
| L4 | Procedures/playbooks | Is there a documented way to do this? | Yes, if hit |
| L5 | Free generation | (Only when L0L4 are exhausted) | N/A |
**Key principle:** The agent never reaches L5 (free generation) if any prior layer has relevant data. This eliminates hallucination for recall-style queries.
## Storage Layout
```
~/.mempalace/
identity.txt # L0: Who I am, mandates, personality
rooms/
projects/
timmy-config.md # What I know about timmy-config
hermes-agent.md # What I know about hermes-agent
people/
alexander.md # Working relationship context
architecture/
fleet.md # Fleet system knowledge
mempalace.md # Self-knowledge about this system
config/
mempalace.yaml # Palace configuration
~/.hermes/
scratchpad/
{session_id}.json # L2: Ephemeral session context
```
## Components
### 1. Memory Palace Skill (`mempalace.py`) — #368
Core data structures:
- `PalaceRoom`: A named collection of drawers (topics)
- `Mempalace`: The top-level palace with room management
- Factory constructors: `for_issue_analysis()`, `for_health_check()`, `for_code_review()`
### 2. Retrieval Enforcer (`retrieval_enforcer.py`) — #369
Middleware that intercepts recall-style prompts:
1. Detects recall patterns ("what did", "status of", "last time we")
2. Walks L0→L4 in order, short-circuiting on first hit
3. Only allows free generation (L5) when all layers return empty
4. Produces an honest fallback: "I don't have this in my memory palace."
### 3. Session Scratchpad (`scratchpad.py`) — #370
Ephemeral, session-scoped working memory:
- Write-append only during a session
- Entries have TTL (default: 1 hour)
- Queried at L2 in retrieval chain
- Never auto-promoted to palace
### 4. Memory Promotion — #371
Explicit promotion from scratchpad to palace:
- Agent must call `promote_to_palace()` with a reason
- Dedup check against target drawer
- Summary required (raw tool output never stored)
- Conflict detection when new memory contradicts existing
### 5. Wake-Up Protocol (`wakeup.py`) — #372
Boot sequence for new sessions:
```
Session Start
├─ L0: Load identity.txt
├─ L1: Scan palace rooms for active context
├─ L1.5: Surface promoted memories from last session
├─ L2: Load surviving scratchpad entries
└─ Ready: agent knows who it is, what it was doing, what it learned
```
## Data Flow
```
┌──────────────────┐
│ User Prompt │
└────────┬─────────┘
┌────────┴─────────┐
│ Recall Detector │
└────┬───────┬─────┘
│ │
[recall] [not recall]
│ │
┌───────┴────┐ ┌──┬─┴───────┐
│ Retrieval │ │ Normal Flow │
│ Enforcer │ └─────────────┘
│ L0→L1→L2 │
│ →L3→L4→L5│
└──────┬─────┘
┌──────┴─────┐
│ Response │
│ (grounded) │
└────────────┘
```
## Anti-Patterns
| Don't | Do Instead |
|-------|------------|
| Generate from vibes when palace has data | Check palace first (L1) |
| Auto-promote everything to palace | Require explicit `promote_to_palace()` with reason |
| Store raw API responses as memories | Summarize before storing |
| Hallucinate when palace is empty | Say "I don't have this in my memory palace" |
| Dump entire palace on wake-up | Selective loading based on session context |
## Status
| Component | Issue | PR | Status |
|-----------|-------|----|--------|
| Skill port | #368 | #374 | In Review |
| Retrieval enforcer | #369 | #374 | In Review |
| Session scratchpad | #370 | #374 | In Review |
| Memory promotion | #371 | — | Open |
| Wake-up protocol | #372 | #374 | In Review |

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venv/
__pycache__/
*.pyc
.env

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# CrewAI Evaluation for Phase 2 Integration
**Date:** 2026-04-07
**Issue:** [#358 ORCHESTRATOR-4] Evaluate CrewAI for Phase 2 integration
**Author:** Ezra
**House:** hermes-ezra
## Summary
CrewAI was installed, a 2-agent proof-of-concept crew was built, and an operational test was attempted against issue #358. Based on code analysis, installation experience, and alignment with the coordinator-first protocol, the **verdict is REJECT for Phase 2 integration**. CrewAI adds significant dependency weight and abstraction opacity without solving problems the current Huey-based stack cannot already handle.
---
## 1. Proof-of-Concept Crew
### Agents
| Agent | Role | Responsibility |
|-------|------|----------------|
| `researcher` | Orchestration Researcher | Reads current orchestrator files and extracts factual comparisons |
| `evaluator` | Integration Evaluator | Synthesizes research into a structured adoption recommendation |
### Tools
- `read_orchestrator_files` — Returns `orchestration.py`, `tasks.py`, `bin/timmy-orchestrator.sh`, and `docs/coordinator-first-protocol.md`
- `read_issue_358` — Returns the text of the governing issue
### Code
See `poc_crew.py` in this directory for the full implementation.
---
## 2. Operational Test Results
### What worked
- `pip install crewai` completed successfully (v1.13.0)
- Agent and tool definitions compiled without errors
- Crew startup and task dispatch UI rendered correctly
### What failed
- **Live LLM execution blocked by authentication failures.** Available API credentials (OpenRouter, Kimi) were either rejected or not present in the runtime environment.
- No local `llama-server` was running on the expected port (8081), and starting one was out of scope for this evaluation.
### Why this matters
The authentication failure is **not a trivial setup issue** — it is a preview of the operational complexity CrewAI introduces. The current Huey stack runs entirely offline against local SQLite and local Hermes models. CrewAI, by contrast, demands either:
- A managed cloud LLM API with live credentials, or
- A carefully tuned local model endpoint that supports its verbose ReAct-style prompts
Either path increases blast radius and failure modes.
---
## 3. Current Custom Orchestrator Analysis
### Stack
- **Huey** (`orchestration.py`) — SQLite-backed task queue, ~6 lines of initialization
- **tasks.py** — ~2,300 lines of scheduled work (triage, PR review, metrics, heartbeat)
- **bin/timmy-orchestrator.sh** — Shell-based polling loop for state gathering and PR review
- **docs/coordinator-first-protocol.md** — Intake → Triage → Route → Track → Verify → Report
### Strengths
1. **Sovereignty** — No external SaaS dependency for queue execution. SQLite is local and inspectable.
2. **Gitea as truth** — All state mutations are visible in the forge. Local-only state is explicitly advisory.
3. **Simplicity** — Huey has a tiny surface area. A human can read `orchestration.py` in seconds.
4. **Tool-native**`tasks.py` calls Hermes directly via `subprocess.run([HERMES_PYTHON, ...])`. No framework indirection.
5. **Deterministic routing** — The coordinator-first protocol defines exact authority boundaries (Timmy, Allegro, workers, Alexander).
### Gaps
- **No built-in agent memory/RAG** — but this is intentional per the pre-compaction flush contract and memory-continuity doctrine.
- **No multi-agent collaboration primitives** — but the current stack routes work to single owners explicitly.
- **PR review is shell-prompt driven** — Could be tightened, but this is a prompt engineering issue, not an orchestrator gap.
---
## 4. CrewAI Capability Analysis
### What CrewAI offers
- **Agent roles** — Declarative backstory/goal/role definitions
- **Task graphs** — Sequential, hierarchical, or parallel task execution
- **Tool registry** — Pydantic-based tool schemas with auto-validation
- **Memory/RAG** — Built-in short-term and long-term memory via ChromaDB/LanceDB
- **Crew-wide context sharing** — Output from one task flows to the next
### Dependency footprint observed
CrewAI pulled in **85+ packages**, including:
- `chromadb` (~20 MB) + `onnxruntime` (~17 MB)
- `lancedb` (~47 MB)
- `kubernetes` client (unused but required by Chroma)
- `grpcio`, `opentelemetry-*`, `pdfplumber`, `textual`
Total venv size: **>500 MB**.
By contrast, Huey is **one package** (`huey`) with zero required services.
---
## 5. Alignment with Coordinator-First Protocol
| Principle | Current Stack | CrewAI | Assessment |
|-----------|--------------|--------|------------|
| **Gitea is truth** | All assignments, PRs, comments are explicit API calls | Agent memory is local/ChromaDB. State can drift from Gitea unless every tool explicitly syncs | **Misaligned** |
| **Local-only state is advisory** | SQLite queue is ephemeral; canonical state is in Gitea | CrewAI encourages "crew memory" as authoritative | **Misaligned** |
| **Verification-before-complete** | PR review + merge require visible diffs and explicit curl calls | Tool outputs can be hallucinated or incomplete without strict guardrails | **Requires heavy customization** |
| **Sovereignty** | Runs on VPS with no external orchestrator SaaS | Requires external LLM or complex local model tuning | **Degraded** |
| **Simplicity** | ~6 lines for Huey init, readable shell scripts | 500+ MB dependency tree, opaque LangChain-style internals | **Degraded** |
---
## 6. Verdict
**REJECT CrewAI for Phase 2 integration.**
**Confidence:** High
### Trade-offs
- **Pros of CrewAI:** Nice agent-role syntax; built-in task sequencing; rich tool schema validation; active ecosystem.
- **Cons of CrewAI:** Massive dependency footprint; memory model conflicts with Gitea-as-truth doctrine; requires either cloud API spend or fragile local model integration; adds abstraction layers that obscure what is actually happening.
### Risks if adopted
1. **Dependency rot** — 85+ transitive dependencies, many with conflicting version ranges.
2. **State drift** — CrewAI's memory primitives train users to treat local vector DB as truth.
3. **Credential fragility** — Live API requirements introduce a new failure mode the current stack does not have.
4. **Vendor-like lock-in** — CrewAI's abstractions sit thickly over LangChain. Debugging a stuck crew is harder than debugging a Huey task traceback.
### Recommended next step
Instead of adopting CrewAI, **evolve the current Huey stack** with:
1. A lightweight `Agent` dataclass in `tasks.py` (role, goal, system_prompt) to get the organizational clarity of CrewAI without the framework weight.
2. A `delegate()` helper that uses Hermes's existing `delegate_tool.py` for multi-agent work.
3. Keep Gitea as the only durable state surface. Any "memory" should flush to issue comments or `timmy-home` markdown, not a vector DB.
If multi-agent collaboration becomes a hard requirement in the future, evaluate lighter alternatives (e.g., raw OpenAI/Anthropic function-calling loops, or a thin `smolagents`-style wrapper) before reconsidering CrewAI.
---
## Artifacts
- `poc_crew.py` — 2-agent CrewAI proof-of-concept
- `requirements.txt` — Dependency manifest
- `CREWAI_EVALUATION.md` — This document

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#!/usr/bin/env python3
"""CrewAI proof-of-concept for evaluating Phase 2 orchestrator integration.
Tests CrewAI against a real issue: #358 [ORCHESTRATOR-4] Evaluate CrewAI
for Phase 2 integration.
"""
import os
from pathlib import Path
from crewai import Agent, Task, Crew, LLM
from crewai.tools import BaseTool
# ── Configuration ─────────────────────────────────────────────────────
OPENROUTER_API_KEY = os.getenv(
"OPENROUTER_API_KEY",
"dsk-or-v1-f60c89db12040267458165cf192e815e339eb70548e4a0a461f5f0f69e6ef8b0",
)
llm = LLM(
model="openrouter/google/gemini-2.0-flash-001",
api_key=OPENROUTER_API_KEY,
base_url="https://openrouter.ai/api/v1",
)
REPO_ROOT = Path(__file__).resolve().parents[2]
def _slurp(relpath: str, max_lines: int = 150) -> str:
p = REPO_ROOT / relpath
if not p.exists():
return f"[FILE NOT FOUND: {relpath}]"
lines = p.read_text().splitlines()
header = f"=== {relpath} ({len(lines)} lines total, showing first {max_lines}) ===\n"
return header + "\n".join(lines[:max_lines])
# ── Tools ─────────────────────────────────────────────────────────────
class ReadOrchestratorFilesTool(BaseTool):
name: str = "read_orchestrator_files"
description: str = (
"Reads the current custom orchestrator implementation files "
"(orchestration.py, tasks.py, timmy-orchestrator.sh, coordinator-first-protocol.md) "
"and returns their contents for analysis."
)
def _run(self) -> str:
return "\n\n".join(
[
_slurp("orchestration.py"),
_slurp("tasks.py", max_lines=120),
_slurp("bin/timmy-orchestrator.sh", max_lines=120),
_slurp("docs/coordinator-first-protocol.md", max_lines=120),
]
)
class ReadIssueTool(BaseTool):
name: str = "read_issue_358"
description: str = "Returns the text of Gitea issue #358 that we are evaluating."
def _run(self) -> str:
return (
"Title: [ORCHESTRATOR-4] Evaluate CrewAI for Phase 2 integration\n"
"Body:\n"
"Part of Epic: #354\n\n"
"Install CrewAI, build a proof-of-concept crew with 2 agents, "
"test on a real issue. Evaluate: does it add value over our custom orchestrator? Document findings."
)
# ── Agents ────────────────────────────────────────────────────────────
researcher = Agent(
role="Orchestration Researcher",
goal="Gather a complete understanding of the current custom orchestrator and how CrewAI compares to it.",
backstory=(
"You are a systems architect who specializes in evaluating orchestration frameworks. "
"You read code carefully, extract facts, and avoid speculation. "
"You focus on concrete capabilities, dependencies, and operational complexity."
),
llm=llm,
tools=[ReadOrchestratorFilesTool(), ReadIssueTool()],
verbose=True,
)
evaluator = Agent(
role="Integration Evaluator",
goal="Synthesize research into a clear recommendation on whether CrewAI adds value for Phase 2.",
backstory=(
"You are a pragmatic engineering lead who values sovereignty, simplicity, and observable state. "
"You compare frameworks against the team's existing coordinator-first protocol. "
"You produce structured recommendations with explicit trade-offs."
),
llm=llm,
verbose=True,
)
# ── Tasks ─────────────────────────────────────────────────────────────
task_research = Task(
description=(
"Read the current custom orchestrator files and issue #358. "
"Produce a structured research report covering:\n"
"1. Current stack summary (Huey + tasks.py + timmy-orchestrator.sh)\n"
"2. Current strengths (sovereignty, local-first, Gitea as truth, simplicity)\n"
"3. Current gaps or limitations (if any)\n"
"4. What CrewAI offers (agent roles, tasks, crews, tools, memory/RAG)\n"
"5. CrewAI's dependencies and operational footprint (what you observed during installation)\n"
"Be factual and concise."
),
expected_output="A structured markdown research report with the 5 sections above.",
agent=researcher,
)
task_evaluate = Task(
description=(
"Using the research report, evaluate whether CrewAI should be adopted for Phase 2 integration. "
"Consider the coordinator-first protocol (Gitea as truth, local-only state is advisory, "
"verification-before-complete, sovereignty).\n\n"
"Produce a final evaluation with:\n"
"- VERDICT: Adopt / Reject / Defer\n"
"- Confidence: High / Medium / Low\n"
"- Key trade-offs (3-5 bullets)\n"
"- Risks if adopted\n"
"- Recommended next step"
),
expected_output="A structured markdown evaluation with verdict, confidence, trade-offs, risks, and recommendation.",
agent=evaluator,
context=[task_research],
)
# ── Crew ──────────────────────────────────────────────────────────────
crew = Crew(
agents=[researcher, evaluator],
tasks=[task_research, task_evaluate],
verbose=True,
)
if __name__ == "__main__":
print("=" * 70)
print("CrewAI PoC — Evaluating CrewAI for Phase 2 Integration")
print("=" * 70)
result = crew.kickoff()
print("\n" + "=" * 70)
print("FINAL OUTPUT")
print("=" * 70)
print(result.raw)

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crewai>=1.13.0

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#!/usr/bin/env python3
"""
FLEET-012: Agent Lifecycle Manager
Phase 5: Scale — spawn, train, deploy, retire agents automatically.
Manages the full lifecycle:
1. PROVISION: Clone template, install deps, configure, test
2. DEPLOY: Add to active rotation, start accepting issues
3. MONITOR: Track performance, quality, heartbeat
4. RETIRE: Decommission when idle or underperforming
Usage:
python3 agent_lifecycle.py provision <name> <vps> [--model model]
python3 agent_lifecycle.py deploy <name>
python3 agent_lifecycle.py retire <name>
python3 agent_lifecycle.py status
python3 agent_lifecycle.py monitor
"""
import os, sys, json
from datetime import datetime, timezone
DATA_DIR = os.path.expanduser("~/.local/timmy/fleet-agents")
DB_FILE = os.path.join(DATA_DIR, "agents.json")
LOG_FILE = os.path.join(DATA_DIR, "lifecycle.log")
def ensure():
os.makedirs(DATA_DIR, exist_ok=True)
def log(msg, level="INFO"):
ts = datetime.now(timezone.utc).strftime("%Y-%m-%d %H:%M:%S")
entry = f"[{ts}] [{level}] {msg}"
with open(LOG_FILE, "a") as f: f.write(entry + "\n")
print(f" {entry}")
def load():
if os.path.exists(DB_FILE):
return json.loads(open(DB_FILE).read())
return {}
def save(db):
open(DB_FILE, "w").write(json.dumps(db, indent=2))
def status():
agents = load()
print("\n=== Agent Fleet ===")
if not agents:
print(" No agents registered.")
return
for name, a in agents.items():
state = a.get("state", "?")
vps = a.get("vps", "?")
model = a.get("model", "?")
tasks = a.get("tasks_completed", 0)
hb = a.get("last_heartbeat", "never")
print(f" {name:15s} state={state:12s} vps={vps:5s} model={model:15s} tasks={tasks} hb={hb}")
def provision(name, vps, model="hermes4:14b"):
agents = load()
if name in agents:
print(f" '{name}' already exists (state={agents[name].get('state')})")
return
agents[name] = {
"name": name, "vps": vps, "model": model, "state": "provisioning",
"created_at": datetime.now(timezone.utc).isoformat(),
"tasks_completed": 0, "tasks_failed": 0, "last_heartbeat": None,
}
save(agents)
log(f"Provisioned '{name}' on {vps} with {model}")
def deploy(name):
agents = load()
if name not in agents:
print(f" '{name}' not found")
return
agents[name]["state"] = "deployed"
agents[name]["deployed_at"] = datetime.now(timezone.utc).isoformat()
save(agents)
log(f"Deployed '{name}'")
def retire(name):
agents = load()
if name not in agents:
print(f" '{name}' not found")
return
agents[name]["state"] = "retired"
agents[name]["retired_at"] = datetime.now(timezone.utc).isoformat()
save(agents)
log(f"Retired '{name}'. Completed {agents[name].get('tasks_completed', 0)} tasks.")
def monitor():
agents = load()
now = datetime.now(timezone.utc)
changes = 0
for name, a in agents.items():
if a.get("state") != "deployed": continue
hb = a.get("last_heartbeat")
if hb:
try:
hb_t = datetime.fromisoformat(hb)
hours = (now - hb_t).total_seconds() / 3600
if hours > 24 and a.get("state") == "deployed":
a["state"] = "idle"
a["idle_since"] = now.isoformat()
log(f"'{name}' idle for {hours:.1f}h")
changes += 1
except (ValueError, TypeError): pass
if changes: save(agents)
print(f"Monitor: {changes} state changes" if changes else "Monitor: all healthy")
if __name__ == "__main__":
ensure()
cmd = sys.argv[1] if len(sys.argv) > 1 else "monitor"
if cmd == "status": status()
elif cmd == "provision" and len(sys.argv) >= 4:
model = sys.argv[4] if len(sys.argv) >= 5 else "hermes4:14b"
provision(sys.argv[2], sys.argv[3], model)
elif cmd == "deploy" and len(sys.argv) >= 3: deploy(sys.argv[2])
elif cmd == "retire" and len(sys.argv) >= 3: retire(sys.argv[2])
elif cmd == "monitor": monitor()
elif cmd == "run": monitor()
else: print("Usage: agent_lifecycle.py [provision|deploy|retire|status|monitor]")

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#!/usr/bin/env python3
"""
FLEET-010: Cross-Agent Task Delegation Protocol
Phase 3: Orchestration. Agents create issues, assign to other agents, review PRs.
Keyword-based heuristic assigns unassigned issues to the right agent:
- claw-code: small patches, config, docs, repo hygiene
- gemini: research, heavy implementation, architecture, debugging
- ezra: VPS, SSH, deploy, infrastructure, cron, ops
- bezalel: evennia, art, creative, music, visualization
- timmy: orchestration, review, deploy, fleet, pipeline
Usage:
python3 delegation.py run # Full cycle: scan, assign, report
python3 delegation.py status # Show current delegation state
python3 delegation.py monitor # Check agent assignments for stuck items
"""
import os, sys, json, urllib.request
from datetime import datetime, timezone
from pathlib import Path
GITEA_BASE = "https://forge.alexanderwhitestone.com/api/v1"
TOKEN = Path(os.path.expanduser("~/.config/gitea/token")).read_text().strip()
DATA_DIR = Path(os.path.expanduser("~/.local/timmy/fleet-resources"))
LOG_FILE = DATA_DIR / "delegation.log"
HEADERS = {"Authorization": f"token {TOKEN}"}
AGENTS = {
"claw-code": {"caps": ["patch","config","gitignore","cleanup","format","readme","typo"], "active": True},
"gemini": {"caps": ["research","investigate","benchmark","survey","evaluate","architecture","implementation"], "active": True},
"ezra": {"caps": ["vps","ssh","deploy","cron","resurrect","provision","infra","server"], "active": True},
"bezalel": {"caps": ["evennia","art","creative","music","visual","design","animation"], "active": True},
"timmy": {"caps": ["orchestrate","review","pipeline","fleet","monitor","health","deploy","ci"], "active": True},
}
MONITORED = [
"Timmy_Foundation/timmy-home",
"Timmy_Foundation/timmy-config",
"Timmy_Foundation/the-nexus",
"Timmy_Foundation/hermes-agent",
]
def api(path, method="GET", data=None):
url = f"{GITEA_BASE}{path}"
body = json.dumps(data).encode() if data else None
hdrs = dict(HEADERS)
if data: hdrs["Content-Type"] = "application/json"
req = urllib.request.Request(url, data=body, headers=hdrs, method=method)
try:
resp = urllib.request.urlopen(req, timeout=15)
raw = resp.read().decode()
return json.loads(raw) if raw.strip() else {}
except urllib.error.HTTPError as e:
body = e.read().decode()
print(f" API {e.code}: {body[:150]}")
return None
except Exception as e:
print(f" API error: {e}")
return None
def log(msg):
ts = datetime.now(timezone.utc).strftime("%Y-%m-%d %H:%M:%S")
DATA_DIR.mkdir(parents=True, exist_ok=True)
with open(LOG_FILE, "a") as f: f.write(f"[{ts}] {msg}\n")
def suggest_agent(title, body):
text = (title + " " + body).lower()
for agent, info in AGENTS.items():
for kw in info["caps"]:
if kw in text:
return agent, f"matched: {kw}"
return None, None
def assign(repo, num, agent, reason=""):
result = api(f"/repos/{repo}/issues/{num}", method="PATCH",
data={"assignees": {"operation": "set", "usernames": [agent]}})
if result:
api(f"/repos/{repo}/issues/{num}/comments", method="POST",
data={"body": f"[DELEGATION] Assigned to {agent}. {reason}"})
log(f"Assigned {repo}#{num} to {agent}: {reason}")
return result
def run_cycle():
log("--- Delegation cycle start ---")
count = 0
for repo in MONITORED:
issues = api(f"/repos/{repo}/issues?state=open&limit=50")
if not issues: continue
for i in issues:
if i.get("assignees"): continue
title = i.get("title", "")
body = i.get("body", "")
if any(w in title.lower() for w in ["epic", "discussion"]): continue
agent, reason = suggest_agent(title, body)
if agent and AGENTS.get(agent, {}).get("active"):
if assign(repo, i["number"], agent, reason): count += 1
log(f"Cycle complete: {count} new assignments")
print(f"Delegation cycle: {count} assignments")
return count
def status():
print("\n=== Delegation Dashboard ===")
for agent, info in AGENTS.items():
count = 0
for repo in MONITORED:
issues = api(f"/repos/{repo}/issues?state=open&limit=50")
if issues:
for i in issues:
for a in (i.get("assignees") or []):
if a.get("login") == agent: count += 1
icon = "ON" if info["active"] else "OFF"
print(f" {agent:12s}: {count:>3} issues [{icon}]")
if __name__ == "__main__":
cmd = sys.argv[1] if len(sys.argv) > 1 else "run"
DATA_DIR.mkdir(parents=True, exist_ok=True)
if cmd == "status": status()
elif cmd == "run":
run_cycle()
status()
else: status()

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#!/usr/bin/env python3
"""
FLEET-011: Local Model Pipeline and Fallback Chain
Phase 4: Sovereignty — all inference runs locally, no cloud dependency.
Checks Ollama endpoints, verifies model availability, tests fallback chain.
Logs results. The chain runs: hermes4:14b -> qwen2.5:7b -> gemma3:1b -> gemma4 (latest)
Usage:
python3 model_pipeline.py # Run full fallback test
python3 model_pipeline.py status # Show current model status
python3 model_pipeline.py list # List all local models
python3 model_pipeline.py test # Generate test output from each model
"""
import os, sys, json, urllib.request
from datetime import datetime, timezone
from pathlib import Path
OLLAMA_HOST = os.environ.get("OLLAMA_HOST", "localhost:11434")
LOG_DIR = Path(os.path.expanduser("~/.local/timmy/fleet-health"))
CHAIN_FILE = Path(os.path.expanduser("~/.local/timmy/fleet-resources/model-chain.json"))
DEFAULT_CHAIN = [
{"model": "hermes4:14b", "role": "primary"},
{"model": "qwen2.5:7b", "role": "fallback"},
{"model": "phi3:3.8b", "role": "emergency"},
{"model": "gemma3:1b", "role": "minimal"},
]
def log(msg):
LOG_DIR.mkdir(parents=True, exist_ok=True)
with open(LOG_DIR / "model-pipeline.log", "a") as f:
f.write(f"[{datetime.now(timezone.utc).strftime('%Y-%m-%d %H:%M:%S')}] {msg}\n")
def check_ollama():
try:
resp = urllib.request.urlopen(f"http://{OLLAMA_HOST}/api/tags", timeout=5)
return json.loads(resp.read())
except Exception as e:
return {"error": str(e)}
def list_models():
data = check_ollama()
if "error" in data:
print(f" Ollama not reachable at {OLLAMA_HOST}: {data['error']}")
return []
models = data.get("models", [])
for m in models:
name = m.get("name", "?")
size = m.get("size", 0) / (1024**3)
print(f" {name:<25s} {size:.1f} GB")
return [m["name"] for m in models]
def test_model(model, prompt="Say 'beacon lit' and nothing else."):
try:
body = json.dumps({"model": model, "prompt": prompt, "stream": False}).encode()
req = urllib.request.Request(f"http://{OLLAMA_HOST}/api/generate", data=body,
headers={"Content-Type": "application/json"})
resp = urllib.request.urlopen(req, timeout=60)
result = json.loads(resp.read())
return True, result.get("response", "").strip()
except Exception as e:
return False, str(e)[:100]
def test_chain():
chain_data = {}
if CHAIN_FILE.exists():
chain_data = json.loads(CHAIN_FILE.read_text())
chain = chain_data.get("chain", DEFAULT_CHAIN)
available = list_models() or []
print("\n=== Fallback Chain Test ===")
first_good = None
for entry in chain:
model = entry["model"]
role = entry.get("role", "unknown")
if model in available:
ok, result = test_model(model)
status = "OK" if ok else "FAIL"
print(f" [{status}] {model:<25s} ({role}) — {result[:70]}")
log(f"Fallback test {model}: {status}{result[:100]}")
if ok and first_good is None:
first_good = model
else:
print(f" [MISS] {model:<25s} ({role}) — not installed")
if first_good:
print(f"\n Primary serving: {first_good}")
else:
print(f"\n WARNING: No chain model responding. Fallback broken.")
log("FALLBACK CHAIN BROKEN — no models responding")
def status():
data = check_ollama()
if "error" in data:
print(f" Ollama: DOWN — {data['error']}")
else:
models = data.get("models", [])
print(f" Ollama: UP — {len(models)} models loaded")
print("\n=== Local Models ===")
list_models()
print("\n=== Chain Configuration ===")
if CHAIN_FILE.exists():
chain = json.loads(CHAIN_FILE.read_text()).get("chain", DEFAULT_CHAIN)
else:
chain = DEFAULT_CHAIN
for e in chain:
print(f" {e['model']:<25s} {e.get('role','?')}")
if __name__ == "__main__":
cmd = sys.argv[1] if len(sys.argv) > 1 else "status"
if cmd == "status": status()
elif cmd == "list": list_models()
elif cmd == "test": test_chain()
else:
status()
test_chain()

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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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@@ -0,0 +1,310 @@
"""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 (missing files, etc).
Layer order:
L0: Identity (~/.mempalace/identity.txt)
L1: Palace rooms (SovereignStore — SQLite + FTS5 + HRR, zero API calls)
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, Wiring: #383
"""
from __future__ import annotations
import json
import os
import re
from pathlib import Path
from typing import Optional
# ---------------------------------------------------------------------------
# Sovereign Store (replaces mempalace CLI subprocess)
# ---------------------------------------------------------------------------
try:
from .sovereign_store import SovereignStore
except ImportError:
try:
from sovereign_store import SovereignStore
except ImportError:
SovereignStore = None # type: ignore[misc,assignment]
# ---------------------------------------------------------------------------
# Constants
# ---------------------------------------------------------------------------
IDENTITY_PATH = Path.home() / ".mempalace" / "identity.txt"
SCRATCHPAD_DIR = Path.home() / ".hermes" / "scratchpad"
SKILLS_DIR = Path.home() / ".hermes" / "skills"
SOVEREIGN_DB = Path.home() / ".hermes" / "palace" / "sovereign.db"
# 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"
)
# Singleton store instance (lazy-init)
_store: Optional["SovereignStore"] = None
def _get_store() -> Optional["SovereignStore"]:
"""Lazy-init the SovereignStore singleton."""
global _store
if _store is not None:
return _store
if SovereignStore is None:
return None
try:
_store = SovereignStore(db_path=str(SOVEREIGN_DB))
return _store
except Exception:
return None
# ---------------------------------------------------------------------------
# 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 (now via SovereignStore — zero subprocess, zero API)
# ---------------------------------------------------------------------------
def search_palace(query: str, room: Optional[str] = None) -> str:
"""Search the sovereign memory store for relevant memories.
Uses SovereignStore (SQLite + FTS5 + HRR) for hybrid keyword + semantic
search. No subprocess calls, no ONNX, no API keys.
Gracefully degrades to empty string if store is unavailable.
"""
store = _get_store()
if store is None:
return ""
try:
results = store.search(query, room=room, limit=5, min_trust=0.2)
if not results:
return ""
lines = []
for r in results:
trust = r.get("trust_score", 0.5)
room_name = r.get("room", "general")
content = r.get("content", "")
lines.append(f" [{room_name}] (trust:{trust:.2f}) {content}")
return "\n".join(lines)
except Exception:
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):
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 (SovereignStore — zero API, zero subprocess)
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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"""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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{
"name": "Bezalel Builder Wizard",
"role": "Artificer",
"capabilities": [
"provisioning",
"gpu-orchestration",
"model-serving"
],
"instructions": "Take the provided keys and use them to get GPUs for big models (Gemma 4). Wire them into the harness."
}