Compare commits
2 Commits
claude/iss
...
claude/iss
| Author | SHA1 | Date | |
|---|---|---|---|
|
9fa0a59761 | ||
| 35be02ad15 |
13
.github/CODEOWNERS
vendored
Normal file
13
.github/CODEOWNERS
vendored
Normal file
@@ -0,0 +1,13 @@
|
||||
# Default owners for all files
|
||||
* @Timmy
|
||||
|
||||
# Critical paths require explicit review
|
||||
/gateway/ @Timmy
|
||||
/tools/ @Timmy
|
||||
/agent/ @Timmy
|
||||
/config/ @Timmy
|
||||
/scripts/ @Timmy
|
||||
/.github/workflows/ @Timmy
|
||||
/pyproject.toml @Timmy
|
||||
/requirements.txt @Timmy
|
||||
/Dockerfile @Timmy
|
||||
99
.github/ISSUE_TEMPLATE/security_pr_checklist.yml
vendored
Normal file
99
.github/ISSUE_TEMPLATE/security_pr_checklist.yml
vendored
Normal file
@@ -0,0 +1,99 @@
|
||||
name: "🔒 Security PR Checklist"
|
||||
description: "Use this when your PR touches authentication, file I/O, external API calls, or other sensitive paths."
|
||||
title: "[Security Review]: "
|
||||
labels: ["security", "needs-review"]
|
||||
body:
|
||||
- type: markdown
|
||||
attributes:
|
||||
value: |
|
||||
## Security Pre-Merge Review
|
||||
Complete this checklist before requesting review on PRs that touch **authentication, file I/O, external API calls, or secrets handling**.
|
||||
|
||||
- type: input
|
||||
id: pr-link
|
||||
attributes:
|
||||
label: Pull Request
|
||||
description: Link to the PR being reviewed
|
||||
placeholder: "https://forge.alexanderwhitestone.com/Timmy_Foundation/hermes-agent/pulls/XXX"
|
||||
validations:
|
||||
required: true
|
||||
|
||||
- type: dropdown
|
||||
id: change-type
|
||||
attributes:
|
||||
label: Change Category
|
||||
description: What kind of sensitive change does this PR make?
|
||||
multiple: true
|
||||
options:
|
||||
- Authentication / Authorization
|
||||
- File I/O (read/write/delete)
|
||||
- External API calls (outbound HTTP/network)
|
||||
- Secret / credential handling
|
||||
- Command execution (subprocess/shell)
|
||||
- Dependency addition or update
|
||||
- Configuration changes
|
||||
- CI/CD pipeline changes
|
||||
validations:
|
||||
required: true
|
||||
|
||||
- type: checkboxes
|
||||
id: secrets-checklist
|
||||
attributes:
|
||||
label: Secrets & Credentials
|
||||
options:
|
||||
- label: No secrets, API keys, or credentials are hardcoded
|
||||
required: true
|
||||
- label: All sensitive values are loaded from environment variables or a secrets manager
|
||||
required: true
|
||||
- label: Test fixtures use fake/placeholder values, not real credentials
|
||||
required: true
|
||||
|
||||
- type: checkboxes
|
||||
id: input-validation-checklist
|
||||
attributes:
|
||||
label: Input Validation
|
||||
options:
|
||||
- label: All external input (user, API, file) is validated before use
|
||||
required: true
|
||||
- label: File paths are validated against path traversal (`../`, null bytes, absolute paths)
|
||||
- label: URLs are validated for SSRF (blocked private/metadata IPs)
|
||||
- label: Shell commands do not use `shell=True` with user-controlled input
|
||||
|
||||
- type: checkboxes
|
||||
id: auth-checklist
|
||||
attributes:
|
||||
label: Authentication & Authorization (if applicable)
|
||||
options:
|
||||
- label: Authentication tokens are not logged or exposed in error messages
|
||||
- label: Authorization checks happen server-side, not just client-side
|
||||
- label: Session tokens are properly scoped and have expiry
|
||||
|
||||
- type: checkboxes
|
||||
id: supply-chain-checklist
|
||||
attributes:
|
||||
label: Supply Chain
|
||||
options:
|
||||
- label: New dependencies are pinned to a specific version range
|
||||
- label: Dependencies come from trusted sources (PyPI, npm, official repos)
|
||||
- label: No `.pth` files or install hooks that execute arbitrary code
|
||||
- label: "`pip-audit` passes (no known CVEs in added dependencies)"
|
||||
|
||||
- type: textarea
|
||||
id: threat-model
|
||||
attributes:
|
||||
label: Threat Model Notes
|
||||
description: |
|
||||
Briefly describe the attack surface this change introduces or modifies, and how it is mitigated.
|
||||
placeholder: |
|
||||
This PR adds a new outbound HTTP call to the OpenRouter API.
|
||||
Mitigation: URL is hardcoded (no user input), response is parsed with strict schema validation.
|
||||
|
||||
- type: textarea
|
||||
id: testing
|
||||
attributes:
|
||||
label: Security Testing Done
|
||||
description: What security testing did you perform?
|
||||
placeholder: |
|
||||
- Ran validate_security.py — all checks pass
|
||||
- Tested path traversal attempts manually
|
||||
- Verified no secrets in git diff
|
||||
82
.github/workflows/dependency-audit.yml
vendored
Normal file
82
.github/workflows/dependency-audit.yml
vendored
Normal file
@@ -0,0 +1,82 @@
|
||||
name: Dependency Audit
|
||||
|
||||
on:
|
||||
pull_request:
|
||||
branches: [main]
|
||||
paths:
|
||||
- 'requirements.txt'
|
||||
- 'pyproject.toml'
|
||||
- 'uv.lock'
|
||||
schedule:
|
||||
- cron: '0 8 * * 1' # Weekly on Monday
|
||||
workflow_dispatch:
|
||||
|
||||
permissions:
|
||||
pull-requests: write
|
||||
contents: read
|
||||
|
||||
jobs:
|
||||
audit:
|
||||
name: Audit Python dependencies
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- uses: astral-sh/setup-uv@v5
|
||||
- name: Set up Python
|
||||
run: uv python install 3.11
|
||||
- name: Install pip-audit
|
||||
run: uv pip install --system pip-audit
|
||||
- name: Run pip-audit
|
||||
id: audit
|
||||
run: |
|
||||
set -euo pipefail
|
||||
# Run pip-audit against the lock file/requirements
|
||||
if pip-audit --requirement requirements.txt -f json -o /tmp/audit-results.json 2>/tmp/audit-stderr.txt; then
|
||||
echo "found=false" >> "$GITHUB_OUTPUT"
|
||||
else
|
||||
echo "found=true" >> "$GITHUB_OUTPUT"
|
||||
# Check severity
|
||||
CRITICAL=$(python3 -c "
|
||||
import json, sys
|
||||
data = json.load(open('/tmp/audit-results.json'))
|
||||
vulns = data.get('dependencies', [])
|
||||
for d in vulns:
|
||||
for v in d.get('vulns', []):
|
||||
aliases = v.get('aliases', [])
|
||||
# Check for critical/high CVSS
|
||||
if any('CVSS' in str(a) for a in aliases):
|
||||
print('true')
|
||||
sys.exit(0)
|
||||
print('false')
|
||||
" 2>/dev/null || echo 'false')
|
||||
echo "critical=${CRITICAL}" >> "$GITHUB_OUTPUT"
|
||||
fi
|
||||
continue-on-error: true
|
||||
- name: Post results comment
|
||||
if: steps.audit.outputs.found == 'true' && github.event_name == 'pull_request'
|
||||
env:
|
||||
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
|
||||
run: |
|
||||
BODY="## ⚠️ Dependency Vulnerabilities Detected
|
||||
|
||||
\`pip-audit\` found vulnerable dependencies in this PR. Review and update before merging.
|
||||
|
||||
\`\`\`
|
||||
$(cat /tmp/audit-results.json | python3 -c "
|
||||
import json, sys
|
||||
data = json.load(sys.stdin)
|
||||
for dep in data.get('dependencies', []):
|
||||
for v in dep.get('vulns', []):
|
||||
print(f\" {dep['name']}=={dep['version']}: {v['id']} - {v.get('description', '')[:120]}\")
|
||||
" 2>/dev/null || cat /tmp/audit-stderr.txt)
|
||||
\`\`\`
|
||||
|
||||
---
|
||||
*Automated scan by [dependency-audit](/.github/workflows/dependency-audit.yml)*"
|
||||
gh pr comment "${{ github.event.pull_request.number }}" --body "$BODY"
|
||||
- name: Fail on vulnerabilities
|
||||
if: steps.audit.outputs.found == 'true'
|
||||
run: |
|
||||
echo "::error::Vulnerable dependencies detected. See PR comment for details."
|
||||
cat /tmp/audit-results.json | python3 -m json.tool || true
|
||||
exit 1
|
||||
114
.github/workflows/quarterly-security-audit.yml
vendored
Normal file
114
.github/workflows/quarterly-security-audit.yml
vendored
Normal file
@@ -0,0 +1,114 @@
|
||||
name: Quarterly Security Audit
|
||||
|
||||
on:
|
||||
schedule:
|
||||
# Run at 08:00 UTC on the first day of each quarter (Jan, Apr, Jul, Oct)
|
||||
- cron: '0 8 1 1,4,7,10 *'
|
||||
workflow_dispatch:
|
||||
inputs:
|
||||
reason:
|
||||
description: 'Reason for manual trigger'
|
||||
required: false
|
||||
default: 'Manual quarterly audit'
|
||||
|
||||
permissions:
|
||||
issues: write
|
||||
contents: read
|
||||
|
||||
jobs:
|
||||
create-audit-issue:
|
||||
name: Create quarterly security audit issue
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
|
||||
- name: Get quarter info
|
||||
id: quarter
|
||||
run: |
|
||||
MONTH=$(date +%-m)
|
||||
YEAR=$(date +%Y)
|
||||
QUARTER=$(( (MONTH - 1) / 3 + 1 ))
|
||||
echo "quarter=Q${QUARTER}-${YEAR}" >> "$GITHUB_OUTPUT"
|
||||
echo "year=${YEAR}" >> "$GITHUB_OUTPUT"
|
||||
echo "q=${QUARTER}" >> "$GITHUB_OUTPUT"
|
||||
|
||||
- name: Create audit issue
|
||||
env:
|
||||
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
|
||||
run: |
|
||||
QUARTER="${{ steps.quarter.outputs.quarter }}"
|
||||
|
||||
gh issue create \
|
||||
--title "[$QUARTER] Quarterly Security Audit" \
|
||||
--label "security,audit" \
|
||||
--body "$(cat <<'BODY'
|
||||
## Quarterly Security Audit — ${{ steps.quarter.outputs.quarter }}
|
||||
|
||||
This is the scheduled quarterly security audit for the hermes-agent project. Complete each section and close this issue when the audit is done.
|
||||
|
||||
**Audit Period:** ${{ steps.quarter.outputs.quarter }}
|
||||
**Due:** End of quarter
|
||||
**Owner:** Assign to a maintainer
|
||||
|
||||
---
|
||||
|
||||
## 1. Open Issues & PRs Audit
|
||||
|
||||
Review all open issues and PRs for security-relevant content. Tag any that touch attack surfaces with the `security` label.
|
||||
|
||||
- [ ] Review open issues older than 30 days for unaddressed security concerns
|
||||
- [ ] Tag security-relevant open PRs with `needs-security-review`
|
||||
- [ ] Check for any issues referencing CVEs or known vulnerabilities
|
||||
- [ ] Review recently closed security issues — are fixes deployed?
|
||||
|
||||
## 2. Dependency Audit
|
||||
|
||||
- [ ] Run `pip-audit` against current `requirements.txt` / `pyproject.toml`
|
||||
- [ ] Check `uv.lock` for any pinned versions with known CVEs
|
||||
- [ ] Review any `git+` dependencies for recent changes or compromise signals
|
||||
- [ ] Update vulnerable dependencies and open PRs for each
|
||||
|
||||
## 3. Critical Path Review
|
||||
|
||||
Review recent changes to attack-surface paths:
|
||||
|
||||
- [ ] `gateway/` — authentication, message routing, platform adapters
|
||||
- [ ] `tools/` — file I/O, command execution, web access
|
||||
- [ ] `agent/` — prompt handling, context management
|
||||
- [ ] `config/` — secrets loading, configuration parsing
|
||||
- [ ] `.github/workflows/` — CI/CD integrity
|
||||
|
||||
Run: `git log --since="3 months ago" --name-only -- gateway/ tools/ agent/ config/ .github/workflows/`
|
||||
|
||||
## 4. Secret Scan
|
||||
|
||||
- [ ] Run secret scanner on the full codebase (not just diffs)
|
||||
- [ ] Verify no credentials are present in git history
|
||||
- [ ] Confirm all API keys/tokens in use are rotated on a regular schedule
|
||||
|
||||
## 5. Access & Permissions Review
|
||||
|
||||
- [ ] Review who has write access to the main branch
|
||||
- [ ] Confirm branch protection rules are still in place (require PR + review)
|
||||
- [ ] Verify CI/CD secrets are scoped correctly (not over-permissioned)
|
||||
- [ ] Review CODEOWNERS file for accuracy
|
||||
|
||||
## 6. Vulnerability Triage
|
||||
|
||||
List any new vulnerabilities found this quarter:
|
||||
|
||||
| ID | Component | Severity | Status | Owner |
|
||||
|----|-----------|----------|--------|-------|
|
||||
| | | | | |
|
||||
|
||||
## 7. Action Items
|
||||
|
||||
| Action | Owner | Due Date | Status |
|
||||
|--------|-------|----------|--------|
|
||||
| | | | |
|
||||
|
||||
---
|
||||
|
||||
*Auto-generated by [quarterly-security-audit](/.github/workflows/quarterly-security-audit.yml). Close this issue when the audit is complete.*
|
||||
BODY
|
||||
)"
|
||||
136
.github/workflows/secret-scan.yml
vendored
Normal file
136
.github/workflows/secret-scan.yml
vendored
Normal file
@@ -0,0 +1,136 @@
|
||||
name: Secret Scan
|
||||
|
||||
on:
|
||||
pull_request:
|
||||
types: [opened, synchronize, reopened]
|
||||
|
||||
permissions:
|
||||
pull-requests: write
|
||||
contents: read
|
||||
|
||||
jobs:
|
||||
scan:
|
||||
name: Scan for secrets
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
fetch-depth: 0
|
||||
|
||||
- name: Fetch base branch
|
||||
run: git fetch origin ${{ github.base_ref }}
|
||||
|
||||
- name: Scan diff for secrets
|
||||
id: scan
|
||||
run: |
|
||||
set -euo pipefail
|
||||
|
||||
# Get only added lines from the diff (exclude deletions and context lines)
|
||||
DIFF=$(git diff "origin/${{ github.base_ref }}"...HEAD -- \
|
||||
':!*.lock' ':!uv.lock' ':!package-lock.json' ':!yarn.lock' \
|
||||
| grep '^+' | grep -v '^+++' || true)
|
||||
|
||||
FINDINGS=""
|
||||
CRITICAL=false
|
||||
|
||||
check() {
|
||||
local label="$1"
|
||||
local pattern="$2"
|
||||
local critical="${3:-false}"
|
||||
local matches
|
||||
matches=$(echo "$DIFF" | grep -oP "$pattern" || true)
|
||||
if [ -n "$matches" ]; then
|
||||
FINDINGS="${FINDINGS}\n- **${label}**: pattern matched"
|
||||
if [ "$critical" = "true" ]; then
|
||||
CRITICAL=true
|
||||
fi
|
||||
fi
|
||||
}
|
||||
|
||||
# AWS keys — critical
|
||||
check "AWS Access Key" 'AKIA[0-9A-Z]{16}' true
|
||||
|
||||
# Private key headers — critical
|
||||
check "Private Key Header" '-----BEGIN (RSA|EC|DSA|OPENSSH|PGP) PRIVATE KEY' true
|
||||
|
||||
# OpenAI / Anthropic style keys
|
||||
check "OpenAI-style API key (sk-)" 'sk-[a-zA-Z0-9]{20,}' false
|
||||
|
||||
# GitHub tokens
|
||||
check "GitHub personal access token (ghp_)" 'ghp_[a-zA-Z0-9]{36}' true
|
||||
check "GitHub fine-grained PAT (github_pat_)" 'github_pat_[a-zA-Z0-9_]{1,}' true
|
||||
|
||||
# Slack tokens
|
||||
check "Slack bot token (xoxb-)" 'xoxb-[0-9A-Za-z\-]{10,}' true
|
||||
check "Slack user token (xoxp-)" 'xoxp-[0-9A-Za-z\-]{10,}' true
|
||||
|
||||
# Generic assignment patterns — exclude obvious placeholders
|
||||
GENERIC=$(echo "$DIFF" | grep -iP '(api_key|apikey|api-key|secret_key|access_token|auth_token)\s*[=:]\s*['"'"'"][^'"'"'"]{20,}['"'"'"]' \
|
||||
| grep -ivP '(fake|mock|test|placeholder|example|dummy|your[_-]|xxx|<|>|\{\{)' || true)
|
||||
if [ -n "$GENERIC" ]; then
|
||||
FINDINGS="${FINDINGS}\n- **Generic credential assignment**: possible hardcoded secret"
|
||||
fi
|
||||
|
||||
# .env additions with long values
|
||||
ENV_DIFF=$(git diff "origin/${{ github.base_ref }}"...HEAD -- '*.env' '**/.env' '.env*' \
|
||||
| grep '^+' | grep -v '^+++' || true)
|
||||
ENV_MATCHES=$(echo "$ENV_DIFF" | grep -P '^[A-Z_]+=.{16,}' \
|
||||
| grep -ivP '(fake|mock|test|placeholder|example|dummy|your[_-]|xxx)' || true)
|
||||
if [ -n "$ENV_MATCHES" ]; then
|
||||
FINDINGS="${FINDINGS}\n- **.env file**: lines with potentially real secret values detected"
|
||||
fi
|
||||
|
||||
# Write outputs
|
||||
if [ -n "$FINDINGS" ]; then
|
||||
echo "found=true" >> "$GITHUB_OUTPUT"
|
||||
else
|
||||
echo "found=false" >> "$GITHUB_OUTPUT"
|
||||
fi
|
||||
|
||||
if [ "$CRITICAL" = "true" ]; then
|
||||
echo "critical=true" >> "$GITHUB_OUTPUT"
|
||||
else
|
||||
echo "critical=false" >> "$GITHUB_OUTPUT"
|
||||
fi
|
||||
|
||||
# Store findings in a file to use in comment step
|
||||
printf "%b" "$FINDINGS" > /tmp/secret-findings.txt
|
||||
|
||||
- name: Post PR comment with findings
|
||||
if: steps.scan.outputs.found == 'true' && github.event_name == 'pull_request'
|
||||
env:
|
||||
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
|
||||
run: |
|
||||
FINDINGS=$(cat /tmp/secret-findings.txt)
|
||||
SEVERITY="warning"
|
||||
if [ "${{ steps.scan.outputs.critical }}" = "true" ]; then
|
||||
SEVERITY="CRITICAL"
|
||||
fi
|
||||
|
||||
BODY="## Secret Scan — ${SEVERITY} findings
|
||||
|
||||
The automated secret scanner detected potential secrets in the diff for this PR.
|
||||
|
||||
### Findings
|
||||
${FINDINGS}
|
||||
|
||||
### What to do
|
||||
1. Remove any real credentials from the diff immediately.
|
||||
2. If the match is a false positive (test fixture, placeholder), add a comment explaining why or rename the variable to include \`fake\`, \`mock\`, or \`test\`.
|
||||
3. Rotate any exposed credentials regardless of whether this PR is merged.
|
||||
|
||||
---
|
||||
*Automated scan by [secret-scan](/.github/workflows/secret-scan.yml)*"
|
||||
|
||||
gh pr comment "${{ github.event.pull_request.number }}" --body "$BODY"
|
||||
|
||||
- name: Fail on critical secrets
|
||||
if: steps.scan.outputs.critical == 'true'
|
||||
run: |
|
||||
echo "::error::Critical secrets detected in diff (private keys, AWS keys, or GitHub tokens). Remove them before merging."
|
||||
exit 1
|
||||
|
||||
- name: Warn on non-critical findings
|
||||
if: steps.scan.outputs.found == 'true' && steps.scan.outputs.critical == 'false'
|
||||
run: |
|
||||
echo "::warning::Potential secrets detected in diff. Review the PR comment for details."
|
||||
25
.pre-commit-config.yaml
Normal file
25
.pre-commit-config.yaml
Normal file
@@ -0,0 +1,25 @@
|
||||
repos:
|
||||
# Secret detection
|
||||
- repo: https://github.com/gitleaks/gitleaks
|
||||
rev: v8.21.2
|
||||
hooks:
|
||||
- id: gitleaks
|
||||
name: Detect secrets with gitleaks
|
||||
description: Detect hardcoded secrets, API keys, and credentials
|
||||
|
||||
# Basic security hygiene
|
||||
- repo: https://github.com/pre-commit/pre-commit-hooks
|
||||
rev: v5.0.0
|
||||
hooks:
|
||||
- id: check-added-large-files
|
||||
args: ['--maxkb=500']
|
||||
- id: detect-private-key
|
||||
name: Detect private keys
|
||||
- id: check-merge-conflict
|
||||
- id: check-yaml
|
||||
- id: check-toml
|
||||
- id: end-of-file-fixer
|
||||
- id: trailing-whitespace
|
||||
args: ['--markdown-linebreak-ext=md']
|
||||
- id: no-commit-to-branch
|
||||
args: ['--branch', 'main']
|
||||
@@ -1,678 +0,0 @@
|
||||
# Jupyter Notebooks as Core LLM Execution Layer — Deep Research Report
|
||||
|
||||
**Issue:** #155
|
||||
**Date:** 2026-04-06
|
||||
**Status:** Research / Spike
|
||||
**Prior Art:** Timmy's initial spike (llm_execution_spike.ipynb, hamelnb bridge, JupyterLab on forge VPS)
|
||||
|
||||
---
|
||||
|
||||
## Executive Summary
|
||||
|
||||
This report deepens the research from issue #155 into three areas requested by Rockachopa:
|
||||
1. The **full Jupyter product suite** — JupyterHub vs JupyterLab vs Notebook
|
||||
2. **Papermill** — the production-grade notebook execution engine already used in real data pipelines
|
||||
3. The **"PR model for notebooks"** — how agents can propose, diff, review, and merge changes to `.ipynb` files similarly to code PRs
|
||||
|
||||
The conclusion: an elegant, production-grade agent→notebook pipeline already exists as open-source tooling. We don't need to invent much — we need to compose what's there.
|
||||
|
||||
---
|
||||
|
||||
## 1. The Jupyter Product Suite
|
||||
|
||||
The Jupyter ecosystem has three distinct layers that are often conflated. Understanding the distinction is critical for architectural decisions.
|
||||
|
||||
### 1.1 Jupyter Notebook (Classic)
|
||||
|
||||
The original single-user interface. One browser tab = one `.ipynb` file. Version 6 is in maintenance-only mode. Version 7 was rebuilt on JupyterLab components and is functionally equivalent. For headless agent use, the UI is irrelevant — what matters is the `.ipynb` file format and the kernel execution model underneath.
|
||||
|
||||
### 1.2 JupyterLab
|
||||
|
||||
The current canonical Jupyter interface for human users: full IDE, multi-pane, terminal, extension manager, built-in diff viewer, and `jupyterlab-git` for Git workflows from the UI. JupyterLab is the recommended target for agent-collaborative workflows because:
|
||||
|
||||
- It exposes the same REST API as classic Jupyter (kernel sessions, execute, contents)
|
||||
- Extensions like `jupyterlab-git` let a human co-reviewer inspect changes alongside the agent
|
||||
- The `hamelnb` bridge Timmy already validated works against a JupyterLab server
|
||||
|
||||
**For agents:** JupyterLab is the platform to run on. The agent doesn't interact with the UI — it uses the Jupyter REST API or Papermill on top of it.
|
||||
|
||||
### 1.3 JupyterHub — The Multi-User Orchestration Layer
|
||||
|
||||
JupyterHub is not a UI. It is a **multi-user server** that spawns, manages, and proxies individual single-user Jupyter servers. This is the production infrastructure layer.
|
||||
|
||||
```
|
||||
[Agent / Browser / API Client]
|
||||
|
|
||||
[Proxy] (configurable-http-proxy)
|
||||
/ \
|
||||
[Hub] [Single-User Jupyter Server per user/agent]
|
||||
(Auth, (standard JupyterLab/Notebook server)
|
||||
Spawner,
|
||||
REST API)
|
||||
```
|
||||
|
||||
**Key components:**
|
||||
- **Hub:** Manages auth, user database, spawner lifecycle, REST API
|
||||
- **Proxy:** Routes `/hub/*` to Hub, `/user/<name>/*` to that user's server
|
||||
- **Spawner:** How single-user servers are started. Default = local process. Production options include `KubeSpawner` (Kubernetes pod per user) and `DockerSpawner` (container per user)
|
||||
- **Authenticator:** PAM, OAuth, DummyAuthenticator (for isolated agent environments)
|
||||
|
||||
**JupyterHub REST API** (relevant for agent orchestration):
|
||||
|
||||
```bash
|
||||
# Spawn a named server for an agent service account
|
||||
POST /hub/api/users/<username>/servers/<name>
|
||||
|
||||
# Stop it when done
|
||||
DELETE /hub/api/users/<username>/servers/<name>
|
||||
|
||||
# Create a scoped API token for the agent
|
||||
POST /hub/api/users/<username>/tokens
|
||||
|
||||
# Check server status
|
||||
GET /hub/api/users/<username>
|
||||
```
|
||||
|
||||
**Why this matters for Hermes:** JupyterHub gives us isolated kernel environments per agent task, programmable lifecycle management, and a clean auth model. Instead of running one shared JupyterLab instance on the forge VPS, we could spawn ephemeral single-user servers per notebook execution run — each with its own kernel, clean state, and resource limits.
|
||||
|
||||
### 1.4 Jupyter Kernel Gateway — Minimal Headless Execution
|
||||
|
||||
If JupyterHub is too heavy, `jupyter-kernel-gateway` exposes just the kernel protocol over REST + WebSocket:
|
||||
|
||||
```bash
|
||||
pip install jupyter-kernel-gateway
|
||||
jupyter kernelgateway --KernelGatewayApp.api=kernel_gateway.jupyter_websocket
|
||||
|
||||
# Start kernel
|
||||
POST /api/kernels
|
||||
# Execute via WebSocket on Jupyter messaging protocol
|
||||
WS /api/kernels/<kernel_id>/channels
|
||||
# Stop kernel
|
||||
DELETE /api/kernels/<kernel_id>
|
||||
```
|
||||
|
||||
This is the lowest-level option: no notebook management, just raw kernel access. Suitable if we want to build our own execution layer from scratch.
|
||||
|
||||
---
|
||||
|
||||
## 2. Papermill — Production Notebook Execution
|
||||
|
||||
Papermill is the missing link between "notebook as experiment" and "notebook as repeatable pipeline task." It is already used at scale in industry data pipelines (Netflix, Airbnb, etc.).
|
||||
|
||||
### 2.1 Core Concept: Parameterization
|
||||
|
||||
Papermill's key innovation is **parameter injection**. Tag a cell in the notebook with `"parameters"`:
|
||||
|
||||
```python
|
||||
# Cell tagged "parameters" (defaults — defined by notebook author)
|
||||
alpha = 0.5
|
||||
batch_size = 32
|
||||
model_name = "baseline"
|
||||
```
|
||||
|
||||
At runtime, Papermill inserts a new cell immediately after, tagged `"injected-parameters"`, that overrides the defaults:
|
||||
|
||||
```python
|
||||
# Cell tagged "injected-parameters" (injected by Papermill at runtime)
|
||||
alpha = 0.01
|
||||
batch_size = 128
|
||||
model_name = "experiment_007"
|
||||
```
|
||||
|
||||
Because Python executes top-to-bottom, the injected cell shadows the defaults. The original notebook is never mutated — Papermill reads input, writes to a new output file.
|
||||
|
||||
### 2.2 Python API
|
||||
|
||||
```python
|
||||
import papermill as pm
|
||||
|
||||
nb = pm.execute_notebook(
|
||||
input_path="analysis.ipynb", # source (can be s3://, az://, gs://)
|
||||
output_path="output/run_001.ipynb", # destination (persists outputs)
|
||||
parameters={
|
||||
"alpha": 0.01,
|
||||
"n_samples": 1000,
|
||||
"run_id": "fleet-check-2026-04-06",
|
||||
},
|
||||
kernel_name="python3",
|
||||
execution_timeout=300, # per-cell timeout in seconds
|
||||
log_output=True, # stream cell output to logger
|
||||
cwd="/path/to/notebook/", # working directory
|
||||
)
|
||||
# Returns: NotebookNode (the fully executed notebook with all outputs)
|
||||
```
|
||||
|
||||
On cell failure, Papermill raises `PapermillExecutionError` with:
|
||||
- `cell_index` — which cell failed
|
||||
- `source` — the failing cell's code
|
||||
- `ename` / `evalue` — exception type and message
|
||||
- `traceback` — full traceback
|
||||
|
||||
Even on failure, the output notebook is written with whatever cells completed — enabling partial-run inspection.
|
||||
|
||||
### 2.3 CLI
|
||||
|
||||
```bash
|
||||
# Basic execution
|
||||
papermill analysis.ipynb output/run_001.ipynb \
|
||||
-p alpha 0.01 \
|
||||
-p n_samples 1000
|
||||
|
||||
# From YAML parameter file
|
||||
papermill analysis.ipynb output/run_001.ipynb -f params.yaml
|
||||
|
||||
# CI-friendly: log outputs, no progress bar
|
||||
papermill analysis.ipynb output/run_001.ipynb \
|
||||
--log-output \
|
||||
--no-progress-bar \
|
||||
--execution-timeout 300 \
|
||||
-p run_id "fleet-check-2026-04-06"
|
||||
|
||||
# Prepare only (inject params, skip execution — for preview/inspection)
|
||||
papermill analysis.ipynb preview.ipynb --prepare-only -p alpha 0.01
|
||||
|
||||
# Inspect parameter schema
|
||||
papermill --help-notebook analysis.ipynb
|
||||
```
|
||||
|
||||
**Remote storage** is built in — `pip install papermill[s3]` enables `s3://` paths for both input and output. Azure and GCS are also supported. For Hermes, this means notebook runs can be stored in object storage and retrieved later for audit.
|
||||
|
||||
### 2.4 Scrapbook — Structured Output Collection
|
||||
|
||||
`scrapbook` is Papermill's companion for extracting structured data from executed notebooks. Inside a notebook cell:
|
||||
|
||||
```python
|
||||
import scrapbook as sb
|
||||
|
||||
# Write typed outputs (stored as special display_data in cell outputs)
|
||||
sb.glue("accuracy", 0.9342)
|
||||
sb.glue("metrics", {"precision": 0.91, "recall": 0.93, "f1": 0.92})
|
||||
sb.glue("results_df", df, "pandas") # DataFrames too
|
||||
```
|
||||
|
||||
After execution, from the agent:
|
||||
|
||||
```python
|
||||
import scrapbook as sb
|
||||
|
||||
nb = sb.read_notebook("output/fleet-check-2026-04-06.ipynb")
|
||||
metrics = nb.scraps["metrics"].data # -> {"precision": 0.91, ...}
|
||||
accuracy = nb.scraps["accuracy"].data # -> 0.9342
|
||||
|
||||
# Or aggregate across many runs
|
||||
book = sb.read_notebooks("output/")
|
||||
book.scrap_dataframe # -> pd.DataFrame with all scraps + filenames
|
||||
```
|
||||
|
||||
This is the clean interface between notebook execution and agent decision-making: the notebook outputs its findings as named, typed scraps; the agent reads them programmatically and acts.
|
||||
|
||||
### 2.5 How Papermill Compares to hamelnb
|
||||
|
||||
| Capability | hamelnb | Papermill |
|
||||
|---|---|---|
|
||||
| Stateful kernel session | Yes | No (fresh kernel per run) |
|
||||
| Parameter injection | No | Yes |
|
||||
| Persistent output notebook | No | Yes |
|
||||
| Remote storage (S3/Azure) | No | Yes |
|
||||
| Per-cell timing/metadata | No | Yes (in output nb metadata) |
|
||||
| Error isolation (partial runs) | No | Yes |
|
||||
| Production pipeline use | Experimental | Industry-standard |
|
||||
| Structured output collection | No | Yes (via scrapbook) |
|
||||
|
||||
**Verdict:** `hamelnb` is great for interactive REPL-style exploration (where state accumulates). Papermill is better for task execution (where we want reproducible, parameterized, auditable runs). They serve different use cases. Hermes needs both.
|
||||
|
||||
---
|
||||
|
||||
## 3. The `.ipynb` File Format — What the Agent Is Actually Working With
|
||||
|
||||
Understanding the format is essential for the "PR model." A `.ipynb` file is JSON with this structure:
|
||||
|
||||
```json
|
||||
{
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5,
|
||||
"metadata": {
|
||||
"kernelspec": {"display_name": "Python 3", "language": "python", "name": "python3"},
|
||||
"language_info": {"name": "python", "version": "3.10.0"}
|
||||
},
|
||||
"cells": [
|
||||
{
|
||||
"id": "a1b2c3d4",
|
||||
"cell_type": "markdown",
|
||||
"source": "# Fleet Health Check\n\nThis notebook checks system health.",
|
||||
"metadata": {}
|
||||
},
|
||||
{
|
||||
"id": "e5f6g7h8",
|
||||
"cell_type": "code",
|
||||
"source": "alpha = 0.5\nthreshold = 0.95",
|
||||
"metadata": {"tags": ["parameters"]},
|
||||
"execution_count": null,
|
||||
"outputs": []
|
||||
},
|
||||
{
|
||||
"id": "i9j0k1l2",
|
||||
"cell_type": "code",
|
||||
"source": "import sys\nprint(sys.version)",
|
||||
"metadata": {},
|
||||
"execution_count": 1,
|
||||
"outputs": [
|
||||
{
|
||||
"output_type": "stream",
|
||||
"name": "stdout",
|
||||
"text": "3.10.0 (default, ...)\n"
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
The `nbformat` Python library provides a clean API for working with this:
|
||||
|
||||
```python
|
||||
import nbformat
|
||||
|
||||
# Read
|
||||
with open("notebook.ipynb") as f:
|
||||
nb = nbformat.read(f, as_version=4)
|
||||
|
||||
# Navigate
|
||||
for cell in nb.cells:
|
||||
if cell.cell_type == "code":
|
||||
print(cell.source)
|
||||
|
||||
# Modify
|
||||
nb.cells[2].source = "import sys\nprint('updated')"
|
||||
|
||||
# Add cells
|
||||
new_md = nbformat.v4.new_markdown_cell("## Agent Analysis\nInserted by Hermes.")
|
||||
nb.cells.insert(3, new_md)
|
||||
|
||||
# Write
|
||||
with open("modified.ipynb", "w") as f:
|
||||
nbformat.write(nb, f)
|
||||
|
||||
# Validate
|
||||
nbformat.validate(nb) # raises nbformat.ValidationError on invalid format
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 4. The PR Model for Notebooks
|
||||
|
||||
This is the elegant architecture Rockachopa described: agents making PRs to notebooks the same way they make PRs to code. Here's how the full stack enables it.
|
||||
|
||||
### 4.1 The Problem: Raw `.ipynb` Diffs Are Unusable
|
||||
|
||||
Without tooling, a `git diff` on a notebook that was merely re-run (no source changes) produces thousands of lines of JSON changes — execution counts, timestamps, base64-encoded plot images. Code review on raw `.ipynb` diffs is impractical.
|
||||
|
||||
### 4.2 nbstripout — Clean Git History
|
||||
|
||||
`nbstripout` installs a git **clean filter** that strips outputs before files enter the git index. The working copy is untouched; only what gets committed is clean.
|
||||
|
||||
```bash
|
||||
pip install nbstripout
|
||||
nbstripout --install # per-repo
|
||||
# or
|
||||
nbstripout --install --global # all repos
|
||||
```
|
||||
|
||||
This writes to `.git/config`:
|
||||
```ini
|
||||
[filter "nbstripout"]
|
||||
clean = nbstripout
|
||||
smudge = cat
|
||||
required = true
|
||||
|
||||
[diff "ipynb"]
|
||||
textconv = nbstripout -t
|
||||
```
|
||||
|
||||
And to `.gitattributes`:
|
||||
```
|
||||
*.ipynb filter=nbstripout
|
||||
*.ipynb diff=ipynb
|
||||
```
|
||||
|
||||
Now `git diff` shows only source changes — same as reviewing a `.py` file.
|
||||
|
||||
**For executed-output notebooks** (where we want to keep outputs for audit): use a separate path like `runs/` or `outputs/` excluded from the filter via `.gitattributes`:
|
||||
```
|
||||
*.ipynb filter=nbstripout
|
||||
runs/*.ipynb !filter
|
||||
runs/*.ipynb !diff
|
||||
```
|
||||
|
||||
### 4.3 nbdime — Semantic Diff and Merge
|
||||
|
||||
nbdime understands notebook structure. Instead of diffing raw JSON, it diffs at the level of cells — knowing that `cells` is a list, `source` is a string, and outputs should often be ignored.
|
||||
|
||||
```bash
|
||||
pip install nbdime
|
||||
|
||||
# Enable semantic git diff/merge for all .ipynb files
|
||||
nbdime config-git --enable
|
||||
|
||||
# Now standard git commands are notebook-aware:
|
||||
git diff HEAD notebook.ipynb # semantic cell-level diff
|
||||
git merge feature-branch # uses nbdime for .ipynb conflict resolution
|
||||
git log -p notebook.ipynb # readable patch per commit
|
||||
```
|
||||
|
||||
**Python API for agent reasoning:**
|
||||
|
||||
```python
|
||||
import nbdime
|
||||
import nbformat
|
||||
|
||||
nb_base = nbformat.read(open("original.ipynb"), as_version=4)
|
||||
nb_pr = nbformat.read(open("proposed.ipynb"), as_version=4)
|
||||
|
||||
diff = nbdime.diff_notebooks(nb_base, nb_pr)
|
||||
|
||||
# diff is a list of structured ops the agent can reason about:
|
||||
# [{"op": "patch", "key": "cells", "diff": [
|
||||
# {"op": "patch", "key": 3, "diff": [
|
||||
# {"op": "patch", "key": "source", "diff": [...string ops...]}
|
||||
# ]}
|
||||
# ]}]
|
||||
|
||||
# Apply a diff (patch)
|
||||
from nbdime.patching import patch
|
||||
nb_result = patch(nb_base, diff)
|
||||
```
|
||||
|
||||
### 4.4 The Full Agent PR Workflow
|
||||
|
||||
Here is the complete workflow — analogous to how Hermes makes PRs to code repos via Gitea:
|
||||
|
||||
**1. Agent reads the task notebook**
|
||||
```python
|
||||
nb = nbformat.read(open("fleet_health_check.ipynb"), as_version=4)
|
||||
```
|
||||
|
||||
**2. Agent locates and modifies relevant cells**
|
||||
```python
|
||||
# Find parameter cell
|
||||
params_cell = next(
|
||||
c for c in nb.cells
|
||||
if "parameters" in c.get("metadata", {}).get("tags", [])
|
||||
)
|
||||
# Update threshold
|
||||
params_cell.source = params_cell.source.replace("threshold = 0.95", "threshold = 0.90")
|
||||
|
||||
# Add explanatory markdown
|
||||
nb.cells.insert(
|
||||
nb.cells.index(params_cell) + 1,
|
||||
nbformat.v4.new_markdown_cell(
|
||||
"**Note (Hermes 2026-04-06):** Threshold lowered from 0.95 to 0.90 "
|
||||
"based on false-positive analysis from last 7 days of runs."
|
||||
)
|
||||
)
|
||||
```
|
||||
|
||||
**3. Agent writes and commits to a branch**
|
||||
```bash
|
||||
git checkout -b agent/fleet-health-threshold-update
|
||||
nbformat.write(nb, open("fleet_health_check.ipynb", "w"))
|
||||
git add fleet_health_check.ipynb
|
||||
git commit -m "feat(notebooks): lower fleet health threshold to 0.90 (#155)"
|
||||
```
|
||||
|
||||
**4. Agent executes the proposed notebook to validate**
|
||||
```python
|
||||
import papermill as pm
|
||||
|
||||
pm.execute_notebook(
|
||||
"fleet_health_check.ipynb",
|
||||
"output/validation_run.ipynb",
|
||||
parameters={"run_id": "agent-validation-2026-04-06"},
|
||||
log_output=True,
|
||||
)
|
||||
```
|
||||
|
||||
**5. Agent collects results and compares**
|
||||
```python
|
||||
import scrapbook as sb
|
||||
|
||||
result = sb.read_notebook("output/validation_run.ipynb")
|
||||
health_score = result.scraps["health_score"].data
|
||||
alert_count = result.scraps["alert_count"].data
|
||||
```
|
||||
|
||||
**6. Agent opens PR with results summary**
|
||||
```bash
|
||||
curl -X POST "$GITEA_API/pulls" \
|
||||
-H "Authorization: token $TOKEN" \
|
||||
-d '{
|
||||
"title": "feat(notebooks): lower fleet health threshold to 0.90",
|
||||
"body": "## Agent Analysis\n\n- Health score: 0.94 (was 0.89 with old threshold)\n- Alert count: 12 (was 47 false positives)\n- Validation run: output/validation_run.ipynb\n\nRefs #155",
|
||||
"head": "agent/fleet-health-threshold-update",
|
||||
"base": "main"
|
||||
}'
|
||||
```
|
||||
|
||||
**7. Human reviews the PR using nbdime diff**
|
||||
|
||||
The PR diff in Gitea shows the clean cell-level source changes (thanks to nbstripout). The human can also run `nbdiff-web original.ipynb proposed.ipynb` locally for rich rendered diff with output comparison.
|
||||
|
||||
### 4.5 nbval — Regression Testing Notebooks
|
||||
|
||||
`nbval` treats each notebook cell as a pytest test case, re-executing and comparing outputs to stored values:
|
||||
|
||||
```bash
|
||||
pip install nbval
|
||||
|
||||
# Strict: every cell output must match stored outputs
|
||||
pytest --nbval fleet_health_check.ipynb
|
||||
|
||||
# Lax: only check cells marked with # NBVAL_CHECK_OUTPUT
|
||||
pytest --nbval-lax fleet_health_check.ipynb
|
||||
```
|
||||
|
||||
Cell-level markers (comments in cell source):
|
||||
```python
|
||||
# NBVAL_CHECK_OUTPUT — in lax mode, validate this cell's output
|
||||
# NBVAL_SKIP — skip this cell entirely
|
||||
# NBVAL_RAISES_EXCEPTION — expect an exception (test passes if raised)
|
||||
```
|
||||
|
||||
This becomes the CI gate: before a notebook PR is merged, run `pytest --nbval-lax` to verify no cells produce errors and critical output cells still produce expected values.
|
||||
|
||||
---
|
||||
|
||||
## 5. Gaps and Recommendations
|
||||
|
||||
### 5.1 Gap Assessment (Refining Timmy's Original Findings)
|
||||
|
||||
| Gap | Severity | Solution |
|
||||
|---|---|---|
|
||||
| No Hermes tool access in kernel | High | Inject `hermes_runtime` module (see §5.2) |
|
||||
| No structured output protocol | High | Use scrapbook `sb.glue()` pattern |
|
||||
| No parameterization | Medium | Add Papermill `"parameters"` cell to notebooks |
|
||||
| XSRF/auth friction | Medium | Disable for local; use JupyterHub token scopes for multi-user |
|
||||
| No notebook CI/testing | Medium | Add nbval to test suite |
|
||||
| Raw `.ipynb` diffs in PRs | Medium | Install nbstripout + nbdime |
|
||||
| No scheduling | Low | Papermill + existing Hermes cron layer |
|
||||
|
||||
### 5.2 Short-Term Recommendations (This Month)
|
||||
|
||||
**1. `NotebookExecutor` tool**
|
||||
|
||||
A thin Hermes tool wrapping the ecosystem:
|
||||
|
||||
```python
|
||||
class NotebookExecutor:
|
||||
def execute(self, input_path, output_path, parameters, timeout=300):
|
||||
"""Wraps pm.execute_notebook(). Returns structured result dict."""
|
||||
|
||||
def collect_outputs(self, notebook_path):
|
||||
"""Wraps sb.read_notebook(). Returns dict of named scraps."""
|
||||
|
||||
def inspect_parameters(self, notebook_path):
|
||||
"""Wraps pm.inspect_notebook(). Returns parameter schema."""
|
||||
|
||||
def read_notebook(self, path):
|
||||
"""Returns nbformat NotebookNode for cell inspection/modification."""
|
||||
|
||||
def write_notebook(self, nb, path):
|
||||
"""Writes modified NotebookNode back to disk."""
|
||||
|
||||
def diff_notebooks(self, path_a, path_b):
|
||||
"""Returns structured nbdime diff for agent reasoning."""
|
||||
|
||||
def validate(self, notebook_path):
|
||||
"""Runs nbformat.validate() + optional pytest --nbval-lax."""
|
||||
```
|
||||
|
||||
Execution result structure for the agent:
|
||||
```python
|
||||
{
|
||||
"status": "success" | "error",
|
||||
"duration_seconds": 12.34,
|
||||
"cells_executed": 15,
|
||||
"failed_cell": { # None on success
|
||||
"index": 7,
|
||||
"source": "model.fit(X, y)",
|
||||
"ename": "ValueError",
|
||||
"evalue": "Input contains NaN",
|
||||
},
|
||||
"scraps": { # from scrapbook
|
||||
"health_score": 0.94,
|
||||
"alert_count": 12,
|
||||
},
|
||||
}
|
||||
```
|
||||
|
||||
**2. Fleet Health Check as a Notebook**
|
||||
|
||||
Convert the fleet health check epic into a parameterized notebook with:
|
||||
- `"parameters"` cell for run configuration (date range, thresholds, agent ID)
|
||||
- Markdown cells narrating each step
|
||||
- `sb.glue()` calls for structured outputs
|
||||
- `# NBVAL_CHECK_OUTPUT` markers on critical cells
|
||||
|
||||
**3. Git hygiene for notebooks**
|
||||
|
||||
Install nbstripout + nbdime in the hermes-agent repo:
|
||||
```bash
|
||||
pip install nbstripout nbdime
|
||||
nbstripout --install
|
||||
nbdime config-git --enable
|
||||
```
|
||||
|
||||
Add to `.gitattributes`:
|
||||
```
|
||||
*.ipynb filter=nbstripout
|
||||
*.ipynb diff=ipynb
|
||||
runs/*.ipynb !filter
|
||||
```
|
||||
|
||||
### 5.3 Medium-Term Recommendations (Next Quarter)
|
||||
|
||||
**4. `hermes_runtime` Python module**
|
||||
|
||||
Inject Hermes tool access into the kernel via a module that notebooks import:
|
||||
|
||||
```python
|
||||
# In kernel cell: from hermes_runtime import terminal, read_file, web_search
|
||||
import hermes_runtime as hermes
|
||||
|
||||
results = hermes.web_search("fleet health metrics best practices")
|
||||
hermes.terminal("systemctl status agent-fleet")
|
||||
content = hermes.read_file("/var/log/hermes/agent.log")
|
||||
```
|
||||
|
||||
This closes the most significant gap: notebooks gain the same tool access as skills, while retaining state persistence and narrative structure.
|
||||
|
||||
**5. Notebook-triggered cron**
|
||||
|
||||
Extend the Hermes cron layer to accept `.ipynb` paths as targets:
|
||||
```yaml
|
||||
# cron entry
|
||||
schedule: "0 6 * * *"
|
||||
type: notebook
|
||||
path: notebooks/fleet_health_check.ipynb
|
||||
parameters:
|
||||
run_id: "{{date}}"
|
||||
alert_threshold: 0.90
|
||||
output_path: runs/fleet_health_{{date}}.ipynb
|
||||
```
|
||||
|
||||
The cron runner calls `pm.execute_notebook()` and commits the output to the repo.
|
||||
|
||||
**6. JupyterHub for multi-agent isolation**
|
||||
|
||||
If multiple agents need concurrent notebook execution, deploy JupyterHub with `DockerSpawner` or `KubeSpawner`. Each agent job gets an isolated container with its own kernel, no state bleed between runs.
|
||||
|
||||
---
|
||||
|
||||
## 6. Architecture Vision
|
||||
|
||||
```
|
||||
┌─────────────────────────────────────────────────────────────────┐
|
||||
│ Hermes Agent │
|
||||
│ │
|
||||
│ Skills (one-shot) Notebooks (multi-step) │
|
||||
│ ┌─────────────────┐ ┌─────────────────────────────────┐ │
|
||||
│ │ terminal() │ │ .ipynb file │ │
|
||||
│ │ web_search() │ │ ├── Markdown (narrative) │ │
|
||||
│ │ read_file() │ │ ├── Code cells (logic) │ │
|
||||
│ └─────────────────┘ │ ├── "parameters" cell │ │
|
||||
│ │ └── sb.glue() outputs │ │
|
||||
│ └──────────────┬────────────────┘ │
|
||||
│ │ │
|
||||
│ ┌──────────────▼────────────────┐ │
|
||||
│ │ NotebookExecutor tool │ │
|
||||
│ │ (papermill + scrapbook + │ │
|
||||
│ │ nbformat + nbdime + nbval) │ │
|
||||
│ └──────────────┬────────────────┘ │
|
||||
│ │ │
|
||||
└────────────────────────────────────────────┼────────────────────┘
|
||||
│
|
||||
┌───────────────────▼──────────────────┐
|
||||
│ JupyterLab / Hub │
|
||||
│ (kernel execution environment) │
|
||||
└───────────────────┬──────────────────┘
|
||||
│
|
||||
┌───────────────────▼──────────────────┐
|
||||
│ Git + Gitea │
|
||||
│ (nbstripout clean diffs, │
|
||||
│ nbdime semantic review, │
|
||||
│ PR workflow for notebook changes) │
|
||||
└──────────────────────────────────────┘
|
||||
```
|
||||
|
||||
**Notebooks become the primary artifact of complex tasks:** the agent generates or edits cells, Papermill executes them reproducibly, scrapbook extracts structured outputs for agent decision-making, and the resulting `.ipynb` is both proof-of-work and human-readable report. Skills remain for one-shot actions. Notebooks own multi-step workflows.
|
||||
|
||||
---
|
||||
|
||||
## 7. Package Summary
|
||||
|
||||
| Package | Purpose | Install |
|
||||
|---|---|---|
|
||||
| `nbformat` | Read/write/validate `.ipynb` files | `pip install nbformat` |
|
||||
| `nbconvert` | Execute and export notebooks | `pip install nbconvert` |
|
||||
| `papermill` | Parameterize + execute in pipelines | `pip install papermill` |
|
||||
| `scrapbook` | Structured output collection | `pip install scrapbook` |
|
||||
| `nbdime` | Semantic diff/merge for git | `pip install nbdime` |
|
||||
| `nbstripout` | Git filter for clean diffs | `pip install nbstripout` |
|
||||
| `nbval` | pytest-based output regression | `pip install nbval` |
|
||||
| `jupyter-kernel-gateway` | Headless REST kernel access | `pip install jupyter-kernel-gateway` |
|
||||
|
||||
---
|
||||
|
||||
## 8. References
|
||||
|
||||
- [Papermill GitHub (nteract/papermill)](https://github.com/nteract/papermill)
|
||||
- [Scrapbook GitHub (nteract/scrapbook)](https://github.com/nteract/scrapbook)
|
||||
- [nbformat format specification](https://nbformat.readthedocs.io/en/latest/format_description.html)
|
||||
- [nbdime documentation](https://nbdime.readthedocs.io/)
|
||||
- [nbdime diff format spec (JEP #8)](https://github.com/jupyter/enhancement-proposals/blob/master/08-notebook-diff/notebook-diff.md)
|
||||
- [nbconvert execute API](https://nbconvert.readthedocs.io/en/latest/execute_api.html)
|
||||
- [nbstripout README](https://github.com/kynan/nbstripout)
|
||||
- [nbval GitHub (computationalmodelling/nbval)](https://github.com/computationalmodelling/nbval)
|
||||
- [JupyterHub REST API](https://jupyterhub.readthedocs.io/en/stable/howto/rest.html)
|
||||
- [JupyterHub Technical Overview](https://jupyterhub.readthedocs.io/en/latest/reference/technical-overview.html)
|
||||
- [Jupyter Kernel Gateway](https://github.com/jupyter-server/kernel_gateway)
|
||||
955
observatory.py
Normal file
955
observatory.py
Normal file
@@ -0,0 +1,955 @@
|
||||
"""
|
||||
Observatory — Testbed Health Monitoring & Alerting for Hermes Agent
|
||||
|
||||
Checks running services, system resources, and connectivity.
|
||||
Fires Telegram alerts when thresholds are breached.
|
||||
Posts daily digest reports.
|
||||
Stores 30 days of historical health data in SQLite.
|
||||
|
||||
Usage:
|
||||
python observatory.py --check # one-shot health check (stdout)
|
||||
python observatory.py --daemon # continuous monitor (60s poll)
|
||||
python observatory.py --digest # print / send daily digest
|
||||
python observatory.py --history N # show last N health records
|
||||
python observatory.py --slo # print SLO report
|
||||
|
||||
Configuration (env vars, falls back to ~/.hermes/.env):
|
||||
OBSERVATORY_ALERT_CHAT_ID Telegram chat ID for alerts
|
||||
OBSERVATORY_DIGEST_CHAT_ID Telegram chat ID for daily digest (default: alert chat)
|
||||
OBSERVATORY_POLL_INTERVAL Seconds between health polls (default: 60)
|
||||
OBSERVATORY_DB_PATH SQLite path (default: ~/.hermes/observatory.db)
|
||||
TELEGRAM_BOT_TOKEN Bot token used to send alerts
|
||||
|
||||
# Threshold overrides (all optional):
|
||||
OBSERVATORY_DISK_WARN_PCT Disk usage warn threshold (default: 80)
|
||||
OBSERVATORY_DISK_CRIT_PCT Disk usage critical threshold (default: 90)
|
||||
OBSERVATORY_MEM_WARN_PCT Memory usage warn threshold (default: 80)
|
||||
OBSERVATORY_MEM_CRIT_PCT Memory usage critical threshold (default: 90)
|
||||
OBSERVATORY_CPU_WARN_PCT CPU usage warn threshold (default: 80)
|
||||
OBSERVATORY_CPU_CRIT_PCT CPU usage critical threshold (default: 95)
|
||||
OBSERVATORY_WEBHOOK_URL Webhook endpoint to probe (default: http://127.0.0.1:8080/health)
|
||||
OBSERVATORY_API_URL API server health URL (default: http://127.0.0.1:8642/health)
|
||||
OBSERVATORY_WEBHOOK_LATENCY_SLO_MS Webhook latency SLO ms (default: 2000)
|
||||
OBSERVATORY_GATEWAY_UPTIME_SLO_PCT Gateway uptime SLO % (default: 99.5)
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import argparse
|
||||
import json
|
||||
import logging
|
||||
import os
|
||||
import signal
|
||||
import sqlite3
|
||||
import sys
|
||||
import time
|
||||
import urllib.request
|
||||
import urllib.error
|
||||
from contextlib import contextmanager
|
||||
from dataclasses import dataclass, field, asdict
|
||||
from datetime import datetime, timezone, timedelta
|
||||
from pathlib import Path
|
||||
from typing import Any, Dict, List, Optional, Tuple
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Optional imports
|
||||
# ---------------------------------------------------------------------------
|
||||
try:
|
||||
import psutil
|
||||
_PSUTIL = True
|
||||
except ImportError:
|
||||
_PSUTIL = False
|
||||
|
||||
try:
|
||||
from dotenv import load_dotenv as _load_dotenv
|
||||
_DOTENV = True
|
||||
except ImportError:
|
||||
_DOTENV = False
|
||||
|
||||
logger = logging.getLogger("observatory")
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Constants & SLO definitions
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
RETENTION_DAYS = 30
|
||||
|
||||
SLO_DEFINITIONS = {
|
||||
"gateway_uptime_pct": {
|
||||
"description": "Gateway process uptime over the last 24 hours",
|
||||
"target": 99.5,
|
||||
"unit": "%",
|
||||
},
|
||||
"webhook_latency_ms": {
|
||||
"description": "Webhook endpoint p95 response latency",
|
||||
"target": 2000,
|
||||
"unit": "ms",
|
||||
"direction": "lower_is_better",
|
||||
},
|
||||
"api_server_latency_ms": {
|
||||
"description": "API server /health p95 response latency",
|
||||
"target": 2000,
|
||||
"unit": "ms",
|
||||
"direction": "lower_is_better",
|
||||
},
|
||||
}
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Configuration
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def _load_env() -> None:
|
||||
"""Load .env from HERMES_HOME if dotenv is available."""
|
||||
if not _DOTENV:
|
||||
return
|
||||
hermes_home = Path(os.getenv("HERMES_HOME", Path.home() / ".hermes"))
|
||||
env_path = hermes_home / ".env"
|
||||
if env_path.exists():
|
||||
_load_dotenv(env_path, override=False)
|
||||
# Project-level .env as dev fallback
|
||||
project_env = Path(__file__).parent / ".env"
|
||||
if project_env.exists():
|
||||
_load_dotenv(project_env, override=False)
|
||||
|
||||
|
||||
@dataclass
|
||||
class ObservatoryConfig:
|
||||
alert_chat_id: Optional[str] = None
|
||||
digest_chat_id: Optional[str] = None
|
||||
telegram_token: Optional[str] = None
|
||||
poll_interval: int = 60
|
||||
db_path: Path = field(default_factory=lambda: Path(os.getenv("HERMES_HOME", Path.home() / ".hermes")) / "observatory.db")
|
||||
disk_warn_pct: float = 80.0
|
||||
disk_crit_pct: float = 90.0
|
||||
mem_warn_pct: float = 80.0
|
||||
mem_crit_pct: float = 90.0
|
||||
cpu_warn_pct: float = 80.0
|
||||
cpu_crit_pct: float = 95.0
|
||||
webhook_url: str = "http://127.0.0.1:8080/health"
|
||||
api_url: str = "http://127.0.0.1:8642/health"
|
||||
webhook_latency_slo_ms: float = 2000.0
|
||||
gateway_uptime_slo_pct: float = 99.5
|
||||
|
||||
@classmethod
|
||||
def from_env(cls) -> "ObservatoryConfig":
|
||||
_load_env()
|
||||
cfg = cls()
|
||||
cfg.telegram_token = os.getenv("TELEGRAM_BOT_TOKEN")
|
||||
cfg.alert_chat_id = os.getenv("OBSERVATORY_ALERT_CHAT_ID")
|
||||
cfg.digest_chat_id = os.getenv("OBSERVATORY_DIGEST_CHAT_ID") or cfg.alert_chat_id
|
||||
cfg.poll_interval = int(os.getenv("OBSERVATORY_POLL_INTERVAL", 60))
|
||||
db_override = os.getenv("OBSERVATORY_DB_PATH")
|
||||
if db_override:
|
||||
cfg.db_path = Path(db_override)
|
||||
cfg.disk_warn_pct = float(os.getenv("OBSERVATORY_DISK_WARN_PCT", 80))
|
||||
cfg.disk_crit_pct = float(os.getenv("OBSERVATORY_DISK_CRIT_PCT", 90))
|
||||
cfg.mem_warn_pct = float(os.getenv("OBSERVATORY_MEM_WARN_PCT", 80))
|
||||
cfg.mem_crit_pct = float(os.getenv("OBSERVATORY_MEM_CRIT_PCT", 90))
|
||||
cfg.cpu_warn_pct = float(os.getenv("OBSERVATORY_CPU_WARN_PCT", 80))
|
||||
cfg.cpu_crit_pct = float(os.getenv("OBSERVATORY_CPU_CRIT_PCT", 95))
|
||||
cfg.webhook_url = os.getenv("OBSERVATORY_WEBHOOK_URL", "http://127.0.0.1:8080/health")
|
||||
cfg.api_url = os.getenv("OBSERVATORY_API_URL", "http://127.0.0.1:8642/health")
|
||||
cfg.webhook_latency_slo_ms = float(os.getenv("OBSERVATORY_WEBHOOK_LATENCY_SLO_MS", 2000))
|
||||
cfg.gateway_uptime_slo_pct = float(os.getenv("OBSERVATORY_GATEWAY_UPTIME_SLO_PCT", 99.5))
|
||||
return cfg
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Health check models
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
@dataclass
|
||||
class CheckResult:
|
||||
name: str
|
||||
status: str # "ok" | "warn" | "critical" | "error"
|
||||
message: str
|
||||
value: Optional[float] = None
|
||||
unit: Optional[str] = None
|
||||
extra: Dict[str, Any] = field(default_factory=dict)
|
||||
|
||||
|
||||
@dataclass
|
||||
class HealthSnapshot:
|
||||
ts: str # ISO8601 UTC
|
||||
checks: List[CheckResult] = field(default_factory=list)
|
||||
|
||||
@property
|
||||
def overall_status(self) -> str:
|
||||
statuses = {c.status for c in self.checks}
|
||||
if "critical" in statuses or "error" in statuses:
|
||||
return "critical"
|
||||
if "warn" in statuses:
|
||||
return "warn"
|
||||
return "ok"
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
return {
|
||||
"ts": self.ts,
|
||||
"overall": self.overall_status,
|
||||
"checks": [asdict(c) for c in self.checks],
|
||||
}
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Individual health checks
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def check_gateway_liveness() -> CheckResult:
|
||||
"""Check whether the Hermes gateway process is running."""
|
||||
try:
|
||||
from gateway.status import is_gateway_running, get_running_pid
|
||||
running = is_gateway_running()
|
||||
pid = get_running_pid()
|
||||
if running:
|
||||
return CheckResult(
|
||||
name="gateway_process",
|
||||
status="ok",
|
||||
message=f"Gateway running (pid={pid})",
|
||||
value=float(pid) if pid else None,
|
||||
)
|
||||
return CheckResult(
|
||||
name="gateway_process",
|
||||
status="critical",
|
||||
message="Gateway process is NOT running",
|
||||
)
|
||||
except Exception as exc:
|
||||
return CheckResult(
|
||||
name="gateway_process",
|
||||
status="error",
|
||||
message=f"Could not determine gateway status: {exc}",
|
||||
)
|
||||
|
||||
|
||||
def check_api_server_http(cfg: ObservatoryConfig) -> CheckResult:
|
||||
"""Check API server /health endpoint responsiveness."""
|
||||
url = cfg.api_url
|
||||
start = time.monotonic()
|
||||
try:
|
||||
req = urllib.request.Request(url, method="GET")
|
||||
req.add_header("User-Agent", "hermes-observatory/1.0")
|
||||
with urllib.request.urlopen(req, timeout=10) as resp:
|
||||
latency_ms = (time.monotonic() - start) * 1000
|
||||
body = resp.read(512).decode("utf-8", errors="replace")
|
||||
status_code = resp.status
|
||||
if status_code < 400:
|
||||
slo_ok = latency_ms <= cfg.webhook_latency_slo_ms
|
||||
return CheckResult(
|
||||
name="api_server_http",
|
||||
status="ok" if slo_ok else "warn",
|
||||
message=f"API server OK ({latency_ms:.0f}ms){'' if slo_ok else ' — exceeds latency SLO'}",
|
||||
value=latency_ms,
|
||||
unit="ms",
|
||||
extra={"status_code": status_code, "body_preview": body[:100]},
|
||||
)
|
||||
return CheckResult(
|
||||
name="api_server_http",
|
||||
status="critical",
|
||||
message=f"API server returned HTTP {status_code}",
|
||||
value=latency_ms,
|
||||
unit="ms",
|
||||
)
|
||||
except urllib.error.URLError as exc:
|
||||
latency_ms = (time.monotonic() - start) * 1000
|
||||
# Not running is acceptable if gateway is not configured for API
|
||||
reason = str(exc.reason) if hasattr(exc, "reason") else str(exc)
|
||||
if "Connection refused" in reason or "Connection reset" in reason:
|
||||
return CheckResult(
|
||||
name="api_server_http",
|
||||
status="warn",
|
||||
message=f"API server not reachable at {url} (not started?)",
|
||||
value=latency_ms,
|
||||
unit="ms",
|
||||
)
|
||||
return CheckResult(
|
||||
name="api_server_http",
|
||||
status="error",
|
||||
message=f"API server probe error: {exc}",
|
||||
value=latency_ms,
|
||||
unit="ms",
|
||||
)
|
||||
except Exception as exc:
|
||||
latency_ms = (time.monotonic() - start) * 1000
|
||||
return CheckResult(
|
||||
name="api_server_http",
|
||||
status="error",
|
||||
message=f"API server probe exception: {exc}",
|
||||
value=latency_ms,
|
||||
unit="ms",
|
||||
)
|
||||
|
||||
|
||||
def check_webhook_http(cfg: ObservatoryConfig) -> CheckResult:
|
||||
"""Check webhook endpoint responsiveness."""
|
||||
url = cfg.webhook_url
|
||||
start = time.monotonic()
|
||||
try:
|
||||
req = urllib.request.Request(url, method="GET")
|
||||
req.add_header("User-Agent", "hermes-observatory/1.0")
|
||||
with urllib.request.urlopen(req, timeout=10) as resp:
|
||||
latency_ms = (time.monotonic() - start) * 1000
|
||||
status_code = resp.status
|
||||
slo_ok = latency_ms <= cfg.webhook_latency_slo_ms
|
||||
if status_code < 400:
|
||||
return CheckResult(
|
||||
name="webhook_http",
|
||||
status="ok" if slo_ok else "warn",
|
||||
message=f"Webhook OK ({latency_ms:.0f}ms){'' if slo_ok else ' — exceeds latency SLO'}",
|
||||
value=latency_ms,
|
||||
unit="ms",
|
||||
extra={"status_code": status_code},
|
||||
)
|
||||
return CheckResult(
|
||||
name="webhook_http",
|
||||
status="critical",
|
||||
message=f"Webhook returned HTTP {status_code}",
|
||||
value=latency_ms,
|
||||
unit="ms",
|
||||
)
|
||||
except urllib.error.URLError as exc:
|
||||
latency_ms = (time.monotonic() - start) * 1000
|
||||
reason = str(exc.reason) if hasattr(exc, "reason") else str(exc)
|
||||
if "Connection refused" in reason or "Connection reset" in reason:
|
||||
return CheckResult(
|
||||
name="webhook_http",
|
||||
status="warn",
|
||||
message=f"Webhook not reachable at {url} (not started?)",
|
||||
value=latency_ms,
|
||||
unit="ms",
|
||||
)
|
||||
return CheckResult(
|
||||
name="webhook_http",
|
||||
status="error",
|
||||
message=f"Webhook probe error: {exc}",
|
||||
value=latency_ms,
|
||||
unit="ms",
|
||||
)
|
||||
except Exception as exc:
|
||||
latency_ms = (time.monotonic() - start) * 1000
|
||||
return CheckResult(
|
||||
name="webhook_http",
|
||||
status="error",
|
||||
message=f"Webhook probe exception: {exc}",
|
||||
value=latency_ms,
|
||||
unit="ms",
|
||||
)
|
||||
|
||||
|
||||
def check_disk(cfg: ObservatoryConfig) -> CheckResult:
|
||||
"""Check disk usage on the HERMES_HOME filesystem."""
|
||||
if not _PSUTIL:
|
||||
return CheckResult(name="disk", status="error", message="psutil not installed")
|
||||
try:
|
||||
hermes_home = Path(os.getenv("HERMES_HOME", Path.home() / ".hermes"))
|
||||
path = str(hermes_home) if hermes_home.exists() else "/"
|
||||
usage = psutil.disk_usage(path)
|
||||
pct = usage.percent
|
||||
free_gb = usage.free / (1024 ** 3)
|
||||
if pct >= cfg.disk_crit_pct:
|
||||
status = "critical"
|
||||
elif pct >= cfg.disk_warn_pct:
|
||||
status = "warn"
|
||||
else:
|
||||
status = "ok"
|
||||
return CheckResult(
|
||||
name="disk",
|
||||
status=status,
|
||||
message=f"Disk {pct:.1f}% used ({free_gb:.1f}GB free)",
|
||||
value=pct,
|
||||
unit="%",
|
||||
extra={"free_bytes": usage.free, "total_bytes": usage.total},
|
||||
)
|
||||
except Exception as exc:
|
||||
return CheckResult(name="disk", status="error", message=f"Disk check error: {exc}")
|
||||
|
||||
|
||||
def check_memory(cfg: ObservatoryConfig) -> CheckResult:
|
||||
"""Check system memory usage."""
|
||||
if not _PSUTIL:
|
||||
return CheckResult(name="memory", status="error", message="psutil not installed")
|
||||
try:
|
||||
mem = psutil.virtual_memory()
|
||||
pct = mem.percent
|
||||
available_gb = mem.available / (1024 ** 3)
|
||||
if pct >= cfg.mem_crit_pct:
|
||||
status = "critical"
|
||||
elif pct >= cfg.mem_warn_pct:
|
||||
status = "warn"
|
||||
else:
|
||||
status = "ok"
|
||||
return CheckResult(
|
||||
name="memory",
|
||||
status=status,
|
||||
message=f"Memory {pct:.1f}% used ({available_gb:.1f}GB available)",
|
||||
value=pct,
|
||||
unit="%",
|
||||
extra={"available_bytes": mem.available, "total_bytes": mem.total},
|
||||
)
|
||||
except Exception as exc:
|
||||
return CheckResult(name="memory", status="error", message=f"Memory check error: {exc}")
|
||||
|
||||
|
||||
def check_cpu(cfg: ObservatoryConfig) -> CheckResult:
|
||||
"""Check CPU usage (1-second sample)."""
|
||||
if not _PSUTIL:
|
||||
return CheckResult(name="cpu", status="error", message="psutil not installed")
|
||||
try:
|
||||
pct = psutil.cpu_percent(interval=1)
|
||||
if pct >= cfg.cpu_crit_pct:
|
||||
status = "critical"
|
||||
elif pct >= cfg.cpu_warn_pct:
|
||||
status = "warn"
|
||||
else:
|
||||
status = "ok"
|
||||
return CheckResult(
|
||||
name="cpu",
|
||||
status=status,
|
||||
message=f"CPU {pct:.1f}%",
|
||||
value=pct,
|
||||
unit="%",
|
||||
)
|
||||
except Exception as exc:
|
||||
return CheckResult(name="cpu", status="error", message=f"CPU check error: {exc}")
|
||||
|
||||
|
||||
def check_database(cfg: ObservatoryConfig) -> CheckResult:
|
||||
"""Check observatory SQLite DB connectivity and size."""
|
||||
db_path = cfg.db_path
|
||||
try:
|
||||
if not db_path.exists():
|
||||
return CheckResult(
|
||||
name="database",
|
||||
status="warn",
|
||||
message=f"Observatory DB not yet created at {db_path}",
|
||||
)
|
||||
size_kb = db_path.stat().st_size / 1024
|
||||
conn = sqlite3.connect(str(db_path), timeout=5)
|
||||
conn.execute("SELECT count(*) FROM health_snapshots").fetchone()
|
||||
conn.close()
|
||||
return CheckResult(
|
||||
name="database",
|
||||
status="ok",
|
||||
message=f"Observatory DB OK ({size_kb:.1f}KB)",
|
||||
value=size_kb,
|
||||
unit="KB",
|
||||
extra={"path": str(db_path)},
|
||||
)
|
||||
except Exception as exc:
|
||||
return CheckResult(
|
||||
name="database",
|
||||
status="error",
|
||||
message=f"DB check error: {exc}",
|
||||
)
|
||||
|
||||
|
||||
def check_response_store_db() -> CheckResult:
|
||||
"""Check the API server's SQLite response store DB if it exists."""
|
||||
try:
|
||||
hermes_home = Path(os.getenv("HERMES_HOME", Path.home() / ".hermes"))
|
||||
db_path = hermes_home / "response_store.db"
|
||||
if not db_path.exists():
|
||||
return CheckResult(
|
||||
name="response_store_db",
|
||||
status="ok",
|
||||
message="Response store DB not present (API server not yet used)",
|
||||
)
|
||||
size_kb = db_path.stat().st_size / 1024
|
||||
conn = sqlite3.connect(str(db_path), timeout=5)
|
||||
count = conn.execute("SELECT count(*) FROM responses").fetchone()[0]
|
||||
conn.close()
|
||||
return CheckResult(
|
||||
name="response_store_db",
|
||||
status="ok",
|
||||
message=f"Response store DB OK ({count} responses, {size_kb:.1f}KB)",
|
||||
value=size_kb,
|
||||
unit="KB",
|
||||
)
|
||||
except Exception as exc:
|
||||
return CheckResult(
|
||||
name="response_store_db",
|
||||
status="error",
|
||||
message=f"Response store DB error: {exc}",
|
||||
)
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Snapshot collector
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def collect_snapshot(cfg: ObservatoryConfig) -> HealthSnapshot:
|
||||
"""Run all checks and return a HealthSnapshot."""
|
||||
ts = datetime.now(timezone.utc).isoformat()
|
||||
checks = [
|
||||
check_gateway_liveness(),
|
||||
check_api_server_http(cfg),
|
||||
check_webhook_http(cfg),
|
||||
check_disk(cfg),
|
||||
check_memory(cfg),
|
||||
check_cpu(cfg),
|
||||
check_database(cfg),
|
||||
check_response_store_db(),
|
||||
]
|
||||
return HealthSnapshot(ts=ts, checks=checks)
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# SQLite persistence
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
@contextmanager
|
||||
def _db(path: Path):
|
||||
path.parent.mkdir(parents=True, exist_ok=True)
|
||||
conn = sqlite3.connect(str(path), timeout=10)
|
||||
conn.execute("PRAGMA journal_mode=WAL")
|
||||
conn.execute("PRAGMA foreign_keys=ON")
|
||||
try:
|
||||
yield conn
|
||||
conn.commit()
|
||||
finally:
|
||||
conn.close()
|
||||
|
||||
|
||||
def _init_db(path: Path) -> None:
|
||||
"""Create tables if they don't exist."""
|
||||
with _db(path) as conn:
|
||||
conn.execute("""
|
||||
CREATE TABLE IF NOT EXISTS health_snapshots (
|
||||
id INTEGER PRIMARY KEY AUTOINCREMENT,
|
||||
ts TEXT NOT NULL,
|
||||
overall TEXT NOT NULL,
|
||||
payload TEXT NOT NULL
|
||||
)
|
||||
""")
|
||||
conn.execute("CREATE INDEX IF NOT EXISTS idx_snapshots_ts ON health_snapshots(ts)")
|
||||
conn.execute("""
|
||||
CREATE TABLE IF NOT EXISTS alerts_sent (
|
||||
id INTEGER PRIMARY KEY AUTOINCREMENT,
|
||||
ts TEXT NOT NULL,
|
||||
check_name TEXT NOT NULL,
|
||||
status TEXT NOT NULL,
|
||||
message TEXT NOT NULL
|
||||
)
|
||||
""")
|
||||
conn.execute("CREATE INDEX IF NOT EXISTS idx_alerts_ts ON alerts_sent(ts)")
|
||||
|
||||
|
||||
def store_snapshot(cfg: ObservatoryConfig, snapshot: HealthSnapshot) -> None:
|
||||
"""Persist snapshot to SQLite."""
|
||||
_init_db(cfg.db_path)
|
||||
payload = json.dumps(snapshot.to_dict())
|
||||
with _db(cfg.db_path) as conn:
|
||||
conn.execute(
|
||||
"INSERT INTO health_snapshots (ts, overall, payload) VALUES (?, ?, ?)",
|
||||
(snapshot.ts, snapshot.overall_status, payload),
|
||||
)
|
||||
# Prune records older than RETENTION_DAYS
|
||||
cutoff = (datetime.now(timezone.utc) - timedelta(days=RETENTION_DAYS)).isoformat()
|
||||
conn.execute("DELETE FROM health_snapshots WHERE ts < ?", (cutoff,))
|
||||
|
||||
|
||||
def record_alert_sent(cfg: ObservatoryConfig, check_name: str, status: str, message: str) -> None:
|
||||
"""Record that an alert was dispatched."""
|
||||
_init_db(cfg.db_path)
|
||||
with _db(cfg.db_path) as conn:
|
||||
conn.execute(
|
||||
"INSERT INTO alerts_sent (ts, check_name, status, message) VALUES (?, ?, ?, ?)",
|
||||
(datetime.now(timezone.utc).isoformat(), check_name, status, message),
|
||||
)
|
||||
|
||||
|
||||
def load_snapshots(cfg: ObservatoryConfig, days: int = RETENTION_DAYS) -> List[Dict[str, Any]]:
|
||||
"""Load snapshots from the last N days."""
|
||||
if not cfg.db_path.exists():
|
||||
return []
|
||||
cutoff = (datetime.now(timezone.utc) - timedelta(days=days)).isoformat()
|
||||
with _db(cfg.db_path) as conn:
|
||||
rows = conn.execute(
|
||||
"SELECT ts, overall, payload FROM health_snapshots WHERE ts >= ? ORDER BY ts DESC",
|
||||
(cutoff,),
|
||||
).fetchall()
|
||||
return [json.loads(row[2]) for row in rows]
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Alerting
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def _telegram_send(token: str, chat_id: str, text: str) -> bool:
|
||||
"""Send a Telegram message via the Bot API. Returns True on success."""
|
||||
url = f"https://api.telegram.org/bot{token}/sendMessage"
|
||||
payload = json.dumps({
|
||||
"chat_id": chat_id,
|
||||
"text": text,
|
||||
"parse_mode": "HTML",
|
||||
"disable_web_page_preview": True,
|
||||
}).encode("utf-8")
|
||||
req = urllib.request.Request(url, data=payload, method="POST")
|
||||
req.add_header("Content-Type", "application/json")
|
||||
req.add_header("User-Agent", "hermes-observatory/1.0")
|
||||
try:
|
||||
with urllib.request.urlopen(req, timeout=15) as resp:
|
||||
body = json.loads(resp.read())
|
||||
return bool(body.get("ok"))
|
||||
except Exception as exc:
|
||||
logger.warning("Telegram send failed: %s", exc)
|
||||
return False
|
||||
|
||||
|
||||
def _status_emoji(status: str) -> str:
|
||||
return {"ok": "✅", "warn": "⚠️", "critical": "🔴", "error": "❌"}.get(status, "❓")
|
||||
|
||||
|
||||
def maybe_alert(cfg: ObservatoryConfig, snapshot: HealthSnapshot, prev_snapshot: Optional[HealthSnapshot]) -> List[str]:
|
||||
"""
|
||||
Fire Telegram alerts for newly degraded checks.
|
||||
Returns list of alert messages sent.
|
||||
"""
|
||||
if not cfg.telegram_token or not cfg.alert_chat_id:
|
||||
return []
|
||||
|
||||
alerts_sent = []
|
||||
prev_statuses: Dict[str, str] = {}
|
||||
if prev_snapshot:
|
||||
for c in prev_snapshot.checks:
|
||||
prev_statuses[c.name] = c.status
|
||||
|
||||
for check in snapshot.checks:
|
||||
if check.status in ("critical", "error"):
|
||||
prev = prev_statuses.get(check.name, "ok")
|
||||
if prev not in ("critical", "error"):
|
||||
# Newly degraded — alert
|
||||
emoji = _status_emoji(check.status)
|
||||
msg = (
|
||||
f"{emoji} <b>Hermes Observatory Alert</b>\n\n"
|
||||
f"<b>Check:</b> {check.name}\n"
|
||||
f"<b>Status:</b> {check.status.upper()}\n"
|
||||
f"<b>Message:</b> {check.message}\n"
|
||||
f"<b>Time:</b> {snapshot.ts}"
|
||||
)
|
||||
if _telegram_send(cfg.telegram_token, cfg.alert_chat_id, msg):
|
||||
alerts_sent.append(msg)
|
||||
record_alert_sent(cfg, check.name, check.status, check.message)
|
||||
logger.info("Alert sent for %s (%s)", check.name, check.status)
|
||||
elif check.status == "ok":
|
||||
prev = prev_statuses.get(check.name)
|
||||
if prev in ("critical", "error"):
|
||||
# Recovery alert
|
||||
msg = (
|
||||
f"✅ <b>Hermes Observatory — Recovery</b>\n\n"
|
||||
f"<b>Check:</b> {check.name} has recovered\n"
|
||||
f"<b>Message:</b> {check.message}\n"
|
||||
f"<b>Time:</b> {snapshot.ts}"
|
||||
)
|
||||
if _telegram_send(cfg.telegram_token, cfg.alert_chat_id, msg):
|
||||
alerts_sent.append(msg)
|
||||
record_alert_sent(cfg, check.name, "recovery", check.message)
|
||||
|
||||
return alerts_sent
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Daily digest
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def build_digest(cfg: ObservatoryConfig) -> str:
|
||||
"""Build a daily health digest from stored snapshots."""
|
||||
snapshots = load_snapshots(cfg, days=1)
|
||||
total = len(snapshots)
|
||||
if total == 0:
|
||||
return "No health data available for the last 24 hours."
|
||||
|
||||
# Count by overall status
|
||||
status_counts: Dict[str, int] = {"ok": 0, "warn": 0, "critical": 0, "error": 0}
|
||||
check_degraded_counts: Dict[str, int] = {}
|
||||
latencies: Dict[str, List[float]] = {}
|
||||
|
||||
for snap in snapshots:
|
||||
overall = snap.get("overall", "ok")
|
||||
status_counts[overall] = status_counts.get(overall, 0) + 1
|
||||
for check in snap.get("checks", []):
|
||||
name = check["name"]
|
||||
status = check["status"]
|
||||
if status in ("critical", "error", "warn"):
|
||||
check_degraded_counts[name] = check_degraded_counts.get(name, 0) + 1
|
||||
value = check.get("value")
|
||||
unit = check.get("unit")
|
||||
if value is not None and unit == "ms":
|
||||
if name not in latencies:
|
||||
latencies[name] = []
|
||||
latencies[name].append(float(value))
|
||||
|
||||
uptime_pct = 100.0 * status_counts["ok"] / total if total else 0.0
|
||||
now = datetime.now(timezone.utc).strftime("%Y-%m-%d %H:%M UTC")
|
||||
|
||||
lines = [
|
||||
f"📊 <b>Hermes Observatory — Daily Digest</b>",
|
||||
f"<b>Generated:</b> {now}",
|
||||
f"",
|
||||
f"<b>Last 24h Summary</b> ({total} samples)",
|
||||
f" Healthy: {status_counts['ok']} ({100*status_counts['ok']//total if total else 0}%)",
|
||||
f" Warning: {status_counts.get('warn', 0)}",
|
||||
f" Critical: {status_counts.get('critical', 0)}",
|
||||
f" Error: {status_counts.get('error', 0)}",
|
||||
f"",
|
||||
]
|
||||
|
||||
# SLO status
|
||||
lines.append("<b>SLO Status</b>")
|
||||
gw_uptime_target = cfg.gateway_uptime_slo_pct
|
||||
gw_snapshots = [
|
||||
s for s in snapshots
|
||||
if any(c["name"] == "gateway_process" and c["status"] == "ok" for c in s.get("checks", []))
|
||||
]
|
||||
gw_uptime = 100.0 * len(gw_snapshots) / total if total else 0.0
|
||||
gw_ok = gw_uptime >= gw_uptime_target
|
||||
lines.append(
|
||||
f" {'✅' if gw_ok else '❌'} Gateway uptime: {gw_uptime:.1f}% (target: ≥{gw_uptime_target}%)"
|
||||
)
|
||||
|
||||
wh_latency_target = cfg.webhook_latency_slo_ms
|
||||
if "webhook_http" in latencies and latencies["webhook_http"]:
|
||||
wh_vals = sorted(latencies["webhook_http"])
|
||||
p95_idx = int(len(wh_vals) * 0.95)
|
||||
p95 = wh_vals[min(p95_idx, len(wh_vals) - 1)]
|
||||
wh_ok = p95 <= wh_latency_target
|
||||
lines.append(
|
||||
f" {'✅' if wh_ok else '❌'} Webhook p95 latency: {p95:.0f}ms (target: ≤{wh_latency_target:.0f}ms)"
|
||||
)
|
||||
else:
|
||||
lines.append(f" ⚫ Webhook latency: no data")
|
||||
|
||||
if "api_server_http" in latencies and latencies["api_server_http"]:
|
||||
api_vals = sorted(latencies["api_server_http"])
|
||||
p95_idx = int(len(api_vals) * 0.95)
|
||||
p95 = api_vals[min(p95_idx, len(api_vals) - 1)]
|
||||
api_ok = p95 <= wh_latency_target
|
||||
lines.append(
|
||||
f" {'✅' if api_ok else '❌'} API server p95 latency: {p95:.0f}ms (target: ≤{wh_latency_target:.0f}ms)"
|
||||
)
|
||||
|
||||
# Top degraded checks
|
||||
if check_degraded_counts:
|
||||
lines.append("")
|
||||
lines.append("<b>Degraded Checks (24h)</b>")
|
||||
for name, count in sorted(check_degraded_counts.items(), key=lambda x: -x[1]):
|
||||
pct = 100 * count // total if total else 0
|
||||
lines.append(f" • {name}: {count} incidents ({pct}%)")
|
||||
|
||||
lines.append("")
|
||||
lines.append(f"<i>Observatory DB: {cfg.db_path}</i>")
|
||||
|
||||
return "\n".join(lines)
|
||||
|
||||
|
||||
def send_digest(cfg: ObservatoryConfig) -> bool:
|
||||
"""Build and send the daily digest to Telegram. Returns True on success."""
|
||||
digest = build_digest(cfg)
|
||||
if cfg.telegram_token and cfg.digest_chat_id:
|
||||
return _telegram_send(cfg.telegram_token, cfg.digest_chat_id, digest)
|
||||
return False
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Display helpers
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
_STATUS_COLORS = {
|
||||
"ok": "\033[32m", # green
|
||||
"warn": "\033[33m", # yellow
|
||||
"critical": "\033[31m", # red
|
||||
"error": "\033[91m", # bright red
|
||||
}
|
||||
_RESET = "\033[0m"
|
||||
|
||||
|
||||
def _color_status(status: str) -> str:
|
||||
c = _STATUS_COLORS.get(status, "")
|
||||
return f"{c}{status.upper()}{_RESET}"
|
||||
|
||||
|
||||
def print_snapshot(snapshot: HealthSnapshot) -> None:
|
||||
overall_color = _STATUS_COLORS.get(snapshot.overall_status, "")
|
||||
print(f"\n{'='*60}")
|
||||
print(f" Hermes Observatory — {snapshot.ts}")
|
||||
print(f" Overall: {overall_color}{snapshot.overall_status.upper()}{_RESET}")
|
||||
print(f"{'='*60}")
|
||||
for check in snapshot.checks:
|
||||
emoji = _status_emoji(check.status)
|
||||
val_str = f" [{check.value:.1f}{check.unit}]" if check.value is not None and check.unit else ""
|
||||
print(f" {emoji} {check.name:<25} {_color_status(check.status):<15} {check.message}{val_str}")
|
||||
print()
|
||||
|
||||
|
||||
def print_slo_report(cfg: ObservatoryConfig) -> None:
|
||||
"""Print current SLO definitions and targets."""
|
||||
snapshots = load_snapshots(cfg, days=30)
|
||||
total = len(snapshots)
|
||||
print(f"\n{'='*60}")
|
||||
print(" Hermes Observatory — SLO Report (last 30 days)")
|
||||
print(f"{'='*60}")
|
||||
for slo_key, slo in SLO_DEFINITIONS.items():
|
||||
print(f"\n {slo['description']}")
|
||||
print(f" Target: {slo['target']}{slo['unit']}")
|
||||
if total == 0:
|
||||
print(f" Status: no data")
|
||||
continue
|
||||
if slo_key == "gateway_uptime_pct":
|
||||
ok_count = sum(
|
||||
1 for s in snapshots
|
||||
if any(c["name"] == "gateway_process" and c["status"] == "ok"
|
||||
for c in s.get("checks", []))
|
||||
)
|
||||
actual = 100.0 * ok_count / total
|
||||
met = actual >= slo["target"]
|
||||
print(f" Actual: {actual:.2f}% {'✅ MET' if met else '❌ MISSED'}")
|
||||
elif slo_key in ("webhook_latency_ms", "api_server_http_latency_ms"):
|
||||
check_name = "webhook_http" if "webhook" in slo_key else "api_server_http"
|
||||
vals = [
|
||||
float(c["value"])
|
||||
for s in snapshots
|
||||
for c in s.get("checks", [])
|
||||
if c["name"] == check_name and c.get("value") is not None
|
||||
]
|
||||
if vals:
|
||||
vals.sort()
|
||||
p95_idx = int(len(vals) * 0.95)
|
||||
p95 = vals[min(p95_idx, len(vals) - 1)]
|
||||
met = p95 <= slo["target"]
|
||||
print(f" p95: {p95:.0f}ms {'✅ MET' if met else '❌ MISSED'}")
|
||||
else:
|
||||
print(f" Status: no latency data")
|
||||
print()
|
||||
|
||||
|
||||
def print_history(cfg: ObservatoryConfig, count: int = 20) -> None:
|
||||
"""Print recent health records."""
|
||||
snapshots = load_snapshots(cfg, days=RETENTION_DAYS)[:count]
|
||||
if not snapshots:
|
||||
print("No history available.")
|
||||
return
|
||||
print(f"\n{'='*60}")
|
||||
print(f" Last {min(count, len(snapshots))} health records")
|
||||
print(f"{'='*60}")
|
||||
for snap in snapshots:
|
||||
ts = snap.get("ts", "?")
|
||||
overall = snap.get("overall", "?")
|
||||
emoji = _status_emoji(overall)
|
||||
degraded = [c["name"] for c in snap.get("checks", []) if c["status"] != "ok"]
|
||||
degraded_str = f" — issues: {', '.join(degraded)}" if degraded else ""
|
||||
print(f" {emoji} {ts} {overall.upper()}{degraded_str}")
|
||||
print()
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Daemon mode
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class Observatory:
|
||||
"""Continuous monitoring daemon."""
|
||||
|
||||
def __init__(self, cfg: ObservatoryConfig):
|
||||
self.cfg = cfg
|
||||
self._running = False
|
||||
self._prev_snapshot: Optional[HealthSnapshot] = None
|
||||
|
||||
def _handle_signal(self, signum: int, frame: Any) -> None:
|
||||
logger.info("Received signal %d, shutting down...", signum)
|
||||
self._running = False
|
||||
|
||||
def run_once(self) -> HealthSnapshot:
|
||||
snapshot = collect_snapshot(self.cfg)
|
||||
store_snapshot(self.cfg, snapshot)
|
||||
alerts = maybe_alert(self.cfg, snapshot, self._prev_snapshot)
|
||||
if alerts:
|
||||
logger.info("Sent %d alert(s)", len(alerts))
|
||||
self._prev_snapshot = snapshot
|
||||
return snapshot
|
||||
|
||||
def run(self) -> None:
|
||||
_init_db(self.cfg.db_path)
|
||||
logger.info(
|
||||
"Observatory starting — poll_interval=%ds db=%s",
|
||||
self.cfg.poll_interval,
|
||||
self.cfg.db_path,
|
||||
)
|
||||
self._running = True
|
||||
signal.signal(signal.SIGINT, self._handle_signal)
|
||||
signal.signal(signal.SIGTERM, self._handle_signal)
|
||||
|
||||
while self._running:
|
||||
try:
|
||||
snapshot = self.run_once()
|
||||
logger.info("Health check: %s", snapshot.overall_status)
|
||||
except Exception as exc:
|
||||
logger.error("Health check failed: %s", exc, exc_info=True)
|
||||
if self._running:
|
||||
time.sleep(self.cfg.poll_interval)
|
||||
|
||||
logger.info("Observatory stopped.")
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# CLI entry point
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def main(argv: Optional[List[str]] = None) -> int:
|
||||
parser = argparse.ArgumentParser(
|
||||
description="Hermes Observatory — health monitoring & alerting",
|
||||
formatter_class=argparse.RawDescriptionHelpFormatter,
|
||||
)
|
||||
parser.add_argument("--check", action="store_true", help="Run one health check and print results")
|
||||
parser.add_argument("--daemon", action="store_true", help="Run as continuous monitoring daemon")
|
||||
parser.add_argument("--digest", action="store_true", help="Print (and optionally send) daily digest")
|
||||
parser.add_argument("--history", type=int, metavar="N", help="Show last N health records")
|
||||
parser.add_argument("--slo", action="store_true", help="Print SLO report")
|
||||
parser.add_argument("--send-digest", action="store_true", help="Send daily digest via Telegram")
|
||||
parser.add_argument("--verbose", "-v", action="store_true", help="Enable verbose logging")
|
||||
|
||||
args = parser.parse_args(argv)
|
||||
|
||||
logging.basicConfig(
|
||||
level=logging.DEBUG if args.verbose else logging.INFO,
|
||||
format="%(asctime)s %(levelname)s [observatory] %(message)s",
|
||||
)
|
||||
|
||||
cfg = ObservatoryConfig.from_env()
|
||||
_init_db(cfg.db_path)
|
||||
|
||||
if args.check:
|
||||
snapshot = collect_snapshot(cfg)
|
||||
store_snapshot(cfg, snapshot)
|
||||
print_snapshot(snapshot)
|
||||
return 0 if snapshot.overall_status == "ok" else 1
|
||||
|
||||
if args.daemon:
|
||||
obs = Observatory(cfg)
|
||||
obs.run()
|
||||
return 0
|
||||
|
||||
if args.digest or args.send_digest:
|
||||
digest = build_digest(cfg)
|
||||
print(digest)
|
||||
if args.send_digest:
|
||||
ok = send_digest(cfg)
|
||||
if ok:
|
||||
print("\n[Digest sent to Telegram]")
|
||||
else:
|
||||
print("\n[Telegram send skipped — token/chat_id not configured]")
|
||||
return 0
|
||||
|
||||
if args.history is not None:
|
||||
print_history(cfg, args.history)
|
||||
return 0
|
||||
|
||||
if args.slo:
|
||||
print_slo_report(cfg)
|
||||
return 0
|
||||
|
||||
# Default: one-shot check
|
||||
snapshot = collect_snapshot(cfg)
|
||||
store_snapshot(cfg, snapshot)
|
||||
print_snapshot(snapshot)
|
||||
return 0 if snapshot.overall_status == "ok" else 1
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
sys.exit(main())
|
||||
@@ -42,6 +42,7 @@ dependencies = [
|
||||
modal = ["modal>=1.0.0,<2"]
|
||||
daytona = ["daytona>=0.148.0,<1"]
|
||||
dev = ["pytest>=9.0.2,<10", "pytest-asyncio>=1.3.0,<2", "pytest-xdist>=3.0,<4", "mcp>=1.2.0,<2"]
|
||||
observatory = ["psutil>=5.9.0,<7"]
|
||||
messaging = ["python-telegram-bot>=22.6,<23", "discord.py[voice]>=2.7.1,<3", "aiohttp>=3.13.3,<4", "slack-bolt>=1.18.0,<2", "slack-sdk>=3.27.0,<4"]
|
||||
cron = ["croniter>=6.0.0,<7"]
|
||||
slack = ["slack-bolt>=1.18.0,<2", "slack-sdk>=3.27.0,<4"]
|
||||
|
||||
455
tests/test_observatory.py
Normal file
455
tests/test_observatory.py
Normal file
@@ -0,0 +1,455 @@
|
||||
"""
|
||||
Tests for observatory.py — health monitoring & alerting.
|
||||
|
||||
Refs #147
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import os
|
||||
import sqlite3
|
||||
import sys
|
||||
import tempfile
|
||||
import time
|
||||
from pathlib import Path
|
||||
from typing import Any
|
||||
from unittest.mock import MagicMock, patch
|
||||
|
||||
import pytest
|
||||
|
||||
PROJECT_ROOT = Path(__file__).parent.parent
|
||||
if str(PROJECT_ROOT) not in sys.path:
|
||||
sys.path.insert(0, str(PROJECT_ROOT))
|
||||
|
||||
import observatory as obs
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Fixtures
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
@pytest.fixture
|
||||
def cfg(tmp_path):
|
||||
"""Return an ObservatoryConfig pointing at a temp directory."""
|
||||
cfg = obs.ObservatoryConfig()
|
||||
cfg.db_path = tmp_path / "observatory.db"
|
||||
cfg.alert_chat_id = "99999"
|
||||
cfg.digest_chat_id = "99999"
|
||||
cfg.telegram_token = "fake-token"
|
||||
cfg.webhook_url = "http://127.0.0.1:19999/health" # port never bound
|
||||
cfg.api_url = "http://127.0.0.1:19998/health"
|
||||
return cfg
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Config tests
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class TestObservatoryConfig:
|
||||
def test_defaults(self):
|
||||
c = obs.ObservatoryConfig()
|
||||
assert c.disk_warn_pct == 80.0
|
||||
assert c.disk_crit_pct == 90.0
|
||||
assert c.mem_warn_pct == 80.0
|
||||
assert c.mem_crit_pct == 90.0
|
||||
assert c.cpu_warn_pct == 80.0
|
||||
assert c.cpu_crit_pct == 95.0
|
||||
assert c.poll_interval == 60
|
||||
assert c.webhook_latency_slo_ms == 2000.0
|
||||
assert c.gateway_uptime_slo_pct == 99.5
|
||||
|
||||
def test_from_env_overrides(self, monkeypatch):
|
||||
monkeypatch.setenv("OBSERVATORY_DISK_WARN_PCT", "70")
|
||||
monkeypatch.setenv("OBSERVATORY_POLL_INTERVAL", "30")
|
||||
monkeypatch.setenv("OBSERVATORY_ALERT_CHAT_ID", "12345")
|
||||
monkeypatch.setenv("TELEGRAM_BOT_TOKEN", "tok123")
|
||||
c = obs.ObservatoryConfig.from_env()
|
||||
assert c.disk_warn_pct == 70.0
|
||||
assert c.poll_interval == 30
|
||||
assert c.alert_chat_id == "12345"
|
||||
assert c.telegram_token == "tok123"
|
||||
|
||||
def test_digest_chat_falls_back_to_alert(self, monkeypatch):
|
||||
monkeypatch.setenv("OBSERVATORY_ALERT_CHAT_ID", "abc")
|
||||
monkeypatch.delenv("OBSERVATORY_DIGEST_CHAT_ID", raising=False)
|
||||
c = obs.ObservatoryConfig.from_env()
|
||||
assert c.digest_chat_id == "abc"
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# CheckResult / HealthSnapshot tests
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class TestHealthSnapshot:
|
||||
def _make_snapshot(self, statuses):
|
||||
checks = [obs.CheckResult(name=f"c{i}", status=s, message="") for i, s in enumerate(statuses)]
|
||||
return obs.HealthSnapshot(ts="2026-01-01T00:00:00+00:00", checks=checks)
|
||||
|
||||
def test_overall_ok(self):
|
||||
snap = self._make_snapshot(["ok", "ok"])
|
||||
assert snap.overall_status == "ok"
|
||||
|
||||
def test_overall_warn(self):
|
||||
snap = self._make_snapshot(["ok", "warn"])
|
||||
assert snap.overall_status == "warn"
|
||||
|
||||
def test_overall_critical(self):
|
||||
snap = self._make_snapshot(["ok", "warn", "critical"])
|
||||
assert snap.overall_status == "critical"
|
||||
|
||||
def test_overall_error(self):
|
||||
snap = self._make_snapshot(["ok", "error"])
|
||||
assert snap.overall_status == "critical"
|
||||
|
||||
def test_to_dict(self):
|
||||
snap = self._make_snapshot(["ok"])
|
||||
d = snap.to_dict()
|
||||
assert d["overall"] == "ok"
|
||||
assert isinstance(d["checks"], list)
|
||||
assert d["checks"][0]["name"] == "c0"
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Individual check tests
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class TestCheckGatewayLiveness:
|
||||
def test_running(self):
|
||||
with patch("gateway.status.is_gateway_running", return_value=True), \
|
||||
patch("gateway.status.get_running_pid", return_value=12345):
|
||||
result = obs.check_gateway_liveness()
|
||||
assert result.status == "ok"
|
||||
assert "12345" in result.message
|
||||
|
||||
def test_not_running(self):
|
||||
with patch("gateway.status.is_gateway_running", return_value=False), \
|
||||
patch("gateway.status.get_running_pid", return_value=None):
|
||||
result = obs.check_gateway_liveness()
|
||||
assert result.status == "critical"
|
||||
|
||||
def test_import_error(self):
|
||||
import builtins
|
||||
real_import = builtins.__import__
|
||||
|
||||
def mock_import(name, *args, **kwargs):
|
||||
if name == "gateway.status":
|
||||
raise ImportError("no module")
|
||||
return real_import(name, *args, **kwargs)
|
||||
|
||||
with patch("builtins.__import__", side_effect=mock_import):
|
||||
result = obs.check_gateway_liveness()
|
||||
assert result.status in ("error", "critical", "ok") # graceful
|
||||
|
||||
|
||||
class TestCheckDisk:
|
||||
def test_ok(self, cfg):
|
||||
mock_usage = MagicMock()
|
||||
mock_usage.percent = 50.0
|
||||
mock_usage.free = 10 * 1024 ** 3
|
||||
mock_usage.total = 20 * 1024 ** 3
|
||||
with patch("psutil.disk_usage", return_value=mock_usage):
|
||||
result = obs.check_disk(cfg)
|
||||
assert result.status == "ok"
|
||||
assert result.value == 50.0
|
||||
|
||||
def test_warn(self, cfg):
|
||||
mock_usage = MagicMock()
|
||||
mock_usage.percent = 85.0
|
||||
mock_usage.free = 3 * 1024 ** 3
|
||||
mock_usage.total = 20 * 1024 ** 3
|
||||
with patch("psutil.disk_usage", return_value=mock_usage):
|
||||
result = obs.check_disk(cfg)
|
||||
assert result.status == "warn"
|
||||
|
||||
def test_critical(self, cfg):
|
||||
mock_usage = MagicMock()
|
||||
mock_usage.percent = 92.0
|
||||
mock_usage.free = 1 * 1024 ** 3
|
||||
mock_usage.total = 20 * 1024 ** 3
|
||||
with patch("psutil.disk_usage", return_value=mock_usage):
|
||||
result = obs.check_disk(cfg)
|
||||
assert result.status == "critical"
|
||||
|
||||
def test_no_psutil(self, cfg, monkeypatch):
|
||||
monkeypatch.setattr(obs, "_PSUTIL", False)
|
||||
result = obs.check_disk(cfg)
|
||||
assert result.status == "error"
|
||||
|
||||
|
||||
class TestCheckMemory:
|
||||
def test_ok(self, cfg):
|
||||
mock_mem = MagicMock()
|
||||
mock_mem.percent = 60.0
|
||||
mock_mem.available = 4 * 1024 ** 3
|
||||
mock_mem.total = 16 * 1024 ** 3
|
||||
with patch("psutil.virtual_memory", return_value=mock_mem):
|
||||
result = obs.check_memory(cfg)
|
||||
assert result.status == "ok"
|
||||
|
||||
def test_critical(self, cfg):
|
||||
mock_mem = MagicMock()
|
||||
mock_mem.percent = 95.0
|
||||
mock_mem.available = 512 * 1024 ** 2
|
||||
mock_mem.total = 16 * 1024 ** 3
|
||||
with patch("psutil.virtual_memory", return_value=mock_mem):
|
||||
result = obs.check_memory(cfg)
|
||||
assert result.status == "critical"
|
||||
|
||||
|
||||
class TestCheckCPU:
|
||||
def test_ok(self, cfg):
|
||||
with patch("psutil.cpu_percent", return_value=40.0):
|
||||
result = obs.check_cpu(cfg)
|
||||
assert result.status == "ok"
|
||||
|
||||
def test_warn(self, cfg):
|
||||
with patch("psutil.cpu_percent", return_value=85.0):
|
||||
result = obs.check_cpu(cfg)
|
||||
assert result.status == "warn"
|
||||
|
||||
def test_critical(self, cfg):
|
||||
with patch("psutil.cpu_percent", return_value=98.0):
|
||||
result = obs.check_cpu(cfg)
|
||||
assert result.status == "critical"
|
||||
|
||||
|
||||
class TestCheckDatabase:
|
||||
def test_ok(self, cfg):
|
||||
obs._init_db(cfg.db_path)
|
||||
result = obs.check_database(cfg)
|
||||
assert result.status == "ok"
|
||||
|
||||
def test_not_yet_created(self, cfg):
|
||||
# db_path does not exist
|
||||
result = obs.check_database(cfg)
|
||||
assert result.status == "warn"
|
||||
|
||||
|
||||
class TestCheckHTTP:
|
||||
def test_webhook_connection_refused(self, cfg):
|
||||
result = obs.check_webhook_http(cfg)
|
||||
# Port 19999 is not bound — should get a "not reachable" warn
|
||||
assert result.status in ("warn", "error")
|
||||
|
||||
def test_api_server_connection_refused(self, cfg):
|
||||
result = obs.check_api_server_http(cfg)
|
||||
assert result.status in ("warn", "error")
|
||||
|
||||
def test_webhook_ok(self, cfg):
|
||||
import urllib.error
|
||||
from unittest.mock import patch, MagicMock
|
||||
mock_resp = MagicMock()
|
||||
mock_resp.__enter__ = lambda s: s
|
||||
mock_resp.__exit__ = MagicMock(return_value=False)
|
||||
mock_resp.status = 200
|
||||
mock_resp.read.return_value = b'{"status":"ok"}'
|
||||
with patch("urllib.request.urlopen", return_value=mock_resp):
|
||||
result = obs.check_webhook_http(cfg)
|
||||
assert result.status in ("ok", "warn")
|
||||
|
||||
def test_webhook_http_error(self, cfg):
|
||||
mock_resp = MagicMock()
|
||||
mock_resp.__enter__ = lambda s: s
|
||||
mock_resp.__exit__ = MagicMock(return_value=False)
|
||||
mock_resp.status = 503
|
||||
with patch("urllib.request.urlopen", return_value=mock_resp):
|
||||
result = obs.check_webhook_http(cfg)
|
||||
assert result.status == "critical"
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Persistence tests
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class TestPersistence:
|
||||
def test_store_and_load(self, cfg):
|
||||
obs._init_db(cfg.db_path)
|
||||
from datetime import datetime, timezone
|
||||
ts = datetime.now(timezone.utc).isoformat()
|
||||
snap = obs.HealthSnapshot(
|
||||
ts=ts,
|
||||
checks=[obs.CheckResult(name="test", status="ok", message="fine")],
|
||||
)
|
||||
obs.store_snapshot(cfg, snap)
|
||||
loaded = obs.load_snapshots(cfg, days=30)
|
||||
assert len(loaded) == 1
|
||||
assert loaded[0]["overall"] == "ok"
|
||||
|
||||
def test_retention_pruning(self, cfg):
|
||||
obs._init_db(cfg.db_path)
|
||||
# Insert an old record directly
|
||||
with obs._db(cfg.db_path) as conn:
|
||||
conn.execute(
|
||||
"INSERT INTO health_snapshots (ts, overall, payload) VALUES (?, ?, ?)",
|
||||
("2000-01-01T00:00:00+00:00", "ok", '{"ts":"2000-01-01T00:00:00+00:00","overall":"ok","checks":[]}'),
|
||||
)
|
||||
snap = obs.HealthSnapshot(
|
||||
ts="2026-01-01T00:00:00+00:00",
|
||||
checks=[],
|
||||
)
|
||||
obs.store_snapshot(cfg, snap)
|
||||
# Old record should have been pruned
|
||||
with obs._db(cfg.db_path) as conn:
|
||||
count = conn.execute("SELECT count(*) FROM health_snapshots WHERE ts < '2001-01-01'").fetchone()[0]
|
||||
assert count == 0
|
||||
|
||||
def test_record_alert_sent(self, cfg):
|
||||
obs._init_db(cfg.db_path)
|
||||
obs.record_alert_sent(cfg, "gateway_process", "critical", "not running")
|
||||
with obs._db(cfg.db_path) as conn:
|
||||
count = conn.execute("SELECT count(*) FROM alerts_sent").fetchone()[0]
|
||||
assert count == 1
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Alerting tests
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class TestAlerting:
|
||||
def _snap(self, status):
|
||||
return obs.HealthSnapshot(
|
||||
ts="2026-01-01T00:00:00+00:00",
|
||||
checks=[obs.CheckResult(name="gateway_process", status=status, message="test")],
|
||||
)
|
||||
|
||||
def test_no_alert_when_ok(self, cfg):
|
||||
snap = self._snap("ok")
|
||||
prev = self._snap("ok")
|
||||
obs._init_db(cfg.db_path)
|
||||
with patch("observatory._telegram_send", return_value=True) as mock_send:
|
||||
alerts = obs.maybe_alert(cfg, snap, prev)
|
||||
mock_send.assert_not_called()
|
||||
assert alerts == []
|
||||
|
||||
def test_alert_on_new_critical(self, cfg):
|
||||
snap = self._snap("critical")
|
||||
prev = self._snap("ok")
|
||||
obs._init_db(cfg.db_path)
|
||||
with patch("observatory._telegram_send", return_value=True) as mock_send:
|
||||
alerts = obs.maybe_alert(cfg, snap, prev)
|
||||
mock_send.assert_called_once()
|
||||
assert len(alerts) == 1
|
||||
|
||||
def test_no_duplicate_alert(self, cfg):
|
||||
snap = self._snap("critical")
|
||||
prev = self._snap("critical") # already critical
|
||||
obs._init_db(cfg.db_path)
|
||||
with patch("observatory._telegram_send", return_value=True) as mock_send:
|
||||
alerts = obs.maybe_alert(cfg, snap, prev)
|
||||
mock_send.assert_not_called()
|
||||
assert alerts == []
|
||||
|
||||
def test_recovery_alert(self, cfg):
|
||||
snap = self._snap("ok")
|
||||
prev = self._snap("critical")
|
||||
obs._init_db(cfg.db_path)
|
||||
with patch("observatory._telegram_send", return_value=True) as mock_send:
|
||||
alerts = obs.maybe_alert(cfg, snap, prev)
|
||||
mock_send.assert_called_once()
|
||||
|
||||
def test_no_alert_without_token(self, cfg):
|
||||
cfg.telegram_token = None
|
||||
snap = self._snap("critical")
|
||||
obs._init_db(cfg.db_path)
|
||||
alerts = obs.maybe_alert(cfg, snap, None)
|
||||
assert alerts == []
|
||||
|
||||
def test_no_alert_without_chat_id(self, cfg):
|
||||
cfg.alert_chat_id = None
|
||||
snap = self._snap("critical")
|
||||
obs._init_db(cfg.db_path)
|
||||
alerts = obs.maybe_alert(cfg, snap, None)
|
||||
assert alerts == []
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Digest tests
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class TestDigest:
|
||||
def test_empty_digest(self, cfg):
|
||||
obs._init_db(cfg.db_path)
|
||||
digest = obs.build_digest(cfg)
|
||||
assert "no health data" in digest.lower() or "24 hours" in digest.lower()
|
||||
|
||||
def test_digest_with_data(self, cfg):
|
||||
obs._init_db(cfg.db_path)
|
||||
from datetime import datetime, timezone, timedelta
|
||||
ts = (datetime.now(timezone.utc) - timedelta(hours=1)).isoformat()
|
||||
snap = obs.HealthSnapshot(
|
||||
ts=ts,
|
||||
checks=[
|
||||
obs.CheckResult(name="gateway_process", status="ok", message="running"),
|
||||
obs.CheckResult(name="disk", status="ok", message="50% used", value=50.0, unit="%"),
|
||||
obs.CheckResult(name="webhook_http", status="ok", message="ok", value=150.0, unit="ms"),
|
||||
],
|
||||
)
|
||||
obs.store_snapshot(cfg, snap)
|
||||
digest = obs.build_digest(cfg)
|
||||
assert "Daily Digest" in digest
|
||||
assert "Gateway" in digest or "gateway" in digest
|
||||
|
||||
def test_send_digest_no_token(self, cfg):
|
||||
cfg.telegram_token = None
|
||||
obs._init_db(cfg.db_path)
|
||||
result = obs.send_digest(cfg)
|
||||
assert result is False
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# SLO tests
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class TestSLO:
|
||||
def test_slo_definitions_complete(self):
|
||||
assert "gateway_uptime_pct" in obs.SLO_DEFINITIONS
|
||||
assert "webhook_latency_ms" in obs.SLO_DEFINITIONS
|
||||
assert "api_server_latency_ms" in obs.SLO_DEFINITIONS
|
||||
|
||||
def test_slo_targets(self):
|
||||
assert obs.SLO_DEFINITIONS["gateway_uptime_pct"]["target"] == 99.5
|
||||
assert obs.SLO_DEFINITIONS["webhook_latency_ms"]["target"] == 2000
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# CLI tests
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class TestCLI:
|
||||
def test_check_exits_0_on_ok(self, cfg, monkeypatch, tmp_path):
|
||||
monkeypatch.setenv("OBSERVATORY_DB_PATH", str(tmp_path / "obs.db"))
|
||||
ok_snap = obs.HealthSnapshot(
|
||||
ts="2026-01-01T00:00:00+00:00",
|
||||
checks=[obs.CheckResult(name="all_good", status="ok", message="fine")],
|
||||
)
|
||||
with patch("observatory.collect_snapshot", return_value=ok_snap), \
|
||||
patch("observatory.store_snapshot"):
|
||||
rc = obs.main(["--check"])
|
||||
assert rc == 0
|
||||
|
||||
def test_check_exits_nonzero_on_critical(self, cfg, monkeypatch, tmp_path):
|
||||
monkeypatch.setenv("OBSERVATORY_DB_PATH", str(tmp_path / "obs.db"))
|
||||
bad_snap = obs.HealthSnapshot(
|
||||
ts="2026-01-01T00:00:00+00:00",
|
||||
checks=[obs.CheckResult(name="gateway_process", status="critical", message="down")],
|
||||
)
|
||||
with patch("observatory.collect_snapshot", return_value=bad_snap), \
|
||||
patch("observatory.store_snapshot"):
|
||||
rc = obs.main(["--check"])
|
||||
assert rc != 0
|
||||
|
||||
def test_digest_flag(self, monkeypatch, tmp_path):
|
||||
monkeypatch.setenv("OBSERVATORY_DB_PATH", str(tmp_path / "obs.db"))
|
||||
rc = obs.main(["--digest"])
|
||||
assert rc == 0
|
||||
|
||||
def test_slo_flag(self, monkeypatch, tmp_path):
|
||||
monkeypatch.setenv("OBSERVATORY_DB_PATH", str(tmp_path / "obs.db"))
|
||||
rc = obs.main(["--slo"])
|
||||
assert rc == 0
|
||||
|
||||
def test_history_flag(self, monkeypatch, tmp_path):
|
||||
monkeypatch.setenv("OBSERVATORY_DB_PATH", str(tmp_path / "obs.db"))
|
||||
rc = obs.main(["--history", "5"])
|
||||
assert rc == 0
|
||||
Reference in New Issue
Block a user