'
'')
# ── Quiz Generator ────────────────────────────────────────────────────
def _generate_quiz(self, html_path, json_path, title, agent_name, parsed):
import html as htmlmod, json as jsonmod
# Get quiz questions from parsed or generate from sections
quiz_questions = parsed.get('quiz_questions', [])
if not quiz_questions:
sections = parsed.get('docx_content', {}).get('sections', [])
for i, s in enumerate(sections[:8]):
heading = s.get('heading', f'Sectie {i+1}')
body = s.get('body', '')[:200]
quiz_questions.append({
'question': f'Welke uitspraak is correct over "{heading}"?',
'options': [
f'Dit onderwerp valt onder de HSEQ-wetgeving',
f'Dit is een optionele richtlijn zonder verplichtingen',
f'Dit onderwerp is alleen relevant voor offshore operaties',
f'Dit onderwerp heeft geen relatie met veiligheidsmanagement'
],
'correct': 0,
'explanation': f'{heading}: {body[:100]}...'
})
while len(quiz_questions) < 6:
quiz_questions.append({
'question': f'Vraag {len(quiz_questions)+1} over {title}',
'options': ['Optie A', 'Optie B', 'Optie C', 'Optie D'],
'correct': 0,
'explanation': 'Raadpleeg het studiemateriaal voor het juiste antwoord.'
})
quiz_data = {'title': f'Quiz: {title}', 'questions': quiz_questions[:10], 'passing_score': 70}
with open(json_path, 'w', encoding='utf-8') as f:
jsonmod.dump(quiz_data, f, ensure_ascii=False, indent=2)
# Generate HTML
questions_js = jsonmod.dumps(quiz_questions[:10], ensure_ascii=False)
quiz_html = f'''
Quiz: {htmlmod.escape(title)}
', html, flags=re.MULTILINE)
html = re.sub(r'^> \s*ℹ️\s*(.+)$', r'
ℹ️ \1
', html, flags=re.MULTILINE)
html = re.sub(r'^> \s*✅\s*(.+)$', r'
✅ \1
', html, flags=re.MULTILINE)
html = re.sub(r'^> \s*🔴\s*(.+)$', r'
🔴 \1
', html, flags=re.MULTILINE)
html = re.sub(r'^> (.+)$', r'
\1
', html, flags=re.MULTILINE)
# Headers
html = re.sub(r'^### (.+)$', r'
\1
', html, flags=re.MULTILINE)
html = re.sub(r'^## (.+)$', r'
\1
', html, flags=re.MULTILINE)
html = re.sub(r'^# (.+)$', r'
\1
', html, flags=re.MULTILINE)
# Inline
html = re.sub(r'\*\*(.+?)\*\*', r'\1', html)
html = re.sub(r'\*(.+?)\*', r'\1', html)
# Tables
lines = html.split('\n')
in_table = False
tbl = []
out = []
for line in lines:
if '|' in line and not line.strip().startswith('<'):
cells = [c.strip() for c in line.split('|')[1:-1]]
if all(set(c) <= {'-', ' ', ':'} for c in cells):
continue
if not in_table:
tbl = ['
', '
' + ''.join(f'
{c}
' for c in cells) + '
']
in_table = True
else:
tbl.append('
' + ''.join(f'
{c}
' for c in cells) + '
')
else:
if in_table:
tbl.append('
')
out.append('\n'.join(tbl))
tbl = []
in_table = False
out.append(line)
if in_table:
tbl.append('')
out.append('\n'.join(tbl))
html = '\n'.join(out)
# Lists
html = re.sub(r'^- (.+)$', r'
\1
', html, flags=re.MULTILINE)
html = re.sub(r'^(\d+)\. (.+)$', r'
\2
', html, flags=re.MULTILINE)
html = re.sub(r'((?:
.*
\n?)+)', r'
\1
', html)
return html
# ── Build System Prompt ────────────────────────────────────────────────
def _build_prompt(self, agent_id, workflow_id, task_desc, context, metadata_json):
personality = AGENT_PERSONALITIES.get(agent_id, DEFAULT_PERSONALITY)
# Load MASTER_SOP context
sop_context = ''
try:
sop_path = '/root/projects/jg/MASTER_SOP.md'
if os.path.exists(sop_path):
with open(sop_path, 'r', encoding='utf-8') as f:
content = f.read()
# Extract §3.5 Deliverables Matrix
start = content.find('### 3.5 Standaard Deliverables Matrix')
if start >= 0:
sop_context = content[start:start+2000]
else:
sop_context = content[:2000]
except Exception:
pass
system = f"""{personality}
## [DELIVERABLE FORMAT — ZERO TOLERANCE]
VERBODEN: Lever GEEN platte Markdown-tekst als eindresultaat.
VERPLICHT: Je output MOET een geldig JSON-object zijn dat door de backend wordt omgezet naar fysieke documenten (DOCX + XLSX + HTML + PPTX).
## MASTER_SOP §3.5 — DELIVERABLES MATRIX
{sop_context}
## GOLDEN STANDARD (NON-ONDERBARELIJK)
1. **Feitelijk** — Geen aannames, geen verzonnen data
2. **Beknopt** — Direct to the point
3. **Hyper-professioneel** — Shell/Arcadis niveau
4. **Autoritair** — Je bent de expert
5. **Gestructureerd** — Headers, tabellen, bullets
6. **Actiegericht** — Elk advies eindigt met concrete acties
## JvG BRANDING & DOCUMENT STANDARDS (VERPLICHT)
- **Document-ID**: JvG-[TYPE]-[JAAR]-[NUMMER] — VERPLICHT in titel
- **JvG Consultancy header** in elk document (eerste sectie)
- **Kleur**: #003366 primair
- **Minimaal 6 secties** in docx_content
- **Tabellen**: REALISTIEKE data — geen placeholder, geen "..."
- **Verplichte secties**: Inleiding, Scope, Analyse, Advies, Acties, Referenties
## VERPLICHT: SST PROTOCOL (MASTER_SOP §14.2)
Activeer direct §3.5 (Deliverables Matrix) en §14.2 (SST Protocol) uit de MASTER_SOP.
Je output moet identiek zijn aan een project dat via de Director in Telegram wordt gestart.
## JSON-OUTPUT STRUCTUUR (COMPACT — VERPLICHT)
Retourneer ALLEEN deze velden:
- "title": string (documenttitel)
- "docx_content": {{"sections": [{{"heading": "...", "body": "..."}}]}}
- "xlsx_tables": {{"tabel_naam": {{"headers": [...], "rows": [[...]]}}}}
- "quiz_questions": [{{"question": "...", "options": ["A","B","C","D"], "correct": 0, "explanation": "..."}}] (max 6 vragen)
NIET RETOURNEREN (backend genereert deze automatisch): elearning_pages, kennisdossier_sections, tables_for_html, scorm
BELANGRIJK:
- De JSON MOET geldig zijn (geen syntax errors)
- Alle tekst in Nederlands
- Minimaal 5-6 secties in docx_content met realistische inhoud
- Tabellen minimaal 5-8 rijen
- Body-tekst mag Markdown bevatten (##, **, -, |)
- DATUMS in de toekomst. NOOIT datums in het verleden.
- docx_content VERPLICHT — minimaal 3 secties
## TAAK
Je ontvangt een taak van JvG Consultancy (HSEQ consultancy, olie/gas/petrochemie/offshore).
De deliverable moet direct bruikbaar zijn voor een professionele HSEQ consultant.
Taal: Nederlands."""
# User message
user_parts = []
if workflow_id and workflow_id in WORKFLOW_PROMPTS:
user_parts.append(WORKFLOW_PROMPTS[workflow_id])
else:
user_parts.append(DIRECT_TASK_PROMPT)
if context:
user_parts.append(f"\n## Input Data\n{context}")
else:
user_parts.append(f"\n## Taak\n{task_desc}")
# KB context
if metadata_json:
try:
meta = json.loads(metadata_json)
kb = meta.get('kb_context', '')
if kb:
user_parts.append(f"\n## Relevante Kennisbank Extracten\n{kb[:3000]}")
except (json.JSONDecodeError, TypeError):
pass
return {'system': system, 'user': '\n'.join(user_parts)}
# ── AI Call ────────────────────────────────────────────────────────────
def _ai_call(self, messages, max_retries=3):
for attempt in range(max_retries):
try:
payload = json.dumps({
"model": AI_MODEL,
"messages": messages,
"stream": False,
"temperature": 0.7,
"max_tokens": 8000
}).encode('utf-8')
req = urllib.request.Request(AI_API_URL, data=payload, headers={
"Content-Type": "application/json",
"Authorization": f"Bearer {AI_API_KEY}"
})
ctx = ssl.create_default_context()
ctx.check_hostname = False
ctx.verify_mode = ssl.CERT_NONE
with urllib.request.urlopen(req, timeout=API_TIMEOUT, context=ctx) as resp:
data = json.loads(resp.read().decode('utf-8'))
return data.get('choices', [{}])[0].get('message', {}).get('content', '')
except Exception as e:
log.warning(f'AI call attempt {attempt+1} failed: {e}')
if attempt == max_retries - 1:
raise
time.sleep(2 ** attempt)
return ""
# ── DB Operations ──────────────────────────────────────────────────────
def _update_task(self, task_id, status, result, deliverable_file=None):
conn = sqlite3.connect(DB_PATH)
conn.execute('BEGIN IMMEDIATE')
try:
conn.execute(
"UPDATE agent_tasks SET status=?, result=?, deliverable_file=?, completed_at=datetime('now') WHERE id=?",
(status, result, deliverable_file, task_id))
conn.commit()
except Exception:
conn.rollback()
raise
finally:
conn.close()
def _register_deliverable(self, task_id, agent_id, agent_name, task_desc, filepath, file_type):
try:
conn = sqlite3.connect(DB_PATH)
safe_name = os.path.basename(filepath)
try:
conn.execute(
"INSERT INTO deliverables (title, agent_name, file_path, file_type, status, version, created_at) VALUES (?,?,?,?,?,?,datetime('now'))",
(task_desc, agent_name, filepath, file_type, 'approved', '1.0'))
conn.commit()
except sqlite3.OperationalError:
log.warning(f'Deliverables table not found, skipping registration')
conn.close()
except Exception as e:
log.warning(f'_register_deliverable error: {e}')
def _update_changelog(self, task_id, agent_name, task_desc, deliverables):
ts = datetime.now().strftime('%Y-%m-%d')
changelog_path = os.path.join(LOG_DIR, 'changelog.md')
header = '| Versie | Datum | Wijziging | Agent |\n|--------|-------|-----------|-------|\n'
row = f'| v1.0 | {ts} | {task_desc[:60]} | {agent_name} |\n'
if not os.path.exists(changelog_path):
with open(changelog_path, 'w', encoding='utf-8') as f:
f.write(f'# Changelog — {os.path.basename(PROJECT_DIR)}\n\n{header}{row}')
else:
with open(changelog_path, 'a', encoding='utf-8') as f:
f.write(row)
# ── Singleton ────────────────────────────────────────────────────────────────
executor = TaskExecutor()
def register_executor_routes(flask_app, BASE_PATH="/hseq-dashboard"):
from flask import jsonify
@flask_app.route(BASE_PATH + '/api/agents/executor/status')
def executor_status():
return jsonify({
'running': executor.running,
'current_task': executor.current_task_id,
'pending_tasks': executor.get_pending_count()
})
@flask_app.route(BASE_PATH + '/api/agents/executor/restart', methods=['POST'])
def executor_restart():
executor.stop()
executor.start()
return jsonify({'ok': True, 'message': 'Executor herstart (v2.0 Multi-Deliverable)'})
@flask_app.route(BASE_PATH + '/api/agents/task//retry', methods=['POST'])
def task_retry(task_id):
conn = sqlite3.connect(DB_PATH)
conn.execute("UPDATE agent_tasks SET status='pending', result=NULL, started_at=NULL, completed_at=NULL WHERE id=?", (task_id,))
conn.commit()
conn.close()
return jsonify({'ok': True, 'message': f'Taak {task_id} opnieuw in queue'})
@flask_app.route(BASE_PATH + '/api/agents/task//cancel', methods=['POST'])
def task_cancel(task_id):
"""Cancel a pending or running task."""
conn = sqlite3.connect(DB_PATH)
row = conn.execute("SELECT status FROM agent_tasks WHERE id=?", (task_id,)).fetchone()
if not row:
conn.close()
return jsonify({'error': 'Taak niet gevonden'}), 404
if row[0] in ('completed', 'cancelled'):
conn.close()
return jsonify({'error': f'Taak is al {row[0]}'}), 400
conn.execute("UPDATE agent_tasks SET status='cancelled', completed_at=datetime('now'), result='Geannuleerd door gebruiker' WHERE id=?", (task_id,))
conn.commit()
conn.close()
# Revert linked intelligence action
executor._sync_intelligence_action(task_id, 'failed')
return jsonify({'ok': True, 'message': f'Taak {task_id} geannuleerd'})