Telegram Integration¶
Telegram integration enables the Studio Platform to leverage Telegram's secure messaging platform for compliance notifications, team communication, and automated workflows with enhanced privacy and security features.
đ¯ Integration Benefits¶
Secure Communication¶
- End-to-end encryption
- Self-destructing messages
- Two-factor authentication
- Privacy-focused design
Global Accessibility¶
- Cross-platform support
- Cloud synchronization
- Large file sharing (up to 2GB)
- Multi-device access
Automation Capabilities¶
- Bot framework integration
- Custom commands
- Inline queries
- Webhook support
đ§ Prerequisites¶
Telegram Requirements¶
- Telegram account
- Bot creation access
- API token generation
- Channel/group management
Technical Requirements¶
- Telegram Bot API access
- Webhook endpoint for receiving messages
- SSL certificate for webhook security
- Python/Node.js bot framework
Permissions Required¶
- Bot token from @BotFather
- Group/channel admin rights
- Message sending permissions
- Webhook configuration access
đ Setup Instructions¶
Step 1: Create Telegram Bot¶
-
Create Bot with BotFather
-
Configure Bot Settings
# Set bot description /setdescription # Select your bot # Enter description: "Studio Platform Compliance Bot" # Set bot commands /setcommands # Select your bot # Enter commands list compliance - Check compliance status evidence - Upload evidence risk - View risk assessment audit - Start audit process help - Show available commands -
Get Bot Token
Step 2: Configure Webhooks¶
-
Set Up Webhook Endpoint
# Flask webhook handler example from flask import Flask, request import telegram app = Flask(__name__) bot = telegram.Bot(token='YOUR_BOT_TOKEN') @app.route('/webhooks/telegram', methods=['POST']) def telegram_webhook(): update = telegram.Update.de_json(request.get_json(force=True), bot) process_telegram_update(update) return 'OK' -
Set Webhook URL
# Set webhook using curl curl -X POST "https://api.telegram.org/botYOUR_BOT_TOKEN/setWebhook" \ -H "Content-Type: application/json" \ -d '{"url": "https://studio.example.com/webhooks/telegram"}' # Or using python-telegram-bot from telegram import Bot bot = Bot(token='YOUR_BOT_TOKEN') bot.set_webhook(url='https://studio.example.com/webhooks/telegram')
Step 3: Configure Studio Platform Integration¶
- Access Integration Settings
- Navigate to Admin > Integrations
-
Select Telegram from available integrations
-
Enter Connection Details
-
Test Connection
- Click "Test Connection" button
- Verify successful API response
- Test bot functionality
đ Integration Features¶
Integration Architecture¶
graph TB
A[Studio Platform] --> B[Telegram Bot API]
B --> C[Message Sending]
B --> D[File Sharing]
B --> E[Inline Queries]
F[Telegram Webhooks] --> A
C --> G[Compliance Alerts]
D --> H[Evidence Collection]
E --> I[Quick Actions] Bot Commands¶
Command Definitions¶
bot_commands:
/compliance:
description: "Check current compliance status"
usage: "/compliance [framework]"
handler: "compliance_status_command"
/evidence:
description: "Upload compliance evidence"
usage: "/evidence [type] [description]"
handler: "evidence_upload_command"
/risk:
description: "View risk assessment"
usage: "/risk [level]"
handler: "risk_assessment_command"
/audit:
description: "Start audit process"
usage: "/audit [type]"
handler: "audit_start_command"
/reports:
description: "Generate compliance reports"
usage: "/reports [type] [period]"
handler: "reports_command"
/help:
description: "Show available commands"
usage: "/help"
handler: "help_command"
Command Handlers¶
from telegram import Update, InlineKeyboardButton, InlineKeyboardMarkup
from telegram.ext import Updater, CommandHandler, MessageHandler, Filters
class TelegramBotHandler:
def __init__(self, bot_token, studio_api):
self.updater = Updater(token=bot_token)
self.studio = studio_api
self.setup_handlers()
def setup_handlers(self):
"""Setup bot command handlers"""
dispatcher = self.updater.dispatcher
# Command handlers
dispatcher.add_handler(CommandHandler("compliance", self.compliance_command))
dispatcher.add_handler(CommandHandler("evidence", self.evidence_command))
dispatcher.add_handler(CommandHandler("risk", self.risk_command))
dispatcher.add_handler(CommandHandler("audit", self.audit_command))
dispatcher.add_handler(CommandHandler("reports", self.reports_command))
dispatcher.add_handler(CommandHandler("help", self.help_command))
# Message handlers
dispatcher.add_handler(MessageHandler(Filters.document, self.handle_document))
dispatcher.add_handler(MessageHandler(Filters.photo, self.handle_photo))
def compliance_command(self, update: Update, context):
"""Handle /compliance command"""
args = context.args
framework = args[0] if args else None
# Get compliance data
compliance_data = self.studio.get_compliance_status(framework)
# Format response
response = self.format_compliance_response(compliance_data)
# Send response
update.message.reply_text(response, parse_mode='Markdown')
def evidence_command(self, update: Update, context):
"""Handle /evidence command"""
args = context.args
if len(args) < 2:
update.message.reply_text(
"Usage: /evidence <type> <description>\n"
"Example: /evidence document \"Quarterly compliance report\""
)
return
evidence_type = args[0]
description = " ".join(args[1:])
# Create evidence record
evidence_id = self.studio.create_evidence_record(
type=evidence_type,
description=description,
user_id=update.effective_user.id
)
# Send upload instructions
keyboard = [
[InlineKeyboardButton("Upload Document", callback_data=f"upload_doc_{evidence_id}")],
[InlineKeyboardButton("Upload Photo", callback_data=f"upload_photo_{evidence_id}")]
]
reply_markup = InlineKeyboardMarkup(keyboard)
update.message.reply_text(
f"Evidence record created (ID: {evidence_id}). "
"Please upload the evidence file:",
reply_markup=reply_markup
)
def risk_command(self, update: Update, context):
"""Handle /risk command"""
args = context.args
level_filter = args[0] if args else None
# Get risk assessment
risk_data = self.studio.get_risk_assessment(level_filter)
# Format response
response = self.format_risk_response(risk_data)
# Send response
update.message.reply_text(response, parse_mode='Markdown')
def format_compliance_response(self, data):
"""Format compliance status response"""
response = f"đ *Compliance Status*\n\n"
response += f"Overall Score: {data['overall_score']}/100\n"
response += f"Critical Issues: {data['critical_issues']}\n"
response += f"Open Tasks: {data['open_tasks']}\n"
response += f"Last Updated: {data['last_updated']}\n\n"
if data['frameworks']:
response += "*Framework Details:*\n"
for framework in data['frameworks']:
response += f"âĸ {framework['name']}: {framework['score']}/100\n"
return response
def format_risk_response(self, data):
"""Format risk assessment response"""
response = f"â ī¸ *Risk Assessment*\n\n"
response += f"Total Risks: {data['total_risks']}\n"
response += f"Critical: {data['critical_risks']}\n"
response += f"High: {data['high_risks']}\n"
response += f"Medium: {data['medium_risks']}\n"
response += f"Low: {data['low_risks']}\n\n"
if data['top_risks']:
response += "*Top Risks:*\n"
for risk in data['top_risks'][:5]:
response += f"âĸ {risk['title']} ({risk['level']})\n"
return response
File Handling¶
Evidence Collection¶
def handle_document(self, update: Update, context):
"""Handle document uploads"""
document = update.message.document
# Download file
file_info = context.bot.get_file(document.file_id)
file_content = file_info.download_as_bytearray()
# Upload to Studio Platform
evidence_id = self.studio.upload_evidence(
file_content=file_content,
file_name=document.file_name,
file_size=document.file_size,
mime_type=document.mime_type,
user_id=update.effective_user.id,
source='telegram'
)
# Send confirmation
update.message.reply_text(
f"â
Document uploaded successfully!\n"
f"File: {document.file_name}\n"
f"Evidence ID: {evidence_id}"
)
def handle_photo(self, update: Update, context):
"""Handle photo uploads"""
photo = update.message.photo[-1] # Get highest resolution
# Download file
file_info = context.bot.get_file(photo.file_id)
file_content = file_info.download_as_bytearray()
# Upload to Studio Platform
evidence_id = self.studio.upload_evidence(
file_content=file_content,
file_name=f"photo_{photo.file_unique_id}.jpg",
file_size=photo.file_size,
mime_type='image/jpeg',
user_id=update.effective_user.id,
source='telegram'
)
# Send confirmation
update.message.reply_text(
f"â
Photo uploaded successfully!\n"
f"Evidence ID: {evidence_id}"
)
Notification System¶
Alert Messages¶
class TelegramNotificationService:
def __init__(self, bot_token, studio_api):
self.bot = telegram.Bot(token=bot_token)
self.studio = studio_api
def send_compliance_alert(self, alert_data):
"""Send compliance alert"""
chat_id = alert_data.get('chat_id', '@compliance_alerts')
# Format message
message = self.format_alert_message(alert_data)
# Send message
self.bot.send_message(
chat_id=chat_id,
text=message,
parse_mode='Markdown',
disable_web_page_preview=True
)
def format_alert_message(self, data):
"""Format alert message"""
severity_emoji = {
'critical': 'đ¨',
'high': 'â ī¸',
'medium': 'đ',
'low': 'âšī¸'
}
emoji = severity_emoji.get(data['severity'], 'đĸ')
message = f"{emoji} *{data['title']}*\n\n"
message += f"*Severity:* {data['severity'].title()}\n"
message += f"*Description:* {data['description']}\n"
if data.get('action_required'):
message += f"*Action Required:* {data['action_required']}\n"
if data.get('due_date'):
message += f"*Due Date:* {data['due_date']}\n"
if data.get('link'):
message += f"\n[View Details]({data['link']})"
return message
def send_report_notification(self, report_data):
"""Send report ready notification"""
chat_id = report_data.get('chat_id', '@compliance_reports')
message = f"đ *Report Ready*\n\n"
message += f"*Report:* {report_data['title']}\n"
message += f"*Period:* {report_data['period']}\n"
message += f"*Generated:* {report_data['generated_date']}\n\n"
if report_data.get('download_link'):
message += f"[Download Report]({report_data['download_link']})"
self.bot.send_message(
chat_id=chat_id,
text=message,
parse_mode='Markdown'
)
đ Dashboard Integration¶
Telegram Widgets¶
- Message Statistics - Sent/received messages
- Bot Activity - Command usage patterns
- File Uploads - Evidence collection metrics
- Response Times - Team engagement rates
Automated Reports¶
- Communication Analytics - Message effectiveness
- Usage Statistics - Feature adoption rates
- Response Metrics - Team responsiveness
- Error Analysis - Failed message patterns
đ Alerting & Notifications¶
Alert Configuration¶
alert_configuration:
critical_compliance:
enabled: true
chat_id: "@compliance_alerts"
message_template: "critical_alert"
priority: "high"
retry_attempts: 3
evidence_deadline:
enabled: true
chat_id: "@compliance_team"
message_template: "deadline_reminder"
priority: "medium"
schedule: "0 9 * * *" # Daily at 9 AM
compliance_updates:
enabled: true
chat_id: "@compliance_team"
message_template: "status_update"
priority: "low"
schedule: "0 17 * * *" # Daily at 5 PM
Notification Routing¶
routing_rules:
security_incidents:
condition: "category == 'security' AND severity == 'critical'"
chat_ids: ["@security_alerts", "@compliance_alerts"]
template: "security_incident"
escalation: true
audit_deadlines:
condition: "type == 'deadline' AND days_remaining <= 2"
chat_ids: ["@audit_team"]
template: "deadline_reminder"
compliance_reports:
condition: "type == 'report_ready'"
chat_ids: ["@compliance_reports", "@management"]
template: "report_notification"
đ ī¸ Advanced Configuration¶
Custom Bots¶
Compliance Assistant Bot¶
class ComplianceAssistantBot:
def __init__(self, bot_token, studio_api):
self.bot = telegram.Bot(token=bot_token)
self.studio = studio_api
self.setup_handlers()
def setup_handlers(self):
"""Setup advanced bot handlers"""
# Inline query handler
self.dispatcher.add_handler(InlineQueryHandler(self.inline_query_handler))
# Callback query handler
self.dispatcher.add_handler(CallbackQueryHandler(self.callback_query_handler))
def inline_query_handler(self, update: Update, context):
"""Handle inline queries"""
query = update.inline_query.query
results = []
if query.startswith('compliance'):
# Search compliance items
compliance_items = self.studio.search_compliance(query[11:])
for item in compliance_items:
results.append(
telegram.InlineQueryResultArticle(
id=item['id'],
title=item['title'],
description=item['description'],
input_message_content=telegram.InputTextMessageContent(
message_text=f"Compliance Item: {item['title']}\n{item['description']}"
)
)
)
update.inline_query.answer(results)
def callback_query_handler(self, update: Update, context):
"""Handle button callbacks"""
query = update.callback_query
query.answer()
if query.data.startswith('upload_'):
self.handle_upload_callback(query)
elif query.data.startswith('approve_'):
self.handle_approve_callback(query)
def handle_upload_callback(self, query):
"""Handle upload button callback"""
evidence_id = query.data.split('_')[2]
query.edit_message_text(
text=f"Please upload the evidence file for Evidence ID: {evidence_id}"
)
Workflow Integration¶
Automated Compliance Workflows¶
class TelegramWorkflowIntegration:
def __init__(self, telegram_bot, studio_api):
self.telegram = telegram_bot
self.studio = studio_api
def start_compliance_workflow(self, user_id, workflow_type):
"""Start compliance workflow via Telegram"""
if workflow_type == 'evidence_collection':
self.start_evidence_collection_workflow(user_id)
elif workflow_type == 'compliance_review':
self.start_compliance_review_workflow(user_id)
elif workflow_type == 'risk_assessment':
self.start_risk_assessment_workflow(user_id)
def start_evidence_collection_workflow(self, user_id):
"""Start evidence collection workflow"""
# Create workflow instance
workflow_id = self.studio.create_workflow(
type='evidence_collection',
user_id=user_id
)
# Send initial message
keyboard = [
[telegram.InlineKeyboardButton("Upload Document", callback_data=f"upload_doc_{workflow_id}")],
[telegram.InlineKeyboardButton("Upload Photo", callback_data=f"upload_photo_{workflow_id}")],
[telegram.InlineKeyboardButton("Cancel", callback_data=f"cancel_{workflow_id}")]
]
reply_markup = telegram.InlineKeyboardMarkup(keyboard)
self.telegram.bot.send_message(
chat_id=user_id,
text="đ Evidence Collection Workflow\n\n"
"Please select the type of evidence you want to upload:",
reply_markup=reply_markup
)
đ Security Best Practices¶
Bot Security¶
- Protect bot token
- Use environment variables
- Implement rate limiting
- Monitor bot activity
Data Protection¶
- Encrypt sensitive files
- Secure webhook endpoints
- Implement access controls
- Regular security audits
Privacy Compliance¶
- Follow Telegram ToS
- User consent management
- Data retention policies
- GDPR compliance
đ Troubleshooting¶
Common Issues¶
Bot Token Issues¶
Webhook Problems¶
# Check webhook status
curl -X GET "https://api.telegram.org/botYOUR_BOT_TOKEN/getWebhookInfo"
# Remove webhook (to use polling)
curl -X POST "https://api.telegram.org/botYOUR_BOT_TOKEN/deleteWebhook"
Message Sending Failures¶
- Check bot permissions
- Verify chat ID format
- Review message content
- Check rate limits
Debug Mode¶
debug_config:
enabled: true
log_level: "debug"
api_timeout: 60
retry_attempts: 3
detailed_logging: true
đ Monitoring & Metrics¶
Key Performance Indicators¶
- Message Delivery Rate - > 98%
- Bot Response Time - < 200ms
- File Upload Success - > 95%
- System Availability - 99.9% uptime
Health Checks¶
đ Maintenance¶
Regular Tasks¶
- Weekly: Review bot activity
- Monthly: Update command configurations
- Quarterly: Security audit
- Annually: Integration review
Updates & Upgrades¶
- Test Telegram API changes in staging
- Review breaking changes
- Update integration configuration
- Validate functionality
đ Support¶
Resources¶
Getting Help¶
- Check troubleshooting section
- Review Telegram bot logs
- Contact support team
- Submit GitHub issue
Best Practice
Use inline keyboards for interactive workflows to provide a better user experience and reduce message clutter.
Rate Limits
Be aware of Telegram API rate limits. Implement appropriate throttling and caching strategies for high-volume operations.
File Size Limits
Telegram supports files up to 2GB, but consider bandwidth and storage costs when handling large evidence files.