This repository documents a mobile-first TikTok comment automation system built for controlled, policy-aware engagement. It focuses on posting and replying to comments on videos, Shorts, and live streams using real devices, proxy rotation, and human-like pacing—prioritizing safety and observability over mass spam.
Created by Appilot, built to showcase our approach to Automation!
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Mass commenting tools often trigger moderation due to repetitive text, synchronized timing, or shared sessions. This system structures comment workflows with queues, per-account caps, and randomized delays so engagement looks organic and remains manageable across multiple accounts.
- Executes on real devices to mirror genuine user behavior
- Isolates accounts with per-account proxies and sessions
- Reduces spam signals via rate limits, jitter, and content variation
- Centralizes logs and health checks for safer scaling
| Feature | Description |
|---|---|
| Real-Device Commenting | Posts and replies to comments on physical devices. |
| Comment Queue Engine | Queues comments with configurable delays and daily caps. |
| Live & Shorts Support | Handles comments on standard videos, Shorts, and live streams. |
| Content Variation | Template rotation and light randomization to avoid repetition. |
| Multi-Account Management | Runs multiple accounts with isolated sessions. |
| Proxy Rotation | Dedicated proxy per account to maintain network separation. |
| Monitoring & Logs | Tracks successes, errors, and account health metrics. |
| Trigger / Input | Core Logic | Output | Safety Controls |
|---|---|---|---|
| Comment source | Validate templates/text | Jobs queued | Sanitization |
| Account allocation | Bind device + proxy | Isolated sessions | Concurrency caps |
| Execution cycle | Post/reply to comments | Comments published | Rate limits, jitter |
| Engagement blend | Add browse/watch time | Natural activity mix | Cooldowns |
| Reporting | Aggregate results | Dashboard logs | Auto-pause rules |
- Automation: Appium (Android real-device control)
- Backend: Python (FastAPI)
- Queues: Redis-based job queues
- Data: PostgreSQL (accounts, comments, logs)
- Networking: Mobile/residential proxies
- Dashboard: Web UI for campaigns and account health
tiktok-comment-automation/
api/
routes.py
campaigns.py
accounts.py
automation/
comment.py
reply.py
engagement.py
pacing.py
core/
session_manager.py
proxy_manager.py
retry_policy.py
dashboard/
app.py
components/
CampaignStatus.js
AccountHealth.js
CommentLogs.js
config/
settings.yaml
data/
comments.csv
scripts/
run_workers.py
requirements.txt
- Creators manage replies and discussions without spam behavior.
- Agencies coordinate multi-account commenting safely.
- Community teams keep conversations active on videos and lives.
- Operators monitor delivery and moderation signals centrally.
Q: Is this a mass-spam commenting tool?
No. It’s designed for paced, policy-aware commenting with caps and variation.
Q: Can it comment on live streams and Shorts?
Yes. Both live comments and Shorts are supported.
Q: How are accounts protected?
Through real-device execution, proxy isolation, pacing, and cooldowns.
Q: Are comments logged and auditable?
Yes. All actions, retries, and errors are logged and exportable.
Q: What happens if moderation limits are hit?
The system cools down, retries later, or pauses the account automatically.
- Comment success rate: 90–95% (network/moderation dependent)
- Throughput: 5–25 comments/day/account with pacing
- Scalability: 10–50 accounts per node (resource dependent)
- Recovery: Automatic retries with backoff and cooldowns
