Suggest intelligent replies to customer chat inquiries based on context and sentiment.
AI AgentLLM ServerEcommerceChatCustomer
0.5×← Perlahan · Cepat →
0%Stage 0 / 7 · Idle
💬Tekan Play Demo untuk lihat Customer Chat Reply Assistant.
Demo Complete — All Stages Generated
01 WhatsApp Command
💼
OpenClaw — AINNA Agent
● Neural Link Active
02 Requirement Analysis
Chats
4
Auto Reply
3
Positive
2
Needs Help
1
Menunggu Sedang aktif Selesai
03 Python Script Generation
1
💬
Baca mesejRead customer message
2
😊
Analisis sentimenDetect sentiment & intent
3
✍️
Cadang balasSuggest reply draft
4
📤
Hantar balasanSend or queue for review
def suggest_reply(message, sentiment):
templates = {
'positive': "Thank you for your kind feedback! We're glad you're happy.",
'neutral': "Thank you for your message. Let me look into this for you.",
'negative': "We apologize for the inconvenience. Let me help resolve this."
}
return templates.get(sentiment, templates['neutral'])
04 Block Diagram
Menunggu Sedang aktif Selesai
05 System Schematic
Menunggu Sedang aktif Selesai
⚠️ Always review AI-suggested replies before sending to customers.
06 Simulasi Chat Reply
Mula Reply
Chats
0
Auto
0
Positive
0
Negative
0
07 Chat Reply Report
Demo
Chat Reply
Chats
0
Auto
0
Positive
0
Status
Standby
Terminal Log
[SISTEM] Customer Chat Reply Assistant sedia
System Architecture
📱 Command Layer
WhatsApp instruction
🤖 Agent Layer
Message parser
Sentiment analyzer
Reply generator
💬 Customer Layer
Chat platform
Customer DB
Reply templates
Safety Notes
Always review AI-suggested replies before sending to customers.