Answer community queries using local regulations, procedures, and public data.
AI AgentLLM ServerGovernmentCommunityDetached System
0.5×← Perlahan · Cepat →
0%Stage 0 / 7 · Idle
💬Tekan Play Demo untuk lihat bagaimana Local Knowledge Assistant menjawab pertanyaan komuniti.
Demo Complete — All Stages Generated
01 WhatsApp Command
🏛️
OpenClaw — AINNA Agent
● Neural Link Active
02 Requirement Analysis
Queries
18
Answered
14
Referred
3
Avg Time
1.2m
Menunggu Sedang aktif Selesai
03 Python Script Generation
1
❓
Terima soalanReceive community query
2
🔍
Cari maklumatSearch local regulation DB
3
🤖
Rumus jawapanFormulate answer with sources
4
📋
Log & laporanLog query and generate report
import pandas as pd
from datetime import datetime
def search_knowledge_base(query, kb):
results = []
for entry in kb:
if query.lower() in entry['keywords']:
results.append(entry)
return results
def formulate_answer(query, results):
if not results:
return 'Maaf, saya perlu rujuk kepada pegawai berkaitan.'
answer = 'Berdasarkan rekod kami:\n'
for r in results:
answer += f"- {r['title']}: {r['summary']}\n"
return answer
# Log query and answer
04 Block Diagram
Menunggu Sedang aktif Selesai
05 System Schematic
Menunggu Sedang aktif Selesai
⚠️ Verify information accuracy with authorized government sources before publishing.
06 Simulasi Knowledge Query
Mula Sesi
Queries
0
Source
-
Confidence
0%
Referred
0
07 Knowledge Report
Demo
Knowledge Asst
Queries
0
Source
-
Confidence
0%
Status
Standby
Terminal Log
[SISTEM] Government/Community Local Knowledge Assistant sedia
System Architecture
📱 Command Layer
WhatsApp instruction
🤖 Agent Layer
Query parser
KB searcher
Answer formatter
🏛️ Government Layer
Regulation DB
Public data
Query log
Reports
Safety Notes
Verify information accuracy with authorized government sources before publishing.