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Initial commit: LLM Automation Docs & Remediation Engine v2.0

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Features:
- Automated datacenter documentation generation
- MCP integration for device connectivity
- Auto-remediation engine with safety checks
- Multi-factor reliability scoring (0-100%)
- Human feedback learning loop
- Pattern recognition and continuous improvement
- Agentic chat support with AI
- API for ticket resolution
- Frontend React with Material-UI
- CI/CD pipelines (GitLab + Gitea)
- Docker & Kubernetes deployment
- Complete documentation and guides

v2.0 Highlights:
- Auto-remediation with write operations (disabled by default)
- Reliability calculator with 4-factor scoring
- Human feedback system for continuous learning
- Pattern-based progressive automation
- Approval workflow for critical actions
- Full audit trail and rollback capability
This commit is contained in:
LLM Automation System
2025-10-17 23:47:28 +00:00
commit 1ba5ce851d
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178
deploy/kubernetes/deployment.yaml Normal file
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---
apiVersion: apps/v1
kind: Deployment
metadata:
name: api
namespace: datacenter-docs
spec:
replicas: 3
selector:
matchLabels:
app: api
template:
metadata:
labels:
app: api
spec:
containers:
- name: api
image: registry.company.local/datacenter-docs/api:latest
ports:
- containerPort: 8000
env:
- name: MONGODB_URL
- name: MONGODB_DATABASE
value: "datacenter_docs"
valueFrom:
secretKeyRef:
name: datacenter-secrets
key: mongodb-url
- name: REDIS_URL
valueFrom:
secretKeyRef:
name: datacenter-secrets
key: redis-url
- name: MCP_SERVER_URL
valueFrom:
configMapKeyRef:
name: datacenter-config
key: mcp-server-url
- name: MCP_API_KEY
valueFrom:
secretKeyRef:
name: datacenter-secrets
key: mcp-api-key
- name: ANTHROPIC_API_KEY
valueFrom:
secretKeyRef:
name: datacenter-secrets
key: anthropic-api-key
resources:
requests:
memory: "512Mi"
cpu: "250m"
limits:
memory: "1Gi"
cpu: "1000m"
livenessProbe:
httpGet:
path: /health
port: 8000
initialDelaySeconds: 30
periodSeconds: 10
readinessProbe:
httpGet:
path: /health
port: 8000
initialDelaySeconds: 5
periodSeconds: 5
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: chat
namespace: datacenter-docs
spec:
replicas: 2
selector:
matchLabels:
app: chat
template:
metadata:
labels:
app: chat
spec:
containers:
- name: chat
image: registry.company.local/datacenter-docs/chat:latest
ports:
- containerPort: 8001
env:
- name: MONGODB_URL
- name: MONGODB_DATABASE
value: "datacenter_docs"
valueFrom:
secretKeyRef:
name: datacenter-secrets
key: mongodb-url
- name: REDIS_URL
valueFrom:
secretKeyRef:
name: datacenter-secrets
key: redis-url
- name: MCP_SERVER_URL
valueFrom:
configMapKeyRef:
name: datacenter-config
key: mcp-server-url
- name: MCP_API_KEY
valueFrom:
secretKeyRef:
name: datacenter-secrets
key: mcp-api-key
- name: ANTHROPIC_API_KEY
valueFrom:
secretKeyRef:
name: datacenter-secrets
key: anthropic-api-key
resources:
requests:
memory: "512Mi"
cpu: "250m"
limits:
memory: "1Gi"
cpu: "1000m"
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: worker
namespace: datacenter-docs
spec:
replicas: 3
selector:
matchLabels:
app: worker
template:
metadata:
labels:
app: worker
spec:
containers:
- name: worker
image: registry.company.local/datacenter-docs/worker:latest
env:
- name: MONGODB_URL
- name: MONGODB_DATABASE
value: "datacenter_docs"
valueFrom:
secretKeyRef:
name: datacenter-secrets
key: mongodb-url
- name: REDIS_URL
valueFrom:
secretKeyRef:
name: datacenter-secrets
key: redis-url
- name: MCP_SERVER_URL
valueFrom:
configMapKeyRef:
name: datacenter-config
key: mcp-server-url
- name: MCP_API_KEY
valueFrom:
secretKeyRef:
name: datacenter-secrets
key: mcp-api-key
- name: ANTHROPIC_API_KEY
valueFrom:
secretKeyRef:
name: datacenter-secrets
key: anthropic-api-key
resources:
requests:
memory: "512Mi"
cpu: "250m"
limits:
memory: "2Gi"
cpu: "1000m"