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ai-deep-template-engine

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by the-Lobbi

Overview

A multi-agent system powered by LangGraph for automating and orchestrating complex DevOps infrastructure tasks, utilizing specialized subagents for IaC, container workflows, and team acceleration.

Installation

Run Command
docker-compose up -d

Environment Variables

  • HARNESS_ACCOUNT_ID
  • HARNESS_API_URL
  • HARNESS_API_TOKEN
  • HARNESS_ORG_IDENTIFIER
  • HARNESS_PROJECT_IDENTIFIER
  • MCP_SERVER_HOST
  • MCP_SERVER_PORT
  • ANTHROPIC_API_KEY
  • LANGSMITH_API_KEY
  • PINECONE_API_KEY
  • PINECONE_ENVIRONMENT
  • VOYAGE_API_KEY
  • TAVILY_API_KEY
  • DEEP_AGENT_LOG_LEVEL
  • AZURE_KEYVAULT_URL
  • AZURE_CLIENT_ID
  • AZURE_TENANT_ID
  • AZURE_CLIENT_SECRET
  • PROMETHEUS_URL
  • LOKI_URL
  • ELASTICSEARCH_URL
  • ALERTMANAGER_URL

Security Notes

The project exhibits strong security practices for secret management through its `secrets.py` module, which supports auto-detection for Azure Key Vault, Harness Secrets Manager, and environment variables. It explicitly warns against hardcoding secrets and is designed for zero secret value logging. No 'eval' or obvious obfuscation was found in the provided source code. Network communication uses `httpx.AsyncClient` with timeouts. The system interacts with powerful APIs like Kubernetes and Harness, which inherently require strict Role-Based Access Control (RBAC) on the target systems. The agent's capability to generate and execute configuration (e.g., YAML for Harness pipelines) introduces a potential risk for prompt injection if input is not carefully sanitized, a common challenge in agentic systems, but the core codebase's security practices are sound.

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Stats

Interest Score0
Security Score9
Cost ClassHigh
Avg Tokens250000
Stars0
Forks0
Last Update2026-01-19

Tags

DevOpsMulti-AgentLangGraphAI OrchestrationInfrastructure as Code