Commit Graph

4 Commits

Author SHA1 Message Date
52655e9eee feat: Implement CLI tool, Celery workers, and VMware collector
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CI/CD Pipeline / Build and Push Docker Images (worker) (push) Failing after 46s
CI/CD Pipeline / Build and Push Docker Images (api) (push) Failing after 40s
CI/CD Pipeline / Deploy to Staging (push) Has been skipped
CI/CD Pipeline / Deploy to Production (push) Has been skipped
Complete implementation of core MVP components:

CLI Tool (src/datacenter_docs/cli.py):
- 11 commands for system management (serve, worker, init-db, generate, etc.)
- Auto-remediation policy management (enable/disable/status)
- System statistics and monitoring
- Rich formatted output with tables and panels

Celery Workers (src/datacenter_docs/workers/):
- celery_app.py with 4 specialized queues (documentation, auto_remediation, data_collection, maintenance)
- tasks.py with 8 async tasks integrated with MongoDB/Beanie
- Celery Beat scheduling (6h docs, 1h data collection, 15m metrics, 2am cleanup)
- Rate limiting (10 auto-remediation/h) and timeout configuration
- Task lifecycle signals and comprehensive logging

VMware Collector (src/datacenter_docs/collectors/):
- BaseCollector abstract class with full workflow (connect/collect/validate/store/disconnect)
- VMwareCollector for vSphere infrastructure data collection
- Collects VMs, ESXi hosts, clusters, datastores, networks with statistics
- MCP client integration with mock data fallback for development
- MongoDB storage via AuditLog and data validation

Documentation & Configuration:
- Updated README.md with CLI commands and Workers sections
- Updated TODO.md with project status (55% completion)
- Added CLAUDE.md with comprehensive project instructions
- Added Docker compose setup for development environment

Project Status:
- Completion: 50% -> 55%
- MVP Milestone: 80% complete (only Infrastructure Generator remaining)
- Estimated time to MVP: 1-2 days

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-19 22:29:59 +02:00
cebd69c780 fix: Update all pipelines to Python 3.14
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Python 3.13 is causing installation errors in CI/CD runners.
Upgrading to Python 3.14 which is the latest stable version.

Changes:
- pyproject.toml: Update python requirement to ^3.14
- pyproject.toml: Update MyPy python_version to 3.14
- pyproject.toml: Update Black target-version to py314
- .gitlab-ci.yml: Update PYTHON_VERSION to 3.14
- .github/workflows/build-deploy.yml: Update PYTHON_VERSION to 3.14
- .gitea/workflows/ci.yml: Update PYTHON_VERSION to 3.14

This fixes the CI/CD error:
"rm: cannot remove '/opt/hostedtoolcache/Python/3.13.9/x64/lib/python3.13/__pycache__': Directory not empty"

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-19 14:22:17 +02:00
ac90dff43a fix: Update GitHub and Gitea workflows for Python 3.13 and MongoDB
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CI/CD Pipeline / Run Tests (push) Has been skipped
CI/CD Pipeline / Security Scanning (push) Has been skipped
CI/CD Pipeline / Build and Push Docker Images (api) (push) Has been skipped
CI/CD Pipeline / Build and Push Docker Images (chat) (push) Has been skipped
CI/CD Pipeline / Build and Push Docker Images (frontend) (push) Has been skipped
CI/CD Pipeline / Build and Push Docker Images (worker) (push) Has been skipped
CI/CD Pipeline / Deploy to Staging (push) Has been skipped
CI/CD Pipeline / Deploy to Production (push) Has been skipped
Changes to GitHub Actions (.github/workflows/build-deploy.yml):
- Update PYTHON_VERSION from 3.11 to 3.13

Changes to Gitea Actions (.gitea/workflows/ci.yml):
- Update PYTHON_VERSION from 3.10 to 3.13
- Update POETRY_VERSION from 1.7.1 to 1.8.0
- Replace PostgreSQL and Redis services with MongoDB
- Update service health check for MongoDB (mongosh)
- Update test environment variables for MongoDB
- Remove DATABASE_URL and REDIS_URL
- Add MONGODB_URL and MONGODB_DATABASE

This ensures all CI/CD pipelines are aligned with:
- Python 3.13 requirement in pyproject.toml
- MongoDB migration from PostgreSQL

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-19 14:14:57 +02:00
LLM Automation System
1ba5ce851d Initial commit: LLM Automation Docs & Remediation Engine v2.0
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
2025-10-17 23:47:28 +00:00