akora/media-batch-manager
github.comSummary
akora/media-batch-manager is a Python-based toolkit designed for organizing and deduplicating large collections of media files and documents. It uses perceptual and content-based hashing for intelligent deduplication and offers batch organization and smart categorization features.
Features2/15
See allMust Have
2 of 5
Semantic Search
Automated Sorting Rules
AI File Chat
Cloud Storage Integration
Privacy Controls
Other
0 of 10
Feedback-Driven Refinement
Manual Approval Workflow
Demo Mode
Local File Access
Usage Credits & Quotas
Multi-User Collaboration
Enterprise SSO & Compliance
Centralized Team Billing
Advanced AI Model
Data Encryption & Security
PricingFreemium
See allFree
- Unlimited public/private repositories
- Dependabot security and version updates
- 2,000 CI/CD minutes/month (Free for public repositories)
- 500MB of Packages storage (Free for public repositories)
- Issues & Projects
- Community support
Team
- Everything included in Free
- Access to GitHub Codespaces
- Protected branches
- Multiple reviewers in pull requests
- Draft pull requests
- Code owners
- Required reviewers
- Pages and Wikis
- Environment deployment branches and secrets
- 3,000 CI/CD minutes/month (Free for public repositories)
- 2GB of Packages storage (Free for public repositories)
- Web-based support
Enterprise
- Everything included in Team
- Data residency
- Enterprise Managed Users
- User provisioning through SCIM
- Enterprise Account to centrally manage multiple organizations
- Environment protection rules
- Repository rules
- Audit Log API
- SOC1, SOC2, type 2 reports annually
- FedRAMP Tailored Authority to Operate (ATO)
- SAML single sign-on
- Advanced auditing
- GitHub Connect
- 50,000 CI/CD minutes/month (Free for public repositories)
- 50GB of Packages storage (Free for public repositories)
Rationale
The `akora/media-batch-manager` is a Python toolkit for organizing and deduplicating media files and documents. It explicitly mentions "Intelligent media file organization tool" and features like "Intelligent deduplication" and "Smart categorization" which align with automated sorting rules. The use of "perceptual hashing" for images and "content-based hashing" for documents suggests a form of semantic understanding for deduplication, which is a basic form of semantic search. However, it lacks explicit AI chat or cloud integration features as described in Dynbox.
