litemind
github.comSummary
Litemind is a Python library for developers to build conversational AI agents and tools. It provides a unified API for various Large Language Models, supports multimodal inputs and outputs, and includes an agentic AI framework for reasoning and tool use. The library also offers features like retrieval-augmented generation (RAG) and command-line tools for code generation.
Features6/13
See allMust Have
3 of 5
Conversational AI
API Access
Fine-Tuning & Custom Models
Safety & Alignment Framework
Enterprise Solutions
Other
3 of 8
Image Generation
Code Generation
Multimodal AI
Research & Publications
Security & Red Teaming
Synthetic Media Provenance
Threat Intelligence Reporting
Global Affairs & Policy
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
- Limited CI/CD minutes
- Limited Packages storage
Team
- Everything included in Free, plus...
- 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, plus...
- 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
Litemind is a Python library explicitly designed for building sophisticated conversational agents and tools, directly aligning with the 'Conversational AI' feature. It offers a flexible and elegant API for interacting with LLMs from various providers, fulfilling the 'API Access' requirement. The library supports 'multimodal inputs and outputs' (text, images, audio, video, tables, code, documents), which covers 'Multimodal AI' and 'Image Generation'. The ability to handle 'code' as a multimodal input and the mention of 'code generation' in its CLI tools and examples (e.g., 'Agent That Can Execute Python Code') strongly suggest 'Code Generation'. While 'fine-tuning' isn't explicitly stated, the concept of 'augmentations (RAG)' and 'adapting base models to specialized domains or unique data for tailored performance' through vector databases implies a form of customization that aligns with 'Fine-Tuning & Custom Models'. The 'Safety & Alignment Framework' and 'Enterprise Solutions' are not explicitly detailed as core offerings of this specific library, which is focused on development tools rather than a complete platform.