dhi.io/litellm
LiteLLM
LiteLLM is a universal LLM API gateway that provides OpenAI-compatible APIs for 100+ LLM providers including Bedrock, Azure, OpenAI, Anthropic, Vertex AI, and more.
pushed 11 hours ago
linux/amd64, linux/arm64
267.06 MB
for linux/amd64
426
for linux/amd64
Active support
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Build Level 3
Tamper-evident proof of how and from what sources this image was built. Build Level 3 is the highest the SLSA build track defines.
CycloneDX SBOM + SPDX SBOM
A software bill of materials in both CycloneDX and SPDX formats so it drops straight into your existing tooling. Audit exactly what you're shipping.
A Vulnerability Exploitability exchange document, Docker's assessment of which CVEs actually affect this image and which don't apply, so you can focus on real risk instead of chasing false positives.
Available
A link to everything used to build the image, package source code, Git repos, and build files, so you can audit or reproduce the build and stay compliant with open source licenses.
Every known vulnerability in this image, shown in full rather than hidden. The VEX data flags which ones actually apply, so you can tell real exposure from noise before you ship.
Exactly what changed in this build, down to the package bumps and fixes behind the version you're pulling.
Verifies no keys, tokens, or credentials were accidentally baked into the image.
The image layers were scanned for known malware signatures before publishing.
About LiteLLM
LiteLLM is a universal LLM API gateway that simplifies LLM API calls by providing a unified OpenAI-compatible interface for 100+ LLM providers. It acts as a proxy that translates requests between different LLM provider APIs, enabling developers to switch between providers without changing their code.
Key Features
- Universal API: OpenAI-compatible interface for all supported LLM providers
- 100+ Providers: Support for OpenAI, Anthropic, Azure, Bedrock, Vertex AI, Cohere, Hugging Face, and many more
- Load Balancing: Built-in load balancing and failover capabilities
- Rate Limiting: Per-user and per-model rate limiting
- Cost Tracking: Usage tracking and budget management
- Caching: Response caching to reduce costs and improve performance
- Authentication: API key management and user authentication
- Monitoring: Comprehensive logging and metrics
Use Cases
- Multi-Provider Strategy: Easily switch between LLM providers
- Cost Optimization: Compare costs across providers and optimize usage
- Reliability: Implement failover and load balancing across multiple providers
- Development: Standardize LLM integration across development teams
- Enterprise: Centralized LLM access control and monitoring
For more details, visit https://docs.litellm.ai/ and https://github.com/BerriAI/litellm.
About Docker Hardened Images
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Why use Docker Hardened Images?
These images are published with zero-known CVEs, include signed provenance, and come with a complete Software Bill of Materials (SBOM) and VEX metadata. They're designed to secure your software supply chain while fitting seamlessly into existing Docker workflows.
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