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* update tgi version Signed-off-by: Xinyao Wang <xinyao.wang@intel.com> * add k8s for faq Signed-off-by: Xinyao Wang <xinyao.wang@intel.com> * add benchmark for faq Signed-off-by: Xinyao Wang <xinyao.wang@intel.com> * refine k8s for faq Signed-off-by: Xinyao Wang <xinyao.wang@intel.com> * add tuning for faq Signed-off-by: Xinyao Wang <xinyao.wang@intel.com> * add prompts with different length for faq Signed-off-by: Xinyao Wang <xinyao.wang@intel.com> * add tgi docker for llama3.1 Signed-off-by: Xinyao Wang <xinyao.wang@intel.com> * remove useless code Signed-off-by: Xinyao Wang <xinyao.wang@intel.com> * remove nodeselector Signed-off-by: Xinyao Wang <xinyao.wang@intel.com> * remove hg token Signed-off-by: Xinyao Wang <xinyao.wang@intel.com> * refine code structure Signed-off-by: Xinyao Wang <xinyao.wang@intel.com> * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix readme Signed-off-by: Xinyao Wang <xinyao.wang@intel.com> --------- Signed-off-by: Xinyao Wang <xinyao.wang@intel.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Generative AI Examples
Introduction
GenAIComps-based Generative AI examples offer streamlined deployment, testing, and scalability. All examples are fully compatible with Docker and Kubernetes, supporting a wide range of hardware platforms such as Gaudi, Xeon, and other hardwares.
Architecture
GenAIComps is a service-based tool that includes microservice components such as llm, embedding, reranking, and so on. Using these components, various examples in GenAIExample can be constructed, including ChatQnA, DocSum, etc.
GenAIInfra, part of the OPEA containerization and cloud-native suite, enables quick and efficient deployment of GenAIExamples in the cloud.
GenAIEval measures service performance metrics such as throughput, latency, and accuracy for GenAIExamples. This feature helps users compare performance across various hardware configurations easily.
Getting Started
GenAIExamples offers flexible deployment options that cater to different user needs, enabling efficient use and deployment in various environments. Here’s a brief overview of the three primary methods: Python startup, Docker Compose, and Kubernetes.
- Docker Compose: Check the released docker images in docker image list for detailed information.
- Kubernetes: Follow the steps at K8s Install and GMC Install to setup k8s and GenAI environment .
Users can choose the most suitable approach based on ease of setup, scalability needs, and the environment in which they are operating.
Deployment
| Use Cases | Deployment | |||
|---|---|---|---|---|
| Docker Compose | Kubernetes | |||
| Xeon | Gaudi | |||
| ChatQnA | Xeon Link | Gaudi Link | K8s Link | |
| CodeGen | Xeon Link | Gaudi Link | K8s Link | |
| CodeTrans | Xeon Link | Gaudi Link | K8s Link | |
| DocSum | Xeon Link | Gaudi Link | K8s Link | |
| SearchQnA | Xeon Link | Gaudi Link | K8s Link | |
| FaqGen | Xeon Link | Gaudi Link | K8s Link | |
| Translation | Xeon Link | Gaudi Link | K8s Link | |
| AudioQnA | Xeon Link | Gaudi Link | Not supported yet | |
| VisualQnA | Xeon Link | Gaudi Link | Not supported yet | |
Support Examples
Check here for detailed information of supported examples, models, hardwares, etc.