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6 changes: 3 additions & 3 deletions ChatQnA/docker_compose/intel/cpu/xeon/README.md
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This document outlines the deployment process for a ChatQnA application utilizing the [GenAIComps](https://github.com/opea-project/GenAIComps.git) microservice pipeline on Intel Xeon server. The steps include Docker image creation, container deployment via Docker Compose, and service execution to integrate microservices such as `embedding`, `retriever`, `rerank`, and `llm`.

The default pipeline deploys with vLLM as the LLM serving component and leverages rerank component. It also provides options of not using rerank in the pipeline and using TGI backend for LLM microservice, please refer to [start-all-the-services-docker-containers](#start-all-the-services-docker-containers) section in this page. Besides, refer to [Build with Pinecone VectorDB](./README_pinecone.md) and [Build with Qdrant VectorDB](./README_qdrant.md) for other deployment variants.
The default pipeline deploys with vLLM as the LLM serving component and leverages rerank component. It also provides options of not using rerank in the pipeline and using TGI backend for LLM microservice, please refer to [start-all-the-services-docker-containers](#start-all-the-services-docker-containers) section in this page. Besides, refer to [Build with Pinecone VectorDB](./README_pinecone.md) and [Build with Qdrant VectorDB](./README_qdrant.md) for other deployment variants.

Quick Start:

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In the first startup, this service will take more time to download, load and warm up the model. After it's finished, the service will be ready.
Try the command below to check whether the LLM serving is ready.
```bash
# vLLM service
docker logs vllm-service 2>&1 | grep complete
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Here is an example of running ChatQnA with Conversational UI (React):
![project-screenshot](../../../../assets/img/conversation_ui_response.png)
![project-screenshot](../../../../assets/img/conversation_ui_response.png)
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networks:
default:
driver: bridge
driver: bridge

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