Update README.md for quick start guide (#1355)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

Author: yinghu5

FaqGen/docker_compose/intel/hpu/gaudi/README.md

@@ -2,6 +2,85 @@
 
 This document outlines the deployment process for a FAQ Generation application utilizing the [GenAIComps](https://github.com/opea-project/GenAIComps.git) microservice pipeline on Intel Gaudi server. The steps include Docker image creation, container deployment via Docker Compose, and service execution to integrate microservices such as llm. We will publish the Docker images to Docker Hub, which will simplify the deployment process for this service.
 
+## Quick Start:
+
+1. Set up the environment variables.
+2. Run Docker Compose.
+3. Consume the ChatQnA Service.
+
+### Quick Start: 1.Setup Environment Variable
+
+To set up environment variables for deploying ChatQnA services, follow these steps:
+
+1. Set the required environment variables:
+
+   ```bash
+   # Example: host_ip="192.168.1.1"
+   export host_ip=$(hostname -I | awk '{print $1}')
+   export HUGGINGFACEHUB_API_TOKEN="Your_Huggingface_API_Token"
+   ```
+
+2. If you are in a proxy environment, also set the proxy-related environment variables:
+
+   ```bash
+   export http_proxy="Your_HTTP_Proxy"
+   export https_proxy="Your_HTTPs_Proxy"
+   # Example: no_proxy="localhost, 127.0.0.1,192.168.1.1"
+   export no_proxy="localhost, 127.0.0.1,192.168.1.1, ${host_ip}"
+   ```
+
+3. Set up other environment variables:
+
+   ```bash
+   export LLM_MODEL_ID="meta-llama/Meta-Llama-3-8B-Instruct"
+   export TGI_LLM_ENDPOINT="http://${host_ip}:8008"
+   export MEGA_SERVICE_HOST_IP=${host_ip}
+   export LLM_SERVICE_HOST_IP=${host_ip}
+   export LLM_SERVICE_PORT=9000
+   export BACKEND_SERVICE_ENDPOINT="http://${host_ip}:8888/v1/faqgen"
+   ```
+
+### Quick Start: 2.Run Docker Compose
+
+```bash
+  docker compose up -d
+```
+
+It will automatically download the docker image on `docker hub`, please check the images' status by the commands
+
+```bash
+  docker ps -a
+  docker logs tgi-gaudi-server -t
+```
+
+it may take some time to download the model.
+In following cases, you could build docker image from source by yourself.
+
+- Failed to download the docker image.
+
+- If you want to use a specific version of Docker image.
+
+Please refer to 'Build Docker Images' in below.
+
+### QuickStart: 3.Consume the Service
+
+```bash
+curl localhost:8008/generate \
+     -X POST \
+     -d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":64, "do_sample": true}}' \
+     -H 'Content-Type: application/json'
+```
+
+here we just test the service on the host machine for a quick start.
+If all networks work fine, please try
+
+```bash
+   curl http://${host_ip}:8008/generate \
+     -X POST \
+     -d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":64, "do_sample": true}}' \
+     -H 'Content-Type: application/json'
+```
+
 ## 🚀 Build Docker Images
 
 First of all, you need to build Docker Images locally. This step can be ignored once the Docker images are published to Docker hub.
@@ -76,7 +155,7 @@ export no_proxy=${your_no_proxy}
 export http_proxy=${your_http_proxy}
 export https_proxy=${your_http_proxy}
 export LLM_MODEL_ID="meta-llama/Meta-Llama-3-8B-Instruct"
-export TGI_LLM_ENDPOINT="http://${your_ip}:8008"
+export TGI_LLM_ENDPOINT="http://${host_ip}:8008"
 export HUGGINGFACEHUB_API_TOKEN=${your_hf_api_token}
 export MEGA_SERVICE_HOST_IP=${host_ip}
 export LLM_SERVICE_HOST_IP=${host_ip}
@@ -98,7 +177,7 @@ docker compose up -d
 1. TGI Service
 
    ```bash
-   curl http://${your_ip}:8008/generate \
+   curl http://${host_ip}:8008/generate \
      -X POST \
      -d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":64, "do_sample": true}}' \
      -H 'Content-Type: application/json'