Fix code trans readme (#199)

Co-authored-by: arthw <14088817+arthw@users.noreply.github.com>

CodeTrans/README.md

@@ -6,11 +6,11 @@ The workflow falls into the following architecture:
 
 ![architecture](https://i.imgur.com/ums0brC.png)
 
-This Code Translation use case uses Text Generation Inference on Intel Gaudi2 or Intel XEON Scalable Processors. The Intel Gaudi2 accelerator supports both training and inference for deep learning models in particular for LLMs. Please visit [Habana AI products](https://habana.ai/products) for more details.
+This Code Translation use case uses Text Generation Inference on Intel Gaudi2 or Intel Xeon Scalable Processor. The Intel Gaudi2 accelerator supports both training and inference for deep learning models in particular for LLMs. Please visit [Habana AI products](https://habana.ai/products) for more details.
 
 # Deploy Code Translation Service
 
-The Code Translation service can be effortlessly deployed on either Intel Gaudi2 or Intel XEON Scalable Processors.
+The Code Translation service can be effortlessly deployed on either Intel Gaudi2 or Intel Xeon Scalable Processor.
 
 ## Deploy Code Translation on Gaudi
 

CodeTrans/docker-composer/gaudi/README.md

@@ -92,7 +92,7 @@ curl http://${host_ip}:7777/v1/codetrans \
     -d '{"language_from": "Golang","language_to": "Python","source_code": "package main\n\nimport \"fmt\"\nfunc main() {\n    fmt.Println(\"Hello, World!\");\n}"}'
 ```
 
-## Enable LangSmith for Monotoring Application (Optional)
+## Enable LangSmith to Monitor an Application (Optional)
 
 LangSmith offers tools to debug, evaluate, and monitor language models and intelligent agents. It can be used to assess benchmark data for each microservice. Before launching your services with `docker compose -f docker_compose.yaml up -d`, you need to enable LangSmith tracing by setting the `LANGCHAIN_TRACING_V2` environment variable to true and configuring your LangChain API key.
 

CodeTrans/docker-composer/xeon/README.md

@@ -2,9 +2,9 @@
 
 This document outlines the deployment process for a CodeTrans 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 using microservices `llm`. We will publish the Docker images to Docker Hub soon, it will simplify the deployment process for this service.
 
-## 🚀 Apply Xeon Server on AWS
+## 🚀 Create an AWS Xeon Instance
 
-To apply a Xeon server on AWS, start by creating an AWS account if you don't have one already. Then, head to the [EC2 Console](https://console.aws.amazon.com/ec2/v2/home) to begin the process. Within the EC2 service, select the Amazon EC2 M7i or M7i-flex instance type to leverage the power of 4th Generation Intel Xeon Scalable processors. These instances are optimized for high-performance computing and demanding workloads.
+To run the example on a AWS Xeon instance, start by creating an AWS account if you don't have one already. Then, get started with the [EC2 Console](https://console.aws.amazon.com/ec2/v2/home). AWS EC2 M7i, C7i, C7i-flex and M7i-flex instances are next-generation compute optimized instances powered by custom 4th Generation Intel Xeon Scalable processors (code named Sapphire Rapids). These instances are optimized for high-performance computing and demanding workloads.
 
 For detailed information about these instance types, you can refer to this [link](https://aws.amazon.com/ec2/instance-types/m7i/). Once you've chosen the appropriate instance type, proceed with configuring your instance settings, including network configurations, security groups, and storage options.
 
@@ -14,14 +14,14 @@ After launching your instance, you can connect to it using SSH (for Linux instan
 
 First of all, you need to build Docker Images locally and install the python package of it. This step can be ignored after the Docker images published to Docker hub.
 
-### 1. Source Code install GenAIComps
+### 1. Install GenAIComps from Source Code
 
 ```bash
 git clone https://github.com/opea-project/GenAIComps.git
 cd GenAIComps
 ```
 
-### 2. Build the LLM Docker Image with the following command
+### 2. Build the LLM Docker Image
 
 ```bash
 docker build -t opea/llm-tgi:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/text-generation/tgi/Dockerfile .
@@ -100,7 +100,7 @@ curl http://${host_ip}:7777/v1/codetrans \
     -d '{"language_from": "Golang","language_to": "Python","source_code": "package main\n\nimport \"fmt\"\nfunc main() {\n    fmt.Println(\"Hello, World!\");\n}"}'
 ```
 
-## Enable LangSmith for Monotoring Application (Optional)
+## Enable LangSmith to Monitor an Application (Optional)
 
 LangSmith offers tools to debug, evaluate, and monitor language models and intelligent agents. It can be used to assess benchmark data for each microservice. Before launching your services with `docker compose -f docker_compose.yaml up -d`, you need to enable LangSmith tracing by setting the `LANGCHAIN_TRACING_V2` environment variable to true and configuring your LangChain API key.
 

CodeTrans/ui/svelte/README.md

@@ -10,7 +10,7 @@
 
 Here're some of the project's features:
 
-- Code Translation: The system is capable of recognizing multiple languages and converting the current code content into the desired language's code format, enabling a set of code to be reused in multiple places, thus alleviating developers' development pressure.
+- Code Translation: The system is capable of recognizing multiple languages and converting the current code content into the desired language's code format, enabling a set of codes to be reused in multiple places, thus alleviating developers' development pressure.
 
 <h2>🛠️ Get it Running:</h2>