diff --git a/CodeGen/docker_compose/intel/cpu/xeon/README.md b/CodeGen/docker_compose/intel/cpu/xeon/README.md
index fa0093e0ad..70db1bfbef 100644
--- a/CodeGen/docker_compose/intel/cpu/xeon/README.md
+++ b/CodeGen/docker_compose/intel/cpu/xeon/README.md
@@ -100,16 +100,90 @@ export host_ip=${your_ip_address}
 export HUGGINGFACEHUB_API_TOKEN=you_huggingface_token
 ```
 
-2. Set Netowork Proxy
+2. Set Network Proxy
 
 **If you access public network through proxy, set the network proxy, otherwise, skip this step**
 
 ```bash
-export no_proxy=${your_no_proxy}
+export no_proxy=${no_proxy},${host_ip}
 export http_proxy=${your_http_proxy}
 export https_proxy=${your_https_proxy}
 ```
 
+## 🚀 Build Docker Images
+
+Should the Docker image you seek not yet be available on Docker Hub, you can build the Docker image locally.
+
+### 1. Build the LLM Docker Image
+
+```bash
+git clone https://github.com/opea-project/GenAIComps.git
+cd GenAIComps
+docker build -t opea/llm-textgen:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/src/text-generation/Dockerfile .
+```
+
+### 2. Build the Retriever Image
+
+```bash
+docker build -t opea/retriever:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/retrievers/src/Dockerfile .
+```
+
+### 3. Build the Dataprep Image
+
+```bash
+docker build -t opea/dataprep:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/dataprep/src/Dockerfile .
+```
+
+### 4. Build the MegaService Docker Image
+
+To construct the Mega Service, we utilize the [GenAIComps](https://github.com/opea-project/GenAIComps.git) microservice pipeline within the `codegen.py` Python script. Build the MegaService Docker image via the command below:
+
+```bash
+git clone https://github.com/opea-project/GenAIExamples
+cd GenAIExamples/CodeGen
+docker build -t opea/codegen:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile .
+```
+
+### 5. Build the UI Gradio Image (Recommended)
+
+Build the frontend Gradio image via the command below:
+
+```bash
+cd GenAIExamples/CodeGen/ui
+docker build -t opea/codegen-gradio-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f docker/Dockerfile.gradio .
+```
+
+### 5a. Build CodeGen React UI Docker Image (Optional)
+
+Build react frontend Docker image via below command:
+
+**Export the value of the public IP address of your Xeon server to the `host_ip` environment variable**
+
+```bash
+cd GenAIExamples/CodeGen/ui
+docker build --no-cache -t opea/codegen-react-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile.react .
+```
+
+### 5b. Build the UI Docker Image
+
+Construct the frontend Docker image via the command below:
+
+```bash
+cd GenAIExamples/CodeGen/ui
+docker build -t opea/codegen-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile .
+```
+
+Then run the command `docker images`, you will have the following Docker images:
+
+- `opea/llm-textgen:latest`
+- `opea/retriever:latest`
+- `opea/dataprep:latest`
+- `opea/codegen:latest`
+- `opea/codegen-gradio-ui:latest` (Recommended)
+- `opea/codegen-ui:latest` (Optional)
+- `opea/codegen-react-ui:latest` (Optional)
+
+
 ### Start the Docker Containers for All Services
 
 CodeGen support TGI service and vLLM service, you can choose start either one of them.
@@ -139,8 +213,9 @@ docker compose --profile codegen-xeon-vllm up -d
    ```bash
    curl http://${host_ip}:8028/v1/chat/completions \
        -X POST \
-       -d '{"model": "Qwen/Qwen2.5-Coder-7B-Instruct", "messages": [{"role": "user", "content": "Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception."}], "max_tokens":32}' \
-       -H 'Content-Type: application/json'
+       -H 'Content-Type: application/json' \
+       -d '{"model": "Qwen/Qwen2.5-Coder-7B-Instruct", "messages": [{"role": "user", "content": "Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception."}], "max_tokens":32}'
+
    ```
 
 2. LLM Microservices
@@ -148,28 +223,59 @@ docker compose --profile codegen-xeon-vllm up -d
    ```bash
    curl http://${host_ip}:9000/v1/chat/completions\
      -X POST \
-     -d '{"query":"Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception.","max_tokens":256,"top_k":10,"top_p":0.95,"typical_p":0.95,"temperature":0.01,"repetition_penalty":1.03,"stream":true}' \
-     -H 'Content-Type: application/json'
+     -H 'Content-Type: application/json' \
+     -d '{"query":"Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception.","max_tokens":256,"top_k":10,"top_p":0.95,"typical_p":0.95,"temperature":0.01,"repetition_penalty":1.03,"stream":true}'
    ```
 
-3. MegaService
+3. Dataprep Microservice
+
+    Make sure to replace the file name placeholders with your correct file name
+
+      ```bash
+      curl http://${host_ip}:6007/v1/dataprep/ingest \
+     -X POST \
+     -H "Content-Type: multipart/form-data" \
+     -F "files=@./file1.pdf" \
+     -F "files=@./file2.txt" \ 
+     -F "index_name=my_API_document"
+      ```
+
+4. MegaService
 
    ```bash
-   curl http://${host_ip}:7778/v1/codegen -H "Content-Type: application/json" -d '{
-        "messages": "Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception."
-        }'
+   curl http://${host_ip}:7778/v1/codegen \
+     -H "Content-Type: application/json" \
+     -d '{"messages": "Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception."}'
    ```
 
-    If the user wants a CodeGen service with RAG and Agents based on dedicated documentation.
+    CodeGen service with RAG and Agents activated based on an index.
    
     ```bash
-    curl http://localhost:7778/v1/codegen \
+    curl http://${host_ip}:7778/v1/codegen \
       -H "Content-Type: application/json" \
       -d '{"agents_flag": "True", "index_name": "my_API_document", "messages": "Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception."}'
     ```
    
 
-## 🚀 Launch the UI
+## 🚀 Launch the Gradio Based UI (Recommended)
+To access the Gradio frontend URL, follow the steps in [this README](../../../../ui/gradio/README.md)
+
+Code Generation Tab
+![project-screenshot](../../../../assets/img/codegen_gradio_ui_main.png)
+
+Resource Management Tab
+![project-screenshot](../../../../assets/img/codegen_gradio_ui_main.png)
+
+Uploading a Knowledge Index
+
+![project-screenshot](../../../../assets/img/codegen_gradio_ui_dataprep.png)
+
+Here is an example of running a query in the Gradio UI using an Index:
+
+![project-screenshot](../../../../assets/img/codegen_gradio_ui_query.png)
+
+
+## 🚀 Launch the Svelte Based UI (Optional)
 
 To access the frontend, open the following URL in your browser: `http://{host_ip}:5173`. By default, the UI runs on port 5173 internally. If you prefer to use a different host port to access the frontend, you can modify the port mapping in the `compose.yaml` file as shown below:
 
@@ -282,54 +388,3 @@ For example:
 - Ask question and get answer
 
 ![qna](../../../../assets/img/codegen_qna.png)
-
-## 🚀 Download or Build Docker Images
-
-Should the Docker image you seek not yet be available on Docker Hub, you can build the Docker image locally.
-
-### 1. Build the LLM Docker Image
-
-```bash
-git clone https://github.com/opea-project/GenAIComps.git
-cd GenAIComps
-docker build -t opea/llm-textgen:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/src/text-generation/Dockerfile .
-```
-
-### 2. Build the MegaService Docker Image
-
-To construct the Mega Service, we utilize the [GenAIComps](https://github.com/opea-project/GenAIComps.git) microservice pipeline within the `codegen.py` Python script. Build MegaService Docker image via the command below:
-
-```bash
-git clone https://github.com/opea-project/GenAIExamples
-cd GenAIExamples/CodeGen
-docker build --no-cache -t opea/codegen:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile .
-```
-
-### 3. Build the UI Docker Image
-
-Build the frontend Docker image via the command below:
-
-```bash
-cd GenAIExamples/CodeGen/ui
-docker build --no-cache -t opea/codegen-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile .
-```
-
-### 4. Build CodeGen React UI Docker Image (Optional)
-
-Build react frontend Docker image via below command:
-
-**Export the value of the public IP address of your Xeon server to the `host_ip` environment variable**
-
-```bash
-cd GenAIExamples/CodeGen/ui
-docker build --no-cache -t opea/codegen-react-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile.react .
-```
-
-Then run the command `docker images`, you will have the following Docker Images:
-
-- `opea/llm-textgen:latest`
-- `opea/codegen:latest`
-- `opea/codegen-ui:latest`
-- `opea/codegen-gradio-ui:latest`
-- `opea/codegen-react-ui:latest` (optional)
-
diff --git a/CodeGen/docker_compose/intel/hpu/gaudi/README.md b/CodeGen/docker_compose/intel/hpu/gaudi/README.md
index 5408e33654..bc1444dc7b 100644
--- a/CodeGen/docker_compose/intel/hpu/gaudi/README.md
+++ b/CodeGen/docker_compose/intel/hpu/gaudi/README.md
@@ -93,16 +93,89 @@ export host_ip=${your_ip_address}
 export HUGGINGFACEHUB_API_TOKEN=you_huggingface_token
 ```
 
-2. Set Netowork Proxy
+2. Set Network Proxy
 
 **If you access public network through proxy, set the network proxy, otherwise, skip this step**
 
 ```bash
-export no_proxy=${your_no_proxy}
+export no_proxy=${no_proxy},${host_ip}
 export http_proxy=${your_http_proxy}
 export https_proxy=${your_https_proxy}
 ```
 
+## 🚀 Build Docker Images
+
+First of all, you need to build the Docker images locally. This step can be ignored after the Docker images published to the Docker Hub.
+
+### 1. Build the LLM Docker Image
+
+```bash
+git clone https://github.com/opea-project/GenAIComps.git
+cd GenAIComps
+docker build -t opea/llm-textgen:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/src/text-generation/Dockerfile .
+```
+
+### 2. Build the Retriever Image
+
+```bash
+docker build -t opea/retriever:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/retrievers/src/Dockerfile .
+```
+
+### 3. Build the Dataprep Image
+
+```bash
+docker build -t opea/dataprep:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/dataprep/src/Dockerfile .
+```
+
+### 4. Build the MegaService Docker Image
+
+To construct the Mega Service, we utilize the [GenAIComps](https://github.com/opea-project/GenAIComps.git) microservice pipeline within the `codegen.py` Python script. Build the MegaService Docker image via the command below:
+
+```bash
+git clone https://github.com/opea-project/GenAIExamples
+cd GenAIExamples/CodeGen
+docker build -t opea/codegen:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile .
+```
+
+### 5. Build the UI Gradio Image (Recommended)
+
+Build the frontend Gradio image via the command below:
+
+```bash
+cd GenAIExamples/CodeGen/ui
+docker build -t opea/codegen-gradio-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f docker/Dockerfile.gradio .
+```
+
+### 5a. Build CodeGen React UI Docker Image (Optional)
+
+Build react frontend Docker image via below command:
+
+**Export the value of the public IP address of your Xeon server to the `host_ip` environment variable**
+
+```bash
+cd GenAIExamples/CodeGen/ui
+docker build --no-cache -t opea/codegen-react-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile.react .
+```
+
+### 5b. Build the UI Docker Image
+
+Construct the frontend Docker image via the command below:
+
+```bash
+cd GenAIExamples/CodeGen/ui
+docker build -t opea/codegen-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile .
+```
+
+Then run the command `docker images`, you will have the following Docker images:
+
+- `opea/llm-textgen:latest`
+- `opea/retriever:latest`
+- `opea/dataprep:latest`
+- `opea/codegen:latest`
+- `opea/codegen-gradio-ui:latest` (Recommended)
+- `opea/codegen-ui:latest` (Optional)
+- `opea/codegen-react-ui:latest` (Optional)
+
 ### Start the Docker Containers for All Services
 
 CodeGen support TGI service and vLLM service, you can choose start either one of them.
@@ -132,8 +205,9 @@ docker compose --profile codegen-gaudi-vllm up -d
    ```bash
    curl http://${host_ip}:8028/v1/chat/completions \
        -X POST \
-       -d '{"model": "Qwen/Qwen2.5-Coder-7B-Instruct", "messages": [{"role": "user", "content": "Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception."}], "max_tokens":32}' \
-       -H 'Content-Type: application/json'
+       -H 'Content-Type: application/json' \
+       -d '{"model": "Qwen/Qwen2.5-Coder-7B-Instruct", "messages": [{"role": "user", "content": "Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception."}], "max_tokens":32}'
+
    ```
 
 2. LLM Microservices
@@ -141,28 +215,58 @@ docker compose --profile codegen-gaudi-vllm up -d
    ```bash
    curl http://${host_ip}:9000/v1/chat/completions\
      -X POST \
-     -d '{"query":"Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception.","max_tokens":256,"top_k":10,"top_p":0.95,"typical_p":0.95,"temperature":0.01,"repetition_penalty":1.03,"stream":true}' \
-     -H 'Content-Type: application/json'
+     -H 'Content-Type: application/json' \
+     -d '{"query":"Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception.","max_tokens":256,"top_k":10,"top_p":0.95,"typical_p":0.95,"temperature":0.01,"repetition_penalty":1.03,"stream":true}'
    ```
 
-3. MegaService
+3. Dataprep Microservice
+
+    Make sure to replace the file name placeholders with your correct file name
+
+      ```bash
+      curl http://${host_ip}:6007/v1/dataprep/ingest \
+     -X POST \
+     -H "Content-Type: multipart/form-data" \
+     -F "files=@./file1.pdf" \
+     -F "files=@./file2.txt" \ 
+     -F "index_name=my_API_document"
+      ```
+
+4. MegaService
 
    ```bash
-   curl http://${host_ip}:7778/v1/codegen -H "Content-Type: application/json" -d '{
-        "messages": "Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception."
-        }'
+   curl http://${host_ip}:7778/v1/codegen \
+     -H "Content-Type: application/json" \
+     -d '{"messages": "Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception."}'
    ```
 
-    If the user wants a CodeGen service with RAG and Agents based on dedicated documentation.
+    CodeGen service with RAG and Agents activated based on an index.
    
     ```bash
-    curl http://localhost:7778/v1/codegen \
+    curl http://${host_ip}$:7778/v1/codegen \
       -H "Content-Type: application/json" \
       -d '{"agents_flag": "True", "index_name": "my_API_document", "messages": "Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception."}'
     ```
-   
 
-## 🚀 Launch the Svelte Based UI
+## 🚀 Launch the Gradio Based UI (Recommended)
+To access the Gradio frontend URL, follow the steps in [this README](../../../../ui/gradio/README.md)
+
+Code Generation Tab
+![project-screenshot](../../../../assets/img/codegen_gradio_ui_main.png)
+
+Resource Management Tab
+![project-screenshot](../../../../assets/img/codegen_gradio_ui_main.png)
+
+Uploading a Knowledge Index
+
+![project-screenshot](../../../../assets/img/codegen_gradio_ui_dataprep.png)
+
+Here is an example of running a query in the Gradio UI using an Index:
+
+![project-screenshot](../../../../assets/img/codegen_gradio_ui_query.png)
+
+
+## 🚀 Launch the Svelte Based UI (Optional)
 
 To access the frontend, open the following URL in your browser: `http://{host_ip}:5173`. By default, the UI runs on port 5173 internally. If you prefer to use a different host port to access the frontend, you can modify the port mapping in the `compose.yaml` file as shown below:
 
@@ -272,51 +376,3 @@ For example:
 
 ![qna](../../../../assets/img/codegen_qna.png)
 
-## 🚀 Build Docker Images
-
-First of all, you need to build the Docker images locally. This step can be ignored after the Docker images published to the Docker Hub.
-
-### 1. Build the LLM Docker Image
-
-```bash
-git clone https://github.com/opea-project/GenAIComps.git
-cd GenAIComps
-docker build -t opea/llm-textgen:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/src/text-generation/Dockerfile .
-```
-
-### 2. Build the MegaService Docker Image
-
-To construct the Mega Service, we utilize the [GenAIComps](https://github.com/opea-project/GenAIComps.git) microservice pipeline within the `codegen.py` Python script. Build the MegaService Docker image via the command below:
-
-```bash
-git clone https://github.com/opea-project/GenAIExamples
-cd GenAIExamples/CodeGen
-docker build -t opea/codegen:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile .
-```
-
-### 3. Build the UI Docker Image
-
-Construct the frontend Docker image via the command below:
-
-```bash
-cd GenAIExamples/CodeGen/ui
-docker build -t opea/codegen-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile .
-```
-
-### 4. Build CodeGen React UI Docker Image (Optional)
-
-Build react frontend Docker image via below command:
-
-**Export the value of the public IP address of your Xeon server to the `host_ip` environment variable**
-
-```bash
-cd GenAIExamples/CodeGen/ui
-docker build --no-cache -t opea/codegen-react-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile.react .
-```
-
-Then run the command `docker images`, you will have the following Docker images:
-
-- `opea/llm-textgen:latest`
-- `opea/codegen:latest`
-- `opea/codegen-ui:latest`
-- `opea/codegen-react-ui:latest`
diff --git a/CodeGen/ui/gradio/codegen_ui_gradio.py b/CodeGen/ui/gradio/codegen_ui_gradio.py
index d0e351960a..84e2a5d652 100644
--- a/CodeGen/ui/gradio/codegen_ui_gradio.py
+++ b/CodeGen/ui/gradio/codegen_ui_gradio.py
@@ -15,14 +15,11 @@
 import uvicorn
 import json
 import argparse
-# from utils import build_logger, make_temp_image, server_error_msg, split_video
 from urllib.parse import urlparse
 from pathlib import Path
 from fastapi import FastAPI
-# from fastapi.responses import JSONResponse, StreamingResponse
 from fastapi.staticfiles import StaticFiles
 
-# logger = build_logger("gradio_web_server", "gradio_web_server.log")
 logflag = os.getenv("LOGFLAG", False)
 
 # create a FastAPI app
@@ -56,7 +53,6 @@
 
 # Define the functions that will be used in the app
 def conversation_history(prompt, index, use_agent, history):
-    # Print the language and prompt, and return a placeholder code
     print(f"Generating code for prompt: {prompt} using index: {index} and use_agent is {use_agent}")
     history.append([prompt, ""])
     response_generator = generate_code(prompt, index, use_agent)
@@ -67,7 +63,6 @@ def conversation_history(prompt, index, use_agent, history):
 
 def upload_media(media, index=None, chunk_size=1500, chunk_overlap=100):
     media = media.strip().split("\n")
-    print("Files passed is ", media, flush=True)
     if not chunk_size:
         chunk_size = 1500
     if not chunk_overlap:
@@ -78,8 +73,6 @@ def upload_media(media, index=None, chunk_size=1500, chunk_overlap=100):
         for file in media:
             file_ext = os.path.splitext(file)[-1]
             if is_valid_url(file):
-                print(file, " is valid URL")
-                print("Ingesting URL...")
                 yield (
                     gr.Textbox(
                         visible=True,
@@ -90,7 +83,6 @@ def upload_media(media, index=None, chunk_size=1500, chunk_overlap=100):
                 requests.append(value)
                 yield value
             elif file_ext in ['.pdf', '.txt']:
-                print("Ingesting File...")
                 yield (
                     gr.Textbox(
                         visible=True,
@@ -101,7 +93,6 @@ def upload_media(media, index=None, chunk_size=1500, chunk_overlap=100):
                 requests.append(value)
                 yield value
             else:
-                print(file, "File type not supported")
                 yield (
                     gr.Textbox(
                         visible=True,
@@ -117,12 +108,9 @@ def upload_media(media, index=None, chunk_size=1500, chunk_overlap=100):
             value = ingest_url(media, index, chunk_size, chunk_overlap)
             yield value
         elif file_ext in ['.pdf', '.txt']:
-            print("Ingesting File...")
             value = ingest_file(media, index, chunk_size, chunk_overlap)
-            # print("Return value is: ", value, flush=True)
             yield value
         else:
-            print(media, "File type not supported")
             yield (
                 gr.Textbox(
                     visible=True,
@@ -180,16 +168,11 @@ def ingest_file(file, index=None, chunk_size=100, chunk_overlap=150):
     else:
         data = {"chunk_size": chunk_size, "chunk_overlap": chunk_overlap}
 
-    print("Calling Request Now!")
     response = requests.post(url=dataprep_ingest_endpoint, headers=headers, files=file_input, data=data)
-    # print("Ingest Files", response)
-    print(response.text)
-        
-    # table = update_table()
+
     return response.text
 
 def ingest_url(url, index=None, chunk_size=100, chunk_overlap=150):
-    print("URL is ", url)
     url = str(url)
     if not is_valid_url(url):
         return "Invalid URL entered. Please enter a valid URL"
@@ -203,8 +186,7 @@ def ingest_url(url, index=None, chunk_size=100, chunk_overlap=150):
     else:
         url_input = {"link_list": json.dumps([url]), "chunk_size": chunk_size, "chunk_overlap": chunk_overlap}
     response = requests.post(url=dataprep_ingest_endpoint, headers=headers, data=url_input)
-    # print("Ingest URL", response)
-    # table = update_table()
+
     return response.text
 
 
@@ -216,18 +198,6 @@ def is_valid_url(url):
     except ValueError:
         return False
 
-
-
-# Initialize the file list
-file_list = []
-
-# def update_files(file):
-#     # Add the uploaded file to the file list
-#     file_list.append(file.name)
-#     file_df["Files"] = file_list
-#     return file_df
-
-
 def get_files(index=None):
     headers = {
         # "Content-Type: multipart/form-data"
@@ -238,13 +208,10 @@ def get_files(index=None):
     if index:
         index = {"index_name": index}
         response = requests.post(url=dataprep_get_files_endpoint, headers=headers, data=index)
-        print("Get files with ", index, response)
         table = response.json()
         return table
     else:
-        # print("URL IS ", dataprep_get_files_endpoint)
         response = requests.post(url=dataprep_get_files_endpoint, headers=headers)
-        print("Get files ", response)
         table = response.json()
         return table
 
@@ -252,7 +219,6 @@ def update_table(index=None):
     if index == "All Files":
         index = None
     files = get_files(index)
-    print("Files is ", files)
     if len(files) == 0:
         df = pd.DataFrame(files, columns=["Files"])
         return df
@@ -270,13 +236,11 @@ def delete_file(file, index=None):
     headers = {
         # "Content-Type: application/json"
     }
-    print("URL IS ", dataprep_delete_files_endpoint)
     if index:
         file_input = {"files": open(file, "rb"), "index_name": index}
     else:
         file_input = {"files": open(file, "rb")}
     response = requests.post(url=dataprep_delete_files_endpoint, headers=headers, data=file_input)
-    print("Delete file ", response)
     table = update_table()
     return response.text
 
@@ -286,7 +250,6 @@ def delete_all_files(index=None):
         # "Content-Type: application/json"
     }
     response = requests.post(url=dataprep_delete_files_endpoint, headers=headers, data='{"file_path": "all"}')
-    print("Delete all files ", response)
     table = update_table()
     
     return "Delete All status: " + response.text
@@ -297,7 +260,6 @@ def get_indices():
     }
     response = requests.post(url=dataprep_get_indices_endpoint, headers=headers)
     indices = ["None"]
-    print("Get Indices", response)
     indices += response.json()
     return indices
 
@@ -325,22 +287,16 @@ def get_file_names(files):
         prompt_input = gr.Textbox(label="Enter your query")
         with gr.Column():
             with gr.Row(equal_height=True):
-                # indices = ["None"] + get_indices()
                 database_dropdown = gr.Dropdown(choices=get_indices(), label="Select Index", value="None", scale=10)
                 db_refresh_button = gr.Button("Refresh Dropdown", scale=0.1)
                 db_refresh_button.click(update_indices_dropdown, outputs=database_dropdown)
                 use_agent = gr.Checkbox(label="Use Agent", container=False)
-            # with gr.Row(scale=1):
-            
         
         generate_button = gr.Button("Generate Code")
-
-        # Connect the generate button to the conversation_history function
         generate_button.click(conversation_history, inputs=[prompt_input, database_dropdown, use_agent, chatbot], outputs=chatbot)
 
     with gr.Tab("Resource Management"):
         # File management components
-        # url_button = gr.Button("Process")
         with gr.Row():
             with gr.Column(scale=1):
                 index_name_input = gr.Textbox(label="Index Name")
@@ -353,26 +309,13 @@ def get_file_names(files):
                 upload_status = gr.Textbox(label="Upload Status")
                 file_upload.change(get_file_names, inputs=file_upload, outputs=url_input)
             with gr.Column(scale=1):
-                # table_dropdown = gr.Dropdown(indices)
-                # file_table = gr.Dataframe(interactive=False, value=update_table())
                 file_table = gr.Dataframe(interactive=False, value=update_indices())
                 refresh_button = gr.Button("Refresh", variant="primary", size="sm")
                 refresh_button.click(update_indices, outputs=file_table)
-                # refresh_button.click(update_indices, outputs=database_dropdown)
-                # table_dropdown.change(fn=update_table, inputs=table_dropdown, outputs=file_table)
-                # upload_button.click(upload_media, inputs=[file_upload, index_name_input, chunk_size_input, chunk_overlap_input], outputs=file_table)
                 upload_button.click(upload_media, inputs=[url_input, index_name_input, chunk_size_input, chunk_overlap_input], outputs=upload_status)
                 
                 delete_all_button = gr.Button("Delete All", variant="primary", size="sm")
                 delete_all_button.click(delete_all_files, outputs=upload_status)
-        
-        
-        
-                # delete_button = gr.Button("Delete Index")
-
-                # selected_file_output = gr.Textbox(label="Selected File")
-                # delete_button.click(delete_file, inputs=indices, outputs=upload_status)
-
       
 
 ui.queue()
@@ -397,14 +340,7 @@ def get_file_names(files):
         "BACKEND_SERVICE_ENDPOINT", f"http://{host_ip}:{MEGA_SERVICE_PORT}/v1/codegen"
     )
 
-    # dataprep_ingest_endpoint = f"{DATAPREP_ENDPOINT}/ingest"
-    # dataprep_get_files_endpoint = f"{DATAPREP_ENDPOINT}/get"
-    # dataprep_delete_files_endpoint = f"{DATAPREP_ENDPOINT}/delete"
-    # dataprep_get_indices_endpoint = f"{DATAPREP_ENDPOINT}/indices"
-
-
     args = parser.parse_args()
-    # logger.info(f"args: {args}")
     global gateway_addr
     gateway_addr = backend_service_endpoint
     global dataprep_ingest_addr