diff --git a/helm-charts/chatqna/README.md b/helm-charts/chatqna/README.md
index 16d090df..a50e87a7 100644
--- a/helm-charts/chatqna/README.md
+++ b/helm-charts/chatqna/README.md
@@ -77,3 +77,7 @@ Open a browser to access `http://<k8s-node-ip-address>:${port}` to play with the
 | service.port                           | string | `"8888"`                      |                                                                                                                                         |
 | tgi.LLM_MODEL_ID                       | string | `"Intel/neural-chat-7b-v3-3"` | Models id from https://huggingface.co/, or predownloaded model directory                                                                |
 | global.horizontalPodAutoscaler.enabled | bop;   | false                         | HPA autoscaling for the TGI and TEI service deployments based on metrics they provide. See HPA section in ../README.md before enabling! |
+
+## Troubleshooting
+
+If you encount any issues, please refer to [ChatQnA Troubleshooting](troubleshooting.md)
diff --git a/helm-charts/chatqna/troubleshooting.md b/helm-charts/chatqna/troubleshooting.md
new file mode 100644
index 00000000..cad40340
--- /dev/null
+++ b/helm-charts/chatqna/troubleshooting.md
@@ -0,0 +1,153 @@
+## ChatQnA Troubleshooting
+
+After deploying chatqna with helm chart, we can use the following command to check whether each service is working properly.
+These commands show the steps how RAG work with LLM.
+
+### a function to get the endpoint of service
+
+This is a based command to get each service endpoint of chatqna components.
+
+```bash
+svc_endpoint() {
+  endpoint=$(kubectl -n ${2:-default} get svc -l ${1} -o jsonpath='{.items[0].spec.clusterIP}:{.items[0].spec.ports[0].port}')
+  echo "${endpoint}"
+}
+```
+
+### define the namespace of service
+
+Please specify the namespace of chatqna, it will be **default** if not define.
+
+```
+# define your namespace
+ns=opea-chatqna
+```
+
+Check the available namespace by:
+
+```console
+kubectl get ns
+NAME                          STATUS   AGE
+calico-system                 Active   21d
+cert-manager                  Active   21d
+default                       Active   21d
+kube-public                   Active   21d
+kube-system                   Active   21d
+nfd                           Active   21d
+observability                 Active   21d
+opea-chatqna                  Active   21d
+openebs                       Active   21d
+orchestrator-system           Active   21d
+tigera-operator               Active   21d
+```
+
+### Update a file to database
+
+This step will upload a pdf about nike revenue information to vector database.
+
+```bash
+# data-prep
+label='app.kubernetes.io/name=data-prep'
+
+wget https://raw.githubusercontent.com/opea-project/GenAIComps/refs/heads/main/comps/retrievers/redis/data/nke-10k-2023.pdf
+
+endpoint=$(svc_endpoint ${label} ${ns})
+echo $endpoint
+curl -x "" -X POST "http://${endpoint}/v1/dataprep" \
+     -H "Content-Type: multipart/form-data" \
+     -F "files=@./nke-10k-2023.pdf"
+```
+
+> **_NOTE:_** Get the service label by:
+>
+> ```bash
+> kubectl get -n ${ns} svc -o json | jq .items[].metadata.labels
+> ```
+>
+> you can use **grep** to filter the labels by key.
+
+### get the embedding of input
+
+This step will get the embedding of your input/question.
+
+```bash
+label='app.kubernetes.io/name=tei'
+input="What is the revenue of Nike in 2023?"
+
+endpoint=$(svc_endpoint ${label} ${ns})
+echo $endpoint
+
+your_embedding=$(curl -x "" http://${endpoint}/embed \
+    -X POST \
+    -d '{"inputs":"'"$input"'"}' \
+    -H 'Content-Type: application/json' |jq .[0] -c)
+```
+
+### get the retriever docs
+
+This step will get related docs related to your input/question.
+
+```bash
+label='app.kubernetes.io/name=retriever-usvc'
+text=$input
+
+endpoint=$(svc_endpoint ${label} ${ns})
+echo $endpoint
+
+retrieved_docs=$(curl -x "" http://${endpoint}/v1/retrieval \
+  -X POST \
+  -d "{\"text\":\"${text}\",\"embedding\":${your_embedding}}" \
+  -H 'Content-Type: application/json' | jq -c .retrieved_docs)
+```
+
+### reranking the docs
+
+This step will get related docs most relevant to your input/question.
+
+```bash
+label='app.kubernetes.io/name=reranking-usvc'
+query=$input
+
+endpoint=$(svc_endpoint ${label} ${ns})
+echo $endpoint
+
+reranking_docs=$(curl -x "" http://${endpoint}/v1/reranking \
+  -X POST \
+  -d '{"initial_query":"'"$query"'", "retrieved_docs": '"$retrieved_docs"'}' \
+  -H 'Content-Type: application/json' | jq -c .documents[0])
+
+# remove "
+reranking_docs=$(sed 's/\\"/ /g' <<< "${reranking_docs}")
+reranking_docs=$(tr -d '"' <<< "${reranking_docs}")
+```
+
+### TGI Q and A
+
+This step will render the answer of your question.
+
+```bash
+label='app.kubernetes.io/name=tgi'
+
+endpoint=$(svc_endpoint ${label} ${ns})
+echo $endpoint
+
+# your question
+query=${input}
+# inputs template.
+inputs="### You are a helpful, respectful and honest assistant to help the user with questions. Please refer to the search results obtained from the local knowledge base. But be careful to not incorporate the information that you think is not relevant to the question. If you don't know the answer to a question, please don't share false information. ### Search results: ${reranking_docs} ### Question: ${query} \n\n### Answer:"
+
+curl -x "" http://${endpoint}/generate \
+  -X POST \
+  -d '{"inputs":"'"${inputs}"'","parameters":{"max_new_tokens":1024, "do_sample": true}}' \
+  -H 'Content-Type: application/json'
+```
+
+The output
+
+```console
+{"generated_text":" In fiscal 2023, NIKE, Inc. achieved record Revenues of $51.2 billion."}
+```
+
+### REF
+
+[Build Mega Service of ChatQnA on Xeon](https://github.com/opea-project/GenAIExamples/tree/main/ChatQnA/docker_compose/intel/cpu/xeon)