diff --git a/EdgeCraftRAG/Dockerfile.server b/EdgeCraftRAG/Dockerfile.server
index 4ac52700a8..119b0ec3f9 100755
--- a/EdgeCraftRAG/Dockerfile.server
+++ b/EdgeCraftRAG/Dockerfile.server
@@ -1,30 +1,17 @@
 FROM python:3.11-slim
 
 SHELL ["/bin/bash", "-o", "pipefail", "-c"]
-
-RUN apt-get update -y && apt-get install -y --no-install-recommends --fix-missing \
-    libjemalloc-dev \
-    libmagic1 \
-    libglib2.0-0 \
-    poppler-utils \
-    tesseract-ocr
-
-RUN apt-get update && apt-get install -y gnupg wget git
-RUN wget -qO - https://repositories.intel.com/gpu/intel-graphics.key | \
-    gpg --yes --dearmor --output /usr/share/keyrings/intel-graphics.gpg
-RUN echo "deb [arch=amd64,i386 signed-by=/usr/share/keyrings/intel-graphics.gpg] https://repositories.intel.com/gpu/ubuntu jammy client" | \
-    tee /etc/apt/sources.list.d/intel-gpu-jammy.list
-RUN apt-get update && apt-get install -y \
-    intel-opencl-icd intel-level-zero-gpu \
-    intel-level-zero-gpu-raytracing \
-    intel-media-va-driver-non-free libmfx1 libmfxgen1 libvpl2 \
-    libegl-mesa0 libegl1-mesa libegl1-mesa-dev libgbm1 libgl1-mesa-dev libgl1-mesa-dri \
-    libglapi-mesa libgles2-mesa-dev libglx-mesa0 libigdgmm12 libxatracker2 mesa-va-drivers \
-    mesa-vdpau-drivers mesa-vulkan-drivers va-driver-all vainfo hwinfo clinfo 
+RUN apt-get update && apt-get install -y gnupg2 wget git
+RUN apt-get remove -y libze-intel-gpu1 libigc1 libigdfcl1 libze-dev || true; \
+    apt-get update; \
+    apt-get install -y curl
+RUN curl -sL 'https://keyserver.ubuntu.com/pks/lookup?fingerprint=on&op=get&search=0x0C0E6AF955CE463C03FC51574D098D70AFBE5E1F' | tee /etc/apt/trusted.gpg.d/driver.asc
+RUN echo -e "Types: deb\nURIs: https://ppa.launchpadcontent.net/kobuk-team/intel-graphics/ubuntu/\nSuites: plucky\nComponents: main\nSigned-By: /etc/apt/trusted.gpg.d/driver.asc" > /etc/apt/sources.list.d/driver.sources
+RUN apt-get update && apt-get install -y libze-intel-gpu1 libze1 intel-metrics-discovery intel-opencl-icd clinfo intel-gsc && apt-get install -y libze-intel-gpu1 libze1 intel-metrics-discovery intel-opencl-icd clinfo intel-gsc && apt-get install -y libze-dev intel-ocloc libze-intel-gpu-raytracing
 
 RUN useradd -m -s /bin/bash user && \
     mkdir -p /home/user && \
-    chown -R user /home/user/ 
+    chown -R user /home/user/
 
 RUN mkdir /templates && \
     chown -R user /templates
@@ -33,17 +20,19 @@ RUN chown -R user /templates/default_prompt.txt
 
 COPY ./edgecraftrag /home/user/edgecraftrag
 
-RUN mkdir -p /home/user/ui_cache 
+RUN mkdir -p /home/user/ui_cache
 ENV UI_UPLOAD_PATH=/home/user/ui_cache
 
 USER user
 
 WORKDIR /home/user/edgecraftrag
-RUN pip install --no-cache-dir --upgrade pip setuptools==70.0.0 && \
-    pip install --no-cache-dir --extra-index-url https://download.pytorch.org/whl/cpu -r requirements.txt
+RUN pip3 install --no-cache-dir --upgrade setuptools==70.0.0 --break-system-packages && \
+    pip3 install --no-cache-dir --extra-index-url https://download.pytorch.org/whl/cpu -r requirements.txt --break-system-packages
+
+RUN pip3 install --no-cache-dir docarray==0.40.0 --break-system-packages
 
 WORKDIR /home/user/
 RUN git clone https://github.com/openvinotoolkit/openvino.genai.git genai
 ENV PYTHONPATH="$PYTHONPATH:/home/user/genai/tools/llm_bench"
 
-ENTRYPOINT ["python", "-m", "edgecraftrag.server"]
\ No newline at end of file
+ENTRYPOINT ["python3", "-m", "edgecraftrag.server"]
diff --git a/EdgeCraftRAG/README.md b/EdgeCraftRAG/README.md
index 314feb3480..ba30b7bf4c 100755
--- a/EdgeCraftRAG/README.md
+++ b/EdgeCraftRAG/README.md
@@ -5,6 +5,12 @@ Retrieval-Augmented Generation system for edge solutions. It is designed to
 curate the RAG pipeline to meet hardware requirements at edge with guaranteed
 quality and performance.
 
+## What's New
+
+1. Support Intel Arc B60 for model inference
+2. support KBadmin for knowledge base management
+3. support Experience Injection module in UI
+
 ## Table of contents
 
 1. [Architecture](#architecture)
diff --git a/EdgeCraftRAG/assets/img/kbadmin_index.png b/EdgeCraftRAG/assets/img/kbadmin_index.png
new file mode 100644
index 0000000000..7383a01c79
Binary files /dev/null and b/EdgeCraftRAG/assets/img/kbadmin_index.png differ
diff --git a/EdgeCraftRAG/assets/img/kbadmin_kb.png b/EdgeCraftRAG/assets/img/kbadmin_kb.png
new file mode 100644
index 0000000000..40f6909a9b
Binary files /dev/null and b/EdgeCraftRAG/assets/img/kbadmin_kb.png differ
diff --git a/EdgeCraftRAG/assets/img/kbadmin_type.png b/EdgeCraftRAG/assets/img/kbadmin_type.png
new file mode 100644
index 0000000000..012ebb0bd8
Binary files /dev/null and b/EdgeCraftRAG/assets/img/kbadmin_type.png differ
diff --git a/EdgeCraftRAG/docker_compose/intel/gpu/arc/README.md b/EdgeCraftRAG/docker_compose/intel/gpu/arc/README.md
index d4d283d8f1..94d920bbc4 100755
--- a/EdgeCraftRAG/docker_compose/intel/gpu/arc/README.md
+++ b/EdgeCraftRAG/docker_compose/intel/gpu/arc/README.md
@@ -10,25 +10,27 @@ This document outlines the deployment process for Edge Craft Retrieval-Augmented
 
 This section describes how to quickly deploy and test the EdgeCraftRAG service manually on Intel® Arc® platform. The basic steps are:
 
-1. [Prerequisites](#prerequisites)
-2. [Access the Code](#access-the-code)
-3. [Prepare models](#prepare-models)
-4. [Prepare env variables and configurations](#prepare-env-variables-and-configurations)
-5. [Configure the Deployment Environment](#configure-the-deployment-environment)
-6. [Deploy the Service Using Docker Compose](#deploy-the-service-using-docker-compose)
-7. [Access UI](#access-ui)
-8. [Cleanup the Deployment](#cleanup-the-deployment)
+1. [Prerequisites](#1-prerequisites)
+2. [Access the Code](#2-access-the-code)
+3. [Prepare models](#3-prepare-models)
+4. [Prepare env variables and configurations](#4-prepare-env-variables-and-configurations)
+5. [Deploy the Service on Arc A770 Using Docker Compose](#5-deploy-the-service-on-intel-gpu-using-docker-compose)
+6. [Access UI](#6-access-ui)
+7. [Cleanup the Deployment](#7-cleanup-the-deployment)
 
-### Prerequisites
+### 1. Prerequisites
 
 EC-RAG supports vLLM deployment(default method) and local OpenVINO deployment for Intel Arc GPU. Prerequisites are shown as below:  
 Hardware: Intel Arc A770  
 OS: Ubuntu Server 22.04.1 or newer (at least 6.2 LTS kernel)  
 Driver & libraries: please to [Installing GPUs Drivers](https://dgpu-docs.intel.com/driver/installation-rolling.html#installing-gpu-drivers) for detailed driver & libraries setup
 
+Hardware: Intel Arc B60  
+please to [Install Native Environment](https://github.com/intel/llm-scaler/tree/main/vllm#11-install-native-environment) for detailed setup
+
 Below steps are based on **vLLM** as inference engine, if you want to choose **OpenVINO**, please refer to [OpenVINO Local Inference](../../../../docs/Advanced_Setup.md#openvino-local-inference)
 
-### Access the Code
+### 2. Access the Code
 
 Clone the GenAIExample repository and access the EdgeCraftRAG Intel® Arc® platform Docker Compose files and supporting scripts:
 
@@ -43,7 +45,7 @@ Checkout a released version, such as v1.3:
 git checkout v1.3
 ```
 
-### Prepare models
+### 3. Prepare models
 
 ```bash
 # Prepare models for embedding, reranking:
@@ -62,7 +64,7 @@ modelscope download --model $LLM_MODEL --local_dir "${MODEL_PATH}/${LLM_MODEL}"
 # huggingface-cli download $LLM_MODEL --local-dir "${MODEL_PATH}/${LLM_MODEL}"
 ```
 
-### Prepare env variables and configurations
+### 4. Prepare env variables and configurations
 
 Below steps are for single Intel Arc GPU inference, if you want to setup multi Intel Arc GPUs inference, please refer to [Multi-ARC Setup](../../../../docs/Advanced_Setup.md#multi-arc-setup)
 
@@ -77,32 +79,23 @@ export HOST_IP=$ip_address # Your host ip
 export VIDEOGROUPID=$(getent group video | cut -d: -f3)
 export RENDERGROUPID=$(getent group render | cut -d: -f3)
 
-# If you have a proxy configured, uncomment below line
-# export no_proxy=${no_proxy},${HOST_IP},edgecraftrag,edgecraftrag-server
-# export NO_PROXY=${NO_PROXY},${HOST_IP},edgecraftrag,edgecraftrag-server
+# If you have a proxy configured, execute below line
+export no_proxy=${no_proxy},${HOST_IP},edgecraftrag,edgecraftrag-server
+export NO_PROXY=${NO_PROXY},${HOST_IP},edgecraftrag,edgecraftrag-server
 # If you have a HF mirror configured, it will be imported to the container
 # export HF_ENDPOINT=https://hf-mirror.com # your HF mirror endpoint"
 
 # Make sure all 3 folders have 1000:1000 permission, otherwise
-# chown 1000:1000 ${MODEL_PATH} ${PWD} # the default value of DOC_PATH and TMPFILE_PATH is PWD ,so here we give permission to ${PWD}
+chown 1000:1000 ${MODEL_PATH} ${PWD} # the default value of DOC_PATH and TMPFILE_PATH is PWD ,so here we give permission to ${PWD}
 # In addition, also make sure the .cache folder has 1000:1000 permission, otherwise
-# chown 1000:1000 -R $HOME/.cache
+chown 1000:1000 -R $HOME/.cache
 ```
 
 For more advanced env variables and configurations, please refer to [Prepare env variables for vLLM deployment](../../../../docs/Advanced_Setup.md#prepare-env-variables-for-vllm-deployment)
 
-#### Generate nginx config file
-
-```bash
-export VLLM_SERVICE_PORT_0=8100 # You can set your own port for vllm service
-# Generate your nginx config file
-# nginx-conf-generator.sh requires 2 parameters: DP_NUM and output filepath
-bash nginx/nginx-conf-generator.sh 1 nginx/nginx.conf
-# set NGINX_CONFIG_PATH
-export NGINX_CONFIG_PATH="${PWD}/nginx/nginx.conf"
-```
+### 5. Deploy the Service on Intel GPU Using Docker Compose
 
-### Deploy the Service Using Docker Compose
+set Milvus DB and chat history round for inference:
 
 ```bash
 # EC-RAG support Milvus as persistent database, by default milvus is disabled, you can choose to set MILVUS_ENABLED=1 to enable it
@@ -112,12 +105,45 @@ export MILVUS_ENABLED=0
 
 # EC-RAG support chat history round setting, by default chat history is disabled, you can set CHAT_HISTORY_ROUND to control it
 # export CHAT_HISTORY_ROUND= # change to your preference
+```
+
+#### option a. Deploy the Service on Arc A770 Using Docker Compose
+
+```bash
+export VLLM_SERVICE_PORT_0=8100 # You can set your own port for vllm service
+# Generate your nginx config file
+# nginx-conf-generator.sh requires 2 parameters: DP_NUM and output filepath
+bash nginx/nginx-conf-generator.sh 1 nginx/nginx.conf
+# set NGINX_CONFIG_PATH
+export NGINX_CONFIG_PATH="${PWD}/nginx/nginx.conf"
 
 # Launch EC-RAG service with compose
 docker compose -f docker_compose/intel/gpu/arc/compose_vllm.yaml up -d
 ```
 
-### Access UI
+#### option b. Deploy the Service on Arc B60 Using Docker Compose
+
+```bash
+# Besides MILVUS_ENABLED and CHAT_HISTORY_ROUND, below environments are exposed for vLLM config, you can change them to your preference:
+# export VLLM_SERVICE_PORT_B60=8086
+# export DTYPE=float16
+# export TP=1 # for multi GPU, you can change TP value
+# export DP=1
+# export ZE_AFFINITY_MASK=0 # for multi GPU, you can export ZE_AFFINITY_MASK=0,1,2...
+# export ENFORCE_EAGER=1
+# export TRUST_REMOTE_CODE=1
+# export DISABLE_SLIDING_WINDOW=1
+# export GPU_MEMORY_UTIL=0.8
+# export NO_ENABLE_PREFIX_CACHING=1
+# export MAX_NUM_BATCHED_TOKENS=8192
+# export DISABLE_LOG_REQUESTS=1
+# export MAX_MODEL_LEN=49152
+# export BLOCK_SIZE=64
+# export QUANTIZATION=fp8
+docker compose -f docker_compose/intel/gpu/arc/compose_vllm_b60.yaml up -d
+```
+
+### 6. Access UI
 
 Open your browser, access http://${HOST_IP}:8082
 
@@ -126,12 +152,13 @@ Open your browser, access http://${HOST_IP}:8082
 Below is the UI front page, for detailed operations on UI and EC-RAG settings, please refer to [Explore_Edge_Craft_RAG](../../../../docs/Explore_Edge_Craft_RAG.md)
 ![front_page](../../../../assets/img/front_page.png)
 
-### Cleanup the Deployment
+### 7. Cleanup the Deployment
 
 To stop the containers associated with the deployment, execute the following command:
 
 ```
 docker compose -f docker_compose/intel/gpu/arc/compose_vllm.yaml down
+# or docker compose -f docker_compose/intel/gpu/arc/compose_vllm_b60.yaml down
 ```
 
 All the EdgeCraftRAG containers will be stopped and then removed on completion of the "down" command.
diff --git a/EdgeCraftRAG/docker_compose/intel/gpu/arc/compose.yaml b/EdgeCraftRAG/docker_compose/intel/gpu/arc/compose.yaml
index 488bccdf7a..8c74ba2717 100755
--- a/EdgeCraftRAG/docker_compose/intel/gpu/arc/compose.yaml
+++ b/EdgeCraftRAG/docker_compose/intel/gpu/arc/compose.yaml
@@ -71,7 +71,6 @@ services:
       no_proxy: ${no_proxy}
       http_proxy: ${http_proxy}
       https_proxy: ${https_proxy}
-      HF_ENDPOINT: ${HF_ENDPOINT}
       vLLM_ENDPOINT: ${vLLM_ENDPOINT:-http://${HOST_IP}:${NGINX_PORT:-8086}}
       ENABLE_BENCHMARK: ${ENABLE_BENCHMARK:-false}
       MAX_MODEL_LEN: ${MAX_MODEL_LEN:-5000}
@@ -80,7 +79,6 @@ services:
       - ${MODEL_PATH:-${PWD}}:/home/user/models
       - ${DOC_PATH:-${PWD}}:/home/user/docs
       - ${TMPFILE_PATH:-${PWD}}:/home/user/ui_cache
-      - ${HF_CACHE:-${HOME}/.cache}:/home/user/.cache
       - ${PROMPT_PATH:-${PWD}}:/templates/custom
     restart: always
     ports:
diff --git a/EdgeCraftRAG/docker_compose/intel/gpu/arc/compose_vllm.yaml b/EdgeCraftRAG/docker_compose/intel/gpu/arc/compose_vllm.yaml
index a1afa20eb9..c0e14dd939 100644
--- a/EdgeCraftRAG/docker_compose/intel/gpu/arc/compose_vllm.yaml
+++ b/EdgeCraftRAG/docker_compose/intel/gpu/arc/compose_vllm.yaml
@@ -72,17 +72,15 @@ services:
       no_proxy: ${no_proxy}
       http_proxy: ${http_proxy}
       https_proxy: ${https_proxy}
-      HF_ENDPOINT: ${HF_ENDPOINT}
       vLLM_ENDPOINT: ${vLLM_ENDPOINT:-http://${HOST_IP}:${NGINX_PORT:-8086}}
       LLM_MODEL: ${LLM_MODEL}
       ENABLE_BENCHMARK: ${ENABLE_BENCHMARK:-false}
-      MAX_MODEL_LEN: ${MAX_MODEL_LEN:-5000}
+      MAX_MODEL_LEN: ${MAX_MODEL_LEN:-10240}
       CHAT_HISTORY_ROUND: ${CHAT_HISTORY_ROUND:-0}
     volumes:
       - ${MODEL_PATH:-${PWD}}:/home/user/models
       - ${DOC_PATH:-${PWD}}:/home/user/docs
       - ${TMPFILE_PATH:-${PWD}}:/home/user/ui_cache
-      - ${HF_CACHE:-${HOME}/.cache}:/home/user/.cache
       - ${PROMPT_PATH:-${PWD}}:/templates/custom
     restart: always
     ports:
@@ -157,7 +155,6 @@ services:
       no_proxy: ${no_proxy}
       http_proxy: ${http_proxy}
       https_proxy: ${https_proxy}
-      HF_ENDPOINT: ${HF_ENDPOINT}
       MODEL_PATH: "/llm/models"
       SERVED_MODEL_NAME: ${LLM_MODEL}
       TENSOR_PARALLEL_SIZE: ${TENSOR_PARALLEL_SIZE:-1}
diff --git a/EdgeCraftRAG/docker_compose/intel/gpu/arc/compose_vllm_b60.yaml b/EdgeCraftRAG/docker_compose/intel/gpu/arc/compose_vllm_b60.yaml
new file mode 100644
index 0000000000..f10b476fc1
--- /dev/null
+++ b/EdgeCraftRAG/docker_compose/intel/gpu/arc/compose_vllm_b60.yaml
@@ -0,0 +1,186 @@
+# Copyright (C) 2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+services:
+  etcd:
+    container_name: milvus-etcd
+    image: quay.io/coreos/etcd:v3.5.5
+    environment:
+      - ETCD_AUTO_COMPACTION_MODE=revision
+      - ETCD_AUTO_COMPACTION_RETENTION=1000
+      - ETCD_QUOTA_BACKEND_BYTES=4294967296
+      - ETCD_SNAPSHOT_COUNT=50000
+    volumes:
+      - ${DOCKER_VOLUME_DIRECTORY:-${PWD}}/volumes/etcd:/etcd
+    command: etcd -advertise-client-urls=http://127.0.0.1:2379 -listen-client-urls http://0.0.0.0:2379 --data-dir /etcd
+    healthcheck:
+      test: ["CMD", "etcdctl", "endpoint", "health"]
+      interval: 30s
+      timeout: 20s
+      retries: 3
+    deploy:
+      replicas: ${MILVUS_ENABLED:-0}
+  minio:
+    container_name: milvus-minio
+    image: minio/minio:RELEASE.2023-03-20T20-16-18Z
+    environment:
+      MINIO_ACCESS_KEY: minioadmin
+      MINIO_SECRET_KEY: minioadmin
+    ports:
+      - "${MINIO_PORT1:-5044}:9001"
+      - "${MINIO_PORT2:-5043}:9000"
+    volumes:
+      - ${DOCKER_VOLUME_DIRECTORY:-${PWD}}/volumes/minio:/minio_data
+    command: minio server /minio_data --console-address ":9001"
+    healthcheck:
+      test: ["CMD", "curl", "-f", "http://localhost:9000/minio/health/live"]
+      interval: 30s
+      timeout: 20s
+      retries: 3
+    deploy:
+      replicas: ${MILVUS_ENABLED:-0}
+  milvus-standalone:
+    container_name: milvus-standalone
+    image: milvusdb/milvus:v2.4.6
+    command: ["milvus", "run", "standalone"]
+    security_opt:
+      - seccomp:unconfined
+    environment:
+      ETCD_ENDPOINTS: etcd:2379
+      MINIO_ADDRESS: minio:9000
+    volumes:
+      - ./milvus.yaml:/milvus/configs/milvus.yaml
+      - ${DOCKER_VOLUME_DIRECTORY:-${PWD}}/volumes/milvus:/var/lib/milvus
+    healthcheck:
+      test: ["CMD", "curl", "-f", "http://localhost:9091/healthz"]
+      interval: 30s
+      start_period: 90s
+      timeout: 20s
+      retries: 3
+    ports:
+      - "19530:19530"
+      - "${MILVUS_STANDALONE_PORT:-9091}:9091"
+    depends_on:
+      - "etcd"
+      - "minio"
+    deploy:
+      replicas: ${MILVUS_ENABLED:-0}
+  edgecraftrag-server:
+    image: ${REGISTRY:-opea}/edgecraftrag-server:${TAG:-latest}
+    container_name: edgecraftrag-server
+    environment:
+      no_proxy: ${no_proxy}
+      http_proxy: ${http_proxy}
+      https_proxy: ${https_proxy}
+      vLLM_ENDPOINT: ${vLLM_ENDPOINT:-http://${HOST_IP}:${NGINX_PORT:-8086}}
+      LLM_MODEL: ${LLM_MODEL}
+      ENABLE_BENCHMARK: ${ENABLE_BENCHMARK:-false}
+      MAX_MODEL_LEN: ${MAX_MODEL_LEN:-49152}
+      CHAT_HISTORY_ROUND: ${CHAT_HISTORY_ROUND:-0}
+    volumes:
+      - ${MODEL_PATH:-${PWD}}:/home/user/models
+      - ${DOC_PATH:-${PWD}}:/home/user/docs
+      - ${TMPFILE_PATH:-${PWD}}:/home/user/ui_cache
+      - ${PROMPT_PATH:-${PWD}}:/templates/custom
+    restart: always
+    ports:
+      - ${PIPELINE_SERVICE_PORT:-16010}:${PIPELINE_SERVICE_PORT:-16010}
+    devices:
+      - /dev/dri:/dev/dri
+    group_add:
+      - ${VIDEOGROUPID:-44}
+      - ${RENDERGROUPID:-109}
+  ecrag:
+    image: ${REGISTRY:-opea}/edgecraftrag:${TAG:-latest}
+    container_name: edgecraftrag
+    environment:
+      no_proxy: ${no_proxy}
+      http_proxy: ${http_proxy}
+      https_proxy: ${https_proxy}
+      MEGA_SERVICE_PORT: ${MEGA_SERVICE_PORT:-16011}
+      MEGA_SERVICE_HOST_IP: ${MEGA_SERVICE_HOST_IP:-${HOST_IP}}
+      PIPELINE_SERVICE_PORT: ${PIPELINE_SERVICE_PORT:-16010}
+      PIPELINE_SERVICE_HOST_IP: ${PIPELINE_SERVICE_HOST_IP:-${HOST_IP}}
+    restart: always
+    ports:
+      - ${MEGA_SERVICE_PORT:-16011}:${MEGA_SERVICE_PORT:-16011}
+    depends_on:
+      - edgecraftrag-server
+  edgecraftrag-ui:
+    image: ${REGISTRY:-opea}/edgecraftrag-ui:${TAG:-latest}
+    container_name: edgecraftrag-ui
+    environment:
+      no_proxy: ${no_proxy}
+      http_proxy: ${http_proxy}
+      https_proxy: ${https_proxy}
+      MEGA_SERVICE_PORT: ${MEGA_SERVICE_PORT:-16011}
+      MEGA_SERVICE_HOST_IP: ${MEGA_SERVICE_HOST_IP:-${HOST_IP}}
+      PIPELINE_SERVICE_PORT: ${PIPELINE_SERVICE_PORT:-16010}
+      PIPELINE_SERVICE_HOST_IP: ${PIPELINE_SERVICE_HOST_IP:-${HOST_IP}}
+      UI_SERVICE_PORT: ${UI_SERVICE_PORT:-8082}
+      UI_SERVICE_HOST_IP: ${UI_SERVICE_HOST_IP:-0.0.0.0}
+    volumes:
+      - ${TMPFILE_PATH:-${PWD}}:/home/user/ui_cache
+    restart: always
+    ports:
+      - ${UI_SERVICE_PORT:-8082}:${UI_SERVICE_PORT:-8082}
+    depends_on:
+      - edgecraftrag-server
+      - ecrag
+  llm-serving-xpu:
+    container_name: ipex-serving-xpu-container
+    image: intel/llm-scaler-vllm:1.0
+    privileged: true
+    restart: always
+    ports:
+      - ${VLLM_SERVICE_PORT_B60:-8086}:${VLLM_SERVICE_PORT_B60:-8086}
+    volumes:
+      - ${MODEL_PATH}:/workspace/vllm/models
+    devices:
+      - /dev/dri:/dev/dri
+    environment:
+      DTYPE: ${DTYPE:-float16}
+      VLLM_SERVICE_PORT_B60: ${VLLM_SERVICE_PORT_B60:-8086}
+      ZE_AFFINITY_MASK: ${ZE_AFFINITY_MASK:-0}
+      ENFORCE_EAGER: ${ENFORCE_EAGER:-1}
+      TRUST_REMOTE_CODE: ${TRUST_REMOTE_CODE:-1}
+      DISABLE_SLIDING_WINDOW: ${DISABLE_SLIDING_WINDOW:-1}
+      GPU_MEMORY_UTIL: ${GPU_MEMORY_UTIL:-0.8}
+      NO_ENABLE_PREFIX_CACHING: ${NO_ENABLE_PREFIX_CACHING:-1}
+      MAX_NUM_BATCHED_TOKENS: ${MAX_NUM_BATCHED_TOKENS:-8192}
+      DISABLE_LOG_REQUESTS: ${DISABLE_LOG_REQUESTS:-1}
+      MAX_MODEL_LEN: ${MAX_MODEL_LEN:-49152}
+      BLOCK_SIZE: ${BLOCK_SIZE:-64}
+      QUANTIZATION: ${QUANTIZATION:-fp8}
+      LLM_MODEL: ${LLM_MODEL}
+      TP: ${TP:-1}
+      DP: ${DP:-1}
+    entrypoint:
+      /bin/bash -c "
+      cd  /workspace/vllm/models &&
+      VLLM_OFFLOAD_WEIGHTS_BEFORE_QUANT=1 \
+      TORCH_LLM_ALLREDUCE=1 \
+      VLLM_USE_V1=1 \
+      CCL_ZE_IPC_EXCHANGE=pidfd \
+      VLLM_ALLOW_LONG_MAX_MODEL_LEN=1 \
+      VLLM_WORKER_MULTIPROC_METHOD=spawn \
+      python3 -m vllm.entrypoints.openai.api_server \
+      --model $${LLM_MODEL} \
+      --dtype $${DTYPE} \
+      --enforce-eager \
+      --port $${VLLM_SERVICE_PORT_B60} \
+      --trust-remote-code \
+      --disable-sliding-window \
+      --gpu-memory-util $${GPU_MEMORY_UTIL} \
+      --no-enable-prefix-caching \
+      --max-num-batched-tokens $${MAX_NUM_BATCHED_TOKENS} \
+      --disable-log-requests \
+      --max-model-len $${MAX_MODEL_LEN} \
+      --block-size $${BLOCK_SIZE} \
+      --quantization $${QUANTIZATION} \
+      --distributed-executor-backend mp \
+      -tp=$${TP} \
+      -dp=$${DP}"
+networks:
+  default:
+    driver: bridge
diff --git a/EdgeCraftRAG/docker_compose/intel/gpu/arc/multi-arc-yaml-generator.sh b/EdgeCraftRAG/docker_compose/intel/gpu/arc/multi-arc-yaml-generator.sh
index 2a819eb552..42d21c0370 100644
--- a/EdgeCraftRAG/docker_compose/intel/gpu/arc/multi-arc-yaml-generator.sh
+++ b/EdgeCraftRAG/docker_compose/intel/gpu/arc/multi-arc-yaml-generator.sh
@@ -87,17 +87,15 @@ services:
       no_proxy: \${no_proxy}
       http_proxy: \${http_proxy}
       https_proxy: \${https_proxy}
-      HF_ENDPOINT: \${HF_ENDPOINT}
       vLLM_ENDPOINT: \${vLLM_ENDPOINT:-http://\${HOST_IP}:\${NGINX_PORT:-8086}}
       LLM_MODEL: \${LLM_MODEL}
       ENABLE_BENCHMARK: \${ENABLE_BENCHMARK:-false}
-      MAX_MODEL_LEN: \${MAX_MODEL_LEN:-5000}
+      MAX_MODEL_LEN: \${MAX_MODEL_LEN:-10240}
       CHAT_HISTORY_ROUND: \${CHAT_HISTORY_ROUND:-0}
     volumes:
       - \${MODEL_PATH:-\${PWD}}:/home/user/models
       - \${DOC_PATH:-\${PWD}}:/home/user/docs
       - \${TMPFILE_PATH:-\${PWD}}:/home/user/ui_cache
-      - \${HF_CACHE:-\${HOME}/.cache}:/home/user/.cache
       - \${PROMPT_PATH:-\${PWD}}:/templates/custom
     restart: always
     ports:
@@ -176,7 +174,6 @@ for ((i = 0; i < PORT_NUM; i++)); do
       no_proxy: \${no_proxy}
       http_proxy: \${http_proxy}
       https_proxy: \${https_proxy}
-      HF_ENDPOINT: \${HF_ENDPOINT}
       MODEL_PATH: "/llm/models"
       SERVED_MODEL_NAME: \${LLM_MODEL}
       TENSOR_PARALLEL_SIZE: \${TENSOR_PARALLEL_SIZE:-1}
diff --git a/EdgeCraftRAG/docs/API_Guide.md b/EdgeCraftRAG/docs/API_Guide.md
index 804fa45397..c13753596c 100644
--- a/EdgeCraftRAG/docs/API_Guide.md
+++ b/EdgeCraftRAG/docs/API_Guide.md
@@ -205,3 +205,18 @@ curl -X POST http://${HOST_IP}:16010/v1/chatqna/prompt/reset -H "Content-Type: a
 ```bash
 curl -X POST http://${HOST_IP}:16010/v1/chatqna/prompt-file -H "Content-Type: multipart/form-data" -F "file=@your_prompt_file.txt"
 ```
+
+## ChatQnA
+
+### Retrieval API
+
+```bash
+curl -X POST http://${HOST_IP}:16010/v1/retrieval -H "Content-Type: application/json" -d '{"messages":"#Please enter the question you need to retrieve here#", "top_n":5, "max_tokens":512}' | jq '.'
+
+```
+
+### ChatQnA API
+
+```bash
+curl -X POST http://${HOST_IP}:16011/v1/chatqna -H "Content-Type: application/json" -d '{"messages":"#REPLACE WITH YOUR QUESTION HERE#", "top_n":5, "max_tokens":512}' | jq '.'
+```
diff --git a/EdgeCraftRAG/docs/Advanced_Setup.md b/EdgeCraftRAG/docs/Advanced_Setup.md
index ef864fc1f4..ed6a080310 100644
--- a/EdgeCraftRAG/docs/Advanced_Setup.md
+++ b/EdgeCraftRAG/docs/Advanced_Setup.md
@@ -55,9 +55,9 @@ EC-RAG support using local OpenVINO models to do inference, please follow below
 ```bash
 git clone https://github.com/opea-project/GenAIExamples.git
 cd GenAIExamples/EdgeCraftRAG
-docker build --build-arg http_proxy=$http_proxy --build-arg https_proxy=$https_proxy --build-arg no_proxy="$no_proxy" -t opea/edgecraftrag:latest -f Dockerfile .
-docker build --build-arg http_proxy=$http_proxy --build-arg https_proxy=$https_proxy --build-arg no_proxy="$no_proxy" -t opea/edgecraftrag-server:latest -f Dockerfile.server .
-docker build --build-arg http_proxy=$http_proxy --build-arg https_proxy=$https_proxy --build-arg no_proxy="$no_proxy" -t opea/edgecraftrag-ui:latest -f ui/docker/Dockerfile.ui .
+docker build --no-cache --pull --build-arg http_proxy=$http_proxy --build-arg https_proxy=$https_proxy --build-arg no_proxy="$no_proxy" -t opea/edgecraftrag:latest -f Dockerfile .
+docker build --no-cache --pull --build-arg http_proxy=$http_proxy --build-arg https_proxy=$https_proxy --build-arg no_proxy="$no_proxy" -t opea/edgecraftrag-server:latest -f Dockerfile.server .
+docker build --no-cache --pull --build-arg http_proxy=$http_proxy --build-arg https_proxy=$https_proxy --build-arg no_proxy="$no_proxy" -t opea/edgecraftrag-ui:latest -f ui/docker/Dockerfile.ui .
 ```
 
 ### 2. Prepare models
@@ -196,3 +196,18 @@ bash docker_compose/intel/gpu/arc/multi-arc-yaml-generator.sh $DP_NUM docker_com
 ### 3. Start Edge Craft RAG Services with Docker Compose
 
 This section is the same as default vLLM inference section, please refer to [Start Edge Craft RAG Services with Docker Compose](../docker_compose/intel/gpu/arc/README.md#deploy-the-service-using-docker-compose)
+
+## EC-RAG with Kbadmin
+
+EC-RAG support kbadmin as a knowledge base manager  
+Please make sure all the kbadmin services have been launched
+EC-RAG Docker Images preparation is the same as local inference section, please refer to [Build Docker Images](#1-optional-build-docker-images-for-mega-service-server-and-ui-by-your-own)
+Model preparation is the same as vLLM inference section, please refer to [Prepare models](../docker_compose/intel/gpu/arc/README.md#2-prepare-models)
+
+### 1. Start Edge Craft RAG Services with Docker Compose
+
+This section is the same as default vLLM inference section, please refer to [Prepare env variables and configurations](../docker_compose/intel/gpu/arc/README.md#prepare-env-variables-and-configurations) and [Start Edge Craft RAG Services with Docker Compose](../docker_compose/intel/gpu/arc/README.md#deploy-the-service-on-arc-a770-using-docker-compose)
+
+### 2. Access Kbadmin UI
+
+please refer to [ChatQnA with Kbadmin in UI](./Explore_Edge_Craft_RAG.md#chatqna-with-kbadmin-in-ui)
diff --git a/EdgeCraftRAG/docs/Explore_Edge_Craft_RAG.md b/EdgeCraftRAG/docs/Explore_Edge_Craft_RAG.md
index a63b3a9f0e..0a5a91ba5e 100644
--- a/EdgeCraftRAG/docs/Explore_Edge_Craft_RAG.md
+++ b/EdgeCraftRAG/docs/Explore_Edge_Craft_RAG.md
@@ -33,3 +33,23 @@ After knowledge base creation, you can upload the documents for retrieval.
 
 Then, you can submit messages in the chat box in `Chat` page.
 ![chat_with_rag](../assets/img/chatqna.png)
+
+## ChatQnA with Kbadmin in UI
+
+### Kbadmin Pipeline
+
+In the `Node Parser` page, select 'kbadmin' as node parser.
+![kbadmin_node_parser](../assets/img/kbadmin_type.png)
+
+In the `Indexer` page, input embedding and vector DB information, please note the embedding service port is 13020; the vector DB port is 29530.
+![kbadmin_indexer](../assets/img/kbadmin_index.png)
+
+### Upload files & ChatQnA
+
+After the pipeline creation, you can go to `Knowledge Base` page and click `Create Knowledge Base` button to create your knowledge base.  
+Please select 'kbadmin' in `Type`and select kb name from the kbs you created in kbadmin UI page.
+
+![upload_data](../assets/img/kbadmin_kb.png)
+
+Then, you can submit messages in the chat box in `Chat` page.
+![chat_with_rag](../assets/img/chatqna.png)
diff --git a/EdgeCraftRAG/edgecraftrag/api/v1/chatqna.py b/EdgeCraftRAG/edgecraftrag/api/v1/chatqna.py
index c3facef41b..7e0f3aa831 100755
--- a/EdgeCraftRAG/edgecraftrag/api/v1/chatqna.py
+++ b/EdgeCraftRAG/edgecraftrag/api/v1/chatqna.py
@@ -17,6 +17,8 @@
 @chatqna_app.post(path="/v1/retrieval")
 async def retrieval(request: ChatCompletionRequest):
     try:
+        active_kb = ctx.knowledgemgr.get_active_knowledge_base()
+        request.user = active_kb if active_kb else None
         contexts = ctx.get_pipeline_mgr().run_retrieve(chat_request=request)
         serialized_contexts = serialize_contexts(contexts)
 
@@ -32,6 +34,11 @@ async def chatqna(request: ChatCompletionRequest):
     try:
         sessionid = request.user
         set_current_session(sessionid)
+        experience_kb = ctx.knowledgemgr.get_active_experience()
+        active_kb = ctx.knowledgemgr.get_active_knowledge_base()
+        request.user = active_kb if active_kb else None
+        if experience_kb:
+            request.tool_choice = "auto" if experience_kb.experience_active else "none"
         generator = ctx.get_pipeline_mgr().get_active_pipeline().generator
         if generator:
             request.model = generator.model_id
@@ -49,6 +56,16 @@ async def chatqna(request: ChatCompletionRequest):
 @chatqna_app.post(path="/v1/ragqna")
 async def ragqna(request: ChatCompletionRequest):
     try:
+        sessionid = request.user
+        set_current_session(sessionid)
+        experience_kb = ctx.knowledgemgr.get_active_experience()
+        active_kb = ctx.knowledgemgr.get_active_knowledge_base()
+        request.user = active_kb if active_kb else None
+        if experience_kb:
+            request.tool_choice = "auto" if experience_kb.experience_active else "none"
+        generator = ctx.get_pipeline_mgr().get_active_pipeline().generator
+        if generator:
+            request.model = generator.model_id
         res, contexts = ctx.get_pipeline_mgr().run_pipeline(chat_request=request)
         if isinstance(res, GeneratedDoc):
             res = res.text
diff --git a/EdgeCraftRAG/edgecraftrag/api/v1/data.py b/EdgeCraftRAG/edgecraftrag/api/v1/data.py
index a000e46e88..4b3fc1b11d 100755
--- a/EdgeCraftRAG/edgecraftrag/api/v1/data.py
+++ b/EdgeCraftRAG/edgecraftrag/api/v1/data.py
@@ -6,24 +6,26 @@
 from edgecraftrag.api_schema import DataIn, FilesIn
 from edgecraftrag.context import ctx
 from fastapi import FastAPI, File, HTTPException, UploadFile, status
+from werkzeug.utils import secure_filename
 
 data_app = FastAPI()
 
 
 # Upload a text or files
 @data_app.post(path="/v1/data")
-async def add_data(request: DataIn):
+async def add_data(request: DataIn, docs_name: str = None):
+    active_pl = ctx.get_pipeline_mgr().get_active_pipeline()
     docs = []
     if request.text is not None:
         docs.extend(ctx.get_file_mgr().add_text(text=request.text))
     if request.local_path is not None:
-        docs.extend(ctx.get_file_mgr().add_files(docs=request.local_path))
+        docs.extend(ctx.get_file_mgr().add_files(docs=request.local_path, docs_name=docs_name))
 
     nodelist = ctx.get_pipeline_mgr().run_data_prepare(docs=docs)
-    if nodelist is None or len(nodelist) == 0:
-        raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="File not found")
-    pl = ctx.get_pipeline_mgr().get_active_pipeline()
-    ctx.get_node_mgr().add_nodes(pl.node_parser.idx, nodelist)
+    if active_pl.indexer.comp_subtype != "kbadmin_indexer":
+        if nodelist is None or len(nodelist) == 0:
+            raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="File not found")
+    ctx.get_node_mgr().add_nodes(active_pl.node_parser.idx, nodelist)
     return "Done"
 
 
@@ -31,16 +33,24 @@ async def add_data(request: DataIn):
 @data_app.post(path="/v1/data/reindex")
 async def redindex_data():
     pl = ctx.get_pipeline_mgr().get_active_pipeline()
-
+    kb = ctx.get_knowledge_mgr().get_active_knowledge_base()
+    if kb:
+        kb_name = kb.name
+        docs_name = kb_name + pl.name + str(pl.indexer.d)
+    else:
+        kb_name = None
+        docs_name = None
     ctx.get_node_mgr().del_nodes_by_np_idx(pl.node_parser.idx)
-    pl.indexer.reinitialize_indexer()
+    pl.indexer.reinitialize_indexer(kb_name)
     pl.update_indexer_to_retriever()
 
-    all_docs = ctx.get_file_mgr().get_all_docs()
+    all_docs = []
+    docs_list = ctx.get_file_mgr().get_kb_files_by_name(docs_name)
+    for docs_file in docs_list:
+        all_docs.extend(docs_file.documents)
     nodelist = ctx.get_pipeline_mgr().run_data_prepare(docs=all_docs)
     if nodelist is not None and len(nodelist) > 0:
         ctx.get_node_mgr().add_nodes(pl.node_parser.idx, nodelist)
-
     return "Done"
 
 
@@ -48,13 +58,15 @@ async def redindex_data():
 @data_app.post(path="/v1/data/files")
 async def add_files(request: FilesIn):
     docs = []
+    pl = ctx.get_pipeline_mgr().get_active_pipeline()
+    kb = ctx.get_knowledge_mgr().get_active_knowledge_base()
+    docs_name = kb.name + pl.name + str(pl.indexer.d)
     if request.local_paths is not None:
-        docs.extend(ctx.get_file_mgr().add_files(docs=request.local_paths))
+        docs.extend(ctx.get_file_mgr().add_files(docs=request.local_path, kb_name=docs_name))
 
     nodelist = ctx.get_pipeline_mgr().run_data_prepare(docs=docs)
     if nodelist is None or len(nodelist) == 0:
         raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="File not found")
-    pl = ctx.get_pipeline_mgr().get_active_pipeline()
     ctx.get_node_mgr().add_nodes(pl.node_parser.idx, nodelist)
     return "Done"
 
@@ -62,32 +74,47 @@ async def add_files(request: FilesIn):
 # GET files
 @data_app.get(path="/v1/data/files")
 async def get_files():
-    return ctx.get_file_mgr().get_files()
+    return ctx.get_file_mgr().get_all_docs()
 
 
 # GET a file
 @data_app.get(path="/v1/data/files/{name}")
-async def get_file_docs(name):
-    return ctx.get_file_mgr().get_file_by_name_or_id(name)
+async def get_kb_files_by_name(name):
+    return ctx.get_file_mgr().get_kb_files_by_name(name)
 
 
 # DELETE a file
 @data_app.delete(path="/v1/data/files/{name}")
-async def delete_file(name):
-    if ctx.get_file_mgr().del_file(name):
-        pl = ctx.get_pipeline_mgr().get_active_pipeline()
-
+async def delete_file(kb_name, file_path):
+    pl = ctx.get_pipeline_mgr().get_active_pipeline()
+    docs_name = kb_name + pl.name + str(pl.indexer.d)
+    if ctx.get_file_mgr().del_file(docs_name, file_path):
         # Current solution: reindexing all docs after deleting one file
         # TODO: delete the nodes related to the file
         ctx.get_node_mgr().del_nodes_by_np_idx(pl.node_parser.idx)
-        pl.indexer.reinitialize_indexer()
+        pl.indexer.reinitialize_indexer(kb_name)
         pl.update_indexer_to_retriever()
-
-        all_docs = ctx.get_file_mgr().get_all_docs()
+        all_docs = ctx.get_file_mgr().get_file_by_name(docs_name)
         nodelist = ctx.get_pipeline_mgr().run_data_prepare(docs=all_docs)
         if nodelist is not None and len(nodelist) > 0:
             ctx.get_node_mgr().add_nodes(pl.node_parser.idx, nodelist)
 
+        return "File is deleted"
+    else:
+        return "File not found"
+
+
+# DELETE a file
+@data_app.delete(path="/v1/data/all_files/{name}")
+async def delete_all_file(name):
+    if ctx.get_file_mgr().del_kb_file(name):
+        pl = ctx.get_pipeline_mgr().get_active_pipeline()
+
+        # Current solution: reindexing all docs after deleting one file
+        # TODO: delete the nodes related to the file
+        ctx.get_node_mgr().del_nodes_by_np_idx(pl.node_parser.idx)
+        pl.indexer.reinitialize_indexer()
+        pl.update_indexer_to_retriever()
         return f"File {name} is deleted"
     else:
         return f"File {name} not found"
@@ -110,8 +137,6 @@ async def upload_file(file_name: str, file: UploadFile = File(...)):
             )
         os.makedirs(UPLOAD_DIRECTORY, exist_ok=True)
         safe_filename = file.filename
-        # Sanitize the uploaded file's name
-        safe_filename = file.filename
         file_path = os.path.normpath(os.path.join(UPLOAD_DIRECTORY, safe_filename))
         # Ensure file_path is within UPLOAD_DIRECTORY
         if not file_path.startswith(os.path.abspath(UPLOAD_DIRECTORY)):
diff --git a/EdgeCraftRAG/edgecraftrag/api/v1/knowledge_base.py b/EdgeCraftRAG/edgecraftrag/api/v1/knowledge_base.py
index 21e0c0621e..5ac3b23622 100755
--- a/EdgeCraftRAG/edgecraftrag/api/v1/knowledge_base.py
+++ b/EdgeCraftRAG/edgecraftrag/api/v1/knowledge_base.py
@@ -5,10 +5,13 @@
 import json
 import os
 import re
+from typing import Dict, List, Union
 
 from edgecraftrag.api.v1.data import add_data
-from edgecraftrag.api_schema import DataIn, KnowledgeBaseCreateIn
+from edgecraftrag.api_schema import DataIn, ExperienceIn, KnowledgeBaseCreateIn
 from edgecraftrag.base import IndexerType
+from edgecraftrag.components.query_preprocess import query_search
+from edgecraftrag.components.retriever import get_kbs_info
 from edgecraftrag.context import ctx
 from edgecraftrag.utils import compare_mappings
 from fastapi import FastAPI, HTTPException, status
@@ -18,6 +21,7 @@
 
 # Define the root directory for knowledge base files
 KNOWLEDGE_BASE_ROOT = "/home/user/ui_cache"
+CONFIG_DIR = "/home/user/ui_cache/configs"
 
 
 # Get all knowledge bases
@@ -41,15 +45,20 @@ async def get_knowledge_base(knowledge_name: str):
 async def create_knowledge_base(knowledge: KnowledgeBaseCreateIn):
     try:
         active_pl = ctx.get_pipeline_mgr().get_active_pipeline()
+        if not active_pl:
+            raise HTTPException(status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail="Please activate pipeline")
         if not re.match(r"^[a-zA-Z_][a-zA-Z0-9_]*$", knowledge.name):
             raise HTTPException(
                 status_code=status.HTTP_404_NOT_FOUND,
                 detail="Knowledge base names must begin with a letter or underscore",
             )
-        kb = ctx.knowledgemgr.create_knowledge_base(knowledge)
-        if kb.active:
-            active_pl.indexer.reinitialize_indexer(kb.name)
+
+        if knowledge.active and knowledge.comp_type == "knowledge" and knowledge.comp_subtype == "origin_kb":
+            active_pl.indexer.reinitialize_indexer(knowledge.name)
             active_pl.update_indexer_to_retriever()
+        elif knowledge.active and knowledge.comp_subtype == "kbadmin_kb":
+            active_pl.retriever.config_kbadmin_milvus(knowledge.name)
+        kb = ctx.knowledgemgr.create_knowledge_base(knowledge)
         await save_knowledge_to_file()
         return "Create knowledge base successfully"
     except Exception as e:
@@ -63,17 +72,28 @@ async def delete_knowledge_base(knowledge_name: str):
         rm_kb = ctx.knowledgemgr.get_knowledge_base_by_name_or_id(knowledge_name)
         active_kb = ctx.knowledgemgr.get_active_knowledge_base()
         active_pl = ctx.get_pipeline_mgr().get_active_pipeline()
-        if active_kb.name == knowledge_name or active_kb.idx == knowledge_name:
-            raise HTTPException(
-                status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail="Cannot delete a running knowledge base."
-            )
-        kb_file_path = rm_kb.get_file_paths()
-        if kb_file_path:
-            if active_pl.indexer.comp_subtype == "milvus_vector":
-                await remove_file_handler([], knowledge_name)
+        if rm_kb.comp_type == "knowledge" and rm_kb.comp_subtype == "origin_kb":
             if active_kb:
-                active_pl.indexer.reinitialize_indexer(active_kb.name)
-                active_pl.update_indexer_to_retriever()
+                if active_kb.name == knowledge_name or active_kb.idx == knowledge_name:
+                    raise HTTPException(
+                        status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
+                        detail="Cannot delete a running knowledge base.",
+                    )
+            kb_file_path = rm_kb.get_file_paths()
+            if kb_file_path:
+                if active_pl.indexer.comp_subtype == "milvus_vector":
+                    await remove_file_handler([], knowledge_name)
+                    if active_kb:
+                        active_pl.indexer.reinitialize_indexer(active_kb.name)
+                        active_pl.update_indexer_to_retriever()
+        if rm_kb.comp_type == "experience":
+            if rm_kb.experience_active:
+                raise HTTPException(
+                    status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
+                    detail="Cannot delete a running experience knowledge base.",
+                )
+            else:
+                rm_kb.clear_experiences()
         result = ctx.knowledgemgr.delete_knowledge_base(knowledge_name)
         await save_knowledge_to_file()
         return result
@@ -87,26 +107,31 @@ async def update_knowledge_base(knowledge: KnowledgeBaseCreateIn):
     try:
         kb = ctx.knowledgemgr.get_knowledge_base_by_name_or_id(knowledge.name)
         active_pl = ctx.get_pipeline_mgr().get_active_pipeline()
-        if active_pl.indexer.comp_subtype != "milvus_vector":
-            if knowledge.active and knowledge.active != kb.active:
-                file_paths = kb.get_file_paths()
-                await update_knowledge_base_handler(file_paths, knowledge.name)
-            elif not knowledge.active and kb.description != knowledge.description:
-                pass
-            elif not knowledge.active:
-                raise HTTPException(
-                    status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail="Must have an active knowledge base"
-                )
-        else:
+        if active_pl.indexer.comp_subtype == "kbadmin_indexer" and kb.comp_subtype != "kbadmin_kb":
+            raise HTTPException(
+                status_code=status.HTTP_404_NOT_FOUND,
+                detail="The kbadmin pipeline must correspond to the kbadmin type kb.",
+            )
+        if active_pl.indexer.comp_subtype != "kbadmin_indexer" and kb.comp_subtype == "kbadmin_kb":
+            raise HTTPException(
+                status_code=status.HTTP_404_NOT_FOUND, detail="Not kbadmin pipeline cannot active kbadmin type kb."
+            )
+        if kb.comp_type == "knowledge" and kb.comp_subtype == "origin_kb":
+            if active_pl.indexer.comp_subtype != "milvus_vector":
+                if knowledge.active and knowledge.active != kb.active:
+                    file_paths = kb.get_file_paths()
+                    await update_knowledge_base_handler(file_paths, knowledge.name)
+                elif not knowledge.active and kb.description != knowledge.description:
+                    pass
+            else:
+                if knowledge.active and knowledge.active != kb.active:
+                    active_pl.indexer.reinitialize_indexer(knowledge.name)
+                    active_pl.update_indexer_to_retriever()
+                elif not knowledge.active and kb.description != knowledge.description:
+                    pass
+        elif kb.comp_subtype == "kbadmin_kb":
             if knowledge.active and knowledge.active != kb.active:
-                active_pl.indexer.reinitialize_indexer(knowledge.name)
-                active_pl.update_indexer_to_retriever()
-            elif not knowledge.active and kb.description != knowledge.description:
-                pass
-            elif not knowledge.active:
-                raise HTTPException(
-                    status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail="Must have an active knowledge base"
-                )
+                active_pl.retriever.config_kbadmin_milvus(kb.name)
         result = ctx.knowledgemgr.update_knowledge_base(knowledge)
         await save_knowledge_to_file()
         return result
@@ -120,6 +145,16 @@ async def add_file_to_knowledge_base(knowledge_name, file_path: DataIn):
     try:
         active_pl = ctx.get_pipeline_mgr().get_active_pipeline()
         kb = ctx.knowledgemgr.get_knowledge_base_by_name_or_id(knowledge_name)
+        if kb.comp_type == "experience":
+            raise HTTPException(
+                status_code=status.HTTP_404_NOT_FOUND, detail="The experience type cannot perform file operations."
+            )
+        if kb.comp_subtype == "kbadmin_kb" or active_pl.indexer.comp_subtype == "kbadmin_indexer":
+            raise HTTPException(
+                status_code=status.HTTP_404_NOT_FOUND,
+                detail="Please proceed to the kbadmin interface to perform the operation.",
+            )
+        # Validate and normalize the user-provided path
         user_path = file_path.local_path
         normalized_path = os.path.normpath(os.path.join(KNOWLEDGE_BASE_ROOT, user_path))
         if not normalized_path.startswith(KNOWLEDGE_BASE_ROOT):
@@ -170,6 +205,15 @@ async def remove_file_from_knowledge_base(knowledge_name, file_path: DataIn):
     try:
         active_pl = ctx.get_pipeline_mgr().get_active_pipeline()
         kb = ctx.knowledgemgr.get_knowledge_base_by_name_or_id(knowledge_name)
+        if kb.comp_type == "experience":
+            raise HTTPException(
+                status_code=status.HTTP_404_NOT_FOUND, detail="The experience type cannot perform file operations."
+            )
+        if kb.comp_subtype == "kbadmin_kb" or active_pl.indexer.comp_subtype == "kbadmin_indexer":
+            raise HTTPException(
+                status_code=status.HTTP_404_NOT_FOUND,
+                detail="Please proceed to the kbadmin interface to perform the operation.",
+            )
         active_kb = ctx.knowledgemgr.get_active_knowledge_base()
         if file_path.local_path in kb.get_file_paths():
             kb.remove_file_path(file_path.local_path)
@@ -178,17 +222,9 @@ async def remove_file_from_knowledge_base(knowledge_name, file_path: DataIn):
 
         kb_file_path = kb.get_file_paths()
         if active_pl.indexer.comp_subtype == "milvus_vector":
-            if active_kb:
-                if active_kb.name == knowledge_name or active_kb.idx == knowledge_name:
-                    await remove_file_handler(kb_file_path, knowledge_name)
-                else:
-                    await remove_file_handler(kb_file_path, knowledge_name)
-                    active_pl.indexer.reinitialize_indexer(active_kb.name)
-                    active_pl.update_indexer_to_retriever()
-            else:
-                await remove_file_handler(kb_file_path, knowledge_name)
-                active_pl.indexer.reinitialize_indexer(active_kb.name)
-                active_pl.update_indexer_to_retriever()
+            docs_name = kb.name + active_pl.name + str(active_pl.indexer.d)
+            docs_list = ctx.get_file_mgr().del_file(docs_name, file_path.local_path)
+            active_pl.indexer.delete(docs_list)
         elif active_kb:
             if active_kb.name == knowledge_name or active_kb.idx == knowledge_name:
                 await update_knowledge_base_handler(kb_file_path, knowledge_name)
@@ -198,14 +234,115 @@ async def remove_file_from_knowledge_base(knowledge_name, file_path: DataIn):
         raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=str(e))
 
 
+@kb_app.post("/v1/experience")
+def get_experience_by_question(req: ExperienceIn):
+    kb = ctx.knowledgemgr.get_experience_kb()
+    result = kb.get_experience_by_question(req.question)
+    if not result:
+        raise HTTPException(404, detail="Experience not found")
+    return result
+
+
+@kb_app.get("/v1/experiences")
+def get_all_experience():
+    kb = ctx.knowledgemgr.get_experience_kb()
+    if kb:
+        return kb.get_all_experience()
+    else:
+        return kb
+
+
+@kb_app.patch("/v1/experiences")
+def update_experience(experience: ExperienceIn):
+    kb = ctx.knowledgemgr.get_experience_kb()
+    result = kb.update_experience(experience.question, experience.content)
+    if not result:
+        raise HTTPException(404, detail="Question not found")
+    return result
+
+
+@kb_app.delete("/v1/experiences")
+def delete_experience(req: ExperienceIn):
+    kb = ctx.knowledgemgr.get_experience_kb()
+    success = kb.delete_experience(req.question)
+    if not success:
+        raise HTTPException(404, detail=f"Question {req.question} not found")
+    return {"message": "Question deleted"}
+
+
+@kb_app.post("/v1/multiple_experiences/check")
+def check_duplicate_multiple_experiences(experiences: List[Dict[str, Union[str, List[str]]]]):
+    kb = ctx.knowledgemgr.get_experience_kb()
+    if not kb:
+        raise HTTPException(404, detail="No active experience type knowledge base")
+    all_existing = kb.get_all_experience()
+    existing_questions = {item["question"] for item in all_existing}
+    new_questions = [exp["question"] for exp in experiences if "question" in exp]
+    duplicate_questions = [q for q in new_questions if q in existing_questions]
+    if duplicate_questions:
+        return {"code": 2001, "detail": "Duplicate experiences are appended OR overwritten!"}
+    else:
+        kb.add_multiple_experiences(experiences=experiences, flag=True)
+        return {"status": "success", "detail": "No duplicate experiences, added successfully"}
+
+
+@kb_app.post("/v1/multiple_experiences/confirm")
+def confirm_multiple_experiences(experiences: List[Dict[str, Union[str, List[str]]]], flag: bool):
+    kb = ctx.knowledgemgr.get_experience_kb()
+    try:
+        if not kb:
+            raise HTTPException(404, detail="No active experience type knowledge base")
+        kb.add_multiple_experiences(experiences=experiences, flag=flag)
+        return {"status": "success", "detail": "Experiences added successfully"}
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Add Failure：{str(e)}")
+
+
+@kb_app.post("/v1/experiences/files")
+def add_experiences_from_file(req: DataIn):
+    kb = ctx.knowledgemgr.get_experience_kb()
+    try:
+        kb.add_experiences_from_file(req.local_path)
+        return {"status": "success"}
+    except Exception as e:
+        raise HTTPException(status_code=400, detail=str(e))
+
+
+@kb_app.post(path="/v1/view_sub_questions")
+async def view_sub_questions(que: ExperienceIn):
+    active_pl = ctx.get_pipeline_mgr().get_active_pipeline()
+    CONFIG_DIR
+    search_config_path = os.path.join(CONFIG_DIR, "search_config.yaml")
+    search_dir = os.path.join(CONFIG_DIR, "experience_dir/experience.json")
+    top1_issue, sub_questions_result = await query_search(
+        user_input=que.question, search_config_path=search_config_path, search_dir=search_dir, pl=active_pl
+    )
+    return sub_questions_result
+
+
+@kb_app.get("/v1/kbadmin/kbs_list")
+def get_kbs_list():
+    active_pl = ctx.get_pipeline_mgr().get_active_pipeline()
+    try:
+        if not active_pl or active_pl.indexer.comp_subtype != "kbadmin_indexer":
+            return []
+        CONNECTION_ARGS = {"uri": active_pl.indexer.vector_url}
+        kbs_list = get_kbs_info(CONNECTION_ARGS)
+        kb_names = [name for name in kbs_list.keys()]
+        return kb_names
+    except Exception as e:
+        raise HTTPException(status_code=400, detail=str(e))
+
+
 # Update knowledge base data
 async def update_knowledge_base_handler(file_path=None, knowledge_name: str = "default_kb", add_file: bool = False):
     if ctx.get_pipeline_mgr().get_active_pipeline() is None:
         raise HTTPException(status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail="Please activate pipeline")
 
     pl = ctx.get_pipeline_mgr().get_active_pipeline()
+    docs_name = knowledge_name + pl.name + str(pl.indexer.d)
     if add_file and file_path:
-        return await add_data(file_path)
+        return await add_data(file_path, docs_name)
     else:
         try:
             ctx.get_node_mgr().del_nodes_by_np_idx(pl.node_parser.idx)
@@ -214,7 +351,7 @@ async def update_knowledge_base_handler(file_path=None, knowledge_name: str = "d
             if file_path:
                 for file in file_path:
                     request = DataIn(local_path=file)
-                    await add_data(request)
+                    await add_data(request, docs_name)
         except MilvusException as e:
             raise HTTPException(status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail=str(e))
         return "Done"
@@ -233,16 +370,16 @@ async def remove_file_handler(file_path=None, knowledge_name: str = "default_kb"
     except MilvusException as e:
         raise HTTPException(status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail=str(e))
     pl.update_indexer_to_retriever()
+    docs_name = knowledge_name + pl.name + str(pl.indexer.d)
     if file_path:
         for file in file_path:
             request = DataIn(local_path=file)
-            await add_data(request)
+            await add_data(request, docs_name)
     return "Done"
 
 
 # Restore knowledge base configuration
 async def load_knowledge_from_file():
-    CONFIG_DIR = "/home/user/ui_cache/configs"
     KNOWLEDGEBASE_FILE = os.path.join(CONFIG_DIR, "knowledgebase.json")
     active_pl = ctx.get_pipeline_mgr().get_active_pipeline()
     if os.path.exists(KNOWLEDGEBASE_FILE):
@@ -253,28 +390,31 @@ async def load_knowledge_from_file():
             for Knowledgebase_data in all_data:
                 pipeline_req = KnowledgeBaseCreateIn(**Knowledgebase_data)
                 kb = ctx.knowledgemgr.create_knowledge_base(pipeline_req)
-                if Knowledgebase_data["file_map"]:
-                    if active_pl.indexer.comp_subtype != "milvus_vector" and Knowledgebase_data["active"]:
-                        for file_path in Knowledgebase_data["file_map"].values():
-                            await update_knowledge_base_handler(
-                                DataIn(local_path=file_path), Knowledgebase_data["name"], add_file=True
-                            )
-                            kb.add_file_path(file_path)
-                    elif Knowledgebase_data["active"]:
-                        active_pl.indexer.reinitialize_indexer(Knowledgebase_data["name"])
-                        active_pl.update_indexer_to_retriever()
-                        for file_path in Knowledgebase_data["file_map"].values():
-                            kb.add_file_path(file_path)
-                    else:
-                        for file_path in Knowledgebase_data["file_map"].values():
-                            kb.add_file_path(file_path)
+                if kb.comp_type == "knowledge" and kb.comp_subtype == "origin_kb":
+                    if Knowledgebase_data["file_map"]:
+                        if active_pl.indexer.comp_subtype != "milvus_vector" and Knowledgebase_data["active"]:
+                            for file_path in Knowledgebase_data["file_map"].values():
+                                await update_knowledge_base_handler(
+                                    DataIn(local_path=file_path), Knowledgebase_data["name"], add_file=True
+                                )
+                                kb.add_file_path(file_path)
+                        elif Knowledgebase_data["active"]:
+                            active_pl.indexer.reinitialize_indexer(Knowledgebase_data["name"])
+                            active_pl.update_indexer_to_retriever()
+                            for file_path in Knowledgebase_data["file_map"].values():
+                                kb.add_file_path(file_path)
+                        else:
+                            for file_path in Knowledgebase_data["file_map"].values():
+                                kb.add_file_path(file_path)
+                elif kb.comp_subtype == "kbadmin_kb":
+                    if Knowledgebase_data["active"]:
+                        active_pl.retriever.config_kbadmin_milvus(kb.name)
         except Exception as e:
             print(f"Error load Knowledge base: {e}")
 
 
 # Configuration of knowledge base for persistence
 async def save_knowledge_to_file():
-    CONFIG_DIR = "/home/user/ui_cache/configs"
     KNOWLEDGEBASE_FILE = os.path.join(CONFIG_DIR, "knowledgebase.json")
     if not os.path.exists(CONFIG_DIR):
         os.makedirs(CONFIG_DIR, exist_ok=True)
@@ -282,7 +422,15 @@ async def save_knowledge_to_file():
         kb_base = ctx.knowledgemgr.get_all_knowledge_bases()
         knowledgebases_data = []
         for kb in kb_base:
-            kb_json = {"name": kb.name, "description": kb.description, "active": kb.active, "file_map": kb.file_map}
+            kb_json = {
+                "name": kb.name,
+                "description": kb.description,
+                "active": kb.active,
+                "file_map": kb.file_map,
+                "comp_type": kb.comp_type,
+                "comp_subtype": kb.comp_subtype,
+                "experience_active": kb.experience_active,
+            }
             knowledgebases_data.append(kb_json)
         json_str = json.dumps(knowledgebases_data, indent=2, ensure_ascii=False)
         with open(KNOWLEDGEBASE_FILE, "w", encoding="utf-8") as f:
@@ -291,7 +439,7 @@ async def save_knowledge_to_file():
         print(f"Error saving Knowledge base: {e}")
 
 
-all_pipeline_milvus_maps = {}
+all_pipeline_milvus_maps = {"change_pl": []}
 current_pipeline_kb_map = {}
 
 
@@ -299,29 +447,87 @@ async def refresh_milvus_map(milvus_name):
     current_pipeline_kb_map.clear()
     knowledge_bases_list = await get_all_knowledge_bases()
     for kb in knowledge_bases_list:
+        if kb.comp_type == "experience":
+            continue
         current_pipeline_kb_map[kb.name] = kb.file_map
     all_pipeline_milvus_maps[milvus_name] = copy.deepcopy(current_pipeline_kb_map)
+    milvus_maps_path = os.path.join(CONFIG_DIR, "milvus_maps.json")
+    with open(milvus_maps_path, "w", encoding="utf-8") as f:
+        json.dump(all_pipeline_milvus_maps, f, ensure_ascii=False, indent=2)
 
 
-async def Synchronizing_vector_data(old_active_pl, new_active_pl):
+def read_milvus_maps():
+    milvus_maps_path = os.path.join(CONFIG_DIR, "milvus_maps.json")
+    global all_pipeline_milvus_maps
     try:
+        with open(milvus_maps_path, "r", encoding="utf-8") as f:
+            all_pipeline_milvus_maps = json.load(f)
+    except Exception as e:
+        all_pipeline_milvus_maps = {"change_pl": []}
+    return all_pipeline_milvus_maps
+
+
+def save_change_pl(pl_name):
+    if pl_name not in all_pipeline_milvus_maps["change_pl"]:
+        return all_pipeline_milvus_maps["change_pl"].append(pl_name)
+
+
+async def Synchronizing_vector_data(old_active_pl, new_active_pl, pl_change):
+    try:
+        if pl_change:
+            save_change_pl(new_active_pl.name)
         active_kb = ctx.knowledgemgr.get_active_knowledge_base()
-        active_pl = ctx.get_pipeline_mgr().get_active_pipeline()
+        # Determine whether it is kbadmin type
+        if old_active_pl:
+            if (
+                old_active_pl.retriever.comp_subtype == "kbadmin_retriever"
+                and new_active_pl.retriever.comp_subtype == "kbadmin_retriever"
+            ):
+                if active_kb:
+                    if active_kb.comp_subtype == "kbadmin_kb":
+                        new_active_pl.retriever.config_kbadmin_milvus(active_kb.name)
+                return True
+            elif old_active_pl.retriever.comp_subtype == "kbadmin_retriever":
+                return True
+
         milvus_name = (
             old_active_pl.name + str(old_active_pl.indexer.model_extra["d"]) if old_active_pl else "default_kb"
         )
-        if not active_kb:
-            return True
-        if not active_pl:
+        if not new_active_pl.status.active:
             if old_active_pl:
                 if old_active_pl.indexer.comp_subtype == "milvus_vector":
                     await refresh_milvus_map(milvus_name)
             return True
-
+        if not active_kb:
+            return True
+        if new_active_pl.retriever.comp_subtype == "kbadmin_retriever":
+            if active_kb:
+                if active_kb.comp_subtype == "kbadmin_kb":
+                    new_active_pl.retriever.config_kbadmin_milvus(active_kb.name)
+            return True
+        # Perform milvus data synchronization
         if new_active_pl.indexer.comp_subtype == "milvus_vector":
+            # Pipeline component state changed
+            if new_active_pl.name in all_pipeline_milvus_maps["change_pl"]:
+                kb_list = await get_all_knowledge_bases()
+                for kb in kb_list:
+                    if kb.comp_type == "knowledge" and kb.comp_subtype == "origin_kb":
+                        new_active_pl.indexer.clear_milvus_collection(kb.name)
+                        new_active_pl.indexer.reinitialize_indexer(kb.name)
+                        new_active_pl.update_indexer_to_retriever()
+                        add_list = kb.get_file_paths()
+                        docs_name = kb.name + new_active_pl.name + str(new_active_pl.indexer.d)
+                        ctx.get_file_mgr().del_kb_file(docs_name)
+                        for file in add_list:
+                            await add_data(DataIn(local_path=file), docs_name)
+                all_pipeline_milvus_maps["change_pl"].remove(new_active_pl.name)
+                return True
+            # Pipeline component state not changed
             new_milvus_map = {}
             kb_list = await get_all_knowledge_bases()
             for kb in kb_list:
+                if kb.comp_type == "experience":
+                    continue
                 new_milvus_map[kb.name] = kb.file_map
             added_files, deleted_files = compare_mappings(
                 new_milvus_map,
@@ -330,21 +536,22 @@ async def Synchronizing_vector_data(old_active_pl, new_active_pl):
             # Synchronization of deleted files
             for kb_name, file_paths in deleted_files.items():
                 if file_paths:
-                    new_active_pl.indexer.clear_milvus_collection(kb_name)
                     if kb_name not in new_milvus_map.keys():
+                        new_active_pl.indexer.clear_milvus_collection(kb_name)
                         continue
                     kb = await get_knowledge_base(kb_name)
                     new_active_pl.indexer.reinitialize_indexer(kb_name)
-                    file_paths = kb.get_file_paths()
-                    if file_paths:
-                        for file in file_paths:
-                            await add_data(DataIn(local_path=file))
+                    for file_path in file_paths.values():
+                        docs_name = kb.name + new_active_pl.name + str(new_active_pl.indexer.d)
+                        docs_list = ctx.get_file_mgr().del_file(docs_name, file_path)
+                        new_active_pl.indexer.delete(docs_list)
             # Synchronization of added files
             for kb_name, file_paths in added_files.items():
                 if file_paths:
                     for file_path in file_paths.values():
                         new_active_pl.indexer.reinitialize_indexer(kb_name)
-                        await add_data(DataIn(local_path=file_path))
+                        docs_name = kb_name + new_active_pl.name + str(new_active_pl.indexer.d)
+                        await add_data(DataIn(local_path=file_path), docs_name)
 
             new_active_pl.indexer.reinitialize_indexer(active_kb.name)
             new_active_pl.update_indexer_to_retriever()
@@ -354,7 +561,8 @@ async def Synchronizing_vector_data(old_active_pl, new_active_pl):
             new_active_pl.update_indexer_to_retriever()
             add_list = active_kb.get_file_paths()
             for file in add_list:
-                await add_data(DataIn(local_path=file))
+                docs_name = active_kb.name + new_active_pl.name + str(new_active_pl.indexer.d)
+                await add_data(DataIn(local_path=file), docs_name)
             if old_active_pl:
                 if old_active_pl.indexer.comp_subtype == "milvus_vector":
                     await refresh_milvus_map(milvus_name)
diff --git a/EdgeCraftRAG/edgecraftrag/api/v1/model.py b/EdgeCraftRAG/edgecraftrag/api/v1/model.py
index bbc0d9806b..bce669280b 100644
--- a/EdgeCraftRAG/edgecraftrag/api/v1/model.py
+++ b/EdgeCraftRAG/edgecraftrag/api/v1/model.py
@@ -123,7 +123,10 @@ def get_available_weights(model_path):
 
 def get_available_models(model_type):
     avail_models = []
-    if model_type == "LLM":
+    if model_type == "vLLM":
+        LLM_MODEL = os.getenv("LLM_MODEL", "Qwen/Qwen3-8B")
+        avail_models.append(LLM_MODEL)
+    elif model_type == "LLM":
         items = os.listdir(CONTAINER_MODEL_PATH)
         for item in items:
             if item == "BAAI":
@@ -134,6 +137,8 @@ def get_available_models(model_type):
                     avail_models.append(item + "/" + sub_path)
             else:
                 avail_models.append(item)
+    elif model_type == "kbadmin_embedding_model":
+        return ["BAAI/bge-large-zh-v1.5"]
     else:
         for item in os.listdir(CONTAINER_MODEL_PATH + "BAAI"):
             if (model_type == "reranker" and "rerank" in item) or (model_type == "embedding" and "rerank" not in item):
diff --git a/EdgeCraftRAG/edgecraftrag/api/v1/pipeline.py b/EdgeCraftRAG/edgecraftrag/api/v1/pipeline.py
index e1cd5b8345..dfa2ec25e6 100755
--- a/EdgeCraftRAG/edgecraftrag/api/v1/pipeline.py
+++ b/EdgeCraftRAG/edgecraftrag/api/v1/pipeline.py
@@ -4,6 +4,7 @@
 import asyncio
 import json
 import os
+import re
 import weakref
 from concurrent.futures import ThreadPoolExecutor
 
@@ -12,15 +13,21 @@
 from edgecraftrag.base import IndexerType, InferenceType, ModelType, NodeParserType, PostProcessorType, RetrieverType
 from edgecraftrag.components.benchmark import Benchmark
 from edgecraftrag.components.generator import QnAGenerator
-from edgecraftrag.components.indexer import VectorIndexer
+from edgecraftrag.components.indexer import KBADMINIndexer, VectorIndexer
 from edgecraftrag.components.node_parser import (
     HierarchyNodeParser,
+    KBADMINParser,
     SimpleNodeParser,
     SWindowNodeParser,
     UnstructedNodeParser,
 )
 from edgecraftrag.components.postprocessor import MetadataReplaceProcessor, RerankProcessor
-from edgecraftrag.components.retriever import AutoMergeRetriever, SimpleBM25Retriever, VectorSimRetriever
+from edgecraftrag.components.retriever import (
+    AutoMergeRetriever,
+    KBadminRetriever,
+    SimpleBM25Retriever,
+    VectorSimRetriever,
+)
 from edgecraftrag.context import ctx
 from fastapi import FastAPI, File, HTTPException, UploadFile, status
 from pymilvus import connections
@@ -51,16 +58,30 @@ async def get_pipeline_json(name):
 
 
 # GET Pipeline benchmark
-@pipeline_app.get(path="/v1/settings/pipelines/{name}/benchmark")
-async def get_pipeline_benchmark(name):
-    pl = ctx.get_pipeline_mgr().get_pipeline_by_name_or_id(name)
+@pipeline_app.get(path="/v1/settings/pipeline/benchmark")
+async def get_pipeline_benchmark():
+    pl = ctx.get_pipeline_mgr().get_active_pipeline()
     if pl and pl.benchmark:
         return pl.benchmark
 
 
+# GET Pipeline benchmark
+@pipeline_app.get(path="/v1/settings/pipelines/{name}/benchmarks")
+async def get_pipeline_benchmarks(name):
+    pl = ctx.get_pipeline_mgr().get_pipeline_by_name_or_id(name)
+    if pl and pl.benchmark:
+        return pl.benchmark.benchmark_data_list
+
+
 # POST Pipeline
 @pipeline_app.post(path="/v1/settings/pipelines")
 async def add_pipeline(request: PipelineCreateIn):
+    pattern = re.compile(r"^[a-zA-Z0-9_]+$")
+    if not pattern.fullmatch(request.name):
+        raise HTTPException(
+            status_code=status.HTTP_400_BAD_REQUEST,
+            detail="Pipeline name must consist of letters, numbers, and underscores.",
+        )
     return load_pipeline(request)
 
 
@@ -126,9 +147,11 @@ def update_pipeline_handler(pl, req):
     active_kb = ctx.knowledgemgr.get_active_knowledge_base()
     active_pipeline = ctx.get_pipeline_mgr().get_active_pipeline()
     kb_name = active_kb.name if active_kb else "default_kb"
+    pl_change = False
 
     if req.node_parser is not None:
         np = req.node_parser
+        pl_change = ctx.get_node_parser_mgr().search_parser_change(pl, req)
         found_parser = ctx.get_node_parser_mgr().search_parser(np)
         if found_parser is not None:
             pl.node_parser = found_parser
@@ -153,12 +176,10 @@ def update_pipeline_handler(pl, req):
                     pl.node_parser = SWindowNodeParser.from_defaults(window_size=np.window_size)
                 case NodeParserType.UNSTRUCTURED:
                     pl.node_parser = UnstructedNodeParser(chunk_size=np.chunk_size, chunk_overlap=np.chunk_overlap)
+                case NodeParserType.KBADMINPARSER:
+                    pl.node_parser = KBADMINParser()
             ctx.get_node_parser_mgr().add(pl.node_parser)
 
-            all_docs = ctx.get_file_mgr().get_all_docs()
-            nodelist = pl.node_parser.run(docs=all_docs)
-            if nodelist is not None and len(nodelist) > 0:
-                ctx.get_node_mgr().add_nodes(pl.node_parser.idx, nodelist)
             pl._node_changed = True
 
     if req.indexer is not None:
@@ -168,17 +189,24 @@ def update_pipeline_handler(pl, req):
             pl.indexer = found_indexer
         else:
             embed_model = None
-            if ind.embedding_model:
-                embed_model = ctx.get_model_mgr().search_model(ind.embedding_model)
-                if embed_model is None:
-                    ind.embedding_model.model_type = ModelType.EMBEDDING
-                    embed_model = ctx.get_model_mgr().load_model(ind.embedding_model)
-                    ctx.get_model_mgr().add(embed_model)
             match ind.indexer_type:
                 case IndexerType.DEFAULT_VECTOR | IndexerType.FAISS_VECTOR | IndexerType.MILVUS_VECTOR:
+                    if ind.embedding_model:
+                        embed_model = ctx.get_model_mgr().search_model(ind.embedding_model)
+                        if embed_model is None:
+                            ind.embedding_model.model_type = ModelType.EMBEDDING
+                            embed_model = ctx.get_model_mgr().load_model(ind.embedding_model)
+                            ctx.get_model_mgr().add(embed_model)
                     # TODO: **RISK** if considering 2 pipelines with different
                     # nodes, but same indexer, what will happen?
-                    pl.indexer = VectorIndexer(embed_model, ind.indexer_type, ind.vector_uri, kb_name)
+                    pl.indexer = VectorIndexer(embed_model, ind.indexer_type, ind.vector_url, kb_name)
+                case IndexerType.KBADMIN_INDEXER:
+                    kbadmin_embedding_url = ind.embedding_url
+                    KBADMIN_VECTOR_URL = ind.vector_url
+                    embed_model = ind.embedding_model.model_id
+                    pl.indexer = KBADMINIndexer(
+                        embed_model, ind.indexer_type, kbadmin_embedding_url, KBADMIN_VECTOR_URL
+                    )
                 case _:
                     pass
             ctx.get_indexer_mgr().add(pl.indexer)
@@ -208,6 +236,8 @@ def update_pipeline_handler(pl, req):
                     pl.retriever = SimpleBM25Retriever(pl.indexer, similarity_top_k=retr.retrieve_topk)
                 else:
                     return Exception("No indexer")
+            case RetrieverType.KBADMIN_RETRIEVER:
+                pl.retriever = KBadminRetriever(pl.indexer, similarity_top_k=retr.retrieve_topk)
             case _:
                 pass
         # Index is updated to retriever
@@ -272,7 +302,7 @@ def run_async_task():
         loop = asyncio.new_event_loop()
         asyncio.set_event_loop(loop)
         try:
-            loop.run_until_complete(Synchronizing_vector_data(active_pipeline, pl))
+            loop.run_until_complete(Synchronizing_vector_data(active_pipeline, pl, pl_change))
         except Exception as e:
             raise HTTPException(status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail=f"Synchronization error: {e}")
         finally:
@@ -292,8 +322,8 @@ def load_pipeline_from_file():
         with open(PIPELINE_FILE, "r", encoding="utf-8") as f:
             all_pipelines = f.read()
         try:
-            all_da = json.loads(all_pipelines)
-            for pipeline_data in all_da:
+            all_data = json.loads(all_pipelines)
+            for pipeline_data in all_data:
                 one_pipelinejson = json.loads(pipeline_data)
                 pipeline_req = PipelineCreateIn(**one_pipelinejson)
                 load_pipeline(pipeline_req)
@@ -323,18 +353,18 @@ def save_pipeline_to_file():
 # Detecting if milvus is connected
 @pipeline_app.post(path="/v1/check/milvus")
 async def check_milvus(request: MilvusConnectRequest):
-    vector_uri = request.vector_uri
+    vector_url = request.vector_url
     try:
-        if vector_uri.startswith("http://"):
-            host_port = vector_uri.replace("http://", "")
-        elif vector_uri.startswith("https://"):
-            host_port = vector_uri.replace("https://", "")
+        if vector_url.startswith("http://"):
+            host_port = vector_url.replace("http://", "")
+        elif vector_url.startswith("https://"):
+            host_port = vector_url.replace("https://", "")
         else:
-            host_port = vector_uri
+            host_port = vector_url
         host, port = host_port.split(":", 1)
-        connections.connect(alias="default", host=host, port=port)
+        connections.connect(alias="knowledge_default", host=host, port=port)
 
-        if connections.has_connection("default"):
+        if connections.has_connection("knowledge_default"):
             return {"status": "200", "message": "Milvus connection successful."}
         else:
             return {"status": "404", "message": "Milvus connection failed."}
diff --git a/EdgeCraftRAG/edgecraftrag/api/v1/prompt.py b/EdgeCraftRAG/edgecraftrag/api/v1/prompt.py
index 86639a40a7..0de6a283a2 100644
--- a/EdgeCraftRAG/edgecraftrag/api/v1/prompt.py
+++ b/EdgeCraftRAG/edgecraftrag/api/v1/prompt.py
@@ -41,6 +41,8 @@ async def get_prompt():
     try:
         generator = ctx.get_pipeline_mgr().get_active_pipeline().generator
         if generator:
+            if generator.prompt_content is not None:
+                return generator.prompt_content
             return generator.prompt
     except Exception as e:
         raise HTTPException(status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail=str(e))
diff --git a/EdgeCraftRAG/edgecraftrag/api_schema.py b/EdgeCraftRAG/edgecraftrag/api_schema.py
index d7ae1c8478..2bdf8dbd4e 100644
--- a/EdgeCraftRAG/edgecraftrag/api_schema.py
+++ b/EdgeCraftRAG/edgecraftrag/api_schema.py
@@ -25,7 +25,8 @@ class NodeParserIn(BaseModel):
 class IndexerIn(BaseModel):
     indexer_type: str
     embedding_model: Optional[ModelIn] = None
-    vector_uri: Optional[str] = None
+    embedding_url: Optional[str] = None
+    vector_url: Optional[str] = None
 
 
 class RetrieverIn(BaseModel):
@@ -80,7 +81,15 @@ class KnowledgeBaseCreateIn(BaseModel):
     name: str
     description: Optional[str] = None
     active: Optional[bool] = None
+    comp_type: Optional[str] = "knowledge"
+    comp_subtype: Optional[str] = "origin_kb"
+    experience_active: Optional[bool] = None
+
+
+class ExperienceIn(BaseModel):
+    question: str
+    content: list[str] = None
 
 
 class MilvusConnectRequest(BaseModel):
-    vector_uri: str
+    vector_url: str
diff --git a/EdgeCraftRAG/edgecraftrag/base.py b/EdgeCraftRAG/edgecraftrag/base.py
index db1dc414b8..3306afc2ed 100644
--- a/EdgeCraftRAG/edgecraftrag/base.py
+++ b/EdgeCraftRAG/edgecraftrag/base.py
@@ -19,7 +19,9 @@ class CompType(str, Enum):
     RETRIEVER = "retriever"
     POSTPROCESSOR = "postprocessor"
     GENERATOR = "generator"
+    QUERYSEARCH = "querysearch"
     FILE = "file"
+    CHUNK_NUM = "chunk_num"
 
 
 class ModelType(str, Enum):
@@ -44,6 +46,7 @@ class NodeParserType(str, Enum):
     HIERARCHY = "hierarchical"
     SENTENCEWINDOW = "sentencewindow"
     UNSTRUCTURED = "unstructured"
+    KBADMINPARSER = "kbadmin_parser"
 
 
 class IndexerType(str, Enum):
@@ -51,6 +54,7 @@ class IndexerType(str, Enum):
     FAISS_VECTOR = "faiss_vector"
     DEFAULT_VECTOR = "vector"
     MILVUS_VECTOR = "milvus_vector"
+    KBADMIN_INDEXER = "kbadmin_indexer"
 
 
 class RetrieverType(str, Enum):
@@ -58,6 +62,7 @@ class RetrieverType(str, Enum):
     VECTORSIMILARITY = "vectorsimilarity"
     AUTOMERGE = "auto_merge"
     BM25 = "bm25"
+    KBADMIN_RETRIEVER = "kbadmin_retriever"
 
 
 class PostProcessorType(str, Enum):
@@ -113,9 +118,19 @@ class BaseMgr:
     def __init__(self):
         self.components = {}
 
-    def add(self, comp: BaseComponent):
+    def add(self, comp: BaseComponent, name: str = None):
+        if name:
+            self.components[name] = comp
+            return True
         self.components[comp.idx] = comp
 
+    def append(self, comp: BaseComponent, name: str = None):
+        key = name if name else comp.idx
+        if key not in self.components:
+            self.components[key] = []
+        self.components[key].append(comp)
+        return True
+
     def get(self, idx: str) -> BaseComponent:
         if idx in self.components:
             return self.components[idx]
diff --git a/EdgeCraftRAG/edgecraftrag/components/benchmark.py b/EdgeCraftRAG/edgecraftrag/components/benchmark.py
index fc3801b5d3..3bf2a7e602 100644
--- a/EdgeCraftRAG/edgecraftrag/components/benchmark.py
+++ b/EdgeCraftRAG/edgecraftrag/components/benchmark.py
@@ -49,7 +49,14 @@ def cal_input_token_size(self, input_text_list):
         return input_token_size
 
     def init_benchmark_data(self):
-        pipeline_comp = [CompType.RETRIEVER, CompType.POSTPROCESSOR, CompType.GENERATOR]
+        pipeline_comp = [
+            CompType.NODEPARSER,
+            CompType.CHUNK_NUM,
+            CompType.RETRIEVER,
+            CompType.POSTPROCESSOR,
+            CompType.QUERYSEARCH,
+            CompType.GENERATOR,
+        ]
         if self.is_enabled():
             with self._idx_lock:
                 self.last_idx += 1
@@ -58,6 +65,8 @@ def init_benchmark_data(self):
             data["idx"] = idx
             for comp in pipeline_comp:
                 data[comp] = ""
+            data[CompType.NODEPARSER] = 0
+            data[CompType.CHUNK_NUM] = 0
             return idx, data
 
     def update_benchmark_data(self, idx, comp_type, start, end):
diff --git a/EdgeCraftRAG/edgecraftrag/components/generator.py b/EdgeCraftRAG/edgecraftrag/components/generator.py
index cb170fcd10..0f746b89cb 100755
--- a/EdgeCraftRAG/edgecraftrag/components/generator.py
+++ b/EdgeCraftRAG/edgecraftrag/components/generator.py
@@ -84,10 +84,39 @@ def extract_unstructured_eles(retrieved_nodes=[], text_gen_context=""):
     return unstructured_str
 
 
+def build_stream_response(status=None, content=None, error=None):
+    response = {"status": status, "contentType": "text"}
+    if content is not None:
+        response["content"] = content
+    if error is not None:
+        response["error"] = error
+    return response
+
+
 async def local_stream_generator(lock, llm, prompt_str, unstructured_str):
     async with lock:
         response = llm.stream_complete(prompt_str)
         collected_data = []
+        try:
+            for r in response:
+                collected_data.append(r.delta)
+                yield r.delta
+                await asyncio.sleep(0)
+            if unstructured_str:
+                collected_data.append(unstructured_str)
+                yield unstructured_str
+            res = "".join(collected_data)
+            save_history(res)
+        except Exception as e:
+            start_idx = str(e).find("message") + len("message")
+            result_error = str(e)[start_idx:]
+            yield f"code:0000{result_error}"
+
+
+async def stream_generator(llm, prompt_str, unstructured_str):
+    response = llm.stream_complete(prompt_str)
+    collected_data = []
+    try:
         for r in response:
             collected_data.append(r.delta)
             yield r.delta
@@ -97,20 +126,10 @@ async def local_stream_generator(lock, llm, prompt_str, unstructured_str):
             yield unstructured_str
         res = "".join(collected_data)
         save_history(res)
-
-
-async def stream_generator(llm, prompt_str, unstructured_str):
-    response = llm.stream_complete(prompt_str)
-    collected_data = []
-    for r in response:
-        collected_data.append(r.delta)
-        yield r.delta
-        await asyncio.sleep(0)
-    if unstructured_str:
-        collected_data.append(unstructured_str)
-        yield unstructured_str
-    res = "".join(collected_data)
-    save_history(res)
+    except Exception as e:
+        start_idx = str(e).find("message") + len("message")
+        result_error = str(e)[start_idx:]
+        yield f"code:0000{result_error}"
 
 
 class QnAGenerator(BaseComponent):
@@ -130,13 +149,20 @@ def __init__(self, llm_model, prompt_template_file, inference_type, vllm_endpoin
         self.llm = llm_model
         if isinstance(llm_model, str):
             self.model_id = llm_model
+            self.model_path = llm_model
         else:
-            self.model_id = llm_model().model_id
+            llm_instance = llm_model()
+            if llm_instance.model_path is None or llm_instance.model_path == "":
+                self.model_id = llm_instance.model_id
+                self.model_path = os.path.join("/home/user/models/", os.getenv("LLM_MODEL", "Qwen/Qwen3-8B"))
+            else:
+                self.model_id = llm_instance.model_id
+                self.model_path = llm_instance.model_path
         if self.inference_type == InferenceType.LOCAL:
             self.lock = asyncio.Lock()
         self.prompt_content = prompt_content
         self.prompt_template_file = prompt_template_file
-        self.prompt = self.init_prompt(self.model_id, self.prompt_content, self.prompt_template_file)
+        self.prompt = self.init_prompt(self.model_path, self.prompt_content, self.prompt_template_file)
 
         self.llm = llm_model
         if isinstance(llm_model, str):
@@ -151,20 +177,13 @@ def __init__(self, llm_model, prompt_template_file, inference_type, vllm_endpoin
                 vllm_endpoint = os.getenv("vLLM_ENDPOINT", "http://localhost:8086")
         self.vllm_endpoint = vllm_endpoint
 
-    def init_prompt(self, model_id, prompt_content=None, prompt_template_file=None, enable_think=False):
-        # using the prompt template enhancement strategy(only tested on Qwen2-7B-Instruction) if template_enhance_on is true
-        template_enhance_on = True if "Qwen2" in self.model_id else False
+    def init_prompt(self, model_path, prompt_content=None, prompt_template_file=None, enable_think=False):
         if prompt_content:
-            self.set_prompt(prompt_content)
-            return get_prompt_template(model_id, prompt_content, prompt_template_file, enable_think)
+            return get_prompt_template(model_path, prompt_content, prompt_template_file, enable_think)
         elif prompt_template_file is None:
             print("There is no template file, using the default template.")
-            prompt_template = get_prompt_template(model_id, prompt_content, prompt_template_file, enable_think)
-            return (
-                DocumentedContextRagPromptTemplate.from_template(prompt_template)
-                if template_enhance_on
-                else prompt_template
-            )
+            prompt_template = get_prompt_template(model_path, prompt_content, prompt_template_file, enable_think)
+            return prompt_template
         else:
             safe_root = "/templates"
             prompt_template_file = os.path.normpath(os.path.join(safe_root, prompt_template_file))
@@ -172,25 +191,19 @@ def init_prompt(self, model_id, prompt_content=None, prompt_template_file=None,
                 raise ValueError("Invalid template path")
             if not os.path.exists(prompt_template_file):
                 raise ValueError("Template file not exists")
-            if template_enhance_on:
-                return DocumentedContextRagPromptTemplate.from_file(prompt_template_file)
-            else:
-                return get_prompt_template(model_id, prompt_content, prompt_template_file, enable_think)
+            return get_prompt_template(model_path, prompt_content, prompt_template_file, enable_think)
 
     def set_prompt(self, prompt):
         if "{context}" not in prompt:
             prompt += "\n<|im_start|>{context}<|im_end|>"
         if "{chat_history}" not in prompt:
             prompt += "\n<|im_start|>{chat_history}"
-        self.prompt = prompt
+        self.prompt_content = prompt
+        self.prompt = self.init_prompt(self.model_path, self.prompt_content, self.prompt_template_file)
 
     def reset_prompt(self):
-        prompt_template = get_prompt_template(self.model_id)
-        self.prompt = (
-            DocumentedContextRagPromptTemplate.from_template(prompt_template)
-            if self.template_enhance_on
-            else prompt_template
-        )
+        self.prompt_content = None
+        self.prompt = self.init_prompt(self.model_path, self.prompt_content, self.prompt_template_file)
 
     def clean_string(self, string):
         ret = string
@@ -206,20 +219,21 @@ def query_transform(self, chat_request, retrieved_nodes, sub_questions=None):
         :return: Generated text_gen_context and prompt_str."""
         text_gen_context = ""
         for n in retrieved_nodes:
-            origin_text = n.node.get_text()
+            origin_text = n.node.text
             text_gen_context += self.clean_string(origin_text.strip())
         query = chat_request.messages
         chat_history = concat_history(chat_request.messages)
         # Modify model think status
         if chat_request.chat_template_kwargs:
-            if self.enable_think != chat_request.chat_template_kwargs["enable_thinking"]:
-                self.prompt = self.init_prompt(
-                    self.model_id,
-                    self.prompt_content,
-                    self.prompt_template_file,
-                    chat_request.chat_template_kwargs["enable_thinking"],
-                )
-                self.enable_think = chat_request.chat_template_kwargs["enable_thinking"]
+            if "enable_thinking" in chat_request.chat_template_kwargs:
+                if self.enable_think != chat_request.chat_template_kwargs["enable_thinking"]:
+                    self.prompt = self.init_prompt(
+                        self.model_path,
+                        self.prompt_content,
+                        self.prompt_template_file,
+                        chat_request.chat_template_kwargs["enable_thinking"],
+                    )
+                    self.enable_think = chat_request.chat_template_kwargs["enable_thinking"]
         if sub_questions:
             final_query = f"{query}\n\n### Sub-questions ###\nThe following list is how you should consider the answer, you MUST follow these steps when responding:\n\n{sub_questions}"
         else:
diff --git a/EdgeCraftRAG/edgecraftrag/components/indexer.py b/EdgeCraftRAG/edgecraftrag/components/indexer.py
index 842122964f..bd79bb3042 100644
--- a/EdgeCraftRAG/edgecraftrag/components/indexer.py
+++ b/EdgeCraftRAG/edgecraftrag/components/indexer.py
@@ -13,8 +13,7 @@
 
 
 class VectorIndexer(BaseComponent, VectorStoreIndex):
-
-    def __init__(self, embed_model, vector_type, milvus_uri="http://localhost:19530", kb_name="default_kb"):
+    def __init__(self, embed_model, vector_type, vector_url="http://localhost:19530", kb_name="default_kb"):
         BaseComponent.__init__(
             self,
             comp_type=CompType.INDEXER,
@@ -26,10 +25,10 @@ def __init__(self, embed_model, vector_type, milvus_uri="http://localhost:19530"
             from llama_index.core import Settings
 
             Settings.embed_model = None
-        self.milvus_uri = milvus_uri
-        self._initialize_indexer(embed_model, vector_type, milvus_uri, kb_name)
+        self.vector_url = vector_url
+        self._initialize_indexer(embed_model, vector_type, vector_url, kb_name)
 
-    def _initialize_indexer(self, embed_model, vector_type, milvus_uri, kb_name):
+    def _initialize_indexer(self, embed_model, vector_type, vector_url, kb_name):
         # get active name
         pl = ctx.get_pipeline_mgr().get_active_pipeline()
         plname = pl.name if pl else ""
@@ -46,7 +45,7 @@ def _initialize_indexer(self, embed_model, vector_type, milvus_uri, kb_name):
                 VectorStoreIndex.__init__(self, embed_model=embed_model, nodes=[], storage_context=faiss_store)
             case IndexerType.MILVUS_VECTOR:
                 milvus_vector_store = MilvusVectorStore(
-                    uri=milvus_uri,
+                    uri=vector_url,
                     dim=self.d,
                     collection_name=kb_name + plname + str(self.d),
                     overwrite=False,
@@ -55,14 +54,14 @@ def _initialize_indexer(self, embed_model, vector_type, milvus_uri, kb_name):
                 VectorStoreIndex.__init__(self, embed_model=embed_model, nodes=[], storage_context=milvus_store)
 
     def reinitialize_indexer(self, kb_name="default_kb"):
-        self._initialize_indexer(self.model, self.comp_subtype, self.milvus_uri, kb_name)
+        self._initialize_indexer(self.model, self.comp_subtype, self.vector_url, kb_name)
 
     def clear_milvus_collection(self, kb_name="default_kb"):
         # get active name
         pl = ctx.get_pipeline_mgr().get_active_pipeline()
         plname = pl.name if pl else ""
         milvus_vector_store = MilvusVectorStore(
-            uri=self.milvus_uri,
+            uri=self.vector_url,
             collection_name=kb_name + plname + str(self.d),
             overwrite=False,
         )
@@ -75,3 +74,42 @@ def run(self, **kwargs) -> Any:
     def ser_model(self):
         set = {"idx": self.idx, "indexer_type": self.comp_subtype, "model": self.model}
         return set
+
+
+class KBADMINIndexer(BaseComponent):
+    # Handled in the kbadmin project
+    def __init__(self, embed_model, vector_type, kbadmin_embedding_url, vector_url="http://localhost:29530"):
+        BaseComponent.__init__(
+            self,
+            comp_type=CompType.INDEXER,
+            comp_subtype=IndexerType.KBADMIN_INDEXER,
+        )
+        self.embed_model = embed_model
+        self.kbadmin_embedding_url = kbadmin_embedding_url
+        self.vector_url = vector_url
+
+    def insert_nodes(self, nodes):
+        return None
+
+    def _index_struct(self, nodes):
+        return None
+
+    def run(self, **kwargs) -> Any:
+        return None
+
+    def reinitialize_indexer(self, kb_name="default_kb"):
+        return None
+
+    def clear_milvus_collection(self, **kwargs):
+        return None
+
+    @model_serializer
+    def ser_model(self):
+        set = {
+            "idx": self.idx,
+            "indexer_type": self.comp_subtype,
+            "model": {"model_id": self.embed_model},
+            "kbadmin_embedding_url": self.kbadmin_embedding_url,
+            "vector_url": self.vector_url,
+        }
+        return set
diff --git a/EdgeCraftRAG/edgecraftrag/components/knowledge_base.py b/EdgeCraftRAG/edgecraftrag/components/knowledge_base.py
index 259c4a463f..45ea309fad 100644
--- a/EdgeCraftRAG/edgecraftrag/components/knowledge_base.py
+++ b/EdgeCraftRAG/edgecraftrag/components/knowledge_base.py
@@ -1,8 +1,9 @@
 # Copyright (C) 2024 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
+import json
 import os
-from typing import Any, List, Optional
+from typing import Any, Dict, List, Optional, Union
 
 from edgecraftrag.base import BaseComponent
 from pydantic import model_serializer
@@ -12,8 +13,12 @@ class Knowledge(BaseComponent):
     file_paths: Optional[List[str]] = []
     file_map: Optional[List[str]] = {}
     description: Optional[str] = "None"
-    comp_type: str = "knowledge"
+    comp_type: Optional[str] = "knowledge"
+    comp_subtype: Optional[str] = "origin_kb"
+    experience_active: Optional[bool] = False if comp_type == "knowledge" else True
     active: bool
+    if comp_type == "experience":
+        comp_subtype = None
 
     def _update_file_names(self) -> None:
         self.file_map = {os.path.basename(path): path for path in self.file_paths if path is not None}
@@ -35,6 +40,105 @@ def remove_file_path(self, file_path: str) -> bool:
     def get_file_paths(self) -> List[str]:
         return self.file_paths
 
+    def ensure_file_exists(self):
+        dir_path = os.path.dirname(self.file_paths[0])
+        os.makedirs(dir_path, exist_ok=True)
+        if not os.path.exists(self.file_paths[0]):
+            with open(self.file_paths[0], "w", encoding="utf-8") as f:
+                json.dump([], f, ensure_ascii=False, indent=4)
+
+    def get_all_experience(self) -> List[Dict]:
+        experinence_file = "/home/user/ui_cache/configs/experience_dir/experience.json"
+        if experinence_file not in self.file_paths:
+            self.file_paths.append(experinence_file)
+        if not os.path.isfile(self.file_paths[0]):
+            self.ensure_file_exists()
+        with open(self.file_paths[0], "r", encoding="utf-8") as f:
+            return json.load(f)
+
+    def get_experience_by_question(self, question: str) -> Optional[Dict]:
+        for item in self.get_all_experience():
+            if item.get("question") == question:
+                return item
+        return None
+
+    def add_multiple_experiences(
+        self, experiences: List[Dict[str, Union[str, List[str]]]], flag: bool = True
+    ) -> List[Dict]:
+        all_experiences = self.get_all_experience()
+        result = []
+        for exp in experiences:
+            question = exp.get("question")
+            if not question:
+                raise ValueError("Must exist when uploading question")
+            content = exp.get("content", [])
+            found = False
+            for item in all_experiences:
+                if item["question"] == question:
+                    if flag:
+                        item["content"].extend([c for c in content if c not in item["content"]])
+                    else:
+                        item["content"] = content
+                    result.append(item)
+                    found = True
+                    break
+            if not found:
+                new_item = {"question": question, "content": content}
+                all_experiences.append(new_item)
+                result.append(new_item)
+        with open(self.file_paths[0], "w", encoding="utf-8") as f:
+            json.dump(all_experiences, f, ensure_ascii=False, indent=4)
+        return result
+
+    def delete_experience(self, question: str) -> bool:
+        items = self.get_all_experience()
+        remaining_items = [item for item in items if item.get("question") != question]
+        if len(remaining_items) == len(items):
+            return False
+        with open(self.file_paths[0], "w", encoding="utf-8") as f:
+            json.dump(remaining_items, f, ensure_ascii=False, indent=4)
+        return True
+
+    def clear_experiences(self) -> bool:
+        all_experiences = self.get_all_experience()
+        with open(self.file_paths[0], "w", encoding="utf-8") as f:
+            json.dump([], f, ensure_ascii=False, indent=4)
+        return True
+
+    def update_experience(self, question: str, content: List[str]) -> Optional[Dict]:
+        items = self.get_all_experience()
+        for i, item in enumerate(items):
+            if item.get("question") == question:
+                updated_item = {"question": question, "content": content}
+                items[i] = updated_item
+                with open(self.file_paths[0], "w", encoding="utf-8") as f:
+                    json.dump(items, f, ensure_ascii=False, indent=4)
+                return updated_item
+        return None
+
+    def add_experiences_from_file(self, file_path: str, flag: bool = False) -> List[Dict]:
+        if not file_path.endswith(".json"):
+            raise ValueError("File upload type error")
+        try:
+            with open(file_path, "r", encoding="utf-8") as f:
+                experiences = json.load(f)
+            if not isinstance(experiences, list):
+                raise ValueError("The contents of the file must be a list")
+            return self.add_multiple_experiences(experiences=experiences, flag=flag)
+        except json.JSONDecodeError as e:
+            raise ValueError("File parsing failure")
+        except Exception as e:
+            raise RuntimeError("File Error")
+
+    def calculate_totals(self):
+        if self.comp_type == "knowledge":
+            total = len(self.file_paths)
+        elif self.comp_type == "experience":
+            total = len(self.get_all_experience())
+        else:
+            total = None
+        return total
+
     def run(self, **kwargs) -> Any:
         pass
 
@@ -44,8 +148,11 @@ def ser_model(self):
             "idx": self.idx,
             "name": self.name,
             "comp_type": self.comp_type,
+            "comp_subtype": self.comp_subtype,
             "file_map": self.file_map,
             "description": self.description,
             "active": self.active,
+            "experience_active": self.experience_active,
+            "total": self.calculate_totals(),
         }
         return set
diff --git a/EdgeCraftRAG/edgecraftrag/components/node_parser.py b/EdgeCraftRAG/edgecraftrag/components/node_parser.py
index 0f386bc61f..0bd49b91b4 100644
--- a/EdgeCraftRAG/edgecraftrag/components/node_parser.py
+++ b/EdgeCraftRAG/edgecraftrag/components/node_parser.py
@@ -168,3 +168,25 @@ def ser_model(self):
             "chunk_overlap": self.chunk_overlap,
         }
         return set
+
+
+class KBADMINParser(BaseComponent):
+    # Handled in the kbadmin project
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+        self.comp_type = CompType.NODEPARSER
+        self.comp_subtype = NodeParserType.KBADMINPARSER
+
+    def run(self, **kwargs) -> Any:
+        return None
+
+    def insert_nodes(self):
+        return None
+
+    @model_serializer
+    def ser_model(self):
+        set = {
+            "idx": self.idx,
+            "parser_type": self.comp_subtype,
+        }
+        return set
diff --git a/EdgeCraftRAG/edgecraftrag/components/pipeline.py b/EdgeCraftRAG/edgecraftrag/components/pipeline.py
index 41780ef88f..29205a3819 100644
--- a/EdgeCraftRAG/edgecraftrag/components/pipeline.py
+++ b/EdgeCraftRAG/edgecraftrag/components/pipeline.py
@@ -44,7 +44,7 @@ def __init__(
         if self.name == "" or self.name is None:
             self.name = self.idx
         self.enable_benchmark = os.getenv("ENABLE_BENCHMARK", "False").lower() == "true"
-        self.run_pipeline_cb = run_generator_ben if self.enable_benchmark else run_generator
+        self.run_pipeline_cb = run_generator
         self.run_retriever_cb = run_retrieve
         self.run_data_prepare_cb = run_simple_doc
 
@@ -97,12 +97,10 @@ def check_active(self, nodelist, kb_name):
     # TODO: update doc changes
     # TODO: more operations needed, add, del, modify
     def update_nodes(self, nodes):
-        print(f"Updating {len(nodes)} nodes ...")
         if self.indexer is not None:
             self.indexer.insert_nodes(nodes)
 
     def update_indexer_to_retriever(self):
-        print("Updating indexer to retriever ...")
         if self.indexer is not None and self.retriever is not None:
             old_retriever = self.retriever
             retriever_type = old_retriever.comp_subtype
@@ -122,7 +120,6 @@ def update_indexer_to_retriever(self):
     # Implement abstract run function
     # callback dispatcher
     def run(self, **kwargs) -> Any:
-        print(kwargs)
         if "cbtype" in kwargs:
             if kwargs["cbtype"] == CallbackType.DATAPREP:
                 if "docs" in kwargs:
@@ -183,9 +180,18 @@ def model_existed(self, model_id: str) -> bool:
 
 # Test callback to retrieve nodes from query
 def run_retrieve(pl: Pipeline, chat_request: ChatCompletionRequest) -> Any:
+    benchmark_data = {}
     query = chat_request.messages
+    top_k = None if chat_request.k == ChatCompletionRequest.model_fields["k"].default else chat_request.k
     contexts = {}
-    retri_res = pl.retriever.run(query=query)
+    start = 0
+    if pl.enable_benchmark:
+        _, benchmark_data = pl.benchmark.init_benchmark_data()
+        start = time.perf_counter()
+    retri_res = pl.retriever.run(query=query, top_k=top_k)
+    if pl.enable_benchmark:
+        benchmark_data[CompType.RETRIEVER] = time.perf_counter() - start
+        pl.benchmark.insert_benchmark_data(benchmark_data)
     contexts[CompType.RETRIEVER] = retri_res
     query_bundle = QueryBundle(query)
     if pl.postprocessor:
@@ -201,10 +207,18 @@ def run_retrieve(pl: Pipeline, chat_request: ChatCompletionRequest) -> Any:
 
 
 def run_simple_doc(pl: Pipeline, docs: List[Document]) -> Any:
+    start = 0
+    benchmark_data = {}
+    if pl.enable_benchmark:
+        _, benchmark_data = pl.benchmark.init_benchmark_data()
+        start = time.perf_counter()
     n = pl.node_parser.run(docs=docs)
     if pl.indexer is not None:
         pl.indexer.insert_nodes(n)
-    print(pl.indexer._index_struct)
+    if pl.enable_benchmark:
+        benchmark_data[CompType.NODEPARSER] += time.perf_counter() - start
+        benchmark_data[CompType.CHUNK_NUM] += len(n)
+        pl.benchmark.insert_benchmark_data(benchmark_data)
     return n
 
 
@@ -225,114 +239,93 @@ async def timing_wrapper():
         return ret
 
 
-def run_generator_ben(pl: Pipeline, chat_request: ChatCompletionRequest) -> Any:
-    benchmark_index, benchmark_data = pl.benchmark.init_benchmark_data()
+def run_generator(pl: Pipeline, chat_request: ChatCompletionRequest) -> Any:
+    if pl.enable_benchmark:
+        benchmark_index, benchmark_data = pl.benchmark.init_benchmark_data()
     contexts = {}
-    start = time.perf_counter()
+    retri_res = []
+    active_kb = chat_request.user if chat_request.user else None
+    enable_rag_retrieval = (
+        chat_request.chat_template_kwargs.get("enable_rag_retrieval", True)
+        if chat_request.chat_template_kwargs
+        else True
+    )
+    if not active_kb:
+        enable_rag_retrieval = False
+    elif pl.retriever.comp_subtype == "kbadmin_retriever" and active_kb.comp_subtype == "origin_kb":
+        enable_rag_retrieval = False
+    elif pl.retriever.comp_subtype != "kbadmin_retriever" and active_kb.comp_subtype == "kbadmin_kb":
+        enable_rag_retrieval = False
     query = chat_request.messages
-    if pl.generator.inference_type == InferenceType.VLLM:
-        UI_DIRECTORY = os.getenv("TMPFILE_PATH", "/home/user/ui_cache")
-        search_config_path = os.path.join(UI_DIRECTORY, "configs/search_config.yaml")
-        search_dir = os.path.join(UI_DIRECTORY, "configs/search_dir")
-
-        def run_async_query_search():
-            loop = asyncio.new_event_loop()
-            asyncio.set_event_loop(loop)
-            try:
-                return loop.run_until_complete(query_search(query, search_config_path, search_dir, pl))
-            finally:
-                loop.close()
-
-        with ThreadPoolExecutor(max_workers=1) as executor:
-            future = executor.submit(run_async_query_search)
-            top1_issue, sub_questionss_result = future.result()
-        if sub_questionss_result:
-            query = query + sub_questionss_result
-
-    retri_res = pl.retriever.run(query=query)
-    query_bundle = QueryBundle(query)
-    benchmark_data[CompType.RETRIEVER] = time.perf_counter() - start
-    contexts[CompType.RETRIEVER] = retri_res
-
-    start = time.perf_counter()
-    if pl.postprocessor:
-        for processor in pl.postprocessor:
-            if (
-                isinstance(processor, RerankProcessor)
-                and chat_request.top_n != ChatCompletionRequest.model_fields["top_n"].default
-            ):
-                processor.top_n = chat_request.top_n
-            retri_res = processor.run(retri_res=retri_res, query_bundle=query_bundle)
-            contexts[CompType.POSTPROCESSOR] = retri_res
-    benchmark_data[CompType.POSTPROCESSOR] = time.perf_counter() - start
+    sub_questionss_result = None
+    experience_status = True if chat_request.tool_choice == "auto" else False
+    if enable_rag_retrieval:
+        start = 0
+        if pl.enable_benchmark:
+            start = time.perf_counter()
+        if pl.generator.inference_type == InferenceType.VLLM and experience_status:
+            UI_DIRECTORY = "/home/user/ui_cache"
+            search_config_path = os.path.join(UI_DIRECTORY, "configs/search_config.yaml")
+            search_dir = os.path.join(UI_DIRECTORY, "configs/experience_dir/experience.json")
+
+            def run_async_query_search():
+                loop = asyncio.new_event_loop()
+                asyncio.set_event_loop(loop)
+                try:
+                    return loop.run_until_complete(query_search(query, search_config_path, search_dir, pl))
+                finally:
+                    loop.close()
+
+            with ThreadPoolExecutor(max_workers=1) as executor:
+                future = executor.submit(run_async_query_search)
+                top1_issue, sub_questionss_result = future.result()
+            if sub_questionss_result:
+                query = query + sub_questionss_result
+        if pl.enable_benchmark:
+            benchmark_data[CompType.QUERYSEARCH] = time.perf_counter() - start
+            start = time.perf_counter()
+        top_k = None if chat_request.k == ChatCompletionRequest.model_fields["k"].default else chat_request.k
+        retri_res = pl.retriever.run(query=query, top_k=top_k)
+        if pl.enable_benchmark:
+            benchmark_data[CompType.RETRIEVER] = time.perf_counter() - start
+        contexts[CompType.RETRIEVER] = retri_res
+        query_bundle = QueryBundle(query)
+        if pl.enable_benchmark:
+            start = time.perf_counter()
+        if pl.postprocessor:
+            for processor in pl.postprocessor:
+                if (
+                    isinstance(processor, RerankProcessor)
+                    and chat_request.top_n != ChatCompletionRequest.model_fields["top_n"].default
+                ):
+                    processor.top_n = chat_request.top_n
+                retri_res = processor.run(retri_res=retri_res, query_bundle=query_bundle)
+                contexts[CompType.POSTPROCESSOR] = retri_res
+        if pl.enable_benchmark:
+            benchmark_data[CompType.POSTPROCESSOR] = time.perf_counter() - start
 
     if pl.generator is None:
         raise ValueError("No Generator Specified")
 
-    text_gen_context, prompt_str = pl.generator.query_transform(chat_request, retri_res)
-    input_token_size = pl.benchmark.cal_input_token_size(prompt_str)
-
-    np_type = pl.node_parser.comp_subtype
-    start = time.perf_counter()
-    if pl.generator.inference_type == InferenceType.LOCAL:
-        ret = pl.generator.run(chat_request, retri_res, np_type)
-    elif pl.generator.inference_type == InferenceType.VLLM:
-        ret = pl.generator.run_vllm(chat_request, retri_res, np_type, sub_questions=sub_questionss_result)
-    else:
-        raise ValueError("LLM inference_type not supported")
-    end = time.perf_counter()
+    if pl.enable_benchmark:
+        _, prompt_str = pl.generator.query_transform(chat_request, retri_res)
+        input_token_size = pl.benchmark.cal_input_token_size(prompt_str)
 
-    if isinstance(ret, StreamingResponse):
-        ret = benchmark_response(ret, pl.benchmark, benchmark_index, benchmark_data, input_token_size, start)
-    else:
-        benchmark_data[CompType.GENERATOR] = end - start
-        pl.benchmark.insert_llm_data(benchmark_index, input_token_size)
-        pl.benchmark.insert_benchmark_data(benchmark_data)
-    return ret, contexts
-
-
-def run_generator(pl: Pipeline, chat_request: ChatCompletionRequest) -> Any:
-    query = chat_request.messages
-    contexts = {}
-    if pl.generator.inference_type == InferenceType.VLLM:
-        UI_DIRECTORY = os.getenv("TMPFILE_PATH", "/home/user/ui_cache")
-        search_config_path = os.path.join(UI_DIRECTORY, "configs/search_config.yaml")
-        search_dir = os.path.join(UI_DIRECTORY, "configs/search_dir")
-
-        def run_async_query_search():
-            loop = asyncio.new_event_loop()
-            asyncio.set_event_loop(loop)
-            try:
-                return loop.run_until_complete(query_search(query, search_config_path, search_dir, pl))
-            finally:
-                loop.close()
-
-        with ThreadPoolExecutor(max_workers=1) as executor:
-            future = executor.submit(run_async_query_search)
-            top1_issue, sub_questionss_result = future.result()
-        if sub_questionss_result:
-            query = query + sub_questionss_result
-    retri_res = pl.retriever.run(query=query)
-    contexts[CompType.RETRIEVER] = retri_res
-    query_bundle = QueryBundle(query)
-
-    if pl.postprocessor:
-        for processor in pl.postprocessor:
-            if (
-                isinstance(processor, RerankProcessor)
-                and chat_request.top_n != ChatCompletionRequest.model_fields["top_n"].default
-            ):
-                processor.top_n = chat_request.top_n
-            retri_res = processor.run(retri_res=retri_res, query_bundle=query_bundle)
-            contexts[CompType.POSTPROCESSOR] = retri_res
-
-    if pl.generator is None:
-        raise ValueError("No Generator Specified")
     np_type = pl.node_parser.comp_subtype
+    if pl.enable_benchmark:
+        start = time.perf_counter()
     if pl.generator.inference_type == InferenceType.LOCAL:
         ret = pl.generator.run(chat_request, retri_res, np_type)
     elif pl.generator.inference_type == InferenceType.VLLM:
         ret = pl.generator.run_vllm(chat_request, retri_res, np_type, sub_questions=sub_questionss_result)
     else:
         raise ValueError("LLM inference_type not supported")
+    if pl.enable_benchmark:
+        end = time.perf_counter()
+        if isinstance(ret, StreamingResponse):
+            ret = benchmark_response(ret, pl.benchmark, benchmark_index, benchmark_data, input_token_size, start)
+        else:
+            benchmark_data[CompType.GENERATOR] = end - start
+            pl.benchmark.insert_llm_data(benchmark_index, input_token_size)
+            pl.benchmark.insert_benchmark_data(benchmark_data)
     return ret, contexts
diff --git a/EdgeCraftRAG/edgecraftrag/components/postprocessor.py b/EdgeCraftRAG/edgecraftrag/components/postprocessor.py
index bb59cc3d21..cbd387f59e 100644
--- a/EdgeCraftRAG/edgecraftrag/components/postprocessor.py
+++ b/EdgeCraftRAG/edgecraftrag/components/postprocessor.py
@@ -60,5 +60,5 @@ def run(self, **kwargs) -> Any:
 
     @model_serializer
     def ser_model(self):
-        set = {"idx": self.idx, "processor_type": self.comp_subtype, "model": None, "top_n": None}
+        set = {"idx": self.idx, "processor_type": self.comp_subtype, "top_n": None}
         return set
diff --git a/EdgeCraftRAG/edgecraftrag/components/query_preprocess.py b/EdgeCraftRAG/edgecraftrag/components/query_preprocess.py
index 124014a038..320f2c32aa 100644
--- a/EdgeCraftRAG/edgecraftrag/components/query_preprocess.py
+++ b/EdgeCraftRAG/edgecraftrag/components/query_preprocess.py
@@ -85,6 +85,7 @@ def __init__(
         output_template="",
         json_key="relevance",
         json_levels=["Low", "High"],
+        scores_weight=None,
         temperature=1.0,
         API_BASE=None,
         **kwargs,
@@ -107,6 +108,19 @@ def __init__(
         self.json_levels = json_levels
         self.API_BASE = API_BASE
 
+        # dynamically set scores_weight, use default if not provided
+        if scores_weight is None:
+            # generate default weights based on json_levels count
+            if len(json_levels) == 2:
+                self.scores_weight = [0.0, 1.0]  # Low, High
+            elif len(json_levels) == 3:
+                self.scores_weight = [0.0, 0.5, 1.0]  # Low, Medium, High
+            else:
+                # for other counts, generate evenly spaced weights
+                self.scores_weight = [i / (len(json_levels) - 1) for i in range(len(json_levels))]
+        else:
+            self.scores_weight = scores_weight
+
     async def invoke_vllm(self, input_texts):
         headers = {"Content-Type": "application/json"}
         payload = {
@@ -152,18 +166,22 @@ async def _calculate_logits_score(self, user_input, issue):
 
     def _calculate_token_score_vllm(self, outputs, output_index=1, transform="exp"):
         generated_scores = outputs[output_index]
-        three_scores = [
-            generated_scores.get("Low", -9999.0),
-            generated_scores.get("Medium", -9999.0),
-            generated_scores.get("High", -9999.0),
-        ]
-        level_scores = [score / self.temperature for score in three_scores]
+
+        # dynamically get scores for all levels
+        level_scores = []
+        for level in self.json_levels:
+            level_scores.append(generated_scores.get(level, -9999.0))
+
+        # apply temperature scaling
+        level_scores = [score / self.temperature for score in level_scores]
 
         level_scores_np = numpy.array(level_scores)
         level_scores_np = numpy.where(level_scores_np < -1000, -1000, level_scores_np)
         level_scores_np_exp = numpy.exp(level_scores_np - numpy.max(level_scores_np))
         scores_probs = level_scores_np_exp / level_scores_np_exp.sum()
-        scores_weight = numpy.array([0.0, 0.5, 1.0])  # Low=0, Medium=0.5, High=1
+
+        # using dynamic scores_weight
+        scores_weight = numpy.array(self.scores_weight)
         final_score = numpy.dot(scores_probs, scores_weight)
 
         return final_score
@@ -172,40 +190,43 @@ async def compute_score(self, input_pair):
         return await self._calculate_logits_score(*input_pair)
 
 
-def read_json_files(directory: str) -> dict:
+def read_json_files(file_path: str) -> dict:
     result = {}
-    for filename in os.listdir(directory):
-        if filename.endswith(".json"):
-            file_path = os.path.join(directory, filename)
-            if os.path.isfile(file_path):
-                try:
-                    with open(file_path, "r", encoding="utf-8") as file:
-                        data = json.load(file)
-                        result.update(data)
-                except Exception:
-                    continue
+    if os.path.isfile(file_path):
+        with open(file_path, "r", encoding="utf-8") as f:
+            result = json.load(f)
     return result
 
 
 async def query_search(user_input, search_config_path, search_dir, pl):
-
     top1_issue = None
-    sub_questionss_result = None
-    if not os.path.exists(search_dir):
-        return top1_issue, sub_questionss_result
+    sub_questions_result = None
 
     model_id = pl.generator.model_id
     vllm_endpoint = pl.generator.vllm_endpoint
 
-    cfg = OmegaConf.load(search_config_path)
-    cfg.query_matcher.model_id = model_id
-    cfg.query_matcher.API_BASE = os.path.join(vllm_endpoint, "v1/completions")
-    query_matcher = LogitsEstimatorJSON(**cfg.query_matcher)
     maintenance_data = read_json_files(search_dir)
-    issues = list(maintenance_data.keys())
+    issues = []
+    for i in range(len(maintenance_data)):
+        issues.append(maintenance_data[i]["question"])
     if not issues:
-        return top1_issue, sub_questionss_result
-
+        return top1_issue, sub_questions_result
+
+    cfg = {}
+    if not os.path.exists(search_config_path):
+        cfg["query_matcher"] = {
+            "instructions": "You're a knowledgeable assistant. Your task is to judge if two queries ask for the same information about the same primary subject. Output only 'Yes' or 'No'. Yes = same subject entity AND same information need, with only wording or stylistic differences. No = different subject entity, different spec or numeric constraint, different attribute/metric, or scope changed by adding/removing a restricting condition. Entity changes MUST lead to No.",
+            "input_template": "Query 1: {}\nQuery 2: {}\n",
+            "output_template": "\nAre these queries equivalent? Answer 'Yes' or 'No':",
+            "json_key": "similarity",
+            "json_levels": ["No", "Yes"],
+            "temperature": 0.1,
+        }
+    else:
+        cfg = OmegaConf.load(search_config_path)
+    cfg["query_matcher"]["model_id"] = model_id
+    cfg["query_matcher"]["API_BASE"] = os.path.join(vllm_endpoint, "v1/completions")
+    query_matcher = LogitsEstimatorJSON(**cfg["query_matcher"])
     semaphore = asyncio.Semaphore(200)
 
     async def limited_compute_score(query_matcher, user_input, issue):
@@ -219,9 +240,9 @@ async def limited_compute_score(query_matcher, user_input, issue):
 
     # Maximum less than 0.6, we don't use query search.
     if match_scores[0][1] < 0.6:
-        return top1_issue, sub_questionss_result
+        return top1_issue, sub_questions_result
     top1_issue = match_scores[0][0]
-    for key, value in maintenance_data.items():
-        if key == top1_issue:
-            sub_questionss_result = value
-    return top1_issue, sub_questionss_result
+    for i in range(len(maintenance_data)):
+        if maintenance_data[i]["question"] == top1_issue:
+            sub_questions_result = "\n".join(maintenance_data[i]["content"])
+    return top1_issue, sub_questions_result
diff --git a/EdgeCraftRAG/edgecraftrag/components/retriever.py b/EdgeCraftRAG/edgecraftrag/components/retriever.py
index fa8553346a..cdd3fe0bc2 100644
--- a/EdgeCraftRAG/edgecraftrag/components/retriever.py
+++ b/EdgeCraftRAG/edgecraftrag/components/retriever.py
@@ -1,14 +1,19 @@
 # Copyright (C) 2024 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
-from typing import Any, List, cast
+import warnings
+from typing import Any, List, Optional, cast
 
+import requests
 from edgecraftrag.base import BaseComponent, CompType, RetrieverType
+from langchain_milvus import Milvus
+from langchain_openai import OpenAIEmbeddings
 from llama_index.core.indices.vector_store.retrievers import VectorIndexRetriever
 from llama_index.core.retrievers import AutoMergingRetriever
-from llama_index.core.schema import BaseNode
+from llama_index.core.schema import BaseNode, Document, NodeWithScore
 from llama_index.retrievers.bm25 import BM25Retriever
 from pydantic import model_serializer
+from pymilvus import Collection, MilvusException, connections, utility
 
 
 class VectorSimRetriever(BaseComponent, VectorIndexRetriever):
@@ -39,6 +44,8 @@ def __init__(self, indexer, **kwargs):
     def run(self, **kwargs) -> Any:
         for k, v in kwargs.items():
             if k == "query":
+                top_k = kwargs["top_k"] if kwargs["top_k"] else self.topk
+                self.similarity_top_k = top_k
                 return self.retrieve(v)
 
         return None
@@ -75,8 +82,9 @@ def __init__(self, indexer, **kwargs):
     def run(self, **kwargs) -> Any:
         for k, v in kwargs.items():
             if k == "query":
+                top_k = kwargs["top_k"] if kwargs["top_k"] else self.topk
                 # vector_retriever needs to be updated
-                self._vector_retriever = self._index.as_retriever(similarity_top_k=self.topk)
+                self._vector_retriever = self._index.as_retriever(similarity_top_k=top_k)
                 return self.retrieve(v)
 
         return None
@@ -108,8 +116,9 @@ def __init__(self, indexer, **kwargs):
     def run(self, **kwargs) -> Any:
         for k, v in kwargs.items():
             if k == "query":
+                top_k = kwargs["top_k"] if kwargs["top_k"] else self.topk
                 nodes = cast(List[BaseNode], list(self._docstore.docs.values()))
-                similarity_top_k = min(len(nodes), self.topk)
+                similarity_top_k = min(len(nodes), top_k)
                 bm25_retr = BM25Retriever.from_defaults(nodes=nodes, similarity_top_k=similarity_top_k)
                 return bm25_retr.retrieve(v)
 
@@ -123,3 +132,139 @@ def ser_model(self):
             "retrieve_topk": self.topk,
         }
         return set
+
+
+class KBadminRetriever(BaseComponent):
+    def __init__(self, indexer, **kwargs):
+        BaseComponent.__init__(
+            self,
+            comp_type=CompType.RETRIEVER,
+            comp_subtype=RetrieverType.KBADMIN_RETRIEVER,
+        )
+        self.vector_db = None
+        self.collection_name = None
+        self.topk = kwargs.get("similarity_top_k", 30)
+        self.KBADMIN_MILVUS_URL = indexer.vector_url
+        self.CONNECTION_ARGS = {"uri": indexer.vector_url}
+        self.vector_field = "q_1024_vec"
+        self.text_field = "content_with_weight"
+        self.embedding_model_name = indexer.embed_model
+        self.embedding_url = indexer.kbadmin_embedding_url + "/v3"
+        self.embedding = OpenAIEmbeddings(
+            model=self.embedding_model_name,
+            api_key="unused",
+            base_url=self.embedding_url,
+            tiktoken_enabled=False,
+            embedding_ctx_length=510,
+        )
+
+    def config_kbadmin_milvus(self, knowledge_name):
+        collection_name = knowledge_name
+        if not kbs_rev_maps:
+            get_kbs_info(self.CONNECTION_ARGS)
+        collection_name = kbs_rev_maps[collection_name]
+        self.vector_db = Milvus(
+            self.embedding,
+            connection_args=self.CONNECTION_ARGS,
+            collection_name=collection_name,
+            vector_field=self.vector_field,
+            text_field=self.text_field,
+            enable_dynamic_field=True,
+            index_params={"index_type": "FLAT", "metric_type": "IP", "params": {}},
+        )
+
+    def similarity_search_with_embedding(self, query: str, k) -> list[tuple[Document, float]]:
+        url = self.embedding_url + "/embeddings"
+        embedding_info = {"model": self.embedding_model_name, "input": query}
+        # Get embedding result from embedding service
+        response = requests.post(url, headers={"Content-Type": "application/json"}, json=embedding_info)
+        embedding_json = response.json()
+        embedding = embedding_json["data"][0]["embedding"]
+        docs_and_scores = self.vector_db.similarity_search_with_score_by_vector(embedding=embedding, k=k)
+        relevance_score_fn = self.vector_db._select_relevance_score_fn()
+        return [(doc, relevance_score_fn(score)) for doc, score in docs_and_scores]
+
+    def run(self, **kwargs) -> Any:
+        query = kwargs["query"]
+        top_k = kwargs["top_k"] if kwargs["top_k"] else self.topk
+        # langchain retrieval
+        docs_and_similarities = self.similarity_search_with_embedding(query=query, k=top_k)
+        node_with_scores: List[NodeWithScore] = []
+        for doc, similarity in docs_and_similarities:
+            score: Optional[float] = None
+            if similarity is not None:
+                score = similarity
+            # convert langchain store format into llamaindex
+            node = Document.from_langchain_format(doc)
+            node_with_scores.append(NodeWithScore(node=node, score=score))
+        return node_with_scores
+
+    @model_serializer
+    def ser_model(self):
+        set = {"idx": self.idx, "retriever_type": self.comp_subtype, "CONNECTION_ARGS": self.CONNECTION_ARGS}
+        return set
+
+
+# global kbs maps.
+global kbs_rev_maps
+kbs_rev_maps = {}
+
+
+def get_kbs_info(CONNECTION_ARGS):
+    alias = "default"
+    try:
+        connections.connect("default", **CONNECTION_ARGS)
+        collections = utility.list_collections()
+        all_kb_infos = {}
+        new_infos = {}
+        for kb in collections:
+            collection = Collection(kb)
+            collection.load()
+            try:
+                if any(field.name == "kb_id" for field in collection.schema.fields):
+                    docs = collection.query(
+                        expr="pk != 0",
+                        output_fields=["kb_name", "kb_id", "docnm_kwd"],
+                        timeout=10,
+                    )
+                else:
+                    docs = collection.query(
+                        expr="pk != 0",
+                        output_fields=["filename"],
+                        timeout=10,
+                    )
+                collection.release()
+            except MilvusException as e:
+                continue
+            this_kbinfo = {}
+            for doc in docs:
+                try:
+                    if "kb_name" in doc:
+                        if not this_kbinfo:
+                            this_kbinfo["name"] = doc["kb_name"]
+                            this_kbinfo["uuid"] = doc["kb_id"]
+                            this_kbinfo["files"] = set([doc["docnm_kwd"]])
+                        else:
+                            this_kbinfo["files"].add(doc["docnm_kwd"])
+                    else:
+                        if not this_kbinfo:
+                            this_kbinfo["name"] = kb
+                            this_kbinfo["uuid"] = ""
+                            this_kbinfo["files"] = set([doc["filename"]])
+                        else:
+                            this_kbinfo["files"].add(doc["filename"])
+                except KeyError:
+                    this_kbinfo = None
+                    break
+            if this_kbinfo:
+                unique_files = list(this_kbinfo["files"])
+                this_kbinfo["files"] = unique_files
+                new_infos[kb] = this_kbinfo
+        all_kb_infos.update(new_infos)
+        kbs_rev_maps.clear()
+        for kb_id in all_kb_infos:
+            kbs_rev_maps[all_kb_infos[kb_id]["name"]] = kb_id
+        return kbs_rev_maps
+    finally:
+        if connections.has_connection(alias):
+            connections.disconnect(alias)
diff --git a/EdgeCraftRAG/edgecraftrag/controllers/compmgr.py b/EdgeCraftRAG/edgecraftrag/controllers/compmgr.py
index b8dd82ab7b..c956ee316d 100644
--- a/EdgeCraftRAG/edgecraftrag/controllers/compmgr.py
+++ b/EdgeCraftRAG/edgecraftrag/controllers/compmgr.py
@@ -26,6 +26,34 @@ def search_parser(self, npin: NodeParserIn) -> BaseComponent:
                     return v
         return None
 
+    def search_parser_change(self, pl, req):
+        pl_change = False
+        try:
+            if pl.node_parser.comp_subtype != req.node_parser.parser_type:
+                return True
+            if pl.node_parser.comp_subtype == req.node_parser.parser_type:
+                if pl.node_parser.comp_subtype == NodeParserType.SIMPLE:
+                    if (
+                        pl.node_parser.chunk_size != req.node_parser.chunk_size
+                        or pl.node_parser.chunk_overlap != req.node_parser.chunk_overlap
+                    ):
+                        pl_change = True
+                elif pl.node_parser.comp_subtype == NodeParserType.SENTENCEWINDOW:
+                    if pl.node_parser.window_size != req.node_parser.window_size:
+                        pl_change = True
+                elif pl.node_parser.comp_subtype == NodeParserType.HIERARCHY:
+                    if pl.node_parser.chunk_sizes != req.node_parser.chunk_sizes:
+                        pl_change = True
+                elif pl.node_parser.comp_subtype == NodeParserType.UNSTRUCTURED:
+                    if (
+                        pl.node_parser.chunk_size != req.node_parser.chunk_size
+                        or pl.node_parser.chunk_overlap != req.node_parser.chunk_overlap
+                    ):
+                        pl_change = True
+        except:
+            return False
+        return pl_change
+
 
 class IndexerMgr(BaseMgr):
 
@@ -43,6 +71,7 @@ def search_indexer(self, indin: IndexerIn) -> BaseComponent:
                         (v.model.model_id_or_path == indin.embedding_model.model_id)
                         or (v.model.model_id_or_path == indin.embedding_model.model_path)
                     )
+                    and v.model.device == indin.embedding_model.device
                 ):
                     return v
         return None
diff --git a/EdgeCraftRAG/edgecraftrag/controllers/filemgr.py b/EdgeCraftRAG/edgecraftrag/controllers/filemgr.py
index 0278f1f6ac..6f29e931e4 100644
--- a/EdgeCraftRAG/edgecraftrag/controllers/filemgr.py
+++ b/EdgeCraftRAG/edgecraftrag/controllers/filemgr.py
@@ -20,7 +20,7 @@ def add_text(self, text: str):
         self.add(file)
         return file.documents
 
-    def add_files(self, docs: Any):
+    def add_files(self, docs: Any, docs_name: str = "default"):
         if not isinstance(docs, list):
             docs = [docs]
 
@@ -41,38 +41,31 @@ def add_files(self, docs: Any):
 
             for file_path in files:
                 file = File(file_path=file_path)
-                self.add(file)
+                self.append(file, docs_name)
                 input_docs.extend(file.documents)
-
         return input_docs
 
-    def get_file_by_name_or_id(self, name: str):
-        for _, file in self.components.items():
-            if file.name == name or file.idx == name:
-                return file
+    def get_file_by_name(self, docs_name: str = "default", file_path: str = None):
+        for name, files in self.components.items():
+            if docs_name == name:
+                for file in files:
+                    if file_path == file.documents[0].metadata["file_path"]:
+                        return file.documents
         return None
 
-    def get_files(self):
-        return [file for _, file in self.components.items()]
+    def get_kb_files_by_name(self, docs_name: str = "default"):
+        file_docs = []
+        for name, files in self.components.items():
+            if name == docs_name:
+                return files
+        return file_docs
 
     def get_all_docs(self) -> List[Document]:
-        all_docs = []
-        for _, file in self.components.items():
-            all_docs.extend(file.documents)
+        all_docs = {}
+        for doc_name, files in self.components.items():
+            all_docs[doc_name] = files
         return all_docs
 
-    def get_docs_by_file(self, name) -> List[Document]:
-        file = self.get_file_by_name_or_id(name)
-        return file.documents if file else []
-
-    def del_file(self, name):
-        file = self.get_file_by_name_or_id(name)
-        if file:
-            self.remove(file.idx)
-            return True
-        else:
-            return False
-
     def update_file(self, name):
         file = self.get_file_by_name_or_id(name)
         if file:
@@ -81,3 +74,20 @@ def update_file(self, name):
             return True
         else:
             return False
+
+    def del_kb_file(self, docs_name: str = "default"):
+        files = self.get_kb_files_by_name(docs_name)
+        if files:
+            self.remove(docs_name)
+
+    def del_file(self, docs_name: str = "default", file_path: str = None):
+        files = self.get_file_by_name(docs_name, file_path)
+        docs_list = []
+        for docs_file in files:
+            docs_list.append(docs_file.id_)
+        files = self.get_kb_files_by_name(docs_name)
+        for docs_file in files:
+            if file_path == docs_file.documents[0].metadata["file_path"]:
+                self.components[docs_name].remove(docs_file)
+                return docs_list
+        return None
diff --git a/EdgeCraftRAG/edgecraftrag/controllers/knowledge_basemgr.py b/EdgeCraftRAG/edgecraftrag/controllers/knowledge_basemgr.py
index dc69943eb2..d6dbba3ead 100644
--- a/EdgeCraftRAG/edgecraftrag/controllers/knowledge_basemgr.py
+++ b/EdgeCraftRAG/edgecraftrag/controllers/knowledge_basemgr.py
@@ -13,6 +13,7 @@ class KnowledgeManager(BaseMgr):
     def __init__(self):
         super().__init__()
         self.active_knowledge_idx: Optional[str] = None
+        self.active_experience_idx: Optional[str] = None
 
     def get_knowledge_base_by_name_or_id(self, name: str):
         for _, kb in self.components.items():
@@ -26,8 +27,17 @@ def get_active_knowledge_base(self) -> Optional[Knowledge]:
         else:
             return None
 
+    def get_active_experience(self):
+        if self.active_experience_idx:
+            return self.get_knowledge_base_by_name_or_id(self.active_experience_idx)
+        else:
+            return None
+
     def active_knowledge(self, knowledge: KnowledgeBaseCreateIn):
         kb = self.get_knowledge_base_by_name_or_id(knowledge.name)
+        if kb.comp_type != "knowledge":
+            raise HTTPException(status_code=status.HTTP_409_CONFLICT, detail="Experience type  cannot be active")
+        kb = self.get_knowledge_base_by_name_or_id(knowledge.name)
         self.active_knowledge_idx = kb.idx if knowledge.active else None
 
         for idx, comp in self.components.items():
@@ -35,16 +45,44 @@ def active_knowledge(self, knowledge: KnowledgeBaseCreateIn):
                 comp.active = idx == self.active_knowledge_idx
         return kb
 
+    def active_experience(self, knowledge: KnowledgeBaseCreateIn):
+        kb = self.get_knowledge_base_by_name_or_id(knowledge.name)
+        if kb.comp_type != "experience":
+            raise HTTPException(status_code=status.HTTP_409_CONFLICT, detail="Knowledge type  cannot be active")
+        self.active_experience_idx = kb.idx if knowledge.experience_active else None
+        if kb.experience_active != knowledge.experience_active:
+            for idx, comp in self.components.items():
+                if isinstance(comp, Knowledge):
+                    comp.experience_active = idx == self.active_experience_idx
+        return kb
+
     def create_knowledge_base(self, knowledge: KnowledgeBaseCreateIn) -> Knowledge:
         for _, kb in self.components.items():
             if kb.name == knowledge.name:
                 raise HTTPException(status_code=status.HTTP_409_CONFLICT, detail="The knowledge base already exists.")
+            if knowledge.comp_type == "experience":
+                for idx, kb in self.components.items():
+                    if kb.comp_type == "experience":
+                        raise HTTPException(
+                            status_code=status.HTTP_409_CONFLICT, detail="Only one experience class can be created."
+                        )
+        if knowledge.comp_type == "experience":
+            knowledge.active = False
         if knowledge.active is None:
             knowledge.active = False
-        kb = Knowledge(name=knowledge.name, description=knowledge.description, active=knowledge.active)
+        kb = Knowledge(
+            name=knowledge.name,
+            description=knowledge.description,
+            active=knowledge.active,
+            comp_type=knowledge.comp_type,
+            comp_subtype=knowledge.comp_subtype,
+            experience_active=knowledge.experience_active,
+        )
         self.add(kb)
         if knowledge.active:
             self.active_knowledge(knowledge)
+        if knowledge.experience_active:
+            self.active_experience(knowledge)
         return kb
 
     def delete_knowledge_base(self, name: str):
@@ -54,12 +92,16 @@ def delete_knowledge_base(self, name: str):
 
     def update_knowledge_base(self, knowledge) -> Knowledge:
         kb = self.get_knowledge_base_by_name_or_id(knowledge.name)
-
-        if knowledge.description is not None:
-            kb.description = knowledge.description
-
-        if knowledge.active is not None and kb.active != knowledge.active:
-            kb = self.active_knowledge(knowledge)
+        if kb.comp_type == "knowledge":
+            if knowledge.description is not None:
+                kb.description = knowledge.description
+            if knowledge.active is not None and kb.active != knowledge.active:
+                kb = self.active_knowledge(knowledge)
+        if kb.comp_type == "experience":
+            if knowledge.description is not None:
+                kb.description = knowledge.description
+            if knowledge.experience_active is not None and kb.experience_active != knowledge.experience_active:
+                kb = self.active_experience(knowledge)
         return "Knowledge base update successfully"
 
     def get_all_knowledge_bases(self) -> List[Dict[str, Any]]:
@@ -67,3 +109,8 @@ def get_all_knowledge_bases(self) -> List[Dict[str, Any]]:
         for idx, kb in self.components.items():
             kb_list.append(kb)
         return kb_list
+
+    def get_experience_kb(self):
+        for idx, kb in self.components.items():
+            if kb.comp_type == "experience":
+                return kb
diff --git a/EdgeCraftRAG/edgecraftrag/controllers/pipelinemgr.py b/EdgeCraftRAG/edgecraftrag/controllers/pipelinemgr.py
index 81524a3754..b22f0c66df 100644
--- a/EdgeCraftRAG/edgecraftrag/controllers/pipelinemgr.py
+++ b/EdgeCraftRAG/edgecraftrag/controllers/pipelinemgr.py
@@ -66,8 +66,8 @@ def activate_pipeline(self, name: str, active: bool, nm: NodeMgr, kb_name: None)
             return
 
         nodelist = None
-        if pl.node_changed:
-            nodelist = nm.get_nodes(pl.node_parser.idx)
+        # if pl.node_changed:
+        #     nodelist = nm.get_nodes(pl.node_parser.idx)
         pl.check_active(nodelist, kb_name)
         prevactive = self._active_pipeline
         if prevactive:
diff --git a/EdgeCraftRAG/edgecraftrag/requirements.txt b/EdgeCraftRAG/edgecraftrag/requirements.txt
old mode 100644
new mode 100755
index 8dc53e6c83..289ba3ef4d
--- a/EdgeCraftRAG/edgecraftrag/requirements.txt
+++ b/EdgeCraftRAG/edgecraftrag/requirements.txt
@@ -3,11 +3,13 @@ EbookLib>=0.18
 faiss-cpu>=1.8.0.post1
 html2text>=2025.4.15
 langchain-core==0.3.60
-llama-index==0.12.41
-llama-index-core==0.12.41
+langchain-milvus
+langchain-openai
+llama-index==0.12.36
+llama-index-core==0.12.37
 llama-index-embeddings-openvino==0.5.2
-llama-index-llms-openai==0.4.0
-llama-index-llms-openai-like==0.4.0
+llama-index-llms-openai==0.3.44
+llama-index-llms-openai-like==0.3.4
 llama-index-llms-openvino==0.4.0
 llama-index-postprocessor-openvino-rerank==0.4.1
 llama-index-readers-file==0.4.7
@@ -20,6 +22,6 @@ pillow>=10.4.0
 py-cpuinfo>=9.0.0
 pymilvus==2.5.10
 python-docx==1.1.2
-unstructured==0.16.11
+unstructured
 unstructured[pdf]
 werkzeug==3.1.3
diff --git a/EdgeCraftRAG/edgecraftrag/utils.py b/EdgeCraftRAG/edgecraftrag/utils.py
index 18a43e5879..1eef20f8c2 100755
--- a/EdgeCraftRAG/edgecraftrag/utils.py
+++ b/EdgeCraftRAG/edgecraftrag/utils.py
@@ -44,15 +44,14 @@ def iter_elements(cls, paragraph: Paragraph, opts: DocxPartitionerOptions) -> It
             yield Image(text="IMAGE", metadata=element_metadata)
 
 
-def get_prompt_template(model_id, prompt_content=None, template_path=None, enable_think=False):
+def get_prompt_template(model_path, prompt_content=None, template_path=None, enable_think=False):
     if prompt_content is not None:
         template = prompt_content
     elif template_path is not None:
         template = Path(template_path).read_text(encoding=None)
     else:
         template = DEFAULT_TEMPLATE
-    tokenizer = AutoTokenizer.from_pretrained(model_id)
-    model_id = model_id.split("/")[-1]
+    tokenizer = AutoTokenizer.from_pretrained(model_path)
     messages = [{"role": "system", "content": template}, {"role": "user", "content": "\n{input}\n"}]
     prompt_template = tokenizer.apply_chat_template(
         messages,
@@ -90,10 +89,6 @@ def compare_mappings(new_dict, old_dict):
         deleted = {name: old_files[name] for name in set(old_files) - set(new_files)}
         if deleted:
             deleted_files[key] = deleted
-
-    for key in list(added_files.keys()):
-        if key in deleted_files:
-            del added_files[key]
     return added_files, deleted_files
 
 
@@ -126,7 +121,7 @@ def concat_history(message: str) -> str:
     max_token = 6000
     active_pl = ctx.get_pipeline_mgr().get_active_pipeline()
     if active_pl.generator.inference_type == InferenceType.VLLM:
-        vllm_max_len = int(os.getenv("MAX_MODEL_LEN", "5000"))
+        vllm_max_len = int(os.getenv("MAX_MODEL_LEN", "10240"))
         if vllm_max_len > 5000:
             max_token = vllm_max_len - 1024
 
diff --git a/EdgeCraftRAG/nginx/nginx-conf-generator.sh b/EdgeCraftRAG/nginx/nginx-conf-generator.sh
index bd8e5b194c..f12799f583 100644
--- a/EdgeCraftRAG/nginx/nginx-conf-generator.sh
+++ b/EdgeCraftRAG/nginx/nginx-conf-generator.sh
@@ -25,7 +25,7 @@ EOL
 # Generate the server lines
 for ((i=0; i<PORT_NUM; i++)); do
     PORT_VAR="VLLM_SERVICE_PORT_$i"
-    echo "        server ${HOST_IP}:${!PORT_VAR};" >> $2
+    echo "        server ${HOST_IP}:${!PORT_VAR:-8$((i+1))00};" >> $2
 done
 
 # Close the upstream block and the http block
diff --git a/EdgeCraftRAG/tests/test_compose_vllm_on_arc.sh b/EdgeCraftRAG/tests/test_compose_vllm_on_arc.sh
index 192e18b67c..700dd92990 100755
--- a/EdgeCraftRAG/tests/test_compose_vllm_on_arc.sh
+++ b/EdgeCraftRAG/tests/test_compose_vllm_on_arc.sh
@@ -35,7 +35,7 @@ TENSOR_PARALLEL_SIZE=1
 SELECTED_XPU_0=0
 vLLM_ENDPOINT="http://${HOST_IP}:${NGINX_PORT}"
 LLM_MODEL="Qwen/Qwen3-8B"
-LLM_MODEL_PATH="${HOME}/qwen/"
+LLM_MODEL_PATH="${MODEL_PATH}/${LLM_MODEL}"
 NGINX_CONFIG_PATH="$WORKPATH/nginx/nginx.conf"
 VLLM_IMAGE_TAG="0.8.3-b20"
 DP_NUM=1
diff --git a/EdgeCraftRAG/tests/test_compose_vllm_on_arc_b60.sh b/EdgeCraftRAG/tests/test_compose_vllm_on_arc_b60.sh
new file mode 100755
index 0000000000..df97274a89
--- /dev/null
+++ b/EdgeCraftRAG/tests/test_compose_vllm_on_arc_b60.sh
@@ -0,0 +1,173 @@
+#!/bin/bash
+# Copyright (C) 2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+set -e
+source ./common.sh
+
+IMAGE_REPO=${IMAGE_REPO:-"opea"}
+IMAGE_TAG=${IMAGE_TAG:-"latest"}
+echo "REGISTRY=IMAGE_REPO=${IMAGE_REPO}"
+echo "TAG=IMAGE_TAG=${IMAGE_TAG}"
+export REGISTRY=${IMAGE_REPO}
+export TAG=${IMAGE_TAG}
+
+WORKPATH=$(dirname "$PWD")
+LOG_PATH="$WORKPATH/tests"
+
+ip_address=$(hostname -I | awk '{print $1}')
+HOST_IP=$ip_address
+
+COMPOSE_FILE="compose_vllm_b60.yaml"
+EC_RAG_SERVICE_PORT=16010
+
+MODEL_PATH="${HOME}/models"
+# MODEL_PATH="$WORKPATH/models"
+DOC_PATH="$WORKPATH/tests"
+UI_UPLOAD_PATH="$WORKPATH/tests"
+
+HF_ENDPOINT=https://hf-mirror.com
+VLLM_SERVICE_PORT_B60=8086
+TP=1
+vLLM_ENDPOINT="http://${HOST_IP}:${VLLM_SERVICE_PORT_B60}"
+LLM_MODEL="Qwen/Qwen3-8B"
+VLLM_IMAGE_TAG="1.0"
+DP=1
+
+function build_docker_images() {
+    opea_branch=${opea_branch:-"main"}
+    cd $WORKPATH/docker_image_build
+    git clone --depth 1 --branch ${opea_branch} https://github.com/opea-project/GenAIComps.git
+    pushd GenAIComps
+    echo "GenAIComps test commit is $(git rev-parse HEAD)"
+    docker build --no-cache -t ${REGISTRY}/comps-base:${TAG} --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile .
+    popd && sleep 1s
+
+    echo "Pull intel/llm-scaler-vllm image"
+    docker pull intel/llm-scaler-vllm:${VLLM_IMAGE_TAG}
+
+    echo "Build all the images with --no-cache, check docker_image_build.log for details..."
+    docker compose -f build.yaml build --no-cache > ${LOG_PATH}/docker_image_build.log
+
+    docker images && sleep 1s
+}
+
+function start_services() {
+    cd $WORKPATH/docker_compose/intel/gpu/arc
+    source set_env.sh
+    # Start Docker Containers
+    docker compose -f $COMPOSE_FILE up -d > ${LOG_PATH}/start_services_with_compose.log
+    echo "ipex-serving-xpu is booting, please wait."
+    sleep 30s
+    n=0
+    until [[ "$n" -ge 100 ]]; do
+        docker logs ipex-serving-xpu-container > ${LOG_PATH}/ipex-serving-xpu-container.log 2>&1
+        if grep -q "Starting vLLM API server on http://0.0.0.0:" ${LOG_PATH}/ipex-serving-xpu-container.log; then
+            break
+        fi
+        sleep 6s
+        n=$((n+1))
+    done
+}
+
+function validate_services() {
+    local URL="$1"
+    local EXPECTED_RESULT="$2"
+    local SERVICE_NAME="$3"
+    local DOCKER_NAME="$4"
+    local INPUT_DATA="$5"
+
+    echo "[ $SERVICE_NAME ] Validating $SERVICE_NAME service..."
+    local RESPONSE=$(curl -s -w "%{http_code}" -o ${LOG_PATH}/${SERVICE_NAME}.log -X POST -d "$INPUT_DATA" -H 'Content-Type: application/json' "$URL")
+    while [ ! -f ${LOG_PATH}/${SERVICE_NAME}.log ]; do
+        sleep 1
+    done
+    local HTTP_STATUS="${RESPONSE: -3}"
+    local CONTENT=$(cat ${LOG_PATH}/${SERVICE_NAME}.log)
+
+    if [ "$HTTP_STATUS" -eq 200 ]; then
+        echo "[ $SERVICE_NAME ] HTTP status is 200. Checking content..."
+    else
+        echo "[ $SERVICE_NAME ] HTTP status is not 200. Received status was $HTTP_STATUS"
+        docker logs ${DOCKER_NAME} >> ${LOG_PATH}/${SERVICE_NAME}.log
+        exit 1
+    fi
+    sleep 1s
+}
+
+function validate_rag() {
+    cd $WORKPATH/tests
+
+    # setup pipeline
+    validate_services \
+        "${HOST_IP}:${EC_RAG_SERVICE_PORT}/v1/settings/pipelines" \
+        "active" \
+        "pipeline" \
+        "edgecraftrag-server" \
+        '@configs/test_pipeline_ipex_vllm.json'
+
+    # add data
+    validate_services \
+        "${HOST_IP}:${EC_RAG_SERVICE_PORT}/v1/data" \
+        "Done" \
+        "data" \
+        "edgecraftrag-server" \
+        '@configs/test_data.json'
+
+    # query
+    validate_services \
+        "${HOST_IP}:${EC_RAG_SERVICE_PORT}/v1/chatqna" \
+        "1234567890" \
+        "query" \
+        "ipex-serving-xpu-container" \
+        '{"messages":"What is the test id?","max_tokens":5}'
+}
+
+function validate_megaservice() {
+    # Curl the Mega Service
+    validate_services \
+        "${HOST_IP}:16011/v1/chatqna" \
+        "1234567890" \
+        "query" \
+        "ipex-serving-xpu-container" \
+        '{"messages":"What is the test id?","max_tokens":5}'
+}
+
+function stop_docker() {
+    cd $WORKPATH/docker_compose/intel/gpu/arc
+    export MODEL_PATH="${HOME}/models"
+    docker compose -f $COMPOSE_FILE down
+}
+
+
+function main() {
+    mkdir -p $LOG_PATH
+
+    echo "::group::stop_docker"
+    stop_docker
+    echo "::endgroup::"
+
+    echo "::group::build_docker_images"
+    if [[ "$IMAGE_REPO" == "opea" ]]; then build_docker_images; fi
+    echo "::endgroup::"
+
+    echo "::group::start_services"
+    start_services
+    echo "::endgroup::"
+
+    echo "::group::validate_rag"
+    validate_rag
+    echo "::endgroup::"
+
+    echo "::group::validate_megaservice"
+    validate_megaservice
+    echo "::endgroup::"
+
+    echo "::group::stop_docker"
+    stop_docker
+    echo y | docker system prune
+    echo "::endgroup::"
+
+}
+
+main
diff --git a/EdgeCraftRAG/tools/quick_start.sh b/EdgeCraftRAG/tools/quick_start.sh
index fdefa797f0..27525d1f97 100755
--- a/EdgeCraftRAG/tools/quick_start.sh
+++ b/EdgeCraftRAG/tools/quick_start.sh
@@ -5,6 +5,8 @@
 set -e
 
 WORKPATH=$(dirname "$(pwd)")
+ip_address=$(hostname -I | awk '{print $1}')
+HOST_IP=$ip_address
 
 get_user_input() {
     local var_name=$1
@@ -32,7 +34,7 @@ function start_vllm_services() {
     MILVUS_ENABLED=$(get_enable_function "MILVUS DB(Enter 1 for enable)" "0")
     CHAT_HISTORY_ROUND=$(get_user_input "chat history round" "0")
     LLM_MODEL=$(get_user_input "your LLM model" "Qwen/Qwen3-8B")
-    MODEL_PATH=$(get_user_input "your model path" "${HOME}/models")
+    MODEL_PATH=$(get_user_input "your model path" "${PWD}/models")
     read -p "Have you prepare models in ${MODEL_PATH}:(yes/no) [yes]" user_input
     user_input=${user_input:-"yes"}
 
@@ -63,14 +65,20 @@ function start_vllm_services() {
     # vllm ENV
     export NGINX_PORT=8086
     export vLLM_ENDPOINT="http://${HOST_IP}:${NGINX_PORT}"
-    TENSOR_PARALLEL_SIZE=$(get_user_input "your tp size" 1)
-    read -p "selected GPU [$(seq -s, 0 $((TENSOR_PARALLEL_SIZE - 1)))] " SELECTED_XPU_0; SELECTED_XPU_0=${SELECTED_XPU_0:-$(seq -s, 0 $((TENSOR_PARALLEL_SIZE - 1)))}
-    DP_NUM=$(get_user_input "DP number(how many containers to run vLLM)" 1)
-    for (( x=0; x<DP_NUM; x++ ))
-    do
+    read -p "DP number(how many containers to run vLLM) [1] , press Enter to confirm, or type a new value:" DP_NUM; DP_NUM=${DP_NUM:-1}
+    read -p "Tensor parallel size(your tp size [1]), press Enter to confirm, or type a new value:" TENSOR_PARALLEL_SIZE; TENSOR_PARALLEL_SIZE=${TENSOR_PARALLEL_SIZE:-1}
+
+    for (( x=0; x<DP_NUM; x++ )); do
+        start_gpu=$(( x * TENSOR_PARALLEL_SIZE ))
+        default_gpu_list=$(seq -s, $start_gpu $(( start_gpu + TENSOR_PARALLEL_SIZE - 1 )))
+
+        read -p "selected XPU(your selected_XPU_${x} [${default_gpu_list}]) , press Enter to confirm, or type a new value:" input_gpu_list
+        selected_gpu_list=${input_gpu_list:-$default_gpu_list}
+
+        export SELECTED_XPU_${x}="$selected_gpu_list"
         export VLLM_SERVICE_PORT_${x}="8$((x+1))00"
-        export SELECTED_XPU_${x}=$x
     done
+    CCL_DG2_USM=$(get_user_input "Set USM (Core=1, Xeon=0, default=0)" 0)
     export HOST_IP=${HOST_IP}
     export VLLM_SERVICE_PORT_0=8100
     # export ENV
@@ -84,6 +92,9 @@ function start_vllm_services() {
     export CHAT_HISTORY_ROUND=${CHAT_HISTORY_ROUND}
     export SELECTED_XPU_0=${SELECTED_XPU_0}
     export TENSOR_PARALLEL_SIZE=${TENSOR_PARALLEL_SIZE}
+    export CCL_DG2_USM=${CCL_DG2_USM}
+    export VIDEOGROUPID=$(getent group video | cut -d: -f3)
+    export RENDERGROUPID=$(getent group render | cut -d: -f3)
 
     bash $WORKPATH/nginx/nginx-conf-generator.sh $DP_NUM $WORKPATH/nginx/nginx.conf
     export NGINX_CONFIG_PATH="${WORKPATH}/nginx/nginx.conf"
@@ -118,7 +129,7 @@ function start_services() {
     MILVUS_ENABLED=$(get_enable_function "MILVUS DB(Enter 1 for enable)" "0")
     CHAT_HISTORY_ROUND=$(get_user_input "chat history round" "0")
     LLM_MODEL=$(get_user_input "your LLM model" "Qwen/Qwen3-8B")
-    MODEL_PATH=$(get_user_input "your model path" "${HOME}/models")
+    MODEL_PATH=$(get_user_input "your model path" "${PWD}/models")
     read -p "Have you prepare models in ${MODEL_PATH}:(yes/no) [yes]" user_input
     user_input=${user_input:-"yes"}
 
@@ -163,6 +174,8 @@ function start_services() {
     export no_proxy="localhost, 127.0.0.1, 192.168.1.1, ${HOST_IP}"
     export MILVUS_ENABLED=${MILVUS_ENABLED}
     export CHAT_HISTORY_ROUND=${CHAT_HISTORY_ROUND}
+    export VIDEOGROUPID=$(getent group video | cut -d: -f3)
+    export RENDERGROUPID=$(getent group render | cut -d: -f3)
 
     # Start Docker Containers
     COMPOSE_FILE="compose.yaml"
@@ -170,14 +183,279 @@ function start_services() {
     docker compose -f $WORKPATH/docker_compose/intel/gpu/arc/$COMPOSE_FILE up -d
 }
 
-function main {
-    read -p "Do you want to start vLLM or local OpenVINO services? (vLLM/ov) [vLLM]: " user_input
-    user_input=${user_input:-"vLLM"}
 
-    if [ "$user_input" == "vLLM" ]; then
-        start_vllm_services
+function check_baai_folder() {
+    local baai_path="${MODEL_PATH}/BAAI"
+
+    if [ -d "${baai_path}" ]; then
+        return 0
+    else
+        echo "Error: BAAI folder not found in ${MODEL_PATH}!"
+        echo "Please prepare the models first, then run quick_start_ov_services again."
+        exit 1
+    fi
+}
+
+
+function quick_start_vllm_services() {
+    WORKPATH=$(dirname "$PWD")
+    COMPOSE_FILE="compose_vllm.yaml"
+    EC_RAG_SERVICE_PORT=16010
+    docker compose -f $WORKPATH/docker_compose/intel/gpu/arc/$COMPOSE_FILE down
+
+    export HOST_IP=${HOST_IP:-"${ip_address}"}
+    export MODEL_PATH=${MODEL_PATH:-"${PWD}/models"}
+    export DOC_PATH=${DOC_PATH:-"$WORKPATH/tests"}
+    export TMPFILE_PATH=${TMPFILE_PATH:-"$WORKPATH/tests"}
+    export DP_NUM=${DP_NUM:-1}
+    export MILVUS_ENABLED=${MILVUS_ENABLED:-1}
+    export CHAT_HISTORY_ROUND=${CHAT_HISTORY_ROUND:-2}
+    export HF_ENDPOINT=${HF_ENDPOINT:-https://hf-mirror.com}
+    export NGINX_PORT=${NGINX_PORT:-8086}
+    export NGINX_PORT_0=${NGINX_PORT_0:-8100}
+    export VLLM_SERVICE_PORT_0=${VLLM_SERVICE_PORT_0:-8100}
+    export TENSOR_PARALLEL_SIZE=${TENSOR_PARALLEL_SIZE:-1}
+    export SELECTED_XPU_0=${SELECTED_XPU_0:-0}
+    export MAX_NUM_SEQS=${MAX_NUM_SEQS:-64}
+    export MAX_NUM_BATCHED_TOKENS=${MAX_NUM_BATCHED_TOKENS:-4000}
+    export MAX_MODEL_LEN=${MAX_MODEL_LEN:-3000}
+    export LOAD_IN_LOW_BIT=${LOAD_IN_LOW_BIT:-fp8}
+    export CCL_DG2_USM=${CCL_DG2_USM:-0}
+    export vLLM_ENDPOINT=${vLLM_ENDPOINT:-"http://${HOST_IP}:${NGINX_PORT}"}
+    export LLM_MODEL=${LLM_MODEL:-Qwen/Qwen3-8B}
+    export LLM_MODEL_PATH=${LLM_MODEL_PATH:-"${MODEL_PATH}/Qwen/Qwen3-8B"}
+    export VIDEOGROUPID=$(getent group video | cut -d: -f3)
+    export RENDERGROUPID=$(getent group render | cut -d: -f3)
+
+    check_baai_folder
+    export HF_CACHE=${HF_CACHE:-"${HOME}/.cache"}
+    export no_proxy="localhost, 127.0.0.1, 192.168.1.1, ${HOST_IP}"
+    if [ ! -d "${HF_CACHE}" ]; then
+        mkdir -p "${HF_CACHE}"
+        echo "Created directory: ${HF_CACHE}"
+    fi
+    sudo chown -R 1000:1000 ${MODEL_PATH} ${DOC_PATH} ${TMPFILE_PATH}
+    sudo chown -R 1000:1000 ${HF_CACHE}
+    cd $WORKPATH/docker_compose/intel/gpu/arc
+    bash $WORKPATH/nginx/nginx-conf-generator.sh $DP_NUM $WORKPATH/nginx/nginx.conf
+    export NGINX_CONFIG_PATH=${NGINX_CONFIG_PATH:-"$WORKPATH/nginx/nginx.conf"}
+
+    bash $WORKPATH/docker_compose/intel/gpu/arc/multi-arc-yaml-generator.sh $DP_NUM $WORKPATH/docker_compose/intel/gpu/arc/$COMPOSE_FILE
+    docker compose -f $WORKPATH/docker_compose/intel/gpu/arc/$COMPOSE_FILE up -d
+    echo "ipex-llm-serving-xpu is booting, please wait..."
+    n=0
+    until [[ "$n" -ge 100 ]]; do
+        docker logs ipex-llm-serving-xpu-container-0 > ipex-llm-serving-xpu-container.log 2>&1
+        if grep -q "Starting vLLM API server on http://0.0.0.0:" ipex-llm-serving-xpu-container.log; then
+            break
+        fi
+        sleep 6s
+        n=$((n+1))
+    done
+    rm -rf ipex-llm-serving-xpu-container.log
+    echo "service launched, please visit UI at ${HOST_IP}:8082"
+}
+
+
+function quick_start_ov_services() {
+    COMPOSE_FILE="compose.yaml"
+    echo "stop former service..."
+    docker compose -f $WORKPATH/docker_compose/intel/gpu/arc/$COMPOSE_FILE down
+
+    ip_address=$(hostname -I | awk '{print $1}')
+    export HOST_IP=${HOST_IP:-"${ip_address}"}
+    export DOC_PATH=${DOC_PATH:-"$WORKPATH/tests"}
+    export TMPFILE_PATH=${TMPFILE_PATH:-"$WORKPATH/tests"}
+    export MILVUS_ENABLED=${MILVUS_ENABLED:-1}
+    export CHAT_HISTORY_ROUND=${CHAT_HISTORY_ROUND:-"0"}
+    export LLM_MODEL=${LLM_MODEL:-"Qwen/Qwen3-8B"}
+    export MODEL_PATH=${MODEL_PATH:-"${HOME}/models"}
+    export VIDEOGROUPID=$(getent group video | cut -d: -f3)
+    export RENDERGROUPID=$(getent group render | cut -d: -f3)
+
+    check_baai_folder
+    export HF_CACHE=${HF_CACHE:-"${HOME}/.cache"}
+    if [ ! -d "${HF_CACHE}" ]; then
+        mkdir -p "${HF_CACHE}"
+        echo "Created directory: ${HF_CACHE}"
+    fi
+
+    sudo chown 1000:1000 "${MODEL_PATH}" "${DOC_PATH}" "${TMPFILE_PATH}"
+    sudo chown -R 1000:1000 "${HF_CACHE}"
+    export HF_ENDPOINT=${HF_ENDPOINT:-"https://hf-mirror.com"}
+    export no_proxy="localhost, 127.0.0.1, 192.168.1.1, ${HOST_IP}"
+    export CCL_DG2_USM=${CCL_DG2_USM:-0}
+
+    echo "Starting service..."
+    docker compose -f "$WORKPATH/docker_compose/intel/gpu/arc/$COMPOSE_FILE" up -d
+}
+
+
+function start_vLLM_B60_services() {
+    COMPOSE_FILE="compose_vllm_b60.yaml"
+    echo "stop former service..."
+    docker compose -f $WORKPATH/docker_compose/intel/gpu/arc/$COMPOSE_FILE down
+
+    ip_address=$(hostname -I | awk '{print $1}')
+    HOST_IP=$(get_user_input "host ip" "${ip_address}")
+    DOC_PATH=$(get_user_input "DOC_PATH" "$WORKPATH/tests")
+    TMPFILE_PATH=$(get_user_input "TMPFILE_PATH" "$WORKPATH/tests")
+    MILVUS_ENABLED=$(get_enable_function "MILVUS DB(Enter 1 for enable)" "0")
+    CHAT_HISTORY_ROUND=$(get_user_input "chat history round" "0")
+    LLM_MODEL=$(get_user_input "your LLM model" "Qwen/Qwen3-72B")
+    MODEL_PATH=$(get_user_input "your model path" "${PWD}/models")
+    read -p "Have you prepare models in ${MODEL_PATH}:(yes/no) [yes]" user_input
+    user_input=${user_input:-"yes"}
+
+    if [ "$user_input" == "yes" ]; then
+        # 模型文件路径请参考以下形式存放， llm为huggingface
+        # Indexer: ${MODEL_PATH}/BAAI/bge-small-en-v1.5
+        # Reranker: ${MODEL_PATH}/BAAI/bge-reranker-large
+        # llm :${MODEL_PATH}/${LLM_MODEL} (从huggingface或modelscope下载的原始模型，而不是经过OpenVINO转换的模型!)
+        echo "you skipped model downloading, please make sure you have prepared all models under ${MODEL_PATH}"
+    else
+        echo "you have not prepare models, starting to download models into ${MODEL_PATH}..."
+        mkdir -p $MODEL_PATH
+        pip install --upgrade --upgrade-strategy eager "optimum[openvino]"
+        optimum-cli export openvino -m BAAI/bge-small-en-v1.5 ${MODEL_PATH}/BAAI/bge-small-en-v1.5 --task sentence-similarity
+        optimum-cli export openvino -m BAAI/bge-reranker-large ${MODEL_PATH}/BAAI/bge-reranker-large --task text-classification
+        pip install -U huggingface_hub
+        huggingface-cli download $LLM_MODEL --local-dir "${MODEL_PATH}/${LLM_MODEL}"
+    fi
+    echo "give permission to related path..."
+    sudo chown 1000:1000 ${MODEL_PATH} ${DOC_PATH} ${TMPFILE_PATH}
+    # vllm ENV
+    export VLLM_SERVICE_PORT_B60=8086
+    export vLLM_ENDPOINT="http://${HOST_IP}:${VLLM_SERVICE_PORT_B60}"
+    read -p "DP number(how many containers to run B60_vLLM) [4] , press Enter to confirm, or type a new value:" DP; DP=${DP:-4}
+    read -p "Tensor parallel size(your tp size [1]), press Enter to confirm, or type a new value:" TP; TP=${TP:-1}
+    DTYPE=$(get_user_input "DTYPE (vLLM data type, e.g. float16/bfloat16)" "float16")
+    ZE_AFFINITY_MASK=$(get_user_input "ZE_AFFINITY_MASK (GPU affinity mask, multi-GPU use 0,1,2...)" "0,1,2,3")
+    ENFORCE_EAGER=$(get_user_input "ENFORCE_EAGER (enable eager execution, 1=enable/0=disable)" "1")
+    TRUST_REMOTE_CODE=$(get_user_input "TRUST_REMOTE_CODE (trust remote code for custom models, 1=enable/0=disable)" "1")
+    DISABLE_SLIDING_WINDOW=$(get_user_input "DISABLE_SLIDING_WINDOW (disable sliding window attention, 1=disable/0=enable)" "1")
+    GPU_MEMORY_UTIL=$(get_user_input "GPU_MEMORY_UTIL (GPU memory utilization, range 0.1-1.0)" "0.8")
+    NO_ENABLE_PREFIX_CACHING=$(get_user_input "NO_ENABLE_PREFIX_CACHING (disable prefix caching, 1=disable/0=enable)" "1")
+    MAX_NUM_BATCHED_TOKENS=$(get_user_input "MAX_NUM_BATCHED_TOKENS (max number of batched tokens)" "8192")
+    DISABLE_LOG_REQUESTS=$(get_user_input "DISABLE_LOG_REQUESTS (disable request logs, 1=disable/0=enable)" "1")
+    MAX_MODEL_LEN=$(get_user_input "MAX_MODEL_LEN (max model context length, e.g. 49152/10240)" "49152")
+    BLOCK_SIZE=$(get_user_input "BLOCK_SIZE (vLLM block size)" "64")
+    QUANTIZATION=$(get_user_input "QUANTIZATION (model quantization method, e.g. fp8/int4)" "fp8")
+    # export ENV
+    export MODEL_PATH=${MODEL_PATH}
+    export DOC_PATH=${DOC_PATH}
+    export TMPFILE_PATH=${TMPFILE_PATH}
+    export LLM_MODEL=${LLM_MODEL}
+    export no_proxy="localhost, 127.0.0.1, 192.168.1.1, ${HOST_IP}"
+    export MILVUS_ENABLED=${MILVUS_ENABLED}
+    export CHAT_HISTORY_ROUND=${CHAT_HISTORY_ROUND}
+    export SELECTED_XPU_0=${SELECTED_XPU_0}
+    export VIDEOGROUPID=$(getent group video | cut -d: -f3)
+    export RENDERGROUPID=$(getent group render | cut -d: -f3)
+    # export vllm ENV
+    export DP=${DP}
+    export TP=${TP}
+    export DTYPE=${DTYPE}
+    export ZE_AFFINITY_MASK=${ZE_AFFINITY_MASK}
+    export ENFORCE_EAGER=${ENFORCE_EAGER}
+    export TRUST_REMOTE_CODE=${TRUST_REMOTE_CODE}
+    export DISABLE_SLIDING_WINDOW=${DISABLE_SLIDING_WINDOW}
+    export GPU_MEMORY_UTIL=${GPU_MEMORY_UTIL}
+    export NO_ENABLE_PREFIX_CACHING=${NO_ENABLE_PREFIX_CACHING}
+    export MAX_NUM_BATCHED_TOKENS=${MAX_NUM_BATCHED_TOKENS}
+    export DISABLE_LOG_REQUESTS=${DISABLE_LOG_REQUESTS}
+    export MAX_MODEL_LEN=${MAX_MODEL_LEN}
+    export BLOCK_SIZE=${BLOCK_SIZE}
+    export QUANTIZATION=${QUANTIZATION}
+
+    # Start Docker Containers
+    docker compose -f $WORKPATH/docker_compose/intel/gpu/arc/$COMPOSE_FILE up -d
+    echo "ipex-llm-serving-xpu is booting, please wait..."
+    n=0
+    until [[ "$n" -ge 100 ]]; do
+        docker logs ipex-llm-serving-xpu-container-0 > ipex-llm-serving-xpu-container.log 2>&1
+        if grep -q "Starting vLLM API server on http://0.0.0.0:" ipex-llm-serving-xpu-container.log; then
+            break
+        fi
+        sleep 6s
+        n=$((n+1))
+    done
+    rm -rf ipex-llm-serving-xpu-container.log
+    echo "service launched, please visit UI at ${HOST_IP}:8082"
+}
+
+
+function quick_start_vllm_B60_services() {
+    WORKPATH=$(dirname "$PWD")
+    COMPOSE_FILE="compose_vllm_b60.yaml"
+    EC_RAG_SERVICE_PORT=16010
+    docker compose -f $WORKPATH/docker_compose/intel/gpu/arc/$COMPOSE_FILE down
+
+    export HOST_IP=${HOST_IP:-"${ip_address}"}
+    export MODEL_PATH=${MODEL_PATH:-"${PWD}/models"}
+    export DOC_PATH=${DOC_PATH:-"$WORKPATH/tests"}
+    export TMPFILE_PATH=${TMPFILE_PATH:-"$WORKPATH/tests"}
+    export MILVUS_ENABLED=${MILVUS_ENABLED:-1}
+    export CHAT_HISTORY_ROUND=${CHAT_HISTORY_ROUND:-2}
+    export LLM_MODEL=${LLM_MODEL:-Qwen/Qwen3-72B}
+    export VIDEOGROUPID=$(getent group video | cut -d: -f3)
+    export RENDERGROUPID=$(getent group render | cut -d: -f3)
+    # export vllm ENV
+    export DP=${DP:-4}
+    export TP=${TP:-1}
+    export DTYPE=${DTYPE:-float16}
+    export ZE_AFFINITY_MASK=${ZE_AFFINITY_MASK:-0,1,2,3}
+    export ENFORCE_EAGER=${ENFORCE_EAGER:-1}
+    export TRUST_REMOTE_CODE=${TRUST_REMOTE_CODE:-1}
+    export DISABLE_SLIDING_WINDOW=${DISABLE_SLIDING_WINDOW:-1}
+    export GPU_MEMORY_UTIL=${GPU_MEMORY_UTIL:-0.8}
+    export NO_ENABLE_PREFIX_CACHING=${NO_ENABLE_PREFIX_CACHING:-1}
+    export MAX_NUM_BATCHED_TOKENS=${MAX_NUM_BATCHED_TOKENS:-8192}
+    export DISABLE_LOG_REQUESTS=${disable_LOG_REQUESTS:-1}
+    export MAX_MODEL_LEN=${MAX_MODEL_LEN:-49152}
+    export BLOCK_SIZE=${BLOCK_SIZE:-64}
+    export QUANTIZATION=${QUANTIZATION:-fp8}
+
+
+    check_baai_folder
+    export no_proxy="localhost, 127.0.0.1, 192.168.1.1, ${HOST_IP}"
+    sudo chown -R 1000:1000 ${MODEL_PATH} ${DOC_PATH} ${TMPFILE_PATH}
+    docker compose -f $WORKPATH/docker_compose/intel/gpu/arc/$COMPOSE_FILE up -d
+    echo "ipex-llm-serving-xpu is booting, please wait..."
+    n=0
+    until [[ "$n" -ge 100 ]]; do
+        docker logs ipex-llm-serving-xpu-container-0 > ipex-llm-serving-xpu-container.log 2>&1
+        if grep -q "Starting vLLM API server on http://0.0.0.0:" ipex-llm-serving-xpu-container.log; then
+            break
+        fi
+        sleep 6s
+        n=$((n+1))
+    done
+    rm -rf ipex-llm-serving-xpu-container.log
+    echo "service launched, please visit UI at ${HOST_IP}:8082"
+}
+
+
+function main {
+    if [[ $- == *i* ]]; then
+        read -p "Do you want to start vLLM or local OpenVINO services? (vLLM_A770/vLLM_B60/ov) [vLLM_A770]: " user_input
+        user_input=${user_input:-"vLLM_A770"}
+        if [[ "$user_input" == "vLLM_A770" ]]; then
+            start_vllm_services
+        elif [[ "$user_input" == "vLLM_B60" ]]; then
+            start_vLLM_B60_services
+        else
+            start_services
+        fi
     else
-        start_services
+        export SERVICE_TYPE=${SERVICE_TYPE:-"vLLM_A770"}
+        if [[ "$SERVICE_TYPE" == "vLLM_A770" || "$SERVICE_TYPE" == "vLLM" ]]; then
+            quick_start_vllm_services
+        elif [[ "$SERVICE_TYPE" == "vLLM_B60" || "$SERVICE_TYPE" == "vLLM_b60" ]]; then
+            quick_start_vllm_B60_services
+        else
+            quick_start_ov_services
+        fi
     fi
 }
 
diff --git a/EdgeCraftRAG/ui/vue/.env.development b/EdgeCraftRAG/ui/vue/.env.development
index d7ef344a8a..ea6834f8a0 100644
--- a/EdgeCraftRAG/ui/vue/.env.development
+++ b/EdgeCraftRAG/ui/vue/.env.development
@@ -2,5 +2,5 @@
 ENV = development
 
 # Local Api
-VITE_API_URL = http://10.67.106.238:16010/
-VITE_CHATBOT_URL = http://10.67.106.238:16011/
+VITE_API_URL = /
+VITE_CHATBOT_URL = /
diff --git a/EdgeCraftRAG/ui/vue/components.d.ts b/EdgeCraftRAG/ui/vue/components.d.ts
index 7959bda79a..599bc31cb8 100644
--- a/EdgeCraftRAG/ui/vue/components.d.ts
+++ b/EdgeCraftRAG/ui/vue/components.d.ts
@@ -45,6 +45,7 @@ declare module 'vue' {
     ASelectOption: typeof import('ant-design-vue/es')['SelectOption']
     ASlider: typeof import('ant-design-vue/es')['Slider']
     ASpace: typeof import('ant-design-vue/es')['Space']
+    ASpin: typeof import('ant-design-vue/es')['Spin']
     ASteps: typeof import('ant-design-vue/es')['Steps']
     ATable: typeof import('ant-design-vue/es')['Table']
     ATag: typeof import('ant-design-vue/es')['Tag']
@@ -52,6 +53,7 @@ declare module 'vue' {
     ATooltip: typeof import('ant-design-vue/es')['Tooltip']
     AUploadDragger: typeof import('ant-design-vue/es')['UploadDragger']
     FormTooltip: typeof import('./src/components/FormTooltip.vue')['default']
+    PartialLoading: typeof import('./src/components/PartialLoading.vue')['default']
     RouterLink: typeof import('vue-router')['RouterLink']
     RouterView: typeof import('vue-router')['RouterView']
     SvgIcon: typeof import('./src/components/SvgIcon.vue')['default']
diff --git a/EdgeCraftRAG/ui/vue/index.html b/EdgeCraftRAG/ui/vue/index.html
index df137679ef..c871332d3c 100644
--- a/EdgeCraftRAG/ui/vue/index.html
+++ b/EdgeCraftRAG/ui/vue/index.html
@@ -9,6 +9,7 @@
     <meta charset="UTF-8" />
     <link rel="icon" type="image/svg+xml" href="" />
     <link rel="icon" href="/favicon.ico" />
+    <!-- <link rel="stylesheet" crossOrigin="anonymous" href="//at.alicdn.com/t/c/font_4784207_cnvru5uhdoq.css" /> -->
     <meta name="viewport" content="width=device-width, initial-scale=1.0" />
     <title>Edge Craft RAG based Q&A Chatbot</title>
   </head>
diff --git a/EdgeCraftRAG/ui/vue/nginx.conf b/EdgeCraftRAG/ui/vue/nginx.conf
index 6d9a233bf8..8b6701e78a 100644
--- a/EdgeCraftRAG/ui/vue/nginx.conf
+++ b/EdgeCraftRAG/ui/vue/nginx.conf
@@ -28,7 +28,7 @@ http {
             proxy_pass http://edgecraftrag-server:16010;
             proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
             proxy_http_version 1.1;
-            proxy_read_timeout 180s;
+            proxy_read_timeout 600s;
             proxy_set_header Connection "";
         }
 
diff --git a/EdgeCraftRAG/ui/vue/package.json b/EdgeCraftRAG/ui/vue/package.json
index 516e870406..d56e123754 100644
--- a/EdgeCraftRAG/ui/vue/package.json
+++ b/EdgeCraftRAG/ui/vue/package.json
@@ -9,7 +9,6 @@
     "preview": "vite preview"
   },
   "dependencies": {
-    "@vueuse/i18n": "^4.0.0-beta.12",
     "ant-design-vue": "^4.0.0-rc.6",
     "axios": "^1.7.9",
     "clipboard": "^2.0.11",
diff --git a/EdgeCraftRAG/ui/vue/src/api/chatbot/index.ts b/EdgeCraftRAG/ui/vue/src/api/chatbot/index.ts
index f7946ad72d..e8981e0f9a 100644
--- a/EdgeCraftRAG/ui/vue/src/api/chatbot/index.ts
+++ b/EdgeCraftRAG/ui/vue/src/api/chatbot/index.ts
@@ -21,9 +21,16 @@ export const requestChatbotConfig = (data: Object) => {
   });
 };
 
-export const getBenchmark = (name: String) => {
+export const getBenchmark = () => {
   return request({
-    url: `/v1/settings/pipelines/${name}/benchmark`,
+    url: `/v1/settings/pipeline/benchmark`,
     method: "get",
   });
 };
+
+export const requestStopChat = () => {
+  return request({
+    url: `/v1/chatqna/stop`,
+    method: "post",
+  });
+};
diff --git a/EdgeCraftRAG/ui/vue/src/api/knowledgeBase/index.ts b/EdgeCraftRAG/ui/vue/src/api/knowledgeBase/index.ts
index bb7bc9a494..fe300d6b33 100644
--- a/EdgeCraftRAG/ui/vue/src/api/knowledgeBase/index.ts
+++ b/EdgeCraftRAG/ui/vue/src/api/knowledgeBase/index.ts
@@ -10,7 +10,7 @@ export const getKnowledgeBaseList = () => {
   });
 };
 
-export const getKnowledgeBaseDetialByName = (kbName: String) => {
+export const getKnowledgeBaseDetailByName = (kbName: String) => {
   return request({
     url: `/v1/knowledge/${kbName}`,
     method: "get",
@@ -54,15 +54,14 @@ export const requestKnowledgeBaseRelation = (kbName: String, data: Object) => {
     url: `/v1/knowledge/${kbName}/files`,
     method: "post",
     data,
-    showLoading: true,
     showSuccessMsg: true,
     successMsg: "request.knowledge.uploadSucc",
   });
 };
 
-export const requestFileDelete = (kbName: String, data: Object) => {
+export const requestFileDelete = (name: String, data: Object) => {
   return request({
-    url: `/v1/knowledge/${kbName}/files`,
+    url: `/v1/knowledge/${name}/files`,
     method: "delete",
     data,
     showLoading: true,
@@ -71,4 +70,86 @@ export const requestFileDelete = (kbName: String, data: Object) => {
   });
 };
 
+export const getExperienceList = () => {
+  return request({
+    url: "/v1/experiences",
+    method: "get",
+  });
+};
+
+export const requestExperienceCreate = (data: EmptyArrayType) => {
+  return request({
+    url: "/v1/multiple_experiences/check",
+    method: "post",
+    data,
+    showLoading: true,
+  });
+};
+export const requestExperienceConfirm = (flag: Boolean, data: EmptyArrayType) => {
+  return request({
+    url: `/v1/multiple_experiences/confirm?flag=${flag}`,
+    method: "post",
+    data,
+    showLoading: true,
+    showSuccessMsg: true,
+    successMsg: "request.experience.createSucc",
+  });
+};
+export const getExperienceDetailByName = (data: Object) => {
+  return request({
+    url: `/v1/experience`,
+    method: "post",
+    data,
+  });
+};
+
+export const requestExperienceUpdate = (data: Object) => {
+  return request({
+    url: `/v1/experiences`,
+    method: "patch",
+    data,
+    showLoading: true,
+    showSuccessMsg: true,
+    successMsg: "request.experience.updateSucc",
+  });
+};
+
+export const requestExperienceDelete = (data: Object) => {
+  return request({
+    url: `/v1/experiences`,
+    method: "delete",
+    data,
+    showLoading: true,
+    showSuccessMsg: true,
+    successMsg: "request.experience.deleteSucc",
+  });
+};
+
+export const requestExperienceRelation = (data: Object) => {
+  return request({
+    url: "/v1/experiences/files",
+    method: "post",
+    data,
+    showLoading: true,
+    showSuccessMsg: true,
+    successMsg: "experience.importSuccTip",
+  });
+};
+
+export const getkbadminList = () => {
+  return request({
+    url: "/v1/kbadmin/kbs_list",
+    method: "get",
+  });
+};
+
+export const requestUploadFileUrl = (kbName: String, data: Object) => {
+  return request({
+    url: `v1/data/file/${kbName}`,
+    method: "post",
+    data,
+    type: "files",
+  });
+};
+
 export const uploadFileUrl = `${import.meta.env.VITE_API_URL}v1/data/file/`;
diff --git a/EdgeCraftRAG/ui/vue/src/api/pipeline/index.ts b/EdgeCraftRAG/ui/vue/src/api/pipeline/index.ts
index fd06d1d3d8..335908b6c9 100644
--- a/EdgeCraftRAG/ui/vue/src/api/pipeline/index.ts
+++ b/EdgeCraftRAG/ui/vue/src/api/pipeline/index.ts
@@ -14,7 +14,6 @@ export const getPipelineList = () => {
   return request({
     url: "/v1/settings/pipelines",
     method: "get",
-    showLoading: true,
   });
 };
 
diff --git a/EdgeCraftRAG/ui/vue/src/api/request.ts b/EdgeCraftRAG/ui/vue/src/api/request.ts
index 91805dbab5..44f6cf2051 100644
--- a/EdgeCraftRAG/ui/vue/src/api/request.ts
+++ b/EdgeCraftRAG/ui/vue/src/api/request.ts
@@ -7,8 +7,6 @@ import axios, { AxiosInstance } from "axios";
 import qs from "qs";
 import i18n from "@/i18n";
 
-const antNotification = serviceManager.getService("antNotification");
-
 const service: AxiosInstance = axios.create({
   baseURL: import.meta.env.VITE_API_URL,
   timeout: 600000,
@@ -39,6 +37,8 @@ service.interceptors.response.use(
     if (NextLoading) NextLoading.done();
     const res = response.data;
     if (config.showSuccessMsg) {
+      const antNotification = serviceManager.getService("antNotification");
+
       if (antNotification)
         antNotification("success", i18n.global.t("common.success"), i18n.global.t(config.successMsg));
     }
@@ -55,6 +55,7 @@ service.interceptors.response.use(
     } else {
       errorMessage = error.message;
     }
+    const antNotification = serviceManager.getService("antNotification");
     if (antNotification) antNotification("error", i18n.global.t("common.error"), errorMessage);
 
     return Promise.reject(error);
diff --git a/EdgeCraftRAG/ui/vue/src/assets/iconFont/iconfont.css b/EdgeCraftRAG/ui/vue/src/assets/iconFont/iconfont.css
index dedd20b357..5163bc195e 100644
--- a/EdgeCraftRAG/ui/vue/src/assets/iconFont/iconfont.css
+++ b/EdgeCraftRAG/ui/vue/src/assets/iconFont/iconfont.css
@@ -1,9 +1,9 @@
 @font-face {
   font-family: "iconfont"; /* Project id 4784207 */
   src:
-    url("iconfont.woff2?t=1754038546130") format("woff2"),
-    url("iconfont.woff?t=1754038546130") format("woff"),
-    url("iconfont.ttf?t=1754038546130") format("truetype");
+    url("iconfont.woff2?t=1757469597873") format("woff2"),
+    url("iconfont.woff?t=1757469597873") format("woff"),
+    url("iconfont.ttf?t=1757469597873") format("truetype");
 }
 
 .iconfont {
@@ -14,6 +14,14 @@
   -moz-osx-font-smoothing: grayscale;
 }
 
+.icon-kb:before {
+  content: "\e639";
+}
+
+.icon-experience:before {
+  content: "\e68e";
+}
+
 .icon-deep-think:before {
   content: "\e772";
 }
diff --git a/EdgeCraftRAG/ui/vue/src/assets/iconFont/iconfont.js b/EdgeCraftRAG/ui/vue/src/assets/iconFont/iconfont.js
index f6731b5c1a..5e96151e2e 100644
--- a/EdgeCraftRAG/ui/vue/src/assets/iconFont/iconfont.js
+++ b/EdgeCraftRAG/ui/vue/src/assets/iconFont/iconfont.js
@@ -2,12 +2,12 @@
 // SPDX-License-Identifier: Apache-2.0
 
 (window._iconfont_svg_string_4784207 =
-  '<svg><symbol id="icon-deep-think" viewBox="0 0 1024 1024"><path d="M513.344 53.44l2.112 0.192a31.616 31.616 0 0 1 10.88 3.2c0.512 0.32 1.152 0.512 1.664 0.768l369.472 213.312 3.584 2.432a32 32 0 0 1 12.416 25.28v426.688a32 32 0 0 1-16 27.712L528 966.4a32.192 32.192 0 0 1-4.8 2.176c-0.128 0-0.32 0-0.448 0.128h-0.128v0.128h-0.256a32 32 0 0 1-4.288 1.152l-0.384 0.128-0.512 0.064-0.192 0.064a32.128 32.128 0 0 1-10.048 0h-0.192l-0.448-0.128-0.448-0.128a31.104 31.104 0 0 1-4.288-1.152h-0.192l-0.128-0.064-0.512-0.192a31.616 31.616 0 0 1-4.736-2.176l-369.472-213.376a32 32 0 0 1-16-27.712V298.624a32 32 0 0 1 16-27.712L496 57.6l3.84-1.856c0.512-0.256 1.152-0.32 1.728-0.512 1.472-0.512 2.944-1.088 4.544-1.344 0.832-0.192 1.664-0.192 2.56-0.256 1.088-0.128 2.176-0.32 3.328-0.32l1.344 0.128zM207.744 726.016l245.184 141.568-85.76-243.008-159.36 101.44z m363.264 141.568l245.12-141.568-159.36-101.44-85.76 243.008zM512 842.432L594.752 608H429.248L512 842.432zM174.528 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+  ((c) => {
     var l = (a = (a = document.getElementsByTagName("script"))[a.length - 1]).getAttribute("data-injectcss"),
       a = a.getAttribute("data-disable-injectsvg");
     if (!a) {
-      var c,
+      var h,
         t,
         i,
         o,
@@ -15,8 +15,8 @@
         m = function (l, a) {
           a.parentNode.insertBefore(l, a);
         };
-      if (l && !h.__iconfont__svg__cssinject__) {
-        h.__iconfont__svg__cssinject__ = !0;
+      if (l && !c.__iconfont__svg__cssinject__) {
+        c.__iconfont__svg__cssinject__ = !0;
         try {
           document.write(
             "<style>.svgfont {display: inline-block;width: 1em;height: 1em;fill: currentColor;vertical-align: -0.1em;font-size:16px;}</style>",
@@ -25,10 +25,10 @@
           console && console.log(l);
         }
       }
-      (c = function () {
+      (h = function () {
         var l,
           a = document.createElement("div");
-        (a.innerHTML = h._iconfont_svg_string_4784207),
+        (a.innerHTML = c._iconfont_svg_string_4784207),
           (a = a.getElementsByTagName("svg")[0]) &&
             (a.setAttribute("aria-hidden", "true"),
             (a.style.position = "absolute"),
@@ -40,14 +40,14 @@
       }),
         document.addEventListener
           ? ~["complete", "loaded", "interactive"].indexOf(document.readyState)
-            ? setTimeout(c, 0)
+            ? setTimeout(h, 0)
             : ((t = function () {
-                document.removeEventListener("DOMContentLoaded", t, !1), c();
+                document.removeEventListener("DOMContentLoaded", t, !1), h();
               }),
               document.addEventListener("DOMContentLoaded", t, !1))
           : document.attachEvent &&
-            ((i = c),
-            (o = h.document),
+            ((i = h),
+            (o = c.document),
             (v = !1),
             s(),
             (o.onreadystatechange = function () {
diff --git a/EdgeCraftRAG/ui/vue/src/assets/iconFont/iconfont.json b/EdgeCraftRAG/ui/vue/src/assets/iconFont/iconfont.json
index a8fea13f43..db90f79659 100644
--- a/EdgeCraftRAG/ui/vue/src/assets/iconFont/iconfont.json
+++ b/EdgeCraftRAG/ui/vue/src/assets/iconFont/iconfont.json
@@ -5,6 +5,20 @@
   "css_prefix_text": "icon-",
   "description": "",
   "glyphs": [
+    {
+      "icon_id": "687788",
+      "name": "知识库",
+      "font_class": "kb",
+      "unicode": "e639",
+      "unicode_decimal": 58937
+    },
+    {
+      "icon_id": "5299955",
+      "name": "experience",
+      "font_class": "experience",
+      "unicode": "e68e",
+      "unicode_decimal": 59022
+    },
     {
       "icon_id": "44419262",
       "name": "deep-think",
diff --git a/EdgeCraftRAG/ui/vue/src/assets/iconFont/iconfont.ttf b/EdgeCraftRAG/ui/vue/src/assets/iconFont/iconfont.ttf
index d49803ef9c..6f8585b8d5 100644
Binary files a/EdgeCraftRAG/ui/vue/src/assets/iconFont/iconfont.ttf and b/EdgeCraftRAG/ui/vue/src/assets/iconFont/iconfont.ttf differ
diff --git a/EdgeCraftRAG/ui/vue/src/assets/iconFont/iconfont.woff b/EdgeCraftRAG/ui/vue/src/assets/iconFont/iconfont.woff
index e9b153a7f5..9e3764205e 100644
Binary files a/EdgeCraftRAG/ui/vue/src/assets/iconFont/iconfont.woff and b/EdgeCraftRAG/ui/vue/src/assets/iconFont/iconfont.woff differ
diff --git a/EdgeCraftRAG/ui/vue/src/assets/iconFont/iconfont.woff2 b/EdgeCraftRAG/ui/vue/src/assets/iconFont/iconfont.woff2
index 1f66b46dff..63a303beba 100644
Binary files a/EdgeCraftRAG/ui/vue/src/assets/iconFont/iconfont.woff2 and b/EdgeCraftRAG/ui/vue/src/assets/iconFont/iconfont.woff2 differ
diff --git a/EdgeCraftRAG/ui/vue/src/components.d.ts b/EdgeCraftRAG/ui/vue/src/components.d.ts
index f79d1e1d69..35e756d199 100644
--- a/EdgeCraftRAG/ui/vue/src/components.d.ts
+++ b/EdgeCraftRAG/ui/vue/src/components.d.ts
@@ -10,11 +10,51 @@ export {};
 /* prettier-ignore */
 declare module 'vue' {
   export interface GlobalComponents {
+    AAffix: typeof import('ant-design-vue/es')['Affix']
     AButton: typeof import('ant-design-vue/es')['Button']
+    ACheckbox: typeof import('ant-design-vue/es')['Checkbox']
+    ACheckboxGroup: typeof import('ant-design-vue/es')['CheckboxGroup']
+    ACol: typeof import('ant-design-vue/es')['Col']
+    ACollapse: typeof import('ant-design-vue/es')['Collapse']
+    ACollapsePanel: typeof import('ant-design-vue/es')['CollapsePanel']
+    AConfigProvider: typeof import('ant-design-vue/es')['ConfigProvider']
+    ADescriptions: typeof import('ant-design-vue/es')['Descriptions']
+    ADescriptionsItem: typeof import('ant-design-vue/es')['DescriptionsItem']
+    ADivider: typeof import('ant-design-vue/es')['Divider']
+    ADrawer: typeof import('ant-design-vue/es')['Drawer']
+    ADropdown: typeof import('ant-design-vue/es')['Dropdown']
+    AEmpty: typeof import('ant-design-vue/es')['Empty']
+    AForm: typeof import('ant-design-vue/es')['Form']
+    AFormItem: typeof import('ant-design-vue/es')['FormItem']
+    AImage: typeof import('ant-design-vue/es')['Image']
     AInput: typeof import('ant-design-vue/es')['Input']
+    AInputNumber: typeof import('ant-design-vue/es')['InputNumber']
     ALayout: typeof import('ant-design-vue/es')['Layout']
     ALayoutContent: typeof import('ant-design-vue/es')['LayoutContent']
+    ALayoutHeader: typeof import('ant-design-vue/es')['LayoutHeader']
+    ALayoutSider: typeof import('ant-design-vue/es')['LayoutSider']
+    AMenu: typeof import('ant-design-vue/es')['Menu']
+    AMenuItem: typeof import('ant-design-vue/es')['MenuItem']
+    AModal: typeof import('ant-design-vue/es')['Modal']
+    APagination: typeof import('ant-design-vue/es')['Pagination']
+    APopover: typeof import('ant-design-vue/es')['Popover']
+    ARadio: typeof import('ant-design-vue/es')['Radio']
+    ARadioGroup: typeof import('ant-design-vue/es')['RadioGroup']
+    ARow: typeof import('ant-design-vue/es')['Row']
+    ASelect: typeof import('ant-design-vue/es')['Select']
+    ASelectOption: typeof import('ant-design-vue/es')['SelectOption']
+    ASlider: typeof import('ant-design-vue/es')['Slider']
+    ASpace: typeof import('ant-design-vue/es')['Space']
+    ASteps: typeof import('ant-design-vue/es')['Steps']
+    ATable: typeof import('ant-design-vue/es')['Table']
+    ATag: typeof import('ant-design-vue/es')['Tag']
+    ATextarea: typeof import('ant-design-vue/es')['Textarea']
+    ATooltip: typeof import('ant-design-vue/es')['Tooltip']
+    AUploadDragger: typeof import('ant-design-vue/es')['UploadDragger']
+    FormTooltip: typeof import('./components/FormTooltip.vue')['default']
     RouterLink: typeof import('vue-router')['RouterLink']
     RouterView: typeof import('vue-router')['RouterView']
+    SvgIcon: typeof import('./components/SvgIcon.vue')['default']
+    TableColumns: typeof import('./components/TableColumns.vue')['default']
   }
 }
diff --git a/EdgeCraftRAG/ui/vue/src/components/PartialLoading.vue b/EdgeCraftRAG/ui/vue/src/components/PartialLoading.vue
new file mode 100644
index 0000000000..b744f43e11
--- /dev/null
+++ b/EdgeCraftRAG/ui/vue/src/components/PartialLoading.vue
@@ -0,0 +1,70 @@
+<template>
+  <div v-if="props.visible" class="loading-container">
+    <div class="loading-wrap">
+      <a-spin :size="size" />
+      <p
+        class="loading-title"
+        :style="{ fontSize: size === 'default' ? '14px' : '18px' }"
+      >
+        {{ title ? title : t("common.loading") }}...
+      </p>
+      <p class="loading-text" v-if="showDes">
+        {{ describe ? describe : t("common.waitTip") }}
+      </p>
+    </div>
+  </div>
+</template>
+
+<script setup lang="ts" name="TunerLoading">
+import { useI18n } from "vue-i18n";
+
+const { t } = useI18n();
+
+const props = defineProps({
+  visible: {
+    type: Boolean,
+    required: true,
+    default: false,
+  },
+  size: {
+    type: String,
+    default: "large",
+  },
+  title: {
+    type: String,
+    default: "",
+  },
+  describe: {
+    type: String,
+    default: "",
+  },
+  showDes: {
+    type: Boolean,
+    default: true,
+  },
+});
+</script>
+
+<style lang="less" scoped>
+.loading-container {
+  width: 100%;
+  height: 100%;
+  flex: 1;
+  .vertical-center;
+  .loading-wrap {
+    text-align: center;
+    padding: 24px;
+    .loading-title {
+      font-size: 18px;
+      line-height: 28px;
+      font-weight: 600;
+      color: var(--font-main-color);
+      margin: 8px auto;
+    }
+    .loading-text {
+      line-height: 20px;
+      color: var(--font-text-color);
+    }
+  }
+}
+</style>
diff --git a/EdgeCraftRAG/ui/vue/src/i18n/en.ts b/EdgeCraftRAG/ui/vue/src/i18n/en.ts
index 39d3cf0fa8..4c6ba3e7f3 100644
--- a/EdgeCraftRAG/ui/vue/src/i18n/en.ts
+++ b/EdgeCraftRAG/ui/vue/src/i18n/en.ts
@@ -27,6 +27,14 @@ export default {
     all: "All",
     reset: "Reset",
     uploadTip: "Click or drag file to this area to upload",
+    loading: "Loading",
+    waitTip: "Please wait patiently and do not refresh the page during this period.",
+    copy: "Copy",
+    send: "Send",
+    regenerate: "Regenerate",
+    copySucc: "Copy successful !",
+    copyError: "Copy failed !",
+    emptyText: "The content is empty !",
   },
   system: {
     title: "System Status",
@@ -85,10 +93,12 @@ export default {
       indexer: "Indexer",
       indexerType: "Indexer Type",
       embedding: "Embedding Model",
+      embeddingUrl: "Embedding URL",
       embeddingDevice: "Embedding run device",
       retriever: "Retriever",
       retrieverType: "Retriever Type",
       topk: "Search top k",
+      topn: "Top n",
       postProcessor: "PostProcessor",
       postProcessorType: "PostProcessor Type",
       rerank: "Rerank Model",
@@ -99,15 +109,17 @@ export default {
       language: "Large Language Model",
       llmDevice: "LLM run device",
       weights: "Weights",
-      local: "Local",
-      vllm: "Vllm",
-      vector_uri: "Vector Uri",
+      local: "Local (OpenVINO)",
+      vllm: "Remote (vLLM)",
+      vector_url: "Vector Database URL",
       modelName: "Model Name",
-      vllm_url: "Vllm Url",
+      vllm_url: "vLLM URL",
+      kbadmin: "kbadmin",
     },
     valid: {
       nameValid1: "Please input name",
       nameValid2: "Name should be between 2 and 30 characters",
+      nameValid3: "The name only supports letters, numbers, and underscores.",
       nodeParserType: "Please select Node Parser Type",
       chunkSizeValid1: "Please select Chunk Size",
       chunkSizeValid2: "The value of Chunk Size cannot be less than Chunk Overlap",
@@ -115,9 +127,11 @@ export default {
       chunkOverlapValid2: "The value of Chunk Overlap cannot be greater than Chunk Size",
       windowSize: "Please select Chunk Window Size",
       indexerType: "Please select Indexer Type",
-      embedding: "Please select Embedding Model",
+      embedding: "Please select embedding Model",
+      embeddingUrl: "IP : Port, (e.g. 192.168.1.1:13020)",
       embeddingDevice: "Please select Embedding run device",
       retrieverType: "Please select Retriever Type",
+      retrieverTypeFormat: "Retriever type can only select kbadmin",
       topk: "Please select Top k",
       postProcessorType: "Please select PostProcessor Type",
       rerank: "Please select Rerank Model",
@@ -126,14 +140,28 @@ export default {
       language: "Please select Large Language Model",
       llmDevice: "Please select LLM run device",
       weights: "Please select Weights",
-      vector_uri: "IP : Port, (e.g. 192.168.1.1:19530)",
+      kb_vector_url: "IP : Port, (e.g. 192.168.1.1:29530)",
+      vector_url: "IP : Port, (e.g. 192.168.1.1:19530)",
       vllm_url: "IP : Port, (e.g. 192.168.1.1:8086)",
-      urlValid1: "Please enter url",
+      urlValid1: "Please enter vector url",
       urlValid2: "Please enter the correct url",
       urlValid3: "URL cannot be accessed",
       urlValid4: "Test passed !",
       urlValid5: "The URL has not passed verification yet",
       modelName: "Please enter model name",
+      vllmUrlValid1: "Please enter vLLM url",
+      vllmUrlValid2: "Please enter the correct url",
+      vllmUrlValid3: "URL cannot be accessed",
+      vllmUrlValid4: "Test passed !",
+      vllmUrlValid5: "The URL has not passed verification yet",
+      nodeParserTypeTip: "Both Indexer Type and  Retriever Type will be set to kbadmin at the same time",
+      indexerTypeTip: "Both Node Parser Type and  Retriever Type will be set to kbadmin at the same time",
+      retrieverTypeTip: "Both Node Parser Type and  Indexer Type will be set to kbadmin at the same time",
+      retrieverChangeTip: "Please go to the Indexer stage to complete the data",
+      indexerTypeValid1: "Indexer type can only select kbadmin",
+      modelRequired: "Please enter embedding model url",
+      modelFormat: "Please enter the correct url",
+      retrieverValid: "Please return to the Indexer stage to supplement information.",
     },
     desc: {
       name: "The name identifier of the pipeline",
@@ -143,14 +171,15 @@ export default {
       windowSize: "The number of sentences on each side of a sentence to capture",
       indexerType: "The type of index structure responsible for building based on the parsed nodes",
       embedding: "Embed the text data to represent it and build a vector index",
-      embeddingDevice: "The device used by the Embedding Model",
+      embeddingUrl: "Connecting embedding model url",
+      embeddingDevice: "The device used by the embedding model",
       retrieverType:
-        "The retrieval type used when retrieving relevant nodes from the index according to the user's query",
+        "The retrieval type used when retrieving relevant nodes from the index according to the user's experience",
       topk: "The number of top k results to return",
       postProcessorType: "Select postprocessors for post-processing of the context",
       rerank: "Rerank Model",
       rerankDevice: "Rerank run device",
-      generatorType: "Local inference generator or vllm generator",
+      generatorType: "Local inference generator or vLLM generator",
       language: "The large model used for generating dialogues",
       llmDevice: "The device used by the  LLM",
       weights: "Model weight",
@@ -167,10 +196,11 @@ export default {
         "Sentence window node parser. Splits a document into Nodes, with each node being a sentence. Each node contains a window from the surrounding sentences in the metadata.",
       unstructured: "UnstructedNodeParser is a component that processes unstructured data.",
       milvusVector: "Embedding vectors stored in milvus",
-      vector_uri: "Connecting milvus uri",
+      vector_url: "Connecting milvus vector url",
       test: "Test",
-      modelName: "Vllm model name",
-      vllm_url: " Test if Vllm url is available ",
+      modelName: "vLLM model name",
+      vllm_url: " Test if vLLM url is available ",
+      kbadmin: "Third party knowledge base engine",
     },
   },
   generation: {
@@ -225,11 +255,28 @@ export default {
     activated: "Activated",
     nameValid1: "Please input knowledge base name",
     nameValid2: "Name should be between 2 and 30 characters",
-    nameValid3: "The name cannot start with a number",
+    nameValid3: "Alphanumeric and underscore only, starting with a letter or underscore.",
     desValid: "Please input knowledge base description",
     activeValid: "Please select whether to activate",
-    uploadValid: "Single file size not exceeding 50M.",
+    uploadValid: "Single file size not exceeding 200M.",
     deleteFileTip: "Are you sure delete this file?",
+    selectTitle: "Create Type Select",
+    selectDes: "Please select the type you want to create",
+    experience: "Experience",
+    experienceDes:
+      "Experience refers to the knowledge and skills acquired through practical involvement, trial, and reflection, serving as a key foundation for solving real-world problems.",
+    kbDes:
+      "A Knowledge Base is a centralized repository for storing organized information such as documents, FAQs, and guides, enabling teams or users to quickly access and share knowledge.",
+    type: "Type",
+    original: "Original",
+    kbadmin: "kbadmin",
+    typeValid: "Please select knowledge base type",
+    nameRequired: "Please select kbadmin name",
+    waitTip: "Please be patient and wait for the file upload to complete.",
+    done: "Finished",
+    successfully: "Successfully ",
+    failed: "Failed",
+    totalTip: "files",
   },
   request: {
     pipeline: {
@@ -248,9 +295,51 @@ export default {
       updateSucc: "Knowledge Base update successfully !",
       deleteSucc: "Knowledge Base deleted successfully !",
     },
+    experience: {
+      createSucc: "Experience created successfully!",
+      updateSucc: "Experience update successful!",
+      deleteSucc: "Experience deleted successfully!",
+    },
   },
   error: {
     notFoundTip: "Uh oh! It seems like you're lost",
     back: "Go Home",
   },
+  experience: {
+    create: "Create Experience",
+    edit: "Edit Experience",
+    import: "Import Experience",
+    fileFormatTip: "Supports JSON format, with file size not exceeding 100M.",
+    importSuccTip: "Files upload successful!",
+    importErrTip: "Files upload failed!",
+    uploadValid: "Single file size not exceeding 100M.",
+    experience: "Experience",
+    detail: "Detail",
+    operation: "Operation",
+    deleteTip: "Are you sure delete this experience?",
+    addExperience: "Add Experience",
+    delExperience: "Delete Experience",
+    addContent: "Add Content",
+    delContent: "Delete Content",
+    total: "Total experience: ",
+    unique: "Unique",
+    selectTip: "Please choose an appropriate method for data update",
+    cover: "Cover",
+    increase: "Append",
+    deactivateTip: "Are you sure deactivate this experience?",
+    activeTip: "Are you sure activate this experience?",
+    label: {
+      experience: "Experience",
+      contents: "Experience Content",
+      content: "Content",
+    },
+    placeholder: {
+      experience: "Please enter Experience",
+      content: "Please enter content",
+    },
+    valid: {
+      experience: "Experience cannot be empty",
+      content: "Content cannot be empty",
+    },
+  },
 };
diff --git a/EdgeCraftRAG/ui/vue/src/i18n/zh.ts b/EdgeCraftRAG/ui/vue/src/i18n/zh.ts
index 2a1a318851..24b810bdc4 100644
--- a/EdgeCraftRAG/ui/vue/src/i18n/zh.ts
+++ b/EdgeCraftRAG/ui/vue/src/i18n/zh.ts
@@ -27,6 +27,14 @@ export default {
     all: "全选",
     reset: "重置",
     uploadTip: "点击或将文件拖到此区域进行上传",
+    loading: "加载中",
+    waitTip: "请耐心等待，在此期间不要刷新页面。",
+    copy: "复制",
+    send: "发送",
+    regenerate: "重新生成",
+    copySucc: "复制成功！",
+    copyError: "复制失败！",
+    emptyText: "内容为空！",
   },
   system: {
     title: "系统状态",
@@ -84,10 +92,12 @@ export default {
       indexer: "索引器",
       indexerType: "索引器类型",
       embedding: "嵌入模型",
+      embeddingUrl: "嵌入模型地址",
       embeddingDevice: "模型运行设备",
       retriever: "检索器",
       retrieverType: "检索器类型",
       topk: "检索 top k",
+      topn: "Top n",
       postProcessor: "节点后处理器",
       postProcessorType: "节点后处理器类型",
       rerank: "重排模型",
@@ -98,15 +108,17 @@ export default {
       language: "语言大模型",
       llmDevice: "运行设备",
       weights: "权重",
-      local: "本地",
-      vllm: "Vllm",
-      vector_uri: "Vector Uri",
+      local: "本地（OpenVINO）",
+      vllm: "远程（vLLM）",
+      vector_url: "向量数据库地址",
       modelName: "模型名称",
-      vllm_url: "Vllm 地址",
+      vllm_url: "vLLM 地址",
+      kbadmin: "kbadmin",
     },
     valid: {
       nameValid1: "请输入名称",
       nameValid2: "请输入 2 到 30 个字符的名称",
+      nameValid3: "名称仅支持字母、数字和下划线",
       nodeParserType: "请选择节点解析器类型",
       chunkSizeValid1: "请选择分块大小",
       chunkSizeValid2: "分块大小的值不能小于分块重叠值",
@@ -115,8 +127,10 @@ export default {
       windowSize: "请选择句子上下文窗口大小",
       indexerType: "请选择索引器类型",
       embedding: "请选择嵌入模型",
+      embeddingUrl: "IP : 端口，(例如 192.168.1.1:13020)",
       embeddingDevice: "请选择嵌入模型运行设备",
       retrieverType: "请选择检索器类型",
+      retrieverTypeFormat: "检索器类型只能选择kbadmin",
       topk: "请选择Top k",
       postProcessorType: "请选择后处理器类型",
       rerank: "请选择重排模型",
@@ -125,14 +139,28 @@ export default {
       language: "请选择大语言模型",
       llmDevice: "请选择大语言模型运行设备",
       weights: "请选择模型权重",
-      vector_uri: "IP : 端口，(例如 192.168.1.1:19530)",
+      kb_vector_url: "IP : 端口，(例如 192.168.1.1:29530)",
+      vector_url: "IP : 端口，(例如 192.168.1.1:19530)",
       vllm_url: "IP : 端口，(例如 192.168.1.1:8086)",
-      urlValid1: "URL 不能为空",
-      urlValid2: "请输入正确的URL",
-      urlValid3: "URL无法访问",
+      urlValid1: "向量数据库地址不能为空",
+      urlValid2: "请输入正确的向量数据库地址",
+      urlValid3: "向量数据库地址无法访问",
       urlValid4: "测试通过！",
-      urlValid5: "URL还未通过校验",
+      urlValid5: "向量数据库地址还未通过校验",
       modelName: "请输入模型名称",
+      vllmUrlValid1: "vLLM地址不能为空",
+      vllmUrlValid2: "请输入正确的vLLM地址",
+      vllmUrlValid3: "vLLM地址无法访问",
+      vllmUrlValid4: "测试通过！",
+      vllmUrlValid5: "vLLM地址还未通过校验",
+      nodeParserTypeTip: "索引器类型和检索器类型将同时设置为kbadmin",
+      indexerTypeTip: "节点解析器类型和检索器类型将同时设置为kbadmin",
+      retrieverTypeTip: "索引器类型和节点解析器类型将同时设置为kbadmin",
+      retrieverChangeTip: "请前往索引器阶段补全数据",
+      indexerTypeValid1: "索引器类型只能选择kbadmin",
+      modelRequired: "请输入嵌入模型地址",
+      modelFormat: "请输入正确的模型地址",
+      retrieverValid: "请回到Indexer阶段补充信息",
     },
     desc: {
       name: "Pipeline的名称标识，用于区分不同工作流",
@@ -142,13 +170,14 @@ export default {
       windowSize: "每个节点捕获的上下文句子窗口大小，用于增强语义完整性",
       indexerType: "基于解析节点构建的索引结构类型",
       embedding: "将文本转换为向量表示的过程",
+      embeddingUrl: "嵌入模型地址",
       embeddingDevice: "执行嵌入模型推理的硬件设备（CPU/GPU）",
       retrieverType: "根据用户查询从索引中检索节点的算法类型",
       topk: "检索时返回的最相关结果数量",
       postProcessorType: "对检索结果进行后处理的组件类型",
       rerank: "对检索结果进行二次排序的模型，提升答案相关性",
       rerankDevice: "执行重排模型推理的硬件设备（CPU/GPU）",
-      generatorType: "回答生成方式的类型（本地部署模型或 vllm 高效推理框架）",
+      generatorType: "回答生成方式的类型（本地部署模型或 vLLM 高效推理框架）",
       language: "用于生成自然语言回答的大模型（如 LLaMA、ChatGLM）",
       llmDevice: "大语言模型推理的硬件设备（需匹配模型规模要求）",
       weights: "大模型的权重",
@@ -157,17 +186,18 @@ export default {
       vectorsimilarity: "根据向量相似性进行检索",
       autoMerge: "该检索器会尝试将上下文合并到父级上下文中",
       bm25: "使用BM25算法检索节点的BM25检索器",
-      faissVector: "嵌入存储在Faiss索引中。",
+      faissVector: "矢量索引存储在Faiss中。",
       vector: "矢量存储索引",
       simple: "解析文本，优先选择完整的句子。",
-      hierarchical: "使用借点解析将文档分割成递归层次节点",
+      hierarchical: "使用NodeParser将文档拆分为递归层次结构的节点。",
       sentencewindow: "将文档分割成节点，每个节点代表一个句子。每个节点包含一个来自元数据中周围句子的窗口",
       unstructured: "一个处理非结构化数据的组件",
-      milvusVector: "嵌入存储在Milvus索引中",
-      vector_uri: "测试Milvus地址是否可用",
+      milvusVector: "矢量索引存储在Milvus中",
+      vector_url: "测试Milvus地址是否可用",
       test: "测 试",
-      modelName: "Vllm 模型名称",
-      vllm_url: "测试Vllm地址是否可用",
+      modelName: "vLLM 模型名称",
+      vllm_url: "测试vLLM地址是否可用",
+      kbadmin: "第三方知识库系统",
     },
   },
   generation: {
@@ -221,11 +251,28 @@ export default {
     activated: "激活状态",
     nameValid1: "请输入知识库名称",
     nameValid2: "请输入 2 到 30 个字符的名称",
-    nameValid3: "名称不能以数字开头",
+    nameValid3: "仅支持字母、数字和下划线，必须以字母或下划线开头。",
     desValid: "请输入知识库描述",
     activeValid: "请选择是否启用该功能。",
-    uploadValid: "单个文件大小不得超过 50MB",
+    uploadValid: "单个文件大小不得超过 200MB",
     deleteFileTip: "您确定要删除此文档吗？此操作不可恢复。",
+    selectTitle: "创建类型选择",
+    selectDes: "请选择要创建的数据类型",
+    experience: "经验注入",
+    experienceDes:
+      "Experience是指个人或团队在实践过程中积累的知识和技能，通常通过实际操作、试错和反思获得，是解决实际问题的重要依据",
+    kbDes:
+      "知识库是系统化存储信息的集合，用于集中管理文档、常见问题、操作指南等知识内容，便于团队或用户快速查找和共享信息。",
+    type: "类型",
+    original: "原始的",
+    kbadmin: "kbadmin",
+    typeValid: "请选择知识库类型",
+    nameRequired: "请选择kbadmin名称",
+    waitTip: "请耐心等待所有文件上传完成！",
+    done: "已完成",
+    successfully: "成功",
+    failed: "失败",
+    totalTip: "个文件",
   },
   request: {
     pipeline: {
@@ -244,9 +291,51 @@ export default {
       updateSucc: "知识库更新成功!",
       deleteSucc: " 知识库删除成功!",
     },
+    experience: {
+      createSucc: "经验创建成功!",
+      updateSucc: "经验更新成功!",
+      deleteSucc: " 经验删除成功!",
+    },
   },
   error: {
     notFoundTip: "Oops 好像走错地方啦～",
     back: "首页",
   },
+  experience: {
+    create: "新建经验",
+    edit: "编辑经验",
+    import: "导入经验",
+    fileFormatTip: "仅支持JSON格式,文件大小不超过100M",
+    importSuccTip: "文件上传成功！",
+    importErrTip: "文件上传失败！",
+    uploadValid: "单个文件大小不得超过 200MB",
+    experience: "经验",
+    detail: "详情",
+    operation: "操作",
+    deleteTip: "确定要删除这个经验？",
+    addExperience: "新增经验",
+    delExperience: "删除经验",
+    addContent: "新增内容",
+    delContent: "删除内容",
+    total: "经验总数: ",
+    unique: "唯一",
+    selectTip: "请选择合适的方式进行数据更新",
+    cover: "覆盖",
+    increase: "追加",
+    deactivateTip: "您确定要停用该经验库吗？",
+    activeTip: "您确定要启用该经验库吗？",
+    label: {
+      experience: "经验",
+      contents: "经验内容",
+      content: "内容",
+    },
+    placeholder: {
+      experience: "请输入经验",
+      content: "请输入内容",
+    },
+    valid: {
+      experience: "经验不能为空",
+      content: "内容不能为空",
+    },
+  },
 };
diff --git a/EdgeCraftRAG/ui/vue/src/layout/Header.vue b/EdgeCraftRAG/ui/vue/src/layout/Header.vue
index 33d0038d62..0de80ece3d 100644
--- a/EdgeCraftRAG/ui/vue/src/layout/Header.vue
+++ b/EdgeCraftRAG/ui/vue/src/layout/Header.vue
@@ -2,7 +2,7 @@
   <div class="header-wrap">
     <img :height="36" :src="headerLog" />
     <div class="setting-wrap">
-      <a-dropdown arrow>
+      <a-dropdown>
         <div @click.prevent>
           <div class="lang-icon">
             <SvgIcon
diff --git a/EdgeCraftRAG/ui/vue/src/layout/Main.vue b/EdgeCraftRAG/ui/vue/src/layout/Main.vue
index 79af5a7f47..ba386bfe55 100644
--- a/EdgeCraftRAG/ui/vue/src/layout/Main.vue
+++ b/EdgeCraftRAG/ui/vue/src/layout/Main.vue
@@ -4,13 +4,16 @@
       <Header />
     </a-layout-header>
     <a-layout-content :class="{ 'layout-main': true, 'full-screen': isFull }">
-      <router-view class="layout-view" />
+      <!-- <router-view class="layout-view" /> -->
+      <Main />
     </a-layout-content>
   </a-layout>
 </template>
 <script lang="ts" setup name="Main">
 import { watch, onMounted } from "vue";
 import Header from "./Header.vue";
+import Main from "@/views/main/index.vue";
+
 const route = useRoute();
 const isFull = ref<boolean>(false);
 
diff --git a/EdgeCraftRAG/ui/vue/src/router/routes.ts b/EdgeCraftRAG/ui/vue/src/router/routes.ts
index 7408390df9..886f67bddf 100644
--- a/EdgeCraftRAG/ui/vue/src/router/routes.ts
+++ b/EdgeCraftRAG/ui/vue/src/router/routes.ts
@@ -8,27 +8,19 @@ export const routeList = [
     path: "/",
     name: "Main",
     component: Layout,
-    redirect: "/rag",
+    redirect: "/chatbot",
     children: [
       {
-        path: "/rag",
-        name: "Rag",
-        component: () => import("@/views/main/index.vue"),
-        redirect: "/rag/chatbot",
-        children: [
-          {
-            path: "/rag/pipeline",
-            name: "Pipeline",
-            component: () => import("@/views/pipeline/index.vue"),
-            meta: { title: "Pipeline" },
-          },
-          {
-            path: "/rag/chatbot",
-            name: "Chatbot",
-            component: () => import("@/views/chatbot/index.vue"),
-            meta: { title: "Chatbot" },
-          },
-        ],
+        path: "/pipeline",
+        name: "Pipeline",
+        component: () => import("@/views/pipeline/index.vue"),
+        meta: { title: "Pipeline" },
+      },
+      {
+        path: "/chatbot",
+        name: "Chatbot",
+        component: () => import("@/views/chatbot/index.vue"),
+        meta: { title: "Chatbot" },
       },
     ],
   },
diff --git a/EdgeCraftRAG/ui/vue/src/store/chatbot.ts b/EdgeCraftRAG/ui/vue/src/store/chatbot.ts
index 0b7bb5b20c..2473570374 100644
--- a/EdgeCraftRAG/ui/vue/src/store/chatbot.ts
+++ b/EdgeCraftRAG/ui/vue/src/store/chatbot.ts
@@ -14,6 +14,7 @@ const configuration = {
     stream: true,
     chat_template_kwargs: {
       enable_thinking: true,
+      enable_rag_retrieval: true,
     },
   },
 };
diff --git a/EdgeCraftRAG/ui/vue/src/theme/common.less b/EdgeCraftRAG/ui/vue/src/theme/common.less
index 0b2ee6085f..b3df87b0ba 100644
--- a/EdgeCraftRAG/ui/vue/src/theme/common.less
+++ b/EdgeCraftRAG/ui/vue/src/theme/common.less
@@ -111,6 +111,10 @@
     background: var(--color-primary-hover) !important;
     transition-duration: 0s;
   }
+  &.is-disabled {
+    color: var(--bg-scrollbar-hover) !important;
+    background: var(--color-scrollbar) !important;
+  }
 }
 .form-wrap {
   .intel-form-item-control-input-content {
@@ -118,7 +122,20 @@
     align-items: center;
     gap: 6px;
   }
+  .column-wrap {
+    .intel-form-item-control-input-content {
+      display: block;
+      .flex-left {
+        gap: 6px;
+      }
+      .option-introduction {
+        top: 0;
+        margin-top: 8px;
+      }
+    }
+  }
   .slider-wrap {
+    width: 100%;
     &:not(:last-child) {
       padding-bottom: 16px;
       margin-bottom: 12px;
@@ -191,9 +208,9 @@
     padding: 16px 24px 0 !important;
   }
 }
-.centered-model {
+.model-centered-footer {
   .ant-modal-confirm-btns {
-    text-align: center;
+    .vertical-center;
   }
 }
 .option-introduction {
@@ -213,6 +230,13 @@
     top: 5px;
   }
 }
+.experience-dialog {
+  .intel-modal-body {
+    max-height: 500px;
+    overflow-y: auto;
+  }
+}
+
 .loopStyle(@counter) when (@counter > 0) {
   .p-@{counter} {
     padding: (1px * @counter);
diff --git a/EdgeCraftRAG/ui/vue/src/theme/variables.less b/EdgeCraftRAG/ui/vue/src/theme/variables.less
index 892c90bd86..6ec22e31b5 100644
--- a/EdgeCraftRAG/ui/vue/src/theme/variables.less
+++ b/EdgeCraftRAG/ui/vue/src/theme/variables.less
@@ -23,6 +23,7 @@
   --color-second-warning: #854d0e;
   --color-warningBg: #feefd0;
   --color-second-warningBg: #fefce8;
+  --color-purple: #9333ea;
   --color-big-icon: #111111;
   --bg-main-color: #f5f5f5;
   --bg-card-color: #f9f9f9;
@@ -93,7 +94,7 @@
   --color-primary-hover: #1668dc;
   --color-primaryBg: #e0eaff;
   --color-primary-second: #1677ff;
-  --color-second-primaryBg: #d4e1fd;
+  --color-second-primaryBg: #93b3f7;
   --bg-box-shadow: rgba(255, 255, 255, 0.1);
   --bg-gradient-shadow: 0px 4px 6px -4px rgba(255, 255, 255, 0.1),
     0px 5px 8px 1px rgba(255, 255, 255, 0.1);
diff --git a/EdgeCraftRAG/ui/vue/src/types/global.d.ts b/EdgeCraftRAG/ui/vue/src/types/global.d.ts
index b8d6ff6718..f21cef6f78 100644
--- a/EdgeCraftRAG/ui/vue/src/types/global.d.ts
+++ b/EdgeCraftRAG/ui/vue/src/types/global.d.ts
@@ -117,14 +117,15 @@ declare interface paginationType<T = any> {
 // Table Columns
 declare type TableColumns<T = any> = {
   title: string;
-  key: string;
+  key?: string;
   dataIndex: string | string[];
   width?: number | string;
-  align?: string;
+  align?: "left" | "center" | "right";
   ellipsis?: boolean;
   visible?: boolean;
-  fixed?: boolean | string;
-  [key: string]: T;
+  fixed?: "left" | "right" | true | undefined;
+} & {
+  [key: string]: any;
 };
 
 // Dialog
@@ -132,3 +133,7 @@ declare interface DialogType<T = any> {
   visible: boolean;
   [key: string]: T;
 }
+
+declare interface FormRules {
+  [key: string]: RuleObject | RuleObject[];
+}
diff --git a/EdgeCraftRAG/ui/vue/src/utils/clipboard.ts b/EdgeCraftRAG/ui/vue/src/utils/clipboard.ts
new file mode 100644
index 0000000000..6be117eec4
--- /dev/null
+++ b/EdgeCraftRAG/ui/vue/src/utils/clipboard.ts
@@ -0,0 +1,100 @@
+// Copyright (C) 2025 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+
+import { ref, Ref } from "vue";
+import { message } from "ant-design-vue";
+import type { MessageType } from "ant-design-vue/es/message";
+import i18n from "@/i18n";
+
+interface UseClipboardOptions {
+  timeout?: number;
+}
+
+interface UseClipboardReturn {
+  copied: Ref<boolean>;
+  clipboardText: Ref<string>;
+  isSupported: Ref<boolean>;
+  copy: (text: string) => Promise<boolean>;
+  read: () => Promise<string | null>;
+  reset: () => void;
+}
+
+export const useClipboard = (options: UseClipboardOptions = {}): UseClipboardReturn => {
+  const { timeout = 2000 } = options;
+
+  const copied = ref(false);
+  const clipboardText = ref("");
+  const isSupported = ref(!!navigator.clipboard);
+  let timeoutId: number | null = null;
+  let messageInstance: MessageType | null = null;
+
+  const setCopiedState = (): void => {
+    copied.value = true;
+
+    if (timeoutId) {
+      clearTimeout(timeoutId);
+    }
+
+    timeoutId = window.setTimeout(() => {
+      copied.value = false;
+    }, timeout);
+  };
+
+  const copy = async (text: string): Promise<boolean> => {
+    if (!text) {
+      message.error(i18n.global.t("common.copyError"));
+      return false;
+    }
+
+    try {
+      if (navigator.clipboard) {
+        await navigator.clipboard.writeText(text);
+      }
+      clipboardText.value = text;
+      setCopiedState();
+      message.success(i18n.global.t("common.copySucc"));
+      return true;
+    } catch (error) {
+      message.error(i18n.global.t("common.copyError"));
+      return false;
+    }
+  };
+
+  const read = async (): Promise<string | null> => {
+    try {
+      if (navigator.clipboard && navigator.clipboard.readText) {
+        const text = await navigator.clipboard.readText();
+        clipboardText.value = text;
+        return text;
+      } else {
+        return null;
+      }
+    } catch (error) {
+      console.error(error);
+
+      return null;
+    }
+  };
+
+  const reset = (): void => {
+    copied.value = false;
+    clipboardText.value = "";
+    if (timeoutId) {
+      clearTimeout(timeoutId);
+      timeoutId = null;
+    }
+    if (messageInstance) {
+      messageInstance();
+      messageInstance = null;
+    }
+  };
+
+  return {
+    copied,
+    clipboardText,
+    isSupported,
+    copy,
+    read,
+    reset,
+  };
+};
diff --git a/EdgeCraftRAG/ui/vue/src/utils/notification.ts b/EdgeCraftRAG/ui/vue/src/utils/notification.ts
index de5b2c9cae..151141e0ea 100644
--- a/EdgeCraftRAG/ui/vue/src/utils/notification.ts
+++ b/EdgeCraftRAG/ui/vue/src/utils/notification.ts
@@ -1,14 +1,11 @@
 // Copyright (C) 2025 Intel Corporation
 // SPDX-License-Identifier: Apache-2.0
 
-import { CheckCircleFilled, CloseCircleFilled, ExclamationCircleFilled, InfoCircleFilled } from "@ant-design/icons-vue";
+import { h } from "vue";
 import { notification } from "ant-design-vue";
-interface NotificationIcon {
-  icon: any;
-  color: string;
-}
+import { CheckCircleFilled, CloseCircleFilled, ExclamationCircleFilled, InfoCircleFilled } from "@ant-design/icons-vue";
 
-const getNotificationIcon = (type: string): NotificationIcon => {
+const getNotificationIcon = (type: string) => {
   switch (type) {
     case "success":
       return { icon: CheckCircleFilled, color: "--color-success" };
@@ -22,19 +19,17 @@ const getNotificationIcon = (type: string): NotificationIcon => {
       return { icon: null, color: "" };
   }
 };
-
 export const customNotification = (
   type: "success" | "warning" | "error" | "info",
   message: string,
-  description: string,
+  description: string | undefined,
 ) => {
   const { icon, color } = getNotificationIcon(type);
-
   const styledIcon = icon ? h(icon, { style: { color: `var(${color})` } }) : null;
 
   notification[type]({
-    message: message,
-    description: description,
+    message,
+    description,
     icon: styledIcon,
   });
 };
diff --git a/EdgeCraftRAG/ui/vue/src/utils/other.ts b/EdgeCraftRAG/ui/vue/src/utils/other.ts
index cb5d56bc6a..85e3268cde 100644
--- a/EdgeCraftRAG/ui/vue/src/utils/other.ts
+++ b/EdgeCraftRAG/ui/vue/src/utils/other.ts
@@ -7,17 +7,19 @@ import type { App } from "vue";
 import { customNotification } from "./notification";
 import FormTooltip from "@/components/FormTooltip.vue";
 import SvgIcon from "@/components/SvgIcon.vue";
+import PartialLoading from "@/components/PartialLoading.vue";
 
 //Global Notification
 notification.config({
   placement: "topRight",
   duration: 3,
-  maxCount: 3,
+  maxCount: 2,
 });
 
 export const antConfig = (app: App) => {
   app.component("SvgIcon", SvgIcon);
   app.component("FormTooltip", FormTooltip);
+  app.component("PartialLoading", PartialLoading);
   app.use(ConfigProvider);
   app.provide("customNotification", customNotification);
   serviceManager.registerService("antNotification", customNotification);
diff --git a/EdgeCraftRAG/ui/vue/src/utils/validate.ts b/EdgeCraftRAG/ui/vue/src/utils/validate.ts
index 5b93df488e..2008de27b0 100644
--- a/EdgeCraftRAG/ui/vue/src/utils/validate.ts
+++ b/EdgeCraftRAG/ui/vue/src/utils/validate.ts
@@ -25,7 +25,12 @@ export const validateIpPort = (ipPortStr: string) => {
   return true;
 };
 
-export const isValidName = (name: string) => {
-  const pattern = /^[^0-9]/;
+export const isValidName = (name: string): boolean => {
+  const pattern = /^[a-zA-Z_][a-zA-Z0-9_]*$/;
   return pattern.test(name);
 };
+
+export const isValidPipelineName = (name: string): boolean => {
+  const validPattern = /^[a-zA-Z0-9_]+$/;
+  return validPattern.test(name);
+};
diff --git a/EdgeCraftRAG/ui/vue/src/views/chatbot/components/Chatbot/Chat.vue b/EdgeCraftRAG/ui/vue/src/views/chatbot/components/Chatbot/Chat.vue
index 17f80c74f9..80563780a1 100644
--- a/EdgeCraftRAG/ui/vue/src/views/chatbot/components/Chatbot/Chat.vue
+++ b/EdgeCraftRAG/ui/vue/src/views/chatbot/components/Chatbot/Chat.vue
@@ -3,14 +3,19 @@
     <div class="message-box" ref="scrollContainer" v-if="messagesLength">
       <div class="intel-markdown">
         <div ref="messageComponent">
-          <div v-for="(msg, index) in messagesList" :key="index" :inResponse>
+          <div v-for="(msg, index) in messagesList" :key="index">
             <MessageItem
               :message="msg"
               ref="messageRef"
               :inResponse
               :think="isThink"
+              :message-Index="index"
+              :last-query="isLastQuery(index)"
+              :last-response="isLastResponse(index)"
               @preview="handleImagePreview"
               @stop="isUserScrolling = true"
+              @regenerate="handleRegenerate"
+              @resend="handleDelete"
             />
           </div>
         </div>
@@ -36,13 +41,23 @@
         :auto-size="{ minRows: 2, maxRows: 5 }"
       />
       <div class="button-wrap">
-        <span
-          :class="{ 'think-btn': true, 'is-deep': isThink }"
-          @click="handleThinkChange"
-        >
-          <SvgIcon name="icon-deep-think" :size="16" inherit />
-          {{ $t(`chat.${isThink ? "reason" : "think"}`) }}
-        </span>
+        <div class="flex-left">
+          <span
+            :class="{ 'think-btn': true, 'is-deep': isThink }"
+            @click="handleThinkChange"
+          >
+            <SvgIcon name="icon-deep-think" :size="16" inherit />
+            {{ $t(`chat.${isThink ? "reason" : "think"}`) }}
+          </span>
+          <span
+            :class="{ 'think-btn': true, 'is-deep': enableKB }"
+            @click="handleKBChange"
+          >
+            <SvgIcon name="icon-kb" :size="16" inherit />
+            {{ $t("knowledge.title") }}
+          </span>
+        </div>
+
         <div class="send-btn">
           <a-tooltip placement="top" :title="$t('chat.new')">
             <span class="common-btn">
@@ -87,23 +102,21 @@
 </template>
 
 <script lang="ts" setup name="Chatbot">
-import { getBenchmark } from "@/api/chatbot";
+import { getBenchmark, requestStopChat } from "@/api/chatbot";
 import lightBulb from "@/assets/svgs/lightBulb.svg";
 import _ from "lodash";
 import { reactive, ref, computed, nextTick } from "vue";
 import { Benchmark, IMessage } from "../../type";
 import MessageItem from "./MessageItem.vue";
 import { handleMessageSend } from "./SseService";
-import { pipelineAppStore } from "@/store/pipeline";
 import { Local } from "@/utils/storage";
-import { ArrowDownOutlined } from "@ant-design/icons-vue";
+import { ArrowDownOutlined, CloseOutlined } from "@ant-design/icons-vue";
 import { throttle } from "lodash";
 import { chatbotAppStore } from "@/store/chatbot";
 
 const chatbotStore = chatbotAppStore();
 const emit = defineEmits(["config"]);
 const ENV_URL = import.meta.env;
-const pipelineStore = pipelineAppStore();
 const defaultBenchmark = reactive<Benchmark>({
   generator: "",
   postprocessor: "",
@@ -123,6 +136,7 @@ const isUserScrolling = ref(false);
 const showScrollToBottomBtn = ref(false);
 const resizeObserverRef = ref<ResizeObserver | null>(null);
 const isThink = ref<boolean>(true);
+const enableKB = ref<boolean>(true);
 
 const inputRef = ref();
 const handleEnvUrl = () => {
@@ -134,6 +148,15 @@ const handleEnvUrl = () => {
 const handleMessageDisplay = (data: any) => {
   if (inResponse.value) {
     isUserScrolling.value = false;
+    const regex = /code:0000(.*)/s;
+    const match = data.match(regex);
+    if (match) {
+      messagesList.value.pop();
+      messagesList.value[messagesList.value?.length - 1].errorMessage =
+        match[1].trim();
+      return;
+    }
+
     messagesList.value[messagesList.value?.length - 1].content = data;
   }
 };
@@ -143,6 +166,26 @@ const notInput = computed(() => {
 const messagesLength = computed(() => {
   return messagesList.value?.length;
 });
+const lastQueryIndex = computed(() => {
+  for (let i = messagesList.value.length - 1; i >= 0; i--) {
+    if (messagesList.value[i].role === "user") {
+      return i;
+    }
+  }
+  return -1;
+});
+
+const lastResponseIndex = computed(() => {
+  for (let i = messagesList.value.length - 1; i >= 0; i--) {
+    if (messagesList.value[i].role === "assistant") {
+      return i;
+    }
+  }
+  return -1;
+});
+const isLastQuery = (index: number) => index === lastQueryIndex.value;
+const isLastResponse = (index: number) => index === lastResponseIndex.value;
+
 const handleStreamEnd = () => {
   handleStopDisplay();
   queryBenchmark();
@@ -183,6 +226,7 @@ const handleSendMessage = async () => {
     {
       role: "assistant",
       content: "",
+      query: inputKeywords.value,
       benchmark: _.cloneDeep(defaultBenchmark),
     }
   );
@@ -196,8 +240,7 @@ const handleStopDisplay = () => {
 };
 
 const queryBenchmark = async () => {
-  const { activatedPipeline } = pipelineStore;
-  const data = (await getBenchmark(activatedPipeline)) || {};
+  const data = (await getBenchmark()) || {};
 
   if (data["Benchmark enabled"]) {
     const benchmarkData = data.last_benchmark_data || {};
@@ -205,7 +248,7 @@ const queryBenchmark = async () => {
       const processedBenchmarkData = Object.fromEntries(
         Object.entries(benchmarkData).map(([key, value]: any) => [
           key,
-          parseFloat(value.toFixed(4)),
+          value ? parseFloat(value.toFixed(4)) : 0,
         ])
       );
       messagesList.value[messagesList.value.length - 1].benchmark =
@@ -227,14 +270,43 @@ const handleNewChat = () => {
 };
 const handleThinkChange = () => {
   isThink.value = !isThink.value;
+  const { chat_template_kwargs } = chatbotStore.configuration;
+
+  const chat_template = {
+    ...chat_template_kwargs,
+    enable_thinking: isThink.value,
+  };
+  chatbotStore.setChatbotConfiguration({
+    chat_template_kwargs: chat_template,
+  });
+};
+const handleKBChange = () => {
+  enableKB.value = !enableKB.value;
+  const { chat_template_kwargs } = chatbotStore.configuration;
+
+  const chat_template = {
+    ...chat_template_kwargs,
+    enable_rag_retrieval: enableKB.value,
+  };
 
   chatbotStore.setChatbotConfiguration({
-    chat_template_kwargs: { enable_thinking: isThink.value },
+    chat_template_kwargs: chat_template,
   });
 };
 const handleConfig = () => {
   emit("config");
 };
+const handleRegenerate = (query: string) => {
+  inputKeywords.value = query;
+
+  handleSendMessage();
+};
+const handleDelete = ({ index, query }: { index: number; query: string }) => {
+  messagesList.value.splice(index);
+  inputKeywords.value = query;
+
+  handleSendMessage();
+};
 
 const scrollToBottom = () => {
   if (!scrollContainer.value) return;
@@ -302,8 +374,10 @@ watch(
   { immediate: true }
 );
 onMounted(() => {
-  isThink.value =
-    chatbotStore.configuration?.chat_template_kwargs.enable_thinking;
+  const { enable_thinking = true, enable_rag_retrieval = false } =
+    chatbotStore.configuration?.chat_template_kwargs;
+  isThink.value = enable_thinking;
+  enableKB.value = enable_rag_retrieval;
 });
 onBeforeUnmount(() => {
   if (resizeObserver && messageComponent.value) {
@@ -421,6 +495,9 @@ onBeforeUnmount(() => {
       align-items: center;
       justify-content: space-between;
       padding: 6px 12px;
+      .flex-left {
+        gap: 8px;
+      }
       .think-btn {
         height: 24px;
         line-height: 24px;
@@ -495,5 +572,28 @@ onBeforeUnmount(() => {
       }
     }
   }
+  .error-tip {
+    border: 1px solid var(--border-warning);
+    background-color: var(--color-warningBg);
+    color: var(--color-second-warning);
+    padding: 8px 12px;
+    border-radius: 0 4px 4px 0;
+    margin-bottom: 12px;
+    font-size: 12px;
+    .flex-between;
+    &:hover {
+      .card-shadow;
+    }
+    .message-wrap {
+      flex: 1;
+    }
+    .close-btn {
+      cursor: pointer;
+      text-align: end;
+      &:hover {
+        color: var(--color-error);
+      }
+    }
+  }
 }
 </style>
diff --git a/EdgeCraftRAG/ui/vue/src/views/chatbot/components/Chatbot/ConfigDrawer.vue b/EdgeCraftRAG/ui/vue/src/views/chatbot/components/Chatbot/ConfigDrawer.vue
index 16258dd73e..fe94bd86e4 100644
--- a/EdgeCraftRAG/ui/vue/src/views/chatbot/components/Chatbot/ConfigDrawer.vue
+++ b/EdgeCraftRAG/ui/vue/src/views/chatbot/components/Chatbot/ConfigDrawer.vue
@@ -27,7 +27,7 @@
           <a-slider
             v-model:value="form.top_n"
             :min="1"
-            :max="30"
+            :max="50"
             :marks="sliderMarks.top_n"
           />
           <div class="tips-wrap">
@@ -164,7 +164,7 @@ const form = reactive<ConfigType>({
   max_tokens,
   stream,
 });
-const rules = reactive({
+const rules: FormRules = reactive({
   top_n: [{ required: true, trigger: "blur" }],
   temperature: [{ required: true, trigger: "blur" }],
   top_p: [{ required: true, trigger: "blur" }],
@@ -175,7 +175,7 @@ const rules = reactive({
 const sliderMarks = reactive<EmptyObjectType>({
   top_n: {
     1: "1",
-    30: "30",
+    50: "50",
   },
   temperature: {
     0: "0",
diff --git a/EdgeCraftRAG/ui/vue/src/views/chatbot/components/Chatbot/MessageItem.vue b/EdgeCraftRAG/ui/vue/src/views/chatbot/components/Chatbot/MessageItem.vue
index b3f7e601d9..fffa99e963 100644
--- a/EdgeCraftRAG/ui/vue/src/views/chatbot/components/Chatbot/MessageItem.vue
+++ b/EdgeCraftRAG/ui/vue/src/views/chatbot/components/Chatbot/MessageItem.vue
@@ -10,8 +10,8 @@
           />
         </div>
         <div class="message-wrap">
-          <div v-if="!props.message?.content" class="dot-loader">
-            <span class="drop" v-for="(drop, index) in 3" :key="index"></span>
+          <div v-if="inResponse && !props.message?.content" class="dot-loader">
+            <span class="drop" v-for="index in 3" :key="index"></span>
           </div>
           <div
             class="think-container"
@@ -55,6 +55,20 @@
             </div>
           </div>
           <div v-html="renderedMarkdown"></div>
+          <div v-if="!inResponse" class="footer-btn">
+            <a-tooltip placement="top" :title="$t('common.copy')">
+              <span class="icon-style" @click="handleCopyResponses()">
+                <CopyOutlined /></span
+            ></a-tooltip>
+            <a-tooltip
+              v-if="lastResponse"
+              placement="top"
+              :title="$t('common.regenerate')"
+            >
+              <span class="icon-style" @click="handleRegenerate()">
+                <SyncOutlined /></span
+            ></a-tooltip>
+          </div>
         </div>
       </div>
       <div
@@ -86,7 +100,67 @@
       </div>
     </template>
     <div v-else class="user-session">
-      <div class="message-wrap">{{ message.content }}</div>
+      <template v-if="editState">
+        <div class="input-wrap">
+          <a-textarea
+            v-model:value.trim="queryInput"
+            :bordered="false"
+            :auto-size="{ minRows: 1, maxRows: 2 }"
+          />
+          <div class="button-wrap">
+            <a-button shape="round" @click="handleCancel">
+              {{ $t("common.cancel") }}
+            </a-button>
+            <a-button
+              type="primary"
+              shape="round"
+              @click="handleSend"
+              :disabled="!queryInput"
+            >
+              {{ $t("common.send") }}
+            </a-button>
+          </div>
+        </div>
+      </template>
+      <template v-else>
+        <a-tooltip
+          v-if="message.errorMessage"
+          placement="left"
+          color="var(--bg-card-color)"
+          :overlayInnerStyle="{
+            color: 'var(--font-text-color)',
+            border: '1px solid var(--color-error)',
+          }"
+        >
+          <template #title>
+            <SvgIcon
+              name="icon-chatbot1"
+              :size="20"
+              :style="{
+                color: 'var(--color-error)',
+              }"
+            />{{ message.errorMessage }}</template
+          >
+          <ExclamationCircleFilled class="error-icon"
+        /></a-tooltip>
+        <div class="message-wrap">
+          {{ message.content }}
+          <div class="footer-btn">
+            <a-tooltip placement="top" :title="$t('common.copy')">
+              <span class="icon-style" @click="handleCopyQuery()">
+                <CopyOutlined /></span
+            ></a-tooltip>
+            <a-tooltip
+              v-if="!inResponse && lastQuery"
+              placement="top"
+              :title="$t('common.edit')"
+            >
+              <span class="icon-style" @click="handleEdit()">
+                <EditOutlined /></span
+            ></a-tooltip>
+          </div>
+        </div>
+      </template>
       <div class="user-wrap">
         <SvgIcon name="icon-user" inherit :size="22" />
       </div>
@@ -97,11 +171,21 @@
 <script lang="ts" setup name="MessageItem">
 import { marked } from "marked";
 import { PropType, ref } from "vue";
-import { CheckCircleFilled, UpOutlined } from "@ant-design/icons-vue";
+import {
+  CheckCircleFilled,
+  UpOutlined,
+  CopyOutlined,
+  SyncOutlined,
+  EditOutlined,
+  ExclamationCircleFilled,
+} from "@ant-design/icons-vue";
 import { IMessage, Benchmark } from "../../type";
 import CustomRenderer from "@/utils/customRenderer";
+import { useClipboard } from "@/utils/clipboard";
 import "highlight.js/styles/atom-one-dark.css";
 
+const { copy } = useClipboard();
+
 const props = defineProps({
   message: {
     type: Object as PropType<IMessage>,
@@ -116,9 +200,20 @@ const props = defineProps({
     type: Boolean,
     required: true,
   },
+  messageIndex: {
+    type: Number,
+  },
+  lastQuery: {
+    type: Boolean,
+    default: false,
+  },
+  lastResponse: {
+    type: Boolean,
+    default: false,
+  },
 });
 
-const emit = defineEmits(["preview", "stop"]);
+const emit = defineEmits(["preview", "stop", "regenerate", "resend"]);
 
 const benchmarkData = computed<Benchmark>(() => {
   return (props.message?.benchmark || {}) as Benchmark;
@@ -126,6 +221,8 @@ const benchmarkData = computed<Benchmark>(() => {
 const isExpanded = ref<boolean>(false);
 const isCollapsed = ref(true);
 const thinkMode = ref(props.think);
+const editState = ref<boolean>(false);
+const queryInput = ref<string>(props.message.content);
 
 marked.setOptions({
   pedantic: false,
@@ -155,13 +252,13 @@ const thinkMarkdown = computed(() => {
   return marked(getThinkMode().value);
 });
 
-const renderedMarkdown = computed(() => {
+const readResponse = computed(() => {
   const content = props.message?.content || "";
 
   if (!content) return "";
 
   if (!thinkMode.value) {
-    return marked(content);
+    return content;
   }
 
   if (!isThinkEnd.value) {
@@ -169,7 +266,10 @@ const renderedMarkdown = computed(() => {
   }
 
   const cleanedContent = content.replace(thinkTagRegexSpecial, "");
-  return marked(cleanedContent);
+  return cleanedContent;
+});
+const renderedMarkdown = computed(() => {
+  return marked(readResponse.value);
 });
 const toggleTabs = () => {
   isExpanded.value = !isExpanded.value;
@@ -192,6 +292,29 @@ const addClickListeners = () => {
     });
   });
 };
+const handleRegenerate = () => {
+  const { query = "" } = props.message;
+  if (!query) return;
+  emit("regenerate", query);
+};
+const handleCopyQuery = async () => {
+  await copy(queryInput.value);
+};
+const handleCopyResponses = async () => {
+  await copy(readResponse.value);
+};
+const handleEdit = () => {
+  queryInput.value = props.message.content;
+  editState.value = true;
+};
+const handleCancel = () => {
+  editState.value = false;
+};
+const handleSend = () => {
+  if (!queryInput.value) return;
+  emit("resend", { index: props.messageIndex, query: queryInput.value });
+  handleCancel();
+};
 
 watch(
   () => props.inResponse,
@@ -290,8 +413,9 @@ watch(
   width: 100%;
 }
 .user-session {
-  margin-bottom: 20px;
+  margin-bottom: 30px;
   display: flex;
+  align-items: center;
   justify-content: flex-end;
   font-size: 16px;
   text-align: end;
@@ -300,6 +424,33 @@ watch(
     background-color: var(--message-bg);
     width: auto;
     text-align: left;
+    position: relative;
+    .footer-btn {
+      position: absolute;
+      bottom: -24px;
+      right: 0;
+      z-index: 20;
+      opacity: 0;
+      visibility: hidden;
+      transition: opacity 0.3s ease, visibility 0s linear 2s;
+      gap: 8px;
+      .anticon {
+        cursor: pointer;
+        &:hover {
+          color: var(--color-primary-hover);
+        }
+      }
+    }
+    &:hover .footer-btn {
+      opacity: 1;
+      visibility: visible;
+      transition: opacity 0.3s ease;
+    }
+  }
+  .error-icon {
+    font-size: 18px;
+    color: var(--color-error);
+    .mr-8;
   }
 }
 .benchmark-wrap {
@@ -493,4 +644,44 @@ watch(
     }
   }
 }
+.footer-btn {
+  .flex-end;
+  .mt-8;
+  gap: 8px;
+  font-size: 14px;
+  color: var(--font-tip-color);
+  .anticon {
+    cursor: pointer;
+    &:hover {
+      color: var(--color-primary-hover);
+    }
+  }
+}
+.input-wrap {
+  padding: 4px;
+  border: 1px solid var(--color-primary);
+  border-radius: 20px;
+  background-color: var(--input-bg);
+  max-width: 960px;
+  min-width: 500px;
+  transition: all 0.2s;
+  width: 100%;
+  display: flow-root;
+  position: relative;
+  left: -2px;
+  text-align: center;
+
+  &:hover {
+    box-shadow: 0 4px 12px var(--bg-primary-shadow);
+    border: 1px solid var(--color-primary-hover);
+  }
+  textarea {
+    resize: none;
+  }
+
+  .button-wrap {
+    .flex-end;
+    padding: 6px 12px;
+  }
+}
 </style>
diff --git a/EdgeCraftRAG/ui/vue/src/views/chatbot/components/Chatbot/SseService.ts b/EdgeCraftRAG/ui/vue/src/views/chatbot/components/Chatbot/SseService.ts
index 1f57ce25b1..de0cc61809 100644
--- a/EdgeCraftRAG/ui/vue/src/views/chatbot/components/Chatbot/SseService.ts
+++ b/EdgeCraftRAG/ui/vue/src/views/chatbot/components/Chatbot/SseService.ts
@@ -1,6 +1,7 @@
 // Copyright (C) 2025 Intel Corporation
 // SPDX-License-Identifier: Apache-2.0
 import { getChatSessionId } from "@/utils/common";
+import { message } from "ant-design-vue";
 
 export const handleMessageSend = async (
   url: string,
@@ -8,6 +9,8 @@ export const handleMessageSend = async (
   onDisplay: (data: any) => void,
   onEnd?: () => void,
 ): Promise<void> => {
+  let reader: ReadableStreamDefaultReader | undefined;
+
   try {
     const response = await fetch(url, {
       method: "POST",
@@ -20,30 +23,48 @@ export const handleMessageSend = async (
     });
 
     if (!response.ok) {
-      throw new Error(`Network response was not ok: ${response.statusText}`);
+      let errorMessage = "";
+      try {
+        const errorText = await response.text();
+        if (errorText) {
+          errorMessage = errorText;
+        }
+      } catch (parseError) {
+        console.warn("Failed to read error response:", parseError);
+      }
+      message.error(errorMessage);
+      throw new Error(errorMessage);
+    }
+
+    reader = response.body?.getReader();
+    if (!reader) {
+      throw new Error("Readable stream is not available");
     }
 
-    const reader = response.body?.getReader();
     const decoder = new TextDecoder("utf-8");
     let buffer = "";
 
-    try {
-      while (true) {
-        const { done, value } = await reader.read();
-        if (done) {
-          onEnd?.();
-          break;
-        }
-        buffer += decoder.decode(value, { stream: true });
-
-        onDisplay(buffer);
+    while (true) {
+      const { done, value } = await reader.read();
+      if (done) {
+        onEnd?.();
+        break;
       }
-    } catch (error) {
-      console.error(error);
-      onEnd?.();
+
+      buffer += decoder.decode(value, { stream: true });
+
+      onDisplay(buffer);
     }
-  } catch (error) {
-    console.error(error);
+  } catch (error: any) {
+    console.error("Request or stream error:", error);
     onEnd?.();
+  } finally {
+    if (reader) {
+      try {
+        await reader.cancel();
+      } catch (cancelError) {
+        console.warn("Failed to cancel reader:", cancelError);
+      }
+    }
   }
 };
diff --git a/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/DetailComponent.vue b/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/DetailComponent.vue
new file mode 100644
index 0000000000..5ba1d94094
--- /dev/null
+++ b/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/DetailComponent.vue
@@ -0,0 +1,93 @@
+<template>
+  <div class="kb-detail-container">
+    <div class="header-wrap">
+      <div class="info-wrap">
+        <div class="name-wrap">{{ kbInfo.name }}</div>
+        <div class="des-wrap" v-if="kbInfo.description">
+          {{ kbInfo.description }}
+        </div>
+      </div>
+      <div class="button-wrap">
+        <a-button
+          type="primary"
+          ghost
+          :icon="h(RollbackOutlined)"
+          @click="handleBack"
+          >{{ $t("common.back") }}</a-button
+        >
+      </div>
+    </div>
+    <component :is="currentComponent" :key="componentKey" :kb-info="kbInfo" />
+  </div>
+</template>
+
+<script setup lang="ts" name="DetailComponent">
+import { h, provide } from "vue";
+import { RollbackOutlined } from "@ant-design/icons-vue";
+import eventBus from "@/utils/mitt";
+import { KnowledgeDetail, ExperienceDetail } from "./index";
+
+const props = defineProps({
+  kbInfo: {
+    type: Object,
+    default: () => {},
+    required: true,
+  },
+});
+
+provide("kbInfo", props.kbInfo);
+const emit = defineEmits(["back"]);
+
+const currentComponent = computed(() => {
+  return props.kbInfo.comp_type === "experience"
+    ? ExperienceDetail
+    : KnowledgeDetail;
+});
+
+const componentKey = computed(() => {
+  return `detail-${props.kbInfo.idx}`;
+});
+const handleBack = () => {
+  emit("back");
+  eventBus.emit("reset");
+};
+</script>
+
+<style lang="less" scoped>
+.kb-detail-container {
+  display: block !important;
+  height: 100%;
+  .flex-column;
+  .header-wrap {
+    padding: 12px 16px;
+    height: 60px;
+    border-bottom: 1px solid var(--border-main-color);
+    .flex-between;
+    gap: 16px;
+    min-width: 0;
+    .info-wrap {
+      flex: 1;
+      .flex-column;
+      gap: 4px;
+      min-width: 0;
+      .name-wrap {
+        font-size: 16px;
+        font-weight: 600;
+        flex: 1;
+        min-width: 0;
+        line-height: 16px;
+        .single-ellipsis;
+      }
+      .des-wrap {
+        color: var(--font-info-color);
+        font-size: 12px;
+        .single-ellipsis;
+      }
+    }
+    .button-wrap {
+      .vertical-center;
+      gap: 4px;
+    }
+  }
+}
+</style>
diff --git a/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/Experience/ExperienceDetail.vue b/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/Experience/ExperienceDetail.vue
new file mode 100644
index 0000000000..24a1f937ec
--- /dev/null
+++ b/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/Experience/ExperienceDetail.vue
@@ -0,0 +1,225 @@
+<template>
+  <div class="experience-container">
+    <div class="table-container">
+      <div class="header-wrap">
+        <span class="title"></span>
+        <div class="btn-wrap">
+          <a-config-provider :theme="antTheme.subTheme">
+            <a-button
+              type="primary"
+              :icon="h(CloudUploadOutlined)"
+              @click="handleImport()"
+              >{{ $t("experience.import") }}</a-button
+            >
+          </a-config-provider>
+          <a-button type="primary" @click="handleCreate()">
+            <template #icon>
+              <PlusOutlined />
+            </template>
+            {{ $t("experience.create") }}</a-button
+          >
+        </div>
+      </div>
+      <a-table
+        :columns="tableColumns"
+        :data-source="tableList"
+        :pagination="false"
+        :row-key="(record) => record?.question"
+      >
+        <template #expandColumnTitle>
+          <div class="expand-column">{{ $t("experience.detail") }}</div>
+        </template>
+        <template #expandedRowRender="{ record }">
+          <p v-for="(item, index) in record.content" class="experience-item">
+            {{ index + 1 }}.
+            {{ item }}
+          </p>
+        </template>
+        <template #bodyCell="{ column, record }">
+          <template v-if="column.dataIndex === 'operation'">
+            <a-space wrap>
+              <a-button
+                type="primary"
+                ghost
+                size="small"
+                :icon="h(EditFilled)"
+                :disabled="record.status?.active"
+                @click="handleUpdate(record)"
+              >
+                {{ $t("common.update") }}</a-button
+              >
+              <a-button
+                danger
+                size="small"
+                :icon="h(DeleteFilled)"
+                :disabled="record.status?.active"
+                @click="handleDelete(record)"
+                >{{ $t("common.delete") }}
+              </a-button>
+            </a-space>
+          </template>
+        </template>
+      </a-table>
+      <a-pagination
+        v-if="paginationData.total > 10"
+        v-model:current="paginationData.pageNum"
+        v-model:pageSize="paginationData.pageSize"
+        showSizeChanger
+        :total="paginationData.total"
+      />
+      <!-- UpdateDialog -->
+      <UpdateDialog
+        v-if="updateDialog.visible"
+        :dialog-data="updateDialog.data"
+        :dialog-type="updateDialog.type"
+        @search="handleSearch"
+        @close="updateDialog.visible = false"
+      />
+      <!-- importDialog -->
+      <ImportDialog
+        v-if="importDialog.visible"
+        @close="importDialog.visible = false"
+        @search="handleSearch"
+      />
+    </div>
+  </div>
+</template>
+
+<script lang="ts" setup name="ExperienceDetail">
+import { createVNode, h, ref, onMounted } from "vue";
+import { antTheme } from "@/utils/antTheme";
+import {
+  CloseCircleFilled,
+  CloudUploadOutlined,
+  PlusOutlined,
+  EditFilled,
+  DeleteFilled,
+} from "@ant-design/icons-vue";
+import { Modal } from "ant-design-vue";
+import {
+  getExperienceDetailByName,
+  getExperienceList,
+  requestExperienceDelete,
+} from "@/api/knowledgeBase";
+import { UpdateDialog, ImportDialog } from "./index.ts";
+import { useI18n } from "vue-i18n";
+import eventBus from "@/utils/mitt";
+
+const { t } = useI18n();
+const tableData = ref<EmptyArrayType>([]);
+const tableColumns = computed<EmptyArrayType>(() => [
+  {
+    title: t("experience.label.experience"),
+    dataIndex: "question",
+    ellipsis: true,
+  },
+  {
+    title: t("experience.operation"),
+    dataIndex: "operation",
+    width: "180px",
+    fixed: "right",
+  },
+]);
+
+const paginationData = reactive<paginationType>({
+  total: 0,
+  pageNum: 1,
+  pageSize: 10,
+});
+const updateDialog = reactive<DialogType>({
+  visible: false,
+  type: "create",
+  data: [],
+});
+const importDialog = reactive<DialogType>({
+  visible: false,
+});
+const tableList = computed(() => {
+  const { pageNum, pageSize } = paginationData;
+  const start = (pageNum - 1) * pageSize;
+  const end = start + pageSize;
+  return tableData.value.slice(start, end);
+});
+const queryExperienceList = async () => {
+  const data: any = await getExperienceList();
+
+  tableData.value = [].concat(data || []);
+};
+//create
+const handleCreate = () => {
+  updateDialog.type = "create";
+  updateDialog.data = [];
+  updateDialog.visible = true;
+};
+//edit
+const handleUpdate = async (row: EmptyObjectType) => {
+  const { question } = row;
+  const data: any = await getExperienceDetailByName({ question });
+
+  updateDialog.type = "edit";
+  updateDialog.data = [data];
+  updateDialog.visible = true;
+};
+//import
+const handleImport = () => {
+  importDialog.visible = true;
+};
+//delete
+const handleDelete = (row: EmptyObjectType) => {
+  Modal.confirm({
+    title: t("common.delete"),
+    icon: createVNode(CloseCircleFilled, { class: "error-icon" }),
+    content: t("experience.deleteTip"),
+    okText: t("common.confirm"),
+    okType: "danger",
+    async onOk() {
+      const { question } = row;
+      await requestExperienceDelete({ question });
+      paginationData.pageNum = 1;
+      handleSearch();
+    },
+  });
+};
+
+//search
+const handleSearch = () => {
+  queryExperienceList();
+  eventBus.emit("refresh");
+};
+onMounted(() => {
+  queryExperienceList();
+});
+</script>
+
+<style scoped lang="less">
+.experience-container {
+  padding: 24px;
+  .table-container {
+    .p-16;
+    .pb-24;
+    border-radius: 8px;
+    background-color: var(--bg-content-color);
+
+    .header-wrap {
+      .flex-between;
+      .mb-20;
+    }
+    .title {
+      .fs-16;
+      font-weight: 600;
+      color: var(--font-main-color);
+    }
+    .btn-wrap {
+      display: flex;
+      gap: 12px;
+    }
+    .experience-item {
+      color: var(--font-text-color);
+      .pl-8;
+    }
+    .expand-column {
+      width: 80px;
+    }
+  }
+}
+</style>
diff --git a/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/Experience/ImportDialog.vue b/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/Experience/ImportDialog.vue
new file mode 100644
index 0000000000..b558bac195
--- /dev/null
+++ b/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/Experience/ImportDialog.vue
@@ -0,0 +1,100 @@
+<template>
+  <a-modal
+    v-model:open="modelVisible"
+    width="500px"
+    centered
+    destroyOnClose
+    :title="$t('experience.import')"
+    :keyboard="false"
+    :maskClosable="false"
+    :footer="null"
+    @cancel="handleClose"
+    class="import-dialog"
+  >
+    <a-upload-dragger
+      v-model:fileList="fileList"
+      name="file"
+      :action="uploadFileApi"
+      accept=".json"
+      :showUploadList="false"
+      :before-upload="handleBeforeUpload"
+      @change="handleChange"
+    >
+      <SvgIcon
+        name="icon-cloudupload-fill"
+        :size="40"
+        :style="{ color: 'var(--color-primary)' }"
+      />
+      <p class="intel-upload-text">{{ $t("common.uploadTip") }}</p>
+      <p class="intel-upload-hint">
+        {{ $t("experience.fileFormatTip") }}
+      </p>
+      <a-button type="primary" class="mt-12">{{
+        $t("common.import")
+      }}</a-button>
+    </a-upload-dragger>
+  </a-modal>
+</template>
+
+<script lang="ts" setup name="ImportDialog">
+import { requestExperienceRelation, uploadFileUrl } from "@/api/knowledgeBase";
+import { ref, inject } from "vue";
+import { useNotification } from "@/utils/common";
+import { NextLoading } from "@/utils/loading";
+import { useI18n } from "vue-i18n";
+import { message, UploadProps } from "ant-design-vue";
+
+const { t } = useI18n();
+const { antNotification } = useNotification();
+
+interface KbType {
+  name: string;
+}
+const emit = defineEmits(["search", "close"]);
+const kbInfo = inject<KbType>("kbInfo");
+const modelVisible = ref<boolean>(true);
+const fileList = ref([]);
+const uploadFileApi = computed(() => {
+  return uploadFileUrl + kbInfo?.name;
+});
+const handleBeforeUpload = (file: UploadProps["fileList"][number]) => {
+  const isFileSize = file.size / 1024 / 1024 < 100;
+
+  if (!isFileSize) {
+    message.error(t("experience.uploadValid"));
+    return;
+  }
+
+  return isFileSize;
+};
+const handleChange = async (info: any) => {
+  const el = <HTMLElement>document.querySelector(".loading-next");
+  if (!el) NextLoading.start();
+  try {
+    const { response, status } = info.file;
+
+    if (status === "done") {
+      const { name = "" } = kbInfo;
+      await requestExperienceRelation({
+        name,
+        local_path: response,
+      });
+      emit("search");
+      handleClose();
+      NextLoading.done();
+    } else if (status === "error") {
+      NextLoading.done();
+      antNotification("error", t("common.error"), t("experience.importErrTip"));
+    }
+  } catch (error) {
+    console.error(error);
+    if (NextLoading) NextLoading.done();
+  }
+};
+
+const handleClose = () => {
+  emit("close");
+};
+</script>
+
+<style scoped lang="less"></style>
diff --git a/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/Experience/UpdateDialog.vue b/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/Experience/UpdateDialog.vue
new file mode 100644
index 0000000000..e828d47356
--- /dev/null
+++ b/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/Experience/UpdateDialog.vue
@@ -0,0 +1,387 @@
+<template>
+  <a-modal
+    v-model:open="modelVisible"
+    width="800px"
+    centered
+    destroyOnClose
+    :title="dialogTitle"
+    :keyboard="false"
+    :maskClosable="false"
+    @cancel="handleCancel"
+    class="experience-dialog"
+  >
+    <div class="enter-wrap">
+      <a-form
+        :model="form"
+        :rules="rules"
+        name="form"
+        ref="formRef"
+        autocomplete="off"
+        class="form-wrap"
+        layout="vertical"
+      >
+        <div
+          class="item-wrap"
+          v-for="(item, index) in form.experience"
+          :key="index"
+        >
+          <a-form-item
+            :label="`${$t('experience.label.experience')} ${
+              isEdit ? '' : `${index + 1}`
+            }`"
+            :name="['experience', index, 'question']"
+            :rules="rules.experience"
+          >
+            <a-textarea
+              v-model:value="item.question"
+              :placeholder="$t('experience.placeholder.experience')"
+              :auto-size="{ minRows: 1, maxRows: 2 }"
+              :disabled="isEdit"
+            />
+          </a-form-item>
+          <a-form-item
+            :label="$t('experience.label.contents')"
+            :name="['experience', index, 'content']"
+            :rules="rules.contentList"
+            class="gt-wrap"
+          >
+            <div
+              v-for="(contentItem, k) in item.content"
+              :key="k"
+              class="item-wrap content-wrap flex-left"
+            >
+              <a-form-item
+                :label="`${$t('experience.label.content')} ${k + 1}`"
+                :name="['experience', index, 'content', k]"
+                :rules="rules.text"
+                class="flex-item"
+              >
+                <a-textarea
+                  v-model:value="item.content[k]"
+                  :placeholder="$t('experience.placeholder.content')"
+                  :auto-size="{ minRows: 1, maxRows: 3 }"
+                />
+              </a-form-item>
+
+              <div class="icon-wrap">
+                <a-tooltip
+                  placement="topRight"
+                  arrow-point-at-center
+                  :title="$t('experience.delContent')"
+                  v-if="item.content?.length > 1"
+                >
+                  <DeleteOutlined
+                    @click="handleContentDelete(item.content, k)"
+                  />
+                </a-tooltip>
+              </div>
+            </div>
+            <div class="add-wrap" @click="handleContentAdd(item.content)">
+              <PlusOutlined /> {{ $t("experience.addContent") }}
+            </div>
+          </a-form-item>
+          <div class="icon-wrap">
+            <a-tooltip
+              placement="topRight"
+              arrow-point-at-center
+              :title="$t('experience.delExperience')"
+              v-if="form.experience?.length > 1"
+            >
+              <MinusCircleOutlined @click="handleDelete(index)" />
+            </a-tooltip>
+          </div>
+        </div>
+        <div v-if="!isEdit" class="operate-wrap" @click="handleAdd">
+          <PlusOutlined />
+          {{ $t("experience.addExperience") }}
+        </div>
+      </a-form>
+    </div>
+    <template #footer>
+      <a-button type="primary" ghost @click="handleCancel">{{
+        $t("common.cancel")
+      }}</a-button>
+      <a-button
+        key="submit"
+        type="primary"
+        :loading="submitLoading"
+        @click="handleSubmit"
+        >{{ $t("common.submit") }}</a-button
+      >
+    </template>
+  </a-modal>
+</template>
+
+<script lang="ts" setup name="UpdateDialog">
+import {
+  requestExperienceConfirm,
+  requestExperienceCreate,
+  requestExperienceUpdate,
+} from "@/api/knowledgeBase";
+import {
+  MinusCircleOutlined,
+  PlusOutlined,
+  DeleteOutlined,
+} from "@ant-design/icons-vue";
+import { FormInstance, Modal } from "ant-design-vue";
+import { computed, ref } from "vue";
+import { useI18n } from "vue-i18n";
+import { useNotification } from "@/utils/common";
+
+interface FormType {
+  experience: ExperienceType[];
+}
+
+interface ExperienceType {
+  question: string;
+  content: string[];
+}
+
+const props = defineProps({
+  dialogData: {
+    type: Array as PropType<ExperienceType[]>,
+    default: () => [],
+  },
+  dialogType: {
+    type: String,
+    default: "create",
+  },
+});
+
+const defaultExperienceList = [
+  {
+    question: "",
+    content: [""],
+  },
+];
+
+const { t } = useI18n();
+const { antNotification } = useNotification();
+const emit = defineEmits(["close", "search"]);
+const typeMap = {
+  create: t("experience.create"),
+  edit: t("experience.edit"),
+} as const;
+const dialogTitle = computed(() => {
+  return typeMap[props.dialogType as keyof typeof typeMap];
+});
+const isEdit = computed(() => {
+  return props.dialogType === "edit";
+});
+
+const modelVisible = ref<boolean>(true);
+const submitLoading = ref<boolean>(false);
+const formRef = ref<FormInstance>();
+
+const form = reactive<FormType>({
+  experience: props.dialogData.length
+    ? props.dialogData
+    : defaultExperienceList,
+});
+
+const rules: FormRules = reactive({
+  question: [
+    {
+      required: true,
+      message: t("experience.valid.experience"),
+      trigger: "change",
+    },
+  ],
+  contentList: [
+    {
+      required: true,
+      type: "array",
+      message: t("experience.valid.content"),
+      trigger: "change",
+    },
+  ],
+  text: [
+    {
+      required: true,
+      message: t("experience.valid.content"),
+      trigger: "change",
+    },
+  ],
+});
+
+const handleAdd = () => {
+  form.experience.push({
+    question: "",
+    content: [""],
+  });
+};
+const handleDelete = (index: number) => {
+  form.experience.splice(index, 1);
+};
+const handleContentAdd = (content: string[]) => {
+  content.push("");
+};
+const handleContentDelete = (content: string[], index: number) => {
+  content.splice(index, 1);
+};
+
+// Submit
+const handleSubmit = () => {
+  formRef.value?.validate().then(() => {
+    submitLoading.value = true;
+    const { experience } = form;
+    const apiUrl = isEdit.value
+      ? requestExperienceUpdate(experience[0])
+      : requestExperienceCreate(experience);
+    apiUrl
+      .then((data: any) => {
+        const { code } = data;
+        if (code === 2001) {
+          handleSelectMode();
+        } else {
+          handleRefresh();
+
+          if (!isEdit.value)
+            antNotification(
+              "success",
+              t("common.success"),
+              t("request.experience.createSucc")
+            );
+        }
+      })
+      .catch((error: any) => {
+        console.error(error);
+      })
+      .finally(() => {
+        submitLoading.value = false;
+      });
+  });
+};
+const handleSelectMode = () => {
+  const { experience } = form;
+  Modal.confirm({
+    title: t("common.prompt"),
+    content: t("experience.selectTip"),
+    okText: t("experience.cover"),
+    cancelText: t("experience.increase"),
+    centered: true,
+    async onOk() {
+      const flag = false;
+      await requestExperienceConfirm(flag, experience);
+      handleRefresh();
+    },
+    async onCancel() {
+      const flag = true;
+      await requestExperienceConfirm(flag, experience);
+      handleRefresh();
+    },
+  });
+};
+
+//close
+const handleCancel = () => {
+  emit("close");
+};
+
+//close
+const handleRefresh = () => {
+  emit("search");
+  handleCancel();
+};
+</script>
+
+<style scoped lang="less">
+.enter-wrap {
+  width: 100%;
+  // max-height: 500px;
+  // overflow-y: auto;
+  .title-wrap {
+    font-size: 20px;
+    font-weight: 600;
+    margin-bottom: 16px;
+    color: var(--font-main-color);
+  }
+  .form-wrap {
+    .item-wrap {
+      padding: 16px 32px 16px 16px;
+      border: 1px solid var(--border-main-color);
+      position: relative;
+      margin-bottom: 16px;
+      border-radius: 6px;
+      .gt-wrap {
+        margin-bottom: 0;
+        :deep(.intel-form-item-control-input-content) {
+          display: block;
+        }
+        .flex-item {
+          flex: 1;
+          :deep(.intel-form-item-control-input-content) {
+            display: flex;
+            align-items: center;
+            gap: 6px;
+          }
+        }
+      }
+      .content-wrap {
+        background-color: var(--bg-card-color);
+        gap: 12px;
+        padding-right: 16px;
+        padding-bottom: 8px;
+        margin-bottom: 12px;
+        :deep(.intel-form-item) {
+          flex: 1;
+        }
+        .icon-wrap {
+          justify-content: end;
+        }
+      }
+      .add-wrap {
+        .flex-end;
+        gap: 6px;
+        cursor: pointer;
+        color: var(--color-primary);
+        &:hover {
+          color: var(--color-primary-hover);
+        }
+      }
+      .flex-wrap {
+        display: flex;
+        gap: 6px;
+        align-items: start;
+      }
+      .icon-wrap {
+        position: absolute;
+        top: 16px;
+        right: 12px;
+        cursor: pointer;
+        display: inline-flex;
+        gap: 8px;
+        width: 42px;
+        .anticon {
+          font-size: 16px;
+          &:hover {
+            color: var(--color-primary);
+          }
+          &.anticon-delete {
+            &:hover {
+              color: var(--color-error) !important;
+            }
+          }
+          &.anticon-minus-circle {
+            &:hover {
+              color: var(--color-error) !important;
+            }
+          }
+        }
+      }
+    }
+  }
+  .operate-wrap {
+    height: 28px;
+    border-radius: 4px;
+    cursor: pointer;
+    gap: 4px;
+    border: 1px dashed var(--border-main-color);
+    .vertical-center;
+    &:hover {
+      border: 1px dashed var(--color-primary-hover);
+      color: var(--color-primary-hover);
+    }
+  }
+}
+</style>
diff --git a/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/Experience/index.ts b/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/Experience/index.ts
new file mode 100644
index 0000000000..c9d1df62ed
--- /dev/null
+++ b/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/Experience/index.ts
@@ -0,0 +1,7 @@
+// Copyright (C) 2025 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+
+import UpdateDialog from "./UpdateDialog.vue";
+import ImportDialog from "./ImportDialog.vue";
+
+export { UpdateDialog, ImportDialog };
diff --git a/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/KnowledgeDetail.vue b/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/KnowledgeDetail.vue
new file mode 100644
index 0000000000..64b13e320d
--- /dev/null
+++ b/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/KnowledgeDetail.vue
@@ -0,0 +1,336 @@
+<template>
+  <div class="detail-wrap">
+    <div class="upload-wrap">
+      <a-upload-dragger
+        v-model:file-list="uploadFileList"
+        name="file"
+        multiple
+        :showUploadList="false"
+        accept=".csv,.doc,.docx,.enex,.epub,.html,.md,.odt,.pdf,.ppt,.pptx,.txt,"
+        :before-upload="handleBeforeUpload"
+        :custom-request="customRequest"
+      >
+        <SvgIcon
+          name="icon-cloudupload-fill"
+          :size="50"
+          :style="{ color: 'var(--font-tip-color)' }"
+        />
+        <p class="upload-text">{{ $t("common.uploadTip") }}</p>
+        <div class="upload-tip">
+          <p>
+            {{ $t("knowledge.uploadTip") }}
+          </p>
+        </div>
+      </a-upload-dragger>
+    </div>
+    <div class="tip-wrap" v-if="startUpload">
+      <div class="tip-text">
+        <ExclamationCircleFilled :style="{ fontSize: '14px' }" />
+        <span>{{ $t("knowledge.waitTip") }}</span>
+      </div>
+      <div class="rated-wrap slider-wrap">
+        <span>{{ $t("knowledge.done") }}:</span>
+        <a-slider
+          v-model:value="uploadedCount"
+          :min="0"
+          :max="totalFiles"
+          disabled
+        /><span
+          >{{ uploadedCount }}/{{ totalFiles }}
+          <span class="pl-8">
+            {{ $t("knowledge.successfully") }}:
+            <span class="is-success">{{ successCount }}</span>
+            {{ $t("knowledge.failed") }}:
+            <span class="is-failed">{{ failCount }}</span></span
+          >
+        </span>
+      </div>
+    </div>
+    <PartialLoading :visible="loading" />
+    <template v-if="!loading">
+      <a-empty v-if="notFile" :description="$t('knowledge.notFileTip')" />
+      <div class="files-container" v-else>
+        <a-row type="flex" wrap :gutter="[20, 20]">
+          <a-col
+            :span="8"
+            v-for="[key, value] in Object.entries(knowledgeData.file_map)"
+            :key="key"
+          >
+            <div class="file-item">
+              <div class="left-wrap">
+                <FileDoneOutlined
+                  :style="{
+                    color: 'var(--color-success)',
+                    fontSize: '20px',
+                  }"
+                />
+                <a-tooltip placement="topLeft" :title="key">
+                  <div class="file-name">{{ key }}</div>
+                </a-tooltip>
+              </div>
+              <div class="right-wrap">
+                <a-tooltip placement="top" :title="$t('common.delete')">
+                  <DeleteFilled
+                    class="delete-icon"
+                    @click="handleFileDelete(value as string)"
+                  />
+                </a-tooltip>
+              </div>
+            </div>
+          </a-col>
+        </a-row></div
+    ></template>
+  </div>
+</template>
+
+<script setup lang="ts" name="KnowledgeBaseDetail">
+import { ref, reactive, createVNode, inject, onMounted } from "vue";
+import {
+  requestKnowledgeBaseRelation,
+  getKnowledgeBaseDetailByName,
+  requestFileDelete,
+  requestUploadFileUrl,
+} from "@/api/knowledgeBase";
+import {
+  CloseCircleFilled,
+  DeleteFilled,
+  FileDoneOutlined,
+  ExclamationCircleFilled,
+} from "@ant-design/icons-vue";
+import { message, Modal, UploadFile, UploadProps } from "ant-design-vue";
+import { useI18n } from "vue-i18n";
+import eventBus from "@/utils/mitt";
+import type { UploadRequestOption } from "ant-design-vue";
+
+interface KbType {
+  name: string;
+}
+const { t } = useI18n();
+const kbInfo = inject<KbType>("kbInfo");
+const uploadFileList = ref([]);
+const knowledgeData = reactive<EmptyObjectType>({});
+const pendingFiles = ref<UploadRequestOption[]>([]);
+let isUploading = ref<boolean>(false);
+const totalFiles = ref<number>(0);
+const uploadedCount = ref<number>(0);
+const successCount = ref<number>(0);
+const failCount = ref<number>(0);
+const startUpload = ref<boolean>(false);
+const loading = ref<boolean>(false);
+
+const notFile = computed(() => {
+  const { file_map = {} } = knowledgeData;
+  return Object.keys(file_map).length === 0;
+});
+
+const queryKnowledgeBaseDetail = async () => {
+  getKnowledgeBaseDetailByName(kbInfo?.name!)
+    .then((data: any) => {
+      Object.assign(knowledgeData, data);
+    })
+    .catch((error: any) => {
+      console.error(error);
+    })
+    .finally(() => {
+      loading.value = false;
+    });
+};
+const handleBeforeUpload = (file: UploadProps["fileList"][number]) => {
+  const isFileSize = file.size / 1024 / 1024 < 200;
+
+  if (!isFileSize) {
+    message.error(t("knowledge.uploadValid"));
+    return;
+  }
+
+  return isFileSize;
+};
+
+const customRequest = (options: UploadRequestOption) => {
+  pendingFiles.value.push(options);
+  totalFiles.value += 1;
+  startUpload.value = true;
+  if (!isUploading.value) {
+    isUploading.value = true;
+    uploadInBatches();
+  }
+};
+
+const uploadInBatches = async () => {
+  while (pendingFiles.value.length > 0) {
+    const batch = pendingFiles.value.splice(0, 20);
+
+    await Promise.all(
+      batch.map(async (options: any) => {
+        const { file, onSuccess, onError } = options;
+        const uploadFile = file as UploadFile;
+
+        try {
+          const { name } = knowledgeData;
+          const res = await requestUploadFileUrl(name, { file });
+          await requestKnowledgeBaseRelation(name, { local_path: res });
+
+          onSuccess?.(res, uploadFile as any);
+          handleSuccess(uploadFile);
+          successCount.value += 1;
+        } catch (err: any) {
+          onError?.(err);
+          failCount.value += 1;
+        } finally {
+          uploadedCount.value += 1;
+        }
+      })
+    );
+    queryKnowledgeBaseDetail();
+  }
+  handleRefresh();
+  isUploading.value = false;
+  setTimeout(() => {
+    startUpload.value = false;
+    totalFiles.value = 0;
+    uploadedCount.value = 0;
+    successCount.value = 0;
+    failCount.value = 0;
+  }, 5000);
+};
+
+const handleSuccess = (file: UploadFile) => {
+  uploadFileList.value = uploadFileList.value.filter(
+    (item: UploadFile) => item.uid !== file.uid
+  );
+};
+const handleFileDelete = (local_path: string) => {
+  Modal.confirm({
+    title: t("common.delete"),
+    icon: createVNode(CloseCircleFilled, { class: "error-icon" }),
+    content: t("knowledge.deleteFileTip"),
+    okText: t("common.confirm"),
+    okType: "danger",
+    async onOk() {
+      const { name } = knowledgeData;
+      await requestFileDelete(name, { local_path });
+      queryKnowledgeBaseDetail();
+      handleRefresh();
+    },
+  });
+};
+
+const handleRefresh = () => {
+  eventBus.emit("refresh");
+};
+
+onMounted(() => {
+  loading.value = true;
+  queryKnowledgeBaseDetail();
+});
+</script>
+
+<style lang="less" scoped>
+.detail-wrap {
+  height: 100%;
+  .flex-column;
+}
+.upload-wrap {
+  padding: 16px;
+  :deep(.intel-upload-drag) {
+    background-color: var(--bg-content-color);
+  }
+  .upload-text {
+    color: var(--font-text-color);
+    margin: 8px 0;
+    font-weight: 500;
+    font-size: 16px;
+  }
+  .upload-tip {
+    color: var(--font-tip-color);
+    font-size: 12px;
+    line-height: 1.4;
+    margin-top: 12px;
+  }
+}
+.files-container {
+  flex: 1;
+  width: 100%;
+  padding: 12px 16px;
+  .file-item {
+    padding: 12px;
+    background-color: var(--bg-content-color);
+    border: 1px solid var(--border-main-color);
+    border-radius: 6px;
+    .flex-between;
+    &:hover {
+      .card-shadow;
+    }
+    .left-wrap {
+      flex: 1;
+      min-width: 0;
+      .flex-left;
+      gap: 6px;
+      .file-name {
+        flex: 1;
+        color: var(--font-main-color);
+        .single-ellipsis;
+      }
+    }
+    .right-wrap {
+      .delete-icon {
+        color: var(--font-tip-color);
+        &:hover {
+          color: var(--color-error);
+        }
+      }
+    }
+  }
+}
+.intel-empty {
+  margin: 200px auto;
+}
+.tip-wrap {
+  margin: 0 20px;
+  border: 1px solid var(--border-warning);
+  border-left: 3px solid var(--color-second-warning);
+  background-color: var(--color-warningBg);
+  color: var(--color-second-warning);
+  padding: 8px 12px 0 12px;
+  border-radius: 0 4px 4px 0;
+  margin-bottom: 12px;
+  font-size: 12px;
+  .flex-between;
+  .tip-text {
+    display: flex;
+    gap: 4px;
+    align-items: center;
+  }
+  .rated-wrap {
+    width: 400px;
+    display: flex;
+    gap: 4px;
+    align-items: center;
+    :deep(.intel-slider-horizontal) {
+      flex: 1;
+      top: -2px;
+      .intel-slider-rail {
+        height: 8px;
+        border-radius: 4px;
+      }
+      .intel-slider-track {
+        height: 8px;
+        border-radius: 4px;
+        background-color: var(--color-primary-tip) !important;
+      }
+      .intel-slider-handle::after {
+        top: 1px;
+        background-color: var(--color-primary-tip) !important;
+        box-shadow: 0 0 0 2px var(--color-primary-second) !important;
+      }
+    }
+  }
+  .is-success {
+    .pr-6;
+    color: var(--color-success);
+  }
+  .is-failed {
+    color: var(--color-error);
+  }
+}
+</style>
diff --git a/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/KnowledgeDetial.vue b/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/KnowledgeDetial.vue
deleted file mode 100644
index 290a85cd8e..0000000000
--- a/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/KnowledgeDetial.vue
+++ /dev/null
@@ -1,302 +0,0 @@
-<template>
-  <div class="kb-detial-container">
-    <div class="header-wrap">
-      <div class="info-wrap">
-        <div class="name-wrap">{{ knowledgeData.name }}</div>
-        <div class="des-wrap" v-if="knowledgeData.description">
-          {{ knowledgeData.description }}
-        </div>
-      </div>
-      <div class="button-wrap">
-        <a-button
-          type="primary"
-          ghost
-          :icon="h(RollbackOutlined)"
-          @click="handleBack"
-          >{{ $t("common.back") }}</a-button
-        >
-      </div>
-    </div>
-    <div class="upload-wrap">
-      <a-upload-dragger
-        v-model:file-list="uploadFileList"
-        name="file"
-        multiple
-        :max-count="20"
-        :showUploadList="false"
-        :action="uploadFileApi"
-        accept=".csv,.doc,.docx,.enex,.epub,.html,.md,.odt,.pdf,.ppt,.pptx,.txt,"
-        :before-upload="handleBeforeUpload"
-        @change="handleChange"
-      >
-        <SvgIcon
-          name="icon-cloudupload-fill"
-          :size="50"
-          :style="{ color: 'var(--font-tip-color)' }"
-        />
-        <p class="upload-text">{{ $t("common.uploadTip") }}</p>
-        <div class="upload-tip">
-          <p>
-            {{ $t("knowledge.uploadTip") }}
-          </p>
-        </div>
-      </a-upload-dragger>
-    </div>
-
-    <a-empty v-if="notFile" :description="$t('knowledge.notFileTip')" />
-    <div class="files-container" v-else>
-      <a-row type="flex" wrap :gutter="[20, 20]">
-        <a-col
-          :span="8"
-          v-for="[key, value] in Object.entries(knowledgeData.file_map)"
-          :key="key"
-        >
-          <div class="file-item">
-            <div class="left-wrap">
-              <FileDoneOutlined
-                :style="{
-                  color: 'var(--color-success)',
-                  fontSize: '20px',
-                }"
-              />
-              <a-tooltip placement="topLeft" :title="key">
-                <div class="file-name">{{ key }}</div>
-              </a-tooltip>
-            </div>
-            <div class="right-wrap">
-              <a-tooltip placement="top" :title="$t('common.delete')">
-                <DeleteFilled
-                  class="delete-icon"
-                  @click="handleFileDelete(value as string)"
-                />
-              </a-tooltip>
-            </div>
-          </div>
-        </a-col>
-      </a-row>
-    </div>
-  </div>
-</template>
-
-<script setup lang="ts" name="KnowledgeBaseDetial">
-import { ref, reactive, createVNode, h } from "vue";
-import {
-  requestKnowledgeBaseRelation,
-  getKnowledgeBaseDetialByName,
-  requestFileDelete,
-  uploadFileUrl,
-} from "@/api/knowledgeBase";
-import { useNotification } from "@/utils/common";
-import {
-  CloseCircleFilled,
-  DeleteFilled,
-  RollbackOutlined,
-  FileDoneOutlined,
-} from "@ant-design/icons-vue";
-import { message, Modal, UploadFile, UploadProps } from "ant-design-vue";
-import { useI18n } from "vue-i18n";
-import { NextLoading } from "@/utils/loading";
-import eventBus from "@/utils/mitt";
-
-const props = defineProps({
-  kbName: {
-    type: String,
-    default: "",
-  },
-});
-
-const { t } = useI18n();
-const emit = defineEmits(["back"]);
-const { antNotification } = useNotification();
-const uploadFileList = ref([]);
-const knowledgeData = reactive<EmptyObjectType>({});
-const notFile = computed(() => {
-  const { file_map = {} } = knowledgeData;
-  return Object.keys(file_map).length === 0;
-});
-const uploadFileApi = computed(() => {
-  return uploadFileUrl + knowledgeData.name;
-});
-
-const queryKnowledgeBaseDetial = async () => {
-  const data: any = await getKnowledgeBaseDetialByName(props.kbName);
-  Object.assign(knowledgeData, data);
-};
-const handleBeforeUpload = (file: UploadProps["fileList"][number]) => {
-  const isFileSize = file.size / 1024 / 1024 < 200;
-
-  if (!isFileSize) {
-    message.error(t("knowledge.uploadValid"));
-  }
-
-  return isFileSize;
-};
-const handleChange = ({
-  fileList,
-  file,
-}: {
-  fileList: UploadFile[];
-  file: UploadFile;
-}) => {
-  const el = <HTMLElement>document.querySelector(".loading-next");
-  if (!el) NextLoading.start();
-  const { response, status } = file;
-  const { name } = knowledgeData;
-  try {
-    if (status === "done") {
-      requestKnowledgeBaseRelation(name, {
-        local_path: response,
-      });
-      handleSuccess(file);
-    } else if (status === "error") {
-      antNotification("error", t("common.error"), response.detail);
-    }
-
-    const isAllEnd = fileList.every((file: any) => file.status !== "uploading");
-
-    if (isAllEnd) {
-      NextLoading.done();
-      setTimeout(() => {
-        queryKnowledgeBaseDetial();
-        handleRefresh();
-      }, 100);
-    }
-  } catch (error) {
-    console.error(error);
-    if (NextLoading) NextLoading.done();
-  }
-};
-const handleSuccess = (file: UploadFile) => {
-  uploadFileList.value = uploadFileList.value.filter(
-    (item: UploadFile) => item.uid !== file.uid
-  );
-};
-const handleFileDelete = (local_path: string) => {
-  Modal.confirm({
-    title: t("common.delete"),
-    icon: createVNode(CloseCircleFilled, { class: "error-icon" }),
-    content: t("knowledge.deleteFileTip"),
-    okText: t("common.confirm"),
-    okType: "danger",
-    async onOk() {
-      const { name } = knowledgeData;
-      await requestFileDelete(name, { local_path });
-      queryKnowledgeBaseDetial();
-      handleRefresh();
-    },
-  });
-};
-
-const handleBack = () => {
-  emit("back");
-  eventBus.emit("reset");
-};
-const handleRefresh = () => {
-  eventBus.emit("refresh");
-};
-
-watch(
-  () => props.kbName,
-  (kbName) => {
-    if (kbName) queryKnowledgeBaseDetial();
-  },
-  { immediate: true, deep: true }
-);
-</script>
-
-<style lang="less" scoped>
-.kb-detial-container {
-  display: block !important;
-  .flex-column;
-  .header-wrap {
-    padding: 0 16px;
-    height: 60px;
-    border-bottom: 1px solid var(--border-main-color);
-    .flex-between;
-    gap: 16px;
-    min-width: 0;
-    .info-wrap {
-      flex: 1;
-      .flex-column;
-      gap: 4px;
-      min-width: 0;
-      .name-wrap {
-        font-size: 16px;
-        font-weight: 600;
-        flex: 1;
-        min-width: 0;
-        line-height: 16px;
-        .single-ellipsis;
-      }
-      .des-wrap {
-        color: var(--font-info-color);
-        font-size: 12px;
-        .single-ellipsis;
-      }
-    }
-    .button-wrap {
-      .vertical-center;
-      gap: 4px;
-    }
-  }
-  .upload-wrap {
-    padding: 16px;
-    :deep(.intel-upload-drag) {
-      background-color: var(--bg-content-color);
-    }
-    .upload-text {
-      color: var(--font-text-color);
-      margin: 8px 0;
-      font-weight: 500;
-      font-size: 16px;
-    }
-    .upload-tip {
-      color: var(--font-tip-color);
-      font-size: 12px;
-      line-height: 1.4;
-      margin-top: 12px;
-    }
-  }
-  .files-container {
-    flex: 1;
-    width: 100%;
-    padding: 12px 16px;
-    .file-item {
-      padding: 12px;
-      background-color: var(--bg-content-color);
-      border: 1px solid var(--border-main-color);
-      border-radius: 6px;
-      .flex-between;
-      &:hover {
-        .card-shadow;
-      }
-      .left-wrap {
-        flex: 1;
-        min-width: 0;
-        .flex-left;
-        gap: 6px;
-        .file-name {
-          flex: 1;
-          color: var(--font-main-color);
-          .single-ellipsis;
-        }
-      }
-      .right-wrap {
-        .delete-icon {
-          color: var(--font-tip-color);
-          &:hover {
-            color: var(--color-error);
-          }
-        }
-      }
-    }
-  }
-  .intel-empty {
-    flex: 1;
-    display: flex;
-    flex-direction: column;
-    justify-content: center;
-    align-items: center;
-  }
-}
-</style>
diff --git a/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/SelectTypeDialog.vue b/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/SelectTypeDialog.vue
new file mode 100644
index 0000000000..8b9ab7978e
--- /dev/null
+++ b/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/SelectTypeDialog.vue
@@ -0,0 +1,134 @@
+<template>
+  <a-modal
+    v-model:open="modelVisible"
+    width="800px"
+    centered
+    destroyOnClose
+    :keyboard="false"
+    :maskClosable="false"
+    :footer="null"
+    :aria-hidden="false"
+    @cancel="handleClose"
+    class="import-dialog"
+  >
+    <div class="guide-wrap">
+      <div class="guide-title">{{ $t("knowledge.selectTitle") }}</div>
+      <div class="guide-text">{{ $t("knowledge.selectDes") }}</div>
+      <div class="card-wrap">
+        <div class="item-wrap">
+          <div class="left-wrap">
+            <SvgIcon name="icon-knowledge" inherit :size="32" />
+          </div>
+          <div class="right-wrap">
+            <div class="title">{{ $t("knowledge.title") }}</div>
+            <div class="des">
+              {{ $t("knowledge.kbDes") }}
+            </div>
+            <a-button
+              class="special-button-primary"
+              :icon="h(PlusOutlined)"
+              @click="handleCreate"
+              >{{ $t("quickStart.create") }}</a-button
+            >
+          </div>
+        </div>
+        <div class="item-wrap">
+          <div class="left-wrap">
+            <SvgIcon name="icon-experience" inherit :size="32" />
+          </div>
+          <div class="right-wrap">
+            <div class="title">{{ $t("knowledge.experience") }}</div>
+            <div class="des">
+              {{ $t("knowledge.experienceDes") }}
+            </div>
+            <a-button
+              :class="{
+                'special-button-primary': true,
+                'is-disabled': created,
+              }"
+              :icon="h(PlusOutlined)"
+              :disabled="created"
+              @click="handleCreateExperience"
+              >{{ $t("quickStart.create") }}</a-button
+            >
+          </div>
+        </div>
+      </div>
+    </div>
+  </a-modal>
+</template>
+
+<script lang="ts" setup name="SelectTypeDialog">
+import { PlusOutlined } from "@ant-design/icons-vue";
+import { h } from "vue";
+
+const props = defineProps({
+  created: {
+    type: Boolean,
+    default: false,
+  },
+});
+
+const emit = defineEmits(["createKB", "close"]);
+const modelVisible = ref<boolean>(true);
+const handleCreate = () => {
+  emit("createKB", "knowledge");
+  handleClose();
+};
+const handleCreateExperience = async () => {
+  emit("createKB", "experience");
+  handleClose();
+};
+const handleClose = () => {
+  emit("close");
+};
+</script>
+
+<style scoped lang="less">
+.guide-wrap {
+  padding: 24px 0;
+  .guide-title {
+    font-size: 24px;
+    font-weight: 600;
+    color: var(--font-main-color);
+    text-align: center;
+  }
+  .guide-text {
+    text-align: center;
+    color: var(--font-tip-color);
+  }
+  .card-wrap {
+    display: flex;
+    gap: 32px;
+    margin-top: 24px;
+    .item-wrap {
+      flex: 1;
+      padding: 20px;
+      border-radius: 6px;
+      box-shadow: var(--bg-gradient-shadow);
+      display: flex;
+      gap: 12px;
+      .left-wrap {
+        .pt-6;
+        color: var(--color-second-primaryBg);
+      }
+      .right-wrap {
+        flex: 1;
+        .title {
+          font-size: 18px;
+          font-weight: 500;
+          line-height: 28px;
+          color: var(--font-main-color);
+          white-space: pre-wrap;
+        }
+        .des {
+          margin-top: 12px;
+          margin-bottom: 20px;
+          line-height: 20px;
+          color: var(--font-text-color);
+        }
+      }
+    }
+  }
+}
+</style>
diff --git a/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/UpdateDialog.vue b/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/UpdateDialog.vue
index f987ff5cb4..e95e7436f6 100644
--- a/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/UpdateDialog.vue
+++ b/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/UpdateDialog.vue
@@ -17,14 +17,45 @@
       autocomplete="off"
       :label-col="{ style: { width: '100px' } }"
     >
-      <a-form-item :label="$t('knowledge.name')" name="name">
+      <a-form-item
+        :label="$t('knowledge.type')"
+        name="comp_subtype"
+        v-if="!isExperience"
+      >
+        <a-radio-group
+          v-model:value="form.comp_subtype"
+          @change="handleTypeChange"
+          :disabled="isEdit"
+        >
+          <a-radio value="origin_kb">{{ $t("knowledge.original") }}</a-radio>
+          <a-radio value="kbadmin_kb">{{ $t("knowledge.kbadmin") }}</a-radio>
+        </a-radio-group>
+      </a-form-item>
+      <a-form-item :label="$t('knowledge.name')" name="name" v-if="isOriginal">
         <a-input
           v-model:value.trim="form.name"
           :maxlength="30"
-          :disabled="isEdit"
+          :disabled="isEdit || isExperience"
           :placeholder="$t('knowledge.nameValid1')"
         />
       </a-form-item>
+      <a-form-item
+        :label="$t('knowledge.name')"
+        :rules="rules.kbName"
+        name="name"
+        v-else
+      >
+        <a-select
+          showSearch
+          v-model:value="form.name"
+          :placeholder="$t('knowledge.nameRequired')"
+          :disabled="isEdit || isExperience"
+        >
+          <a-select-option v-for="item in kbList" :key="item" :value="item">{{
+            item
+          }}</a-select-option>
+        </a-select>
+      </a-form-item>
       <a-form-item :label="$t('knowledge.des')">
         <a-textarea
           v-model:value.trim="form.description"
@@ -34,7 +65,7 @@
         />
       </a-form-item>
       <a-form-item :label="$t('pipeline.isActive')" name="active">
-        <a-radio-group v-model:value="form.active" :disabled="isActivated">
+        <a-radio-group v-model:value="form.active">
           <a-radio :value="true">{{ $t("pipeline.activated") }}</a-radio>
           <a-radio :value="false">{{ $t("pipeline.inactive") }}</a-radio>
         </a-radio-group>
@@ -59,10 +90,11 @@
 import {
   requestKnowledgeBaseCreate,
   requestKnowledgeBaseUpdate,
+  getkbadminList,
 } from "@/api/knowledgeBase";
 import { isValidName } from "@/utils/validate";
 import { FormInstance } from "ant-design-vue";
-import { computed, ref } from "vue";
+import { computed, ref, onMounted } from "vue";
 import { useI18n } from "vue-i18n";
 
 const props = defineProps({
@@ -74,11 +106,17 @@ const props = defineProps({
     type: String,
     default: "create",
   },
+  dialogFlag: {
+    type: String,
+    default: "knowledge",
+  },
 });
 interface FormType {
-  name: string;
+  name: string | undefined;
   description: string;
+  comp_type: string;
   active: boolean;
+  comp_subtype: string;
 }
 
 const validateName = async (rule: any, value: string) => {
@@ -89,7 +127,6 @@ const validateName = async (rule: any, value: string) => {
   if (len < 2 || len > 30) {
     return Promise.reject(t("knowledge.nameValid2"));
   }
-  console.log(isValidName(value));
   if (!isValidName(value)) {
     return Promise.reject(t("knowledge.nameValid3"));
   }
@@ -98,9 +135,11 @@ const validateName = async (rule: any, value: string) => {
 
 const { t } = useI18n();
 const emit = defineEmits(["close", "switch"]);
+const { dialogFlag } = props;
+
 const typeMap = {
-  create: t("knowledge.create"),
-  edit: t("knowledge.edit"),
+  create: t(`${dialogFlag}.create`),
+  edit: t(`${dialogFlag}.edit`),
 } as const;
 const dialogTitle = computed(() => {
   return typeMap[props.dialogType as keyof typeof typeMap];
@@ -108,20 +147,39 @@ const dialogTitle = computed(() => {
 const isEdit = computed(() => {
   return props.dialogType === "edit";
 });
-const isActivated = computed(() => {
-  return props.dialogData?.active;
+const isExperience = computed(() => {
+  return props.dialogFlag === "experience";
+});
+
+const isOriginal = computed(() => {
+  return form.comp_subtype === "origin_kb";
 });
 const modelVisible = ref<boolean>(true);
 const submitLoading = ref<boolean>(false);
 const formRef = ref<FormInstance>();
-const { name = "", description = "", active = false } = props.dialogData;
+const {
+  comp_subtype = "origin_kb",
+  name = undefined,
+  description = "",
+  active = false,
+  experience_active = false,
+} = props.dialogData;
 const form = reactive<FormType>({
-  name,
+  comp_subtype,
+  name: isExperience.value ? "Experience" : name,
   description,
-  active,
+  comp_type: dialogFlag,
+  active: isExperience.value ? experience_active : active,
 });
-
-const rules = reactive({
+const kbList = ref<EmptyArrayType>([]);
+const rules: FormRules = reactive({
+  comp_subtype: [
+    {
+      required: true,
+      message: t("knowledge.typeValid"),
+      trigger: "change",
+    },
+  ],
   name: [
     {
       required: true,
@@ -129,6 +187,13 @@ const rules = reactive({
       trigger: ["blur", "change"],
     },
   ],
+  kbName: [
+    {
+      required: true,
+      message: t("knowledge.nameRequired"),
+      trigger: "change",
+    },
+  ],
   active: [
     {
       required: true,
@@ -137,17 +202,36 @@ const rules = reactive({
     },
   ],
 });
+const handleTypeChange = () => {
+  form.name = undefined;
+};
+const queryKbadmin = async () => {
+  const data: any = await getkbadminList();
+  kbList.value = [].concat(data);
+};
+// Format parameter
+const formatFormParam = () => {
+  const { name, description, comp_type, active, comp_subtype } = form;
+  return {
+    name,
+    description,
+    comp_type,
+    comp_subtype: !isExperience.value ? comp_subtype : undefined,
+    active: !isExperience.value ? active : undefined,
+    experience_active: isExperience.value ? active : undefined,
+  };
+};
 // Submit
 const handleSubmit = () => {
   formRef.value?.validate().then(() => {
     submitLoading.value = true;
     const { name } = form;
-    const apiUrl =
-      props.dialogType === "edit"
-        ? requestKnowledgeBaseUpdate
-        : requestKnowledgeBaseCreate;
 
-    apiUrl(form)
+    const apiUrl = isEdit.value
+      ? requestKnowledgeBaseUpdate
+      : requestKnowledgeBaseCreate;
+
+    apiUrl(formatFormParam())
       .then(() => {
         emit("switch", name);
         handleCancel();
@@ -165,6 +249,9 @@ const handleSubmit = () => {
 const handleCancel = () => {
   emit("close");
 };
+onMounted(() => {
+  queryKbadmin();
+});
 </script>
 
 <style scoped lang="less">
diff --git a/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/index.ts b/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/index.ts
index 7de279c52c..ebc0eee355 100644
--- a/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/index.ts
+++ b/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/index.ts
@@ -2,5 +2,8 @@
 // SPDX-License-Identifier: Apache-2.0
 
 import UpdateDialog from "./UpdateDialog.vue";
+import SelectTypeDialog from "./SelectTypeDialog.vue";
+import KnowledgeDetail from "./KnowledgeDetail.vue";
+import ExperienceDetail from "./Experience/ExperienceDetail.vue";
 
-export { UpdateDialog };
+export { UpdateDialog, SelectTypeDialog, KnowledgeDetail, ExperienceDetail };
diff --git a/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/index.vue b/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/index.vue
index 9c48a2e122..b8d2ecdc5e 100644
--- a/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/index.vue
+++ b/EdgeCraftRAG/ui/vue/src/views/chatbot/components/KnowledgeBase/index.vue
@@ -2,7 +2,7 @@
   <div class="knowledge-base">
     <div class="menu-container">
       <div class="header-menu">
-        <a-button type="primary" @click="handleCreate">
+        <a-button type="primary" block @click="handleCreateSelect">
           <template #icon>
             <PlusOutlined />
           </template>
@@ -16,19 +16,44 @@
           :key="item.idx"
           @click="handleView(item)"
         >
-          <span class="active-icon" v-if="item.active"
+          <span
+            :class="{
+              'active-icon': true,
+              'is-experience': item.comp_type === 'experience',
+            }"
+            v-if="item.active || item.experience_active"
             ><CheckOutlined :style="{ fontSize: '12px' }"
           /></span>
           <div class="left-wrap">
             <SvgIcon
-              name="icon-knowledge"
+              :name="
+                item.comp_type === 'experience'
+                  ? 'icon-experience'
+                  : 'icon-knowledge'
+              "
               :style="{ color: 'var(--color-primary-second)' }"
             />
             <div class="des-wrap">
-              <div class="name-wrap">{{ item.name }}</div>
+              <div class="flex-left">
+                <div class="name-wrap">
+                  {{ item.name }}
+                </div>
+                <template v-if="item.comp_type === 'experience'">
+                  <span class="tag-wrap"> {{ $t("experience.unique") }}</span>
+                </template>
+                <template v-if="item?.comp_subtype === 'kbadmin_kb'">
+                  <span class="tag-wrap">kbadmin</span>
+                </template>
+              </div>
               <div class="total-wrap">
-                {{ $t("knowledge.total") }}
-                {{ Object.keys(item.file_map).length || 0 }}
+                <template v-if="item.comp_type === 'experience'">
+                  {{ $t("experience.total") }}
+                  {{ item.total }}
+                </template>
+                <template v-else-if="item?.comp_subtype === 'origin_kb'">
+                  {{ $t("knowledge.total") }}
+                  {{ item.total }}</template
+                >
               </div>
             </div>
           </div>
@@ -37,16 +62,44 @@
               <a @click.prevent class="expand-wrap"> ... </a>
               <template #overlay>
                 <a-menu>
-                  <a-menu-item
-                    key="activate"
-                    :disabled="item.active"
-                    @click="handleSwitchState(item)"
-                  >
-                    <CheckCircleFilled
-                      :style="{ color: 'var(--color-success)' }"
-                    />
-                    {{ $t("common.active") }}</a-menu-item
-                  >
+                  <template v-if="item.comp_type === 'knowledge'">
+                    <a-menu-item
+                      key="activate"
+                      @click="handleSwitchState(item)"
+                    >
+                      <template v-if="!item.active">
+                        <CheckCircleFilled
+                          :style="{ color: 'var(--color-success)' }"
+                        />
+                        {{ $t("common.active") }}
+                      </template>
+                      <template v-else>
+                        <PauseCircleFilled
+                          :style="{ color: 'var(--color-error)' }"
+                        />
+                        {{ $t("common.deactivate") }}
+                      </template>
+                    </a-menu-item>
+                  </template>
+                  <template v-else>
+                    <a-menu-item
+                      key="experience_active"
+                      @click="handleSwitchExperienceState(item)"
+                    >
+                      <template v-if="!item.experience_active">
+                        <CheckCircleFilled
+                          :style="{ color: 'var(--color-success)' }"
+                        />
+                        {{ $t("common.active") }}</template
+                      >
+                      <template v-else>
+                        <PauseCircleFilled
+                          :style="{ color: 'var(--color-error)' }"
+                        />
+                        {{ $t("common.deactivate") }}
+                      </template>
+                    </a-menu-item>
+                  </template>
                   <a-menu-item key="update" @click="handleUpdate(item)">
                     <EditFilled
                       :style="{ color: 'var(--color-primary-second)' }"
@@ -56,7 +109,7 @@
                   <a-menu-item
                     key="delete"
                     @click="handleDelete(item)"
-                    :disabled="item.active"
+                    :disabled="item.active || item.experience_active"
                   >
                     <DeleteFilled :style="{ color: 'var(--color-error)' }" />
                     {{ $t("common.delete") }}</a-menu-item
@@ -73,18 +126,25 @@
       v-if="updateDialog.visible"
       :dialog-data="updateDialog.data"
       :dialog-type="updateDialog.type"
+      :dialog-flag="updateDialog.flag"
       @switch="handleSwitch"
       @close="updateDialog.visible = false"
     />
+    <SelectTypeDialog
+      v-if="selectTypeDialog.visible"
+      :created="isCreated"
+      @close="selectTypeDialog.visible = false"
+      @createKB="handleCreate"
+    />
   </div>
 </template>
 
 <script lang="ts" setup name="KnowledgeBase">
 import { onMounted, reactive, createVNode } from "vue";
-import { UpdateDialog } from "./index";
+import { UpdateDialog, SelectTypeDialog } from "./index";
 import {
   getKnowledgeBaseList,
-  getKnowledgeBaseDetialByName,
+  getKnowledgeBaseDetailByName,
   requestKnowledgeBaseUpdate,
   requestKnowledgeBaseDelete,
 } from "@/api/knowledgeBase";
@@ -95,7 +155,7 @@ import {
   EditFilled,
   CheckCircleFilled,
   CloseCircleFilled,
-  FileDoneOutlined,
+  PauseCircleFilled,
 } from "@ant-design/icons-vue";
 import { useI18n } from "vue-i18n";
 import { Modal } from "ant-design-vue";
@@ -108,35 +168,49 @@ const selectedKB = ref<string>("");
 const updateDialog = reactive<DialogType>({
   visible: false,
   type: "create",
+  flag: "knowledge",
   data: {},
 });
+const selectTypeDialog = reactive<DialogType>({
+  visible: false,
+});
 
 const kbList = ref<EmptyArrayType>([]);
-
+const isCreated = computed(() =>
+  kbList.value.some((item) => item.comp_type === "experience")
+);
 const queryKnowledgeBaseList = async () => {
   const data: any = await getKnowledgeBaseList();
 
   kbList.value = [].concat(data);
 };
+const handleCreateSelect = () => {
+  selectTypeDialog.visible = true;
+};
 //create
-const handleCreate = () => {
+const handleCreate = (flag = "create") => {
   updateDialog.type = "create";
+  updateDialog.flag = flag;
   updateDialog.data = {};
   updateDialog.visible = true;
 };
 //edit
 const handleUpdate = async (row: EmptyObjectType) => {
-  const data: any = await getKnowledgeBaseDetialByName(row.name);
+  const data: any = await getKnowledgeBaseDetailByName(row.name);
 
   updateDialog.data = data;
   updateDialog.type = "edit";
+  updateDialog.flag = row.comp_type;
   updateDialog.visible = true;
 };
 //detail
 const handleView = async (row: EmptyObjectType) => {
-  const { idx, name } = row;
-  selectedKB.value = idx;
-  emit("view", name);
+  const { idx } = row;
+
+  if (row.comp_subtype !== "kbadmin_kb") {
+    selectedKB.value = idx;
+    emit("view", row);
+  }
 };
 //delete
 const handleDelete = (row: EmptyObjectType) => {
@@ -153,21 +227,40 @@ const handleDelete = (row: EmptyObjectType) => {
 
       if (selectedKB.value === idx) {
         selectedKB.value = "";
-        emit("view", "");
+        emit("view", { name: "" });
       }
     },
   });
 };
 //activate
 const handleSwitchState = (row: EmptyObjectType) => {
-  const { name } = row;
+  const { name, active } = row;
 
   Modal.confirm({
     title: t("common.prompt"),
     content: t("knowledge.activeTip"),
     okText: t("common.confirm"),
     async onOk() {
-      await requestKnowledgeBaseUpdate({ name, active: true });
+      await requestKnowledgeBaseUpdate({ name, active: !active });
+      handleSearch();
+    },
+  });
+};
+const handleSwitchExperienceState = (row: EmptyObjectType) => {
+  const { name, experience_active } = row;
+
+  const text = experience_active
+    ? t("experience.deactivateTip")
+    : t("experience.activeTip");
+  Modal.confirm({
+    title: t("common.prompt"),
+    content: text,
+    okText: t("common.confirm"),
+    async onOk() {
+      await requestKnowledgeBaseUpdate({
+        name,
+        experience_active: !experience_active,
+      });
       handleSearch();
     },
   });
@@ -216,9 +309,6 @@ onUnmounted(() => {
       padding: 0 12px;
       height: 60px;
       border-bottom: 1px solid var(--border-main-color);
-      .intel-btn {
-        width: 100%;
-      }
     }
     .list-container {
       flex: 1;
@@ -227,6 +317,7 @@ onUnmounted(() => {
       padding: 0 16px;
       .kb-list {
         width: 100%;
+        height: 60px;
         border: 1px solid var(--border-main-color);
         border-radius: 6px;
         padding: 8px;
@@ -252,12 +343,24 @@ onUnmounted(() => {
             gap: 8px;
             .name-wrap {
               font-weight: 600;
-              flex: 1;
               min-width: 0;
               line-height: 16px;
               text-align: left;
               .single-ellipsis;
             }
+            .tag-wrap {
+              display: inline-flex;
+              align-items: center;
+              justify-content: center;
+              height: 16px;
+              line-height: 1;
+              padding: 0 6px;
+              border-radius: 10px;
+              font-size: 10px;
+              margin-left: 4px;
+              color: var(--color-primary-tip);
+              background-color: var(--color-second-primaryBg);
+            }
             .total-wrap {
               color: var(--font-info-color);
               font-size: 12px;
@@ -289,6 +392,9 @@ onUnmounted(() => {
           background-color: var(--color-success);
           color: var(--color-white);
           .vertical-center;
+          &.is-experience {
+            background-color: var(--color-purple);
+          }
         }
       }
     }
diff --git a/EdgeCraftRAG/ui/vue/src/views/chatbot/components/index.ts b/EdgeCraftRAG/ui/vue/src/views/chatbot/components/index.ts
index cfbbc273ed..a216726886 100644
--- a/EdgeCraftRAG/ui/vue/src/views/chatbot/components/index.ts
+++ b/EdgeCraftRAG/ui/vue/src/views/chatbot/components/index.ts
@@ -4,7 +4,7 @@
 import Chatbot from "./Chatbot/index.vue";
 import KnowledgeBase from "./KnowledgeBase/index.vue";
 import SystemChart from "@/views/pipeline/components/SystemChart.vue";
-import KnowledgeDetial from "./KnowledgeBase/KnowledgeDetial.vue";
+import DetailComponent from "./KnowledgeBase/DetailComponent.vue";
 import Pipeline from "../../pipeline/index.vue";
 
-export { Chatbot, KnowledgeBase, SystemChart, KnowledgeDetial, Pipeline };
+export { Chatbot, KnowledgeBase, SystemChart, DetailComponent, Pipeline };
diff --git a/EdgeCraftRAG/ui/vue/src/views/chatbot/index.vue b/EdgeCraftRAG/ui/vue/src/views/chatbot/index.vue
index d7aa155d59..c65d7b0126 100644
--- a/EdgeCraftRAG/ui/vue/src/views/chatbot/index.vue
+++ b/EdgeCraftRAG/ui/vue/src/views/chatbot/index.vue
@@ -3,7 +3,7 @@
     <a-layout class="content-container">
       <a-layout-sider :width="currentMenu === 'knowledge' ? 240 : 0">
         <KnowledgeBase
-          @view="handleViewKBDetial"
+          @view="handleViewKBDetail"
           v-if="currentMenu === 'knowledge'"
         />
       </a-layout-sider>
@@ -12,7 +12,7 @@
           <component
             :is="currentComponent"
             class="body-wrap"
-            :kb-name="kbName"
+            :kb-info="kbInfo"
             @back="handleBack"
           />
         </keep-alive>
@@ -23,13 +23,13 @@
 
 <script lang="ts" setup name="Chatbot">
 import { onMounted, computed } from "vue";
-import { Chatbot, KnowledgeDetial, KnowledgeBase } from "./components";
+import { Chatbot, DetailComponent, KnowledgeBase } from "./components";
 
 const route = useRoute();
 
 const currentMenu = ref<string>("chat");
 const currentPage = ref<string>("chat");
-const kbName = ref<string>("");
+let kbInfo = reactive<EmptyObjectType>({});
 
 const componentList = ref<EmptyArrayType>([
   {
@@ -42,7 +42,7 @@ const componentList = ref<EmptyArrayType>([
     label: "knowledge.title",
     id: "knowledge",
     icon: "icon-knowledge",
-    component: markRaw(KnowledgeDetial),
+    component: markRaw(DetailComponent),
   },
 ]);
 
@@ -51,9 +51,10 @@ const currentComponent = computed(() => {
     ?.component;
 });
 
-const handleViewKBDetial = (name: string) => {
-  kbName.value = name;
-  if (kbName.value) currentPage.value = "knowledge";
+const handleViewKBDetail = (row: EmptyObjectType) => {
+  Object.assign(kbInfo, row);
+
+  if (kbInfo.name) currentPage.value = "knowledge";
   else currentPage.value = "chat";
 };
 const handleBack = () => {
@@ -71,7 +72,6 @@ watch(
   },
   { immediate: true, deep: true }
 );
-onMounted(() => {});
 </script>
 
 <style scoped lang="less">
diff --git a/EdgeCraftRAG/ui/vue/src/views/chatbot/type.ts b/EdgeCraftRAG/ui/vue/src/views/chatbot/type.ts
index b426be5df8..6f853480c3 100644
--- a/EdgeCraftRAG/ui/vue/src/views/chatbot/type.ts
+++ b/EdgeCraftRAG/ui/vue/src/views/chatbot/type.ts
@@ -9,10 +9,13 @@ export interface Benchmark {
 export interface IMessage {
   role: string;
   content: string;
+  query?: string;
+  errorMessage?: string;
   benchmark?: Benchmark | undefined;
 }
 export interface ThinkType {
   enable_thinking?: boolean;
+  enable_rag_retrieval?: boolean;
 }
 export interface ConfigType {
   top_n: number;
diff --git a/EdgeCraftRAG/ui/vue/src/views/error/404.vue b/EdgeCraftRAG/ui/vue/src/views/error/404.vue
index 4683c892f2..b1d3e0df30 100644
--- a/EdgeCraftRAG/ui/vue/src/views/error/404.vue
+++ b/EdgeCraftRAG/ui/vue/src/views/error/404.vue
@@ -2,12 +2,11 @@
   <div class="not-found">
     <img :src="notFound" alt="" class="not-found-icon" />
     <p>{{ $t("error.notFoundTip") }}</p>
-    <a-button
-      type="primary"
-      size="large"
-      :icon="h(HomeFilled)"
-      @click="handleGoHome"
-      >{{ $t("error.back") }}
+    <a-button type="primary" size="large" @click="handleGoHome">
+      <template #icon>
+        <HomeFilled />
+      </template>
+      {{ $t("error.back") }}
     </a-button>
   </div>
 </template>
diff --git a/EdgeCraftRAG/ui/vue/src/views/main/index.vue b/EdgeCraftRAG/ui/vue/src/views/main/index.vue
index a2ab2a0874..d819f75d0a 100644
--- a/EdgeCraftRAG/ui/vue/src/views/main/index.vue
+++ b/EdgeCraftRAG/ui/vue/src/views/main/index.vue
@@ -68,17 +68,17 @@ let systemData = reactive<EmptyObjectType>({});
 const componentList = ref<EmptyArrayType>([
   {
     label: "chat.title",
-    path: "/rag/chatbot",
+    path: "/chatbot",
     icon: "icon-chat",
   },
   {
     label: "knowledge.title",
-    path: "/rag/chatbot?type=kb",
+    path: "/chatbot?type=kb",
     icon: "icon-knowledge",
   },
   {
     label: "chat.setting",
-    path: "/rag/pipeline",
+    path: "/pipeline",
     icon: "icon-setting",
   },
 ]);
diff --git a/EdgeCraftRAG/ui/vue/src/views/pipeline/components/DetailDrawer.vue b/EdgeCraftRAG/ui/vue/src/views/pipeline/components/DetailDrawer.vue
index 616ca925f2..fb54741f73 100644
--- a/EdgeCraftRAG/ui/vue/src/views/pipeline/components/DetailDrawer.vue
+++ b/EdgeCraftRAG/ui/vue/src/views/pipeline/components/DetailDrawer.vue
@@ -83,6 +83,17 @@
                 formData.indexer.indexer_type
               }}</span>
             </li>
+            <li
+              class="item-wrap"
+              v-if="formData.indexer.indexer_type === 'kbadmin_indexer'"
+            >
+              <span class="label-wrap">{{
+                $t("pipeline.config.embeddingUrl")
+              }}</span>
+              <span class="content-wrap">{{
+                formData.indexer?.embedding_url
+              }}</span>
+            </li>
             <li class="item-wrap">
               <span class="label-wrap">{{
                 $t("pipeline.config.embedding")
@@ -101,13 +112,17 @@
             </li>
             <li
               class="item-wrap"
-              v-if="formData.indexer.indexer_type === 'milvus_vector'"
+              v-if="
+                ['kbadmin_indexer', 'milvus_vector'].includes(
+                  formData.indexer.indexer_type
+                )
+              "
             >
               <span class="label-wrap">{{
-                $t("pipeline.config.vector_uri")
+                $t("pipeline.config.vector_url")
               }}</span>
               <span class="content-wrap">{{
-                formData.indexer.vector_uri
+                formData.indexer?.vector_url
               }}</span>
             </li>
           </ul>
@@ -165,6 +180,10 @@
               <span class="content-wrap">{{ item.processor_type }}</span>
             </li>
             <template v-if="item.processor_type === 'reranker'">
+              <li class="item-wrap">
+                <span class="label-wrap">{{ $t("pipeline.config.topn") }}</span>
+                <span class="content-wrap">{{ item.top_n }}</span>
+              </li>
               <li class="item-wrap">
                 <span class="label-wrap">{{
                   $t("pipeline.config.rerank")
@@ -266,11 +285,15 @@ const postProcessorActive = ref<string>("postProcessor");
 const generatorActive = ref<string>("generator");
 
 const isHierarchical = computed(() => {
-  return formData.node_parser.parser_type === "hierarchical";
+  return (
+    formData.node_parser.parser_type === "hierarchical" ||
+    formData.node_parser.parser_type === "kbadmin_parser"
+  );
 });
 const isSentencewindow = computed(() => {
   return formData.node_parser.parser_type === "sentencewindow";
 });
+
 const handleClose = () => {
   emit("close");
 };
diff --git a/EdgeCraftRAG/ui/vue/src/views/pipeline/components/ImportDialog.vue b/EdgeCraftRAG/ui/vue/src/views/pipeline/components/ImportDialog.vue
index 62227db062..ed266f2681 100644
--- a/EdgeCraftRAG/ui/vue/src/views/pipeline/components/ImportDialog.vue
+++ b/EdgeCraftRAG/ui/vue/src/views/pipeline/components/ImportDialog.vue
@@ -17,6 +17,7 @@
       :action="importUrl"
       accept=".json"
       :showUploadList="false"
+      :before-upload="handleBeforeUpload"
       @change="handleChange"
     >
       <SvgIcon
@@ -41,6 +42,7 @@ import { ref } from "vue";
 import { useNotification } from "@/utils/common";
 import { NextLoading } from "@/utils/loading";
 import { useI18n } from "vue-i18n";
+import { message, UploadProps } from "ant-design-vue";
 
 const { t } = useI18n();
 const { antNotification } = useNotification();
@@ -49,6 +51,16 @@ const emit = defineEmits(["search", "close"]);
 const modelVisible = ref<boolean>(true);
 const fileList = ref([]);
 
+const handleBeforeUpload = (file: UploadProps["fileList"][number]) => {
+  const isFileSize = file.size / 1024 / 1024 < 10;
+
+  if (!isFileSize) {
+    message.error(t("pipeline.pipelineFormatTip"));
+    return;
+  }
+
+  return isFileSize;
+};
 const handleChange = (info: any) => {
   const el = <HTMLElement>document.querySelector(".loading-next");
   if (!el) NextLoading.start();
diff --git a/EdgeCraftRAG/ui/vue/src/views/pipeline/components/QuickStart.vue b/EdgeCraftRAG/ui/vue/src/views/pipeline/components/QuickStart.vue
index a817fbba68..93c5abb1b9 100644
--- a/EdgeCraftRAG/ui/vue/src/views/pipeline/components/QuickStart.vue
+++ b/EdgeCraftRAG/ui/vue/src/views/pipeline/components/QuickStart.vue
@@ -50,7 +50,7 @@
   </a-modal>
 </template>
 
-<script lang="ts" setup name="EditDialog">
+<script lang="ts" setup name="QuickStart">
 import { userAppStore } from "@/store/user";
 import { PlusOutlined } from "@ant-design/icons-vue";
 import { computed, h } from "vue";
diff --git a/EdgeCraftRAG/ui/vue/src/views/pipeline/components/Table.vue b/EdgeCraftRAG/ui/vue/src/views/pipeline/components/Table.vue
index b997be75cb..d925ca8df4 100644
--- a/EdgeCraftRAG/ui/vue/src/views/pipeline/components/Table.vue
+++ b/EdgeCraftRAG/ui/vue/src/views/pipeline/components/Table.vue
@@ -24,6 +24,7 @@
       :columns="tableColumns"
       :data-source="tableList"
       :pagination="false"
+      :loading="loading"
       :scroll="{ x: 'max-content' }"
     >
       <template #bodyCell="{ column, record }">
@@ -36,14 +37,14 @@
           {{
             record.postprocessor
               .map((item: any) => item?.processor_type)
-              .join(", ")
+              .join(",")
           }}
         </template>
         <template v-if="column.dataIndex === 'rerank'">
           {{
             record.postprocessor
               .map((item: any) => item?.model?.model_id)
-              .join(", ") || "--"
+              .join(" ") || "--"
           }}
         </template>
         <template v-if="column.dataIndex === 'status'">
@@ -116,7 +117,6 @@
 
 <script lang="ts" setup name="Table">
 import {
-  getPipelineDetailByName,
   requestPipelineDelete,
   requestPipelineSwitchState,
 } from "@/api/pipeline";
@@ -143,6 +143,10 @@ const props = defineProps({
     type: Array,
     default: () => [],
   },
+  loading: {
+    type: Boolean,
+    default: false,
+  },
 });
 
 const emit = defineEmits(["update", "create", "view", "import", "search"]);
@@ -153,6 +157,7 @@ const paginationData = reactive<paginationType>({
 });
 const tableColumns = ref<TableColumns[]>([]);
 const allColumns = computed(() => getTableColumns(t));
+
 const tableList = computed(() => {
   const { pageNum, pageSize } = paginationData;
   const start = (pageNum - 1) * pageSize;
diff --git a/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/Activated.vue b/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/Activated.vue
index b3da88a5d1..7670be85de 100644
--- a/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/Activated.vue
+++ b/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/Activated.vue
@@ -39,7 +39,7 @@ const formRef = ref<FormInstance>();
 const form = reactive<FormType>({
   active,
 });
-const rules = reactive({
+const rules: FormRules = reactive({
   active: [{ required: true, trigger: "change" }],
 });
 // Validate the form, throw results form
diff --git a/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/Basic.vue b/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/Basic.vue
index d4d7c7bd71..c18e73eb96 100644
--- a/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/Basic.vue
+++ b/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/Basic.vue
@@ -20,6 +20,7 @@
 </template>
 
 <script lang="ts" setup name="Basic">
+import { isValidPipelineName } from "@/utils/validate";
 import type { FormInstance } from "ant-design-vue";
 import { reactive, ref, computed } from "vue";
 import { useI18n } from "vue-i18n";
@@ -36,6 +37,19 @@ const props = defineProps({
     default: "create",
   },
 });
+const validateName = async (rule: any, value: string) => {
+  if (!value) {
+    return Promise.reject(t("pipeline.valid.nameValid1"));
+  }
+  const len = value.length;
+  if (len < 2 || len > 30) {
+    return Promise.reject(t("pipeline.valid.nameValid2"));
+  }
+  if (!isValidPipelineName(value)) {
+    return Promise.reject(t("pipeline.valid.nameValid3"));
+  }
+  return Promise.resolve();
+};
 const disabledName = computed(() => {
   const { formType } = props;
   return formType === "update";
@@ -49,18 +63,12 @@ const formRef = ref<FormInstance>();
 const form = reactive<FormType>({
   name,
 });
-const rules = reactive({
+const rules: FormRules = reactive({
   name: [
     {
       required: true,
-      message: t("pipeline.valid.nameValid1"),
-      trigger: "blur",
-    },
-    {
-      min: 2,
-      max: 30,
-      message: t("pipeline.valid.nameValid2"),
-      trigger: "blur",
+      validator: validateName,
+      trigger: ["blur", "change"],
     },
   ],
 });
diff --git a/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/CreateDialog.vue b/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/CreateDialog.vue
index 377bb57ba9..28515b4ce7 100644
--- a/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/CreateDialog.vue
+++ b/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/CreateDialog.vue
@@ -20,13 +20,11 @@
       </div>
     </div>
     <div class="body-container">
-      <keep-alive>
-        <component
-          :is="currentComponent"
-          :form-data="formData"
-          ref="pipelineRef"
-        />
-      </keep-alive>
+      <component
+        :is="currentComponent"
+        :form-data="formData"
+        ref="pipelineRef"
+      />
     </div>
     <template #footer>
       <div class="flex-between">
@@ -140,12 +138,17 @@ const handleLast = () => {
 //next，update form
 const handleNext = async () => {
   if (pipelineRef.value) {
-    const { result = false, data = {} } = await pipelineRef.value?.validate();
+    const {
+      result = false,
+      data = {},
+      dest = null,
+    } = await pipelineRef.value?.validate();
 
     if (result) {
       Object.assign(formData, data);
+
       if (currentStep.value < 7) {
-        currentStep.value++;
+        currentStep.value = dest ? dest : currentStep.value + 1;
       }
     } else {
       console.log(t("pipeline.validErr"));
diff --git a/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/EditDialog.vue b/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/EditDialog.vue
index 0f769e9228..3e7db0625c 100644
--- a/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/EditDialog.vue
+++ b/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/EditDialog.vue
@@ -148,14 +148,18 @@ const handleSelect = async (value?: number) => {
     if (result) {
       await Object.assign(formData, data);
       if (value) currentStep.value = value;
+      return true;
     } else {
       console.log(t("pipeline.validErr"));
+      return false;
     }
   }
+  return false;
 };
 // Submit
 const handleSubmit = async () => {
-  await handleSelect();
+  const isValid = await handleSelect();
+  if (!isValid) return;
   submitLoading.value = true;
   const { name } = props.dialogData;
 
diff --git a/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/Generator.vue b/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/Generator.vue
index cbe0af28d9..63e24138b2 100644
--- a/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/Generator.vue
+++ b/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/Generator.vue
@@ -27,12 +27,70 @@
       <FormTooltip :title="$t('pipeline.desc.generatorType')" />
     </a-form-item>
     <a-form-item :label="$t('pipeline.config.llm')" name="inference_type">
-      <a-radio-group v-model:value="form.inference_type">
+      <a-radio-group
+        v-model:value="form.inference_type"
+        @change="handleTypeChange"
+      >
         <a-radio value="vllm">{{ $t("pipeline.config.vllm") }}</a-radio>
         <a-radio value="local">{{ $t("pipeline.config.local") }}</a-radio>
       </a-radio-group>
     </a-form-item>
-    <template v-if="form.inference_type === 'local'">
+    <template v-if="isVllm">
+      <a-form-item
+        :label="$t('pipeline.config.language')"
+        :name="['model', 'model_id']"
+        :rules="rules.model_id"
+      >
+        <a-select
+          showSearch
+          v-model:value="form.model.model_id"
+          :placeholder="$t('pipeline.valid.language')"
+          @dropdownVisibleChange="handleVllmModelVisible"
+        >
+          <a-select-option
+            v-for="item in vllmModelList"
+            :key="item"
+            :value="item"
+            >{{ item }}</a-select-option
+          >
+        </a-select>
+        <FormTooltip :title="$t('pipeline.desc.language')" />
+      </a-form-item>
+      <a-form-item
+        :label="$t('pipeline.config.vllm_url')"
+        name="vllm_endpoint"
+        :rules="rules.vllm_endpoint"
+      >
+        <a-input
+          v-model:value="form.vllm_endpoint"
+          :placeholder="$t('pipeline.valid.vllm_url')"
+          @change="handleUrlChange"
+        >
+          <template #addonBefore>
+            <a-select v-model:value="protocol">
+              <a-select-option value="http://">Http://</a-select-option>
+              <a-select-option value="https://">Https://</a-select-option>
+            </a-select>
+          </template>
+          <template #addonAfter>
+            <a-button
+              type="primary"
+              class="text-btn"
+              :disabled="!isPass"
+              @click="handleTestUrl"
+            >
+              <CheckCircleFilled
+                v-if="validatePass"
+                :style="{ color: 'var(--color-success)', fontSize: '18px' }"
+              />
+              <span v-else> {{ $t("pipeline.desc.test") }}</span>
+            </a-button>
+          </template>
+        </a-input>
+        <FormTooltip :title="$t('pipeline.desc.vllm_url')" />
+      </a-form-item>
+    </template>
+    <template v-else>
       <a-form-item
         :label="$t('pipeline.config.language')"
         :name="['model', 'model_id']"
@@ -95,48 +153,6 @@
         <FormTooltip :title="t('pipeline.desc.weights')" />
       </a-form-item>
     </template>
-    <template v-else>
-      <a-form-item
-        :label="$t('pipeline.config.language')"
-        name="modelName"
-        :rules="rules.modelName"
-      >
-        <a-input
-          v-model:value.trim="form.modelName"
-          :placeholder="$t('pipeline.valid.modelName')"
-        >
-        </a-input>
-        <FormTooltip :title="$t('pipeline.desc.language')" />
-      </a-form-item>
-      <a-form-item
-        :label="$t('pipeline.config.vllm_url')"
-        name="vllm_endpoint"
-        :rules="rules.vllm_endpoint"
-      >
-        <a-input
-          v-model:value="form.vllm_endpoint"
-          :addon-before="protocol"
-          :placeholder="$t('pipeline.valid.vllm_url')"
-          @change="handleUrlChange"
-        >
-          <template #addonAfter>
-            <a-button
-              type="primary"
-              class="text-btn"
-              :disabled="!isPass"
-              @click="handleTestUrl"
-            >
-              <CheckCircleFilled
-                v-if="validatePass"
-                :style="{ color: 'var(--color-success)', fontSize: '18px' }"
-              />
-              <span v-else> {{ $t("pipeline.desc.test") }}</span>
-            </a-button>
-          </template>
-        </a-input>
-        <FormTooltip :title="$t('pipeline.desc.vllm_url')" />
-      </a-form-item>
-    </template>
   </a-form>
 </template>
 
@@ -173,14 +189,13 @@ interface FormType {
   inference_type: string;
   model: ModelType;
   vllm_endpoint?: string;
-  modelName?: string;
 }
 const validateUnique = async (rule: any, value: string) => {
   if (!value) {
-    return Promise.reject(t("pipeline.valid.urlValid1"));
+    return Promise.reject(t("pipeline.valid.vllmUrlValid1"));
   }
   if (!validateIpPort(value)) {
-    return Promise.reject(t("pipeline.valid.urlValid2"));
+    return Promise.reject(t("pipeline.valid.vllmUrlValid2"));
   }
 
   isPass.value = true;
@@ -188,7 +203,7 @@ const validateUnique = async (rule: any, value: string) => {
 };
 const handleUrlFormat = (url: string) => {
   if (!url) return "";
-  return url.replace(/http:\/\//g, "");
+  return url.replace(/https?:\/\//g, "");
 };
 const {
   generator_type = "chatqna",
@@ -210,10 +225,9 @@ const form = reactive<FormType>({
   generator_type,
   inference_type,
   vllm_endpoint: handleUrlFormat(vllm_endpoint),
-  modelName: inference_type === "vllm" ? model.model_id : "",
   model,
 });
-const rules = reactive({
+const rules: FormRules = reactive({
   generator_type: [
     {
       required: true,
@@ -256,23 +270,25 @@ const rules = reactive({
       trigger: "blur",
     },
   ],
-  modelName: [
-    {
-      required: true,
-      message: t("pipeline.valid.modelName"),
-      trigger: "change",
-    },
-  ],
 });
 const generatorList = Generator;
 const generatorWeightList = ref<EmptyArrayType>([]);
 const modelList = ref<EmptyArrayType>([]);
+const vllmModelList = ref<EmptyArrayType>([]);
 const deviceList = ref<EmptyArrayType>([]);
 
+const isVllm = computed(() => {
+  return form.inference_type === "vllm";
+});
 // Complete model_cath
 const handleModelChange = () => {
   form.model.weight = "";
 };
+// Reset  model_ID
+const handleTypeChange = () => {
+  form.model.model_id = undefined;
+};
+
 // Handling Model Folding Events
 const handleModelVisible = async (visible: boolean) => {
   if (visible) {
@@ -284,6 +300,17 @@ const handleModelVisible = async (visible: boolean) => {
     }
   }
 };
+// Handling Model Folding Events
+const handleVllmModelVisible = async (visible: boolean) => {
+  if (visible) {
+    try {
+      const data: any = await getModelList("vLLM");
+      vllmModelList.value = [].concat(data);
+    } catch (err) {
+      console.error(err);
+    }
+  }
+};
 const handleModelPath = (
   modelId: string,
   weights?: string,
@@ -323,7 +350,7 @@ const handleWeightVisible = async (visible: boolean) => {
   if (visible) {
     try {
       const { model_id } = form.model;
-      const data: any = await getModelWeight(model_id);
+      const data: any = await getModelWeight(model_id!);
       generatorWeightList.value = [].concat(data);
     } catch (err) {
       console.error(err);
@@ -336,38 +363,40 @@ const handleUrlChange = () => {
 };
 // Format parameter
 const formatFormParam = () => {
-  const { inference_type, model, modelName, vllm_endpoint } = form;
+  const { inference_type, model, vllm_endpoint } = form;
   const { model_id, weight } = model;
-  model.model_path = handleModelPath(model_id, weight);
-  model.model_id = inference_type === "vllm" ? modelName : model_id;
+  model.model_path = handleModelPath(model_id!, weight);
   return {
     inference_type,
     prompt_path: "./default_prompt.txt",
-    model,
-    vllm_endpoint:
-      inference_type === "vllm" ? protocol.value + vllm_endpoint : undefined,
+    model: isVllm.value ? { model_id } : model,
+    vllm_endpoint: isVllm.value ? protocol.value + vllm_endpoint : undefined,
   };
 };
 
 const handleTestUrl = async () => {
-  formRef.value?.validateFields(["modelName"]);
-  const { modelName } = form;
-  if (!modelName) return;
+  formRef.value?.validateFields([["model", "model_id"]]);
+  const { model_id } = form.model;
+  if (!model_id) return;
   const server_address = protocol.value + form.vllm_endpoint;
 
-  const { status = "" } = await requestUrlVllm({
+  const { status = "" } = (await requestUrlVllm({
     server_address,
-    model_name: modelName,
-  });
+    model_name: model_id,
+  })) as any;
   if (status !== "200") {
-    antNotification("error", t("common.error"), t("pipeline.valid.urlValid3"));
+    antNotification(
+      "error",
+      t("common.error"),
+      t("pipeline.valid.vllmUrlValid3")
+    );
     return;
   }
   validatePass.value = true;
   antNotification(
     "success",
     t("common.success"),
-    t("pipeline.valid.urlValid4")
+    t("pipeline.valid.vllmUrlValid4")
   );
 };
 // Validate the form, throw results form
@@ -376,11 +405,11 @@ const handleValidate = (): Promise<object> => {
     formRef.value
       ?.validate()
       .then(() => {
-        if (form.inference_type === "vllm" && !validatePass.value) {
+        if (isVllm.value && !validatePass.value) {
           antNotification(
             "warning",
             t("common.prompt"),
-            t("pipeline.valid.urlValid5")
+            t("pipeline.valid.vllmUrlValid5")
           );
           return;
         }
@@ -398,7 +427,7 @@ defineExpose({
   validate: handleValidate,
 });
 onMounted(() => {
-  if (props.formType === "update") {
+  if (props.formType === "update" && isVllm.value) {
     isPass.value = true;
     validatePass.value = true;
   }
@@ -409,6 +438,9 @@ onMounted(() => {
 :deep(.intel-input-group) {
   .intel-input-group-addon {
     overflow: hidden;
+    .intel-select-selector {
+      border: 1px solid transparent !important;
+    }
   }
 }
 .text-btn {
diff --git a/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/Indexer.vue b/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/Indexer.vue
index d1e76b4649..b4f0237d4c 100644
--- a/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/Indexer.vue
+++ b/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/Indexer.vue
@@ -8,24 +8,34 @@
     autocomplete="off"
     class="form-wrap"
   >
-    <a-form-item :label="$t('pipeline.config.indexerType')" name="indexer_type">
-      <a-select
-        showSearch
-        v-model:value="form.indexer_type"
-        :placeholder="$t('pipeline.valid.indexerType')"
+    <div class="column-wrap">
+      <a-form-item
+        :label="$t('pipeline.config.indexerType')"
+        class="row-item"
+        name="indexer_type"
       >
-        <a-select-option
-          v-for="item in indexerList"
-          :key="item.value"
-          :value="item.value"
-          >{{ item.name }}</a-select-option
-        >
-      </a-select>
-      <FormTooltip :title="$t('pipeline.desc.indexerType')" />
-    </a-form-item>
-    <div class="option-introduction">
-      <InfoCircleOutlined />
-      {{ $t(optionIntroduction!) }}
+        <div class="flex-left">
+          <a-select
+            showSearch
+            v-model:value="form.indexer_type"
+            :placeholder="$t('pipeline.valid.indexerType')"
+            @change="handleTypeChange"
+          >
+            <a-select-option
+              v-for="item in indexerList"
+              :key="item.value"
+              :value="item.value"
+              >{{ item.name }}</a-select-option
+            >
+          </a-select>
+          <FormTooltip :title="$t('pipeline.desc.indexerType')" />
+        </div>
+
+        <div class="option-introduction">
+          <InfoCircleOutlined />
+          {{ $t(optionIntroduction!) }}
+        </div>
+      </a-form-item>
     </div>
     <a-form-item
       :label="$t('pipeline.config.embedding')"
@@ -46,6 +56,26 @@
       <FormTooltip :title="$t('pipeline.desc.embedding')" />
     </a-form-item>
     <a-form-item
+      :label="$t('pipeline.config.embeddingUrl')"
+      name="embedding_url"
+      :rules="rules.embedding_url"
+      v-if="isKbadmin"
+    >
+      <a-input
+        v-model:value="form.embedding_url"
+        :placeholder="$t('pipeline.valid.embeddingUrl')"
+      >
+        <template #addonBefore>
+          <a-select v-model:value="modelProtocol">
+            <a-select-option value="http://">Http://</a-select-option>
+            <a-select-option value="https://">Https://</a-select-option>
+          </a-select>
+        </template>
+      </a-input>
+      <FormTooltip :title="$t('pipeline.desc.embeddingUrl')" />
+    </a-form-item>
+    <a-form-item
+      v-if="!isKbadmin"
       :label="$t('pipeline.config.embeddingDevice')"
       :name="['embedding_model', 'device']"
       :rules="rules.device"
@@ -63,18 +93,23 @@
       <FormTooltip :title="$t('pipeline.desc.embeddingDevice')" />
     </a-form-item>
     <a-form-item
-      :label="$t('pipeline.config.vector_uri')"
-      name="vector_uri"
-      :rules="rules.vector_uri"
-      v-if="form.indexer_type === 'milvus_vector'"
+      :label="$t('pipeline.config.vector_url')"
+      name="vector_url"
+      :rules="rules.vector_url"
+      v-if="isMilvus || isKbadmin"
     >
       <a-input
-        v-model:value="form.vector_uri"
-        :addon-before="protocol"
-        :placeholder="$t('pipeline.valid.vector_uri')"
+        v-model:value="form.vector_url"
+        :placeholder="$t(`${TIP_MESSAGES[form.indexer_type]}`)"
         @change="handleUriChange"
       >
-        <template #addonAfter>
+        <template #addonBefore>
+          <a-select v-model:value="protocol">
+            <a-select-option value="http://">Http://</a-select-option>
+            <a-select-option value="https://">Https://</a-select-option>
+          </a-select>
+        </template>
+        <template #addonAfter v-if="isMilvus">
           <a-button
             type="primary"
             class="text-btn"
@@ -89,7 +124,7 @@
           </a-button>
         </template>
       </a-input>
-      <FormTooltip :title="$t('pipeline.desc.vector_uri')" />
+      <FormTooltip :title="$t('pipeline.desc.vector_url')" />
     </a-form-item>
   </a-form>
 </template>
@@ -104,6 +139,8 @@ import { InfoCircleOutlined, CheckCircleFilled } from "@ant-design/icons-vue";
 import { useI18n } from "vue-i18n";
 import { validateIpPort } from "@/utils/validate.ts";
 import { useNotification } from "@/utils/common";
+import { SelectValue } from "ant-design-vue/es/select/index";
+import { RuleObject } from "ant-design-vue/es/form/interface";
 
 const { t } = useI18n();
 const { antNotification } = useNotification();
@@ -119,26 +156,15 @@ const props = defineProps({
 });
 interface FormType {
   indexer_type: string;
-  vector_uri?: string;
+  vector_url?: string;
+  embedding_url?: string;
   embedding_model: ModelType;
 }
-const validateUnique = async (rule: any, value: string) => {
-  if (!value) {
-    return Promise.reject(t("pipeline.valid.urlValid1"));
-  }
-  if (!validateIpPort(value)) {
-    return Promise.reject(t("pipeline.valid.urlValid2"));
-  }
-  isPass.value = true;
-  return Promise.resolve();
-};
-const handleUrlFormat = (url: string) => {
-  if (!url) return "";
-  return url.replace(/http:\/\//g, "");
-};
+
 const {
   indexer_type = "faiss_vector",
-  vector_uri = "",
+  vector_url = "",
+  embedding_url = "",
   embedding_model = {
     model_id: "BAAI/bge-small-en-v1.5",
     model_path: "./models/BAAI/bge-small-en-v1.5",
@@ -146,21 +172,74 @@ const {
     weight: "INT4",
   },
 } = props.formData?.indexer || {};
+const { parser_type = "" } = props.formData?.node_parser || {};
+const TIP_MESSAGES = {
+  kbadmin_indexer: "pipeline.valid.kb_vector_url",
+  milvus_vector: "pipeline.valid.vector_url",
+} as const;
+const VALIDATION_MESSAGES = {
+  vector: {
+    required: "pipeline.valid.urlValid1",
+    format: "pipeline.valid.urlValid2",
+  },
+  model: {
+    required: "pipeline.valid.modelRequired",
+    format: "pipeline.valid.modelFormat",
+  },
+} as const;
+const validateUnique = (type: "vector" | "model") => {
+  return async (rule: RuleObject, value: string) => {
+    const messages = VALIDATION_MESSAGES[type];
+    if (!value) {
+      return Promise.reject(new Error(t(messages.required)));
+    }
+    if (!validateIpPort(value)) {
+      return Promise.reject(new Error(t(messages.format)));
+    }
+    isPass.value = true;
+    return Promise.resolve();
+  };
+};
+
+const validateIndeserType = async (rule: any, value: string) => {
+  if (!value) {
+    return Promise.reject(t("pipeline.valid.indexerType"));
+  }
+  if (parser_type === "kbadmin_parser" && value !== "kbadmin_indexer") {
+    return Promise.reject(t("pipeline.valid.indexerTypeValid1"));
+  }
+  return Promise.resolve();
+};
+
+const handleUrlFormat = (url: string) => {
+  if (!url) return "";
+  return url.replace(/https?:\/\//g, "");
+};
 
 const isPass = ref<boolean>(false);
 const validatePass = ref<boolean>(false);
 const protocol = ref<string>("http://");
+const modelProtocol = ref<string>("http://");
 const formRef = ref<FormInstance>();
 const form = reactive<FormType>({
   indexer_type,
-  vector_uri: handleUrlFormat(vector_uri),
-  embedding_model,
+  vector_url: handleUrlFormat(vector_url),
+  embedding_url: handleUrlFormat(embedding_url),
+  embedding_model: {
+    ...embedding_model,
+    model_id:
+      props.formType === "update"
+        ? embedding_model.model_id
+        : indexer_type === "kbadmin_indexer"
+        ? undefined
+        : embedding_model.model_id,
+  },
 });
-const rules = reactive({
+const rules: FormRules = reactive({
   indexer_type: [
     {
       required: true,
-      message: t("pipeline.valid.indexerType"),
+      validator: validateIndeserType,
       trigger: "change",
     },
   ],
@@ -178,24 +257,58 @@ const rules = reactive({
       trigger: "change",
     },
   ],
-  vector_uri: [
+  vector_url: [
     {
       required: true,
-      validator: validateUnique,
+      validator: validateUnique("vector"),
       trigger: "blur",
     },
   ],
+
+  embedding_url: [
+    {
+      required: true,
+      validator: validateUnique("model"),
+      trigger: "change",
+    },
+  ],
 });
-const indexerList = Indexer;
+
 const deviceList = ref<EmptyArrayType>([]);
 const modelList = ref<EmptyArrayType>([]);
-
+const isCreate = computed(() => {
+  return props.formType === "create";
+});
+const isKbadmin = computed(() => {
+  return form.indexer_type === "kbadmin_indexer";
+});
+const isMilvus = computed(() => {
+  return form.indexer_type === "milvus_vector";
+});
+const indexerList = computed(() => {
+  if (isCreate.value) {
+    return Indexer;
+  }
+  return isKbadmin.value
+    ? Indexer.filter((item) => item.value === "kbadmin_indexer")
+    : Indexer.filter((item) => item.value !== "kbadmin_indexer");
+});
 const optionIntroduction = computed(() => {
   const { indexer_type } = form;
 
-  return indexerList.find((item) => item.value === indexer_type)?.describe;
+  return Indexer.find((item) => item.value === indexer_type)?.describe;
 });
 
+const handleTypeChange = (value: SelectValue) => {
+  if (value === "kbadmin_indexer")
+    antNotification(
+      "warning",
+      t("common.prompt"),
+      t("pipeline.valid.indexerTypeTip")
+    );
+  form.embedding_model.model_id = undefined;
+  form.embedding_model.model_path = "";
+};
 // Handling Device Folding Events
 const handleDeviceVisible = async (visible: boolean) => {
   if (visible) {
@@ -211,7 +324,10 @@ const handleDeviceVisible = async (visible: boolean) => {
 const handleModelVisible = async (visible: boolean) => {
   if (visible) {
     try {
-      const data: any = await getModelList("embedding");
+      const modelType = isKbadmin.value
+        ? "kbadmin_embedding_model"
+        : "embedding";
+      const data: any = await getModelList(modelType);
       modelList.value = [].concat(data);
     } catch (err) {
       console.error(err);
@@ -219,12 +335,12 @@ const handleModelVisible = async (visible: boolean) => {
   }
 };
 //Complete model_cath
-const handleModelChange = (value: string) => {
+const handleModelChange = (value: SelectValue) => {
   form.embedding_model.model_path = `./models/${value}`;
 };
 const handleTestUrl = async () => {
-  const vector_uri = protocol.value + form.vector_uri;
-  const { status = "" } = await requestUrlVerify({ vector_uri });
+  const vector_url = protocol.value + form.vector_url;
+  const { status = "" } = (await requestUrlVerify({ vector_url })) as any;
 
   if (status !== "200") {
     antNotification("error", t("common.error"), t("pipeline.valid.urlValid3"));
@@ -243,24 +359,41 @@ const handleUriChange = () => {
 };
 // Format parameter
 const formatFormParam = () => {
-  const { indexer_type, vector_uri, embedding_model } = form;
+  const { indexer_type, vector_url, embedding_url, embedding_model } = form;
 
   return {
     indexer_type,
-    embedding_model,
-    vector_uri:
-      indexer_type === "milvus_vector"
-        ? protocol.value + vector_uri
+    embedding_model: embedding_model,
+    vector_url:
+      isMilvus.value || isKbadmin.value
+        ? protocol.value + vector_url
         : undefined,
+    embedding_url: isKbadmin.value
+      ? modelProtocol.value + embedding_url
+      : undefined,
   };
 };
+const generateFormData = () => {
+  const baseData = { indexer: formatFormParam() };
+  const { retriever } = props.formData;
+
+  if (isKbadmin.value && parser_type !== "kbadmin_parser") {
+    return {
+      ...baseData,
+      node_parser: { parser_type: "kbadmin_parser" },
+      retriever: { ...retriever, retriever_type: "kbadmin_retriever" },
+    };
+  }
+
+  return baseData;
+};
 // Validate the form, throw results form
 const handleValidate = (): Promise<object> => {
   return new Promise((resolve) => {
     formRef.value
       ?.validate()
       .then(() => {
-        if (form.indexer_type === "milvus_vector" && !validatePass.value) {
+        if (isMilvus.value && !validatePass.value) {
           antNotification(
             "warning",
             t("common.prompt"),
@@ -270,7 +403,7 @@ const handleValidate = (): Promise<object> => {
         }
         resolve({
           result: true,
-          data: { indexer: formatFormParam() },
+          data: generateFormData(),
         });
       })
       .catch(() => {
@@ -283,7 +416,7 @@ defineExpose({
 });
 
 onMounted(() => {
-  if (props.formType === "update") {
+  if (props.formType === "update" && isMilvus.value) {
     isPass.value = true;
     validatePass.value = true;
   }
@@ -294,6 +427,9 @@ onMounted(() => {
 :deep(.intel-input-group) {
   .intel-input-group-addon {
     overflow: hidden;
+    .intel-select-selector {
+      border: 1px solid transparent !important;
+    }
   }
 }
 .text-btn {
diff --git a/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/NodeParser.vue b/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/NodeParser.vue
index d72119e8e6..a1ae33c207 100644
--- a/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/NodeParser.vue
+++ b/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/NodeParser.vue
@@ -13,9 +13,10 @@
       name="parser_type"
     >
       <a-select
-        v-model:value="form.parser_type"
         showSearch
+        v-model:value="form.parser_type"
         :placeholder="$t('pipeline.valid.nodeParserType')"
+        @change="handleTypeChange"
       >
         <a-select-option
           v-for="item in nodeParserList"
@@ -30,7 +31,7 @@
       <InfoCircleOutlined />
       {{ $t(optionIntroduction!) }}
     </div>
-    <template v-if="!isHierarchical && !isSentencewindow">
+    <template v-if="!isHierarchical && !isSentencewindow && !isKbadmin">
       <a-form-item
         :label="$t('pipeline.config.chunkSize')"
         name="chunk_size"
@@ -83,7 +84,7 @@
           v-model:value="form.window_size"
           :min="1"
           :max="10"
-          :marks="sliderMarks.size"
+          :marks="sliderMarks.window"
         />
         <a-form-item noStyle>
           <a-input-number
@@ -105,13 +106,20 @@ import { computed, reactive, ref } from "vue";
 import { NodeParser } from "../../enum.ts";
 import { InfoCircleOutlined } from "@ant-design/icons-vue";
 import { useI18n } from "vue-i18n";
+import { useNotification } from "@/utils/common";
+import { SelectValue } from "ant-design-vue/es/select/index";
 
 const { t } = useI18n();
+const { antNotification } = useNotification();
 const props = defineProps({
   formData: {
     type: Object,
     default: () => {},
   },
+  formType: {
+    type: String,
+    default: "create",
+  },
 });
 interface FormType {
   parser_type: string;
@@ -132,9 +140,7 @@ const validate = {
     }
   },
   chunkOverlap: async (_rule: any, value: number) => {
-    if (!value) {
-      return Promise.reject(t("pipeline.valid.chunkOverlapValid1"));
-    } else if (form?.chunk_size && value > form?.chunk_size) {
+    if (form?.chunk_size && value > form?.chunk_size) {
       return Promise.reject(t("pipeline.valid.chunkOverlapValid2"));
     } else {
       return Promise.resolve();
@@ -158,7 +164,7 @@ const form = reactive<FormType>({
   chunk_sizes,
   window_size,
 });
-const rules = reactive({
+const rules: FormRules = reactive({
   parser_type: [
     {
       required: true,
@@ -189,17 +195,30 @@ const rules = reactive({
   ],
 });
 
-const nodeParserList = NodeParser;
+const isCreate = computed(() => {
+  return props.formType === "create";
+});
 const isHierarchical = computed(() => {
   return form.parser_type === "hierarchical";
 });
+const isKbadmin = computed(() => {
+  return form.parser_type === "kbadmin_parser";
+});
 const isSentencewindow = computed(() => {
   return form.parser_type === "sentencewindow";
 });
+const nodeParserList = computed(() => {
+  if (isCreate.value) {
+    return NodeParser;
+  }
+  return isKbadmin.value
+    ? NodeParser.filter((item) => item.value === "kbadmin_parser")
+    : NodeParser.filter((item) => item.value !== "kbadmin_parser");
+});
 const optionIntroduction = computed(() => {
   const { parser_type } = form;
 
-  return nodeParserList.find((item) => item.value === parser_type)?.describe;
+  return NodeParser.find((item) => item.value === parser_type)?.describe;
 });
 const sliderMarks = reactive<EmptyObjectType>({
   size: {
@@ -210,7 +229,20 @@ const sliderMarks = reactive<EmptyObjectType>({
     0: "0",
     400: "400",
   },
+  window: {
+    1: "1",
+    10: "10",
+  },
 });
+
+const handleTypeChange = (value: SelectValue) => {
+  if (value === "kbadmin_parser")
+    antNotification(
+      "warning",
+      t("common.prompt"),
+      t("pipeline.valid.nodeParserTypeTip")
+    );
+};
 const handleChunkSizeChange = () => {
   formRef.value?.validateFields(["chunk_size"]);
 };
@@ -225,19 +257,44 @@ const formatFormParam = () => {
   const { parser_type, chunk_size, chunk_overlap, chunk_sizes, window_size } =
     form;
 
+  const chunkSizes = isHierarchical.value ? chunk_sizes : undefined;
+  const windowSize = isSentencewindow.value ? window_size : undefined;
+
+  const chunkSize =
+    !isHierarchical.value && !isSentencewindow.value && !isKbadmin.value
+      ? chunk_size
+      : undefined;
+
+  const chunkOverlap = isHierarchical.value
+    ? 20
+    : isKbadmin.value
+    ? undefined
+    : !isSentencewindow.value
+    ? chunk_overlap
+    : undefined;
+
   return {
     parser_type,
-    chunk_sizes: isHierarchical.value ? chunk_sizes : undefined,
-    window_size: isSentencewindow.value ? window_size : undefined,
-    chunk_size:
-      !isHierarchical.value && !isSentencewindow.value ? chunk_size : undefined,
-    chunk_overlap: isHierarchical.value
-      ? 20
-      : !isSentencewindow.value
-      ? chunk_overlap
-      : undefined,
+    chunk_sizes: chunkSizes,
+    window_size: windowSize,
+    chunk_size: chunkSize,
+    chunk_overlap: chunkOverlap,
   };
 };
+const generateFormData = () => {
+  const baseData = { node_parser: formatFormParam() };
+  const { indexer, retriever } = props.formData;
+
+  if (isKbadmin.value) {
+    return {
+      ...baseData,
+      indexer: { ...indexer, indexer_type: "kbadmin_indexer" },
+      retriever: { ...retriever, retriever_type: "kbadmin_retriever" },
+    };
+  }
+
+  return baseData;
+};
 // Validate the form, throw results form
 const handleValidate = (): Promise<object> => {
   return new Promise((resolve) => {
@@ -246,7 +303,7 @@ const handleValidate = (): Promise<object> => {
       .then(() => {
         resolve({
           result: true,
-          data: { node_parser: formatFormParam() },
+          data: generateFormData(),
         });
       })
       .catch(() => {
diff --git a/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/PostProcessor.vue b/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/PostProcessor.vue
index 0a0aa8e279..84811f93a9 100644
--- a/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/PostProcessor.vue
+++ b/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/PostProcessor.vue
@@ -22,6 +22,7 @@
           showSearch
           v-model:value="processor.processor_type"
           :placeholder="$t('pipeline.valid.postProcessorType')"
+          @change="(value) => handleTypeChange(value, processor)"
         >
           <a-select-option
             v-for="item in postProcessorList"
@@ -48,7 +49,7 @@
             v-model:value="processor.reranker_model.model_id"
             :placeholder="$t('pipeline.valid.rerank')"
             @dropdownVisibleChange="handleModelVisible"
-            @change="(value:string) => handleModelChange(processor.reranker_model, value)"
+            @change="(value:SelectValue) => handleModelChange(processor.reranker_model, value)"
           >
             <a-select-option
               v-for="item in modelList"
@@ -112,6 +113,7 @@ import { PostProcessor } from "../../enum.ts";
 import { ModelType } from "../../type.ts";
 import { InfoCircleOutlined } from "@ant-design/icons-vue";
 import { useI18n } from "vue-i18n";
+import { SelectValue } from "ant-design-vue/es/select/index";
 
 const { t } = useI18n();
 const props = defineProps({
@@ -129,7 +131,7 @@ interface ProcessorType {
 interface FormType {
   postprocessor: ProcessorType[];
 }
-const { postprocessor = [] } = props.formData.postprocessor || [];
+const { postprocessor = [] } = props.formData || [];
 
 const defaultConfig = [
   {
@@ -147,7 +149,7 @@ const formRef = ref<FormInstance>();
 const form = reactive<FormType>({
   postprocessor: postprocessor.length ? postprocessor : defaultConfig,
 });
-const rules = reactive({
+const rules: FormRules = reactive({
   processor_type: [
     {
       required: true,
@@ -180,6 +182,19 @@ const getDisable = (value: string) => {
 const getOptionIntroduction = (value: string) => {
   return postProcessorList.find((item) => item.value === value)?.describe;
 };
+const handleTypeChange = (value: SelectValue, row: EmptyObjectType) => {
+  if (value === "reranker") {
+    Object.assign(row, {
+      top_n: 25,
+      reranker_model: {
+        model_id: "BAAI/bge-reranker-large",
+        model_path: "./models/BAAI/bge-reranker-large",
+        device: "AUTO",
+        weight: "INT4",
+      },
+    });
+  }
+};
 // Handling Model Folding Events
 const handleModelVisible = async (visible: boolean) => {
   if (visible) {
@@ -198,6 +213,7 @@ const handleModelChange = (item: EmptyObjectType, value: string) => {
 const handleAdd = () => {
   form.postprocessor.push({
     processor_type: "",
+    top_n: 25,
     reranker_model: {
       model_id: "",
       model_path: "",
@@ -220,6 +236,19 @@ const handleDeviceVisible = async (visible: boolean) => {
     }
   }
 };
+// Format parameter
+const formatFormParam = () => {
+  const { postprocessor } = form;
+  return postprocessor.map((item) => {
+    if (item.processor_type === "metadata_replace") {
+      return {
+        processor_type: item.processor_type,
+      };
+    } else {
+      return item;
+    }
+  });
+};
 // Validate the form, throw results form
 const handleValidate = (): Promise<object> => {
   return new Promise((resolve) => {
@@ -228,7 +257,7 @@ const handleValidate = (): Promise<object> => {
       .then(() => {
         resolve({
           result: true,
-          data: form,
+          data: { postprocessor: formatFormParam() },
         });
       })
       .catch(() => {
diff --git a/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/Retriever.vue b/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/Retriever.vue
index eb12bef097..9d22ccd08b 100644
--- a/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/Retriever.vue
+++ b/EdgeCraftRAG/ui/vue/src/views/pipeline/components/UpdateDialog/Retriever.vue
@@ -8,28 +8,33 @@
     autocomplete="off"
     class="form-wrap"
   >
-    <a-form-item
-      :label="$t('pipeline.config.retrieverType')"
-      name="retriever_type"
-    >
-      <a-select
-        v-model:value="form.retriever_type"
-        showSearch
-        :placeholder="$t('pipeline.valid.retrieverType')"
-      >
-        <a-select-option
-          v-for="item in retrieverList"
-          :key="item.value"
-          :value="item.value"
-          >{{ item.name }}</a-select-option
-        >
-      </a-select>
-      <FormTooltip :title="$t('pipeline.desc.retrieverType')" />
-    </a-form-item>
-    <div class="option-introduction">
-      <InfoCircleOutlined />
-      {{ $t(optionIntroduction!) }}
+    <div class="column-wrap">
+      <a-form-item
+        :label="$t('pipeline.config.retrieverType')"
+        name="retriever_type"
+        ><div class="flex-left">
+          <a-select
+            showSearch
+            v-model:value="form.retriever_type"
+            :placeholder="$t('pipeline.valid.retrieverType')"
+            @change="handleTypeChange"
+          >
+            <a-select-option
+              v-for="item in retrieverList"
+              :key="item.value"
+              :value="item.value"
+              >{{ item.name }}</a-select-option
+            >
+          </a-select>
+          <FormTooltip :title="$t('pipeline.desc.retrieverType')" />
+        </div>
+        <div class="option-introduction">
+          <InfoCircleOutlined />
+          {{ $t(optionIntroduction!) }}
+        </div>
+      </a-form-item>
     </div>
+
     <a-form-item
       :label="$t('pipeline.config.topk')"
       name="retrieve_topk"
@@ -60,32 +65,52 @@ import { reactive, ref } from "vue";
 import { Retriever } from "../../enum.ts";
 import { InfoCircleOutlined } from "@ant-design/icons-vue";
 import { useI18n } from "vue-i18n";
+import { useNotification } from "@/utils/common";
+import { SelectValue } from "ant-design-vue/es/select/index";
 
 const { t } = useI18n();
+const { antNotification } = useNotification();
+
 const props = defineProps({
   formData: {
     type: Object,
     default: () => {},
   },
+  formType: {
+    type: String,
+    default: "create",
+  },
 });
 interface FormType {
   retriever_type: string;
   retrieve_topk: number;
 }
+
 const { retriever_type = "vectorsimilarity", retrieve_topk = 30 } =
   props.formData?.retriever || {};
+const { indexer_type = "" } = props.formData?.indexer || {};
+
+const validateIndeserType = async (rule: any, value: string) => {
+  if (!value) {
+    return Promise.reject(t("pipeline.valid.retrieverType"));
+  }
+  if (indexer_type === "kbadmin_indexer" && value !== "kbadmin_retriever") {
+    return Promise.reject(t("pipeline.valid.retrieverTypeFormat"));
+  }
+  return Promise.resolve();
+};
 
 const formRef = ref<FormInstance>();
 const form = reactive<FormType>({
   retriever_type,
   retrieve_topk,
 });
-const rules = reactive({
+const rules: FormRules = reactive({
   retriever_type: [
     {
       required: true,
-      message: t("pipeline.valid.retrieverType"),
-      trigger: "blur",
+      validator: validateIndeserType,
+      trigger: "change",
     },
   ],
   retrieve_topk: [
@@ -96,11 +121,25 @@ const rules = reactive({
     },
   ],
 });
-const retrieverList = Retriever;
+
+const isCreate = computed(() => {
+  return props.formType === "create";
+});
+const isKbadmin = computed(() => {
+  return form.retriever_type === "kbadmin_retriever";
+});
+const retrieverList = computed(() => {
+  if (isCreate.value) {
+    return Retriever;
+  }
+  return isKbadmin.value
+    ? Retriever.filter((item) => item.value === "kbadmin_retriever")
+    : Retriever.filter((item) => item.value !== "kbadmin_retriever");
+});
 const optionIntroduction = computed(() => {
   const { retriever_type } = form;
 
-  return retrieverList.find((item) => item.value === retriever_type)?.describe;
+  return Retriever.find((item) => item.value === retriever_type)?.describe;
 });
 const sliderMarks = reactive<EmptyObjectType>({
   retrieval: {
@@ -108,18 +147,60 @@ const sliderMarks = reactive<EmptyObjectType>({
     200: "200",
   },
 });
+const handleTypeChange = (value: SelectValue) => {
+  if (value === "kbadmin_retriever")
+    antNotification(
+      "warning",
+      t("common.prompt"),
+      t("pipeline.valid.retrieverTypeTip")
+    );
+};
 const handleTopkChange = () => {
   formRef.value?.validateFields(["retrieve_topk"]);
 };
+const generateFormData = () => {
+  const baseData = { retriever: form };
+  const { indexer } = props.formData;
+
+  if (isKbadmin.value && indexer_type !== "kbadmin_indexer") {
+    antNotification(
+      "warning",
+      t("common.prompt"),
+      t("pipeline.valid.retrieverTypeTip")
+    );
+    return {
+      ...baseData,
+      node_parser: { parser_type: "kbadmin_parser" },
+      indexer: {
+        ...indexer,
+        indexer_type: "kbadmin_indexer",
+        embedding_url: "",
+        vector_url: "",
+      },
+    };
+  }
+
+  return baseData;
+};
 // Validate the form, throw results form
 const handleValidate = (): Promise<object> => {
   return new Promise((resolve) => {
     formRef.value
       ?.validate()
       .then(() => {
+        let dest = null;
+        if (indexer_type !== "kbadmin_indexer" && isKbadmin.value) {
+          antNotification(
+            "warning",
+            t("common.prompt"),
+            t("pipeline.valid.retrieverValid")
+          );
+          dest = 3;
+        }
         resolve({
           result: true,
-          data: { retriever: form },
+          data: generateFormData(),
+          dest,
         });
       })
       .catch(() => {
diff --git a/EdgeCraftRAG/ui/vue/src/views/pipeline/enum.ts b/EdgeCraftRAG/ui/vue/src/views/pipeline/enum.ts
index 712afd807f..0c1aadf6e8 100644
--- a/EdgeCraftRAG/ui/vue/src/views/pipeline/enum.ts
+++ b/EdgeCraftRAG/ui/vue/src/views/pipeline/enum.ts
@@ -22,6 +22,11 @@ export const NodeParser = [
     value: "unstructured",
     describe: "pipeline.desc.unstructured",
   },
+  {
+    name: "kbadmin",
+    value: "kbadmin_parser",
+    describe: "pipeline.desc.kbadmin",
+  },
 ] as const;
 
 export const Indexer = [
@@ -40,6 +45,11 @@ export const Indexer = [
     value: "milvus_vector",
     describe: "pipeline.desc.milvusVector",
   },
+  {
+    name: "kbadmin",
+    value: "kbadmin_indexer",
+    describe: "pipeline.desc.kbadmin",
+  },
 ] as const;
 export const Retriever = [
   {
@@ -57,6 +67,11 @@ export const Retriever = [
     value: "bm25",
     describe: "pipeline.desc.bm25",
   },
+  {
+    name: "kbadmin",
+    value: "kbadmin_retriever",
+    describe: "pipeline.desc.kbadmin",
+  },
 ] as const;
 
 export const PostProcessor = [
diff --git a/EdgeCraftRAG/ui/vue/src/views/pipeline/index.vue b/EdgeCraftRAG/ui/vue/src/views/pipeline/index.vue
index b0ff597a5f..f4440fd90a 100644
--- a/EdgeCraftRAG/ui/vue/src/views/pipeline/index.vue
+++ b/EdgeCraftRAG/ui/vue/src/views/pipeline/index.vue
@@ -15,6 +15,7 @@
     <System />
     <!-- pipelines list -->
     <Table
+      :loading
       :table-data="tableData"
       @create="handleCreate"
       @update="handleUpdate"
@@ -69,6 +70,7 @@ import { useI18n } from "vue-i18n";
 const { t } = useI18n();
 const { antNotification } = useNotification();
 const pipelineStore = pipelineAppStore();
+const loading = ref<boolean>(true);
 const createDialog = reactive<DialogType>({
   visible: false,
 });
@@ -87,9 +89,15 @@ const importDialog = reactive<DialogType>({
 const tableData = ref<EmptyArrayType>([]);
 
 const queryPipelineList = async () => {
-  const data: any = await getPipelineList();
-
-  tableData.value = [].concat(data);
+  try {
+    loading.value = true;
+    const data: any = await getPipelineList();
+    tableData.value = [].concat(data);
+  } catch (error) {
+    console.log(error);
+  } finally {
+    loading.value = false;
+  }
 };
 
 //create
diff --git a/EdgeCraftRAG/ui/vue/src/views/pipeline/type.ts b/EdgeCraftRAG/ui/vue/src/views/pipeline/type.ts
index f842d086da..c01c56ff7a 100644
--- a/EdgeCraftRAG/ui/vue/src/views/pipeline/type.ts
+++ b/EdgeCraftRAG/ui/vue/src/views/pipeline/type.ts
@@ -2,8 +2,9 @@
 // SPDX-License-Identifier: Apache-2.0
 
 export interface ModelType {
-  model_id: string;
+  model_id: string | undefined;
   model_path: string;
+  model_url?: string;
   device: string;
   weight?: string;
 }