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workloads: Added opea-chatqna workload yaml's & readme
Signed-off-by: vbedida79 <veenadhari.bedida@intel.com>
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‎workloads/opea/chatqna/README.md

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# Deploy OPEA ChatQnA workload on OCP
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## Overview
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The workload is based on the [OPEA ChatQnA Application](https://github.com/opea-project/GenAIExamples/tree/v0.8/ChatQnA) running on Intel® Gaudi Accelerator with OpenShift and OpenShift AI. Refer to the [OPEA Generative AI Examples](https://github.com/opea-project/GenAIExamples/tree/v0.8) for more details about the OPEA workloads.
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**Note**: It is still under heavy development, and the updates are expected.
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## Prerequisites
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* Provisioned RHOCP cluster. Follow steps [here](/README.md#provisioning-rhocp-cluster)
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* The Persistent storage using NFS is ready. Refer to [documentation](https://docs.openshift.com/container-platform/4.16/storage/persistent_storage/persistent-storage-nfs.html) for the details to set it up.
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**Note**: Refer to [documentation](https://docs.openshift.com/container-platform/4.16/storage/index.html) for setting up other types of persistent storages.
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* Provisioned Intel Gaudi accelerator on RHOCP cluster. Follow steps [here](/gaudi/README.md)
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* RHOAI is installed. Follow steps [here](../inference/README.md/#install-rhoai)
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* The Intel Gaudi AI accelerator is enabled with RHOAI. Follow steps [here]((../inference/README.md/#enable-intel-gaudi-ai-accelerator-with-rhoai))
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* Minio based S3 service ready for RHOAI. Follow steps [here](https://ai-on-openshift.io/tools-and-applications/minio/minio/#create-a-matching-data-connection-for-minio)
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## Deploy Model Serving for OPEA ChatQnA Microservices with RHOAI
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### Create OpenShift AI Data Science Project
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* Click ```Search -> Routes -> rhods-dashboard``` from the OCP web console and launch the RHOAI dashboard.
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* Follow the dashboard and click ```Data Science Projects``` to create a project. For example, ```OPEA-chatqna-modserving```.
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### Preload the models
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* Refer to [link](https://huggingface.co/docs/hub/en/models-downloading) and download the model [Llama2-70b-chat-hf](https://huggingface.co/meta-llama/Llama-2-70b-chat-hf).
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* Refer to [link](https://ai-on-openshift.io/tools-and-applications/minio/minio/#create-a-matching-data-connection-for-minio) and upload the model to minio/s3 storage.
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* Click ```OPEA-chatqna-modserving```, and choose ```Data Connection``` section. In the fields, add your access and secret keys from minio. Follow [link](https://ai-on-openshift.io/tools-and-applications/minio/minio/#create-a-matching-data-connection-for-minio).
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### Launch the Model Serving with Intel Gaudi AI Accelerator
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* Click on the Settings and choose ```ServingRuntime```. Copy or import the [tgi_gaudi_servingruntime.yaml](tgi-gaudi-servingruntime.yaml). The [tgi-gaudi](https://github.com/huggingface/tgi-gaudi) serving runtime is used. Follow the image below.
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* In the project ```OPEA-chatqna-modserving``` --> ```Models``` section and follow the image below.
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* The model server is now in the creation state. Once ready, the status will be updated to green and the inference endpoint can be seen. Refer to the image below.
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## Deploy ChatQnA Megaservice and Database
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### Create namespace
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```
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oc create namespace opea-chatqna
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```
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### Create persistent volumes
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The NFS is used to create the Persistent Volumes for ChatQnA MegaService to claim and use.
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Make sure to update NFS server IP and path in ```persistent_volumes.yaml``` before applying command below.
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For example:
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```
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nfs:
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server: 10.20.1.2 # nfs server
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path: /my_nfs # nfs path
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```
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```
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$ oc apply -f https://raw.githubusercontent.com/intel/intel-technology-enabling-for-openshift/main/workloads/opea/chatqna/persistent_volumes.yaml
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```
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* Check that the persistent volumes are created:
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```
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$ oc get pv
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NAME CAPACITY ACCESS MODES RECLAIM POLICY STATUS
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chatqna-megaservice-pv-0 100Mi RWO Retain Available
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chatqna-megaservice-pv-1 100Mi RWO Retain Available
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chatqna-megaservice-pv-2 100Mi RWO Retain Available
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```
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### Building OPEA ChatQnA MegaService Container Image
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```
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create_megaservice_container.sh
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```
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### Deploy Redis Vector Database Service
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```
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$ oc apply -f https://raw.githubusercontent.com/intel/intel-technology-enabling-for-openshift/main/workloads/opea/chatqna/redis_deployment_service.yaml
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```
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Check that the pod and service are running:
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```
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$ oc get pods
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NAME READY STATUS RESTARTS AGE
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redis-vector-db-6b5747bf7-sl8fr 1/1 Running 0 21s
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```
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```
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$ oc get svc
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NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
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redis-vector-db ClusterIP 1.2.3.4 <none> 6379/TCP,8001/TCP 43s
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```
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### Deploy ChatQnA MegaService
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Update the inference endpoint from the <image name> in the chatqna_megaservice_deployment.
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```
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$ oc apply -f https://raw.githubusercontent.com/intel/intel-technology-enabling-for-openshift/main/workloads/opea/chatqna/chatqna_megaservice_deployment.yaml
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```
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Check that the pod and service are running:
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```
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$ oc get pods
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NAME READY STATUS RESTARTS AGE
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chatqna-megaservice-54487649b5-sgsh2 1/1 Running 0 95s
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```
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```
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$ oc get svc
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NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
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chatqna-megaservice ClusterIP 1.2.3.4 <none> 8000/TCP 99s
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```
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### Verify the Megaservice
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Use the command below:
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```
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curl <megaservice_pod_ip>/v1/rag/chat_stream \
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-X POST \
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-d '{"query":"What is a constellation?"}' \
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-H 'Content-Type: application/json'
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```

‎workloads/opea/chatqna/chatqna_megaservice_buildconfig.yaml

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# Copyright (c) 2024 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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apiVersion: image.openshift.io/v1
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kind: ImageStream
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metadata:
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name: chatqna-megaservice
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namespace: opea-chatqna
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spec: {}
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---
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apiVersion: build.openshift.io/v1
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kind: BuildConfig
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metadata:
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name: chatqna-megaservice
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namespace: opea-chatqna
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spec:
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triggers:
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- type: "ConfigChange"
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- type: "ImageChange"
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runPolicy: "Serial"
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source:
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dockerfile: |
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FROM langchain/langchain:latest
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RUN apt-get update -y && apt-get install -y --no-install-recommends --fix-missing \
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libgl1-mesa-glx \
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libjemalloc-dev
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RUN useradd -m -s /bin/bash user && \
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mkdir -p /home/user && \
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chown -R user /home/user/
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USER user
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COPY requirements.txt /tmp/requirements.txt
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USER root
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COPY tls.crt /rhoai-ca/tls.crt
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RUN cat /rhoai-ca/tls.crt | tee -a '/usr/lib/ssl/cert.pem'
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USER user
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RUN pip install --no-cache-dir --upgrade pip && \
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pip install --no-cache-dir -r /tmp/requirements.txt
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ENV PYTHONPATH=$PYTHONPATH:/ws:/home/user:/home/user/qna-app/app
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WORKDIR /home/user/qna-app
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COPY qna-app /home/user/qna-app
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ENTRYPOINT ["/usr/bin/sleep", "infinity"]
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triggers:
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- type: ConfigChange
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runPolicy: SerialLatestOnly
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strategy:
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type: Docker
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dockerStrategy: {}
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postCommit: {}
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output:
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to:
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kind: ImageStreamTag
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name: chatqna-megaservice:latest

‎workloads/opea/chatqna/chatqna_megaservice_deployment.yaml

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# Copyright (c) 2024 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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---
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apiVersion: v1
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kind: PersistentVolumeClaim
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metadata:
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name: chatqna-megaservice-pvc-0
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namespace: opea-chatqna
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spec:
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accessModes:
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- ReadWriteOnce
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resources:
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requests:
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storage: 100Mi
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---
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apiVersion: v1
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kind: PersistentVolumeClaim
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metadata:
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name: chatqna-megaservice-pvc-1
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namespace: opea-chatqna
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spec:
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accessModes:
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- ReadWriteOnce
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resources:
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requests:
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storage: 100Mi
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---
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apiVersion: v1
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kind: PersistentVolumeClaim
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metadata:
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name: chatqna-megaservice-pvc-2
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namespace: opea-chatqna
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spec:
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accessModes:
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- ReadWriteOnce
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resources:
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requests:
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storage: 100Mi
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---
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apiVersion: apps/v1
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kind: Deployment
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metadata:
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name: chatqna-megaservice
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namespace: opea-chatqna
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spec:
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selector:
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matchLabels:
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app: chatqna-megaservice
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replicas: 1
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template:
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metadata:
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labels:
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app: chatqna-megaservice
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spec:
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serviceAccount: opea-chatqna
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containers:
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- name: chatqna-megaservice
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image: 'image-registry.openshift-image-registry.svc:5000/opea-chatqna/chatqna-megaservice:latest'
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env:
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- name: EMBED_MODEL
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value: BAAI/bge-base-en-v1.5
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- name: HUGGINGFACEHUB_API_TOKEN
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valueFrom:
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secretKeyRef:
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key: HUGGINGFACEHUB_API_TOKEN
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name: hf-token
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- name: MODEL_SIZE
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value: 70b
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- name: PYTHONPATH
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value: $PYTHONPATH:/ws:/home/user:/home/user/qna-app/app
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- name: RAG_UPLOAD_DIR
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value: /upload_dir
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- name: REDIS_PORT
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value: "6379"
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- name: REDIS_HOST
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value: "redis-vector-db"
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- name: REDIS_SCHEMA
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value: schema_dim_768.yml
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- name: TGI_ENDPOINT
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value: http://xxx.xxx.xxx.xxx:xxx
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ports:
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- containerPort: 8000
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command:
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- /bin/bash
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- '-c'
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- |
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cd /ws && \
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python ingest.py /ws/data_intel/ && \
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cd /home/user/qna-app && \
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python app/server.py
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volumeMounts:
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- mountPath: /ws
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name: chatqna-megaservice-pvc-0
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- mountPath: /test
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name: chatqna-megaservice-pvc-1
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- mountPath: /upload_dir
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name: chatqna-megaservice-pvc-2
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volumes:
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- name: chatqna-megaservice-pvc-0
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persistentVolumeClaim:
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claimName: chatqna-megaservice-pvc-0
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- name: chatqna-megaservice-pvc-1
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persistentVolumeClaim:
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claimName: chatqna-megaservice-pvc-1
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- name: chatqna-megaservice-pvc-2
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persistentVolumeClaim:
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claimName: chatqna-megaservice-pvc-2
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---
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# Chatqna megaservice Service
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apiVersion: v1
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kind: Service
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metadata:
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name: chatqna-megaservice
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namespace: opea-chatqna
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spec:
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type: ClusterIP
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selector:
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app: chatqna-megaservice
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ports:
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- port: 8000
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targetPort: 8000

‎workloads/opea/chatqna/create_megaservice_container.sh

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# Copyright (c) 2024 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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#!/bin/sh
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tag="v0.8"
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namespace="opea-chatqna"
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repo="https://github.com/opea-project/GenAIExamples.git"
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yaml_url="https://raw.githubusercontent.com/intel/intel-technology-enabling-for-openshift/main/workloads/opea/chatqna/chatqna_megaservice_buildconfig.yaml"
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oc $namespace &&
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git clone --depth 1 --branch $tag $repo &&
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cd GenAIExamples/ChatQnA/deprecated/langchain/docker &&
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oc extract secret/knative-serving-cert -n istio-system --to=. --keys=tls.crt &&
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oc apply -f $yaml_url &&
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oc start-build chatqna-megaservice --from-dir=./ --follow

‎workloads/opea/chatqna/persistent_volumes.yaml

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# Copyright (c) 2024 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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---
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apiVersion: v1
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kind: PersistentVolume
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metadata:
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name: chatqna-megaservice-pv-0
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spec:
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capacity:
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storage: 100Mi
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accessModes:
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- ReadWriteOnce
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persistentVolumeReclaimPolicy: Retain
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nfs:
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server: x.x.x.x # nfs server
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path: /nfs # nfs path
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---
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apiVersion: v1
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kind: PersistentVolume
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metadata:
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name: chatqna-megaservice-pv-1
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spec:
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capacity:
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storage: 100Mi
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accessModes:
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- ReadWriteOnce
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persistentVolumeReclaimPolicy: Retain
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nfs:
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server: x.x.x.x # nfs server
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path: /nfs # nfs path
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---
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apiVersion: v1
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kind: PersistentVolume
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metadata:
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name: chatqna-megaservice-pv-2
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spec:
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capacity:
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storage: 100Mi
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accessModes:
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- ReadWriteOnce
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persistentVolumeReclaimPolicy: Retain
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nfs:
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server: x.x.x.x # nfs server
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path: /nfs # nfs path

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