From a8b4a9c42ee0875e7dd6a670af618e11fc8b4265 Mon Sep 17 00:00:00 2001 From: "Tian, Feng" Date: Fri, 17 May 2024 17:46:00 +0800 Subject: [PATCH 1/6] Add OPEA deployment design RFC Signed-off-by: Tian, Feng --- .../24-05-17-001-OPEA-Deployment-Design.md | 104 ++++++++++++++++++ community/rfcs/opea_deploy_workflow.png | Bin 0 -> 354815 bytes 2 files changed, 104 insertions(+) create mode 100644 community/rfcs/24-05-17-001-OPEA-Deployment-Design.md create mode 100644 community/rfcs/opea_deploy_workflow.png diff --git a/community/rfcs/24-05-17-001-OPEA-Deployment-Design.md b/community/rfcs/24-05-17-001-OPEA-Deployment-Design.md new file mode 100644 index 00000000..4c31a906 --- /dev/null +++ b/community/rfcs/24-05-17-001-OPEA-Deployment-Design.md @@ -0,0 +1,104 @@ +**Author** + +[ftian1](https://github.com/ftian1), [lvliang-intel](https://github.com/lvliang-intel), [hshen14](https://github.com/hshen14), **Edit Here to add your id** + +**Status** + +Under Review + +**Objective** + +Have a clear and good design for users to deploy their own GenAI applications on-premis or cloud environment. + + +**Motivation** + +This RFC is used to present the OPEA deployment related design for community discussion. + +**Design Proposal** + +The overall architecture please refer to [this](24-05-16-001-OPEA-Overall-Design.md). + +The proposed OPEA deployment workflow is + + + Deployment + + +For GenAI applications, we provides two interfaces for deployment + +1. on-premis deployment by python + + For example, constructing RAG (Retrieval-Augmented Generation) application with python code is something like: + + ```python + from comps import MicroService, ServiceOrchestrator + class ChatQnAService: +     def __init__(self, port=8080): +         self.service_builder = ServiceOrchestrator(port=port, endpoint="/v1/chatqna") +     def add_remote_service(self): +         embedding = MicroService( +             name="embedding", port=6000, expose_endpoint="/v1/embeddings", use_remote_service=True +         ) +         retriever = MicroService( +             name="retriever", port=7000, expose_endpoint="/v1/retrieval", use_remote_service=True +         ) +         rerank = MicroService( +             name="rerank", port=8000, expose_endpoint="/v1/reranking", use_remote_service=True +         ) +         llm = MicroService( +             name="llm", port=9000, expose_endpoint="/v1/chat/completions", use_remote_service=True +         ) +         self.service_builder.add(embedding).add(retriever).add(rerank).add(llm) +         self.service_builder.flow_to(embedding, retriever) +         self.service_builder.flow_to(retriever, rerank) +         self.service_builder.flow_to(rerank, llm) + + ``` + +2. cloud deployment by yaml + + For example, constructing RAG (Retrieval-Augmented Generation) application with yaml is something like: + + ```yaml + opea_micro_services: +   embedding: +     endpoint: /v1/embeddings + port: 6000 +   retrieval: +     endpoint: /v1/retrieval + port: 7000 +   reranking: +     endpoint: /v1/reranking + port: 8000 +   llm: +     endpoint: /v1/chat/completions + port: 9000 +   + opea_mega_service: +   port: 8080 +   mega_flow: +     - embedding >> retrieval >> reranking >> llm + + ``` + +When user wants to deploy the GenAI application to clould environment, such yaml configuration file should be defined and coverted to `docker composer` or `kubernetes manifest` or `kubernetes helm chart` files. + + +**Alternatives Considered** + +n/a + +**Compatibility** + +n/a + +**Miscs** + +- TODO List: + + - [ ] one click deployment on AWS, GCP, Azure cloud + - [ ] static cloud resource allocator vs dynamic cloud resource allocator + - [ ] k8s GMC with istio + + diff --git a/community/rfcs/opea_deploy_workflow.png b/community/rfcs/opea_deploy_workflow.png new file mode 100644 index 0000000000000000000000000000000000000000..184622853bbc7623a3b76d5f6a7de53767396941 GIT binary patch literal 354815 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zJkO*dF_Qa4piMA03p@4->`<*ZiBVjieq}eT4bJ0*QN9sSUr+XKY;jLNpdn=p4EEkN zp*o>`+i_w{{?n(RY7&yxuLI+_nn8GT@yJl}R{p4$mBC(JBSYQTyng0WWxznwC_deP zx&lMU5C;#sFYQIX)DpVhgEGApwR!g&nb{`&^BuoIQcp<965%Q0V-HTTJ;%%-OO)*iK=w(>uw2dZ+pFB1yN6JYb;#`N-{k&CSnwneMDwK!l-|`Pvd}KW9xzX0 z%~E|TW)fWyupN60jARj+EKae!q2`yALbhQ~q3I*PSH3Y<8 WOCG_>I_qu!Lklx&Q}ns(_x=x@t#Jte literal 0 HcmV?d00001 From a0a6e03ef420563e83dbdee7ab9704bb39513238 Mon Sep 17 00:00:00 2001 From: "Tian, Feng" Date: Fri, 24 May 2024 21:07:36 +0800 Subject: [PATCH 2/6] Add development process for OPEA GenAI application deployment Signed-off-by: Tian, Feng --- .../rfcs/24-05-17-001-OPEA-Deployment-Design.md | 6 ++++++ community/rfcs/opea_deploy_process.png | Bin 0 -> 81915 bytes 2 files changed, 6 insertions(+) create mode 100644 community/rfcs/opea_deploy_process.png diff --git a/community/rfcs/24-05-17-001-OPEA-Deployment-Design.md b/community/rfcs/24-05-17-001-OPEA-Deployment-Design.md index 4c31a906..96b80493 100644 --- a/community/rfcs/24-05-17-001-OPEA-Deployment-Design.md +++ b/community/rfcs/24-05-17-001-OPEA-Deployment-Design.md @@ -84,6 +84,12 @@ For GenAI applications, we provides two interfaces for deployment When user wants to deploy the GenAI application to clould environment, such yaml configuration file should be defined and coverted to `docker composer` or `kubernetes manifest` or `kubernetes helm chart` files. +The whole deployment process illustrated by the diagram below. + + + Deployment Process + + **Alternatives Considered** diff --git a/community/rfcs/opea_deploy_process.png b/community/rfcs/opea_deploy_process.png new file mode 100644 index 0000000000000000000000000000000000000000..3178d2d19eb07d2805801d8bb3e53e09fc5ec700 GIT binary patch literal 81915 zcmd?QWmr|;8wE&*)Rk^7NJy8`4bmmujg+)>cXuNQBHbXJ7q~PcAfYr!cgLmX;O{^4 z%zT&+^Lcz86)p$3XYY5fcfD(^6Q!ywgY|;+1soh4mYl4V8XO#=5gZ&sAsPzs3aI#q zANUX6RZT_$u6mq&7x)CpN?b`C4z4Z%4pgsTd0u$pQ<$oW`!i%rH`}Zmu 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z?)^{AmSLUpX;#8eToJ}0rtBjA^yC89(DhE(9E63nXlS28{q4@}>06T){N6cCw>o!x zD0=xxZc!RDIiXK>E|?n`=N{4co*#0k&E?}#Oi;wzk1rT;N~A+nfq>N3y6`nGeiv6D z3zXZ#mDp5&=U4vy#S$HrANxL(q;-72e2WQ{AhSYcT4-<5nnNF0y-)Y%y>oKDGJ&sp z-nUawBpc%pU8chknypeg{30LEL8nfz!dgi(qkcraTd<(K7)3#;IlA;wgXeB=!AKhN%97XSbN literal 0 HcmV?d00001 From 028989ae53685667e6831037a66df06c4a2edf8b Mon Sep 17 00:00:00 2001 From: irisdingbj Date: Tue, 28 May 2024 15:04:45 -0700 Subject: [PATCH 3/6] add kubernetes deployment info Signed-off-by: irisdingbj --- .../24-05-17-001-OPEA-Deployment-Design.md | 163 ++++++++++++++---- ...process.png => opea_deploy_process_v0.png} | Bin community/rfcs/opea_deploy_process_v1.png | Bin 0 -> 79010 bytes 3 files changed, 126 insertions(+), 37 deletions(-) rename community/rfcs/{opea_deploy_process.png => opea_deploy_process_v0.png} (100%) create mode 100644 community/rfcs/opea_deploy_process_v1.png diff --git a/community/rfcs/24-05-17-001-OPEA-Deployment-Design.md b/community/rfcs/24-05-17-001-OPEA-Deployment-Design.md index 96b80493..817edb79 100644 --- a/community/rfcs/24-05-17-001-OPEA-Deployment-Design.md +++ b/community/rfcs/24-05-17-001-OPEA-Deployment-Design.md @@ -1,6 +1,6 @@ **Author** -[ftian1](https://github.com/ftian1), [lvliang-intel](https://github.com/lvliang-intel), [hshen14](https://github.com/hshen14), **Edit Here to add your id** +[ftian1](https://github.com/ftian1), [lvliang-intel](https://github.com/lvliang-intel), [hshen14](https://github.com/hshen14), [irisdingbj](https://github.com/irisdingbj), [KfreeZ](https://github.com/kfreez), [zhlsunshine](https://github.com/zhlsunshine) **Edit Here to add your id** **Status** @@ -8,7 +8,7 @@ Under Review **Objective** -Have a clear and good design for users to deploy their own GenAI applications on-premis or cloud environment. +Have a clear and good design for users to deploy their own GenAI applications on docker or Kubernetes environment. **Motivation** @@ -27,67 +27,155 @@ The proposed OPEA deployment workflow is For GenAI applications, we provides two interfaces for deployment -1. on-premis deployment by python +1. Docker deployment by python For example, constructing RAG (Retrieval-Augmented Generation) application with python code is something like: ```python from comps import MicroService, ServiceOrchestrator class ChatQnAService: -     def __init__(self, port=8080): -         self.service_builder = ServiceOrchestrator(port=port, endpoint="/v1/chatqna") -     def add_remote_service(self): -         embedding = MicroService( -             name="embedding", port=6000, expose_endpoint="/v1/embeddings", use_remote_service=True -         ) -         retriever = MicroService( -             name="retriever", port=7000, expose_endpoint="/v1/retrieval", use_remote_service=True -         ) -         rerank = MicroService( -             name="rerank", port=8000, expose_endpoint="/v1/reranking", use_remote_service=True -         ) -         llm = MicroService( -             name="llm", port=9000, expose_endpoint="/v1/chat/completions", use_remote_service=True -         ) -         self.service_builder.add(embedding).add(retriever).add(rerank).add(llm) -         self.service_builder.flow_to(embedding, retriever) -         self.service_builder.flow_to(retriever, rerank) -         self.service_builder.flow_to(rerank, llm) + def __init__(self, port=8080): + self.service_builder = ServiceOrchestrator(port=port, endpoint="/v1/chatqna") + def add_remote_service(self): + embedding = MicroService( + name="embedding", port=6000, expose_endpoint="/v1/embeddings", use_remote_service=True + ) + retriever = MicroService( + name="retriever", port=7000, expose_endpoint="/v1/retrieval", use_remote_service=True + ) + rerank = MicroService( + name="rerank", port=8000, expose_endpoint="/v1/reranking", use_remote_service=True + ) + llm = MicroService( + name="llm", port=9000, expose_endpoint="/v1/chat/completions", use_remote_service=True + ) + self.service_builder.add(embedding).add(retriever).add(rerank).add(llm) + self.service_builder.flow_to(embedding, retriever) + self.service_builder.flow_to(retriever, rerank) + self.service_builder.flow_to(rerank, llm) ``` -2. cloud deployment by yaml +2. Kubernetes deployment by yaml For example, constructing RAG (Retrieval-Augmented Generation) application with yaml is something like: ```yaml opea_micro_services: -   embedding: -     endpoint: /v1/embeddings + embedding: + endpoint: /v1/embeddings port: 6000 -   retrieval: -     endpoint: /v1/retrieval + retrieval: + endpoint: /v1/retrieval port: 7000 -   reranking: -     endpoint: /v1/reranking + reranking: + endpoint: /v1/reranking port: 8000 -   llm: -     endpoint: /v1/chat/completions + llm: + endpoint: /v1/chat/completions port: 9000 -   + opea_mega_service: -   port: 8080 -   mega_flow: -     - embedding >> retrieval >> reranking >> llm + port: 8080 + mega_flow: + - embedding >> retrieval >> reranking >> llm ``` -When user wants to deploy the GenAI application to clould environment, such yaml configuration file should be defined and coverted to `docker composer` or `kubernetes manifest` or `kubernetes helm chart` files. +When user wants to deploy the GenAI application to Kubernetes environment, such yaml configuration file should be defined and coverted to `docker composer`or [GenAI Microservice Connecto -(GMC)](https://github.com/opea-project/GenAIInfra/tree/main/microservices-connector) Custom Resource files. +A sample GMC Custom Resource is like below: +```yaml + apiVersion: gmc.opea.io/v1alpha3 + kind: GMConnector + metadata: + labels: + app.kubernetes.io/name: gmconnector + name: chatqna + namespace: gmcsample + spec: + routerConfig: + name: router + serviceName: router-service + nodes: + root: + routerType: Sequence + steps: + - name: Embedding + internalService: + serviceName: embedding-service + config: + endpoint: /v1/embeddings + - name: TeiEmbedding + internalService: + serviceName: tei-embedding-service + config: + gmcTokenSecret: gmc-tokens + hostPath: /root/GMC/data/tei + modelId: BAAI/bge-base-en-v1.5 + endpoint: /embed + isDownstreamService: true + - name: Retriever + data: $response + internalService: + serviceName: retriever-redis-server + config: + RedisUrl: redis-vector-db + IndexName: rag-redis + tei_endpoint: tei-embedding-service + endpoint: /v1/retrieval + - name: VectorDB + internalService: + serviceName: redis-vector-db + isDownstreamService: true + - name: Reranking + data: $response + internalService: + serviceName: reranking-service + config: + tei_reranking_endpoint: tei-reranking-service + gmcTokenSecret: gmc-tokens + endpoint: /v1/reranking + - name: TeiReranking + internalService: + serviceName: tei-reranking-service + config: + gmcTokenSecret: gmc-tokens + hostPath: /root/GMC/data/rerank + modelId: BAAI/bge-reranker-large + endpoint: /rerank + isDownstreamService: true + - name: Llm + data: $response + internalService: + serviceName: llm-service + config: + tgi_endpoint: tgi-service + gmcTokenSecret: gmc-tokens + endpoint: /v1/chat/completions + - name: Tgi + internalService: + serviceName: tgi-service + config: + gmcTokenSecret: gmc-tokens + hostPath: /root/GMC/data/tgi + modelId: Intel/neural-chat-7b-v3-3 + endpoint: /generate + isDownstreamService: true +``` +There should be an available `gmconnectors.gmc.opea.io` CR named `chatqna` under the namespace `gmcsample`, showing below: + +```bash +$kubectl get gmconnectors.gmc.opea.io -n gmcsample +NAME URL READY AGE +chatqa http://router-service.gmcsample.svc.cluster.local:8080 Success 3m +``` + +And the user can access the application pipeline via the value of `URL` field in above. 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zwkFE6YL-9s!boyn{h;aN0hEYeRrd3+-bi$%2=0ZXNoBx6Hlws6$A2(E9WS8wI zTgmdjB!d%7o|1ZpcY>)yBd~r`2B`R#HNDW-eswa3rQ<3q^g%osy@>W` zcmRjHu*!OHz|}hz{2^pI{hCFo_umGj@=zW+fwMzUsVh>ki-0|} zn4|$~D=55hebG6pzwy^2G4_cR5 Hdc^( Date: Thu, 30 May 2024 09:46:33 +0800 Subject: [PATCH 4/6] Revise the OPEA deployment design doc Signed-off-by: Tian, Feng --- ... => 24-05-17-OPEA-001-Deployment-Design.md} | 17 +++++++++-------- community/rfcs/opea_deploy_process_v2.png | Bin 0 -> 71484 bytes 2 files changed, 9 insertions(+), 8 deletions(-) rename community/rfcs/{24-05-17-001-OPEA-Deployment-Design.md => 24-05-17-OPEA-001-Deployment-Design.md} (86%) create mode 100644 community/rfcs/opea_deploy_process_v2.png diff --git a/community/rfcs/24-05-17-001-OPEA-Deployment-Design.md b/community/rfcs/24-05-17-OPEA-001-Deployment-Design.md similarity index 86% rename from community/rfcs/24-05-17-001-OPEA-Deployment-Design.md rename to community/rfcs/24-05-17-OPEA-001-Deployment-Design.md index 817edb79..c2298612 100644 --- a/community/rfcs/24-05-17-001-OPEA-Deployment-Design.md +++ b/community/rfcs/24-05-17-OPEA-001-Deployment-Design.md @@ -13,11 +13,11 @@ Have a clear and good design for users to deploy their own GenAI applications on **Motivation** -This RFC is used to present the OPEA deployment related design for community discussion. +This RFC presents the OPEA deployment-related design for community discussion. **Design Proposal** -The overall architecture please refer to [this](24-05-16-001-OPEA-Overall-Design.md). +Refer to this [OPEA overall architecture design document](24-05-16-OPEA-001-Overall-Design.md). The proposed OPEA deployment workflow is @@ -25,11 +25,11 @@ The proposed OPEA deployment workflow is Deployment -For GenAI applications, we provides two interfaces for deployment +We provide two interfaces for deploying GenAI applications: 1. Docker deployment by python - For example, constructing RAG (Retrieval-Augmented Generation) application with python code is something like: + Here is a python example for constructing a RAG (Retrieval-Augmented Generation) application: ```python from comps import MicroService, ServiceOrchestrator @@ -56,9 +56,9 @@ For GenAI applications, we provides two interfaces for deployment ``` -2. Kubernetes deployment by yaml +2. Kubernetes deployment using YAML - For example, constructing RAG (Retrieval-Augmented Generation) application with yaml is something like: + Here is a YAML example for constructing a RAG (Retrieval-Augmented Generation) application: ```yaml opea_micro_services: @@ -82,7 +82,8 @@ For GenAI applications, we provides two interfaces for deployment ``` -When user wants to deploy the GenAI application to Kubernetes environment, such yaml configuration file should be defined and coverted to `docker composer`or [GenAI Microservice Connecto -(GMC)](https://github.com/opea-project/GenAIInfra/tree/main/microservices-connector) Custom Resource files. +When deploying the GenAI application to Kubernetes environment, you should define and convert the YAML configuration file to an appropriate `docker compose`, `kubernetes manifest`, , `kubernetes helm chart` or `[GenAI Microservice Connector-(GMC)](https://github.com/opea-project/GenAIInfra/tree/main/microservices-connector) custom resource` file. + A sample GMC Custom Resource is like below: ```yaml apiVersion: gmc.opea.io/v1alpha3 @@ -175,7 +176,7 @@ And the user can access the application pipeline via the value of `URL` field in The whole deployment process illustrated by the diagram below. - Deployment Process + Deployment Process diff --git a/community/rfcs/opea_deploy_process_v2.png b/community/rfcs/opea_deploy_process_v2.png new file mode 100644 index 0000000000000000000000000000000000000000..9337451a2bc19c45312ce41fb6b00d4a69ad492a GIT binary patch literal 71484 zcmcG0Wmpt#_^%4m%}R%Yz|tVnDbgL%-Q6G{B@MfTbk~wfNiQwkt$;KvDGkzfhWCB{ z=X^ZZ`Eb0(i&E>3e_z1;|M7ytsV^xh;X6~s2+#H# zN~su%$fZ`FA?8>eLlqU{Uwb4hy0vKU!?5C_Z*GFk+BehfoUeC^&1NbLG;OxlGo0Gu zF2X8#Mw04KfBpJ(c|Pw{WzvOGS`bHUTG@+)EA)AYtr;sVEltgTHI&#C=t*m9>+cmppML)QxiVuE5L#SZ zOu=r@1oH6ksIIJ~c4|3BIcPam`kst$_ z_W!|<;~R8y(2U!#^ojZYB&FTBH;VM~s0(*>bu}>H7D26DXPe}4HW4fyjo?E>ad9}z zy=Bq<{$yuoXZrU+-_=%5Y(c?mZwF;v0vJe+VhrwrC?k+mZQ}Z8SQ2rt%URi5{}Lz( 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zdD7wkg2M*^fOqWWbX=46cEvCIyXtsB&cksSMH=C)YYnwug!rmPW+(10yZsCogxJ#? z$o6OYmQe_Vh-hh4kWtqz3{_wPVrLpQ4`0Lp5Ru8q63?S2N`D5=YR0KW;3vq9fV9P2 zKK&;M^vc`bix(O`I+r21eqn@71e@~&>}g)@ zpR~F^$~Wz*LWj3^665d&+UzRmrt}zJk*k?-O&rcJd3Kj#0z!fvw0N`}BBSR3%6)4( zZYVp*3pY7y1<8nKl3|Me0uj@;fHCvN_S|i%{Z2pi0vPS#VvVqzKVd=Z3(;wRuY*wo zF!VB9Kn*c$u>;+ZAeDAl~i!)sn zU>?K7r$e~_-Kja=3u|GZXhS&Dnam73y_e9E~o=+L74MJ8sNAOPtJyc-cQW( z6AdKKUxm!Av;>!?F;&g>ce{| zq+`5DW@Jf-8ZNcRx62Ad$iGl>|G(w7|37~C cQGWZNbyBnVY=_0O_c%a{vGU literal 0 HcmV?d00001 From 7c48ab1e06a4a4d27dd6472986b0508e8afa3564 Mon Sep 17 00:00:00 2001 From: irisdingbj Date: Wed, 12 Jun 2024 04:28:17 +0800 Subject: [PATCH 5/6] update kubernetes deployment info Signed-off-by: irisdingbj --- .../24-05-17-OPEA-001-Deployment-Design.md | 24 +++++++++++-------- 1 file changed, 14 insertions(+), 10 deletions(-) diff --git a/community/rfcs/24-05-17-OPEA-001-Deployment-Design.md b/community/rfcs/24-05-17-OPEA-001-Deployment-Design.md index c2298612..6b48c90e 100644 --- a/community/rfcs/24-05-17-OPEA-001-Deployment-Design.md +++ b/community/rfcs/24-05-17-OPEA-001-Deployment-Design.md @@ -1,6 +1,6 @@ **Author** -[ftian1](https://github.com/ftian1), [lvliang-intel](https://github.com/lvliang-intel), [hshen14](https://github.com/hshen14), [irisdingbj](https://github.com/irisdingbj), [KfreeZ](https://github.com/kfreez), [zhlsunshine](https://github.com/zhlsunshine) **Edit Here to add your id** +[ftian1](https://github.com/ftian1), [lvliang-intel](https://github.com/lvliang-intel), [hshen14](https://github.com/hshen14), [mkbhanda](https://github.com/mkbhanda), [irisdingbj](https://github.com/irisdingbj), [KfreeZ](https://github.com/kfreez), [zhlsunshine](https://github.com/zhlsunshine) **Edit Here to add your id** **Status** @@ -53,7 +53,7 @@ We provide two interfaces for deploying GenAI applications: self.service_builder.flow_to(embedding, retriever) self.service_builder.flow_to(retriever, rerank) self.service_builder.flow_to(rerank, llm) - + ``` 2. Kubernetes deployment using YAML @@ -74,17 +74,21 @@ We provide two interfaces for deploying GenAI applications: llm: endpoint: /v1/chat/completions port: 9000 - + opea_mega_service: port: 8080 mega_flow: - embedding >> retrieval >> reranking >> llm - + ``` +This YAML will be acting as a unified language interface for end user to define their GenAI Application. + +When deploying the GenAI application to Kubernetes environment, you should define and convert the YAML configuration file to an appropriate [docker compose](https://docs.docker.com/compose/), or [GenAI Microservice Connector-(GMC)](https://github.com/opea-project/GenAIInfra/tree/main/microservices-connector) custom resource file. + +Note: A convert tool will be provided for OPEA to convert unified language interface to docker componse or GMC. -When deploying the GenAI application to Kubernetes environment, you should define and convert the YAML configuration file to an appropriate `docker compose`, `kubernetes manifest`, , `kubernetes helm chart` or `[GenAI Microservice Connector-(GMC)](https://github.com/opea-project/GenAIInfra/tree/main/microservices-connector) custom resource` file. +A sample GMC [Custom Resource](https://kubernetes.io/docs/concepts/extend-kubernetes/api-extension/custom-resources/) is like below: -A sample GMC Custom Resource is like below: ```yaml apiVersion: gmc.opea.io/v1alpha3 kind: GMConnector @@ -161,7 +165,7 @@ A sample GMC Custom Resource is like below: hostPath: /root/GMC/data/tgi modelId: Intel/neural-chat-7b-v3-3 endpoint: /generate - isDownstreamService: true + isDownstreamService: true ``` There should be an available `gmconnectors.gmc.opea.io` CR named `chatqna` under the namespace `gmcsample`, showing below: @@ -176,13 +180,15 @@ And the user can access the application pipeline via the value of `URL` field in The whole deployment process illustrated by the diagram below. + Deployment Process Deployment Process **Alternatives Considered** -n/a +[Kserve](https://github.com/kserve/kserve): has provided [InferenceGraph](https://kserve.github.io/website/0.9/modelserving/inference_graph/), however it only supports inference service and lack of deployment support. + **Compatibility** @@ -196,5 +202,3 @@ n/a - [ ] static cloud resource allocator vs dynamic cloud resource allocator - [ ] k8s GMC with istio - - From 86a9e23ff03be86db76f7df7f8c7593bcaee639e Mon Sep 17 00:00:00 2001 From: irisdingbj Date: Wed, 12 Jun 2024 04:31:14 +0800 Subject: [PATCH 6/6] remove v2 pic Signed-off-by: irisdingbj --- community/rfcs/24-05-17-OPEA-001-Deployment-Design.md | 1 - 1 file changed, 1 deletion(-) diff --git a/community/rfcs/24-05-17-OPEA-001-Deployment-Design.md b/community/rfcs/24-05-17-OPEA-001-Deployment-Design.md index 6b48c90e..23c1e2b2 100644 --- a/community/rfcs/24-05-17-OPEA-001-Deployment-Design.md +++ b/community/rfcs/24-05-17-OPEA-001-Deployment-Design.md @@ -181,7 +181,6 @@ The whole deployment process illustrated by the diagram below. Deployment Process - Deployment Process