From 0c61b69ca09541e152aaff7e64abd609129f3fd9 Mon Sep 17 00:00:00 2001 From: Ying Hu Date: Fri, 18 Oct 2024 15:28:56 +0800 Subject: [PATCH 01/34] Update README.md for usage experience (#215) * Update README.md for usage experience Update README.md for usage experience Check docker images before run the test so able to avoid the first error. * Update README.md for check before run Signed-off-by: alexsin368 --- getting-started/README.md | 12 ++++++++++-- 1 file changed, 10 insertions(+), 2 deletions(-) diff --git a/getting-started/README.md b/getting-started/README.md index c5a2edf3..f3bab89f 100644 --- a/getting-started/README.md +++ b/getting-started/README.md @@ -33,7 +33,6 @@ To deploy ChatQnA services, follow these steps: git clone https://github.com/opea-project/GenAIExamples.git cd GenAIExamples/ChatQnA ``` - ### Set the required environment variables: ``` # Example: host_ip="192.168.1.1" @@ -42,7 +41,6 @@ export host_ip="External_Public_IP" export no_proxy="Your_No_Proxy" export HUGGINGFACEHUB_API_TOKEN="Your_Huggingface_API_Token" ``` - If you are in a proxy environment, also set the proxy-related environment variables: ``` export http_proxy="Your_HTTP_Proxy" @@ -89,6 +87,16 @@ In the following cases, you will need to build the docker image from source by y Refer to the {ref}`ChatQnA Example Deployment Options ` section for building from source instructions matching your hardware. ## Interact with ChatQnA Megaservice and Microservice +Before interact ChatQnA Service, make sure the TGI service is ready (which takes up to 2 minutes to start). +``` +docker ps +# expected: all images's status are up +# TGI example on on Xeon and Nvidia GPU +docker logs tgi-service | grep Connected +# TGI example on on Gaudi +docker logs tgi-gaudi-service | grep Connected +# execpted output: ... INFO text_generation_router::server: router/src/server.rs:2311: Connected +``` ``` curl http://${host_ip}:8888/v1/chatqna \ -H "Content-Type: application/json" \ From b3e2a61c90f3cf4218c5ce6f14c9540b2c93bc08 Mon Sep 17 00:00:00 2001 From: xiguiw <111278656+xiguiw@users.noreply.github.com> Date: Fri, 18 Oct 2024 16:49:08 +0800 Subject: [PATCH 02/34] Update ChatQnA APIC deploy docuement (#216) Signed-off-by: Wang, Xigui Signed-off-by: alexsin368 --- examples/ChatQnA/deploy/aipc.md | 158 +++++++++++++++++++++++--------- 1 file changed, 113 insertions(+), 45 deletions(-) diff --git a/examples/ChatQnA/deploy/aipc.md b/examples/ChatQnA/deploy/aipc.md index 141a41f9..8ec007e3 100644 --- a/examples/ChatQnA/deploy/aipc.md +++ b/examples/ChatQnA/deploy/aipc.md @@ -36,18 +36,18 @@ fundamental necessary components used to build examples you find in GenAIExamples and deploy them as microservices. ``` +mkdir ~/OPEA -p +cd ~/OPEA git clone https://github.com/opea-project/GenAIComps.git git clone https://github.com/opea-project/GenAIExamples.git ``` Checkout the release tag ``` -cd GenAIComps +cd ~/OPEA/GenAIComps git checkout tags/v1.0 ``` -The examples utilize model weights from Ollama and langchain. - Setup your [HuggingFace](https://huggingface.co/) account and generate [user access token](https://huggingface.co/docs/transformers.js/en/guides/private#step-1-generating-a-user-access-token). @@ -69,6 +69,103 @@ export http_proxy=${your_http_proxy} export https_proxy=${your_http_proxy} ``` +The examples utilize model weights from Ollama and langchain. + +### Set Up Ollama LLM Service +We use [Ollama](https://ollama.com/) as our LLM service for AIPC. + +Please follow the instructions to set up Ollama on your PC. This will set the entrypoint needed for the Ollama to suit the ChatQnA examples. + +#### Install Ollama Service + +Install Ollama service with one command: + +``` +curl -fsSL https://ollama.com/install.sh | sh +``` + +#### Set Ollama Service Configuration + +Ollama Service Configuration file is /etc/systemd/system/ollama.service. Edit the file to set OLLAMA_HOST environment. +Replace **** with your host IPV4 (please use external public IP). For example the host_ip is 10.132.x.y, then `Environment="OLLAMA_HOST=10.132.x.y:11434"'. + +``` +Environment="OLLAMA_HOST=host_ip:11434" +``` + +#### Set https_proxy environment for Ollama + +If your system access network through proxy, add https_proxy in Ollama Service Configuration file + +``` +Environment="https_proxy=Your_HTTPS_Proxy" +``` + +#### Restart Ollama services + +``` +$ sudo systemctl daemon-reload +$ sudo systemctl restart ollama.service +``` + +#### Check the service started + +``` +netstat -tuln | grep 11434 +``` + +The output are: + +``` +tcp 0 0 10.132.x.y:11434 0.0.0.0:* LISTEN +``` + +#### Pull Ollama LLM model + +Run the command to download LLM models. The is the one set in [Ollama Service Configuration](#Set-Ollama-Service-Configuration) + +``` +export host_ip= +export OLLAMA_HOST=http://${host_ip}:11434 +ollama pull llama3.2 +``` + +After downloaded the models, you can list the models by `ollama list`. + +The output should be similar to the following: + +``` +NAME ID SIZE MODIFIED +llama3.2:latest a80c4f17acd5 2.0 GB 2 minutes ago +``` + +### Consume Ollama LLM Service + +Access ollama service to verify that the ollama is functioning correctly. + +```bash +curl http://${host_ip}:11434/api/generate -d '{"model": "llama3.2", "prompt":"What is Deep Learning?"}' +``` + +The outputs are similar to these: + +``` +{"model":"llama3.2","created_at":"2024-10-12T12:55:28.098813868Z","response":"Deep","done":false} +{"model":"llama3.2","created_at":"2024-10-12T12:55:28.124514468Z","response":" learning","done":false} +{"model":"llama3.2","created_at":"2024-10-12T12:55:28.149754216Z","response":" is","done":false} +{"model":"llama3.2","created_at":"2024-10-12T12:55:28.180420784Z","response":" a","done":false} +{"model":"llama3.2","created_at":"2024-10-12T12:55:28.229185873Z","response":" subset","done":false} +{"model":"llama3.2","created_at":"2024-10-12T12:55:28.263956118Z","response":" of","done":false} +{"model":"llama3.2","created_at":"2024-10-12T12:55:28.289097354Z","response":" machine","done":false} +{"model":"llama3.2","created_at":"2024-10-12T12:55:28.316838918Z","response":" learning","done":false} +{"model":"llama3.2","created_at":"2024-10-12T12:55:28.342309506Z","response":" that","done":false} +{"model":"llama3.2","created_at":"2024-10-12T12:55:28.367221264Z","response":" involves","done":false} +{"model":"llama3.2","created_at":"2024-10-12T12:55:28.39205893Z","response":" the","done":false} +{"model":"llama3.2","created_at":"2024-10-12T12:55:28.417933974Z","response":" use","done":false} +{"model":"llama3.2","created_at":"2024-10-12T12:55:28.443110388Z","response":" of","done":false} +... +``` + ## Prepare (Building / Pulling) Docker images This step will involve building/pulling ( maybe in future) relevant docker @@ -88,6 +185,7 @@ From within the `GenAIComps` folder #### Build Dataprep Image ``` +cd ~/OPEA/GenAIComps docker build --no-cache -t opea/dataprep-redis:latest --build-arg https_proxy=$https_proxy \ --build-arg http_proxy=$http_proxy -f comps/dataprep/redis/langchain/Dockerfile . ``` @@ -120,10 +218,6 @@ docker build --no-cache -t opea/reranking-tei:latest --build-arg https_proxy=$ht :::{tab-item} Ollama :sync: Ollama -We set up the Ollama LLM service with one command -```bash -curl -fsSL https://ollama.com/install.sh | sh -``` Next, we'll build the Ollama microservice docker. This will set the entry point needed for Ollama to suit the ChatQnA examples @@ -132,38 +226,10 @@ docker build --no-cache -t opea/llm-ollama:latest --build-arg https_proxy=$https --build-arg http_proxy=$http_proxy -f comps/llms/text-generation/ollama/langchain/Dockerfile . ``` -Set Ollama Service Configuration - -Ollama Service Configuration file is `/etc/systemd/system/ollama.service`. -Edit the file to set OLLAMA_HOST environment (Replace **${host_ip}** with your host IPV4). -``` -Environment="OLLAMA_HOST=${host_ip}:11434" -``` -Set https_proxy environment for Ollama if your system access network through proxy. -``` -Environment="https_proxy=http://proxy.example.com:8080" -``` -Restart Ollama services -``` -sudo systemctl daemon-reload -sudo systemctl restart ollama.service -``` - -Pull LLM model - -```bash -export OLLAMA_HOST=http://${host_ip}:11434 -ollama pull llama3 -ollama list - -NAME ID SIZE MODIFIED -llama3:latest 365c0bd3c000 4.7 GB 5 days ago -``` ::: :::: - ### Build Mega Service images The Megaservice is a pipeline that channels data through different @@ -177,8 +243,7 @@ megaservice to suit the needs. Build the megaservice image for this use case ``` -cd .. -cd GenAIExamples/ChatQnA +cd ~/OPEA/GenAIExamples/ChatQnA git checkout tags/v1.0 ``` @@ -196,7 +261,7 @@ As mentioned, you can build 2 modes of UI *Basic UI* ``` -cd GenAIExamples/ChatQnA/ui/ +cd ~/OPEA/GenAIExamples/ChatQnA/ui/ docker build --no-cache -t opea/chatqna-ui:latest --build-arg https_proxy=$https_proxy \ --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile . ``` @@ -205,7 +270,7 @@ docker build --no-cache -t opea/chatqna-ui:latest --build-arg https_proxy=$https If you want a conversational experience with chatqna megaservice. ``` -cd GenAIExamples/ChatQnA/ui/ +cd ~/OPEA/GenAIExamples/ChatQnA/ui/ docker build --no-cache -t opea/chatqna-conversation-ui:latest --build-arg https_proxy=$https_proxy \ --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile.react . ``` @@ -376,13 +441,19 @@ This section will walk you through what are the different ways to interact with the microservices deployed ### Dataprep Microservice（Optional） - If you want to add/update the default knowledge base, you can use the following commands. The dataprep microservice extracts the texts from variety of data sources, chunks the data, embeds each chunk using embedding microservice and store the embedded vectors in the redis vector database. -Local File `nke-10k-2023.pdf` Upload: +Download pdf file: + +``` +wget https://raw.githubusercontent.com/opea-project/GenAIComps/main/comps/retrievers/redis/data/nke-10k-2023.pdf +``` + +Local File `nke-10k-2023.pdf` Upload with dataprep: +This command updates a knowledge base by uploading a local file for processing. ``` curl -X POST "http://${host_ip}:6007/v1/dataprep" \ @@ -390,10 +461,7 @@ curl -X POST "http://${host_ip}:6007/v1/dataprep" \ -F "files=@./nke-10k-2023.pdf" ``` -This command updates a knowledge base by uploading a local file for processing. -Update the file path according to your environment. - -Add Knowledge Base via HTTP Links: +Alternatively, you can add knowledge base via HTTP Links: ``` curl -X POST "http://${host_ip}:6007/v1/dataprep" \ From 71c2d4479371b2060d2ef38f7ef4703864d8a453 Mon Sep 17 00:00:00 2001 From: devpramod Date: Mon, 21 Oct 2024 19:58:49 -0400 Subject: [PATCH 03/34] Ibm getting started (#221) * getting started with ibm cloud Signed-off-by: devpramod * note on rag Signed-off-by: devpramod * remove hyperlink Signed-off-by: devpramod * add docker logs Signed-off-by: devpramod * format table Signed-off-by: devpramod --------- Signed-off-by: devpramod Signed-off-by: alexsin368 --- getting-started/README.md | 153 +++++++++++--------- getting-started/assets/chat_ui_response.png | Bin 0 -> 76033 bytes getting-started/assets/getting_started.gif | Bin 857560 -> 0 bytes 3 files changed, 84 insertions(+), 69 deletions(-) create mode 100644 getting-started/assets/chat_ui_response.png delete mode 100644 getting-started/assets/getting_started.gif diff --git a/getting-started/README.md b/getting-started/README.md index f3bab89f..6ef0b8af 100644 --- a/getting-started/README.md +++ b/getting-started/README.md @@ -1,110 +1,125 @@ # Getting Started with OPEA +This document specifically details the steps for deploying services on IBM Cloud, providing a tailored guide to help you leverage IBM's cloud infrastructure to deploy the ChatQnA application from OPEA GenAI Examples. For additional deployment targets, see the [ChatQnA Sample Guide](https://opea-project.github.io/latest/examples/ChatQnA/ChatQnA_Guide.html) + +## Understanding OPEA's Core Components + +Before moving forward, it's important to familiarize yourself with two key elements of OPEA: GenAIComps and GenAIExamples. + +- GenAIComps is a collection of microservice components that form a service-based toolkit. This includes a variety of services such as llm (large language models), embedding, and reranking, among others. +- While GenAIComps offers a range of microservices, GenAIExamples provides practical, deployable solutions to help users implement these services effectively. Examples include ChatQnA and DocSum, which leverage the microservices for specific applications. + ## Prerequisites -To get started with OPEA you need the right hardware and basic software setup. -- Hardware Requirements: For the hardware configuration, If you need Hardware Access visit the [Intel Tiber Developer Cloud](https://cloud.intel.com) to select from options such as Xeon or Gaudi processors that meet the necessary specifications. +## Create and Configure a Virtual Server +1. Navigate to [IBM Cloud](https://cloud.ibm.com). - Click the **Create resource** button at the top right of the screen. Select **Compute** from the options available and select `Virtual Server for VPC` -- Software Requirements: Refer to the [Support Matrix](https://github.com/opea-project/GenAIExamples/blob/main/README.md#getting-started) to ensure you have the required software components in place. +2. Select a location for the instance. Assign a name to it. -Note : If you are deploying it on cloud, say AWS, select a VM instance from R7iz or m7i family of instances with base OS as Ubuntu 22.04 (AWS ami id : ami-05134c8ef96964280). Use the command below to install docker on a clean machine. -``` -wget https://raw.githubusercontent.com/opea-project/GenAIExamples/refs/heads/main/ChatQnA/docker_compose/install_docker.sh -chmod +x install_docker.sh -./install_docker.sh -``` -## Understanding OPEA's Core Components +3. Under Stock Images, select Ubuntu 24.04 (`ibm-ubuntu-24-04-6-minimal-amd64-1`) -Before moving forward, it's important to familiarize yourself with two key elements of OPEA: GenAIComps and GenAIExamples. +4. Select a virtual server. +> **Note:** We recommend selecting a 3-series instance with an Intel(R) 4th Gen Xeon(C) Scalable Processor, such as `bx3d-16x80` or above. For more information on virtual servers on IBM cloud visit [Intel® solutions on IBM Cloud®](https://www.ibm.com/cloud/intel). -- GenAIComps is a collection of microservice components that form a service-based toolkit. This includes a variety of services such as llm (language learning models), embedding, and reranking, among others. -- While GenAIComps offers a range of microservices, GenAIExamples provides practical, deployable solutions to help users implement these services effectively. Examples include ChatQnA and DocSum, which leverage the microservices for specific applications. +5. Add an SSH key to the instance, if necessary, create one first. + +6. Click on `Create virtual server`. + +7. Once the instance is running, create and attach a `Floating IP` to the instance. For more information visit [this](https://cloud.ibm.com/docs/vpc?topic=vpc-fip-working&interface=ui) site -## Visual Guide to Deployment -To illustrate, here's a simplified visual guide on deploying a ChatQnA GenAIExample, showcasing how you can set up this solution in just a few steps. +8. `ssh` into the instance using the floating IP (`ssh -i ubuntu@`) -![Getting started with OPEA](assets/getting_started.gif) -## Setup ChatQnA Parameters -To deploy ChatQnA services, follow these steps: +## Deploy the ChatQnA Solution +Use the command below to install docker on a clean virtual machine +```bash +wget https://raw.githubusercontent.com/opea-project/GenAIExamples/refs/heads/main/ChatQnA/docker_compose/install_docker.sh +chmod +x install_docker.sh +./install_docker.sh ``` +Configure Docker to run as a non-root user by following these [instructions](https://docs.docker.com/engine/install/linux-postinstall/) + +Clone the repo and navigate to ChatQnA + +```bash git clone https://github.com/opea-project/GenAIExamples.git cd GenAIExamples/ChatQnA ``` -### Set the required environment variables: -``` -# Example: host_ip="192.168.1.1" -export host_ip="External_Public_IP" -# Example: no_proxy="localhost, 127.0.0.1, 192.168.1.1" -export no_proxy="Your_No_Proxy" +Set the required environment variables: +```bash +export host_ip="localhost" export HUGGINGFACEHUB_API_TOKEN="Your_Huggingface_API_Token" ``` -If you are in a proxy environment, also set the proxy-related environment variables: -``` -export http_proxy="Your_HTTP_Proxy" -export https_proxy="Your_HTTPs_Proxy" -``` - -Set up other specific use-case environment variables by choosing one of these options, according to your hardware: +Set up other specific use-case environment variables: +```bash +cd docker_compose/intel/cpu/xeon/ +source set_env.sh ``` -# on Xeon -source ./docker_compose/intel/cpu/xeon/set_env.sh -# on Gaudi -source ./docker_compose/intel/hpu/gaudi/set_env.sh -# on Nvidia GPU -source ./docker_compose/nvidia/gpu/set_env.sh +Now we can start the services +```bash +docker compose up -d ``` +It takes a few minutes for the services to start. Check the logs for the services to ensure that ChatQnA is running. +For example to check the logs for the `tgi-service`: -## Deploy ChatQnA Megaservice and Microservices -Select the directory containing the `compose.yaml` file that matches your hardware. +```bash +docker compose logs tgi-service | grep Connected ``` -#xeon -cd docker_compose/intel/cpu/xeon/ -#gaudi -cd docker_compose/intel/hpu/gaudi/ -#nvidia -cd docker_compose/nvidia/gpu/ +The output shows `Connected` as shown: ``` -Now we can start the services +tgi-service | 2024-10-18T22:41:18.973042Z INFO text_generation_router::server: router/src/server.rs:2311: Connected ``` -docker compose up -d + +Run `docker ps -a` as an additional check to verify that all the services are running as shown: + ``` -It will automatically download the needed docker images from docker hub: +| CONTAINER ID | IMAGE | COMMAND | CREATED | STATUS | PORTS | NAMES | +|--------------|------------------------------------------------------------------------|------------------------|--------------|-------------|------------------------------------------------------------------------------------------|------------------------------| +| 3a65ff9e16bd | opea/nginx:latest | `/docker-entrypoint.\…`| 14 hours ago | Up 14 hours | 0.0.0.0:80->80/tcp, :::80->80/tcp | chatqna-xeon-nginx-server | +| 7563b2ee1cd9 | opea/chatqna-ui:latest | `docker-entrypoint.s\…`| 14 hours ago | Up 14 hours | 0.0.0.0:5173->5173/tcp, :::5173->5173/tcp | chatqna-xeon-ui-server | +| 9ea57a660cd6 | opea/chatqna:latest | `python chatqna.py` | 14 hours ago | Up 14 hours | 0.0.0.0:8888->8888/tcp, :::8888->8888/tcp | chatqna-xeon-backend-server | +| 451bacaac3e6 | opea/retriever-redis:latest | `python retriever_re\…`| 14 hours ago | Up 14 hours | 0.0.0.0:7000->7000/tcp, :::7000->7000/tcp | retriever-redis-server | +| c1f952ef5c08 | opea/dataprep-redis:latest | `python prepare_doc_\…`| 14 hours ago | Up 14 hours | 0.0.0.0:6007->6007/tcp, :::6007->6007/tcp | dataprep-redis-server | +| 2a874ed8ce6f | redis/redis-stack:7.2.0-v9 | `/entrypoint.sh` | 14 hours ago | Up 14 hours | 0.0.0.0:6379->6379/tcp, :::6379->6379/tcp, 0.0.0.0:8001->8001/tcp, :::8001->8001/tcp | redis-vector-db | +| ac7b62306eb8 | ghcr.io/huggingface/text-embeddings-inference:cpu-1.5 | `text-embeddings-rou\…`| 14 hours ago | Up 14 hours | 0.0.0.0:8808->80/tcp, [::]:8808->80/tcp | tei-reranking-server | +| 521cc7faa00e | ghcr.io/huggingface/text-generation-inference:sha-e4201f4-intel-cpu | `text-generation-lau\…`| 14 hours ago | Up 14 hours | 0.0.0.0:9009->80/tcp, [::]:9009->80/tcp | tgi-service | +| 9faf553d3939 | ghcr.io/huggingface/text-embeddings-inference:cpu-1.5 | `text-embeddings-rou\…`| 14 hours ago | Up 14 hours | 0.0.0.0:6006->80/tcp, [::]:6006->80/tcp | tei-embedding-server | -- docker pull opea/chatqna:latest -- docker pull opea/chatqna-ui:latest +``` -In the following cases, you will need to build the docker image from source by yourself. +### Interact with ChatQnA -- The docker image failed to download. (You may want to first check the - [Docker Images](https://github.com/opea-project/GenAIExamples/blob/main/docker_images_list.md) - list and verify that the docker image you're downloading exists on dockerhub.) -- You want to use a different version than latest. +You can interact with ChatQnA via a browser interface: +* Under `Infrastructure` in the left pane, go to `Network/Security groups//Rules` +* Select `Create` +* Enable inbound traffic for port 80 +* To view the ChatQnA interface, open a browser and navigate to the UI by inserting your externally facing IP address in the following: `http://{external_public_ip}:80'. -Refer to the {ref}`ChatQnA Example Deployment Options ` section for building from source instructions matching your hardware. +For more information on editing inbound/outbound rules, click [here](https://cloud.ibm.com/docs/vpc?topic=vpc-updating-the-default-security-group&interface=ui) -## Interact with ChatQnA Megaservice and Microservice -Before interact ChatQnA Service, make sure the TGI service is ready (which takes up to 2 minutes to start). -``` -docker ps -# expected: all images's status are up -# TGI example on on Xeon and Nvidia GPU -docker logs tgi-service | grep Connected -# TGI example on on Gaudi -docker logs tgi-gaudi-service | grep Connected -# execpted output: ... INFO text_generation_router::server: router/src/server.rs:2311: Connected -``` -``` +A snapshot of the interface looks as follows: + +![Chat Interface](assets/chat_ui_response.png) + + +> **Note:** this example leverages the Nike 2023 Annual report for its RAG based content. See the [ChatQnA Sample Guide](https://opea-project.github.io/latest/examples/ChatQnA/ChatQnA_Guide.html) +to learn how you can customize the example with your own content. + +To interact with the ChatQnA application via a `curl` command: + +```bash curl http://${host_ip}:8888/v1/chatqna \ -H "Content-Type: application/json" \ -d '{ "messages": "What is the revenue of Nike in 2023?" }' ``` -This command will provide the response as a stream of text. You can modify the `message` parameter in the `curl` command and interact with the ChatQnA service. +ChatQnA provides the answer to your query as a text stream. + +Modify the `message` parameter in the `curl` command to continue interacting with ChatQnA. ## What’s Next diff --git a/getting-started/assets/chat_ui_response.png b/getting-started/assets/chat_ui_response.png new file mode 100644 index 0000000000000000000000000000000000000000..c65c5d1c21226d1f9c27a5c487f0d9268d651f04 GIT binary patch literal 76033 zcmeFYcTiJZ*e_}qK?PAjL_kDErHLpVqM#zu6qF88dPi!201*Xg0s_+83kZlb={-TE zx6n%P^+&SNO?jD%gv&+hQ)_U6S_dGl7xt8h~=1a_n z4jnq9_Vkg?p+hH_4jnq`&2$8~lFYvK`_Q3xhtwWDeCdr^MZ^3|UZw9a&L6Y;RXQ4W z$MJ{O)z}Nem9)|O*TYzbL{GhHmU1Z6oKY1`dG;>g>KTfmdU;A#VUoEL$I(dCtEYM6 zduq2i)sIg8Bc(FSKKUf@M)Qq|T*DJdPj}*9K3Jf%XN62c2~%}M!Q@IZ$!{y#dZDig zmj>;tv%$C{>$qc{J_05M9L+vj>X7{j0>@{*V;}#XT@G(%J2-o%a_-{ayKiqEQTcoG z?BmyfT)@$s#dP}c!I{j3K!JmkLm^l196LDs^ZdWqV9HaK zZAt4&(3LyK1cJQ%=l%#PDpJSK>drdwRx^o}@Gul~H; 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zQH9ZD_I5tkG=B6AA4BefLDL&`o$Qu?-JNHH_nDNNBzI0HvOSwCs)v|6T2DEj`9pf5 zBQ`(vO#X+u)Srhc;ddJK7Xys9AL$C(qG+cG(@*QLym~L?kCSd+2TQ$oJx`Ax%#U8J zAo5_+TXMb|KDzyYY<7Pu;qi}#KVR0j58d$74EgjU_NVc;W4a$L0>1cn9C-uby#qDb z$Q3G( zdR`9x1T$v;*1po Date: Thu, 24 Oct 2024 15:06:38 -0700 Subject: [PATCH 04/34] fix formating for pull/build docker images Signed-off-by: asin Signed-off-by: alexsin368 --- examples/ChatQnA/deploy/gaudi.md | 25 ++++++++++++++----------- 1 file changed, 14 insertions(+), 11 deletions(-) diff --git a/examples/ChatQnA/deploy/gaudi.md b/examples/ChatQnA/deploy/gaudi.md index aa59a165..09aa30a8 100644 --- a/examples/ChatQnA/deploy/gaudi.md +++ b/examples/ChatQnA/deploy/gaudi.md @@ -87,15 +87,18 @@ ChatQnA megaservice, and UI (conversational React UI is optional). In total, there are 8 required and an optional docker images. ### Build/Pull Microservice images -::::{tab-set} -:::{tab-item} Pull + +::::::{tab-set} + +:::::{tab-item} Pull :sync: Pull -To pull pre-built docker images on Docker Hub, proceed to the next step. To customize -your application, you can choose to build individual docker images for the microservices -before proceeding. -::: -:::{tab-item} Build +If you decide to pull the docker containers and not build them locally, +you can proceed to the next step where all the necessary containers will +be pulled in from dockerhub. + +::::: +:::::{tab-item} Build :sync: Build From within the `GenAIComps` folder, checkout the release tag. @@ -103,8 +106,6 @@ From within the `GenAIComps` folder, checkout the release tag. cd GenAIComps git checkout tags/v1.0 ``` -::: -:::: #### Build Dataprep Image @@ -130,7 +131,7 @@ docker build --no-cache -t opea/retriever-redis:latest --build-arg https_proxy=$ docker build --no-cache -t opea/reranking-tei:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/reranks/tei/Dockerfile . ``` -#### Build docker +#### Build LLM Image ::::{tab-set} @@ -240,7 +241,6 @@ Check if you have the below set of docker images, before moving on to the next s * opea/chatqna-ui:latest * opea/vllm:latest * opea/llm-vllm:latest - ::: :::{tab-item} TGI :sync: TGI @@ -256,6 +256,9 @@ Check if you have the below set of docker images, before moving on to the next s ::: :::: +::::: +:::::: + ## Use Case Setup As mentioned the use case will use the following combination of the GenAIComps From 882ebd95a190200ab61ad03ed49130cbf92522bb Mon Sep 17 00:00:00 2001 From: Ying Hu Date: Mon, 28 Oct 2024 09:12:44 +0800 Subject: [PATCH 05/34] Update README.md for fix link (#229) fix https://github.com/opea-project/GenAIExamples/issues/1024 Signed-off-by: alexsin368 --- getting-started/README.md | 20 ++++++++++---------- 1 file changed, 10 insertions(+), 10 deletions(-) diff --git a/getting-started/README.md b/getting-started/README.md index 6ef0b8af..737373c1 100644 --- a/getting-started/README.md +++ b/getting-started/README.md @@ -130,21 +130,21 @@ Modify the `message` parameter in the `curl` command to continue interacting wit Have you ideas and skills to build out genAI components, microservices, and solutions? Would you like to be a part of this evolving technology in its early stages? Welcome! * Register for our mailing list: - * General: https://lists.lfaidata.foundation/g/OPEA-announce - * Technical Discussions: https://lists.lfaidata.foundation/g/OPEA-technical-discuss + * [Mailing List](https://lists.lfaidata.foundation/g/OPEA-announce) + * [Technical Discussions](https://lists.lfaidata.foundation/g/OPEA-technical-discuss) * Subscribe to the working group mailing lists that interest you - * End user https://lists.lfaidata.foundation/g/OPEA-End-User - * Evaluation https://lists.lfaidata.foundation/g/OPEA-Evaluation - * Community https://lists.lfaidata.foundation/g/OPEA-Community - * Research https://lists.lfaidata.foundation/g/OPEA-Research - * Security https://lists.lfaidata.foundation/g/OPEA-Security -* Go to the Community Section of the OPEA repo for Contribution Guidelines and step by step instructions. + * [End user](https://lists.lfaidata.foundation/g/OPEA-End-User) + * [Evaluation](https://lists.lfaidata.foundation/g/OPEA-Evaluation) + * [Community](https://lists.lfaidata.foundation/g/OPEA-Community) + * [Research](https://lists.lfaidata.foundation/g/OPEA-Research) + * [Security](https://lists.lfaidata.foundation/g/OPEA-Security) +* Go to the Community Section of the OPEA repo for [Contribution Guidelines](https://opea-project.github.io/latest/community/CONTRIBUTING.html) and step by step instructions. * Attend any of our community events and hackathons. https://wiki.lfaidata.foundation/display/DL/OPEA+Community+Events Current GenAI Examples - Simple chatbot that uses retrieval augmented generation (RAG) architecture. [ChatQnA](/examples/ChatQnA/ChatQnA_Guide.rst) -- Code generation, from enabling non-programmers to generate code to improving productivity with code completion of complex applications. [CodeGen] -- Make your applications more flexible by porting to different languages. [CodeTrans](https://opea-project.github.io/latest/GenAIExamples/CodeGen/README.html) +- Code generation, from enabling non-programmers to generate code to improving productivity with code completion of complex applications. [CodeGen](https://opea-project.github.io/latest/GenAIExamples/CodeGen/README.html) +- Make your applications more flexible by porting to different languages. [CodeTrans](https://opea-project.github.io/latest/GenAIExamples/CodeTrans/README.html) - Create summaries of news articles, research papers, technical documents, etc. to streamline content systems. [DocSum](https://opea-project.github.io/latest/GenAIExamples/DocSum/README.html) - Mimic human behavior by iteratively searching, selecting, and synthesizing information across large bodies of content. [SearchQnA](https://opea-project.github.io/latest/GenAIExamples/SearchQnA/README.html) - Provide critical content to your customers by automatically generating Frequently Asked Questions (FAQ) resources. [FaqGen](https://opea-project.github.io/latest/GenAIExamples/FaqGen/README.html) From c189a7b08a948c4bad47e92fff48b4a81fdb877b Mon Sep 17 00:00:00 2001 From: devpramod Date: Mon, 28 Oct 2024 10:22:29 -0400 Subject: [PATCH 06/34] combine ibm, aws into tabs, add tabset for getting started (#230) * combine ibm, aws, add tabset Signed-off-by: devpramod * Update getting-started/README.md Co-authored-by: Malini Bhandaru * Update getting-started/README.md Co-authored-by: Malini Bhandaru * Update getting-started/README.md Co-authored-by: Louie Tsai * Update getting-started/README.md Co-authored-by: Louie Tsai * gcp instructions and updates Signed-off-by: aice-support --------- Signed-off-by: devpramod Signed-off-by: aice-support Co-authored-by: Ying Hu Co-authored-by: Malini Bhandaru Co-authored-by: Louie Tsai Co-authored-by: aice-support Signed-off-by: alexsin368 --- getting-started/README.md | 113 ++++++++++++++++++++++++++++++++++++-- 1 file changed, 109 insertions(+), 4 deletions(-) diff --git a/getting-started/README.md b/getting-started/README.md index 737373c1..98a8ec18 100644 --- a/getting-started/README.md +++ b/getting-started/README.md @@ -1,5 +1,7 @@ # Getting Started with OPEA -This document specifically details the steps for deploying services on IBM Cloud, providing a tailored guide to help you leverage IBM's cloud infrastructure to deploy the ChatQnA application from OPEA GenAI Examples. For additional deployment targets, see the [ChatQnA Sample Guide](https://opea-project.github.io/latest/examples/ChatQnA/ChatQnA_Guide.html) +In this document, we provide a tailored guide to deploying the ChatQnA application in OPEA GenAI Examples across multiple cloud platforms, including IBM Cloud, Amazon Web Services (AWS), and others, + +enabling you to choose the best fit for your specific needs and requirements. For additional deployment targets, see the [ChatQnA Sample Guide](https://opea-project.github.io/latest/examples/ChatQnA/ChatQnA_Guide.html) ## Understanding OPEA's Core Components @@ -11,8 +13,42 @@ Before moving forward, it's important to familiarize yourself with two key eleme ## Prerequisites - ## Create and Configure a Virtual Server + +::::{tab-set} + +:sync-group: Cloud Service Providers + + + +:::{tab-item} AWS + +:sync: AWS + +1. Navigate to [AWS console](https://console.aws.amazon.com/console/home) – Search EC2 in the search bar and select it. Click the `Launch Instance` button highlighted in orange. + +2. Provide a name to the VM. + +3. In Quick Start, select the base OS as Ubuntu (ami-id : ami-04dd23e62ed049936). + +4. Select an Instance type that is based on Intel hardware. + +>**Note**: We recommend selecting a m7i.4xlarge or larger instance with an Intel(R) 4th Gen Xeon(C) Scalable Processor. For more information on virtual servers on AWS visit [here](https://aws.amazon.com/intel/). + +5. Next, create a new key pair, give it a name or select one from the existing key pairs. + +6. Under Network settings select an existing security group. If there is none, create a new one by selecting the Create security group radio button and select the Allow SSH traffic and Allow HTTP traffic check box. + +7. Configure the storage to 100 GiB and click `Launch Instance`. + +8. Click on the connect button on the top right and connect using your preferred method. + +::: + +:::{tab-item} IBM Cloud + +:sync: IBM Cloud + 1. Navigate to [IBM Cloud](https://cloud.ibm.com). - Click the **Create resource** button at the top right of the screen. Select **Compute** from the options available and select `Virtual Server for VPC` 2. Select a location for the instance. Assign a name to it. @@ -20,6 +56,7 @@ Before moving forward, it's important to familiarize yourself with two key eleme 3. Under Stock Images, select Ubuntu 24.04 (`ibm-ubuntu-24-04-6-minimal-amd64-1`) 4. Select a virtual server. + > **Note:** We recommend selecting a 3-series instance with an Intel(R) 4th Gen Xeon(C) Scalable Processor, such as `bx3d-16x80` or above. For more information on virtual servers on IBM cloud visit [Intel® solutions on IBM Cloud®](https://www.ibm.com/cloud/intel). 5. Add an SSH key to the instance, if necessary, create one first. @@ -31,6 +68,32 @@ Before moving forward, it's important to familiarize yourself with two key eleme 8. `ssh` into the instance using the floating IP (`ssh -i ubuntu@`) +::: + +:::{tab-item} GCP + +:sync: GCP + +1. Navigate to [GCP console](https://console.cloud.google.com/) – Click the `Create a VM` button. + +2. Provide a name to the VM. + +3. Select the base OS as Ubuntu 24.04 LTS from Marketplace . + +4. Select an Instance type that is based on Intel hardware. + +> **Note:**  We recommend selecting a c3-standard-22 or larger instance with an Intel(R) 4th Gen Xeon(C) Scalable Processor, and the minimum supported c3 instance type is c3-standard-8 with 32GB memory. For more information on virtual servers on GCP visit [here](https://cloud.google.com/intel). + +5. Under Firewall settings select “Allow HTTP traffic” to access ChatQnA UI web portal. + +6. Change the Boot disk to 100 GiB and click Create. + +7. Use any preferred SSH method such as ”Open in browser window” to connect to the instance + +::: + +:::: + ## Deploy the ChatQnA Solution Use the command below to install docker on a clean virtual machine @@ -62,11 +125,12 @@ Now we can start the services ```bash docker compose up -d ``` -It takes a few minutes for the services to start. Check the logs for the services to ensure that ChatQnA is running. +>**Note**: It takes a few minutes for the services to start. Check the logs for the services to ensure that ChatQnA is running before proceeding further. + For example to check the logs for the `tgi-service`: ```bash -docker compose logs tgi-service | grep Connected +docker logs tgi-service | grep Connected ``` The output shows `Connected` as shown: ``` @@ -92,6 +156,33 @@ Run `docker ps -a` as an additional check to verify that all the services are ru ### Interact with ChatQnA + +::::{tab-set} + +:sync-group: Cloud Service Providers + +:::{tab-item} AWS + +:sync: AWS + +You can interact with ChatQnA via a browser interface: + +* To view the ChatQnA interface, open a browser and navigate to the UI by inserting your public facing IP address in the following: `http://{public_ip}:80’. + +>**Note**: If you are having issue accessing the UI, you need to add an inbound rule in the security group. + +* Look up Security Groups in the search bar and select the security group used when creating the instance. +* Click on the Edit inbound rules on the right side of the window. +* Select Add rule at the bottom, and create a rule with type as Custom TCP , port range as 80 and source as 0.0.0.0/0 + +For more information on editing inbound/outbound rules, click [here](https://docs.aws.amazon.com/finspace/latest/userguide/step5-config-inbound-rule.html) + +::: + +:::{tab-item} IBM Cloud + +:sync: IBM Cloud + You can interact with ChatQnA via a browser interface: * Under `Infrastructure` in the left pane, go to `Network/Security groups//Rules` * Select `Create` @@ -100,6 +191,20 @@ You can interact with ChatQnA via a browser interface: For more information on editing inbound/outbound rules, click [here](https://cloud.ibm.com/docs/vpc?topic=vpc-updating-the-default-security-group&interface=ui) +::: + +:::{tab-item} GCP + +:sync: GCP + +You can interact with ChatQnA via a browser interface: + +* To view the ChatQnA interface, open a browser and navigate to the UI by inserting your public facing IP address in the following: `http://{external_ip}:80’. + +::: +:::: + + A snapshot of the interface looks as follows: ![Chat Interface](assets/chat_ui_response.png) From 17300c280e25dc049c80d1efd1c90015ebc33a4a Mon Sep 17 00:00:00 2001 From: Ying Hu Date: Mon, 28 Oct 2024 23:57:26 +0800 Subject: [PATCH 07/34] Revert "combine ibm, aws into tabs, add tabset for getting started (#230)" (#231) This reverts commit d4075b2b25a35f63cef7ee679997c85200f356d3. Signed-off-by: alexsin368 --- getting-started/README.md | 113 ++------------------------------------ 1 file changed, 4 insertions(+), 109 deletions(-) diff --git a/getting-started/README.md b/getting-started/README.md index 98a8ec18..737373c1 100644 --- a/getting-started/README.md +++ b/getting-started/README.md @@ -1,7 +1,5 @@ # Getting Started with OPEA -In this document, we provide a tailored guide to deploying the ChatQnA application in OPEA GenAI Examples across multiple cloud platforms, including IBM Cloud, Amazon Web Services (AWS), and others, - -enabling you to choose the best fit for your specific needs and requirements. For additional deployment targets, see the [ChatQnA Sample Guide](https://opea-project.github.io/latest/examples/ChatQnA/ChatQnA_Guide.html) +This document specifically details the steps for deploying services on IBM Cloud, providing a tailored guide to help you leverage IBM's cloud infrastructure to deploy the ChatQnA application from OPEA GenAI Examples. For additional deployment targets, see the [ChatQnA Sample Guide](https://opea-project.github.io/latest/examples/ChatQnA/ChatQnA_Guide.html) ## Understanding OPEA's Core Components @@ -13,42 +11,8 @@ Before moving forward, it's important to familiarize yourself with two key eleme ## Prerequisites -## Create and Configure a Virtual Server - -::::{tab-set} - -:sync-group: Cloud Service Providers - - - -:::{tab-item} AWS - -:sync: AWS - -1. Navigate to [AWS console](https://console.aws.amazon.com/console/home) – Search EC2 in the search bar and select it. Click the `Launch Instance` button highlighted in orange. - -2. Provide a name to the VM. - -3. In Quick Start, select the base OS as Ubuntu (ami-id : ami-04dd23e62ed049936). - -4. Select an Instance type that is based on Intel hardware. - ->**Note**: We recommend selecting a m7i.4xlarge or larger instance with an Intel(R) 4th Gen Xeon(C) Scalable Processor. For more information on virtual servers on AWS visit [here](https://aws.amazon.com/intel/). - -5. Next, create a new key pair, give it a name or select one from the existing key pairs. - -6. Under Network settings select an existing security group. If there is none, create a new one by selecting the Create security group radio button and select the Allow SSH traffic and Allow HTTP traffic check box. - -7. Configure the storage to 100 GiB and click `Launch Instance`. - -8. Click on the connect button on the top right and connect using your preferred method. - -::: - -:::{tab-item} IBM Cloud - -:sync: IBM Cloud +## Create and Configure a Virtual Server 1. Navigate to [IBM Cloud](https://cloud.ibm.com). - Click the **Create resource** button at the top right of the screen. Select **Compute** from the options available and select `Virtual Server for VPC` 2. Select a location for the instance. Assign a name to it. @@ -56,7 +20,6 @@ Before moving forward, it's important to familiarize yourself with two key eleme 3. Under Stock Images, select Ubuntu 24.04 (`ibm-ubuntu-24-04-6-minimal-amd64-1`) 4. Select a virtual server. - > **Note:** We recommend selecting a 3-series instance with an Intel(R) 4th Gen Xeon(C) Scalable Processor, such as `bx3d-16x80` or above. For more information on virtual servers on IBM cloud visit [Intel® solutions on IBM Cloud®](https://www.ibm.com/cloud/intel). 5. Add an SSH key to the instance, if necessary, create one first. @@ -68,32 +31,6 @@ Before moving forward, it's important to familiarize yourself with two key eleme 8. `ssh` into the instance using the floating IP (`ssh -i ubuntu@`) -::: - -:::{tab-item} GCP - -:sync: GCP - -1. Navigate to [GCP console](https://console.cloud.google.com/) – Click the `Create a VM` button. - -2. Provide a name to the VM. - -3. Select the base OS as Ubuntu 24.04 LTS from Marketplace . - -4. Select an Instance type that is based on Intel hardware. - -> **Note:**  We recommend selecting a c3-standard-22 or larger instance with an Intel(R) 4th Gen Xeon(C) Scalable Processor, and the minimum supported c3 instance type is c3-standard-8 with 32GB memory. For more information on virtual servers on GCP visit [here](https://cloud.google.com/intel). - -5. Under Firewall settings select “Allow HTTP traffic” to access ChatQnA UI web portal. - -6. Change the Boot disk to 100 GiB and click Create. - -7. Use any preferred SSH method such as ”Open in browser window” to connect to the instance - -::: - -:::: - ## Deploy the ChatQnA Solution Use the command below to install docker on a clean virtual machine @@ -125,12 +62,11 @@ Now we can start the services ```bash docker compose up -d ``` ->**Note**: It takes a few minutes for the services to start. Check the logs for the services to ensure that ChatQnA is running before proceeding further. - +It takes a few minutes for the services to start. Check the logs for the services to ensure that ChatQnA is running. For example to check the logs for the `tgi-service`: ```bash -docker logs tgi-service | grep Connected +docker compose logs tgi-service | grep Connected ``` The output shows `Connected` as shown: ``` @@ -156,33 +92,6 @@ Run `docker ps -a` as an additional check to verify that all the services are ru ### Interact with ChatQnA - -::::{tab-set} - -:sync-group: Cloud Service Providers - -:::{tab-item} AWS - -:sync: AWS - -You can interact with ChatQnA via a browser interface: - -* To view the ChatQnA interface, open a browser and navigate to the UI by inserting your public facing IP address in the following: `http://{public_ip}:80’. - ->**Note**: If you are having issue accessing the UI, you need to add an inbound rule in the security group. - -* Look up Security Groups in the search bar and select the security group used when creating the instance. -* Click on the Edit inbound rules on the right side of the window. -* Select Add rule at the bottom, and create a rule with type as Custom TCP , port range as 80 and source as 0.0.0.0/0 - -For more information on editing inbound/outbound rules, click [here](https://docs.aws.amazon.com/finspace/latest/userguide/step5-config-inbound-rule.html) - -::: - -:::{tab-item} IBM Cloud - -:sync: IBM Cloud - You can interact with ChatQnA via a browser interface: * Under `Infrastructure` in the left pane, go to `Network/Security groups//Rules` * Select `Create` @@ -191,20 +100,6 @@ You can interact with ChatQnA via a browser interface: For more information on editing inbound/outbound rules, click [here](https://cloud.ibm.com/docs/vpc?topic=vpc-updating-the-default-security-group&interface=ui) -::: - -:::{tab-item} GCP - -:sync: GCP - -You can interact with ChatQnA via a browser interface: - -* To view the ChatQnA interface, open a browser and navigate to the UI by inserting your public facing IP address in the following: `http://{external_ip}:80’. - -::: -:::: - - A snapshot of the interface looks as follows: ![Chat Interface](assets/chat_ui_response.png) From e362e7e61c4d2645145806003005daf92d38dbe8 Mon Sep 17 00:00:00 2001 From: devpramod Date: Tue, 29 Oct 2024 01:31:25 -0400 Subject: [PATCH 08/34] add tabset for aws, gcp and ibm cloud (#232) * update readme Signed-off-by: devpramod Update getting-started/README.md Co-authored-by: Malini Bhandaru Update getting-started/README.md Co-authored-by: Malini Bhandaru Update getting-started/README.md Co-authored-by: Louie Tsai Update getting-started/README.md Co-authored-by: Louie Tsai * gcp instructions and updates Signed-off-by: aice-support * fix tabset issue Signed-off-by: devpramod * tabset fix Signed-off-by: aice-support * removing tabset Signed-off-by: aice-support * Update getting-started/README.md Co-authored-by: Neo Zhang Jianyu * Update getting-started/README.md Co-authored-by: Neo Zhang Jianyu * Update getting-started/README.md --------- Signed-off-by: aice-support Signed-off-by: devpramod Co-authored-by: Louie Tsai Co-authored-by: aice-support Co-authored-by: Ying Hu Co-authored-by: Neo Zhang Jianyu Signed-off-by: alexsin368 --- getting-started/README.md | 93 +++++++++++++++++++++++++++++++++++++-- 1 file changed, 89 insertions(+), 4 deletions(-) diff --git a/getting-started/README.md b/getting-started/README.md index 737373c1..1ab8ced8 100644 --- a/getting-started/README.md +++ b/getting-started/README.md @@ -1,5 +1,6 @@ # Getting Started with OPEA -This document specifically details the steps for deploying services on IBM Cloud, providing a tailored guide to help you leverage IBM's cloud infrastructure to deploy the ChatQnA application from OPEA GenAI Examples. For additional deployment targets, see the [ChatQnA Sample Guide](https://opea-project.github.io/latest/examples/ChatQnA/ChatQnA_Guide.html) +In this document, we provide a tailored guide to deploying the ChatQnA application in OPEA GenAI Examples across multiple cloud platforms, including IBM Cloud, Amazon Web Services (AWS), and others, enabling you to choose the best fit for your specific needs and requirements. For additional deployment targets, see the [ChatQnA Sample Guide](https://opea-project.github.io/latest/examples/ChatQnA/ChatQnA_Guide.html). + ## Understanding OPEA's Core Components @@ -11,8 +12,34 @@ Before moving forward, it's important to familiarize yourself with two key eleme ## Prerequisites - ## Create and Configure a Virtual Server + +::::{tab-set} +:::{tab-item} AWS +:sync: AWS + +1. Navigate to [AWS console](https://console.aws.amazon.com/console/home) – Search EC2 in the search bar and select it. Click the `Launch Instance` button highlighted in orange. + +2. Provide a name to the VM. + +3. In Quick Start, select the base OS as Ubuntu (ami-id : ami-04dd23e62ed049936). + +4. Select an Instance type that is based on Intel hardware. + +>**Note**: We recommend selecting a m7i.4xlarge or larger instance with an Intel(R) 4th Gen Xeon(C) Scalable Processor. For more information on virtual servers on AWS visit [here](https://aws.amazon.com/intel/). + +5. Next, create a new key pair, give it a name or select one from the existing key pairs. + +6. Under Network settings select an existing security group. If there is none, create a new one by selecting the Create security group radio button and select the Allow SSH traffic and Allow HTTP traffic check box. + +7. Configure the storage to 100 GiB and click `Launch Instance`. + +8. Click on the connect button on the top right and connect using your preferred method. + +::: +:::{tab-item} IBM Cloud +:sync: IBM Cloud + 1. Navigate to [IBM Cloud](https://cloud.ibm.com). - Click the **Create resource** button at the top right of the screen. Select **Compute** from the options available and select `Virtual Server for VPC` 2. Select a location for the instance. Assign a name to it. @@ -20,6 +47,7 @@ Before moving forward, it's important to familiarize yourself with two key eleme 3. Under Stock Images, select Ubuntu 24.04 (`ibm-ubuntu-24-04-6-minimal-amd64-1`) 4. Select a virtual server. + > **Note:** We recommend selecting a 3-series instance with an Intel(R) 4th Gen Xeon(C) Scalable Processor, such as `bx3d-16x80` or above. For more information on virtual servers on IBM cloud visit [Intel® solutions on IBM Cloud®](https://www.ibm.com/cloud/intel). 5. Add an SSH key to the instance, if necessary, create one first. @@ -31,6 +59,29 @@ Before moving forward, it's important to familiarize yourself with two key eleme 8. `ssh` into the instance using the floating IP (`ssh -i ubuntu@`) +::: +:::{tab-item} GCP +:sync: GCP + +1. Navigate to [GCP console](https://console.cloud.google.com/) – Click the `Create a VM` button. + +2. Provide a name to the VM. + +3. Select the base OS as Ubuntu 24.04 LTS from Marketplace . + +4. Select an Instance type that is based on Intel hardware. + +> **Note:**  We recommend selecting a c3-standard-22 or larger instance with an Intel(R) 4th Gen Xeon(C) Scalable Processor, and the minimum supported c3 instance type is c3-standard-8 with 32GB memory. For more information on virtual servers on GCP visit [here](https://cloud.google.com/intel). + +5. Under Firewall settings select “Allow HTTP traffic” to access ChatQnA UI web portal. + +6. Change the Boot disk to 100 GiB and click Create. + +7. Use any preferred SSH method such as ”Open in browser window” to connect to the instance + +::: +:::: + ## Deploy the ChatQnA Solution Use the command below to install docker on a clean virtual machine @@ -62,11 +113,12 @@ Now we can start the services ```bash docker compose up -d ``` -It takes a few minutes for the services to start. Check the logs for the services to ensure that ChatQnA is running. +>**Note**: It takes a few minutes for the services to start. Check the logs for the services to ensure that ChatQnA is running before proceeding further. + For example to check the logs for the `tgi-service`: ```bash -docker compose logs tgi-service | grep Connected +docker logs tgi-service | grep Connected ``` The output shows `Connected` as shown: ``` @@ -92,6 +144,27 @@ Run `docker ps -a` as an additional check to verify that all the services are ru ### Interact with ChatQnA + +::::{tab-set} +:::{tab-item} AWS +:sync: AWS + +You can interact with ChatQnA via a browser interface: + +* To view the ChatQnA interface, open a browser and navigate to the UI by inserting your public facing IP address in the following: `http://{public_ip}:80’. + +>**Note**: If you are having issue accessing the UI, you need to add an inbound rule in the security group. + +* Look up Security Groups in the search bar and select the security group used when creating the instance. +* Click on the Edit inbound rules on the right side of the window. +* Select Add rule at the bottom, and create a rule with type as Custom TCP , port range as 80 and source as 0.0.0.0/0 + +For more information on editing inbound/outbound rules, click [here](https://docs.aws.amazon.com/finspace/latest/userguide/step5-config-inbound-rule.html) + +::: +:::{tab-item} IBM Cloud +:sync: IBM Cloud + You can interact with ChatQnA via a browser interface: * Under `Infrastructure` in the left pane, go to `Network/Security groups//Rules` * Select `Create` @@ -100,6 +173,18 @@ You can interact with ChatQnA via a browser interface: For more information on editing inbound/outbound rules, click [here](https://cloud.ibm.com/docs/vpc?topic=vpc-updating-the-default-security-group&interface=ui) +::: +:::{tab-item} GCP +:sync: GCP + +You can interact with ChatQnA via a browser interface: + +* To view the ChatQnA interface, open a browser and navigate to the UI by inserting your public facing IP address in the following: `http://{external_ip}:80’. + +::: +:::: + + A snapshot of the interface looks as follows: ![Chat Interface](assets/chat_ui_response.png) From ba012c6fbe9409abcc8419568d70abca50112b5a Mon Sep 17 00:00:00 2001 From: Chun Tao Date: Tue, 29 Oct 2024 07:06:23 -0700 Subject: [PATCH 09/34] Update up-to-date public information for the avatar chatbot example (#228) * Fix invalid link fixed link for LivePortrait Signed-off-by: Chun Tao * remove sharepoint locations Signed-off-by: Chun Tao * update avatar project doc Signed-off-by: Chun Tao * update Signed-off-by: Chun Tao * add YT video link Signed-off-by: Chun Tao * update Signed-off-by: Chun Tao * add idz article link Signed-off-by: Chun Tao --------- Signed-off-by: Chun Tao Signed-off-by: alexsin368 --- .../rfcs/24-08-02-OPEA-AIAvatarChatbot.md | 36 +++++++++++------- community/rfcs/assets/avatar_design.png | Bin 0 -> 318854 bytes community/rfcs/assets/design.png | Bin 173014 -> 0 bytes 3 files changed, 22 insertions(+), 14 deletions(-) create mode 100644 community/rfcs/assets/avatar_design.png delete mode 100644 community/rfcs/assets/design.png diff --git a/community/rfcs/24-08-02-OPEA-AIAvatarChatbot.md b/community/rfcs/24-08-02-OPEA-AIAvatarChatbot.md index 09dd97f7..fbfd8c5f 100644 --- a/community/rfcs/24-08-02-OPEA-AIAvatarChatbot.md +++ b/community/rfcs/24-08-02-OPEA-AIAvatarChatbot.md @@ -1,7 +1,14 @@ # 24-08-02-OPEA-AIAvatarChatbot -A RAG-Powered Human-Like AI Avatar Audio Chatbot integrated with OPEA AudioQnA - +A Human-Like AI Avatar Audio Chatbot integrated with OPEA AudioQnA + +Code contributions: +"animation" component: https://github.com/opea-project/GenAIComps/tree/main/comps/animation/wav2lip +"AvatarChatbot" examples: https://github.com/opea-project/GenAIExamples/tree/main/AvatarChatbot + +Intel Developer Zone Article "Create an AI Avatar Talking Bot with PyTorch* and Open Platform for Enterprise AI (OPEA)": https://www.intel.com/content/www/us/en/developer/articles/technical/ai-avatar-talking-bot-with-pytorch-and-opea.html + +YouTube tech-talk video: https://youtu.be/OjaElyUB8Z0?si=6-IdxwTg0YFMraFl ## Author @@ -9,9 +16,9 @@ A RAG-Powered Human-Like AI Avatar Audio Chatbot integrated with OPEA AudioQnA ## Status -v0.1 - ASMO Team sharing on Fri 6/28/2024 -[GenAIComps pr #400](https://github.com/opea-project/GenAIComps/pull/400) (Under Review) -[GenAIExamples pr #523](https://github.com/opea-project/GenAIExamples/pull/523) (Under Review) +v0.1 - ASMO Team sharing on Thursday 10/24/2024 +* [GenAIComps pr #775](https://github.com/opea-project/GenAIComps/pull/775) | Merged +* [GenAIExamples pr #923](https://github.com/opea-project/GenAIExamples/pull/923) | Merged ## Objective @@ -39,10 +46,10 @@ The chatbot will: * Use multimodal retrieval-augmented generation (RAG) to generate more accurate, in-domain responses, in v0.2 New microservices include: -* animation +* [animation](https://github.com/opea-project/GenAIComps/tree/main/comps/animation/wav2lip) New megaservices include: -* AvatarChatbot +* [AvatarChatbot](https://github.com/opea-project/GenAIExamples/tree/main/AvatarChatbot) ## Motivation @@ -60,9 +67,9 @@ Related works include [Nvidia Audio2Face](https://docs.nvidia.com/ace/latest/mod ### Avatar Chatbot design -![avatar chatbot design](assets/design.png) +![avatar chatbot design](assets/avatar_design.png) -Currently, the RAG feature using the `embedding` and `dataprep` microservices is missing in the above design, including uploading relevant documents/weblinks, storing them in the database, and retrieving them for the LLM model. These features will be added in v0.2. +Currently, the RAG feature using the `embedding`, `retrieval`, `reranking` and `dataprep` microservices and VectorDB is missing in the above design, including uploading relevant documents/weblinks, storing them in the database, and retrieving them for the LLM model. These features will be added in v0.2. Flowchart: AvatarChatbot Megaservice @@ -217,13 +224,14 @@ End-to-End Inference Time for AvatarChatbot Megaservice (asr -> llm -> tts -> an On SPR: ~30 seconds for AudioQnA on SPR, -~40-200 seconds for AvatarAnimation on SPR +~30-200 seconds for AvatarAnimation on SPR On Gaudi 2: ~5 seconds for AudioQnA on Gaudi, -~10-50 seconds for AvatarAnimation on Gaudi, depending on: +~10-40 seconds for AvatarAnimation on Gaudi, depending on: 1) Whether the input is an image or a multi-frame, fixed-fps video -1) LipSync Animation DL model used: Wav2Lip_only or Wav2Lip+GFPGAN or SadTalker -2) Resolution and FPS rate of the resulting mp4 video +2) The `max_tokens` parameter used in LLM text generation +3) LipSync Animation DL model used: Wav2Lip_only or Wav2Lip+GFPGAN or SadTalker +4) Resolution and FPS rate of the resulting mp4 video -All latency reportings are as of 8/2/2024. +All latency reportings are as of 10/24/2024. diff --git a/community/rfcs/assets/avatar_design.png 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z3yXSnXVMC;Ck+cky~tzF+n@3T9V`XiNd9{>nj4%O98<+(vc0nAzIzMLOV{|WadM!2L0zdgU+pfw5=MSS$he@7_h(uWE8iJJwkBq z$+KXk)iaO3t#j?Ffg6rPM)?=M*P9|k{}ZSG|6%*<+tumn+q>msrYMc4q-J;UPfJ}_ KtxDxp`2PW@Ci~_9 From 935af7c864b4664b71f13735243819256c5f2604 Mon Sep 17 00:00:00 2001 From: Neo Zhang Jianyu Date: Fri, 1 Nov 2024 11:26:50 +0800 Subject: [PATCH 10/34] check error of make html (#236) Signed-off-by: alexsin368 --- scripts/build.sh | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/scripts/build.sh b/scripts/build.sh index 245ce56d..89679883 100755 --- a/scripts/build.sh +++ b/scripts/build.sh @@ -41,6 +41,14 @@ cd docs make clean make html +retval=$? +if [ $retval -ne 0 ]; then + echo "make html is error" + exit 1 +else + echo "Done" +fi + if [ ! -d _build/html ]; then echo "Build online doc is wrong!" exit 1 From 77cb1895039103507c79c40ddfcb0d0e9e98ebc0 Mon Sep 17 00:00:00 2001 From: Kevin Putnam Date: Fri, 1 Nov 2024 16:18:00 -0700 Subject: [PATCH 11/34] Clean up GenAI Examples page (#238) 1. Increase nav depth to 4 to see examples in site nav 2. Move examples section of examples/index.rst to examples.rst 3. Add examples/examples.rst to examples/index.rst toctree Signed-off-by: Putnam, Kevin Signed-off-by: alexsin368 --- conf.py | 2 +- examples/examples.rst | 15 +++++++++++++++ examples/index.rst | 15 +-------------- 3 files changed, 17 insertions(+), 15 deletions(-) create mode 100644 examples/examples.rst diff --git a/conf.py b/conf.py index d80915e2..43164625 100644 --- a/conf.py +++ b/conf.py @@ -84,7 +84,7 @@ # Toc options 'collapse_navigation': False, 'sticky_navigation': True, - 'navigation_depth': 3, + 'navigation_depth': 4, } diff --git a/examples/examples.rst b/examples/examples.rst new file mode 100644 index 00000000..a86a36e1 --- /dev/null +++ b/examples/examples.rst @@ -0,0 +1,15 @@ +Examples +########## + +.. rst-class:: rst-columns + +.. contents:: + :local: + :depth: 1 + +---- + +.. comment This include file is generated in the Makefile during doc build + time from all the directories found in the GenAIExamples top level directory + +.. include:: examples.txt \ No newline at end of file diff --git a/examples/index.rst b/examples/index.rst index 18ce1704..09509a1e 100644 --- a/examples/index.rst +++ b/examples/index.rst @@ -23,19 +23,6 @@ We're building this documentation from content in the :glob: /GenAIExamples/README + examples.rst /GenAIExamples/* -**Example Applications Table of Contents** - -.. rst-class:: rst-columns - -.. contents:: - :local: - :depth: 1 - ----- - -.. comment This include file is generated in the Makefile during doc build - time from all the directories found in the GenAIExamples top level directory - -.. include:: examples.txt From 188955e9d4e160991354a37022846cc1dbc52285 Mon Sep 17 00:00:00 2001 From: ZePan110 Date: Mon, 4 Nov 2024 15:57:21 +0800 Subject: [PATCH 12/34] Exclude portal.azure.com (#239) Signed-off-by: ZePan110 Signed-off-by: alexsin368 --- .github/workflows/pr-path-detection.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/pr-path-detection.yml b/.github/workflows/pr-path-detection.yml index f2430bce..aceb81d6 100644 --- a/.github/workflows/pr-path-detection.yml +++ b/.github/workflows/pr-path-detection.yml @@ -104,7 +104,7 @@ jobs: link_head="https://github.com/opea-project/docs/blob/main" merged_commit=$(git log -1 --format='%H') changed_files="$(git diff --name-status --diff-filter=ARM ${{ github.event.pull_request.base.sha }} ${merged_commit} | awk '/\.md$/ {print $NF}')" - png_lines=$(grep -Eo '\]\([^)]+\)' --include='*.md' -r .|grep -Ev 'http'|grep -Ev 'mailto') + png_lines=$(grep -Eo '\]\([^)]+\)' --include='*.md' -r .|grep -Ev 'http'|grep -Ev 'mailto'|grep -Ev 'portal.azure.com') if [ -n "$png_lines" ]; then for png_line in $png_lines; do refer_path=$(echo "$png_line"|cut -d':' -f1 | cut -d'/' -f2-) From 98defe6418e3e583c25ac95b966a55c18fdcdc5e Mon Sep 17 00:00:00 2001 From: sri-intel <108247623+srinarayan-srikanthan@users.noreply.github.com> Date: Mon, 4 Nov 2024 14:43:06 -0500 Subject: [PATCH 13/34] Adding Azure instructions (#237) * added oci Signed-off-by: aice-support * modified links Signed-off-by: aice-support * added rag doc and png Signed-off-by: aice-support * fix broken link Signed-off-by: aice-support * standardization of code blocks Signed-off-by: aice-support * fix typo Signed-off-by: aice-support * rolling one commit back Signed-off-by: aice-support * resolved suggestions from malini Signed-off-by: aice-support --------- Signed-off-by: aice-support Co-authored-by: aice-support Co-authored-by: chen, suyue Signed-off-by: alexsin368 --- getting-started/README.md | 128 +++++++++--------- getting-started/assets/chat_ui_response.png | Bin 76033 -> 73870 bytes .../assets/chat_ui_response_rag.png | Bin 0 -> 121890 bytes getting-started/assets/what_is_opea.pdf | Bin 0 -> 53618 bytes 4 files changed, 65 insertions(+), 63 deletions(-) create mode 100644 getting-started/assets/chat_ui_response_rag.png create mode 100644 getting-started/assets/what_is_opea.pdf diff --git a/getting-started/README.md b/getting-started/README.md index 1ab8ced8..4d9a8e6f 100644 --- a/getting-started/README.md +++ b/getting-started/README.md @@ -14,19 +14,18 @@ Before moving forward, it's important to familiarize yourself with two key eleme ## Create and Configure a Virtual Server -::::{tab-set} -:::{tab-item} AWS -:sync: AWS +::::{tab-set} :sync-group: cloudserviceproviders +:::{tab-item} AWS :sync: aws -1. Navigate to [AWS console](https://console.aws.amazon.com/console/home) – Search EC2 in the search bar and select it. Click the `Launch Instance` button highlighted in orange. +1. Navigate to [AWS console](https://console.aws.amazon.com/console/home) – Search EC2 in the search bar and select it. Click the "Launch Instance" button highlighted in orange. 2. Provide a name to the VM. -3. In Quick Start, select the base OS as Ubuntu (ami-id : ami-04dd23e62ed049936). +3. In Quick Start, select the base OS as Ubuntu (`ami-id : ami-04dd23e62ed049936`). 4. Select an Instance type that is based on Intel hardware. ->**Note**: We recommend selecting a m7i.4xlarge or larger instance with an Intel(R) 4th Gen Xeon(C) Scalable Processor. For more information on virtual servers on AWS visit [here](https://aws.amazon.com/intel/). +>**Note**: We recommend selecting a `m7i.4xlarge` or larger instance with an Intel(R) 4th Gen Xeon(C) Scalable Processor. For more information on virtual servers on AWS visit [here](https://aws.amazon.com/intel/). 5. Next, create a new key pair, give it a name or select one from the existing key pairs. @@ -34,53 +33,86 @@ Before moving forward, it's important to familiarize yourself with two key eleme 7. Configure the storage to 100 GiB and click `Launch Instance`. -8. Click on the connect button on the top right and connect using your preferred method. +8. Click on the "connect" button on the top right and connect using your preferred method. + +9. Look up Security Groups in the search bar and select the security group used when creating the instance. + +10. Click on the Edit inbound rules on the right side of the window. + +11. Select Add rule at the bottom, and create a rule with type as Custom TCP , port range as 80 and source as 0.0.0.0/0 . Learn more about [editing inbound/outbound rules](https://docs.aws.amazon.com/finspace/latest/userguide/step5-config-inbound-rule.html) ::: -:::{tab-item} IBM Cloud -:sync: IBM Cloud +:::{tab-item} Azure :sync: azure -1. Navigate to [IBM Cloud](https://cloud.ibm.com). - Click the **Create resource** button at the top right of the screen. Select **Compute** from the options available and select `Virtual Server for VPC` +1. Navigate to [Microsoft Azure](portal.azure.com) – Select the "Skip" button on the bottom right to land on the service offerings page. Search for "Virtual Machines" in the search bar and select it. Click the "Create" button and select "Azure Virtual Machine". -2. Select a location for the instance. Assign a name to it. +2. Select an existing "Resource group" from the drop down or click "Create" for a new Resource group and give it a name. If you have issues refer to [cannot create resource groups](https://learn.microsoft.com/en-us/answers/questions/1520133/cannot-create-resource-groups). -3. Under Stock Images, select Ubuntu 24.04 (`ibm-ubuntu-24-04-6-minimal-amd64-1`) +3. Provide a name to the VM and select the base OS as `Ubuntu 24.04 LTS` -4. Select a virtual server. +4. Select x64 in VM architecture. -> **Note:** We recommend selecting a 3-series instance with an Intel(R) 4th Gen Xeon(C) Scalable Processor, such as `bx3d-16x80` or above. For more information on virtual servers on IBM cloud visit [Intel® solutions on IBM Cloud®](https://www.ibm.com/cloud/intel). +5. Select an Instance type that is based on Intel hardware. -5. Add an SSH key to the instance, if necessary, create one first. +>**Note**: We recommend selecting a `Standard_D16ds_v5` instance or larger with an Intel(R) 3rd/4th Gen Xeon(C) Scalable Processor. You can find this family of instances in the (US) West US Region. Visit for more information [virtual machines on Azure](https://azure.microsoft.com/en-us/partners/directory/intel-corporation). + +6. Select Password as Authentication type and create username and password for your instance. -6. Click on `Create virtual server`. +7. Choose the Allow selected ports in Inbound port rule section and select HTTP. -7. Once the instance is running, create and attach a `Floating IP` to the instance. For more information visit [this](https://cloud.ibm.com/docs/vpc?topic=vpc-fip-working&interface=ui) site +8. Click "Next: Disk" button and select OS disk size as 128GiB. -8. `ssh` into the instance using the floating IP (`ssh -i ubuntu@`) +9. Click on "Review + Create" to launch the VM. +10. Click Go to resource -> Connect -> Connect -> SSH using Azure CLI. Accept the terms and then select "Configure + connect" +>**Note**: If you have issues connecting to the instance with SSH, you could use instead Bastion with your username and password. ::: -:::{tab-item} GCP -:sync: GCP +:::{tab-item} GCP :sync: gcp -1. Navigate to [GCP console](https://console.cloud.google.com/) – Click the `Create a VM` button. +1. Navigate to [GCP console](https://console.cloud.google.com/) – Click the "Create a VM" button. 2. Provide a name to the VM. -3. Select the base OS as Ubuntu 24.04 LTS from Marketplace . +3. Select the base OS as `Ubuntu 24.04 LTS` from Marketplace . 4. Select an Instance type that is based on Intel hardware. -> **Note:**  We recommend selecting a c3-standard-22 or larger instance with an Intel(R) 4th Gen Xeon(C) Scalable Processor, and the minimum supported c3 instance type is c3-standard-8 with 32GB memory. For more information on virtual servers on GCP visit [here](https://cloud.google.com/intel). +> **Note:**   We recommend selecting a `c3-standard-22` or larger instance with an Intel(R) 4th Gen Xeon(C) Scalable Processor, and the minimum supported c3 instance type is c3-standard-8 with 32GB memory. For more information, visit [virtual servers on GCP](https://cloud.google.com/intel). 5. Under Firewall settings select “Allow HTTP traffic” to access ChatQnA UI web portal. -6. Change the Boot disk to 100 GiB and click Create. +6. Change the Boot disk to 100 GiB and click "Create". -7. Use any preferred SSH method such as ”Open in browser window” to connect to the instance +7. Use any preferred SSH method such as "Open in browser window" to connect to the instance. ::: -:::: +:::{tab-item} IBM Cloud :sync: ibmcloud + +1. Navigate to [IBM Cloud](https://cloud.ibm.com). - Click the **Create resource** button at the top right of the screen. Select **Compute** from the options available and select "Virtual Server for VPC" + +2. Select a location for the instance. Assign a name to it. + +3. Under Stock Images, select Ubuntu 24.04 (`ibm-ubuntu-24-04-6-minimal-amd64-1`) + +4. Select a virtual server. + +> **Note:** We recommend selecting a 3-series instance with an Intel(R) 4th Gen Xeon(C) Scalable Processor, such as `bx3d-16x80` or above. For more information on virtual servers on IBM cloud visit [Intel® solutions on IBM Cloud®](https://www.ibm.com/cloud/intel). + +5. Add an SSH key to the instance, if necessary, create one first. + +6. Click on "Create virtual server". + +7. Once the instance is running, create and attach a "Floating IP" to the instance. For more information visit [this](https://cloud.ibm.com/docs/vpc?topic=vpc-fip-working&interface=ui) site + +8. Under "Infrastructure" in the left pane, go to Network/Security groups//Rules + +9. Select "Create" + +10. Enable inbound traffic for port 80. For more information on editing inbound/outbound rules, click [here](https://cloud.ibm.com/docs/vpc?topic=vpc-updating-the-default-security-group&interface=ui) + +11. ssh into the instance using the floating IP (`ssh -i ubuntu@`) +::: :::: ## Deploy the ChatQnA Solution @@ -144,53 +176,23 @@ Run `docker ps -a` as an additional check to verify that all the services are ru ### Interact with ChatQnA - -::::{tab-set} -:::{tab-item} AWS -:sync: AWS - You can interact with ChatQnA via a browser interface: * To view the ChatQnA interface, open a browser and navigate to the UI by inserting your public facing IP address in the following: `http://{public_ip}:80’. ->**Note**: If you are having issue accessing the UI, you need to add an inbound rule in the security group. - -* Look up Security Groups in the search bar and select the security group used when creating the instance. -* Click on the Edit inbound rules on the right side of the window. -* Select Add rule at the bottom, and create a rule with type as Custom TCP , port range as 80 and source as 0.0.0.0/0 - -For more information on editing inbound/outbound rules, click [here](https://docs.aws.amazon.com/finspace/latest/userguide/step5-config-inbound-rule.html) - -::: -:::{tab-item} IBM Cloud -:sync: IBM Cloud - -You can interact with ChatQnA via a browser interface: -* Under `Infrastructure` in the left pane, go to `Network/Security groups//Rules` -* Select `Create` -* Enable inbound traffic for port 80 -* To view the ChatQnA interface, open a browser and navigate to the UI by inserting your externally facing IP address in the following: `http://{external_public_ip}:80'. - -For more information on editing inbound/outbound rules, click [here](https://cloud.ibm.com/docs/vpc?topic=vpc-updating-the-default-security-group&interface=ui) - -::: -:::{tab-item} GCP -:sync: GCP - -You can interact with ChatQnA via a browser interface: - -* To view the ChatQnA interface, open a browser and navigate to the UI by inserting your public facing IP address in the following: `http://{external_ip}:80’. - -::: -:::: - +We can go ahead and ask a sample question, say 'What is OPEA?'. A snapshot of the interface looks as follows: ![Chat Interface](assets/chat_ui_response.png) +Given that any information about OPEA was not in the training data for the model, we see the model hallucinating and coming up with a response. We can upload a document (PDF) with information and observe how the response changes. + +> **Note:** this example leverages the [OPEA document](assets/what_is_opea.pdf) for its RAG based content. You can download the [OPEA document](assets/what_is_opea.pdf) and upload it using the UI. + +![Chat Interface with RAG](assets/chat_ui_response_rag.png) -> **Note:** this example leverages the Nike 2023 Annual report for its RAG based content. See the [ChatQnA Sample Guide](https://opea-project.github.io/latest/examples/ChatQnA/ChatQnA_Guide.html) +We observe that the response is relevant and is based on the PDF uploaded. See the [ChatQnA Sample Guide](https://opea-project.github.io/latest/examples/ChatQnA/ChatQnA_Guide.html) to learn how you can customize the example with your own content. 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zD+G*>6tHj@1`$liZR3!}gT-N!`ijLt26|l);B;X^VD118vJfxgQz=Vhqfx|E+6FtD;FqZHWpCN?sG^BJq(*6fJTjc#f z2((mEUOwskz%Ud}2VWNqx`5bM7!$?XA*Lhm?HH3o>MM-JM`B&L_F_x{dIlt5h^9!y zc%*d%GYyHW;qyZDDPo@jX@)e{pf03!gt34WN-7VY>_`~-Y{X!ykkdRbo zm_3P-Md}xzhmh7Z7Z|u7wJma;F9bkaM}detE`iYyln0*cERg~m{GkFvjtEkk7-TTr bH7u)$NZ)mlnrA>RsIc-WRI1H4UsL`KL=-=P literal 0 HcmV?d00001 From 9b435ac9c856dbac58018a8da9b33d18d5e8e485 Mon Sep 17 00:00:00 2001 From: jiahuit1 <165232408+jiahuit1@users.noreply.github.com> Date: Tue, 5 Nov 2024 09:03:30 +0800 Subject: [PATCH 14/34] Add CONTRIBUTING.md file to root folder (#226) Signed-off-by: jiahuit1 Signed-off-by: alexsin368 --- CONTRIBUTING.md | 14 ++++++++++++++ 1 file changed, 14 insertions(+) create mode 100644 CONTRIBUTING.md diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md new file mode 100644 index 00000000..fd98dc42 --- /dev/null +++ b/CONTRIBUTING.md @@ -0,0 +1,14 @@ +## Contributing to OPEA + +Welcome to the OPEA open-source community! We are thrilled to have you here and excited about the potential contributions you can bring to the OPEA platform. Whether you are fixing bugs, adding new GenAI components, improving documentation, or sharing your unique use cases, your contributions are invaluable. + +Together, we can make OPEA the go-to platform for enterprise AI solutions. Let's work together to push the boundaries of what's possible and create a future where AI is accessible, efficient, and impactful for everyone. + +Please check the [Contributing guidelines](https://github.com/opea-project/docs/tree/main/community/CONTRIBUTING.md) for a detailed guide on how to contribute a GenAI component and all the ways you can contribute! + +Thank you for being a part of this journey. We can't wait to see what we can achieve together! + +## Additional Content + +- [Code of Conduct](https://github.com/opea-project/docs/tree/main/community/CODE_OF_CONDUCT.md) +- [Security Policy](https://github.com/opea-project/docs/tree/main/community/SECURITY.md) \ No newline at end of file From 4db044324562706991ed6f92b03fb6193371b891 Mon Sep 17 00:00:00 2001 From: Neo Zhang Jianyu Date: Tue, 5 Nov 2024 14:35:37 +0800 Subject: [PATCH 15/34] fix format issue, add CONTRIBUTING.md to index (#240) Co-authored-by: ZhangJianyu Signed-off-by: alexsin368 --- CONTRIBUTING.md | 4 +- getting-started/README.md | 106 ++++++++++++++++++++------------------ index.rst | 1 + 3 files changed, 59 insertions(+), 52 deletions(-) diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index fd98dc42..9c8bd2dc 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -1,4 +1,4 @@ -## Contributing to OPEA +# Contributing to OPEA Welcome to the OPEA open-source community! We are thrilled to have you here and excited about the potential contributions you can bring to the OPEA platform. Whether you are fixing bugs, adding new GenAI components, improving documentation, or sharing your unique use cases, your contributions are invaluable. @@ -8,7 +8,7 @@ Please check the [Contributing guidelines](https://github.com/opea-project/docs/ Thank you for being a part of this journey. We can't wait to see what we can achieve together! -## Additional Content +# Additional Content - [Code of Conduct](https://github.com/opea-project/docs/tree/main/community/CODE_OF_CONDUCT.md) - [Security Policy](https://github.com/opea-project/docs/tree/main/community/SECURITY.md) \ No newline at end of file diff --git a/getting-started/README.md b/getting-started/README.md index 4d9a8e6f..9d115caa 100644 --- a/getting-started/README.md +++ b/getting-started/README.md @@ -14,80 +14,84 @@ Before moving forward, it's important to familiarize yourself with two key eleme ## Create and Configure a Virtual Server -::::{tab-set} :sync-group: cloudserviceproviders -:::{tab-item} AWS :sync: aws +::::{tab-set} +:::{tab-item} AWS +:sync: AWS -1. Navigate to [AWS console](https://console.aws.amazon.com/console/home) – Search EC2 in the search bar and select it. Click the "Launch Instance" button highlighted in orange. +1. Navigate to [AWS console](https://console.aws.amazon.com/console/home) – Search EC2 in the search bar and select it. Click the "Launch Instance" button highlighted in orange. -2. Provide a name to the VM. +2. Provide a name to the VM. -3. In Quick Start, select the base OS as Ubuntu (`ami-id : ami-04dd23e62ed049936`). +3. In Quick Start, select the base OS as Ubuntu (`ami-id : ami-04dd23e62ed049936`). -4. Select an Instance type that is based on Intel hardware. +4. Select an Instance type that is based on Intel hardware. ->**Note**: We recommend selecting a `m7i.4xlarge` or larger instance with an Intel(R) 4th Gen Xeon(C) Scalable Processor. For more information on virtual servers on AWS visit [here](https://aws.amazon.com/intel/). +>**Note**: We recommend selecting a `m7i.4xlarge` or larger instance with an Intel(R) 4th Gen Xeon(C) Scalable Processor. For more information on virtual servers on AWS visit [here](https://aws.amazon.com/intel/). -5. Next, create a new key pair, give it a name or select one from the existing key pairs. +5. Next, create a new key pair, give it a name or select one from the existing key pairs. -6. Under Network settings select an existing security group. If there is none, create a new one by selecting the Create security group radio button and select the Allow SSH traffic and Allow HTTP traffic check box. +6. Under Network settings select an existing security group. If there is none, create a new one by selecting the Create security group radio button and select the Allow SSH traffic and Allow HTTP traffic check box. -7. Configure the storage to 100 GiB and click `Launch Instance`. +7. Configure the storage to 100 GiB and click `Launch Instance`. 8. Click on the "connect" button on the top right and connect using your preferred method. -9. Look up Security Groups in the search bar and select the security group used when creating the instance. +9. Look up Security Groups in the search bar and select the security group used when creating the instance. -10. Click on the Edit inbound rules on the right side of the window. +10. Click on the Edit inbound rules on the right side of the window. 11. Select Add rule at the bottom, and create a rule with type as Custom TCP , port range as 80 and source as 0.0.0.0/0 . Learn more about [editing inbound/outbound rules](https://docs.aws.amazon.com/finspace/latest/userguide/step5-config-inbound-rule.html) ::: -:::{tab-item} Azure :sync: azure +:::{tab-item} Azure +:sync: Azure 1. Navigate to [Microsoft Azure](portal.azure.com) – Select the "Skip" button on the bottom right to land on the service offerings page. Search for "Virtual Machines" in the search bar and select it. Click the "Create" button and select "Azure Virtual Machine". -2. Select an existing "Resource group" from the drop down or click "Create" for a new Resource group and give it a name. If you have issues refer to [cannot create resource groups](https://learn.microsoft.com/en-us/answers/questions/1520133/cannot-create-resource-groups). +2. Select an existing "Resource group" from the drop down or click "Create" for a new Resource group and give it a name. If you have issues refer to [cannot create resource groups](https://learn.microsoft.com/en-us/answers/questions/1520133/cannot-create-resource-groups). 3. Provide a name to the VM and select the base OS as `Ubuntu 24.04 LTS` -4. Select x64 in VM architecture. +4. Select x64 in VM architecture. -5. Select an Instance type that is based on Intel hardware. +5. Select an Instance type that is based on Intel hardware. ->**Note**: We recommend selecting a `Standard_D16ds_v5` instance or larger with an Intel(R) 3rd/4th Gen Xeon(C) Scalable Processor. You can find this family of instances in the (US) West US Region. Visit for more information [virtual machines on Azure](https://azure.microsoft.com/en-us/partners/directory/intel-corporation). +>**Note**: We recommend selecting a `Standard_D16ds_v5` instance or larger with an Intel(R) 3rd/4th Gen Xeon(C) Scalable Processor. You can find this family of instances in the (US) West US Region. Visit for more information [virtual machines on Azure](https://azure.microsoft.com/en-us/partners/directory/intel-corporation). -6. Select Password as Authentication type and create username and password for your instance. +6. Select Password as Authentication type and create username and password for your instance. -7. Choose the Allow selected ports in Inbound port rule section and select HTTP. +7. Choose the Allow selected ports in Inbound port rule section and select HTTP. -8. Click "Next: Disk" button and select OS disk size as 128GiB. +8. Click "Next: Disk" button and select OS disk size as 128GiB. -9. Click on "Review + Create" to launch the VM. +9. Click on "Review + Create" to launch the VM. -10. Click Go to resource -> Connect -> Connect -> SSH using Azure CLI. Accept the terms and then select "Configure + connect" +10. Click Go to resource -> Connect -> Connect -> SSH using Azure CLI. Accept the terms and then select "Configure + connect" ->**Note**: If you have issues connecting to the instance with SSH, you could use instead Bastion with your username and password. +>**Note**: If you have issues connecting to the instance with SSH, you could use instead Bastion with your username and password. ::: -:::{tab-item} GCP :sync: gcp +:::{tab-item} GCP +:sync: GCP -1. Navigate to [GCP console](https://console.cloud.google.com/) – Click the "Create a VM" button. +1. Navigate to [GCP console](https://console.cloud.google.com/) – Click the "Create a VM" button. -2. Provide a name to the VM. +2. Provide a name to the VM. -3. Select the base OS as `Ubuntu 24.04 LTS` from Marketplace . +3. Select the base OS as `Ubuntu 24.04 LTS` from Marketplace . -4. Select an Instance type that is based on Intel hardware. +4. Select an Instance type that is based on Intel hardware. -> **Note:**   We recommend selecting a `c3-standard-22` or larger instance with an Intel(R) 4th Gen Xeon(C) Scalable Processor, and the minimum supported c3 instance type is c3-standard-8 with 32GB memory. For more information, visit [virtual servers on GCP](https://cloud.google.com/intel). +> **Note:**   We recommend selecting a `c3-standard-22` or larger instance with an Intel(R) 4th Gen Xeon(C) Scalable Processor, and the minimum supported c3 instance type is c3-standard-8 with 32GB memory. For more information, visit [virtual servers on GCP](https://cloud.google.com/intel). -5. Under Firewall settings select “Allow HTTP traffic” to access ChatQnA UI web portal. +5. Under Firewall settings select “Allow HTTP traffic” to access ChatQnA UI web portal. -6. Change the Boot disk to 100 GiB and click "Create". +6. Change the Boot disk to 100 GiB and click "Create". -7. Use any preferred SSH method such as "Open in browser window" to connect to the instance. +7. Use any preferred SSH method such as "Open in browser window" to connect to the instance. ::: -:::{tab-item} IBM Cloud :sync: ibmcloud +:::{tab-item} IBM Cloud +:sync: IBM Cloud 1. Navigate to [IBM Cloud](https://cloud.ibm.com). - Click the **Create resource** button at the top right of the screen. Select **Compute** from the options available and select "Virtual Server for VPC" @@ -112,7 +116,9 @@ Before moving forward, it's important to familiarize yourself with two key eleme 10. Enable inbound traffic for port 80. For more information on editing inbound/outbound rules, click [here](https://cloud.ibm.com/docs/vpc?topic=vpc-updating-the-default-security-group&interface=ui) 11. ssh into the instance using the floating IP (`ssh -i ubuntu@`) -::: :::: + +::: +:::: ## Deploy the ChatQnA Solution @@ -176,9 +182,9 @@ Run `docker ps -a` as an additional check to verify that all the services are ru ### Interact with ChatQnA -You can interact with ChatQnA via a browser interface: +You can interact with ChatQnA via a browser interface: -* To view the ChatQnA interface, open a browser and navigate to the UI by inserting your public facing IP address in the following: `http://{public_ip}:80’. +* To view the ChatQnA interface, open a browser and navigate to the UI by inserting your public facing IP address in the following: `http://{public_ip}:80’. We can go ahead and ask a sample question, say 'What is OPEA?'. @@ -188,12 +194,12 @@ A snapshot of the interface looks as follows: Given that any information about OPEA was not in the training data for the model, we see the model hallucinating and coming up with a response. We can upload a document (PDF) with information and observe how the response changes. -> **Note:** this example leverages the [OPEA document](assets/what_is_opea.pdf) for its RAG based content. You can download the [OPEA document](assets/what_is_opea.pdf) and upload it using the UI. +> **Note:** this example leverages the [OPEA document](assets/what_is_opea.pdf) for its RAG based content. You can download the [OPEA document](assets/what_is_opea.pdf) and upload it using the UI. ![Chat Interface with RAG](assets/chat_ui_response_rag.png) We observe that the response is relevant and is based on the PDF uploaded. See the [ChatQnA Sample Guide](https://opea-project.github.io/latest/examples/ChatQnA/ChatQnA_Guide.html) -to learn how you can customize the example with your own content. +to learn how you can customize the example with your own content. To interact with the ChatQnA application via a `curl` command: @@ -215,26 +221,26 @@ Modify the `message` parameter in the `curl` command to continue interacting wit ### Get Involved -Have you ideas and skills to build out genAI components, microservices, and solutions? Would you like to be a part of this evolving technology in its early stages? Welcome! -* Register for our mailing list: - * [Mailing List](https://lists.lfaidata.foundation/g/OPEA-announce) +Have you ideas and skills to build out genAI components, microservices, and solutions? Would you like to be a part of this evolving technology in its early stages? Welcome! +* Register for our mailing list: + * [Mailing List](https://lists.lfaidata.foundation/g/OPEA-announce) * [Technical Discussions](https://lists.lfaidata.foundation/g/OPEA-technical-discuss) * Subscribe to the working group mailing lists that interest you - * [End user](https://lists.lfaidata.foundation/g/OPEA-End-User) - * [Evaluation](https://lists.lfaidata.foundation/g/OPEA-Evaluation) - * [Community](https://lists.lfaidata.foundation/g/OPEA-Community) - * [Research](https://lists.lfaidata.foundation/g/OPEA-Research) - * [Security](https://lists.lfaidata.foundation/g/OPEA-Security) -* Go to the Community Section of the OPEA repo for [Contribution Guidelines](https://opea-project.github.io/latest/community/CONTRIBUTING.html) and step by step instructions. -* Attend any of our community events and hackathons. https://wiki.lfaidata.foundation/display/DL/OPEA+Community+Events + * [End user](https://lists.lfaidata.foundation/g/OPEA-End-User) + * [Evaluation](https://lists.lfaidata.foundation/g/OPEA-Evaluation) + * [Community](https://lists.lfaidata.foundation/g/OPEA-Community) + * [Research](https://lists.lfaidata.foundation/g/OPEA-Research) + * [Security](https://lists.lfaidata.foundation/g/OPEA-Security) +* Go to the Community Section of the OPEA repo for [Contribution Guidelines](https://opea-project.github.io/latest/community/CONTRIBUTING.html) and step by step instructions. +* Attend any of our community events and hackathons. https://wiki.lfaidata.foundation/display/DL/OPEA+Community+Events Current GenAI Examples -- Simple chatbot that uses retrieval augmented generation (RAG) architecture. [ChatQnA](/examples/ChatQnA/ChatQnA_Guide.rst) +- Simple chatbot that uses retrieval augmented generation (RAG) architecture. [ChatQnA](/examples/ChatQnA/ChatQnA_Guide.rst) - Code generation, from enabling non-programmers to generate code to improving productivity with code completion of complex applications. [CodeGen](https://opea-project.github.io/latest/GenAIExamples/CodeGen/README.html) - Make your applications more flexible by porting to different languages. [CodeTrans](https://opea-project.github.io/latest/GenAIExamples/CodeTrans/README.html) - Create summaries of news articles, research papers, technical documents, etc. to streamline content systems. [DocSum](https://opea-project.github.io/latest/GenAIExamples/DocSum/README.html) - Mimic human behavior by iteratively searching, selecting, and synthesizing information across large bodies of content. [SearchQnA](https://opea-project.github.io/latest/GenAIExamples/SearchQnA/README.html) - Provide critical content to your customers by automatically generating Frequently Asked Questions (FAQ) resources. [FaqGen](https://opea-project.github.io/latest/GenAIExamples/FaqGen/README.html) - Provide text descriptions from pictures, enabling your users to inquire directly about products, services, sites, etc. [VisualQnA](https://opea-project.github.io/latest/GenAIExamples/VisualQnA/README.html) -- Reduce language barriers through customizable text translation systems. [Translation](https://opea-project.github.io/latest/GenAIExamples/Translation/README.html) +- Reduce language barriers through customizable text translation systems. [Translation](https://opea-project.github.io/latest/GenAIExamples/Translation/README.html) diff --git a/index.rst b/index.rst index 42974299..4c6b3f37 100644 --- a/index.rst +++ b/index.rst @@ -76,6 +76,7 @@ Source code for the OPEA Project is maintained in the developer-guides/index community/index release_notes/index + CONTRIBUTING faq .. _OPEA Project GitHub repository: https://github.com/opea-project From 8f21481dc88730bf251446e028b4efc3510e99c8 Mon Sep 17 00:00:00 2001 From: sri-intel <108247623+srinarayan-srikanthan@users.noreply.github.com> Date: Tue, 5 Nov 2024 12:17:45 -0500 Subject: [PATCH 16/34] oci instruction (#242) Signed-off-by: aice-support Co-authored-by: aice-support Signed-off-by: alexsin368 --- getting-started/README.md | 36 +++++++++++++++++++++++++++++++++--- 1 file changed, 33 insertions(+), 3 deletions(-) diff --git a/getting-started/README.md b/getting-started/README.md index 9d115caa..3e923514 100644 --- a/getting-started/README.md +++ b/getting-started/README.md @@ -32,7 +32,7 @@ Before moving forward, it's important to familiarize yourself with two key eleme 6. Under Network settings select an existing security group. If there is none, create a new one by selecting the Create security group radio button and select the Allow SSH traffic and Allow HTTP traffic check box. -7. Configure the storage to 100 GiB and click `Launch Instance`. +7. Configure the storage to 100 GiB and click "Launch Instance". 8. Click on the "connect" button on the top right and connect using your preferred method. @@ -81,7 +81,7 @@ Before moving forward, it's important to familiarize yourself with two key eleme 4. Select an Instance type that is based on Intel hardware. -> **Note:**   We recommend selecting a `c3-standard-22` or larger instance with an Intel(R) 4th Gen Xeon(C) Scalable Processor, and the minimum supported c3 instance type is c3-standard-8 with 32GB memory. For more information, visit [virtual servers on GCP](https://cloud.google.com/intel). +> **Note:**   We recommend selecting a `c4-standard-32` or larger instance with an Intel(R) 4th Gen Xeon(C) Scalable Processor, and the minimum supported c3 instance type is c3-standard-8 with 32GB memory. For more information, visit [virtual servers on GCP](https://cloud.google.com/intel). 5. Under Firewall settings select “Allow HTTP traffic” to access ChatQnA UI web portal. @@ -93,7 +93,7 @@ Before moving forward, it's important to familiarize yourself with two key eleme :::{tab-item} IBM Cloud :sync: IBM Cloud -1. Navigate to [IBM Cloud](https://cloud.ibm.com). - Click the **Create resource** button at the top right of the screen. Select **Compute** from the options available and select "Virtual Server for VPC" +1. Navigate to [IBM Cloud](https://cloud.ibm.com). - Click the "Create resource" button at the top right of the screen. Select "Compute" from the options available and select "Virtual Server for VPC" 2. Select a location for the instance. Assign a name to it. @@ -117,6 +117,36 @@ Before moving forward, it's important to familiarize yourself with two key eleme 11. ssh into the instance using the floating IP (`ssh -i ubuntu@`) +::: +:::{tab-item} OCI +:sync: OCI + +1. Navigate to [Oracle Cloud Console](https://www.oracle.com/cloud/sign-in.html?redirect_uri=https%3A%2F%2Fcloud.oracle.com%2F) – Then navigate to [Compute Instances](https://cloud.oracle.com/compute/instances). Click the "Create Instance" button. + +2. Provide a name to the VM and select the placement in the availability domains. + +3. In Image and Shape section click "Change Image" > "Ubuntu" and then select `Canonical Ubuntu 24.04`. Submit using the "Select Image" button at the bottom. + +4. Click the "Change Shape" > "Bare Metal Machine" then select the `BM.Standard3.64`. Submit using the "Select Shape" button at the bottom. + +5. Select the VCN and the public subnet that the server needs to reside in. If a new VCN/Subnet needs to be created then select the "Create new virtual cloud network" and the "Create new public subnet" to create a subnet that is exposed to the internet. + +6. Next, save a private key by or upload an existing public key. + +7. Specify a boot volume size of 100 GiB with 30 VPU units of performance. + +8. Click Create to launch the instance. + +9. Note the public IP address of the machine once its launched. + +10. Once the instance is launched, click on the subnet in the Primary VNIC section. Then click on the "Default Security List for vcn-xxxxxxxx-xxxx" , click on the "Add Ingress Rules". Add the following information: + Source CIDR: 0.0.0.0/0 + Source Port Range : All + Destination Port Range : 80 + Click on "Save" + +11. Connect using ssh (`ssh -i ubuntu@`). + ::: :::: From 77ff17943e2279ddb4f6c0357d05f5d66b66f343 Mon Sep 17 00:00:00 2001 From: sri-intel <108247623+srinarayan-srikanthan@users.noreply.github.com> Date: Thu, 7 Nov 2024 16:20:05 -0500 Subject: [PATCH 17/34] Update on gsg (#245) * updated based on comments Signed-off-by: aice-support * removed curl instruction Signed-off-by: aice-support * incorporated feedback Signed-off-by: aice-support --------- Signed-off-by: aice-support Co-authored-by: aice-support Signed-off-by: alexsin368 --- getting-started/README.md | 85 ++++++++---------- .../assets/chat_ui_response_rag.png | Bin 121890 -> 70860 bytes 2 files changed, 35 insertions(+), 50 deletions(-) diff --git a/getting-started/README.md b/getting-started/README.md index 3e923514..a8c80ee4 100644 --- a/getting-started/README.md +++ b/getting-started/README.md @@ -1,13 +1,12 @@ # Getting Started with OPEA -In this document, we provide a tailored guide to deploying the ChatQnA application in OPEA GenAI Examples across multiple cloud platforms, including IBM Cloud, Amazon Web Services (AWS), and others, enabling you to choose the best fit for your specific needs and requirements. For additional deployment targets, see the [ChatQnA Sample Guide](https://opea-project.github.io/latest/examples/ChatQnA/ChatQnA_Guide.html). - +In this document, we provide a tailored guide to deploying the ChatQnA application in OPEA GenAI Examples across multiple cloud platforms, including Amazon Web Services (AWS), Google Cloud Platform (GCP), IBM Cloud, Microsoft Azure and Oracle Cloud Infrastructure, enabling you to choose the best fit for your specific needs and requirements. For additional deployment targets, see the [ChatQnA Sample Guide](https://opea-project.github.io/latest/examples/ChatQnA/ChatQnA_Guide.html). ## Understanding OPEA's Core Components Before moving forward, it's important to familiarize yourself with two key elements of OPEA: GenAIComps and GenAIExamples. - GenAIComps is a collection of microservice components that form a service-based toolkit. This includes a variety of services such as llm (large language models), embedding, and reranking, among others. -- While GenAIComps offers a range of microservices, GenAIExamples provides practical, deployable solutions to help users implement these services effectively. Examples include ChatQnA and DocSum, which leverage the microservices for specific applications. +- GenAIExamples provides practical and deployable solutions to help users implement these services effectively. Examples include ChatQnA and DocSum, which leverage the microservices for specific applications. ## Prerequisites @@ -15,7 +14,7 @@ Before moving forward, it's important to familiarize yourself with two key eleme ## Create and Configure a Virtual Server ::::{tab-set} -:::{tab-item} AWS +:::{tab-item} Amazon Web Services :sync: AWS 1. Navigate to [AWS console](https://console.aws.amazon.com/console/home) – Search EC2 in the search bar and select it. Click the "Launch Instance" button highlighted in orange. @@ -43,34 +42,7 @@ Before moving forward, it's important to familiarize yourself with two key eleme 11. Select Add rule at the bottom, and create a rule with type as Custom TCP , port range as 80 and source as 0.0.0.0/0 . Learn more about [editing inbound/outbound rules](https://docs.aws.amazon.com/finspace/latest/userguide/step5-config-inbound-rule.html) ::: -:::{tab-item} Azure -:sync: Azure - -1. Navigate to [Microsoft Azure](portal.azure.com) – Select the "Skip" button on the bottom right to land on the service offerings page. Search for "Virtual Machines" in the search bar and select it. Click the "Create" button and select "Azure Virtual Machine". - -2. Select an existing "Resource group" from the drop down or click "Create" for a new Resource group and give it a name. If you have issues refer to [cannot create resource groups](https://learn.microsoft.com/en-us/answers/questions/1520133/cannot-create-resource-groups). - -3. Provide a name to the VM and select the base OS as `Ubuntu 24.04 LTS` - -4. Select x64 in VM architecture. - -5. Select an Instance type that is based on Intel hardware. - ->**Note**: We recommend selecting a `Standard_D16ds_v5` instance or larger with an Intel(R) 3rd/4th Gen Xeon(C) Scalable Processor. You can find this family of instances in the (US) West US Region. Visit for more information [virtual machines on Azure](https://azure.microsoft.com/en-us/partners/directory/intel-corporation). - -6. Select Password as Authentication type and create username and password for your instance. - -7. Choose the Allow selected ports in Inbound port rule section and select HTTP. - -8. Click "Next: Disk" button and select OS disk size as 128GiB. - -9. Click on "Review + Create" to launch the VM. - -10. Click Go to resource -> Connect -> Connect -> SSH using Azure CLI. Accept the terms and then select "Configure + connect" - ->**Note**: If you have issues connecting to the instance with SSH, you could use instead Bastion with your username and password. -::: -:::{tab-item} GCP +:::{tab-item} Google Cloud Platform :sync: GCP 1. Navigate to [GCP console](https://console.cloud.google.com/) – Click the "Create a VM" button. @@ -116,12 +88,38 @@ Before moving forward, it's important to familiarize yourself with two key eleme 10. Enable inbound traffic for port 80. For more information on editing inbound/outbound rules, click [here](https://cloud.ibm.com/docs/vpc?topic=vpc-updating-the-default-security-group&interface=ui) 11. ssh into the instance using the floating IP (`ssh -i ubuntu@`) +::: +:::{tab-item} Microsoft Azure +:sync: Azure +1. Navigate to [Microsoft Azure](portal.azure.com) – Select the "Skip" button on the bottom right to land on the service offerings page. Search for "Virtual Machines" in the search bar and select it. Click the "Create" button and select "Azure Virtual Machine". + +2. Select an existing "Resource group" from the drop down or click "Create" for a new Resource group and give it a name. If you have issues refer to [cannot create resource groups](https://learn.microsoft.com/en-us/answers/questions/1520133/cannot-create-resource-groups). + +3. Provide a name to the VM and select the base OS as `Ubuntu 24.04 LTS` + +4. Select x64 in VM architecture. + +5. Select an Instance type that is based on Intel hardware. + +>**Note**: We recommend selecting a `Standard_D16ds_v5` instance or larger with an Intel(R) 3rd/4th Gen Xeon(C) Scalable Processor. You can find this family of instances in the (US) West US Region. Visit for more information [virtual machines on Azure](https://azure.microsoft.com/en-us/partners/directory/intel-corporation). + +6. Select Password as Authentication type and create username and password for your instance. + +7. Choose the Allow selected ports in Inbound port rule section and select HTTP. + +8. Click "Next: Disk" button and select OS disk size as 128GiB. + +9. Click on "Review + Create" to launch the VM. + +10. Click Go to resource -> Connect -> Connect -> SSH using Azure CLI. Accept the terms and then select "Configure + connect" + +>**Note**: If you have issues connecting to the instance with SSH, you could use instead Bastion with your username and password. ::: -:::{tab-item} OCI +:::{tab-item} Oracle Cloud Infrastructure :sync: OCI -1. Navigate to [Oracle Cloud Console](https://www.oracle.com/cloud/sign-in.html?redirect_uri=https%3A%2F%2Fcloud.oracle.com%2F) – Then navigate to [Compute Instances](https://cloud.oracle.com/compute/instances). Click the "Create Instance" button. +1. Login to [Oracle Cloud Console](https://www.oracle.com/cloud/sign-in.html?redirect_uri=https%3A%2F%2Fcloud.oracle.com%2F) – Then navigate to [Compute Instances](https://cloud.oracle.com/compute/instances). Click the "Create Instance" button. 2. Provide a name to the VM and select the placement in the availability domains. @@ -152,7 +150,7 @@ Before moving forward, it's important to familiarize yourself with two key eleme ## Deploy the ChatQnA Solution -Use the command below to install docker on a clean virtual machine +Use the command below to install docker: ```bash wget https://raw.githubusercontent.com/opea-project/GenAIExamples/refs/heads/main/ChatQnA/docker_compose/install_docker.sh chmod +x install_docker.sh @@ -188,7 +186,7 @@ For example to check the logs for the `tgi-service`: ```bash docker logs tgi-service | grep Connected ``` -The output shows `Connected` as shown: +Proceed further **only after** the output shows `Connected` as shown: ``` tgi-service | 2024-10-18T22:41:18.973042Z INFO text_generation_router::server: router/src/server.rs:2311: Connected ``` @@ -224,26 +222,13 @@ A snapshot of the interface looks as follows: Given that any information about OPEA was not in the training data for the model, we see the model hallucinating and coming up with a response. We can upload a document (PDF) with information and observe how the response changes. -> **Note:** this example leverages the [OPEA document](assets/what_is_opea.pdf) for its RAG based content. You can download the [OPEA document](assets/what_is_opea.pdf) and upload it using the UI. +> **Note:** this example leverages the OPEA document for its RAG based content. You can download the [OPEA document](assets/what_is_opea.pdf) and upload it using the UI. ![Chat Interface with RAG](assets/chat_ui_response_rag.png) We observe that the response is relevant and is based on the PDF uploaded. See the [ChatQnA Sample Guide](https://opea-project.github.io/latest/examples/ChatQnA/ChatQnA_Guide.html) to learn how you can customize the example with your own content. -To interact with the ChatQnA application via a `curl` command: - -```bash -curl http://${host_ip}:8888/v1/chatqna \ - -H "Content-Type: application/json" \ - -d '{ - "messages": "What is the revenue of Nike in 2023?" - }' -``` -ChatQnA provides the answer to your query as a text stream. - -Modify the `message` parameter in the `curl` command to continue interacting with ChatQnA. - ## What’s Next - Try [GenAIExamples](/examples/index.rst) in-detail starting with [ChatQnA](/examples/ChatQnA/ChatQnA_Guide.rst) example; this is a great example to orient yourself to the OPEA ecosystem. diff --git a/getting-started/assets/chat_ui_response_rag.png b/getting-started/assets/chat_ui_response_rag.png index d687c16424889e3b28854f252245028dd4b0c585..b5e27fa9c4039c251a993d1986aade581cbb36f9 100644 GIT binary patch literal 70860 zcmeFZXH-*b*EY)DZe?##k&S{Y zN)Iix5S5T9ReA{!P3Q>;0YVbePTbG;i0^yG_x?EJ{5WTP&l-clSYfTKd(C^^*SzL6 z=S}=ID~s)0m9|PrNo~J$@!Sn5sjcs%q&B(!x<&HIJ}<2p$*-S6Zdm*wRo<;KFFESq!bQ)`}yh8je|>4QsRP3=g!=WaHCJiWT}S1jYLe( zcjtbJaT&k)=I}%B{ntKdlzsNxyr6yb$g3Iy=e{wIT&L19OMKDgT9oXV#mGRBTY~Kk z=Q~59g1;0xJ+U6xKg|z3q22iK%;C}R4HxV09JsIs3h8FjbAZ0x3=>#~)p9h>?X1sC zXL<*dlW7vN7R9w3zIIqLy8m^&Jh*mA{PVxhq)s3G_1(tVwPQb5e*cry^8~5m8)pRv zq-4IIoqqeD+oYuaN0U?=Nx@u$L&L&$Z^NGaTj8hgwtG2}tS;Mz<$!i)GA8y~Ga^j8 zCiFtLd-rkaPo+J27Odsjc6h=oHd^0u^A5-Z+pAp>9tz-${zD)WY5{x0&2T?}i!S&*KnhN`;=Y zU)y#M?`T`s>;Fs5LqlzH7i|)KY*N6oRDBfFWbLe~&Kqe%3qCgZbqCZO)p5G#*$gT5 zsjAnl8*edHD7^H21TRNOAd!cFI;(DNvuGmtY{GgALPR%ziR2fWOrHz`zGI9lDMyQ6 zynqat$Zy3lo*V;W)`(+dkcL7R0JNo#9v;v%BX9_viw8%?ejOgK(=A7aBs=Z&b%ELh zSg-hG>y{_hQVpH~hT0y(`i;Lo_u5>Qzk1+ST=ztURy3_MIsa z7qAcO6h=PVLvhU2B_d`*pnnUxewF_E`L=(mGL}f~0CyU{^i4WTlW0&kNgc-T!GsQ<@^k?~WH4_NA=Iy8nKK zTz|}NyX+OOPhTfa8ey%}?6CV%k&4mTdLXEk^GTOvEh}0)FQm_3I{^Ubv8vy?$iAi%OVd_>@j zHxREZMKFHqxfpUlrzzYntk$Ib(k~tm!aHZE*MtKRP^4)moX}>yOMVrx3d7(DC|9*K zSy^RjDigR9@HiZwj|om{SxLp8q5fjRxkKXTLn0A&#bu$yWn9A{wF%ap@vzqQulHRL zt*)cZs^H-wyS5KCx1U%dpwXpGx|Vc1fLE)na$f}Y5V(6eN8c^jxfDw&)Zg)a@B=Qa z24bHB{->U?qP`XXrsbV<-j&>Eg$G(fNhnGiuKG|ajxVZ@5Nfc#tmPKk`xM1Xdjz)_ zPYU8s_EqS@eaE?O;-MtfK4I#;DAQ@WT<`;p8G)BAn=UMgq4hP5lL7jPuyO3niRIp1XvoUzz6;CIA%4LPEMjI}ikNG<0ok zE8x8py?YKphUHJ6WxMw&Lg3RB;|AeA7M?z)mT8VY+&$;GbEUB{ujEu`;%1;PKEpa7 zVX>+2zE|XZ34EbJLn6OmZ=lSM;<6&sPUp&fR%ZT|68}6AUgto5*WSp<8Wh|U7mFP1 zFq2WnGkrH7TCZ7roo>h2(-;2sk=D6_gH4Ch9%3}6Kz@MGz252cd zoJMIqkBzX)QcH8MHiafYk7ZwmR3v&^sO-`dO^(%nWdxr5y>)yqiP5ruNHiG_{wz0p z4pBlBkxA;LVZf0AxHS;Qe^$gbKCRhR9LZ44pRjf75&IaIGoK=IvCaPM%Dc~|pF zBOARRX=K9JKr=emp5a$|+?3(EmhzT{c!Jf#*G+ZAcey@9_&}9I$aG<^ceS2w8i!zF z(UoX38D>*se~d&~z-cW!TAOkZWi&H~pXGCqkA53*fD9g=!zz4#f1mhSwWTC|yINY& zS-(;}9KU!LFBX23q2?p{R1x=P1jb*_=f~7!G7-nRnXrA9U25`M-vu>ApY5>d>w)(J zyavDed1la?VS!mAA<^3cuIM?9)=AI`7BYTwmzmo59wC`g%IO=4v}xu{J?e!`3_SJ- zu5Wo`Jup6A{{`j5nR6-ybn~$N{SnpMbNy{YkdpUeYA1QC@44DvHnEDcil4NuyMCDC zs!GG<5NO)wnyH0`A^6%Ob63db2Mt@8aoi@1cATPFFnRSZzRWpV1yRR%rEdVZdPEA=VOa*H(vt_h{?aWX zSfXbP{5@?ll!n((_+r@rOL?1Hu+`i_WuZ;#pA)-`qIHml^T>jtg5DjWxpn%`zKHy6 z$oOvR^y3g`&^@c;O;y4e6)rZB@)-Pcag4gN^PVh*V}qGOAp${+ zCg=s`Y$l4>z-$10!;QYI;uu+#2@U$~=7mE&$q1NOF8_~8`=~W^{koR*>$elZKmRmR zc9PqrKQ^^$JblP7bSwZ_M!uAv-Y_xI3$#*v8-u9UA<&7T(bid_^}$|9+aQ=-bhmYV z4o3a-1oQ$odfH{xUc=wz-a@eho1ow9Y1}^QaVyKs`S5mZ;;i?IdR$rA?{9VI{r28g z?SBG9A4D2P-ht6C=6f~FCx-2xZE)O+vi}GG{Z1ond$WVEu9f)kBM`knZ#Qz@=8{J@}uq5lrrHE#Bm303=Ts4CCAfijx3}Cq%HpR-ddmOHMA~=_eew}~PngrnD+r_qA(vC0E>2s&W|+Q0B*@)9jT$X);H zb|mR?M=}Rkd)={41WiaAk(#{+oQol|8B1=2TE7>X^$*A|HpSXu* zOoMqdrBUIxy|dE#&l(W`#9xic_xkq;mnWOehXyyN#bWP89tWO6Y8K%N>t#pkXBI}5 zZYxRud#WE`KO&;Vn&_Eei&%G9kMW7}ChihLv5pt-xP&Y_WVvD|=m18;Evih+8<&o8fK$~sdV<%?DUjQ_bRwMIZo>4`zt;JAE z&wfo}TduSEmHylLfsk!=^jGXct)UCoEie-mprWJtKu%|fQ-IgmQk<3gM*cyEE5($k z!~7vG%lz23cnf59jNpp_ir^l-{6v2@Ym$w^TZn3fJLw&W=+K@j@|YRmev|}47;Yid zhamUe6Mn^RoQ4w0s=oPHcSMb_v0Z_zMyd-;e6Jf6x7|J{PFdY*#bQ)RcGn?O-=+rX zwljXA$3w`g-40<98E=dbk*hiB1m!^ZKDCSa`Siy9Lx|=#?;*tE>CM751{tcnN!{Ij z&+BiA-#^C#;2=kRVz-#fBlh3KZ>|6yNyUbW^#{kKjm(so;-V)@{$2calI;7O`}Agg zJNATxksue{Y?L2hy()!7n)S%Cv2Z|t><#S9trOu_0hqSJk|9FIZeRRKi{o*TuCBcX z%$E+89%ocS)=j|O?FQ&qbG^d!?54htx9K2|!t36{9N>xfm9rk>_brqHL#IB}wcp`s zCFJ8HrFc^|%KQLTqP-!$F;74n5Ak%o&TJetv;tMPt>H%0l@D!Dxsk;2(BU~>PA(^5 zQ@?|MWKRWCEY4`HFo^thtyO#~`qywGD%Z-(Rua&{SFxslV&~%J6^nWg8xg)>{X&&2 zMJ!ReD~VcoC9UmYqzna5c98c6MV{R@i7A`b5M*vAxMudx-44}_d*oO1$uiT^Uup3p zgz)PDbxb9DZNc*VUd>Ip+>5swy5U~ISy=?-u-t~c^T91f_{NfhKa3J4xHo%Esl;^Z z9r|o^WM%D}+2IQa-X{x6{&1kROf2ecn@7VR=QBiUXb9C0^7nzvfMV;Ku!i1*{9eE2*#1dzWt`N}En0 zjYfE{Z1S|2V9Xtdd(q>6r}~H5hzF}*PX5~iq&$2CcV_3@91!cPbEgBa2rk_##lycz zGz>CVv5#h;^#|!%7!(6uhyQ6L&c@209U+K&4{_bK$+|G!@os-pYFkD{QT&#PqOv$! 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607e34806d26ec257a682322ef438a5a8dd286e3 Mon Sep 17 00:00:00 2001 From: Neo Zhang Jianyu Date: Fri, 8 Nov 2024 09:38:54 +0800 Subject: [PATCH 18/34] add ci for build online doc (#241) * add ci for build online doc * for debug * for debug * fix bug * add print Signed-off-by: ZhangJianyu * add print * debug * debug * debug * debug * debug * fix * debug * fix * debug * debug * debug * debug * debug * debug * debug * debug * debug * debug * debug * debug * debug * debug * debug * debug * debug * debug * debug * debug * debug * debug * debug * debug * debug * debug * rm write access --------- Signed-off-by: ZhangJianyu Co-authored-by: ZhangJianyu Signed-off-by: alexsin368 --- .github/workflows/check-online-doc-build.yml | 21 ++++++++++++++++++++ CONTRIBUTING.md | 2 +- conf.py | 1 + scripts/build.sh | 2 +- scripts/filter-doc-log.sh | 8 ++++---- scripts/filter-known-issues.py | 12 +++++++++-- 6 files changed, 38 insertions(+), 8 deletions(-) create mode 100644 .github/workflows/check-online-doc-build.yml diff --git a/.github/workflows/check-online-doc-build.yml b/.github/workflows/check-online-doc-build.yml new file mode 100644 index 00000000..f4c21fbe --- /dev/null +++ b/.github/workflows/check-online-doc-build.yml @@ -0,0 +1,21 @@ +# Copyright (C) 2024 Intel Corporation +# SPDX-License-Identifier: Apache-2.0 + +name: Check Online Document Building +permissions: {} + +on: + pull_request: + branches: [main] + +jobs: + build: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + - name: Build Online Document + shell: bash + run: | + git config --local --get remote.origin.url + echo "build online doc" + bash scripts/build.sh diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index 9c8bd2dc..2a3bfc2c 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -11,4 +11,4 @@ Thank you for being a part of this journey. We can't wait to see what we can ach # Additional Content - [Code of Conduct](https://github.com/opea-project/docs/tree/main/community/CODE_OF_CONDUCT.md) -- [Security Policy](https://github.com/opea-project/docs/tree/main/community/SECURITY.md) \ No newline at end of file +- [Security Policy](https://github.com/opea-project/docs/tree/main/community/SECURITY.md) diff --git a/conf.py b/conf.py index 43164625..40e46375 100644 --- a/conf.py +++ b/conf.py @@ -114,6 +114,7 @@ ) } +show_warning_types = True # Theme options are theme-specific and customize the look and feel of a theme # further. For a list of options available for each theme, see the diff --git a/scripts/build.sh b/scripts/build.sh index 89679883..9cedec55 100755 --- a/scripts/build.sh +++ b/scripts/build.sh @@ -40,8 +40,8 @@ echo "Build HTML" cd docs make clean make html - retval=$? +echo "result = $retval" if [ $retval -ne 0 ]; then echo "make html is error" exit 1 diff --git a/scripts/filter-doc-log.sh b/scripts/filter-doc-log.sh index 61f2417c..a7cbd90a 100755 --- a/scripts/filter-doc-log.sh +++ b/scripts/filter-doc-log.sh @@ -9,7 +9,7 @@ # Only argument is the name of the log file saved by the build. KI_SCRIPT=scripts/filter-known-issues.py -CONFIG_DIR=.known-issues/doc +CONFIG_DIR=.known-issues/ LOG_FILE=$1 BUILDDIR=$(dirname $LOG_FILE) @@ -32,7 +32,7 @@ else fi if [ -s "${LOG_FILE}" ]; then - $KI_SCRIPT --config-dir ${CONFIG_DIR} ${LOG_FILE} > ${BUILDDIR}/doc.warnings 2>&1 + python3 $KI_SCRIPT --config-dir ${CONFIG_DIR} ${LOG_FILE} > ${BUILDDIR}/doc.warnings 2>&1 if [ -s ${BUILDDIR}/doc.warnings ]; then echo echo -e "${red}New errors/warnings found, please fix them:" @@ -41,7 +41,7 @@ if [ -s "${LOG_FILE}" ]; then echo cat ${BUILDDIR}/doc.warnings echo - exit 1 + exit 2 else echo -e "${green}No new errors/warnings." $TPUT sgr0 @@ -49,5 +49,5 @@ if [ -s "${LOG_FILE}" ]; then else echo "Error in $0: logfile \"${LOG_FILE}\" not found." - exit 1 + exit 3 fi diff --git a/scripts/filter-known-issues.py b/scripts/filter-known-issues.py index 79f56fd1..256aa3be 100755 --- a/scripts/filter-known-issues.py +++ b/scripts/filter-known-issues.py @@ -113,12 +113,21 @@ def config_import(paths): _paths = [] # Go over the list, flush it if the user gave an empty path ("") for path in paths: + if not os.path.exists(path): + logging.debug("{} not exist".format(path)) + continue + if path == "" or path is None: logging.debug("flushing current config list: %s", _paths) _paths = [] else: _paths.append(path) logging.debug("config list: %s", _paths) + + if len(_paths)==0: + logging.debug("No available path") + assert(False) + for path in _paths: config_import_path(path) @@ -146,8 +155,7 @@ def config_import(paths): logging.basicConfig(level=40 - 10 * (args.verbosity - args.quiet), format="%(levelname)s: %(message)s") -path = ".known-issues/" -logging.debug("Reading configuration from directory `%s`", path) +logging.debug("Reading configuration from directory `%s`", args.config_dir) config_import(args.config_dir) exclude_ranges = [] From 230a1468b7d79ce25ed04d157e4cf6a43dfc5b35 Mon Sep 17 00:00:00 2001 From: alexsin368 Date: Fri, 8 Nov 2024 17:56:04 -0800 Subject: [PATCH 19/34] CodeGen: add gaudi deployment sample guide Signed-off-by: alexsin368 --- examples/CodeGen/deploy/gaudi.md | 372 +++++++++++++++++++++++++++++++ 1 file changed, 372 insertions(+) create mode 100644 examples/CodeGen/deploy/gaudi.md diff --git a/examples/CodeGen/deploy/gaudi.md b/examples/CodeGen/deploy/gaudi.md new file mode 100644 index 00000000..9ad3971d --- /dev/null +++ b/examples/CodeGen/deploy/gaudi.md @@ -0,0 +1,372 @@ +# Single node on-prem deployment with vLLM or TGI on Gaudi AI Accelerator + +This deployment section covers single-node on-prem deployment of the CodeGen +example with OPEA comps to deploy using the TGI service. We will be showcasing how +to build an e2e CodeGen solution with the CodeLlama-7b-hf model, +deployed on Intel® Tiber™ AI Cloud (ITAC). To quickly learn about OPEA in just 5 minutes and set up the required hardware and software, please follow the instructions in the +[Getting Started](https://opea-project.github.io/latest/getting-started/README.html) section. If you do +not have an ITAC instance or the hardware is not supported in the ITAC yet, you can still run this on-prem. + +## Overview + +The CodeGen use case uses a single microservice called LLM. In this tutorial, we +will walk through the steps on how on enable it from OPEA GenAIComps to deploy on +a single node TGI megaservice solution. + +The solution is aimed to show how to use the CodeLlama-7b-hf model on the Intel® +Gaudi® AI Accelerator. We will go through how to setup docker containers to start +the microservice and megaservice. The solution will then take text input as the +prompt and generate code accordingly. It is deployed with a UI with 2 modes to +choose from: + +1. Svelte-Based UI +2. React-Based UI + +The React-based UI is optional, but this feature is supported in this example if you +are interested in using it. + +Below is the list of content we will be covering in this tutorial: + +1. Prerequisites +2. Prepare (Building / Pulling) Docker images +3. Use case setup +4. Deploy the use case +5. Interacting with CodeGen deployment + +## Prerequisites + +The first step is to clone the GenAIExamples and GenAIComps. GenAIComps are +fundamental necessary components used to build examples you find in +GenAIExamples and deploy them as microservices. + +```bash +git clone https://github.com/opea-project/GenAIComps.git +git clone https://github.com/opea-project/GenAIExamples.git +``` + +The examples utilize model weights from HuggingFace and langchain. + +Setup your [HuggingFace](https://huggingface.co/) account and generate +[user access token](https://huggingface.co/docs/transformers.js/en/guides/private#step-1-generating-a-user-access-token). + +Setup the HuggingFace token +``` +export HUGGINGFACEHUB_API_TOKEN="Your_Huggingface_API_Token" +``` + +Additionally, if you plan to use the default model CodeLlama-7b-hf, you will +need to [request access](https://huggingface.co/meta-llama/CodeLlama-7b-hf) from HuggingFace. + +The example requires you to set the `host_ip` to deploy the microservices on +endpoint enabled with ports. Set the host_ip env variable +``` +export host_ip=$(hostname -I | awk '{print $1}') +``` + +Make sure to setup Proxies if you are behind a firewall +``` +export no_proxy=${your_no_proxy},$host_ip +export http_proxy=${your_http_proxy} +export https_proxy=${your_http_proxy} +``` + +## Prepare (Building / Pulling) Docker images + +This step will involve building/pulling relevant docker +images with step-by-step process along with sanity check in the end. For +CodeGen, the following docker images will be needed: LLM with TGI. +Additionally, you will need to build docker images for the +CodeGen megaservice, and UI (React UI is optional). In total, +there are **3 required docker images** and an optional docker image. + +### Build/Pull Microservice image + +::::::{tab-set} + +:::::{tab-item} Pull +:sync: Pull + +If you decide to pull the docker containers and not build them locally, +you can proceed to the next step where all the necessary containers will +be pulled in from dockerhub. + +::::: +:::::{tab-item} Build +:sync: Build + +From within the `GenAIComps` folder, checkout the release tag. +``` +cd GenAIComps +git checkout tags/v1.1 +``` + +#### Build LLM Image + +```bash +docker build --no-cache -t opea/llm-tgi:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/text-generation/tgi/Dockerfile . +``` + +### Build Mega Service images + +The Megaservice is a pipeline that channels data through different +microservices, each performing varied tasks. The LLM microservice and +flow of data are defined in the `codegen.py` file. You can also add or +remove microservices and customize the megaservice to suit your needs. + +Build the megaservice image for this use case + +```bash +cd .. +cd GenAIExamples +git checkout tags/v1.1 +cd CodeGen +``` + +```bash +docker build --no-cache -t opea/codegen:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile . +cd ../.. +``` + +### Build the UI Image + +You can build 2 modes of UI + +*Svelte UI* + +```bash +cd GenAIExamples/CodeGen/ui/ +docker build --no-cache -t opea/codegen-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile . +cd ../../.. +``` + +*React UI (Optional)* +If you want a React-based frontend. + +```bash +cd GenAIExamples/CodeGen/ui/ +docker build --no-cache -t opea/codegen-react-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile.react . +cd ../../.. +``` + +### Sanity Check +Check if you have the following set of docker images by running the command `docker images` before moving on to the next step: + +* `opea/llm-tgi:latest` +* `opea/codegen:latest` +* `opea/codegen-ui:latest` +* `opea/codegen-react-ui:latest` (optional) + +::::: +:::::: + +## Use Case Setup + +The use case will use the following combination of GenAIComps and tools + +|Use Case Components | Tools | Model | Service Type | +|---------------- |--------------|-----------------------------|-------| +|LLM | TGI | meta-llama/CodeLlama-7b-hf | OPEA Microservice | +|UI | | NA | Gateway Service | + +Tools and models mentioned in the table are configurable either through the +environment variables or `compose.yaml` file. + +Set the necessary environment variables to setup the use case case by running the `set_env.sh` script. +Here is where the environment variable `LLM_MODEL_ID` is set, and you can change it to another model +by specifying the HuggingFace model card ID. + +```bash +cd GenAIExamples/CodeGen/docker_compose/ +source ./set_env.sh +cd ../../.. +``` + +## Deploy the Use Case + +In this tutorial, we will be deploying via docker compose with the provided +YAML file. The docker compose instructions should be starting all the +above mentioned services as containers. + +```bash +cd GenAIExamples/CodeGen/docker_compose/intel/hpu/gaudi +docker compose up -d +``` + + +### Checks to Ensure the Services are Running +#### Check Startup and Env Variables +Check the start up log by running `docker compose logs` to ensure there are no errors. +The warning messages print out the variables if they are **NOT** set. + +Here are some sample messages if proxy environment variables are not set: + + WARN[0000] The "no_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "https_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "http_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "no_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "https_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "http_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "no_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "http_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "https_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "no_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "http_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "https_proxy" variable is not set. Defaulting to a blank string. + +#### Check the Container Status + +Check if all the containers launched via docker compose has started. + +The CodeGen example starts 4 docker containers. Check that these docker +containers are all running, i.e, all the containers `STATUS` are `Up`. +You can do this with the `docker ps -a` command. + +``` +CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES +bbd235074c3d opea/codegen-ui:latest "docker-entrypoint.s…" About a minute ago Up About a minute 0.0.0.0:5173->5173/tcp, :::5173->5173/tcp codegen-gaudi-ui-server +8d3872ca66fa opea/codegen:latest "python codegen.py" About a minute ago Up About a minute 0.0.0.0:7778->7778/tcp, :::7778->7778/tcp codegen-gaudi-backend-server +b9fc39f51cdb opea/llm-tgi:latest "bash entrypoint.sh" About a minute ago Up About a minute 0.0.0.0:9000->9000/tcp, :::9000->9000/tcp llm-tgi-gaudi-server +39994e007f15 ghcr.io/huggingface/tgi-gaudi:2.0.1 "text-generation-lau…" About a minute ago Up About a minute 0.0.0.0:8028->80/tcp, :::8028->80/tcp tgi-gaudi-server +``` + +## Interacting with CodeGen for Deployment + +This section will walk you through the different ways to interact with +the microservices deployed. After a couple minutes, rerun `docker ps -a` +to ensure all the docker containers are still up and running. Then proceed +to validate each microservice and megaservice. + +### TGI Service + +```bash +curl http://${host_ip}:8028/generate \ + -X POST \ + -d '{"inputs":"Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception.","parameters":{"max_new_tokens":256, "do_sample": true}}' \ + -H 'Content-Type: application/json' +``` + +Here is the output: + +``` +{"generated_text":"\n\nIO iflow diagram:\n\n![IO flow diagram(s)](TodoList.iflow.svg)\n\n### TDD Kata walkthrough\n\n1. Start with a user story. We will add story tests later. In this case, we'll choose a story about adding a TODO:\n ```ruby\n as a user,\n i want to add a todo,\n so that i can get a todo list.\n\n conformance:\n - a new todo is added to the list\n - if the todo text is empty, raise an exception\n ```\n\n1. Write the first test:\n ```ruby\n feature Testing the addition of a todo to the list\n\n given a todo list empty list\n when a user adds a todo\n the todo should be added to the list\n\n inputs:\n when_values: [[\"A\"]]\n\n output validations:\n - todo_list contains { text:\"A\" }\n ```\n\n1. Write the first step implementation in any programming language you like. In this case, we will choose Ruby:\n ```ruby\n def add_"} +``` + +### LLM Microservice + +```bash +curl http://${host_ip}:9000/v1/chat/completions\ + -X POST \ + -d '{"query":"Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception.","max_tokens":256,"top_k":10,"top_p":0.95,"typical_p":0.95,"temperature":0.01,"repetition_penalty":1.03,"streaming":true}' \ + -H 'Content-Type: application/json' +``` + +The output is given one character at a time. It is too long to show +here but the last item will be +``` +data: [DONE] +``` + +### MegaService + +```bash +curl http://${host_ip}:7778/v1/codegen -H "Content-Type: application/json" -d '{ + "messages": "Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception." + }' +``` + +The output is given one character at a time. It is too long to show +here but the last item will be +``` +data: [DONE] +``` + +## Launch UI +### Svelte UI +To access the frontend, open the following URL in your browser: http://{host_ip}:5173. By default, the UI runs on port 5173 internally. If you prefer to use a different host port to access the frontend, you can modify the port mapping in the `compose.yaml` file as shown below: +```bash + codegen-gaudi-ui-server: + image: ${REGISTRY:-opea}/codegen-ui:${TAG:-latest} + ... + ports: + - "5173:5173" +``` + +### React-Based UI (Optional) +To access the React-based frontend, modify the UI service in the `compose.yaml` file. Replace `codegen-gaudi-ui-server` service with the codegen-gaudi-react-ui-server service as per the config below: +```bash +codegen-gaudi-react-ui-server: + image: ${REGISTRY:-opea}/codegen-react-ui:${TAG:-latest} + container_name: codegen-gaudi-react-ui-server + environment: + - no_proxy=${no_proxy} + - https_proxy=${https_proxy} + - http_proxy=${http_proxy} + - APP_CODE_GEN_URL=${BACKEND_SERVICE_ENDPOINT} + depends_on: + - codegen-gaudi-backend-server + ports: + - "5174:80" + ipc: host + restart: always +``` +Once the services are up, open the following URL in your browser: http://{host_ip}:5174. By default, the UI runs on port 80 internally. If you prefer to use a different host port to access the frontend, you can modify the port mapping in the `compose.yaml` file as shown below: +```bash + codegen-gaudi-react-ui-server: + image: ${REGISTRY:-opea}/codegen-react-ui:${TAG:-latest} + ... + ports: + - "80:80" +``` + +## Check Docker Container Logs + +You can check the log of a container by running this command: + +```bash +docker logs -t +``` + +You can also check the overall logs with the following command, where the +`compose.yaml` is the megaservice docker-compose configuration file. + +Assumming you are still in this directory `GenAIExamples/CodeGen/docker_compose/intel/hpu/gaudi`, +run the following command to check the logs: +```bash +docker compose -f compose.yaml logs +``` + +View the docker input parameters in `./CodeGen/docker_compose/intel/hpu/gaudi/compose.yaml` + +```yaml + tgi-service: + image: ghcr.io/huggingface/tgi-gaudi:2.0.1 + container_name: tgi-gaudi-server + ports: + - "8028:80" + volumes: + - "./data:/data" + environment: + no_proxy: ${no_proxy} + http_proxy: ${http_proxy} + https_proxy: ${https_proxy} + HABANA_VISIBLE_DEVICES: all + OMPI_MCA_btl_vader_single_copy_mechanism: none + HF_TOKEN: ${HUGGINGFACEHUB_API_TOKEN} + runtime: habana + cap_add: + - SYS_NICE + ipc: host + command: --model-id ${LLM_MODEL_ID} --max-input-length 1024 --max-total-tokens 2048 +``` + +The input `--model-id` is `${LLM_MODEL_ID}`. Ensure the environment variable `LLM_MODEL_ID` +is set correctly. Check spelling. Whenever this is changed, restart the containers to use +the newly selected model. + + +## Stop the services + +Once you are done with the entire pipeline and wish to stop and remove all the containers, use the command below: +``` +docker compose down +``` From 77e2e9844cebd6494054772b6afc59e2f009a028 Mon Sep 17 00:00:00 2001 From: alexsin368 Date: Tue, 12 Nov 2024 16:17:53 -0800 Subject: [PATCH 20/34] Revert "CodeGen: add gaudi deployment sample guide" This reverts commit e3790579d5f2944b58b9d1065757a0a76a6d1ec9. Signed-off-by: alexsin368 --- examples/CodeGen/deploy/gaudi.md | 372 ------------------------------- 1 file changed, 372 deletions(-) delete mode 100644 examples/CodeGen/deploy/gaudi.md diff --git a/examples/CodeGen/deploy/gaudi.md b/examples/CodeGen/deploy/gaudi.md deleted file mode 100644 index 9ad3971d..00000000 --- a/examples/CodeGen/deploy/gaudi.md +++ /dev/null @@ -1,372 +0,0 @@ -# Single node on-prem deployment with vLLM or TGI on Gaudi AI Accelerator - -This deployment section covers single-node on-prem deployment of the CodeGen -example with OPEA comps to deploy using the TGI service. We will be showcasing how -to build an e2e CodeGen solution with the CodeLlama-7b-hf model, -deployed on Intel® Tiber™ AI Cloud (ITAC). To quickly learn about OPEA in just 5 minutes and set up the required hardware and software, please follow the instructions in the -[Getting Started](https://opea-project.github.io/latest/getting-started/README.html) section. If you do -not have an ITAC instance or the hardware is not supported in the ITAC yet, you can still run this on-prem. - -## Overview - -The CodeGen use case uses a single microservice called LLM. In this tutorial, we -will walk through the steps on how on enable it from OPEA GenAIComps to deploy on -a single node TGI megaservice solution. - -The solution is aimed to show how to use the CodeLlama-7b-hf model on the Intel® -Gaudi® AI Accelerator. We will go through how to setup docker containers to start -the microservice and megaservice. The solution will then take text input as the -prompt and generate code accordingly. It is deployed with a UI with 2 modes to -choose from: - -1. Svelte-Based UI -2. React-Based UI - -The React-based UI is optional, but this feature is supported in this example if you -are interested in using it. - -Below is the list of content we will be covering in this tutorial: - -1. Prerequisites -2. Prepare (Building / Pulling) Docker images -3. Use case setup -4. Deploy the use case -5. Interacting with CodeGen deployment - -## Prerequisites - -The first step is to clone the GenAIExamples and GenAIComps. GenAIComps are -fundamental necessary components used to build examples you find in -GenAIExamples and deploy them as microservices. - -```bash -git clone https://github.com/opea-project/GenAIComps.git -git clone https://github.com/opea-project/GenAIExamples.git -``` - -The examples utilize model weights from HuggingFace and langchain. - -Setup your [HuggingFace](https://huggingface.co/) account and generate -[user access token](https://huggingface.co/docs/transformers.js/en/guides/private#step-1-generating-a-user-access-token). - -Setup the HuggingFace token -``` -export HUGGINGFACEHUB_API_TOKEN="Your_Huggingface_API_Token" -``` - -Additionally, if you plan to use the default model CodeLlama-7b-hf, you will -need to [request access](https://huggingface.co/meta-llama/CodeLlama-7b-hf) from HuggingFace. - -The example requires you to set the `host_ip` to deploy the microservices on -endpoint enabled with ports. Set the host_ip env variable -``` -export host_ip=$(hostname -I | awk '{print $1}') -``` - -Make sure to setup Proxies if you are behind a firewall -``` -export no_proxy=${your_no_proxy},$host_ip -export http_proxy=${your_http_proxy} -export https_proxy=${your_http_proxy} -``` - -## Prepare (Building / Pulling) Docker images - -This step will involve building/pulling relevant docker -images with step-by-step process along with sanity check in the end. For -CodeGen, the following docker images will be needed: LLM with TGI. -Additionally, you will need to build docker images for the -CodeGen megaservice, and UI (React UI is optional). In total, -there are **3 required docker images** and an optional docker image. - -### Build/Pull Microservice image - -::::::{tab-set} - -:::::{tab-item} Pull -:sync: Pull - -If you decide to pull the docker containers and not build them locally, -you can proceed to the next step where all the necessary containers will -be pulled in from dockerhub. - -::::: -:::::{tab-item} Build -:sync: Build - -From within the `GenAIComps` folder, checkout the release tag. -``` -cd GenAIComps -git checkout tags/v1.1 -``` - -#### Build LLM Image - -```bash -docker build --no-cache -t opea/llm-tgi:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/text-generation/tgi/Dockerfile . -``` - -### Build Mega Service images - -The Megaservice is a pipeline that channels data through different -microservices, each performing varied tasks. The LLM microservice and -flow of data are defined in the `codegen.py` file. You can also add or -remove microservices and customize the megaservice to suit your needs. - -Build the megaservice image for this use case - -```bash -cd .. -cd GenAIExamples -git checkout tags/v1.1 -cd CodeGen -``` - -```bash -docker build --no-cache -t opea/codegen:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile . -cd ../.. -``` - -### Build the UI Image - -You can build 2 modes of UI - -*Svelte UI* - -```bash -cd GenAIExamples/CodeGen/ui/ -docker build --no-cache -t opea/codegen-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile . -cd ../../.. -``` - -*React UI (Optional)* -If you want a React-based frontend. - -```bash -cd GenAIExamples/CodeGen/ui/ -docker build --no-cache -t opea/codegen-react-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile.react . -cd ../../.. -``` - -### Sanity Check -Check if you have the following set of docker images by running the command `docker images` before moving on to the next step: - -* `opea/llm-tgi:latest` -* `opea/codegen:latest` -* `opea/codegen-ui:latest` -* `opea/codegen-react-ui:latest` (optional) - -::::: -:::::: - -## Use Case Setup - -The use case will use the following combination of GenAIComps and tools - -|Use Case Components | Tools | Model | Service Type | -|---------------- |--------------|-----------------------------|-------| -|LLM | TGI | meta-llama/CodeLlama-7b-hf | OPEA Microservice | -|UI | | NA | Gateway Service | - -Tools and models mentioned in the table are configurable either through the -environment variables or `compose.yaml` file. - -Set the necessary environment variables to setup the use case case by running the `set_env.sh` script. -Here is where the environment variable `LLM_MODEL_ID` is set, and you can change it to another model -by specifying the HuggingFace model card ID. - -```bash -cd GenAIExamples/CodeGen/docker_compose/ -source ./set_env.sh -cd ../../.. -``` - -## Deploy the Use Case - -In this tutorial, we will be deploying via docker compose with the provided -YAML file. The docker compose instructions should be starting all the -above mentioned services as containers. - -```bash -cd GenAIExamples/CodeGen/docker_compose/intel/hpu/gaudi -docker compose up -d -``` - - -### Checks to Ensure the Services are Running -#### Check Startup and Env Variables -Check the start up log by running `docker compose logs` to ensure there are no errors. -The warning messages print out the variables if they are **NOT** set. - -Here are some sample messages if proxy environment variables are not set: - - WARN[0000] The "no_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "https_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "http_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "no_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "https_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "http_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "no_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "http_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "https_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "no_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "http_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "https_proxy" variable is not set. Defaulting to a blank string. - -#### Check the Container Status - -Check if all the containers launched via docker compose has started. - -The CodeGen example starts 4 docker containers. Check that these docker -containers are all running, i.e, all the containers `STATUS` are `Up`. -You can do this with the `docker ps -a` command. - -``` -CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES -bbd235074c3d opea/codegen-ui:latest "docker-entrypoint.s…" About a minute ago Up About a minute 0.0.0.0:5173->5173/tcp, :::5173->5173/tcp codegen-gaudi-ui-server -8d3872ca66fa opea/codegen:latest "python codegen.py" About a minute ago Up About a minute 0.0.0.0:7778->7778/tcp, :::7778->7778/tcp codegen-gaudi-backend-server -b9fc39f51cdb opea/llm-tgi:latest "bash entrypoint.sh" About a minute ago Up About a minute 0.0.0.0:9000->9000/tcp, :::9000->9000/tcp llm-tgi-gaudi-server -39994e007f15 ghcr.io/huggingface/tgi-gaudi:2.0.1 "text-generation-lau…" About a minute ago Up About a minute 0.0.0.0:8028->80/tcp, :::8028->80/tcp tgi-gaudi-server -``` - -## Interacting with CodeGen for Deployment - -This section will walk you through the different ways to interact with -the microservices deployed. After a couple minutes, rerun `docker ps -a` -to ensure all the docker containers are still up and running. Then proceed -to validate each microservice and megaservice. - -### TGI Service - -```bash -curl http://${host_ip}:8028/generate \ - -X POST \ - -d '{"inputs":"Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception.","parameters":{"max_new_tokens":256, "do_sample": true}}' \ - -H 'Content-Type: application/json' -``` - -Here is the output: - -``` -{"generated_text":"\n\nIO iflow diagram:\n\n![IO flow diagram(s)](TodoList.iflow.svg)\n\n### TDD Kata walkthrough\n\n1. Start with a user story. We will add story tests later. In this case, we'll choose a story about adding a TODO:\n ```ruby\n as a user,\n i want to add a todo,\n so that i can get a todo list.\n\n conformance:\n - a new todo is added to the list\n - if the todo text is empty, raise an exception\n ```\n\n1. Write the first test:\n ```ruby\n feature Testing the addition of a todo to the list\n\n given a todo list empty list\n when a user adds a todo\n the todo should be added to the list\n\n inputs:\n when_values: [[\"A\"]]\n\n output validations:\n - todo_list contains { text:\"A\" }\n ```\n\n1. Write the first step implementation in any programming language you like. In this case, we will choose Ruby:\n ```ruby\n def add_"} -``` - -### LLM Microservice - -```bash -curl http://${host_ip}:9000/v1/chat/completions\ - -X POST \ - -d '{"query":"Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception.","max_tokens":256,"top_k":10,"top_p":0.95,"typical_p":0.95,"temperature":0.01,"repetition_penalty":1.03,"streaming":true}' \ - -H 'Content-Type: application/json' -``` - -The output is given one character at a time. It is too long to show -here but the last item will be -``` -data: [DONE] -``` - -### MegaService - -```bash -curl http://${host_ip}:7778/v1/codegen -H "Content-Type: application/json" -d '{ - "messages": "Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception." - }' -``` - -The output is given one character at a time. It is too long to show -here but the last item will be -``` -data: [DONE] -``` - -## Launch UI -### Svelte UI -To access the frontend, open the following URL in your browser: http://{host_ip}:5173. By default, the UI runs on port 5173 internally. If you prefer to use a different host port to access the frontend, you can modify the port mapping in the `compose.yaml` file as shown below: -```bash - codegen-gaudi-ui-server: - image: ${REGISTRY:-opea}/codegen-ui:${TAG:-latest} - ... - ports: - - "5173:5173" -``` - -### React-Based UI (Optional) -To access the React-based frontend, modify the UI service in the `compose.yaml` file. Replace `codegen-gaudi-ui-server` service with the codegen-gaudi-react-ui-server service as per the config below: -```bash -codegen-gaudi-react-ui-server: - image: ${REGISTRY:-opea}/codegen-react-ui:${TAG:-latest} - container_name: codegen-gaudi-react-ui-server - environment: - - no_proxy=${no_proxy} - - https_proxy=${https_proxy} - - http_proxy=${http_proxy} - - APP_CODE_GEN_URL=${BACKEND_SERVICE_ENDPOINT} - depends_on: - - codegen-gaudi-backend-server - ports: - - "5174:80" - ipc: host - restart: always -``` -Once the services are up, open the following URL in your browser: http://{host_ip}:5174. By default, the UI runs on port 80 internally. If you prefer to use a different host port to access the frontend, you can modify the port mapping in the `compose.yaml` file as shown below: -```bash - codegen-gaudi-react-ui-server: - image: ${REGISTRY:-opea}/codegen-react-ui:${TAG:-latest} - ... - ports: - - "80:80" -``` - -## Check Docker Container Logs - -You can check the log of a container by running this command: - -```bash -docker logs -t -``` - -You can also check the overall logs with the following command, where the -`compose.yaml` is the megaservice docker-compose configuration file. - -Assumming you are still in this directory `GenAIExamples/CodeGen/docker_compose/intel/hpu/gaudi`, -run the following command to check the logs: -```bash -docker compose -f compose.yaml logs -``` - -View the docker input parameters in `./CodeGen/docker_compose/intel/hpu/gaudi/compose.yaml` - -```yaml - tgi-service: - image: ghcr.io/huggingface/tgi-gaudi:2.0.1 - container_name: tgi-gaudi-server - ports: - - "8028:80" - volumes: - - "./data:/data" - environment: - no_proxy: ${no_proxy} - http_proxy: ${http_proxy} - https_proxy: ${https_proxy} - HABANA_VISIBLE_DEVICES: all - OMPI_MCA_btl_vader_single_copy_mechanism: none - HF_TOKEN: ${HUGGINGFACEHUB_API_TOKEN} - runtime: habana - cap_add: - - SYS_NICE - ipc: host - command: --model-id ${LLM_MODEL_ID} --max-input-length 1024 --max-total-tokens 2048 -``` - -The input `--model-id` is `${LLM_MODEL_ID}`. Ensure the environment variable `LLM_MODEL_ID` -is set correctly. Check spelling. Whenever this is changed, restart the containers to use -the newly selected model. - - -## Stop the services - -Once you are done with the entire pipeline and wish to stop and remove all the containers, use the command below: -``` -docker compose down -``` From eb970012bd022c3e25e0f162e94c51adece548aa Mon Sep 17 00:00:00 2001 From: alexsin368 Date: Thu, 14 Nov 2024 13:27:00 -0800 Subject: [PATCH 21/34] signing off latest commit Signed-off-by: alexsin368 --- examples/ChatQnA/deploy/gaudi.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/ChatQnA/deploy/gaudi.md b/examples/ChatQnA/deploy/gaudi.md index 09aa30a8..f11fa2f4 100644 --- a/examples/ChatQnA/deploy/gaudi.md +++ b/examples/ChatQnA/deploy/gaudi.md @@ -957,4 +957,4 @@ docker compose -f compose_vllm.yaml down docker compose -f compose.yaml down ``` ::: -:::: +:::: \ No newline at end of file From ffea6ff40e89acdd4419ffc1558e8c9f029f6477 Mon Sep 17 00:00:00 2001 From: Neo Zhang Jianyu Date: Mon, 11 Nov 2024 09:58:34 +0800 Subject: [PATCH 22/34] support copy all image to html folder (#247) Signed-off-by: ZhangJianyu Signed-off-by: alexsin368 --- conf.py | 24 ++++++++++++++++++++++++ 1 file changed, 24 insertions(+) diff --git a/conf.py b/conf.py index 40e46375..35051272 100644 --- a/conf.py +++ b/conf.py @@ -4,6 +4,9 @@ import os import sys from datetime import datetime +import glob +import shutil + sys.path.insert(0, os.path.abspath('.')) @@ -131,10 +134,31 @@ # paths that contain custom static files (such as style sheets) html_static_path = ['sphinx/_static'] +def copy_images(src ,dst): + image_types = ["png", "svg"] + for image_type in image_types: + pattern = "{}/**/*.{}".format(src, image_type) + files = glob.glob(pattern, recursive = True) + for file in files: + sub_name = file.replace(src, '') + dst_filename = "{}{}".format(dst, sub_name) + folder = os.path.dirname(dst_filename) + if not os.path.exists(folder): + os.makedirs(folder) + shutil.copy(file, dst_filename) + +def copy_image_to_html(app, docname): + if app.builder.name == 'html': + if os.path.exists(app.srcdir) and os.path.exists(app.outdir): + copy_images(str(app.srcdir) ,str(app.outdir)) + else: + print("No existed {} or {}".format(app.srcdir ,app.outdir)) + def setup(app): app.add_css_file("opea-custom.css") app.add_js_file("opea-custom.js") + app.connect('build-finished', copy_image_to_html) # Disable "Created using Sphinx" in the HTML footer. Default is True. html_show_sphinx = False From 0eb826ff4a6060baf61ebbc61d72738bf4e6c625 Mon Sep 17 00:00:00 2001 From: Ying Hu Date: Wed, 13 Nov 2024 10:07:04 +0800 Subject: [PATCH 23/34] Update opea-custom.js to fix235 fix #235 the link to main page Signed-off-by: alexsin368 --- sphinx/_static/opea-custom.js | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/sphinx/_static/opea-custom.js b/sphinx/_static/opea-custom.js index ac0f4453..cb2d0221 100644 --- a/sphinx/_static/opea-custom.js +++ b/sphinx/_static/opea-custom.js @@ -2,7 +2,7 @@ $(document).ready(function(){ /* tweak logo link to the marketing site instead of doc site */ - $( ".icon-home" ).attr({href: "https://opea.dev/", target: "_blank"}); + $( ".icon-home" ).attr({href: "https://opea-project.github.io/latest/index.html", target: "_blank"}); /* open external links in a new tab */ $('a[class*=external]').attr({target: '_blank', rel: 'noopener'}); From c54860a9c4ebd5aa7cf07e8ad404a09acc35f9f9 Mon Sep 17 00:00:00 2001 From: Abdul Arif Date: Thu, 14 Nov 2024 10:43:34 +0800 Subject: [PATCH 24/34] reformat agentQnA sample guide (#219) Signed-off-by: abdulari Co-authored-by: Ying Hu Signed-off-by: alexsin368 --- examples/AgentQnA/AgentQnA_Guide.rst | 47 ++++++++++++++++++++++++++++ examples/AgentQnA/deploy/index.rst | 14 +++++++++ examples/AgentQnA/deploy/xeon.md | 37 ++++++++++++++++++++++ examples/index.rst | 2 ++ 4 files changed, 100 insertions(+) create mode 100644 examples/AgentQnA/AgentQnA_Guide.rst create mode 100644 examples/AgentQnA/deploy/index.rst create mode 100644 examples/AgentQnA/deploy/xeon.md diff --git a/examples/AgentQnA/AgentQnA_Guide.rst b/examples/AgentQnA/AgentQnA_Guide.rst new file mode 100644 index 00000000..c8424071 --- /dev/null +++ b/examples/AgentQnA/AgentQnA_Guide.rst @@ -0,0 +1,47 @@ +.. _AgentQnA_Guide: + +AgentQnA Sample Guide +##################### + +.. note:: This guide is in its early development and is a work-in-progress with + placeholder content. + +Overview +******** + +This example showcases a hierarchical multi-agent system for question-answering applications. + +Purpose +******* +* Improve relevancy of retrieved context. Agent can rephrase user queries, decompose user queries, and iterate to get the most relevant context for answering user’s questions. Compared to conventional RAG, RAG agent can significantly improve the correctness and relevancy of the answer. +* Use tools to get additional knowledge. For example, knowledge graphs and SQL databases can be exposed as APIs for Agents to gather knowledge that may be missing in the retrieval vector database. +* Hierarchical agent can further improve performance. Expert worker agents, such as retrieval agent, knowledge graph agent, SQL agent, etc., can provide high-quality output for different aspects of a complex query, and the supervisor agent can aggregate the information together to provide a comprehensive answer. + +How It Works +************ + +The supervisor agent interfaces with the user and dispatch tasks to the worker agent and other tools to gather information and come up with answers. +The worker agent uses the retrieval tool to generate answers to the queries posted by the supervisor agent. + + +.. mermaid:: + + graph LR; + U[User]-->SA[Supervisor Agent]; + SA-->WA[Worker Agent]; + WA-->RT[Retrieval Tool]; + SA-->T1[Tool 1]; + SA-->T2[Tool 2]; + SA-->TN[Tool N]; + SA-->U; + WA-->SA; + RT-->WA; + T1-->SA; + T2-->SA; + TN-->SA; + + +Deployment +********** + +See the :ref:`agentqna-example-deployment`. \ No newline at end of file diff --git a/examples/AgentQnA/deploy/index.rst b/examples/AgentQnA/deploy/index.rst new file mode 100644 index 00000000..629d84ae --- /dev/null +++ b/examples/AgentQnA/deploy/index.rst @@ -0,0 +1,14 @@ +.. _agentqna-example-deployment: + +AgentQnA Example Deployment Options +################################### + +Here are some deployment options, depending on your hardware and environment: + +Single Node +*********** + +.. toctree:: + :maxdepth: 1 + + Xeon Scalable Processor \ No newline at end of file diff --git a/examples/AgentQnA/deploy/xeon.md b/examples/AgentQnA/deploy/xeon.md new file mode 100644 index 00000000..d1d66573 --- /dev/null +++ b/examples/AgentQnA/deploy/xeon.md @@ -0,0 +1,37 @@ +# Single node on-prem deployment with Docker Compose on Xeon Scalable processors + +1. [Optional] Build `Agent` docker image + +``` +git clone https://github.com/opea-project/GenAIComps.git +cd GenAIComps +docker build -t opea/agent-langchain:latest -f comps/agent/langchain/Dockerfile . +``` + +2. Launch Tool service + +In this example, we will use some of the mock APIs provided in the Meta CRAG KDD Challenge to demonstrate the benefits of gaining additional context from mock knowledge graphs. + +``` +docker run -d -p=8080:8000 docker.io/aicrowd/kdd-cup-24-crag-mock-api:v0 +``` + +3. clone repo +``` +export WORKDIR=$(pwd) +git clone https://github.com/opea-project/GenAIExamples.git + +export TOOLSET_PATH=$WORKDIR/GenAIExamples/AgentQnA/tools/ + +# optional: OPANAI_API_KEY +export OPENAI_API_KEY= +``` + +4. launch `Agent` service + +The configurations of the supervisor agent and the worker agent are defined in the docker-compose yaml file. We currently use openAI GPT-4o-mini as LLM, and we plan to add support for llama3.1-70B-instruct (served by TGI-Gaudi) in a subsequent release. To use openai llm, run command below. + +``` +cd $WORKDIR/GenAIExamples/AgentQnA/docker_compose/intel/cpu/xeon +bash launch_agent_service_openai.sh +``` \ No newline at end of file diff --git a/examples/index.rst b/examples/index.rst index 09509a1e..6524dc1d 100644 --- a/examples/index.rst +++ b/examples/index.rst @@ -10,6 +10,8 @@ GenAIExamples are designed to give developers an easy entry into generative AI, ChatQnA/ChatQnA_Guide ChatQnA/deploy/index + AgentQnA/AgentQnA_Guide + AgentQnA/deploy/index ---- From 3bab1dad9e84d6909a1f2afd0f8755ba6e087f0f Mon Sep 17 00:00:00 2001 From: alexsin368 Date: Fri, 8 Nov 2024 17:56:04 -0800 Subject: [PATCH 25/34] CodeGen: add gaudi deployment sample guide Signed-off-by: alexsin368 --- examples/CodeGen/deploy/gaudi.md | 372 +++++++++++++++++++++++++++++++ 1 file changed, 372 insertions(+) create mode 100644 examples/CodeGen/deploy/gaudi.md diff --git a/examples/CodeGen/deploy/gaudi.md b/examples/CodeGen/deploy/gaudi.md new file mode 100644 index 00000000..9ad3971d --- /dev/null +++ b/examples/CodeGen/deploy/gaudi.md @@ -0,0 +1,372 @@ +# Single node on-prem deployment with vLLM or TGI on Gaudi AI Accelerator + +This deployment section covers single-node on-prem deployment of the CodeGen +example with OPEA comps to deploy using the TGI service. We will be showcasing how +to build an e2e CodeGen solution with the CodeLlama-7b-hf model, +deployed on Intel® Tiber™ AI Cloud (ITAC). To quickly learn about OPEA in just 5 minutes and set up the required hardware and software, please follow the instructions in the +[Getting Started](https://opea-project.github.io/latest/getting-started/README.html) section. If you do +not have an ITAC instance or the hardware is not supported in the ITAC yet, you can still run this on-prem. + +## Overview + +The CodeGen use case uses a single microservice called LLM. In this tutorial, we +will walk through the steps on how on enable it from OPEA GenAIComps to deploy on +a single node TGI megaservice solution. + +The solution is aimed to show how to use the CodeLlama-7b-hf model on the Intel® +Gaudi® AI Accelerator. We will go through how to setup docker containers to start +the microservice and megaservice. The solution will then take text input as the +prompt and generate code accordingly. It is deployed with a UI with 2 modes to +choose from: + +1. Svelte-Based UI +2. React-Based UI + +The React-based UI is optional, but this feature is supported in this example if you +are interested in using it. + +Below is the list of content we will be covering in this tutorial: + +1. Prerequisites +2. Prepare (Building / Pulling) Docker images +3. Use case setup +4. Deploy the use case +5. Interacting with CodeGen deployment + +## Prerequisites + +The first step is to clone the GenAIExamples and GenAIComps. GenAIComps are +fundamental necessary components used to build examples you find in +GenAIExamples and deploy them as microservices. + +```bash +git clone https://github.com/opea-project/GenAIComps.git +git clone https://github.com/opea-project/GenAIExamples.git +``` + +The examples utilize model weights from HuggingFace and langchain. + +Setup your [HuggingFace](https://huggingface.co/) account and generate +[user access token](https://huggingface.co/docs/transformers.js/en/guides/private#step-1-generating-a-user-access-token). + +Setup the HuggingFace token +``` +export HUGGINGFACEHUB_API_TOKEN="Your_Huggingface_API_Token" +``` + +Additionally, if you plan to use the default model CodeLlama-7b-hf, you will +need to [request access](https://huggingface.co/meta-llama/CodeLlama-7b-hf) from HuggingFace. + +The example requires you to set the `host_ip` to deploy the microservices on +endpoint enabled with ports. Set the host_ip env variable +``` +export host_ip=$(hostname -I | awk '{print $1}') +``` + +Make sure to setup Proxies if you are behind a firewall +``` +export no_proxy=${your_no_proxy},$host_ip +export http_proxy=${your_http_proxy} +export https_proxy=${your_http_proxy} +``` + +## Prepare (Building / Pulling) Docker images + +This step will involve building/pulling relevant docker +images with step-by-step process along with sanity check in the end. For +CodeGen, the following docker images will be needed: LLM with TGI. +Additionally, you will need to build docker images for the +CodeGen megaservice, and UI (React UI is optional). In total, +there are **3 required docker images** and an optional docker image. + +### Build/Pull Microservice image + +::::::{tab-set} + +:::::{tab-item} Pull +:sync: Pull + +If you decide to pull the docker containers and not build them locally, +you can proceed to the next step where all the necessary containers will +be pulled in from dockerhub. + +::::: +:::::{tab-item} Build +:sync: Build + +From within the `GenAIComps` folder, checkout the release tag. +``` +cd GenAIComps +git checkout tags/v1.1 +``` + +#### Build LLM Image + +```bash +docker build --no-cache -t opea/llm-tgi:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/text-generation/tgi/Dockerfile . +``` + +### Build Mega Service images + +The Megaservice is a pipeline that channels data through different +microservices, each performing varied tasks. The LLM microservice and +flow of data are defined in the `codegen.py` file. You can also add or +remove microservices and customize the megaservice to suit your needs. + +Build the megaservice image for this use case + +```bash +cd .. +cd GenAIExamples +git checkout tags/v1.1 +cd CodeGen +``` + +```bash +docker build --no-cache -t opea/codegen:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile . +cd ../.. +``` + +### Build the UI Image + +You can build 2 modes of UI + +*Svelte UI* + +```bash +cd GenAIExamples/CodeGen/ui/ +docker build --no-cache -t opea/codegen-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile . +cd ../../.. +``` + +*React UI (Optional)* +If you want a React-based frontend. + +```bash +cd GenAIExamples/CodeGen/ui/ +docker build --no-cache -t opea/codegen-react-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile.react . +cd ../../.. +``` + +### Sanity Check +Check if you have the following set of docker images by running the command `docker images` before moving on to the next step: + +* `opea/llm-tgi:latest` +* `opea/codegen:latest` +* `opea/codegen-ui:latest` +* `opea/codegen-react-ui:latest` (optional) + +::::: +:::::: + +## Use Case Setup + +The use case will use the following combination of GenAIComps and tools + +|Use Case Components | Tools | Model | Service Type | +|---------------- |--------------|-----------------------------|-------| +|LLM | TGI | meta-llama/CodeLlama-7b-hf | OPEA Microservice | +|UI | | NA | Gateway Service | + +Tools and models mentioned in the table are configurable either through the +environment variables or `compose.yaml` file. + +Set the necessary environment variables to setup the use case case by running the `set_env.sh` script. +Here is where the environment variable `LLM_MODEL_ID` is set, and you can change it to another model +by specifying the HuggingFace model card ID. + +```bash +cd GenAIExamples/CodeGen/docker_compose/ +source ./set_env.sh +cd ../../.. +``` + +## Deploy the Use Case + +In this tutorial, we will be deploying via docker compose with the provided +YAML file. The docker compose instructions should be starting all the +above mentioned services as containers. + +```bash +cd GenAIExamples/CodeGen/docker_compose/intel/hpu/gaudi +docker compose up -d +``` + + +### Checks to Ensure the Services are Running +#### Check Startup and Env Variables +Check the start up log by running `docker compose logs` to ensure there are no errors. +The warning messages print out the variables if they are **NOT** set. + +Here are some sample messages if proxy environment variables are not set: + + WARN[0000] The "no_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "https_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "http_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "no_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "https_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "http_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "no_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "http_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "https_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "no_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "http_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "https_proxy" variable is not set. Defaulting to a blank string. + +#### Check the Container Status + +Check if all the containers launched via docker compose has started. + +The CodeGen example starts 4 docker containers. Check that these docker +containers are all running, i.e, all the containers `STATUS` are `Up`. +You can do this with the `docker ps -a` command. + +``` +CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES +bbd235074c3d opea/codegen-ui:latest "docker-entrypoint.s…" About a minute ago Up About a minute 0.0.0.0:5173->5173/tcp, :::5173->5173/tcp codegen-gaudi-ui-server +8d3872ca66fa opea/codegen:latest "python codegen.py" About a minute ago Up About a minute 0.0.0.0:7778->7778/tcp, :::7778->7778/tcp codegen-gaudi-backend-server +b9fc39f51cdb opea/llm-tgi:latest "bash entrypoint.sh" About a minute ago Up About a minute 0.0.0.0:9000->9000/tcp, :::9000->9000/tcp llm-tgi-gaudi-server +39994e007f15 ghcr.io/huggingface/tgi-gaudi:2.0.1 "text-generation-lau…" About a minute ago Up About a minute 0.0.0.0:8028->80/tcp, :::8028->80/tcp tgi-gaudi-server +``` + +## Interacting with CodeGen for Deployment + +This section will walk you through the different ways to interact with +the microservices deployed. After a couple minutes, rerun `docker ps -a` +to ensure all the docker containers are still up and running. Then proceed +to validate each microservice and megaservice. + +### TGI Service + +```bash +curl http://${host_ip}:8028/generate \ + -X POST \ + -d '{"inputs":"Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception.","parameters":{"max_new_tokens":256, "do_sample": true}}' \ + -H 'Content-Type: application/json' +``` + +Here is the output: + +``` +{"generated_text":"\n\nIO iflow diagram:\n\n![IO flow diagram(s)](TodoList.iflow.svg)\n\n### TDD Kata walkthrough\n\n1. Start with a user story. We will add story tests later. In this case, we'll choose a story about adding a TODO:\n ```ruby\n as a user,\n i want to add a todo,\n so that i can get a todo list.\n\n conformance:\n - a new todo is added to the list\n - if the todo text is empty, raise an exception\n ```\n\n1. Write the first test:\n ```ruby\n feature Testing the addition of a todo to the list\n\n given a todo list empty list\n when a user adds a todo\n the todo should be added to the list\n\n inputs:\n when_values: [[\"A\"]]\n\n output validations:\n - todo_list contains { text:\"A\" }\n ```\n\n1. Write the first step implementation in any programming language you like. In this case, we will choose Ruby:\n ```ruby\n def add_"} +``` + +### LLM Microservice + +```bash +curl http://${host_ip}:9000/v1/chat/completions\ + -X POST \ + -d '{"query":"Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception.","max_tokens":256,"top_k":10,"top_p":0.95,"typical_p":0.95,"temperature":0.01,"repetition_penalty":1.03,"streaming":true}' \ + -H 'Content-Type: application/json' +``` + +The output is given one character at a time. It is too long to show +here but the last item will be +``` +data: [DONE] +``` + +### MegaService + +```bash +curl http://${host_ip}:7778/v1/codegen -H "Content-Type: application/json" -d '{ + "messages": "Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception." + }' +``` + +The output is given one character at a time. It is too long to show +here but the last item will be +``` +data: [DONE] +``` + +## Launch UI +### Svelte UI +To access the frontend, open the following URL in your browser: http://{host_ip}:5173. By default, the UI runs on port 5173 internally. If you prefer to use a different host port to access the frontend, you can modify the port mapping in the `compose.yaml` file as shown below: +```bash + codegen-gaudi-ui-server: + image: ${REGISTRY:-opea}/codegen-ui:${TAG:-latest} + ... + ports: + - "5173:5173" +``` + +### React-Based UI (Optional) +To access the React-based frontend, modify the UI service in the `compose.yaml` file. Replace `codegen-gaudi-ui-server` service with the codegen-gaudi-react-ui-server service as per the config below: +```bash +codegen-gaudi-react-ui-server: + image: ${REGISTRY:-opea}/codegen-react-ui:${TAG:-latest} + container_name: codegen-gaudi-react-ui-server + environment: + - no_proxy=${no_proxy} + - https_proxy=${https_proxy} + - http_proxy=${http_proxy} + - APP_CODE_GEN_URL=${BACKEND_SERVICE_ENDPOINT} + depends_on: + - codegen-gaudi-backend-server + ports: + - "5174:80" + ipc: host + restart: always +``` +Once the services are up, open the following URL in your browser: http://{host_ip}:5174. By default, the UI runs on port 80 internally. If you prefer to use a different host port to access the frontend, you can modify the port mapping in the `compose.yaml` file as shown below: +```bash + codegen-gaudi-react-ui-server: + image: ${REGISTRY:-opea}/codegen-react-ui:${TAG:-latest} + ... + ports: + - "80:80" +``` + +## Check Docker Container Logs + +You can check the log of a container by running this command: + +```bash +docker logs -t +``` + +You can also check the overall logs with the following command, where the +`compose.yaml` is the megaservice docker-compose configuration file. + +Assumming you are still in this directory `GenAIExamples/CodeGen/docker_compose/intel/hpu/gaudi`, +run the following command to check the logs: +```bash +docker compose -f compose.yaml logs +``` + +View the docker input parameters in `./CodeGen/docker_compose/intel/hpu/gaudi/compose.yaml` + +```yaml + tgi-service: + image: ghcr.io/huggingface/tgi-gaudi:2.0.1 + container_name: tgi-gaudi-server + ports: + - "8028:80" + volumes: + - "./data:/data" + environment: + no_proxy: ${no_proxy} + http_proxy: ${http_proxy} + https_proxy: ${https_proxy} + HABANA_VISIBLE_DEVICES: all + OMPI_MCA_btl_vader_single_copy_mechanism: none + HF_TOKEN: ${HUGGINGFACEHUB_API_TOKEN} + runtime: habana + cap_add: + - SYS_NICE + ipc: host + command: --model-id ${LLM_MODEL_ID} --max-input-length 1024 --max-total-tokens 2048 +``` + +The input `--model-id` is `${LLM_MODEL_ID}`. Ensure the environment variable `LLM_MODEL_ID` +is set correctly. Check spelling. Whenever this is changed, restart the containers to use +the newly selected model. + + +## Stop the services + +Once you are done with the entire pipeline and wish to stop and remove all the containers, use the command below: +``` +docker compose down +``` From d20130c65b2b8561868d89ed03492ad0a98ee5e8 Mon Sep 17 00:00:00 2001 From: alexsin368 Date: Tue, 12 Nov 2024 16:17:53 -0800 Subject: [PATCH 26/34] Revert "CodeGen: add gaudi deployment sample guide" This reverts commit e3790579d5f2944b58b9d1065757a0a76a6d1ec9. Signed-off-by: alexsin368 --- examples/CodeGen/deploy/gaudi.md | 372 ------------------------------- 1 file changed, 372 deletions(-) delete mode 100644 examples/CodeGen/deploy/gaudi.md diff --git a/examples/CodeGen/deploy/gaudi.md b/examples/CodeGen/deploy/gaudi.md deleted file mode 100644 index 9ad3971d..00000000 --- a/examples/CodeGen/deploy/gaudi.md +++ /dev/null @@ -1,372 +0,0 @@ -# Single node on-prem deployment with vLLM or TGI on Gaudi AI Accelerator - -This deployment section covers single-node on-prem deployment of the CodeGen -example with OPEA comps to deploy using the TGI service. We will be showcasing how -to build an e2e CodeGen solution with the CodeLlama-7b-hf model, -deployed on Intel® Tiber™ AI Cloud (ITAC). To quickly learn about OPEA in just 5 minutes and set up the required hardware and software, please follow the instructions in the -[Getting Started](https://opea-project.github.io/latest/getting-started/README.html) section. If you do -not have an ITAC instance or the hardware is not supported in the ITAC yet, you can still run this on-prem. - -## Overview - -The CodeGen use case uses a single microservice called LLM. In this tutorial, we -will walk through the steps on how on enable it from OPEA GenAIComps to deploy on -a single node TGI megaservice solution. - -The solution is aimed to show how to use the CodeLlama-7b-hf model on the Intel® -Gaudi® AI Accelerator. We will go through how to setup docker containers to start -the microservice and megaservice. The solution will then take text input as the -prompt and generate code accordingly. It is deployed with a UI with 2 modes to -choose from: - -1. Svelte-Based UI -2. React-Based UI - -The React-based UI is optional, but this feature is supported in this example if you -are interested in using it. - -Below is the list of content we will be covering in this tutorial: - -1. Prerequisites -2. Prepare (Building / Pulling) Docker images -3. Use case setup -4. Deploy the use case -5. Interacting with CodeGen deployment - -## Prerequisites - -The first step is to clone the GenAIExamples and GenAIComps. GenAIComps are -fundamental necessary components used to build examples you find in -GenAIExamples and deploy them as microservices. - -```bash -git clone https://github.com/opea-project/GenAIComps.git -git clone https://github.com/opea-project/GenAIExamples.git -``` - -The examples utilize model weights from HuggingFace and langchain. - -Setup your [HuggingFace](https://huggingface.co/) account and generate -[user access token](https://huggingface.co/docs/transformers.js/en/guides/private#step-1-generating-a-user-access-token). - -Setup the HuggingFace token -``` -export HUGGINGFACEHUB_API_TOKEN="Your_Huggingface_API_Token" -``` - -Additionally, if you plan to use the default model CodeLlama-7b-hf, you will -need to [request access](https://huggingface.co/meta-llama/CodeLlama-7b-hf) from HuggingFace. - -The example requires you to set the `host_ip` to deploy the microservices on -endpoint enabled with ports. Set the host_ip env variable -``` -export host_ip=$(hostname -I | awk '{print $1}') -``` - -Make sure to setup Proxies if you are behind a firewall -``` -export no_proxy=${your_no_proxy},$host_ip -export http_proxy=${your_http_proxy} -export https_proxy=${your_http_proxy} -``` - -## Prepare (Building / Pulling) Docker images - -This step will involve building/pulling relevant docker -images with step-by-step process along with sanity check in the end. For -CodeGen, the following docker images will be needed: LLM with TGI. -Additionally, you will need to build docker images for the -CodeGen megaservice, and UI (React UI is optional). In total, -there are **3 required docker images** and an optional docker image. - -### Build/Pull Microservice image - -::::::{tab-set} - -:::::{tab-item} Pull -:sync: Pull - -If you decide to pull the docker containers and not build them locally, -you can proceed to the next step where all the necessary containers will -be pulled in from dockerhub. - -::::: -:::::{tab-item} Build -:sync: Build - -From within the `GenAIComps` folder, checkout the release tag. -``` -cd GenAIComps -git checkout tags/v1.1 -``` - -#### Build LLM Image - -```bash -docker build --no-cache -t opea/llm-tgi:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/text-generation/tgi/Dockerfile . -``` - -### Build Mega Service images - -The Megaservice is a pipeline that channels data through different -microservices, each performing varied tasks. The LLM microservice and -flow of data are defined in the `codegen.py` file. You can also add or -remove microservices and customize the megaservice to suit your needs. - -Build the megaservice image for this use case - -```bash -cd .. -cd GenAIExamples -git checkout tags/v1.1 -cd CodeGen -``` - -```bash -docker build --no-cache -t opea/codegen:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile . -cd ../.. -``` - -### Build the UI Image - -You can build 2 modes of UI - -*Svelte UI* - -```bash -cd GenAIExamples/CodeGen/ui/ -docker build --no-cache -t opea/codegen-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile . -cd ../../.. -``` - -*React UI (Optional)* -If you want a React-based frontend. - -```bash -cd GenAIExamples/CodeGen/ui/ -docker build --no-cache -t opea/codegen-react-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile.react . -cd ../../.. -``` - -### Sanity Check -Check if you have the following set of docker images by running the command `docker images` before moving on to the next step: - -* `opea/llm-tgi:latest` -* `opea/codegen:latest` -* `opea/codegen-ui:latest` -* `opea/codegen-react-ui:latest` (optional) - -::::: -:::::: - -## Use Case Setup - -The use case will use the following combination of GenAIComps and tools - -|Use Case Components | Tools | Model | Service Type | -|---------------- |--------------|-----------------------------|-------| -|LLM | TGI | meta-llama/CodeLlama-7b-hf | OPEA Microservice | -|UI | | NA | Gateway Service | - -Tools and models mentioned in the table are configurable either through the -environment variables or `compose.yaml` file. - -Set the necessary environment variables to setup the use case case by running the `set_env.sh` script. -Here is where the environment variable `LLM_MODEL_ID` is set, and you can change it to another model -by specifying the HuggingFace model card ID. - -```bash -cd GenAIExamples/CodeGen/docker_compose/ -source ./set_env.sh -cd ../../.. -``` - -## Deploy the Use Case - -In this tutorial, we will be deploying via docker compose with the provided -YAML file. The docker compose instructions should be starting all the -above mentioned services as containers. - -```bash -cd GenAIExamples/CodeGen/docker_compose/intel/hpu/gaudi -docker compose up -d -``` - - -### Checks to Ensure the Services are Running -#### Check Startup and Env Variables -Check the start up log by running `docker compose logs` to ensure there are no errors. -The warning messages print out the variables if they are **NOT** set. - -Here are some sample messages if proxy environment variables are not set: - - WARN[0000] The "no_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "https_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "http_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "no_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "https_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "http_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "no_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "http_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "https_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "no_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "http_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "https_proxy" variable is not set. Defaulting to a blank string. - -#### Check the Container Status - -Check if all the containers launched via docker compose has started. - -The CodeGen example starts 4 docker containers. Check that these docker -containers are all running, i.e, all the containers `STATUS` are `Up`. -You can do this with the `docker ps -a` command. - -``` -CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES -bbd235074c3d opea/codegen-ui:latest "docker-entrypoint.s…" About a minute ago Up About a minute 0.0.0.0:5173->5173/tcp, :::5173->5173/tcp codegen-gaudi-ui-server -8d3872ca66fa opea/codegen:latest "python codegen.py" About a minute ago Up About a minute 0.0.0.0:7778->7778/tcp, :::7778->7778/tcp codegen-gaudi-backend-server -b9fc39f51cdb opea/llm-tgi:latest "bash entrypoint.sh" About a minute ago Up About a minute 0.0.0.0:9000->9000/tcp, :::9000->9000/tcp llm-tgi-gaudi-server -39994e007f15 ghcr.io/huggingface/tgi-gaudi:2.0.1 "text-generation-lau…" About a minute ago Up About a minute 0.0.0.0:8028->80/tcp, :::8028->80/tcp tgi-gaudi-server -``` - -## Interacting with CodeGen for Deployment - -This section will walk you through the different ways to interact with -the microservices deployed. After a couple minutes, rerun `docker ps -a` -to ensure all the docker containers are still up and running. Then proceed -to validate each microservice and megaservice. - -### TGI Service - -```bash -curl http://${host_ip}:8028/generate \ - -X POST \ - -d '{"inputs":"Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception.","parameters":{"max_new_tokens":256, "do_sample": true}}' \ - -H 'Content-Type: application/json' -``` - -Here is the output: - -``` -{"generated_text":"\n\nIO iflow diagram:\n\n![IO flow diagram(s)](TodoList.iflow.svg)\n\n### TDD Kata walkthrough\n\n1. Start with a user story. We will add story tests later. In this case, we'll choose a story about adding a TODO:\n ```ruby\n as a user,\n i want to add a todo,\n so that i can get a todo list.\n\n conformance:\n - a new todo is added to the list\n - if the todo text is empty, raise an exception\n ```\n\n1. Write the first test:\n ```ruby\n feature Testing the addition of a todo to the list\n\n given a todo list empty list\n when a user adds a todo\n the todo should be added to the list\n\n inputs:\n when_values: [[\"A\"]]\n\n output validations:\n - todo_list contains { text:\"A\" }\n ```\n\n1. Write the first step implementation in any programming language you like. In this case, we will choose Ruby:\n ```ruby\n def add_"} -``` - -### LLM Microservice - -```bash -curl http://${host_ip}:9000/v1/chat/completions\ - -X POST \ - -d '{"query":"Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception.","max_tokens":256,"top_k":10,"top_p":0.95,"typical_p":0.95,"temperature":0.01,"repetition_penalty":1.03,"streaming":true}' \ - -H 'Content-Type: application/json' -``` - -The output is given one character at a time. It is too long to show -here but the last item will be -``` -data: [DONE] -``` - -### MegaService - -```bash -curl http://${host_ip}:7778/v1/codegen -H "Content-Type: application/json" -d '{ - "messages": "Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception." - }' -``` - -The output is given one character at a time. It is too long to show -here but the last item will be -``` -data: [DONE] -``` - -## Launch UI -### Svelte UI -To access the frontend, open the following URL in your browser: http://{host_ip}:5173. By default, the UI runs on port 5173 internally. If you prefer to use a different host port to access the frontend, you can modify the port mapping in the `compose.yaml` file as shown below: -```bash - codegen-gaudi-ui-server: - image: ${REGISTRY:-opea}/codegen-ui:${TAG:-latest} - ... - ports: - - "5173:5173" -``` - -### React-Based UI (Optional) -To access the React-based frontend, modify the UI service in the `compose.yaml` file. Replace `codegen-gaudi-ui-server` service with the codegen-gaudi-react-ui-server service as per the config below: -```bash -codegen-gaudi-react-ui-server: - image: ${REGISTRY:-opea}/codegen-react-ui:${TAG:-latest} - container_name: codegen-gaudi-react-ui-server - environment: - - no_proxy=${no_proxy} - - https_proxy=${https_proxy} - - http_proxy=${http_proxy} - - APP_CODE_GEN_URL=${BACKEND_SERVICE_ENDPOINT} - depends_on: - - codegen-gaudi-backend-server - ports: - - "5174:80" - ipc: host - restart: always -``` -Once the services are up, open the following URL in your browser: http://{host_ip}:5174. By default, the UI runs on port 80 internally. If you prefer to use a different host port to access the frontend, you can modify the port mapping in the `compose.yaml` file as shown below: -```bash - codegen-gaudi-react-ui-server: - image: ${REGISTRY:-opea}/codegen-react-ui:${TAG:-latest} - ... - ports: - - "80:80" -``` - -## Check Docker Container Logs - -You can check the log of a container by running this command: - -```bash -docker logs -t -``` - -You can also check the overall logs with the following command, where the -`compose.yaml` is the megaservice docker-compose configuration file. - -Assumming you are still in this directory `GenAIExamples/CodeGen/docker_compose/intel/hpu/gaudi`, -run the following command to check the logs: -```bash -docker compose -f compose.yaml logs -``` - -View the docker input parameters in `./CodeGen/docker_compose/intel/hpu/gaudi/compose.yaml` - -```yaml - tgi-service: - image: ghcr.io/huggingface/tgi-gaudi:2.0.1 - container_name: tgi-gaudi-server - ports: - - "8028:80" - volumes: - - "./data:/data" - environment: - no_proxy: ${no_proxy} - http_proxy: ${http_proxy} - https_proxy: ${https_proxy} - HABANA_VISIBLE_DEVICES: all - OMPI_MCA_btl_vader_single_copy_mechanism: none - HF_TOKEN: ${HUGGINGFACEHUB_API_TOKEN} - runtime: habana - cap_add: - - SYS_NICE - ipc: host - command: --model-id ${LLM_MODEL_ID} --max-input-length 1024 --max-total-tokens 2048 -``` - -The input `--model-id` is `${LLM_MODEL_ID}`. Ensure the environment variable `LLM_MODEL_ID` -is set correctly. Check spelling. Whenever this is changed, restart the containers to use -the newly selected model. - - -## Stop the services - -Once you are done with the entire pipeline and wish to stop and remove all the containers, use the command below: -``` -docker compose down -``` From ad3fb525b626d69329909bd3e92ddc0f22c165da Mon Sep 17 00:00:00 2001 From: asin Date: Thu, 24 Oct 2024 15:06:38 -0700 Subject: [PATCH 27/34] fix formating for pull/build docker images Signed-off-by: asin --- examples/ChatQnA/deploy/gaudi.md | 25 ++++++++++++++----------- 1 file changed, 14 insertions(+), 11 deletions(-) diff --git a/examples/ChatQnA/deploy/gaudi.md b/examples/ChatQnA/deploy/gaudi.md index aa59a165..09aa30a8 100644 --- a/examples/ChatQnA/deploy/gaudi.md +++ b/examples/ChatQnA/deploy/gaudi.md @@ -87,15 +87,18 @@ ChatQnA megaservice, and UI (conversational React UI is optional). In total, there are 8 required and an optional docker images. ### Build/Pull Microservice images -::::{tab-set} -:::{tab-item} Pull + +::::::{tab-set} + +:::::{tab-item} Pull :sync: Pull -To pull pre-built docker images on Docker Hub, proceed to the next step. To customize -your application, you can choose to build individual docker images for the microservices -before proceeding. -::: -:::{tab-item} Build +If you decide to pull the docker containers and not build them locally, +you can proceed to the next step where all the necessary containers will +be pulled in from dockerhub. + +::::: +:::::{tab-item} Build :sync: Build From within the `GenAIComps` folder, checkout the release tag. @@ -103,8 +106,6 @@ From within the `GenAIComps` folder, checkout the release tag. cd GenAIComps git checkout tags/v1.0 ``` -::: -:::: #### Build Dataprep Image @@ -130,7 +131,7 @@ docker build --no-cache -t opea/retriever-redis:latest --build-arg https_proxy=$ docker build --no-cache -t opea/reranking-tei:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/reranks/tei/Dockerfile . ``` -#### Build docker +#### Build LLM Image ::::{tab-set} @@ -240,7 +241,6 @@ Check if you have the below set of docker images, before moving on to the next s * opea/chatqna-ui:latest * opea/vllm:latest * opea/llm-vllm:latest - ::: :::{tab-item} TGI :sync: TGI @@ -256,6 +256,9 @@ Check if you have the below set of docker images, before moving on to the next s ::: :::: +::::: +:::::: + ## Use Case Setup As mentioned the use case will use the following combination of the GenAIComps From c7fa7719d35dbbdf00fa42eaa0d49090a8da3db1 Mon Sep 17 00:00:00 2001 From: alexsin368 Date: Fri, 8 Nov 2024 17:56:04 -0800 Subject: [PATCH 28/34] CodeGen: add gaudi deployment sample guide Signed-off-by: alexsin368 --- examples/CodeGen/deploy/gaudi.md | 372 +++++++++++++++++++++++++++++++ 1 file changed, 372 insertions(+) create mode 100644 examples/CodeGen/deploy/gaudi.md diff --git a/examples/CodeGen/deploy/gaudi.md b/examples/CodeGen/deploy/gaudi.md new file mode 100644 index 00000000..9ad3971d --- /dev/null +++ b/examples/CodeGen/deploy/gaudi.md @@ -0,0 +1,372 @@ +# Single node on-prem deployment with vLLM or TGI on Gaudi AI Accelerator + +This deployment section covers single-node on-prem deployment of the CodeGen +example with OPEA comps to deploy using the TGI service. We will be showcasing how +to build an e2e CodeGen solution with the CodeLlama-7b-hf model, +deployed on Intel® Tiber™ AI Cloud (ITAC). To quickly learn about OPEA in just 5 minutes and set up the required hardware and software, please follow the instructions in the +[Getting Started](https://opea-project.github.io/latest/getting-started/README.html) section. If you do +not have an ITAC instance or the hardware is not supported in the ITAC yet, you can still run this on-prem. + +## Overview + +The CodeGen use case uses a single microservice called LLM. In this tutorial, we +will walk through the steps on how on enable it from OPEA GenAIComps to deploy on +a single node TGI megaservice solution. + +The solution is aimed to show how to use the CodeLlama-7b-hf model on the Intel® +Gaudi® AI Accelerator. We will go through how to setup docker containers to start +the microservice and megaservice. The solution will then take text input as the +prompt and generate code accordingly. It is deployed with a UI with 2 modes to +choose from: + +1. Svelte-Based UI +2. React-Based UI + +The React-based UI is optional, but this feature is supported in this example if you +are interested in using it. + +Below is the list of content we will be covering in this tutorial: + +1. Prerequisites +2. Prepare (Building / Pulling) Docker images +3. Use case setup +4. Deploy the use case +5. Interacting with CodeGen deployment + +## Prerequisites + +The first step is to clone the GenAIExamples and GenAIComps. GenAIComps are +fundamental necessary components used to build examples you find in +GenAIExamples and deploy them as microservices. + +```bash +git clone https://github.com/opea-project/GenAIComps.git +git clone https://github.com/opea-project/GenAIExamples.git +``` + +The examples utilize model weights from HuggingFace and langchain. + +Setup your [HuggingFace](https://huggingface.co/) account and generate +[user access token](https://huggingface.co/docs/transformers.js/en/guides/private#step-1-generating-a-user-access-token). + +Setup the HuggingFace token +``` +export HUGGINGFACEHUB_API_TOKEN="Your_Huggingface_API_Token" +``` + +Additionally, if you plan to use the default model CodeLlama-7b-hf, you will +need to [request access](https://huggingface.co/meta-llama/CodeLlama-7b-hf) from HuggingFace. + +The example requires you to set the `host_ip` to deploy the microservices on +endpoint enabled with ports. Set the host_ip env variable +``` +export host_ip=$(hostname -I | awk '{print $1}') +``` + +Make sure to setup Proxies if you are behind a firewall +``` +export no_proxy=${your_no_proxy},$host_ip +export http_proxy=${your_http_proxy} +export https_proxy=${your_http_proxy} +``` + +## Prepare (Building / Pulling) Docker images + +This step will involve building/pulling relevant docker +images with step-by-step process along with sanity check in the end. For +CodeGen, the following docker images will be needed: LLM with TGI. +Additionally, you will need to build docker images for the +CodeGen megaservice, and UI (React UI is optional). In total, +there are **3 required docker images** and an optional docker image. + +### Build/Pull Microservice image + +::::::{tab-set} + +:::::{tab-item} Pull +:sync: Pull + +If you decide to pull the docker containers and not build them locally, +you can proceed to the next step where all the necessary containers will +be pulled in from dockerhub. + +::::: +:::::{tab-item} Build +:sync: Build + +From within the `GenAIComps` folder, checkout the release tag. +``` +cd GenAIComps +git checkout tags/v1.1 +``` + +#### Build LLM Image + +```bash +docker build --no-cache -t opea/llm-tgi:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/text-generation/tgi/Dockerfile . +``` + +### Build Mega Service images + +The Megaservice is a pipeline that channels data through different +microservices, each performing varied tasks. The LLM microservice and +flow of data are defined in the `codegen.py` file. You can also add or +remove microservices and customize the megaservice to suit your needs. + +Build the megaservice image for this use case + +```bash +cd .. +cd GenAIExamples +git checkout tags/v1.1 +cd CodeGen +``` + +```bash +docker build --no-cache -t opea/codegen:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile . +cd ../.. +``` + +### Build the UI Image + +You can build 2 modes of UI + +*Svelte UI* + +```bash +cd GenAIExamples/CodeGen/ui/ +docker build --no-cache -t opea/codegen-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile . +cd ../../.. +``` + +*React UI (Optional)* +If you want a React-based frontend. + +```bash +cd GenAIExamples/CodeGen/ui/ +docker build --no-cache -t opea/codegen-react-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile.react . +cd ../../.. +``` + +### Sanity Check +Check if you have the following set of docker images by running the command `docker images` before moving on to the next step: + +* `opea/llm-tgi:latest` +* `opea/codegen:latest` +* `opea/codegen-ui:latest` +* `opea/codegen-react-ui:latest` (optional) + +::::: +:::::: + +## Use Case Setup + +The use case will use the following combination of GenAIComps and tools + +|Use Case Components | Tools | Model | Service Type | +|---------------- |--------------|-----------------------------|-------| +|LLM | TGI | meta-llama/CodeLlama-7b-hf | OPEA Microservice | +|UI | | NA | Gateway Service | + +Tools and models mentioned in the table are configurable either through the +environment variables or `compose.yaml` file. + +Set the necessary environment variables to setup the use case case by running the `set_env.sh` script. +Here is where the environment variable `LLM_MODEL_ID` is set, and you can change it to another model +by specifying the HuggingFace model card ID. + +```bash +cd GenAIExamples/CodeGen/docker_compose/ +source ./set_env.sh +cd ../../.. +``` + +## Deploy the Use Case + +In this tutorial, we will be deploying via docker compose with the provided +YAML file. The docker compose instructions should be starting all the +above mentioned services as containers. + +```bash +cd GenAIExamples/CodeGen/docker_compose/intel/hpu/gaudi +docker compose up -d +``` + + +### Checks to Ensure the Services are Running +#### Check Startup and Env Variables +Check the start up log by running `docker compose logs` to ensure there are no errors. +The warning messages print out the variables if they are **NOT** set. + +Here are some sample messages if proxy environment variables are not set: + + WARN[0000] The "no_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "https_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "http_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "no_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "https_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "http_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "no_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "http_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "https_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "no_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "http_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "https_proxy" variable is not set. Defaulting to a blank string. + +#### Check the Container Status + +Check if all the containers launched via docker compose has started. + +The CodeGen example starts 4 docker containers. Check that these docker +containers are all running, i.e, all the containers `STATUS` are `Up`. +You can do this with the `docker ps -a` command. + +``` +CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES +bbd235074c3d opea/codegen-ui:latest "docker-entrypoint.s…" About a minute ago Up About a minute 0.0.0.0:5173->5173/tcp, :::5173->5173/tcp codegen-gaudi-ui-server +8d3872ca66fa opea/codegen:latest "python codegen.py" About a minute ago Up About a minute 0.0.0.0:7778->7778/tcp, :::7778->7778/tcp codegen-gaudi-backend-server +b9fc39f51cdb opea/llm-tgi:latest "bash entrypoint.sh" About a minute ago Up About a minute 0.0.0.0:9000->9000/tcp, :::9000->9000/tcp llm-tgi-gaudi-server +39994e007f15 ghcr.io/huggingface/tgi-gaudi:2.0.1 "text-generation-lau…" About a minute ago Up About a minute 0.0.0.0:8028->80/tcp, :::8028->80/tcp tgi-gaudi-server +``` + +## Interacting with CodeGen for Deployment + +This section will walk you through the different ways to interact with +the microservices deployed. After a couple minutes, rerun `docker ps -a` +to ensure all the docker containers are still up and running. Then proceed +to validate each microservice and megaservice. + +### TGI Service + +```bash +curl http://${host_ip}:8028/generate \ + -X POST \ + -d '{"inputs":"Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception.","parameters":{"max_new_tokens":256, "do_sample": true}}' \ + -H 'Content-Type: application/json' +``` + +Here is the output: + +``` +{"generated_text":"\n\nIO iflow diagram:\n\n![IO flow diagram(s)](TodoList.iflow.svg)\n\n### TDD Kata walkthrough\n\n1. Start with a user story. We will add story tests later. In this case, we'll choose a story about adding a TODO:\n ```ruby\n as a user,\n i want to add a todo,\n so that i can get a todo list.\n\n conformance:\n - a new todo is added to the list\n - if the todo text is empty, raise an exception\n ```\n\n1. Write the first test:\n ```ruby\n feature Testing the addition of a todo to the list\n\n given a todo list empty list\n when a user adds a todo\n the todo should be added to the list\n\n inputs:\n when_values: [[\"A\"]]\n\n output validations:\n - todo_list contains { text:\"A\" }\n ```\n\n1. Write the first step implementation in any programming language you like. In this case, we will choose Ruby:\n ```ruby\n def add_"} +``` + +### LLM Microservice + +```bash +curl http://${host_ip}:9000/v1/chat/completions\ + -X POST \ + -d '{"query":"Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception.","max_tokens":256,"top_k":10,"top_p":0.95,"typical_p":0.95,"temperature":0.01,"repetition_penalty":1.03,"streaming":true}' \ + -H 'Content-Type: application/json' +``` + +The output is given one character at a time. It is too long to show +here but the last item will be +``` +data: [DONE] +``` + +### MegaService + +```bash +curl http://${host_ip}:7778/v1/codegen -H "Content-Type: application/json" -d '{ + "messages": "Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception." + }' +``` + +The output is given one character at a time. It is too long to show +here but the last item will be +``` +data: [DONE] +``` + +## Launch UI +### Svelte UI +To access the frontend, open the following URL in your browser: http://{host_ip}:5173. By default, the UI runs on port 5173 internally. If you prefer to use a different host port to access the frontend, you can modify the port mapping in the `compose.yaml` file as shown below: +```bash + codegen-gaudi-ui-server: + image: ${REGISTRY:-opea}/codegen-ui:${TAG:-latest} + ... + ports: + - "5173:5173" +``` + +### React-Based UI (Optional) +To access the React-based frontend, modify the UI service in the `compose.yaml` file. Replace `codegen-gaudi-ui-server` service with the codegen-gaudi-react-ui-server service as per the config below: +```bash +codegen-gaudi-react-ui-server: + image: ${REGISTRY:-opea}/codegen-react-ui:${TAG:-latest} + container_name: codegen-gaudi-react-ui-server + environment: + - no_proxy=${no_proxy} + - https_proxy=${https_proxy} + - http_proxy=${http_proxy} + - APP_CODE_GEN_URL=${BACKEND_SERVICE_ENDPOINT} + depends_on: + - codegen-gaudi-backend-server + ports: + - "5174:80" + ipc: host + restart: always +``` +Once the services are up, open the following URL in your browser: http://{host_ip}:5174. By default, the UI runs on port 80 internally. If you prefer to use a different host port to access the frontend, you can modify the port mapping in the `compose.yaml` file as shown below: +```bash + codegen-gaudi-react-ui-server: + image: ${REGISTRY:-opea}/codegen-react-ui:${TAG:-latest} + ... + ports: + - "80:80" +``` + +## Check Docker Container Logs + +You can check the log of a container by running this command: + +```bash +docker logs -t +``` + +You can also check the overall logs with the following command, where the +`compose.yaml` is the megaservice docker-compose configuration file. + +Assumming you are still in this directory `GenAIExamples/CodeGen/docker_compose/intel/hpu/gaudi`, +run the following command to check the logs: +```bash +docker compose -f compose.yaml logs +``` + +View the docker input parameters in `./CodeGen/docker_compose/intel/hpu/gaudi/compose.yaml` + +```yaml + tgi-service: + image: ghcr.io/huggingface/tgi-gaudi:2.0.1 + container_name: tgi-gaudi-server + ports: + - "8028:80" + volumes: + - "./data:/data" + environment: + no_proxy: ${no_proxy} + http_proxy: ${http_proxy} + https_proxy: ${https_proxy} + HABANA_VISIBLE_DEVICES: all + OMPI_MCA_btl_vader_single_copy_mechanism: none + HF_TOKEN: ${HUGGINGFACEHUB_API_TOKEN} + runtime: habana + cap_add: + - SYS_NICE + ipc: host + command: --model-id ${LLM_MODEL_ID} --max-input-length 1024 --max-total-tokens 2048 +``` + +The input `--model-id` is `${LLM_MODEL_ID}`. Ensure the environment variable `LLM_MODEL_ID` +is set correctly. Check spelling. Whenever this is changed, restart the containers to use +the newly selected model. + + +## Stop the services + +Once you are done with the entire pipeline and wish to stop and remove all the containers, use the command below: +``` +docker compose down +``` From 3fb3085e46c58bedcb586f71edeffc2c6f484ade Mon Sep 17 00:00:00 2001 From: alexsin368 Date: Tue, 12 Nov 2024 16:17:53 -0800 Subject: [PATCH 29/34] Revert "CodeGen: add gaudi deployment sample guide" This reverts commit e3790579d5f2944b58b9d1065757a0a76a6d1ec9. --- examples/CodeGen/deploy/gaudi.md | 372 ------------------------------- 1 file changed, 372 deletions(-) delete mode 100644 examples/CodeGen/deploy/gaudi.md diff --git a/examples/CodeGen/deploy/gaudi.md b/examples/CodeGen/deploy/gaudi.md deleted file mode 100644 index 9ad3971d..00000000 --- a/examples/CodeGen/deploy/gaudi.md +++ /dev/null @@ -1,372 +0,0 @@ -# Single node on-prem deployment with vLLM or TGI on Gaudi AI Accelerator - -This deployment section covers single-node on-prem deployment of the CodeGen -example with OPEA comps to deploy using the TGI service. We will be showcasing how -to build an e2e CodeGen solution with the CodeLlama-7b-hf model, -deployed on Intel® Tiber™ AI Cloud (ITAC). To quickly learn about OPEA in just 5 minutes and set up the required hardware and software, please follow the instructions in the -[Getting Started](https://opea-project.github.io/latest/getting-started/README.html) section. If you do -not have an ITAC instance or the hardware is not supported in the ITAC yet, you can still run this on-prem. - -## Overview - -The CodeGen use case uses a single microservice called LLM. In this tutorial, we -will walk through the steps on how on enable it from OPEA GenAIComps to deploy on -a single node TGI megaservice solution. - -The solution is aimed to show how to use the CodeLlama-7b-hf model on the Intel® -Gaudi® AI Accelerator. We will go through how to setup docker containers to start -the microservice and megaservice. The solution will then take text input as the -prompt and generate code accordingly. It is deployed with a UI with 2 modes to -choose from: - -1. Svelte-Based UI -2. React-Based UI - -The React-based UI is optional, but this feature is supported in this example if you -are interested in using it. - -Below is the list of content we will be covering in this tutorial: - -1. Prerequisites -2. Prepare (Building / Pulling) Docker images -3. Use case setup -4. Deploy the use case -5. Interacting with CodeGen deployment - -## Prerequisites - -The first step is to clone the GenAIExamples and GenAIComps. GenAIComps are -fundamental necessary components used to build examples you find in -GenAIExamples and deploy them as microservices. - -```bash -git clone https://github.com/opea-project/GenAIComps.git -git clone https://github.com/opea-project/GenAIExamples.git -``` - -The examples utilize model weights from HuggingFace and langchain. - -Setup your [HuggingFace](https://huggingface.co/) account and generate -[user access token](https://huggingface.co/docs/transformers.js/en/guides/private#step-1-generating-a-user-access-token). - -Setup the HuggingFace token -``` -export HUGGINGFACEHUB_API_TOKEN="Your_Huggingface_API_Token" -``` - -Additionally, if you plan to use the default model CodeLlama-7b-hf, you will -need to [request access](https://huggingface.co/meta-llama/CodeLlama-7b-hf) from HuggingFace. - -The example requires you to set the `host_ip` to deploy the microservices on -endpoint enabled with ports. Set the host_ip env variable -``` -export host_ip=$(hostname -I | awk '{print $1}') -``` - -Make sure to setup Proxies if you are behind a firewall -``` -export no_proxy=${your_no_proxy},$host_ip -export http_proxy=${your_http_proxy} -export https_proxy=${your_http_proxy} -``` - -## Prepare (Building / Pulling) Docker images - -This step will involve building/pulling relevant docker -images with step-by-step process along with sanity check in the end. For -CodeGen, the following docker images will be needed: LLM with TGI. -Additionally, you will need to build docker images for the -CodeGen megaservice, and UI (React UI is optional). In total, -there are **3 required docker images** and an optional docker image. - -### Build/Pull Microservice image - -::::::{tab-set} - -:::::{tab-item} Pull -:sync: Pull - -If you decide to pull the docker containers and not build them locally, -you can proceed to the next step where all the necessary containers will -be pulled in from dockerhub. - -::::: -:::::{tab-item} Build -:sync: Build - -From within the `GenAIComps` folder, checkout the release tag. -``` -cd GenAIComps -git checkout tags/v1.1 -``` - -#### Build LLM Image - -```bash -docker build --no-cache -t opea/llm-tgi:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/text-generation/tgi/Dockerfile . -``` - -### Build Mega Service images - -The Megaservice is a pipeline that channels data through different -microservices, each performing varied tasks. The LLM microservice and -flow of data are defined in the `codegen.py` file. You can also add or -remove microservices and customize the megaservice to suit your needs. - -Build the megaservice image for this use case - -```bash -cd .. -cd GenAIExamples -git checkout tags/v1.1 -cd CodeGen -``` - -```bash -docker build --no-cache -t opea/codegen:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile . -cd ../.. -``` - -### Build the UI Image - -You can build 2 modes of UI - -*Svelte UI* - -```bash -cd GenAIExamples/CodeGen/ui/ -docker build --no-cache -t opea/codegen-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile . -cd ../../.. -``` - -*React UI (Optional)* -If you want a React-based frontend. - -```bash -cd GenAIExamples/CodeGen/ui/ -docker build --no-cache -t opea/codegen-react-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile.react . -cd ../../.. -``` - -### Sanity Check -Check if you have the following set of docker images by running the command `docker images` before moving on to the next step: - -* `opea/llm-tgi:latest` -* `opea/codegen:latest` -* `opea/codegen-ui:latest` -* `opea/codegen-react-ui:latest` (optional) - -::::: -:::::: - -## Use Case Setup - -The use case will use the following combination of GenAIComps and tools - -|Use Case Components | Tools | Model | Service Type | -|---------------- |--------------|-----------------------------|-------| -|LLM | TGI | meta-llama/CodeLlama-7b-hf | OPEA Microservice | -|UI | | NA | Gateway Service | - -Tools and models mentioned in the table are configurable either through the -environment variables or `compose.yaml` file. - -Set the necessary environment variables to setup the use case case by running the `set_env.sh` script. -Here is where the environment variable `LLM_MODEL_ID` is set, and you can change it to another model -by specifying the HuggingFace model card ID. - -```bash -cd GenAIExamples/CodeGen/docker_compose/ -source ./set_env.sh -cd ../../.. -``` - -## Deploy the Use Case - -In this tutorial, we will be deploying via docker compose with the provided -YAML file. The docker compose instructions should be starting all the -above mentioned services as containers. - -```bash -cd GenAIExamples/CodeGen/docker_compose/intel/hpu/gaudi -docker compose up -d -``` - - -### Checks to Ensure the Services are Running -#### Check Startup and Env Variables -Check the start up log by running `docker compose logs` to ensure there are no errors. -The warning messages print out the variables if they are **NOT** set. - -Here are some sample messages if proxy environment variables are not set: - - WARN[0000] The "no_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "https_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "http_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "no_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "https_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "http_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "no_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "http_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "https_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "no_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "http_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "https_proxy" variable is not set. Defaulting to a blank string. - -#### Check the Container Status - -Check if all the containers launched via docker compose has started. - -The CodeGen example starts 4 docker containers. Check that these docker -containers are all running, i.e, all the containers `STATUS` are `Up`. -You can do this with the `docker ps -a` command. - -``` -CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES -bbd235074c3d opea/codegen-ui:latest "docker-entrypoint.s…" About a minute ago Up About a minute 0.0.0.0:5173->5173/tcp, :::5173->5173/tcp codegen-gaudi-ui-server -8d3872ca66fa opea/codegen:latest "python codegen.py" About a minute ago Up About a minute 0.0.0.0:7778->7778/tcp, :::7778->7778/tcp codegen-gaudi-backend-server -b9fc39f51cdb opea/llm-tgi:latest "bash entrypoint.sh" About a minute ago Up About a minute 0.0.0.0:9000->9000/tcp, :::9000->9000/tcp llm-tgi-gaudi-server -39994e007f15 ghcr.io/huggingface/tgi-gaudi:2.0.1 "text-generation-lau…" About a minute ago Up About a minute 0.0.0.0:8028->80/tcp, :::8028->80/tcp tgi-gaudi-server -``` - -## Interacting with CodeGen for Deployment - -This section will walk you through the different ways to interact with -the microservices deployed. After a couple minutes, rerun `docker ps -a` -to ensure all the docker containers are still up and running. Then proceed -to validate each microservice and megaservice. - -### TGI Service - -```bash -curl http://${host_ip}:8028/generate \ - -X POST \ - -d '{"inputs":"Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception.","parameters":{"max_new_tokens":256, "do_sample": true}}' \ - -H 'Content-Type: application/json' -``` - -Here is the output: - -``` -{"generated_text":"\n\nIO iflow diagram:\n\n![IO flow diagram(s)](TodoList.iflow.svg)\n\n### TDD Kata walkthrough\n\n1. Start with a user story. We will add story tests later. In this case, we'll choose a story about adding a TODO:\n ```ruby\n as a user,\n i want to add a todo,\n so that i can get a todo list.\n\n conformance:\n - a new todo is added to the list\n - if the todo text is empty, raise an exception\n ```\n\n1. Write the first test:\n ```ruby\n feature Testing the addition of a todo to the list\n\n given a todo list empty list\n when a user adds a todo\n the todo should be added to the list\n\n inputs:\n when_values: [[\"A\"]]\n\n output validations:\n - todo_list contains { text:\"A\" }\n ```\n\n1. Write the first step implementation in any programming language you like. In this case, we will choose Ruby:\n ```ruby\n def add_"} -``` - -### LLM Microservice - -```bash -curl http://${host_ip}:9000/v1/chat/completions\ - -X POST \ - -d '{"query":"Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception.","max_tokens":256,"top_k":10,"top_p":0.95,"typical_p":0.95,"temperature":0.01,"repetition_penalty":1.03,"streaming":true}' \ - -H 'Content-Type: application/json' -``` - -The output is given one character at a time. It is too long to show -here but the last item will be -``` -data: [DONE] -``` - -### MegaService - -```bash -curl http://${host_ip}:7778/v1/codegen -H "Content-Type: application/json" -d '{ - "messages": "Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception." - }' -``` - -The output is given one character at a time. It is too long to show -here but the last item will be -``` -data: [DONE] -``` - -## Launch UI -### Svelte UI -To access the frontend, open the following URL in your browser: http://{host_ip}:5173. By default, the UI runs on port 5173 internally. If you prefer to use a different host port to access the frontend, you can modify the port mapping in the `compose.yaml` file as shown below: -```bash - codegen-gaudi-ui-server: - image: ${REGISTRY:-opea}/codegen-ui:${TAG:-latest} - ... - ports: - - "5173:5173" -``` - -### React-Based UI (Optional) -To access the React-based frontend, modify the UI service in the `compose.yaml` file. Replace `codegen-gaudi-ui-server` service with the codegen-gaudi-react-ui-server service as per the config below: -```bash -codegen-gaudi-react-ui-server: - image: ${REGISTRY:-opea}/codegen-react-ui:${TAG:-latest} - container_name: codegen-gaudi-react-ui-server - environment: - - no_proxy=${no_proxy} - - https_proxy=${https_proxy} - - http_proxy=${http_proxy} - - APP_CODE_GEN_URL=${BACKEND_SERVICE_ENDPOINT} - depends_on: - - codegen-gaudi-backend-server - ports: - - "5174:80" - ipc: host - restart: always -``` -Once the services are up, open the following URL in your browser: http://{host_ip}:5174. By default, the UI runs on port 80 internally. If you prefer to use a different host port to access the frontend, you can modify the port mapping in the `compose.yaml` file as shown below: -```bash - codegen-gaudi-react-ui-server: - image: ${REGISTRY:-opea}/codegen-react-ui:${TAG:-latest} - ... - ports: - - "80:80" -``` - -## Check Docker Container Logs - -You can check the log of a container by running this command: - -```bash -docker logs -t -``` - -You can also check the overall logs with the following command, where the -`compose.yaml` is the megaservice docker-compose configuration file. - -Assumming you are still in this directory `GenAIExamples/CodeGen/docker_compose/intel/hpu/gaudi`, -run the following command to check the logs: -```bash -docker compose -f compose.yaml logs -``` - -View the docker input parameters in `./CodeGen/docker_compose/intel/hpu/gaudi/compose.yaml` - -```yaml - tgi-service: - image: ghcr.io/huggingface/tgi-gaudi:2.0.1 - container_name: tgi-gaudi-server - ports: - - "8028:80" - volumes: - - "./data:/data" - environment: - no_proxy: ${no_proxy} - http_proxy: ${http_proxy} - https_proxy: ${https_proxy} - HABANA_VISIBLE_DEVICES: all - OMPI_MCA_btl_vader_single_copy_mechanism: none - HF_TOKEN: ${HUGGINGFACEHUB_API_TOKEN} - runtime: habana - cap_add: - - SYS_NICE - ipc: host - command: --model-id ${LLM_MODEL_ID} --max-input-length 1024 --max-total-tokens 2048 -``` - -The input `--model-id` is `${LLM_MODEL_ID}`. Ensure the environment variable `LLM_MODEL_ID` -is set correctly. Check spelling. Whenever this is changed, restart the containers to use -the newly selected model. - - -## Stop the services - -Once you are done with the entire pipeline and wish to stop and remove all the containers, use the command below: -``` -docker compose down -``` From 2992b5b09344f78e039c1aa05088cbf737867d7f Mon Sep 17 00:00:00 2001 From: alexsin368 Date: Fri, 8 Nov 2024 17:56:04 -0800 Subject: [PATCH 30/34] CodeGen: add gaudi deployment sample guide Signed-off-by: alexsin368 --- examples/CodeGen/deploy/gaudi.md | 372 +++++++++++++++++++++++++++++++ 1 file changed, 372 insertions(+) create mode 100644 examples/CodeGen/deploy/gaudi.md diff --git a/examples/CodeGen/deploy/gaudi.md b/examples/CodeGen/deploy/gaudi.md new file mode 100644 index 00000000..9ad3971d --- /dev/null +++ b/examples/CodeGen/deploy/gaudi.md @@ -0,0 +1,372 @@ +# Single node on-prem deployment with vLLM or TGI on Gaudi AI Accelerator + +This deployment section covers single-node on-prem deployment of the CodeGen +example with OPEA comps to deploy using the TGI service. We will be showcasing how +to build an e2e CodeGen solution with the CodeLlama-7b-hf model, +deployed on Intel® Tiber™ AI Cloud (ITAC). To quickly learn about OPEA in just 5 minutes and set up the required hardware and software, please follow the instructions in the +[Getting Started](https://opea-project.github.io/latest/getting-started/README.html) section. If you do +not have an ITAC instance or the hardware is not supported in the ITAC yet, you can still run this on-prem. + +## Overview + +The CodeGen use case uses a single microservice called LLM. In this tutorial, we +will walk through the steps on how on enable it from OPEA GenAIComps to deploy on +a single node TGI megaservice solution. + +The solution is aimed to show how to use the CodeLlama-7b-hf model on the Intel® +Gaudi® AI Accelerator. We will go through how to setup docker containers to start +the microservice and megaservice. The solution will then take text input as the +prompt and generate code accordingly. It is deployed with a UI with 2 modes to +choose from: + +1. Svelte-Based UI +2. React-Based UI + +The React-based UI is optional, but this feature is supported in this example if you +are interested in using it. + +Below is the list of content we will be covering in this tutorial: + +1. Prerequisites +2. Prepare (Building / Pulling) Docker images +3. Use case setup +4. Deploy the use case +5. Interacting with CodeGen deployment + +## Prerequisites + +The first step is to clone the GenAIExamples and GenAIComps. GenAIComps are +fundamental necessary components used to build examples you find in +GenAIExamples and deploy them as microservices. + +```bash +git clone https://github.com/opea-project/GenAIComps.git +git clone https://github.com/opea-project/GenAIExamples.git +``` + +The examples utilize model weights from HuggingFace and langchain. + +Setup your [HuggingFace](https://huggingface.co/) account and generate +[user access token](https://huggingface.co/docs/transformers.js/en/guides/private#step-1-generating-a-user-access-token). + +Setup the HuggingFace token +``` +export HUGGINGFACEHUB_API_TOKEN="Your_Huggingface_API_Token" +``` + +Additionally, if you plan to use the default model CodeLlama-7b-hf, you will +need to [request access](https://huggingface.co/meta-llama/CodeLlama-7b-hf) from HuggingFace. + +The example requires you to set the `host_ip` to deploy the microservices on +endpoint enabled with ports. Set the host_ip env variable +``` +export host_ip=$(hostname -I | awk '{print $1}') +``` + +Make sure to setup Proxies if you are behind a firewall +``` +export no_proxy=${your_no_proxy},$host_ip +export http_proxy=${your_http_proxy} +export https_proxy=${your_http_proxy} +``` + +## Prepare (Building / Pulling) Docker images + +This step will involve building/pulling relevant docker +images with step-by-step process along with sanity check in the end. For +CodeGen, the following docker images will be needed: LLM with TGI. +Additionally, you will need to build docker images for the +CodeGen megaservice, and UI (React UI is optional). In total, +there are **3 required docker images** and an optional docker image. + +### Build/Pull Microservice image + +::::::{tab-set} + +:::::{tab-item} Pull +:sync: Pull + +If you decide to pull the docker containers and not build them locally, +you can proceed to the next step where all the necessary containers will +be pulled in from dockerhub. + +::::: +:::::{tab-item} Build +:sync: Build + +From within the `GenAIComps` folder, checkout the release tag. +``` +cd GenAIComps +git checkout tags/v1.1 +``` + +#### Build LLM Image + +```bash +docker build --no-cache -t opea/llm-tgi:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/text-generation/tgi/Dockerfile . +``` + +### Build Mega Service images + +The Megaservice is a pipeline that channels data through different +microservices, each performing varied tasks. The LLM microservice and +flow of data are defined in the `codegen.py` file. You can also add or +remove microservices and customize the megaservice to suit your needs. + +Build the megaservice image for this use case + +```bash +cd .. +cd GenAIExamples +git checkout tags/v1.1 +cd CodeGen +``` + +```bash +docker build --no-cache -t opea/codegen:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile . +cd ../.. +``` + +### Build the UI Image + +You can build 2 modes of UI + +*Svelte UI* + +```bash +cd GenAIExamples/CodeGen/ui/ +docker build --no-cache -t opea/codegen-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile . +cd ../../.. +``` + +*React UI (Optional)* +If you want a React-based frontend. + +```bash +cd GenAIExamples/CodeGen/ui/ +docker build --no-cache -t opea/codegen-react-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile.react . +cd ../../.. +``` + +### Sanity Check +Check if you have the following set of docker images by running the command `docker images` before moving on to the next step: + +* `opea/llm-tgi:latest` +* `opea/codegen:latest` +* `opea/codegen-ui:latest` +* `opea/codegen-react-ui:latest` (optional) + +::::: +:::::: + +## Use Case Setup + +The use case will use the following combination of GenAIComps and tools + +|Use Case Components | Tools | Model | Service Type | +|---------------- |--------------|-----------------------------|-------| +|LLM | TGI | meta-llama/CodeLlama-7b-hf | OPEA Microservice | +|UI | | NA | Gateway Service | + +Tools and models mentioned in the table are configurable either through the +environment variables or `compose.yaml` file. + +Set the necessary environment variables to setup the use case case by running the `set_env.sh` script. +Here is where the environment variable `LLM_MODEL_ID` is set, and you can change it to another model +by specifying the HuggingFace model card ID. + +```bash +cd GenAIExamples/CodeGen/docker_compose/ +source ./set_env.sh +cd ../../.. +``` + +## Deploy the Use Case + +In this tutorial, we will be deploying via docker compose with the provided +YAML file. The docker compose instructions should be starting all the +above mentioned services as containers. + +```bash +cd GenAIExamples/CodeGen/docker_compose/intel/hpu/gaudi +docker compose up -d +``` + + +### Checks to Ensure the Services are Running +#### Check Startup and Env Variables +Check the start up log by running `docker compose logs` to ensure there are no errors. +The warning messages print out the variables if they are **NOT** set. + +Here are some sample messages if proxy environment variables are not set: + + WARN[0000] The "no_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "https_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "http_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "no_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "https_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "http_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "no_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "http_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "https_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "no_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "http_proxy" variable is not set. Defaulting to a blank string. + WARN[0000] The "https_proxy" variable is not set. Defaulting to a blank string. + +#### Check the Container Status + +Check if all the containers launched via docker compose has started. + +The CodeGen example starts 4 docker containers. Check that these docker +containers are all running, i.e, all the containers `STATUS` are `Up`. +You can do this with the `docker ps -a` command. + +``` +CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES +bbd235074c3d opea/codegen-ui:latest "docker-entrypoint.s…" About a minute ago Up About a minute 0.0.0.0:5173->5173/tcp, :::5173->5173/tcp codegen-gaudi-ui-server +8d3872ca66fa opea/codegen:latest "python codegen.py" About a minute ago Up About a minute 0.0.0.0:7778->7778/tcp, :::7778->7778/tcp codegen-gaudi-backend-server +b9fc39f51cdb opea/llm-tgi:latest "bash entrypoint.sh" About a minute ago Up About a minute 0.0.0.0:9000->9000/tcp, :::9000->9000/tcp llm-tgi-gaudi-server +39994e007f15 ghcr.io/huggingface/tgi-gaudi:2.0.1 "text-generation-lau…" About a minute ago Up About a minute 0.0.0.0:8028->80/tcp, :::8028->80/tcp tgi-gaudi-server +``` + +## Interacting with CodeGen for Deployment + +This section will walk you through the different ways to interact with +the microservices deployed. After a couple minutes, rerun `docker ps -a` +to ensure all the docker containers are still up and running. Then proceed +to validate each microservice and megaservice. + +### TGI Service + +```bash +curl http://${host_ip}:8028/generate \ + -X POST \ + -d '{"inputs":"Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception.","parameters":{"max_new_tokens":256, "do_sample": true}}' \ + -H 'Content-Type: application/json' +``` + +Here is the output: + +``` +{"generated_text":"\n\nIO iflow diagram:\n\n![IO flow diagram(s)](TodoList.iflow.svg)\n\n### TDD Kata walkthrough\n\n1. Start with a user story. We will add story tests later. In this case, we'll choose a story about adding a TODO:\n ```ruby\n as a user,\n i want to add a todo,\n so that i can get a todo list.\n\n conformance:\n - a new todo is added to the list\n - if the todo text is empty, raise an exception\n ```\n\n1. Write the first test:\n ```ruby\n feature Testing the addition of a todo to the list\n\n given a todo list empty list\n when a user adds a todo\n the todo should be added to the list\n\n inputs:\n when_values: [[\"A\"]]\n\n output validations:\n - todo_list contains { text:\"A\" }\n ```\n\n1. Write the first step implementation in any programming language you like. In this case, we will choose Ruby:\n ```ruby\n def add_"} +``` + +### LLM Microservice + +```bash +curl http://${host_ip}:9000/v1/chat/completions\ + -X POST \ + -d '{"query":"Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception.","max_tokens":256,"top_k":10,"top_p":0.95,"typical_p":0.95,"temperature":0.01,"repetition_penalty":1.03,"streaming":true}' \ + -H 'Content-Type: application/json' +``` + +The output is given one character at a time. It is too long to show +here but the last item will be +``` +data: [DONE] +``` + +### MegaService + +```bash +curl http://${host_ip}:7778/v1/codegen -H "Content-Type: application/json" -d '{ + "messages": "Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception." + }' +``` + +The output is given one character at a time. It is too long to show +here but the last item will be +``` +data: [DONE] +``` + +## Launch UI +### Svelte UI +To access the frontend, open the following URL in your browser: http://{host_ip}:5173. By default, the UI runs on port 5173 internally. If you prefer to use a different host port to access the frontend, you can modify the port mapping in the `compose.yaml` file as shown below: +```bash + codegen-gaudi-ui-server: + image: ${REGISTRY:-opea}/codegen-ui:${TAG:-latest} + ... + ports: + - "5173:5173" +``` + +### React-Based UI (Optional) +To access the React-based frontend, modify the UI service in the `compose.yaml` file. Replace `codegen-gaudi-ui-server` service with the codegen-gaudi-react-ui-server service as per the config below: +```bash +codegen-gaudi-react-ui-server: + image: ${REGISTRY:-opea}/codegen-react-ui:${TAG:-latest} + container_name: codegen-gaudi-react-ui-server + environment: + - no_proxy=${no_proxy} + - https_proxy=${https_proxy} + - http_proxy=${http_proxy} + - APP_CODE_GEN_URL=${BACKEND_SERVICE_ENDPOINT} + depends_on: + - codegen-gaudi-backend-server + ports: + - "5174:80" + ipc: host + restart: always +``` +Once the services are up, open the following URL in your browser: http://{host_ip}:5174. By default, the UI runs on port 80 internally. If you prefer to use a different host port to access the frontend, you can modify the port mapping in the `compose.yaml` file as shown below: +```bash + codegen-gaudi-react-ui-server: + image: ${REGISTRY:-opea}/codegen-react-ui:${TAG:-latest} + ... + ports: + - "80:80" +``` + +## Check Docker Container Logs + +You can check the log of a container by running this command: + +```bash +docker logs -t +``` + +You can also check the overall logs with the following command, where the +`compose.yaml` is the megaservice docker-compose configuration file. + +Assumming you are still in this directory `GenAIExamples/CodeGen/docker_compose/intel/hpu/gaudi`, +run the following command to check the logs: +```bash +docker compose -f compose.yaml logs +``` + +View the docker input parameters in `./CodeGen/docker_compose/intel/hpu/gaudi/compose.yaml` + +```yaml + tgi-service: + image: ghcr.io/huggingface/tgi-gaudi:2.0.1 + container_name: tgi-gaudi-server + ports: + - "8028:80" + volumes: + - "./data:/data" + environment: + no_proxy: ${no_proxy} + http_proxy: ${http_proxy} + https_proxy: ${https_proxy} + HABANA_VISIBLE_DEVICES: all + OMPI_MCA_btl_vader_single_copy_mechanism: none + HF_TOKEN: ${HUGGINGFACEHUB_API_TOKEN} + runtime: habana + cap_add: + - SYS_NICE + ipc: host + command: --model-id ${LLM_MODEL_ID} --max-input-length 1024 --max-total-tokens 2048 +``` + +The input `--model-id` is `${LLM_MODEL_ID}`. Ensure the environment variable `LLM_MODEL_ID` +is set correctly. Check spelling. Whenever this is changed, restart the containers to use +the newly selected model. + + +## Stop the services + +Once you are done with the entire pipeline and wish to stop and remove all the containers, use the command below: +``` +docker compose down +``` From 2636a8211b60d62180be52270140f5bd67c3be12 Mon Sep 17 00:00:00 2001 From: alexsin368 Date: Tue, 12 Nov 2024 16:17:53 -0800 Subject: [PATCH 31/34] Revert "CodeGen: add gaudi deployment sample guide" This reverts commit e3790579d5f2944b58b9d1065757a0a76a6d1ec9. --- examples/CodeGen/deploy/gaudi.md | 372 ------------------------------- 1 file changed, 372 deletions(-) delete mode 100644 examples/CodeGen/deploy/gaudi.md diff --git a/examples/CodeGen/deploy/gaudi.md b/examples/CodeGen/deploy/gaudi.md deleted file mode 100644 index 9ad3971d..00000000 --- a/examples/CodeGen/deploy/gaudi.md +++ /dev/null @@ -1,372 +0,0 @@ -# Single node on-prem deployment with vLLM or TGI on Gaudi AI Accelerator - -This deployment section covers single-node on-prem deployment of the CodeGen -example with OPEA comps to deploy using the TGI service. We will be showcasing how -to build an e2e CodeGen solution with the CodeLlama-7b-hf model, -deployed on Intel® Tiber™ AI Cloud (ITAC). To quickly learn about OPEA in just 5 minutes and set up the required hardware and software, please follow the instructions in the -[Getting Started](https://opea-project.github.io/latest/getting-started/README.html) section. If you do -not have an ITAC instance or the hardware is not supported in the ITAC yet, you can still run this on-prem. - -## Overview - -The CodeGen use case uses a single microservice called LLM. In this tutorial, we -will walk through the steps on how on enable it from OPEA GenAIComps to deploy on -a single node TGI megaservice solution. - -The solution is aimed to show how to use the CodeLlama-7b-hf model on the Intel® -Gaudi® AI Accelerator. We will go through how to setup docker containers to start -the microservice and megaservice. The solution will then take text input as the -prompt and generate code accordingly. It is deployed with a UI with 2 modes to -choose from: - -1. Svelte-Based UI -2. React-Based UI - -The React-based UI is optional, but this feature is supported in this example if you -are interested in using it. - -Below is the list of content we will be covering in this tutorial: - -1. Prerequisites -2. Prepare (Building / Pulling) Docker images -3. Use case setup -4. Deploy the use case -5. Interacting with CodeGen deployment - -## Prerequisites - -The first step is to clone the GenAIExamples and GenAIComps. GenAIComps are -fundamental necessary components used to build examples you find in -GenAIExamples and deploy them as microservices. - -```bash -git clone https://github.com/opea-project/GenAIComps.git -git clone https://github.com/opea-project/GenAIExamples.git -``` - -The examples utilize model weights from HuggingFace and langchain. - -Setup your [HuggingFace](https://huggingface.co/) account and generate -[user access token](https://huggingface.co/docs/transformers.js/en/guides/private#step-1-generating-a-user-access-token). - -Setup the HuggingFace token -``` -export HUGGINGFACEHUB_API_TOKEN="Your_Huggingface_API_Token" -``` - -Additionally, if you plan to use the default model CodeLlama-7b-hf, you will -need to [request access](https://huggingface.co/meta-llama/CodeLlama-7b-hf) from HuggingFace. - -The example requires you to set the `host_ip` to deploy the microservices on -endpoint enabled with ports. Set the host_ip env variable -``` -export host_ip=$(hostname -I | awk '{print $1}') -``` - -Make sure to setup Proxies if you are behind a firewall -``` -export no_proxy=${your_no_proxy},$host_ip -export http_proxy=${your_http_proxy} -export https_proxy=${your_http_proxy} -``` - -## Prepare (Building / Pulling) Docker images - -This step will involve building/pulling relevant docker -images with step-by-step process along with sanity check in the end. For -CodeGen, the following docker images will be needed: LLM with TGI. -Additionally, you will need to build docker images for the -CodeGen megaservice, and UI (React UI is optional). In total, -there are **3 required docker images** and an optional docker image. - -### Build/Pull Microservice image - -::::::{tab-set} - -:::::{tab-item} Pull -:sync: Pull - -If you decide to pull the docker containers and not build them locally, -you can proceed to the next step where all the necessary containers will -be pulled in from dockerhub. - -::::: -:::::{tab-item} Build -:sync: Build - -From within the `GenAIComps` folder, checkout the release tag. -``` -cd GenAIComps -git checkout tags/v1.1 -``` - -#### Build LLM Image - -```bash -docker build --no-cache -t opea/llm-tgi:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/text-generation/tgi/Dockerfile . -``` - -### Build Mega Service images - -The Megaservice is a pipeline that channels data through different -microservices, each performing varied tasks. The LLM microservice and -flow of data are defined in the `codegen.py` file. You can also add or -remove microservices and customize the megaservice to suit your needs. - -Build the megaservice image for this use case - -```bash -cd .. -cd GenAIExamples -git checkout tags/v1.1 -cd CodeGen -``` - -```bash -docker build --no-cache -t opea/codegen:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile . -cd ../.. -``` - -### Build the UI Image - -You can build 2 modes of UI - -*Svelte UI* - -```bash -cd GenAIExamples/CodeGen/ui/ -docker build --no-cache -t opea/codegen-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile . -cd ../../.. -``` - -*React UI (Optional)* -If you want a React-based frontend. - -```bash -cd GenAIExamples/CodeGen/ui/ -docker build --no-cache -t opea/codegen-react-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile.react . -cd ../../.. -``` - -### Sanity Check -Check if you have the following set of docker images by running the command `docker images` before moving on to the next step: - -* `opea/llm-tgi:latest` -* `opea/codegen:latest` -* `opea/codegen-ui:latest` -* `opea/codegen-react-ui:latest` (optional) - -::::: -:::::: - -## Use Case Setup - -The use case will use the following combination of GenAIComps and tools - -|Use Case Components | Tools | Model | Service Type | -|---------------- |--------------|-----------------------------|-------| -|LLM | TGI | meta-llama/CodeLlama-7b-hf | OPEA Microservice | -|UI | | NA | Gateway Service | - -Tools and models mentioned in the table are configurable either through the -environment variables or `compose.yaml` file. - -Set the necessary environment variables to setup the use case case by running the `set_env.sh` script. -Here is where the environment variable `LLM_MODEL_ID` is set, and you can change it to another model -by specifying the HuggingFace model card ID. - -```bash -cd GenAIExamples/CodeGen/docker_compose/ -source ./set_env.sh -cd ../../.. -``` - -## Deploy the Use Case - -In this tutorial, we will be deploying via docker compose with the provided -YAML file. The docker compose instructions should be starting all the -above mentioned services as containers. - -```bash -cd GenAIExamples/CodeGen/docker_compose/intel/hpu/gaudi -docker compose up -d -``` - - -### Checks to Ensure the Services are Running -#### Check Startup and Env Variables -Check the start up log by running `docker compose logs` to ensure there are no errors. -The warning messages print out the variables if they are **NOT** set. - -Here are some sample messages if proxy environment variables are not set: - - WARN[0000] The "no_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "https_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "http_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "no_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "https_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "http_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "no_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "http_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "https_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "no_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "http_proxy" variable is not set. Defaulting to a blank string. - WARN[0000] The "https_proxy" variable is not set. Defaulting to a blank string. - -#### Check the Container Status - -Check if all the containers launched via docker compose has started. - -The CodeGen example starts 4 docker containers. Check that these docker -containers are all running, i.e, all the containers `STATUS` are `Up`. -You can do this with the `docker ps -a` command. - -``` -CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES -bbd235074c3d opea/codegen-ui:latest "docker-entrypoint.s…" About a minute ago Up About a minute 0.0.0.0:5173->5173/tcp, :::5173->5173/tcp codegen-gaudi-ui-server -8d3872ca66fa opea/codegen:latest "python codegen.py" About a minute ago Up About a minute 0.0.0.0:7778->7778/tcp, :::7778->7778/tcp codegen-gaudi-backend-server -b9fc39f51cdb opea/llm-tgi:latest "bash entrypoint.sh" About a minute ago Up About a minute 0.0.0.0:9000->9000/tcp, :::9000->9000/tcp llm-tgi-gaudi-server -39994e007f15 ghcr.io/huggingface/tgi-gaudi:2.0.1 "text-generation-lau…" About a minute ago Up About a minute 0.0.0.0:8028->80/tcp, :::8028->80/tcp tgi-gaudi-server -``` - -## Interacting with CodeGen for Deployment - -This section will walk you through the different ways to interact with -the microservices deployed. After a couple minutes, rerun `docker ps -a` -to ensure all the docker containers are still up and running. Then proceed -to validate each microservice and megaservice. - -### TGI Service - -```bash -curl http://${host_ip}:8028/generate \ - -X POST \ - -d '{"inputs":"Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception.","parameters":{"max_new_tokens":256, "do_sample": true}}' \ - -H 'Content-Type: application/json' -``` - -Here is the output: - -``` -{"generated_text":"\n\nIO iflow diagram:\n\n![IO flow diagram(s)](TodoList.iflow.svg)\n\n### TDD Kata walkthrough\n\n1. Start with a user story. We will add story tests later. In this case, we'll choose a story about adding a TODO:\n ```ruby\n as a user,\n i want to add a todo,\n so that i can get a todo list.\n\n conformance:\n - a new todo is added to the list\n - if the todo text is empty, raise an exception\n ```\n\n1. Write the first test:\n ```ruby\n feature Testing the addition of a todo to the list\n\n given a todo list empty list\n when a user adds a todo\n the todo should be added to the list\n\n inputs:\n when_values: [[\"A\"]]\n\n output validations:\n - todo_list contains { text:\"A\" }\n ```\n\n1. Write the first step implementation in any programming language you like. In this case, we will choose Ruby:\n ```ruby\n def add_"} -``` - -### LLM Microservice - -```bash -curl http://${host_ip}:9000/v1/chat/completions\ - -X POST \ - -d '{"query":"Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception.","max_tokens":256,"top_k":10,"top_p":0.95,"typical_p":0.95,"temperature":0.01,"repetition_penalty":1.03,"streaming":true}' \ - -H 'Content-Type: application/json' -``` - -The output is given one character at a time. It is too long to show -here but the last item will be -``` -data: [DONE] -``` - -### MegaService - -```bash -curl http://${host_ip}:7778/v1/codegen -H "Content-Type: application/json" -d '{ - "messages": "Implement a high-level API for a TODO list application. The API takes as input an operation request and updates the TODO list in place. If the request is invalid, raise an exception." - }' -``` - -The output is given one character at a time. It is too long to show -here but the last item will be -``` -data: [DONE] -``` - -## Launch UI -### Svelte UI -To access the frontend, open the following URL in your browser: http://{host_ip}:5173. By default, the UI runs on port 5173 internally. If you prefer to use a different host port to access the frontend, you can modify the port mapping in the `compose.yaml` file as shown below: -```bash - codegen-gaudi-ui-server: - image: ${REGISTRY:-opea}/codegen-ui:${TAG:-latest} - ... - ports: - - "5173:5173" -``` - -### React-Based UI (Optional) -To access the React-based frontend, modify the UI service in the `compose.yaml` file. Replace `codegen-gaudi-ui-server` service with the codegen-gaudi-react-ui-server service as per the config below: -```bash -codegen-gaudi-react-ui-server: - image: ${REGISTRY:-opea}/codegen-react-ui:${TAG:-latest} - container_name: codegen-gaudi-react-ui-server - environment: - - no_proxy=${no_proxy} - - https_proxy=${https_proxy} - - http_proxy=${http_proxy} - - APP_CODE_GEN_URL=${BACKEND_SERVICE_ENDPOINT} - depends_on: - - codegen-gaudi-backend-server - ports: - - "5174:80" - ipc: host - restart: always -``` -Once the services are up, open the following URL in your browser: http://{host_ip}:5174. By default, the UI runs on port 80 internally. If you prefer to use a different host port to access the frontend, you can modify the port mapping in the `compose.yaml` file as shown below: -```bash - codegen-gaudi-react-ui-server: - image: ${REGISTRY:-opea}/codegen-react-ui:${TAG:-latest} - ... - ports: - - "80:80" -``` - -## Check Docker Container Logs - -You can check the log of a container by running this command: - -```bash -docker logs -t -``` - -You can also check the overall logs with the following command, where the -`compose.yaml` is the megaservice docker-compose configuration file. - -Assumming you are still in this directory `GenAIExamples/CodeGen/docker_compose/intel/hpu/gaudi`, -run the following command to check the logs: -```bash -docker compose -f compose.yaml logs -``` - -View the docker input parameters in `./CodeGen/docker_compose/intel/hpu/gaudi/compose.yaml` - -```yaml - tgi-service: - image: ghcr.io/huggingface/tgi-gaudi:2.0.1 - container_name: tgi-gaudi-server - ports: - - "8028:80" - volumes: - - "./data:/data" - environment: - no_proxy: ${no_proxy} - http_proxy: ${http_proxy} - https_proxy: ${https_proxy} - HABANA_VISIBLE_DEVICES: all - OMPI_MCA_btl_vader_single_copy_mechanism: none - HF_TOKEN: ${HUGGINGFACEHUB_API_TOKEN} - runtime: habana - cap_add: - - SYS_NICE - ipc: host - command: --model-id ${LLM_MODEL_ID} --max-input-length 1024 --max-total-tokens 2048 -``` - -The input `--model-id` is `${LLM_MODEL_ID}`. Ensure the environment variable `LLM_MODEL_ID` -is set correctly. Check spelling. Whenever this is changed, restart the containers to use -the newly selected model. - - -## Stop the services - -Once you are done with the entire pipeline and wish to stop and remove all the containers, use the command below: -``` -docker compose down -``` From 2228ae628446114012e0a5e325ac52fee0d52c32 Mon Sep 17 00:00:00 2001 From: alexsin368 Date: Thu, 14 Nov 2024 13:27:00 -0800 Subject: [PATCH 32/34] signing off latest commit Signed-off-by: alexsin368 --- examples/ChatQnA/deploy/gaudi.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/ChatQnA/deploy/gaudi.md b/examples/ChatQnA/deploy/gaudi.md index 09aa30a8..f11fa2f4 100644 --- a/examples/ChatQnA/deploy/gaudi.md +++ b/examples/ChatQnA/deploy/gaudi.md @@ -957,4 +957,4 @@ docker compose -f compose_vllm.yaml down docker compose -f compose.yaml down ``` ::: -:::: +:::: \ No newline at end of file From 925c8395ac59cb3ec488d930814520f782a2450f Mon Sep 17 00:00:00 2001 From: alexsin368 Date: Fri, 15 Nov 2024 11:11:42 -0800 Subject: [PATCH 33/34] update with tag 1.1 Signed-off-by: alexsin368 --- examples/ChatQnA/deploy/gaudi.md | 104 +++++++++++++++---------------- 1 file changed, 52 insertions(+), 52 deletions(-) diff --git a/examples/ChatQnA/deploy/gaudi.md b/examples/ChatQnA/deploy/gaudi.md index f11fa2f4..d2ce84a3 100644 --- a/examples/ChatQnA/deploy/gaudi.md +++ b/examples/ChatQnA/deploy/gaudi.md @@ -104,31 +104,31 @@ be pulled in from dockerhub. From within the `GenAIComps` folder, checkout the release tag. ``` cd GenAIComps -git checkout tags/v1.0 +git checkout tags/v1.1 ``` #### Build Dataprep Image ```bash -docker build --no-cache -t opea/dataprep-redis:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/dataprep/redis/langchain/Dockerfile . +docker build --no-cache -t opea/dataprep-redis:1.1 --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/dataprep/redis/langchain/Dockerfile . ``` #### Build Embedding Image ```bash -docker build --no-cache -t opea/embedding-tei:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/embeddings/tei/langchain/Dockerfile . +docker build --no-cache -t opea/embedding-tei:1.1 --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/embeddings/tei/langchain/Dockerfile . ``` #### Build Retriever Image ```bash -docker build --no-cache -t opea/retriever-redis:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/retrievers/redis/langchain/Dockerfile . +docker build --no-cache -t opea/retriever-redis:1.1 --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/retrievers/redis/langchain/Dockerfile . ``` #### Build Rerank Image ```bash -docker build --no-cache -t opea/reranking-tei:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/reranks/tei/Dockerfile . +docker build --no-cache -t opea/reranking-tei:1.1 --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/reranks/tei/Dockerfile . ``` #### Build LLM Image @@ -140,12 +140,12 @@ docker build --no-cache -t opea/reranking-tei:latest --build-arg https_proxy=$ht Build vLLM docker image with hpu support ``` -docker build --no-cache -t opea/llm-vllm-hpu:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/text-generation/vllm/langchain/dependency/Dockerfile.intel_hpu . +docker build --no-cache -t opea/llm-vllm-hpu:1.1 --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/text-generation/vllm/langchain/dependency/Dockerfile.intel_hpu . ``` Build vLLM Microservice image ``` -docker build --no-cache -t opea/llm-vllm:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/text-generation/vllm/langchain/Dockerfile . +docker build --no-cache -t opea/llm-vllm:1.1 --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/text-generation/vllm/langchain/Dockerfile . cd .. ``` ::: @@ -153,7 +153,7 @@ cd .. :sync: TGI ```bash -docker build --no-cache -t opea/llm-tgi:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/text-generation/tgi/Dockerfile . +docker build --no-cache -t opea/llm-tgi:1.1 --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/text-generation/tgi/Dockerfile . ``` ::: :::: @@ -165,7 +165,7 @@ Since a TEI Gaudi Docker image hasn't been published, we'll need to build it fro ```bash git clone https://github.com/huggingface/tei-gaudi cd tei-gaudi/ -docker build --no-cache -f Dockerfile-hpu -t opea/tei-gaudi:latest . +docker build --no-cache -f Dockerfile-hpu -t opea/tei-gaudi:1.1 . cd .. ``` @@ -184,12 +184,12 @@ Build the megaservice image for this use case ``` cd .. cd GenAIExamples -git checkout tags/v1.0 +git checkout tags/v1.1 cd ChatQnA ``` ```bash -docker build --no-cache -t opea/chatqna:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile . +docker build --no-cache -t opea/chatqna:1.1 --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile . cd ../.. ``` @@ -199,7 +199,7 @@ If you want to enable guardrails microservice in the pipeline, please use the be ```bash cd GenAIExamples/ChatQnA/ -docker build --no-cache -t opea/chatqna-guardrails:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile.guardrails . +docker build --no-cache -t opea/chatqna-guardrails:1.1 --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile.guardrails . cd ../.. ``` @@ -211,7 +211,7 @@ As mentioned, you can build 2 modes of UI ```bash cd GenAIExamples/ChatQnA/ui/ -docker build --no-cache -t opea/chatqna-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile . +docker build --no-cache -t opea/chatqna-ui:1.1 --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile . cd ../../.. ``` @@ -220,7 +220,7 @@ If you want a conversational experience with chatqna megaservice. ```bash cd GenAIExamples/ChatQnA/ui/ -docker build --no-cache -t opea/chatqna-conversation-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile.react . +docker build --no-cache -t opea/chatqna-conversation-ui:1.1 --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile.react . cd ../../.. ``` @@ -231,28 +231,28 @@ Check if you have the below set of docker images, before moving on to the next s :::{tab-item} vllm :sync: vllm -* opea/dataprep-redis:latest -* opea/embedding-tei:latest -* opea/retriever-redis:latest -* opea/reranking-tei:latest -* opea/tei-gaudi:latest -* opea/chatqna:latest or opea/chatqna-guardrails:latest -* opea/chatqna:latest -* opea/chatqna-ui:latest -* opea/vllm:latest -* opea/llm-vllm:latest +* opea/dataprep-redis:1.1 +* opea/embedding-tei:1.1 +* opea/retriever-redis:1.1 +* opea/reranking-tei:1.1 +* opea/tei-gaudi:1.1 +* opea/chatqna:1.1 or opea/chatqna-guardrails:1.1 +* opea/chatqna:1.1 +* opea/chatqna-ui:1.1 +* opea/vllm:1.1 +* opea/llm-vllm:1.1 ::: :::{tab-item} TGI :sync: TGI -* opea/dataprep-redis:latest -* opea/embedding-tei:latest -* opea/retriever-redis:latest -* opea/reranking-tei:latest -* opea/tei-gaudi:latest -* opea/chatqna:latest or opea/chatqna-guardrails:latest -* opea/chatqna-ui:latest -* opea/llm-tgi:latest +* opea/dataprep-redis:1.1 +* opea/embedding-tei:1.1 +* opea/retriever-redis:1.1 +* opea/reranking-tei:1.1 +* opea/tei-gaudi:1.1 +* opea/chatqna:1.1 or opea/chatqna-guardrails:1.1 +* opea/chatqna-ui:1.1 +* opea/llm-tgi:1.1 ::: :::: @@ -403,15 +403,15 @@ To do a quick sanity check, try `docker ps -a` to see if all the containers are :sync: vllm ```bash CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES -42c8d5ec67e9 opea/chatqna-ui:latest "docker-entrypoint.s…" About a minute ago Up About a minute 0.0.0.0:5173->5173/tcp, :::5173->5173/tcp chatqna-gaudi-ui-server -7f7037a75f8b opea/chatqna:latest "python chatqna.py" About a minute ago Up About a minute 0.0.0.0:8888->8888/tcp, :::8888->8888/tcp chatqna-gaudi-backend-server -4049c181da93 opea/embedding-tei:latest "python embedding_te…" About a minute ago Up About a minute 0.0.0.0:6000->6000/tcp, :::6000->6000/tcp embedding-tei-server -171816f0a789 opea/dataprep-redis:latest "python prepare_doc_…" About a minute ago Up About a minute 0.0.0.0:6007->6007/tcp, :::6007->6007/tcp dataprep-redis-server -10ee6dec7d37 opea/llm-vllm:latest "bash entrypoint.sh" About a minute ago Up About a minute 0.0.0.0:9000->9000/tcp, :::9000->9000/tcp llm-vllm-gaudi-server -ce4e7802a371 opea/retriever-redis:latest "python retriever_re…" About a minute ago Up About a minute 0.0.0.0:7000->7000/tcp, :::7000->7000/tcp retriever-redis-server -be6cd2d0ea38 opea/reranking-tei:latest "python reranking_te…" About a minute ago Up About a minute 0.0.0.0:8000->8000/tcp, :::8000->8000/tcp reranking-tei-gaudi-server -cc45ff032e8c opea/tei-gaudi:latest "text-embeddings-rou…" About a minute ago Up About a minute 0.0.0.0:8090->80/tcp, :::8090->80/tcp tei-embedding-gaudi-server -4969ec3aea02 opea/llm-vllm-hpu:latest "/bin/bash -c 'expor…" About a minute ago Up About a minute 0.0.0.0:8007->80/tcp, :::8007->80/tcp vllm-gaudi-server +42c8d5ec67e9 opea/chatqna-ui:1.1 "docker-entrypoint.s…" About a minute ago Up About a minute 0.0.0.0:5173->5173/tcp, :::5173->5173/tcp chatqna-gaudi-ui-server +7f7037a75f8b opea/chatqna:1.1 "python chatqna.py" About a minute ago Up About a minute 0.0.0.0:8888->8888/tcp, :::8888->8888/tcp chatqna-gaudi-backend-server +4049c181da93 opea/embedding-tei:1.1 "python embedding_te…" About a minute ago Up About a minute 0.0.0.0:6000->6000/tcp, :::6000->6000/tcp embedding-tei-server +171816f0a789 opea/dataprep-redis:1.1 "python prepare_doc_…" About a minute ago Up About a minute 0.0.0.0:6007->6007/tcp, :::6007->6007/tcp dataprep-redis-server +10ee6dec7d37 opea/llm-vllm:1.1 "bash entrypoint.sh" About a minute ago Up About a minute 0.0.0.0:9000->9000/tcp, :::9000->9000/tcp llm-vllm-gaudi-server +ce4e7802a371 opea/retriever-redis:1.1 "python retriever_re…" About a minute ago Up About a minute 0.0.0.0:7000->7000/tcp, :::7000->7000/tcp retriever-redis-server +be6cd2d0ea38 opea/reranking-tei:1.1 "python reranking_te…" About a minute ago Up About a minute 0.0.0.0:8000->8000/tcp, :::8000->8000/tcp reranking-tei-gaudi-server +cc45ff032e8c opea/tei-gaudi:1.1 "text-embeddings-rou…" About a minute ago Up About a minute 0.0.0.0:8090->80/tcp, :::8090->80/tcp tei-embedding-gaudi-server +4969ec3aea02 opea/llm-vllm-hpu:1.1 "/bin/bash -c 'expor…" About a minute ago Up About a minute 0.0.0.0:8007->80/tcp, :::8007->80/tcp vllm-gaudi-server 0657cb66df78 redis/redis-stack:7.2.0-v9 "/entrypoint.sh" About a minute ago Up About a minute 0.0.0.0:6379->6379/tcp, :::6379->6379/tcp, 0.0.0.0:8001->8001/tcp, :::8001->8001/tcp redis-vector-db 684d3e9d204a ghcr.io/huggingface/text-embeddings-inference:cpu-1.2 "text-embeddings-rou…" About a minute ago Up About a minute 0.0.0.0:8808->80/tcp, :::8808->80/tcp tei-reranking-gaudi-server ``` @@ -421,15 +421,15 @@ cc45ff032e8c opea/tei-gaudi:latest "text-emb :sync: TGI ```bash CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES -0355d705484a opea/chatqna-ui:latest "docker-entrypoint.s…" 2 minutes ago Up 2 minutes 0.0.0.0:5173->5173/tcp, :::5173->5173/tcp chatqna-gaudi-ui-server -29a7a43abcef opea/chatqna:latest "python chatqna.py" 2 minutes ago Up 2 minutes 0.0.0.0:8888->8888/tcp, :::8888->8888/tcp chatqna-gaudi-backend-server -1eb6f5ad6f85 opea/llm-tgi:latest "bash entrypoint.sh" 2 minutes ago Up 2 minutes 0.0.0.0:9000->9000/tcp, :::9000->9000/tcp llm-tgi-gaudi-server -ad27729caf68 opea/reranking-tei:latest "python reranking_te…" 2 minutes ago Up 2 minutes 0.0.0.0:8000->8000/tcp, :::8000->8000/tcp reranking-tei-gaudi-server -84f02cf2a904 opea/dataprep-redis:latest "python prepare_doc_…" 2 minutes ago Up 2 minutes 0.0.0.0:6007->6007/tcp, :::6007->6007/tcp dataprep-redis-server -367459f6e65b opea/embedding-tei:latest "python embedding_te…" 2 minutes ago Up 2 minutes 0.0.0.0:6000->6000/tcp, :::6000->6000/tcp embedding-tei-server -8c78cde9f588 opea/retriever-redis:latest "python retriever_re…" 2 minutes ago Up 2 minutes 0.0.0.0:7000->7000/tcp, :::7000->7000/tcp retriever-redis-server +0355d705484a opea/chatqna-ui:1.1 "docker-entrypoint.s…" 2 minutes ago Up 2 minutes 0.0.0.0:5173->5173/tcp, :::5173->5173/tcp chatqna-gaudi-ui-server +29a7a43abcef opea/chatqna:1.1 "python chatqna.py" 2 minutes ago Up 2 minutes 0.0.0.0:8888->8888/tcp, :::8888->8888/tcp chatqna-gaudi-backend-server +1eb6f5ad6f85 opea/llm-tgi:1.1 "bash entrypoint.sh" 2 minutes ago Up 2 minutes 0.0.0.0:9000->9000/tcp, :::9000->9000/tcp llm-tgi-gaudi-server +ad27729caf68 opea/reranking-tei:1.1 "python reranking_te…" 2 minutes ago Up 2 minutes 0.0.0.0:8000->8000/tcp, :::8000->8000/tcp reranking-tei-gaudi-server +84f02cf2a904 opea/dataprep-redis:1.1 "python prepare_doc_…" 2 minutes ago Up 2 minutes 0.0.0.0:6007->6007/tcp, :::6007->6007/tcp dataprep-redis-server +367459f6e65b opea/embedding-tei:1.1 "python embedding_te…" 2 minutes ago Up 2 minutes 0.0.0.0:6000->6000/tcp, :::6000->6000/tcp embedding-tei-server +8c78cde9f588 opea/retriever-redis:1.1 "python retriever_re…" 2 minutes ago Up 2 minutes 0.0.0.0:7000->7000/tcp, :::7000->7000/tcp retriever-redis-server fa80772de92c ghcr.io/huggingface/tgi-gaudi:2.0.1 "text-generation-lau…" 2 minutes ago Up 2 minutes 0.0.0.0:8005->80/tcp, :::8005->80/tcp tgi-gaudi-server -581687a2cc1a opea/tei-gaudi:latest "text-embeddings-rou…" 2 minutes ago Up 2 minutes 0.0.0.0:8090->80/tcp, :::8090->80/tcp tei-embedding-gaudi-server +581687a2cc1a opea/tei-gaudi:1.1 "text-embeddings-rou…" 2 minutes ago Up 2 minutes 0.0.0.0:8090->80/tcp, :::8090->80/tcp tei-embedding-gaudi-server c59178629901 redis/redis-stack:7.2.0-v9 "/entrypoint.sh" 2 minutes ago Up 2 minutes 0.0.0.0:6379->6379/tcp, :::6379->6379/tcp, 0.0.0.0:8001->8001/tcp, :::8001->8001/tcp redis-vector-db 5c3a78144498 ghcr.io/huggingface/text-embeddings-inference:cpu-1.5 "text-embeddings-rou…" 2 minutes ago Up 2 minutes 0.0.0.0:8808->80/tcp, :::8808->80/tcp tei-reranking-gaudi-server ``` @@ -799,7 +799,7 @@ curl http://${host_ip}:9090/v1/guardrails\ To access the frontend, open the following URL in your browser: http://{host_ip}:5173. By default, the UI runs on port 5173 internally. If you prefer to use a different host port to access the frontend, you can modify the port mapping in the compose.yaml file as shown below: ```bash chaqna-gaudi-ui-server: - image: opea/chatqna-ui:latest + image: opea/chatqna-ui:1.1 ... ports: - "80:5173" @@ -809,7 +809,7 @@ To access the frontend, open the following URL in your browser: http://{host_ip} To access the Conversational UI (react based) frontend, modify the UI service in the compose.yaml file. Replace chaqna-gaudi-ui-server service with the chatqna-gaudi-conversation-ui-server service as per the config below: ```bash chaqna-gaudi-conversation-ui-server: - image: opea/chatqna-conversation-ui:latest + image: opea/chatqna-conversation-ui:1.1 container_name: chatqna-gaudi-conversation-ui-server environment: - APP_BACKEND_SERVICE_ENDPOINT=${BACKEND_SERVICE_ENDPOINT} @@ -824,7 +824,7 @@ chaqna-gaudi-conversation-ui-server: Once the services are up, open the following URL in your browser: http://{host_ip}:5174. By default, the UI runs on port 80 internally. If you prefer to use a different host port to access the frontend, you can modify the port mapping in the compose.yaml file as shown below: ``` chaqna-gaudi-conversation-ui-server: - image: opea/chatqna-conversation-ui:latest + image: opea/chatqna-conversation-ui:1.1 ... ports: - "80:80" From ca160c1833dbebc389de1cf5e3c639df85a00a05 Mon Sep 17 00:00:00 2001 From: alexsin368 Date: Fri, 15 Nov 2024 14:12:34 -0800 Subject: [PATCH 34/34] change version to generic TAG Signed-off-by: alexsin368 --- examples/ChatQnA/deploy/gaudi.md | 126 +++++++++++++++---------------- 1 file changed, 59 insertions(+), 67 deletions(-) diff --git a/examples/ChatQnA/deploy/gaudi.md b/examples/ChatQnA/deploy/gaudi.md index b039c354..e0679cd9 100644 --- a/examples/ChatQnA/deploy/gaudi.md +++ b/examples/ChatQnA/deploy/gaudi.md @@ -47,11 +47,13 @@ To summarize, Below is the flow of contents we will be covering in this tutorial First step is to clone the GenAIExamples and GenAIComps. GenAIComps are fundamental necessary components used to build examples you find in -GenAIExamples and deploy them as microservices. +GenAIExamples and deploy them as microservices. Also set the `TAG` +environment variable with the version. ``` git clone https://github.com/opea-project/GenAIComps.git git clone https://github.com/opea-project/GenAIExamples.git +export TAG=1.1 ``` The examples utilize model weights from HuggingFace and langchain. @@ -104,31 +106,31 @@ be pulled in from dockerhub. From within the `GenAIComps` folder, checkout the release tag. ``` cd GenAIComps -git checkout tags/v1.1 +git checkout tags/v${TAG} ``` #### Build Dataprep Image ```bash -docker build --no-cache -t opea/dataprep-redis:1.1 --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/dataprep/redis/langchain/Dockerfile . +docker build --no-cache -t opea/dataprep-redis:${TAG} --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/dataprep/redis/langchain/Dockerfile . ``` #### Build Embedding Image ```bash -docker build --no-cache -t opea/embedding-tei:1.1 --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/embeddings/tei/langchain/Dockerfile . +docker build --no-cache -t opea/embedding-tei:${TAG} --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/embeddings/tei/langchain/Dockerfile . ``` #### Build Retriever Image ```bash -docker build --no-cache -t opea/retriever-redis:1.1 --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/retrievers/redis/langchain/Dockerfile . +docker build --no-cache -t opea/retriever-redis:${TAG} --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/retrievers/redis/langchain/Dockerfile . ``` #### Build Rerank Image ```bash -docker build --no-cache -t opea/reranking-tei:1.1 --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/reranks/tei/Dockerfile . +docker build --no-cache -t opea/reranking-tei:${TAG} --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/reranks/tei/Dockerfile . ``` #### Build LLM Image @@ -140,12 +142,12 @@ docker build --no-cache -t opea/reranking-tei:1.1 --build-arg https_proxy=$https Build vLLM docker image with hpu support ``` -docker build --no-cache -t opea/llm-vllm-hpu:1.1 --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/text-generation/vllm/langchain/dependency/Dockerfile.intel_hpu . +docker build --no-cache -t opea/llm-vllm-hpu:${TAG} --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/text-generation/vllm/langchain/dependency/Dockerfile.intel_hpu . ``` Build vLLM Microservice image ``` -docker build --no-cache -t opea/llm-vllm:1.1 --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/text-generation/vllm/langchain/Dockerfile . +docker build --no-cache -t opea/llm-vllm:${TAG} --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/text-generation/vllm/langchain/Dockerfile . cd .. ``` ::: @@ -153,7 +155,7 @@ cd .. :sync: TGI ```bash -docker build --no-cache -t opea/llm-tgi:1.1 --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/text-generation/tgi/Dockerfile . +docker build --no-cache -t opea/llm-tgi:${TAG} --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/text-generation/tgi/Dockerfile . ``` ::: :::: @@ -165,7 +167,7 @@ Since a TEI Gaudi Docker image hasn't been published, we'll need to build it fro ```bash git clone https://github.com/huggingface/tei-gaudi cd tei-gaudi/ -docker build --no-cache -f Dockerfile-hpu -t opea/tei-gaudi:1.1 . +docker build --no-cache -f Dockerfile-hpu -t opea/tei-gaudi:${TAG} . cd .. ``` @@ -189,7 +191,7 @@ cd ChatQnA ``` ```bash -docker build --no-cache -t opea/chatqna:1.1 --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile . +docker build --no-cache -t opea/chatqna:${TAG} --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile . cd ../.. ``` @@ -199,7 +201,7 @@ If you want to enable guardrails microservice in the pipeline, please use the be ```bash cd GenAIExamples/ChatQnA/ -docker build --no-cache -t opea/chatqna-guardrails:1.1 --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile.guardrails . +docker build --no-cache -t opea/chatqna-guardrails:${TAG} --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile.guardrails . cd ../.. ``` @@ -211,7 +213,7 @@ As mentioned, you can build 2 modes of UI ```bash cd GenAIExamples/ChatQnA/ui/ -docker build --no-cache -t opea/chatqna-ui:1.1 --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile . +docker build --no-cache -t opea/chatqna-ui:${TAG} --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile . cd ../../.. ``` @@ -220,52 +222,41 @@ If you want a conversational experience with chatqna megaservice. ```bash cd GenAIExamples/ChatQnA/ui/ -docker build --no-cache -t opea/chatqna-conversation-ui:1.1 --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile.react . +docker build --no-cache -t opea/chatqna-conversation-ui:${TAG} --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile.react . cd ../../.. ``` ### Sanity Check -Check if you have the below set of docker images, before moving on to the next step: +Check if you have the below set of docker images before moving on to the next step. The tags are +based on what you set the environment variable `TAG` to. ::::{tab-set} :::{tab-item} vllm :sync: vllm -<<<<<<< HEAD -* opea/dataprep-redis:1.1 -* opea/embedding-tei:1.1 -* opea/retriever-redis:1.1 -* opea/reranking-tei:1.1 -* opea/tei-gaudi:1.1 -* opea/chatqna:1.1 or opea/chatqna-guardrails:1.1 -* opea/chatqna:1.1 -* opea/chatqna-ui:1.1 -* opea/vllm:1.1 -* opea/llm-vllm:1.1 -======= -* opea/dataprep-redis:latest -* opea/embedding-tei:latest -* opea/retriever-redis:latest -* opea/reranking-tei:latest -* opea/tei-gaudi:latest -* opea/chatqna:latest or opea/chatqna-guardrails:latest -* opea/chatqna:latest -* opea/chatqna-ui:latest -* opea/vllm:latest -* opea/llm-vllm:latest ->>>>>>> 2228ae628446114012e0a5e325ac52fee0d52c32 +* opea/dataprep-redis:${TAG} +* opea/embedding-tei:${TAG} +* opea/retriever-redis:${TAG} +* opea/reranking-tei:${TAG} +* opea/tei-gaudi:${TAG} +* opea/chatqna:${TAG} or opea/chatqna-guardrails:${TAG} +* opea/chatqna:${TAG} +* opea/chatqna-ui:${TAG} +* opea/vllm:${TAG} +* opea/llm-vllm:${TAG} + ::: :::{tab-item} TGI :sync: TGI -* opea/dataprep-redis:1.1 -* opea/embedding-tei:1.1 -* opea/retriever-redis:1.1 -* opea/reranking-tei:1.1 -* opea/tei-gaudi:1.1 -* opea/chatqna:1.1 or opea/chatqna-guardrails:1.1 -* opea/chatqna-ui:1.1 -* opea/llm-tgi:1.1 +* opea/dataprep-redis:${TAG} +* opea/embedding-tei:${TAG} +* opea/retriever-redis:${TAG} +* opea/reranking-tei:${TAG} +* opea/tei-gaudi:${TAG} +* opea/chatqna:${TAG} or opea/chatqna-guardrails:${TAG} +* opea/chatqna-ui:${TAG} +* opea/llm-tgi:${TAG} ::: :::: @@ -408,7 +399,8 @@ Check if all the containers launched via docker compose has started For example, the ChatQnA example starts 11 docker (services), check these docker containers are all running, i.e, all the containers `STATUS` are `Up` -To do a quick sanity check, try `docker ps -a` to see if all the containers are running +To do a quick sanity check, try `docker ps -a` to see if all the containers are running. +Note that `TAG` will be the value you set earlier. ::::{tab-set} @@ -416,15 +408,15 @@ To do a quick sanity check, try `docker ps -a` to see if all the containers are :sync: vllm ```bash CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES -42c8d5ec67e9 opea/chatqna-ui:1.1 "docker-entrypoint.s…" About a minute ago Up About a minute 0.0.0.0:5173->5173/tcp, :::5173->5173/tcp chatqna-gaudi-ui-server -7f7037a75f8b opea/chatqna:1.1 "python chatqna.py" About a minute ago Up About a minute 0.0.0.0:8888->8888/tcp, :::8888->8888/tcp chatqna-gaudi-backend-server -4049c181da93 opea/embedding-tei:1.1 "python embedding_te…" About a minute ago Up About a minute 0.0.0.0:6000->6000/tcp, :::6000->6000/tcp embedding-tei-server -171816f0a789 opea/dataprep-redis:1.1 "python prepare_doc_…" About a minute ago Up About a minute 0.0.0.0:6007->6007/tcp, :::6007->6007/tcp dataprep-redis-server -10ee6dec7d37 opea/llm-vllm:1.1 "bash entrypoint.sh" About a minute ago Up About a minute 0.0.0.0:9000->9000/tcp, :::9000->9000/tcp llm-vllm-gaudi-server -ce4e7802a371 opea/retriever-redis:1.1 "python retriever_re…" About a minute ago Up About a minute 0.0.0.0:7000->7000/tcp, :::7000->7000/tcp retriever-redis-server -be6cd2d0ea38 opea/reranking-tei:1.1 "python reranking_te…" About a minute ago Up About a minute 0.0.0.0:8000->8000/tcp, :::8000->8000/tcp reranking-tei-gaudi-server -cc45ff032e8c opea/tei-gaudi:1.1 "text-embeddings-rou…" About a minute ago Up About a minute 0.0.0.0:8090->80/tcp, :::8090->80/tcp tei-embedding-gaudi-server -4969ec3aea02 opea/llm-vllm-hpu:1.1 "/bin/bash -c 'expor…" About a minute ago Up About a minute 0.0.0.0:8007->80/tcp, :::8007->80/tcp vllm-gaudi-server +42c8d5ec67e9 opea/chatqna-ui:${TAG} "docker-entrypoint.s…" About a minute ago Up About a minute 0.0.0.0:5173->5173/tcp, :::5173->5173/tcp chatqna-gaudi-ui-server +7f7037a75f8b opea/chatqna:${TAG} "python chatqna.py" About a minute ago Up About a minute 0.0.0.0:8888->8888/tcp, :::8888->8888/tcp chatqna-gaudi-backend-server +4049c181da93 opea/embedding-tei:${TAG} "python embedding_te…" About a minute ago Up About a minute 0.0.0.0:6000->6000/tcp, :::6000->6000/tcp embedding-tei-server +171816f0a789 opea/dataprep-redis:${TAG} "python prepare_doc_…" About a minute ago Up About a minute 0.0.0.0:6007->6007/tcp, :::6007->6007/tcp dataprep-redis-server +10ee6dec7d37 opea/llm-vllm:${TAG} "bash entrypoint.sh" About a minute ago Up About a minute 0.0.0.0:9000->9000/tcp, :::9000->9000/tcp llm-vllm-gaudi-server +ce4e7802a371 opea/retriever-redis:${TAG} "python retriever_re…" About a minute ago Up About a minute 0.0.0.0:7000->7000/tcp, :::7000->7000/tcp retriever-redis-server +be6cd2d0ea38 opea/reranking-tei:${TAG} "python reranking_te…" About a minute ago Up About a minute 0.0.0.0:8000->8000/tcp, :::8000->8000/tcp reranking-tei-gaudi-server +cc45ff032e8c opea/tei-gaudi:${TAG} "text-embeddings-rou…" About a minute ago Up About a minute 0.0.0.0:8090->80/tcp, :::8090->80/tcp tei-embedding-gaudi-server +4969ec3aea02 opea/llm-vllm-hpu:${TAG} "/bin/bash -c 'expor…" About a minute ago Up About a minute 0.0.0.0:8007->80/tcp, :::8007->80/tcp vllm-gaudi-server 0657cb66df78 redis/redis-stack:7.2.0-v9 "/entrypoint.sh" About a minute ago Up About a minute 0.0.0.0:6379->6379/tcp, :::6379->6379/tcp, 0.0.0.0:8001->8001/tcp, :::8001->8001/tcp redis-vector-db 684d3e9d204a ghcr.io/huggingface/text-embeddings-inference:cpu-1.2 "text-embeddings-rou…" About a minute ago Up About a minute 0.0.0.0:8808->80/tcp, :::8808->80/tcp tei-reranking-gaudi-server ``` @@ -434,15 +426,15 @@ cc45ff032e8c opea/tei-gaudi:1.1 "text-embedd :sync: TGI ```bash CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES -0355d705484a opea/chatqna-ui:1.1 "docker-entrypoint.s…" 2 minutes ago Up 2 minutes 0.0.0.0:5173->5173/tcp, :::5173->5173/tcp chatqna-gaudi-ui-server -29a7a43abcef opea/chatqna:1.1 "python chatqna.py" 2 minutes ago Up 2 minutes 0.0.0.0:8888->8888/tcp, :::8888->8888/tcp chatqna-gaudi-backend-server -1eb6f5ad6f85 opea/llm-tgi:1.1 "bash entrypoint.sh" 2 minutes ago Up 2 minutes 0.0.0.0:9000->9000/tcp, :::9000->9000/tcp llm-tgi-gaudi-server -ad27729caf68 opea/reranking-tei:1.1 "python reranking_te…" 2 minutes ago Up 2 minutes 0.0.0.0:8000->8000/tcp, :::8000->8000/tcp reranking-tei-gaudi-server -84f02cf2a904 opea/dataprep-redis:1.1 "python prepare_doc_…" 2 minutes ago Up 2 minutes 0.0.0.0:6007->6007/tcp, :::6007->6007/tcp dataprep-redis-server -367459f6e65b opea/embedding-tei:1.1 "python embedding_te…" 2 minutes ago Up 2 minutes 0.0.0.0:6000->6000/tcp, :::6000->6000/tcp embedding-tei-server -8c78cde9f588 opea/retriever-redis:1.1 "python retriever_re…" 2 minutes ago Up 2 minutes 0.0.0.0:7000->7000/tcp, :::7000->7000/tcp retriever-redis-server +0355d705484a opea/chatqna-ui:${TAG} "docker-entrypoint.s…" 2 minutes ago Up 2 minutes 0.0.0.0:5173->5173/tcp, :::5173->5173/tcp chatqna-gaudi-ui-server +29a7a43abcef opea/chatqna:${TAG} "python chatqna.py" 2 minutes ago Up 2 minutes 0.0.0.0:8888->8888/tcp, :::8888->8888/tcp chatqna-gaudi-backend-server +1eb6f5ad6f85 opea/llm-tgi:${TAG} "bash entrypoint.sh" 2 minutes ago Up 2 minutes 0.0.0.0:9000->9000/tcp, :::9000->9000/tcp llm-tgi-gaudi-server +ad27729caf68 opea/reranking-tei:${TAG} "python reranking_te…" 2 minutes ago Up 2 minutes 0.0.0.0:8000->8000/tcp, :::8000->8000/tcp reranking-tei-gaudi-server +84f02cf2a904 opea/dataprep-redis:${TAG} "python prepare_doc_…" 2 minutes ago Up 2 minutes 0.0.0.0:6007->6007/tcp, :::6007->6007/tcp dataprep-redis-server +367459f6e65b opea/embedding-tei:${TAG} "python embedding_te…" 2 minutes ago Up 2 minutes 0.0.0.0:6000->6000/tcp, :::6000->6000/tcp embedding-tei-server +8c78cde9f588 opea/retriever-redis:${TAG} "python retriever_re…" 2 minutes ago Up 2 minutes 0.0.0.0:7000->7000/tcp, :::7000->7000/tcp retriever-redis-server fa80772de92c ghcr.io/huggingface/tgi-gaudi:2.0.1 "text-generation-lau…" 2 minutes ago Up 2 minutes 0.0.0.0:8005->80/tcp, :::8005->80/tcp tgi-gaudi-server -581687a2cc1a opea/tei-gaudi:1.1 "text-embeddings-rou…" 2 minutes ago Up 2 minutes 0.0.0.0:8090->80/tcp, :::8090->80/tcp tei-embedding-gaudi-server +581687a2cc1a opea/tei-gaudi:${TAG} "text-embeddings-rou…" 2 minutes ago Up 2 minutes 0.0.0.0:8090->80/tcp, :::8090->80/tcp tei-embedding-gaudi-server c59178629901 redis/redis-stack:7.2.0-v9 "/entrypoint.sh" 2 minutes ago Up 2 minutes 0.0.0.0:6379->6379/tcp, :::6379->6379/tcp, 0.0.0.0:8001->8001/tcp, :::8001->8001/tcp redis-vector-db 5c3a78144498 ghcr.io/huggingface/text-embeddings-inference:cpu-1.5 "text-embeddings-rou…" 2 minutes ago Up 2 minutes 0.0.0.0:8808->80/tcp, :::8808->80/tcp tei-reranking-gaudi-server ``` @@ -812,7 +804,7 @@ curl http://${host_ip}:9090/v1/guardrails\ To access the frontend, open the following URL in your browser: http://{host_ip}:5173. By default, the UI runs on port 5173 internally. If you prefer to use a different host port to access the frontend, you can modify the port mapping in the compose.yaml file as shown below: ```bash chaqna-gaudi-ui-server: - image: opea/chatqna-ui:1.1 + image: opea/chatqna-ui:${TAG} ... ports: - "80:5173" @@ -822,7 +814,7 @@ To access the frontend, open the following URL in your browser: http://{host_ip} To access the Conversational UI (react based) frontend, modify the UI service in the compose.yaml file. Replace chaqna-gaudi-ui-server service with the chatqna-gaudi-conversation-ui-server service as per the config below: ```bash chaqna-gaudi-conversation-ui-server: - image: opea/chatqna-conversation-ui:1.1 + image: opea/chatqna-conversation-ui:${TAG} container_name: chatqna-gaudi-conversation-ui-server environment: - APP_BACKEND_SERVICE_ENDPOINT=${BACKEND_SERVICE_ENDPOINT} @@ -837,7 +829,7 @@ chaqna-gaudi-conversation-ui-server: Once the services are up, open the following URL in your browser: http://{host_ip}:5174. By default, the UI runs on port 80 internally. If you prefer to use a different host port to access the frontend, you can modify the port mapping in the compose.yaml file as shown below: ``` chaqna-gaudi-conversation-ui-server: - image: opea/chatqna-conversation-ui:1.1 + image: opea/chatqna-conversation-ui:${TAG} ... ports: - "80:80"