From 34e7bd1740fa470c5511f4ba2daa6d45ce0c4347 Mon Sep 17 00:00:00 2001 From: Archana Krishnan Date: Thu, 8 Aug 2024 21:16:19 -0500 Subject: [PATCH 01/13] update pipeline script --- source_code/40_pipelines/train-car-rekon.py | 21 ++++++++------------- 1 file changed, 8 insertions(+), 13 deletions(-) diff --git a/source_code/40_pipelines/train-car-rekon.py b/source_code/40_pipelines/train-car-rekon.py index af5bbb8..353c1bd 100644 --- a/source_code/40_pipelines/train-car-rekon.py +++ b/source_code/40_pipelines/train-car-rekon.py @@ -1,12 +1,9 @@ import os - import kfp.compiler -from dotenv import load_dotenv from kfp import dsl -load_dotenv(override=True) - kubeflow_endpoint = os.environ["KUBEFLOW_ENDPOINT"] +#kubeflow_endpoint = 'https://ds-pipeline-dspa.parasol-insurance.svc.cluster.local:8443' base_image = os.getenv( "BASE_IMAGE", "image-registry.openshift-image-registry.svc:5000/openshift/python:latest") @@ -80,7 +77,7 @@ def upload_to_s3(model_onnx: dsl.Input[dsl.Model]): print("configuring s3 instance") # Configuration - minio_url = "http://minio.object-datastore.svc.cluster.local:9000" + minio_url = "http://minio.parasol-insurance.svc.cluster.local:9000" access_key = "minio" secret_key = "minio123" @@ -112,18 +109,18 @@ def accident_detection_pipeline(model_obc: str = "accident-detection"): if __name__ == "__main__": print(f"Connecting to kfp: {kubeflow_endpoint}") - sa_token_path = "/run/secrets/kubernetes.io/serviceaccount/token" - if os.path.isfile(sa_token_path): + sa_token_path = "/run/secrets/kubernetes.io/serviceaccount/token" # noqa: S105 + if "BEARER_TOKEN" in os.environ: + bearer_token = os.environ["BEARER_TOKEN"] + elif os.path.isfile(sa_token_path): with open(sa_token_path) as f: bearer_token = f.read().rstrip() - else: - bearer_token = os.environ["BEARER_TOKEN"] # Check if the script is running in a k8s pod # Get the CA from the service account if it is # Skip the CA if it is not sa_ca_cert = "/run/secrets/kubernetes.io/serviceaccount/service-ca.crt" - if os.path.isfile(sa_ca_cert): + if os.path.isfile(sa_ca_cert) and "svc" in kubeflow_endpoint: ssl_ca_cert = sa_ca_cert else: ssl_ca_cert = None @@ -133,9 +130,7 @@ def accident_detection_pipeline(model_obc: str = "accident-detection"): existing_token=bearer_token, ssl_ca_cert=ssl_ca_cert, ) - result = client.create_run_from_pipeline_func( - accident_detection_pipeline, arguments={}, - experiment_name="accident detection") + result = client.create_run_from_pipeline_func(accident_detection_pipeline, arguments={}, experiment_name="accident_detection") print(f"Starting pipeline run with run_id: {result.run_id}") # Wait 20 minutes for the pipeline to complete client.wait_for_run_completion(run_id=result.run_id, timeout=1200) From a7710ef5d404448f61e82dddf6fb7bd713ba8e24 Mon Sep 17 00:00:00 2001 From: Archana Krishnan Date: Fri, 9 Aug 2024 16:20:38 -0500 Subject: [PATCH 02/13] Add details about pipeline experiments and runs --- .DS_Store | Bin 0 -> 6148 bytes workshop/.DS_Store | Bin 0 -> 6148 bytes workshop/content/.DS_Store | Bin 0 -> 6148 bytes .../content/42_working_with_pipelines.adoc | 43 ++++++++++++++++++ workshop/content/images/.DS_Store | Bin 0 -> 6148 bytes .../41_working_with_pipelines/.DS_Store | Bin 0 -> 6148 bytes .../41_working_with_pipelines/artifacts.png | Bin 0 -> 160164 bytes .../41_working_with_pipelines/executions.png | Bin 0 -> 133357 bytes .../experiments_runs.png | Bin 0 -> 152646 bytes .../pipeline_run_details.png | Bin 0 -> 155451 bytes .../pipeline_runs.png | Bin 0 -> 245318 bytes .../41_working_with_pipelines/schedule-1.png | Bin 0 -> 137914 bytes .../41_working_with_pipelines/schedule-2.png | Bin 0 -> 148518 bytes 13 files changed, 43 insertions(+) create mode 100644 .DS_Store create mode 100644 workshop/.DS_Store create mode 100644 workshop/content/.DS_Store create mode 100644 workshop/content/images/.DS_Store create mode 100644 workshop/content/images/41_working_with_pipelines/.DS_Store create mode 100644 workshop/content/images/41_working_with_pipelines/artifacts.png create mode 100644 workshop/content/images/41_working_with_pipelines/executions.png create mode 100644 workshop/content/images/41_working_with_pipelines/experiments_runs.png create mode 100644 workshop/content/images/41_working_with_pipelines/pipeline_run_details.png create mode 100644 workshop/content/images/41_working_with_pipelines/pipeline_runs.png create mode 100644 workshop/content/images/41_working_with_pipelines/schedule-1.png create mode 100644 workshop/content/images/41_working_with_pipelines/schedule-2.png diff --git a/.DS_Store b/.DS_Store new file mode 100644 index 0000000000000000000000000000000000000000..6f9c02d4575bbbcbd98481a0bba439952006272b GIT binary patch literal 6148 zcmeHKPfNov6i>FPDMQ#nL2m)C1Gk}5@lxvi0#@{(GFvuWS#8F;*~1w0u3yM6;^*GP-vT1PvFVHD0?8zS|u}U7m zx5!(>6A}Z&05Pya4A>)3R99%tv{Yh%82A|jcs@u_MAu?&P#+!8;Pnyx6+{&1<68nz zT68Vu2EhZuO)8*C<@SleO*+`6jdLyL22DESdS>{JotfJg3fHrPUFvYgU4zsT1H`~G z17$O;Vf{b<{{6q4L?dE=82DEV@Jh$;c(5c}TMLWBS}Q^CK~XR+H~5hP9bJkc7EAFC bs1~qG>;SqJbAw<3p^Jc~ff{1qR~dK*WHe2m literal 0 HcmV?d00001 diff --git a/workshop/.DS_Store b/workshop/.DS_Store new file mode 100644 index 0000000000000000000000000000000000000000..d23ba2e73d8eddc72b721da61c85329f87bcda31 GIT binary patch literal 6148 zcmeHK%}T>S5Z<-bCKMqD1-&hJEtnRqikA@U3mDOZN=iguB3EO?EMs|8jE7OW zV4%Nf!nHTp9h10n_G$ex0?%7COp|f$y6=3YR$pCfSeDhaZh{9{1bLWG#(p@u!rr-* zX;kT9bdkhG-`O~kSso@?JW>hCAcm0Z%Oo4f!k3e5Fjl#Nc38G;_nqzOv~zgS5}p0_ ztR<#xx9hecO zAO?s5VqmElFvoz^T&k+6SYm(}_z45JKL}`up21S1+B)Ea*Jt$C5m7+Lw*;av=ou_E zf(L}_R6w1|%@c#`bg&B(=NT+D>U74{%rK6bxq7^CH9Oda3TNEYNMB-r7?@|Ern?TF z|EKWFEPUk8r%;a=AO`*!1H9e~dOj3o&em_`;aMx7-9kgbxDpi*(C01z(7}CVOF6Y) bpbl}K!BQiRf_9Y-NEZP`2z`iwUtr(^S5Z-NTO({YT3VK`cS}-kI6)&OI7cim+m70)JgK4%jsX3HF?)pN$h|lB9 z?&c5-coVTRu=~x<&u->}>@Y|a#WHaWmDJy^fhd+u2F3r(BbtN{S8DE(D5ySC=5CVbB*8u z;W`yir*iYe;5r@b!o)cSbB#KkakVncV^%I6FI=q-cA>%q34j6aBm2s!{Q`A} Ya}4GhaTc_zbU?ZYC_< *Experiments and Runs*. Validate that new experiment `accident_detection` is created + +image::images/41_working_with_pipelines/experiments_runs.png[] + +. Click on the experiment `accident_detection` to view pipeline runs. + +image::images/41_working_with_pipelines/pipeline_runs.png[] + +. Click on each pipeline run to view more details. + +image::images/41_working_with_pipelines/pipeline_run_details.png[] + +. We can schedule periodic pipeline runs for an experiment. Click on 'Schedules'. Click on 'Create Schedule'. Please fill following details: +* *Experiment:* We can choose an existing Experiment or create a new Experiment. +* *Name:* Name for the schedule +* *Trigger Type:* Periodic +* *Run Every:* 1 hour +* *Start Date:* Start date for the schedule +* *End Date:* End Date for the schedule +* *Pipeline:* Name of the pipeline +* *Pipeline version:* Version of the pipeline + +image::images/41_working_with_pipelines/schedule-1.png[] + +image::images/41_working_with_pipelines/schedule-2.png[] + +## Executions + +On Executions page, you can view the execution details of each pipeline task execution, such as its name, status, unique ID, and execution type. + +image::images/41_working_with_pipelines/executions.png[] + +## Artifacts + +On Artifacts page, you can view the pipeline artifacts. 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z6@keLL435fwcR$pY(wXnw!JYLKroO0zWiI-$C2C9h0lUhwZ*3R-;#ND2Nb@|A$|kG zgh&OKqt8gT Date: Mon, 12 Aug 2024 11:05:01 -0500 Subject: [PATCH 03/13] Fixed location of 'accident_detect.onnx' in upload command --- workshop/content/34_boto3.adoc | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/workshop/content/34_boto3.adoc b/workshop/content/34_boto3.adoc index aa7d9f2..72da47b 100644 --- a/workshop/content/34_boto3.adoc +++ b/workshop/content/34_boto3.adoc @@ -423,7 +423,7 @@ def upload_file(file_path, bucket_name, object_name): from ultralytics import YOLO model = YOLO("https://rhods-public.s3.amazonaws.com/demo-models/ic-models/accident/accident_detect.onnx", task="detect") # Upload the file -upload_file('accident_detect.onnx', 'models', 'accident_model/accident_detect.onnx') +upload_file('weights/accident_detect.onnx', 'models', 'accident_model/accident_detect.onnx') ---- . View the contents of the bucket From 2c8c3953cf42aaba864b7a67c275dbaa767899a8 Mon Sep 17 00:00:00 2001 From: Vasant Tokale Date: Tue, 13 Aug 2024 09:53:08 -0500 Subject: [PATCH 04/13] Fixed docs for intro and working with pipelines --- workshop/content/41_introduction_to_kfp_pipelines.adoc | 6 ++++-- workshop/content/42_working_with_pipelines.adoc | 7 ++++--- 2 files changed, 8 insertions(+), 5 deletions(-) diff --git a/workshop/content/41_introduction_to_kfp_pipelines.adoc b/workshop/content/41_introduction_to_kfp_pipelines.adoc index 9d33db0..fd43e53 100644 --- a/workshop/content/41_introduction_to_kfp_pipelines.adoc +++ b/workshop/content/41_introduction_to_kfp_pipelines.adoc @@ -67,8 +67,10 @@ image::images/Compiled_pipeline.png[] + `python pipelines/02_submitted_pipeline_via_route.py` - -This will create a pipeline and also submit a run. To view this run go to RHOAI into Data Science Pipelines and check the Runs section. ++ +This will create a pipeline and also submit a run. To view this run go to `RHOAI Dashboard` -> `Experiments` -> `Experiments and runs`. ++ +image::images/41_working_with_pipelines/pipeline_runs.png[] [start=4] . The next file, `03_outputs_pipeline.py`, introduces the output capability. Run it in the notebook terminal with the below command and check the output in the Runs section in RHOAI: diff --git a/workshop/content/42_working_with_pipelines.adoc b/workshop/content/42_working_with_pipelines.adoc index a668d13..31f735a 100644 --- a/workshop/content/42_working_with_pipelines.adoc +++ b/workshop/content/42_working_with_pipelines.adoc @@ -81,6 +81,7 @@ def accident_detection_pipeline(model_obc: str = "accident-detection"): [source,python] ---- print(f"Connecting to kfp: {KUBEFLOW_ENDPOINT}") +import os bearer_token = "sha256~P0wEh46fxWa4uzPKR-b3fhcnsyXvCju4GovRd2YNNKM" @@ -173,7 +174,7 @@ Notice how we use the output of the `download_data` task as the input of the `tr . Save and run your notebook. -. Validate that the pipeline is running, using the RHOAI dashboard, navigate to the *pipeline runs* of the *parasol-insurance* data science project: You should find a run with a name starting with *accident-detection* +. Validate that the pipeline is running, using the RHOAI dashboard, navigate to the *Experiments* -> *Experiments and runs*: You should find a run with a name starting with *accident-detection* . Create a cell to upload the model to s3 using the `boto3` package, organize this cell to appear before the cell that defines the pipeline (`@kfp.dsl.pipeline`): @@ -227,7 +228,7 @@ def accident_detection_pipeline(model_obc: str = "accident-detection"): . Save and run your notebook. -. Validate that the pipeline is running, using the RHOAI dashboard, navigate to the *pipeline runs* of the *parasol-insurance* data science project: You should find a run with a name starting with *accident-detection* +. Validate that the pipeline is running, using the RHOAI dashboard, navigate to *Experiments* -> *Experiments and runs*: You should find a run with a name starting with *accident-detection* . Validate that the model is uploaded to the s3 bucket, by navigating to the s3 bucket in the OpenShift console. @@ -479,7 +480,7 @@ resources: . Click on the `model-retrain` pipeline, and validate that there is a pipeline run, wait the pipeline run to complete -. Navigate to the RHOAI dashboard, and validate that the *Data Science Pipelines > Runs* has a new pipeline run with a name starting with `accident detection`. +. Navigate to the RHOAI dashboard -> *Experiments* -> *Experiments and runs*: You should find a run with a name starting with *accident-detection* + [TIP] From a43ad1ee42d88b24a1cd65eaa5cc09e6300685e4 Mon Sep 17 00:00:00 2001 From: Vasant Tokale Date: Wed, 14 Aug 2024 09:09:46 -0500 Subject: [PATCH 05/13] fixed the tip on iterating over client.get_job_status(submission_id) --- workshop/content/50_distributed_training.adoc | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/workshop/content/50_distributed_training.adoc b/workshop/content/50_distributed_training.adoc index f744402..0ef6797 100644 --- a/workshop/content/50_distributed_training.adoc +++ b/workshop/content/50_distributed_training.adoc @@ -526,7 +526,7 @@ You can iterate over the `client.get_job_status(submission_id)` instruction to c [source,python] ---- -while client.get_job_status(submission_id) != "Succeeded": +while client.get_job_status(submission_id).upper() != "SUCCEEDED": pass print("Job Succeeded") ---- From 73a15b7c8b5d18e038bd7bc7389584906ac0e444 Mon Sep 17 00:00:00 2001 From: Vasant Tokale Date: Thu, 15 Aug 2024 13:38:00 -0500 Subject: [PATCH 06/13] Fixed rag_llm and some typos --- workshop/content/31_custom_notebook.adoc | 2 +- workshop/content/34_boto3.adoc | 2 +- workshop/content/40_setup_pipeline_server.adoc | 2 +- workshop/content/42_working_with_pipelines.adoc | 2 +- workshop/content/70_rag_llm.adoc | 6 +++--- 5 files changed, 7 insertions(+), 7 deletions(-) diff --git a/workshop/content/31_custom_notebook.adoc b/workshop/content/31_custom_notebook.adoc index 44d4496..daa65c2 100644 --- a/workshop/content/31_custom_notebook.adoc +++ b/workshop/content/31_custom_notebook.adoc @@ -2,7 +2,7 @@ ## Need for custom notebooks -RHOAI provides many pre-built notebooks like Standard Data Science notebook, Tensorflow notebook, Pytorch notebook etc. Data scientists can spin up these notebooks and start runnings their experiments and creating their machine learning models without much set up. +RHOAI provides many pre-built notebooks like Standard Data Science notebook, Tensorflow notebook, Pytorch notebook etc. Data scientists can spin up these notebooks and start running their experiments and creating their machine learning models without much set up. These inbuilt notebooks come with most of the packages that one would need to run their Data Science projects. But the world of Data Science and Machine Learning is vast and there might be a need to download other python packages. diff --git a/workshop/content/34_boto3.adoc b/workshop/content/34_boto3.adoc index 72da47b..e4223e0 100644 --- a/workshop/content/34_boto3.adoc +++ b/workshop/content/34_boto3.adoc @@ -79,7 +79,7 @@ resources: - ../../base ---- -+ + [TIP] ==== The same content will work for both overlays (dev and prod) diff --git a/workshop/content/40_setup_pipeline_server.adoc b/workshop/content/40_setup_pipeline_server.adoc index 70aead8..60e0ddb 100644 --- a/workshop/content/40_setup_pipeline_server.adoc +++ b/workshop/content/40_setup_pipeline_server.adoc @@ -84,7 +84,7 @@ spec: + [TIP] ==== -Your Data Science Cluster requires of a dspa, so that you can create pipelines. +Your Data Science Cluster requires a dspa, so that you can create pipelines. Before creating the dspa object, your Data Science Project shows a button to *Configure pipeline server*: diff --git a/workshop/content/42_working_with_pipelines.adoc b/workshop/content/42_working_with_pipelines.adoc index 31f735a..4beafd0 100644 --- a/workshop/content/42_working_with_pipelines.adoc +++ b/workshop/content/42_working_with_pipelines.adoc @@ -110,7 +110,7 @@ Provide your own token, you can find the token in the OpenShift Web Console by c . Validate that the pipeline is running, using the RHOAI dashboard, navigate to the *pipeline runs* of the *parasol-insurance* data science project: You should find a run with a name starting with *accident-detection* -. Create a cell to train the model, organize this cell to appear before the cell that defines the pipeline (`@kfp.dsl.pipeline`). The contents of this cell were crafter after from a combination of functions from https://github.com/rh-aiservices-bu/parasol-insurance/blob/dev/lab-materials/04/04-03-model-retraining.ipynb[04-03-model-retraining.ipynb]; we recommend you to compare this cell with the original notebook contents: +. Create a cell to train the model, organize this cell to appear before the cell that defines the pipeline (`@kfp.dsl.pipeline`). The contents of this cell were crafted after from a combination of functions from https://github.com/rh-aiservices-bu/parasol-insurance/blob/dev/lab-materials/04/04-03-model-retraining.ipynb[04-03-model-retraining.ipynb]; we recommend you to compare this cell with the original notebook contents: + [source,python] diff --git a/workshop/content/70_rag_llm.adoc b/workshop/content/70_rag_llm.adoc index 6909da4..83a810a 100644 --- a/workshop/content/70_rag_llm.adoc +++ b/workshop/content/70_rag_llm.adoc @@ -498,7 +498,7 @@ Depended on which workbench image you are using, we have to make some changes to 2. Update the _Base Parameters and PostgreSQL info_ ``` -product_version = 2.9 +product_version = 2.11 CONNECTION_STRING = "postgresql+psycopg://vectordb:vectordb@postgresql.rag-llm-demo.svc.cluster.local:5432/vectordb" COLLECTION_NAME = f"rhoai-doc-{product_version}" ``` @@ -513,7 +513,7 @@ NOTE: _Create the index and ingest the documents_ will take more than 5 minutes ``` CONNECTION_STRING = "postgresql+psycopg://vectordb:vectordb@postgresql.rag-llm-demo.svc.cluster.local:5432/vectordb" -COLLECTION_NAME = "rhoai-doc-2.9" +COLLECTION_NAME = "rhoai-doc-2.11" ``` Run through the notebook @@ -530,7 +530,7 @@ TEMPERATURE=0.01 PRESENCE_PENALTY=1.03 CONNECTION_STRING = "postgresql+psycopg://vectordb:vectordb@postgresql.rag-llm-demo.svc.cluster.local:5432/vectordb" -COLLECTION_NAME = "rhoai-doc-2.9" +COLLECTION_NAME = "rhoai-doc-2.11" ``` At the end, should have a successful RAG with LLM sample that you can query. 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