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[BUG] Pip: not found when using mlflow build-docker locally

See original GitHub issue

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Willingness to contribute

The MLflow Community encourages bug fix contributions. Would you or another member of your organization be willing to contribute a fix for this bug to the MLflow code base?

Yes. I can contribute a fix for this bug independently.
Yes. I would be willing to contribute a fix for this bug with guidance from the MLflow community.
No. I cannot contribute a bug fix at this time.

System information

Have I written custom code (as opposed to using a stock example script provided in MLflow): No
OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Mac OS Big Sur 11.3.1 (Apple M1 chip)
MLflow installed from (source or binary): PiPy
MLflow version (run mlflow --version): 1.18.0
Python version: 3.8.5
npm version, if running the dev UI:
Exact command to reproduce: mlflow models build-docker -m 'models:/{model_name}/{model_version}' -n my-mlflow-image

Describe the problem

I have tried to create a Docker image from a registered model in Mlflow (I am using the Databricks managed version here). The model was registered as a PyFunc. It will download the model, identify its flavour and run until the 6/12 step, where it breaks with the following message:

#9 0.665 /bin/sh: 1: pip: not found
#9 ERROR: executor failed running [/bin/sh -c pip install mlflow==1.19.0]: exit code: 127
------
 > [ 6/12] RUN pip install mlflow==1.19.0:
------
executor failed running [/bin/sh -c pip install mlflow==1.19.0]: exit code: 127

Code to reproduce issue

You must have a registered model or run in an Mlflow artifact storage. Then: mlflow models build-docker -m 'models:/{model_name}/{model_version}' -n my-mlflow-image or mlflow models build-docker -m 'runs:/{run_id}/model' -n my-mlflow-image

Other info / logs

The full output from the command is as follows:

mlflow models build-docker -m 'runs:/{my_run}/model' -n direct-mlflow-image
2021/07/14 17:25:44 INFO mlflow.models.cli: Selected backend for flavor 'python_function'
2021/07/14 17:25:49 INFO mlflow.models.docker_utils: Building docker image with name direct-mlflow-image
/var/folders/yx/6fcq_tx96n52vr0kc66ypy9w0000gp/T/tmpyesejo4m/
/var/folders/yx/6fcq_tx96n52vr0kc66ypy9w0000gp/T/tmpyesejo4m//model_dir
/var/folders/yx/6fcq_tx96n52vr0kc66ypy9w0000gp/T/tmpyesejo4m//model_dir/model
/var/folders/yx/6fcq_tx96n52vr0kc66ypy9w0000gp/T/tmpyesejo4m//model_dir/model/MLmodel
/var/folders/yx/6fcq_tx96n52vr0kc66ypy9w0000gp/T/tmpyesejo4m//model_dir/model/model.pkl
/var/folders/yx/6fcq_tx96n52vr0kc66ypy9w0000gp/T/tmpyesejo4m//model_dir/model/input_example.json
/var/folders/yx/6fcq_tx96n52vr0kc66ypy9w0000gp/T/tmpyesejo4m//model_dir/model/conda.yaml
/var/folders/yx/6fcq_tx96n52vr0kc66ypy9w0000gp/T/tmpyesejo4m//Dockerfile
#1 [internal] load build definition from Dockerfile
#1 sha256:c4ce501e24{}
#1 transferring dockerfile: 1.58kB done
#1 DONE 0.0s

#2 [internal] load .dockerignore
#2 sha256:7094b9fc79b9{}
#2 transferring context: 2B done
#2 DONE 0.0s

#3 [internal] load metadata for docker.io/library/ubuntu:18.04
#3 sha256:fbbba859d4013c87{}
#3 DONE 1.8s

#4 [ 1/12] FROM docker.io/library/ubuntu:18.04@sha256:3b8692dc4{}
#4 sha256:f601b492ef7f7c5a96{}
#4 DONE 0.0s

#5 [ 2/12] RUN apt-get -y update && apt-get install -y --no-install-recommends          wget          curl          nginx          ca-certificates          bzip2          build-essential          cmake          openjdk-8-jdk          git-core          maven     && rm -rf /var/lib/apt/lists/*
#5 sha256:28ae033a3a{}
#5 CACHED

#6 [ 3/12] RUN curl -L https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh >> miniconda.sh
#6 sha256:3dd39dfce1f4b9{}
#6 CACHED

#7 [ 4/12] RUN bash ./miniconda.sh -b -p /miniconda; rm ./miniconda.sh;
#7 sha256:15001db7c7586{}
#7 CACHED

#8 [ 5/12] WORKDIR /opt/mlflow
#8 sha256:7464451f9d65e5{}
#8 CACHED

#14 [internal] load build context
#14 sha256:e3a6a2a7307c9d8b79dc{}
#14 transferring context: 274.43kB 0.0s done
#14 DONE 0.0s

#9 [ 6/12] RUN pip install mlflow==1.19.0
#9 sha256:d1629c303a1736432{}
#9 0.665 /bin/sh: 1: pip: not found
#9 ERROR: executor failed running [/bin/sh -c pip install mlflow==1.19.0]: exit code: 127
------
 > [ 6/12] RUN pip install mlflow==1.19.0:
------
executor failed running [/bin/sh -c pip install mlflow==1.19.0]: exit code: 127

PS: I’m just redacting some sha’s for readability!

What component(s), interfaces, languages, and integrations does this bug affect?

Components

area/artifacts: Artifact stores and artifact logging
area/build: Build and test infrastructure for MLflow
area/docs: MLflow documentation pages
area/examples: Example code
area/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registry
area/models: MLmodel format, model serialization/deserialization, flavors
area/projects: MLproject format, project running backends
area/scoring: Local serving, model deployment tools, spark UDFs
area/server-infra: MLflow server, JavaScript dev server
area/tracking: Tracking Service, tracking client APIs, autologging

Interface

area/uiux: Front-end, user experience, JavaScript, plotting
area/docker: Docker use across MLflow’s components, such as MLflow Projects and MLflow Models
area/sqlalchemy: Use of SQLAlchemy in the Tracking Service or Model Registry
area/windows: Windows support

Language