[BUG] Langchain RunnableParallel has no attribute "steps"

[green-sh]

Issues Policy acknowledgement

• [X] I have read and agree to submit bug reports in accordance with the issues policy

Where did you encounter this bug?

Local machine

Willingness to contribute

Yes. I would be willing to contribute a fix for this bug with guidance from the MLflow community.

MLflow version

• Client: 1.12.1
• Tracking server: 1.12.1

System information

• OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Ubuntu
• Python version: Python 3.10.12
• yarn version, if running the dev UI:

Describe the problem

Trying to log a RunnableParallel in langchain results in an error.

workaround: in mlflow.langchain.runnables in _save_runnable_with_steps change

    steps = model.steps
# to
    if hasattr(model, "steps"):
        steps = model.steps
    else: 
        steps = model.steps__
# makes saving the chain possible
# alternatively one could check if the model is of instance RunnableParallel, and use steps__ if thats the case

Tracking information

Tracking URI: file:///home/user/mlruns
Artifact URI: mlflow-artifacts:/0/81284ebe1b844f2bab7b990aad40e276/artifacts
System information: Linux #1 SMP Fri Jan 27 02:56:13 UTC 2023
Python version: 3.10.12
MLflow version: 2.12.1
MLflow module location: .venv/lib/python3.10/site-packages/mlflow/__init__.py
Active experiment ID: 0
Active run ID: 81284ebe1b844f2bab7b990aad40e276
Active run artifact URI: mlflow-artifacts:/0/81284ebe1b844f2bab7b990aad40e276/artifacts
MLflow dependencies: 
  Flask: 3.0.3
  Jinja2: 3.1.3
  aiohttp: 3.9.3
  alembic: 1.13.1
  click: 8.1.7
  cloudpickle: 3.0.0
  docker: 7.0.0
  entrypoints: 0.4
  gitpython: 3.1.43
  graphene: 3.3
  gunicorn: 21.2.0
  importlib-metadata: 7.1.0
  markdown: 3.6
  matplotlib: 3.8.4
  numpy: 1.26.4
  packaging: 23.2
  pandas: 2.2.1
  protobuf: 4.25.3
  pyarrow: 15.0.2
  pydantic: 2.7.0
  pytz: 2024.1
  pyyaml: 6.0.1
  querystring-parser: 1.2.4
  requests: 2.31.0
  scikit-learn: 1.4.2
  scipy: 1.13.0
  sqlalchemy: 2.0.29
  sqlparse: 0.4.4
  tiktoken: 0.6.0
  virtualenv: 20.25.1

Code to reproduce issue

import mlflow
from langchain.llms.fake import FakeListLLM
from langchain.schema.runnable.passthrough import RunnablePassthrough
from langchain.schema.output_parser import StrOutputParser
from langchain.prompts import PromptTemplate
import mlflow.langchain

llm = FakeListLLM(responses=["not relevant"])

chain = (
    {"question": RunnablePassthrough()}
    | PromptTemplate.from_template("hello {question}")
    | llm
    | StrOutputParser())

chain.invoke("Hey")

# mlflow.set_tracking_uri("http://127.0.0.1:5000")
mlflow.langchain.log_model(
    chain,
    artifact_path="model",
)

Stack trace

Traceback (most recent call last):
  File "/usr/lib/python3.10/runpy.py", line 196, in _run_module_as_main
    return _run_code(code, main_globals, None,
  File "/usr/lib/python3.10/runpy.py", line 86, in _run_code
    exec(code, run_globals)
  File "/home//.vscode-server/extensions/ms-python.debugpy-2024.4.0/bundled/libs/debugpy/adapter/../../debugpy/launcher/../../debugpy/__main__.py", line 39, in <module>
    cli.main()
  File "/home//.vscode-server/extensions/ms-python.debugpy-2024.4.0/bundled/libs/debugpy/adapter/../../debugpy/launcher/../../debugpy/../debugpy/server/cli.py", line 430, in main
    run()
  File "/home//.vscode-server/extensions/ms-python.debugpy-2024.4.0/bundled/libs/debugpy/adapter/../../debugpy/launcher/../../debugpy/../debugpy/server/cli.py", line 284, in run_file
    runpy.run_path(target, run_name="__main__")
  File "/home//.vscode-server/extensions/ms-python.debugpy-2024.4.0/bundled/libs/debugpy/_vendored/pydevd/_pydevd_bundle/pydevd_runpy.py", line 321, in run_path
    return _run_module_code(code, init_globals, run_name,
  File "/home//.vscode-server/extensions/ms-python.debugpy-2024.4.0/bundled/libs/debugpy/_vendored/pydevd/_pydevd_bundle/pydevd_runpy.py", line 135, in _run_module_code
    _run_code(code, mod_globals, init_globals,
  File "/home//.vscode-server/extensions/ms-python.debugpy-2024.4.0/bundled/libs/debugpy/_vendored/pydevd/_pydevd_bundle/pydevd_runpy.py", line 124, in _run_code
    exec(code, run_globals)
  File "/home//projects//minimal.py", line 23, in <module>
    mlflow.langchain.log_model(
  File "/home//projects//.venv/lib/python3.10/site-packages/mlflow/langchain/__init__.py", line 519, in log_model
    return Model.log(
  File "/home//projects//.venv/lib/python3.10/site-packages/mlflow/models/model.py", line 625, in log
    flavor.save_model(path=local_path, mlflow_model=mlflow_model, **kwargs)
  File "/home//projects//.venv/lib/python3.10/site-packages/mlflow/langchain/__init__.py", line 311, in save_model
    model_data_kwargs = _save_model(lc_model, path, loader_fn, persist_dir)
  File "/home//projects//.venv/lib/python3.10/site-packages/mlflow/langchain/__init__.py", line 549, in _save_model
    return _save_runnables(model, path, loader_fn=loader_fn, persist_dir=persist_dir)
  File "/home//projects//.venv/lib/python3.10/site-packages/mlflow/langchain/runnables.py", line 401, in _save_runnables
    _save_runnable_with_steps(
  File "/home//projects//.venv/lib/python3.10/site-packages/mlflow/langchain/runnables.py", line 322, in _save_runnable_with_steps
    raise MlflowException(f"Failed to save runnable sequence: {unsaved_runnables}.")
mlflow.exceptions.MlflowException: Failed to save runnable sequence: {'0': "steps__={'question': RunnablePassthrough()} -- 'RunnableParallel' object has no attribute 'steps'"}.

Other info / logs

What component(s) does this bug affect?

• [ ] area/artifacts: Artifact stores and artifact logging
• [ ] area/build: Build and test infrastructure for MLflow
• [ ] area/deployments: MLflow Deployments client APIs, server, and third-party Deployments integrations
• [ ] area/docs: MLflow documentation pages
• [ ] area/examples: Example code
• [ ] area/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registry
• [X] area/models: MLmodel format, model serialization/deserialization, flavors
• [ ] area/recipes: Recipes, Recipe APIs, Recipe configs, Recipe Templates
• [ ] area/projects: MLproject format, project running backends
• [ ] area/scoring: MLflow Model server, model deployment tools, Spark UDFs
• [ ] area/server-infra: MLflow Tracking server backend
• [ ] area/tracking: Tracking Service, tracking client APIs, autologging

What interface(s) does this bug affect?

• [ ] area/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev server
• [ ] 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

What language(s) does this bug affect?

• [ ] language/r: R APIs and clients
• [ ] language/java: Java APIs and clients
• [ ] language/new: Proposals for new client languages

What integration(s) does this bug affect?

• [ ] integrations/azure: Azure and Azure ML integrations
• [ ] integrations/sagemaker: SageMaker integrations
• [ ] integrations/databricks: Databricks integrations

[daniellok-db]

This should be fixed by https://github.com/mlflow/mlflow/pull/11774

[opalchonlapat]

I found the same problem.

[github-actions[bot]]

@mlflow/mlflow-team Please assign a maintainer and start triaging this issue.