-
Notifications
You must be signed in to change notification settings - Fork 4.3k
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Fix LangChain compatibility with SQLDatabase #9192
Conversation
Signed-off-by: dbczumar <[email protected]>
Signed-off-by: dbczumar <[email protected]>
Signed-off-by: dbczumar <[email protected]>
Signed-off-by: dbczumar <[email protected]>
Signed-off-by: dbczumar <[email protected]>
Documentation preview for 2da6697 will be available here when this CircleCI job completes successfully. More info
|
Signed-off-by: dbczumar <[email protected]>
Signed-off-by: dbczumar <[email protected]>
Signed-off-by: dbczumar <[email protected]>
): | ||
logger.warning( | ||
_UNSUPPORTED_LLM_WARNING_MESSAGE, | ||
type(lc_model.llm).__name__, | ||
) | ||
|
||
if ( | ||
isinstance(lc_model, langchain.agents.agent.AgentExecutor) | ||
and type(lc_model.agent.llm_chain.llm) not in _SUPPORTED_LLMS |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
This is quite brittle, since it doesn't support subclasses. Changed to isinstance()
.
): | ||
logger.warning( | ||
_UNSUPPORTED_LLM_WARNING_MESSAGE, | ||
type(lc_model.agent.llm_chain.llm).__name__, | ||
) | ||
|
||
if type(lc_model).__name__ in special_chains: |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
This is quite brittle, since it doesn't support subclasses. Changed to isinstance()
in _get_special_chain_info_or_none
model = None | ||
if key := special_chains.get(model_type): |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
This breaks for subclasses of special chains. It also breaks if the chain class name changes in a future version of langchain. Accordingly, rather than relying on the class name, we store the name of the loader argument for dependent objects (e.g. embeddings
, database
, ...) as part of the MLModel flavor config for improved compatibility across versions.
@@ -68,6 +70,7 @@ | |||
_MODEL_TYPE_KEY = "model_type" | |||
_LOADER_FN_FILE_NAME = "loader_fn.pkl" | |||
_LOADER_FN_KEY = "loader_fn" | |||
_LOADER_ARG_KEY = "loader_arg" |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Signed-off-by: dbczumar <[email protected]>
Signed-off-by: dbczumar <[email protected]>
Signed-off-by: dbczumar <[email protected]>
Signed-off-by: dbczumar <[email protected]>
def test_log_and_load_subclass_of_specialized_chain(): | ||
class APIChainSubclass(APIChain): | ||
pass | ||
|
||
llm = OpenAI(temperature=0) | ||
apichain_subclass = APIChainSubclass.from_llm_and_api_docs( | ||
llm, open_meteo_docs.OPEN_METEO_DOCS, verbose=True | ||
) | ||
|
||
with mlflow.start_run(): | ||
logged_model = mlflow.langchain.log_model( | ||
apichain_subclass, | ||
"apichain_subclass", | ||
loader_fn=load_requests_wrapper, | ||
) | ||
|
||
# Load the chain | ||
loaded_model = mlflow.langchain.load_model(logged_model.model_uri) | ||
assert loaded_model == apichain_subclass |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
This fails on master with:
def _load_api_chain(config: dict, **kwargs: Any) -> APIChain:
if "api_request_chain" in config:
api_request_chain_config = config.pop("api_request_chain")
api_request_chain = load_chain_from_config(api_request_chain_config)
elif "api_request_chain_path" in config:
api_request_chain = load_chain(config.pop("api_request_chain_path"))
else:
raise ValueError(
"One of `api_request_chain` or `api_request_chain_path` must be present."
)
if "api_answer_chain" in config:
api_answer_chain_config = config.pop("api_answer_chain")
api_answer_chain = load_chain_from_config(api_answer_chain_config)
elif "api_answer_chain_path" in config:
api_answer_chain = load_chain(config.pop("api_answer_chain_path"))
else:
raise ValueError(
"One of `api_answer_chain` or `api_answer_chain_path` must be present."
)
if "requests_wrapper" in kwargs:
requests_wrapper = kwargs.pop("requests_wrapper")
else:
> raise ValueError("`requests_wrapper` must be present.")
E ValueError: `requests_wrapper` must be present.
But it passes on the PR branch :)
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
LGTM!
Signed-off-by: dbczumar <[email protected]> Signed-off-by: santiagxf <[email protected]>
Related Issues/PRs
Fixes #9188
What changes are proposed in this pull request?
Fix LangChain compatibility with SQLDatabase
How is this patch tested?
Does this PR change the documentation?
Release Notes
Is this a user-facing change?
(Details in 1-2 sentences. You can just refer to another PR with a description if this PR is part of a larger change.)
What component(s), interfaces, languages, and integrations does this PR affect?
Components
area/artifacts
: Artifact stores and artifact loggingarea/build
: Build and test infrastructure for MLflowarea/docs
: MLflow documentation pagesarea/examples
: Example codearea/gateway
: AI Gateway service, Gateway client APIs, third-party Gateway integrationsarea/model-registry
: Model Registry service, APIs, and the fluent client calls for Model Registryarea/models
: MLmodel format, model serialization/deserialization, flavorsarea/recipes
: Recipes, Recipe APIs, Recipe configs, Recipe Templatesarea/projects
: MLproject format, project running backendsarea/scoring
: MLflow Model server, model deployment tools, Spark UDFsarea/server-infra
: MLflow Tracking server backendarea/tracking
: Tracking Service, tracking client APIs, autologgingInterface
area/uiux
: Front-end, user experience, plotting, JavaScript, JavaScript dev serverarea/docker
: Docker use across MLflow's components, such as MLflow Projects and MLflow Modelsarea/sqlalchemy
: Use of SQLAlchemy in the Tracking Service or Model Registryarea/windows
: Windows supportLanguage
language/r
: R APIs and clientslanguage/java
: Java APIs and clientslanguage/new
: Proposals for new client languagesIntegrations
integrations/azure
: Azure and Azure ML integrationsintegrations/sagemaker
: SageMaker integrationsintegrations/databricks
: Databricks integrationsHow should the PR be classified in the release notes? Choose one:
rn/breaking-change
- The PR will be mentioned in the "Breaking Changes" sectionrn/none
- No description will be included. The PR will be mentioned only by the PR number in the "Small Bugfixes and Documentation Updates" sectionrn/feature
- A new user-facing feature worth mentioning in the release notesrn/bug-fix
- A user-facing bug fix worth mentioning in the release notesrn/documentation
- A user-facing documentation change worth mentioning in the release notes