Native App
Version 2026.3.29-58b69bc-1 of the RelationalAI Native App is now available!
Note that RelationalAI Native App upgrades are applied automatically and require no action on your part, unless you have opted-in to manual upgrades.
Native App
Version 2026.3.29-58b69bc of the RelationalAI Native App is now available!
Note that RelationalAI Native App upgrades are applied automatically and require no action on your part, unless you have opted-in to manual upgrades.
Python SDK
Version 1.0.12 of the relationalai Python package is now available!
To upgrade, activate your virtual environment and run the following command:
pip install --upgrade relationalai
Added a tables section in raiconfig.yaml so you can set defaults and named sources and export targets.
See Use a Snowflake table with Model.Table() and Export results to Snowflake tables for details and examples.
Added a type parameter to Model.Table() for specifying the table type, such as "native" or "iceberg".
See Use a Snowflake table with Model.Table() and Export results to Snowflake tables for details and examples.
Python SDK
Version 1.0.11 of the relationalai Python package is now available!
To upgrade, activate your virtual environment and run the following command:
pip install --upgrade relationalai
direct_access: true is used with an unsupported authenticator.
Before, the warning could use older terminology that did not match the v1 config fields.
Now the warning uses v1 naming, explains the fallback to direct_access: false, and lists the supported authenticator names.
For direct access configuration details, see Enable Direct Access.Python SDK
Version 1.0.10 of the relationalai Python package is now available!
To upgrade, activate your virtual environment and run the following command:
pip install --upgrade relationalai
repr(), str(), and .pprint().
Before, inspecting concepts, expressions, fragments, aggregates, refs, fields, and models showed generic values like <ClassName object at 0x...>.
Now those representations show the object structure directly, which makes debugging and interactive inspection easier..in_() inside select() queries so they no longer create temporary data tables or mutate model state.
Before, filters like Person.name.in_(["Alice", "Bob"]) could register extra model state as a side effect.
Now those select() filters compile as literal unions, leave the model unchanged, and still return the expected results.Python SDK
Version 1.0.9 of the relationalai Python package is now available!
To upgrade, activate your virtual environment and run the following command:
pip install --upgrade relationalai
Added RAI_CONFIG_FILE_PATH support so PyRel can load a specific config file instead of auto-discovering one.
PyRel now checks that path first, raises a clearer error when the override is invalid, and shows the active config file when you run rai config:explain.
Restored Snowflake OAuth authorization-code sign-in for Direct Access. This restores the interactive browser callback and token-exchange sign-in flow that Direct Access workflows use. For setup, see Create an OAuth Security Integration for Direct Access.
Added weighted-graph support to Graph.preferential_attachment().
The graph docs now also clarify how self-loops contribute to degree() and weighted_degree().
Graph.diameter_range() to raise explicit unsupported-graph errors for directed and weighted graphs.
Before, those graph types were documented as supported.
Now PyRel fails early with an explicit error instead of implying that those modes are available.Python SDK
Version 1.0.8 of the relationalai Python package is now available!
To upgrade, activate your virtual environment and run the following command:
pip install --upgrade relationalai
Fixed .into(table).exec() when exporting to a destination table that does not yet exist.
Before, exporting to a new table could fail during setup because PyRel treated the destination as an existing table.
Now PyRel treats the destination as a new export target during setup.
Improved the error PyRel raises when you use a concept, relationship, or chain from one non-library model in another model.
Before, these references could fail later with an unclear error.
Now PyRel raises Cross-model concept usage at the call site.
Concepts from library models are still allowed.
Improved the error PyRel raises when you access a relationship field with dot syntax instead of bracket indexing.
Before, an expression such as relationship.foo could produce an unhelpful error when foo was a field name rather than a relationship.
Now PyRel raises Invalid field access and tells you to use indexing such as relationship["foo"] instead.
Native App
Version 2026.3.23-7c6ad4c-1 of the RelationalAI Native App is now available!
Note that RelationalAI Native App upgrades are applied automatically and require no action on your part, unless you have opted-in to manual upgrades.
Python SDK
Version 1.0.7 of the relationalai Python package is now available!
To upgrade, activate your virtual environment and run the following command:
pip install --upgrade relationalai
Added Relationship.ref() for relationships declared directly, not attached to a concept attribute.
Before, if you used the same standalone relationship twice in one query, PyRel treated both uses as the same query occurrence, so they could not match independently.
Now, Relationship.ref() gives you a second occurrence of the same relationship definition, similar to Chain.ref().
Debugger UI packages are now optional.
Before, a standard PyRel install included nicegui even if you did not use the debugger.
Now a standard install stays smaller, and if you do use the debugger without its extra packages, PyRel tells you to install relationalai[debugger].
select() with not_() so select(not_(expr)) evaluates to a boolean result.
Before, selecting a negated expression did not behave the same way as selecting other boolean expressions such as x == 2.
Now select(not_(expr)) works like a normal boolean selection.auto_suspend_mins and await_storage_vacuum are no longer managed in raiconfig.yaml.
Before, these reasoner lifecycle settings could appear in raiconfig.yaml, and rai init --migrate could carry them over when converting raiconfig.toml to raiconfig.yaml.
Now PyRel warns if they appear in config and leaves them out of the generated raiconfig.yaml during migration.
Manage auto_suspend_mins with rai reasoners:alter.
Set await_storage_vacuum when you create a reasoner with rai reasoners:create.
For broader reasoner configuration, see Configure reasoners.Python SDK
Version 1.0.6 of the relationalai Python package is now available!
To upgrade, activate your virtual environment and run the following command:
pip install --upgrade relationalai
Fixed require() checks that reference columns from data().
Before, a .require() condition that used model.data() columns could emit a warning even when the input rows satisfied the requirement.
Now PyRel warns only when the condition is actually violated.
Fixed std.math.isclose() so that it correctly evaluates an absolute-tolerance comparison.
Before, std.math.isclose() could silently produce the wrong result in filters and selections.
Fixed lookups on subtypes such as Manager, a subtype of Employee.
Before, a lookup such as Manager.approves_budget could use the wrong relationship or raise a type mismatch.
Now PyRel resolves the subtype before resolving the relationship.
Improved reserved-name diagnostics for concepts and tables.
Before, if you used a reserved name such as alias, new, or require, the error could be unclear or point to the wrong place.
Now PyRel points the error at the call site.
For reserved table column names, the message also tells you to use table indexing, such as table["alias"].
The use_direct_access config option is now deprecated. Use the top-level direct_access setting instead.
Preferred configuration:
connections:
snowflake:
account: my-account
user: my-user
password: ${SNOWFLAKE_PASSWORD}
database: MY_DB
schema: PUBLIC
warehouse: COMPUTE_WH
direct_access: true
Deprecated configuration:
connections:
snowflake:
account: my-account
user: my-user
password: ${SNOWFLAKE_PASSWORD}
database: MY_DB
schema: PUBLIC
warehouse: COMPUTE_WH
use_direct_access: true
Existing use_direct_access entries still work.
PyRel warns that they are deprecated and maps them to the top-level direct_access setting.
For details, see Configure reasoners.
Native App
Version 2026.3.16-75ea12b-1 of the RelationalAI Native App is now available!
Note that RelationalAI Native App upgrades are applied automatically and require no action on your part, unless you have opted-in to manual upgrades.
Python SDK
Version 1.0.5 of the relationalai Python package is now available!
To upgrade, activate your virtual environment and run the following command:
pip install --upgrade relationalai
Added explicit schema= support to data() and Model.data().
Before, PyRel always inferred column types from the in-memory rows or DataFrame you provided, which made empty inputs and ambiguous columns harder to control.
Now you can declare some or all column types explicitly, and the returned Data object preserves those types even when the input is empty.
For example:
from relationalai.semantics import Date, Integer, Model, String
m = Model("OpsModel")
# A daily exceptions feed can legitimately be empty, but downstream logic
# still needs stable column types.
shipment_exceptions = m.data(
[],
schema={
"order_id": Integer,
"warehouse": String,
"reason": String,
"requested_ship_date": Date,
},
)
# You can still use the schema in model logic, even with no rows.
ShipmentException = m.Concept("ShipmentException")
m.define(ShipmentException.new(shipment_exceptions.to_schema()))
PyRel now supports batching multiple pending table exports into a single model execution.
Before, export-heavy workflows had to execute table exports separately.
Now you can queue multiple .into() exports and submit them together with m.exec():
# Create two export fragments.
m.select(Customer.id, Customer.name).into(customer_table)
m.select(Product.id, Product.name).into(product_table)
# Execute both exports together in a single model execution.
m.exec()
Improved dtype inference for pandas float columns.
Before, dataframe float columns could be inferred as a more generic numeric type.
Now PyRel maps pandas float columns to Float, which keeps inferred schemas closer to the original dataframe types.
Fixed table-based schema and column mapping when model.implicit_properties is disabled.
model.implicit_properties controls whether PyRel creates undeclared properties automatically.
Before, when you turned this option off, Table objects could still implicitly create properties.
Now Table objects respect the model.implicit_properties setting, so you can disable implicit properties for tables as well as concepts.
Fixed use of std.datetime.datetime.now() in queries and filters.
Before, using the current date and time in a query or filter could fail with an argument error.
Now you can use std.datetime.datetime.now() directly in PyRel logic, including in time-based derived definitions.
For example:
from relationalai.semantics import DateTime, Integer, Model, std
from relationalai.semantics.std.datetime import datetime
m = Model("OpsModel")
# Declare the base shipment concept.
Shipment = m.Concept("Shipment", identify_by={"id": Integer})
# Add the promised ship timestamp.
Shipment.promised_ship_at = m.Property(f"{Shipment} promised ship at {DateTime}")
OverdueShipments = m.Concept("OverdueShipments", extends=[Shipment])
# Define some shipment entities.
m.define(
Shipment.new(id=1, promised_ship_at=datetime(2026, 3, 17, 9, 0)),
Shipment.new(id=2, promised_ship_at=datetime(2026, 3, 28, 9, 0)),
)
# Define overdue shipments using the current time.
m.define(OverdueShipments(Shipment)).where(
Shipment.promised_ship_at < std.datetime.datetime.now(),
)
Fixed ProgrammaticAccessTokenAuth so PAT-based Snowflake authentication includes the required user field and expands ~ in token_file_path.
Before, Snowflake could reject the PAT as invalid, and token files referenced with ~ could fail with FileNotFoundError.
Now PAT authentication works in both cases.
Fixed Problem.solve() so it uses the app name from the model config.
Before, Problem.solve() could ignore a custom rai_app_name in the model config.
Now it reuses the configured app name.
Fixed create_config() for PyRel running inside an existing Snowflake session, including notebooks, stored procedures, and SPCS containers.
Before, the returned config could fail when PyRel later needed a Snowflake SQL connection.
Now configs created from active sessions work correctly in those environments.
Fixed notebook diagnostics so notebook users see all collected PyRel diagnostics in a single exception. Before, earlier diagnostics could be easy to miss, so you often saw only the final failure. Now notebook exceptions include the diagnostic context that led to the error.
Python SDK
Version 1.0.4 of the relationalai Python package is now available!
To upgrade, activate your virtual environment and run the following command:
pip install --upgrade relationalai
Added a new rai config:explain command to inspect the active configuration and where each value came from.
Now you can inspect the active config directly from the CLI and optionally show full provenance details with --verbose:
rai config:explain
rai config:explain --verbose
Improved dtype inference for pandas columns with object dtype when PyRel derives concept types from data.
PyRel now does a better job recognizing numbers in pandas object columns.
For example, if a column contains decimal values, PyRel now treats it as numeric instead of treating it as text.
Fixed an issue with rai connect where invalid Snowflake warehouse names could pass basic connectivity checks.
The command now validates the configured warehouse.
Fixed a bug that caused select() to raise a ValueError when selecting a Match object.
Fixed a bug where PyRel would warn about graph validation whenever you selected a Graph.Edge entity.
You can now select or inspect Graph.Edge without triggering validation warnings.
PyRel waits to validate until you run a graph operation that actually needs it.
Fixed a bug that could cause the client to get disconnected during long-running graph algorithms or other work if a jobs polling attempt was delayed or missed. The maximum polling delay is now short enough to prevent accidental disconnects from transient polling issues.
Fixed a bug that could affect results in some queries involving values that could match multiple types.
Native App
Version 2026.3.9-4685f01-1 of the RelationalAI Native App is now available!
Note that RelationalAI Native App upgrades are applied automatically and require no action on your part, unless you have opted-in to manual upgrades.
Added app.set_warm_reasoners() so app admins can configure multiple warm reasoners for the same reasoner type and size.
Added new SQL APIs for managing jobs, including:
Python SDK
Version 1.0.3 of the relationalai Python package is now available!
To upgrade, activate your virtual environment and run the following command:
pip install --upgrade relationalai
Added a new reasoner library for prescriptive reasoning. See the prescriptive reasoning guides. For API reference docs, see std.reasoners.prescriptive.
Improved typing support for Graph.
Graph.__init__() now has overloads so IDEs and static type checkers can catch incorrect combinations of graph constructor parameters.
Made Graph attributes directed and weighted read-only.
Mutations to these attributes had no effect on graph behavior.
They are now immutable to avoid confusion.
Improved configuration and authentication diagnostics.
create_config() now includes the active profile name in YAML validation errors when available.
Improved CLI diagnostics for Snowflake authentication failures. The CLI now surfaces clearer guidance for login and SSO failures.
Added support for the await_storage_vacuum reasoner setting in configuration.
You can now set this in raiconfig.yaml under reasoners.*.
Use it when you want a reasoner to wait for storage vacuum work to finish before suspending.
:::caution
This guidance applies only through PyRel 1.0.6.
As of PyRel 1.0.7, you no longer manage reasoner lifecycle settings in raiconfig.yaml.
Instead, set await_storage_vacuum when you create a reasoner with rai reasoners:create.
For current guidance, see Configure reasoners or What's New in Version 1.0.7.
:::
Made field access by name in relationships case-insensitive.
For example, Thermometer.readings["time"] and Thermometer.readings["Time"] now refer to the same field.
rai init --migrate now produces cleaner raiconfig.yaml output when migrating from raiconfig.toml.
Generated YAML no longer includes spurious default fields, places reuse_model under model, and formats profiles and connections more readably.
Fixed ProgrammaticAccessTokenAuth so token_file_path works correctly in v1 configuration.
You can now provide either a literal token string or a file path to a Programmatic Access Token in raiconfig.yaml.
Improved type checking for relationships and properties. If a field's target type can't be inferred, PyRel now raises a type mismatch error.
DataConfig.data_freshness_mins is now capped at 30240 minutes (3 weeks).
If you set a larger value, PyRel clamps it to 3 weeks and emits a warning during config creation.Native App
Version 2026.3.2-62ce088 of the RelationalAI Native App is now available!
Note that RelationalAI Native App upgrades are applied automatically and require no action on your part, unless you have opted-in to manual upgrades.
Python SDK
Version 1.0.2 of the relationalai Python package is now available!
To upgrade, activate your virtual environment and run the following command:
pip install --upgrade relationalai
raiconfig.toml is deprecated, and PyRel now reliably emits a visible warning when it loads a raiconfig.toml config.
The warning points you to rai init to migrate or create a raiconfig.yaml.
Fixed an issue in Snowflake stored procedures where importing your package could fail or behave unexpectedly if it triggered config auto-discovery at import time.
This could attempt to read config files in a restricted runtime, and raise errors such as ConfigFileNotFoundError.
If your code relied on implicit config loading, update it to construct a Config explicitly and pass it into the SDK objects you create.
For example: cfg = create_config(...).
In stored procedures, prefer creating the config inside the stored procedure handler rather than at module import time.
See create_config() for the supported config sources and defaults.
Python SDK
Version 1.0.1 of the relationalai Python package is now available!
To upgrade, activate your virtual environment and run the following command:
pip install --upgrade relationalai
Improved concurrent call handling for ReasonersClient.ensure() and ReasonersClientSync.ensure().
When multiple processes try to create or resume the same reasoner at the same time, ensure() will wait for the in-progress operation to complete instead of failing with a conflict error.
Improved the error raised when a logic reasoner job is aborted because the client disconnected.
If that happens, JobsClient.wait() / JobsClientSync.wait() raises JobClientDisconnectedError:
from relationalai.services.jobs.errors import JobClientDisconnectedError
try:
job = await client.jobs.wait("LOGIC", job_id)
except JobClientDisconnectedError:
# The client disconnected before the job completed.
# Retry after restoring connectivity.
...
rai reasoners:create, could fail with an ImportError.Python SDK
Version 1.0.0 of the relationalai Python package is now available!
To upgrade, activate your virtual environment and run the following command:
pip install --upgrade relationalai
Version 1.0.0 is a major update of the Python SDK that introduces:
PyRel, a new modeling and query DSL organized around Concept, Property, and Relationship classes, and new chainable query methods like define, where, and select.
See Build a semantic model for an introduction to the new modeling and query patterns.
Improved configuration management with a new raiconfig.yaml format.
The v1 SDK treats raiconfig.toml as deprecated, so if you have an existing raiconfig.toml, you should migrate to YAML using rai init --migrate.
See Configuring PyRel for details on new configuration patterns.
A new CLI with updated commands for managing reasoners, which were previously called engines, and job, which were previously called transactions. Check out the CLI reference for details on the new CLI commands and syntax.
:::note
For docs on the v0.x versions of the Python SDK and CLI, check out https://v0.docs.relational.ai.
:::
Treat this upgrade as a migration. You should expect to make non-trivial changes to your codebase when upgrading from v0.x to v1.0.0. If you need help, contact RelationalAI support for assistance.
Protect existing workflows.
Make sure existing production and staging environments install relationalai in a way that doesn't break existing code until you're ready to migrate.
For example, if you use pip, you can specify the version in your requirements.txt or setup.py to avoid accidentally upgrading to v1.0.0 before you're ready.
You can pin your project to the latest v0.x version with:
relationalai==0.14.3
Or, you can use a version specifier to allow the latest v0.x but prevent upgrading to v1.0.0 until you're ready:
relationalai>=0.14.0,<1.0.0
Native App
Version 2026.2.23-91bdaf5-1 of the RelationalAI Native App is now available!
Note that RelationalAI Native App upgrades are applied automatically and require no action on your part, unless you have opted-in to manual upgrades.
Native App
Version 2026.2.17-f9af1b6 of the RelationalAI Native App is now available!
Note that RelationalAI Native App upgrades are applied automatically and require no action on your part, unless you have opted-in to manual upgrades.
Native App
Version 2026.2.8-e6a1f8a of the RelationalAI Native App is now available!
Note that RelationalAI Native App upgrades are applied automatically and require no action on your part, unless you have opted-in to manual upgrades.
WARM_PROVISION column to the api.engines view and to the table returned by api.get_engine() procedure, which indicates whether or not an engine was provisioned off a warm engine.Native App
Version 2026.2.2-51ae489 of the RelationalAI Native App is now available!
Note that RelationalAI Native App upgrades are applied automatically and require no action on your part, unless you have opted-in to manual upgrades.
Native App
Version 2026.1.26-ba18c9d-2 of the RelationalAI Native App is now available!
Note that RelationalAI Native App upgrades are applied automatically and require no action on your part, unless you have opted-in to manual upgrades.
api.show_warm_engines() which shows information about all currently existing warm engines.Native App
Version 2026.1.17-e94e8cc-6 of the RelationalAI Native App is now available!
Note that RelationalAI Native App upgrades are applied automatically and require no action on your part, unless you have opted-in to manual upgrades.
Native App
Version 2026.1.11-d4d9cef of the RelationalAI Native App is now available!
Note that RelationalAI Native App upgrades are applied automatically and require no action on your part, unless you have opted-in to manual upgrades.
Native App
Version 2026.1.4-301050f of the RelationalAI Native App is now available!
Note that RelationalAI Native App upgrades are applied automatically and require no action on your part, unless you have opted-in to manual upgrades.
enable_warm_engine and disable_warm_engine, which replace set_warm_engines. These endpoints let you pre-provision a logic engine, so a "warm" engine is ready to use immediately when you create or resume an engine. This reduces provisioning time to just a few seconds. Keeping a warm engine running increases costs, as one engine of the chosen size stays active in the background.