dify/api/controllers/API_SCHEMA_GUIDE.md

API Schema Guide

This guide describes the expected Flask-RESTX + Pydantic pattern for controller request payloads, query parameters, response schemas, and Swagger documentation.

Principles

• Use Pydantic BaseModel for request bodies and query parameters.
• Use fields.base.ResponseModel for response DTOs.
• Keep runtime validation and Swagger documentation wired to the same Pydantic model.
• Prefer explicit validation and serialization in controller methods over Flask-RESTX marshalling.
• Do not add new Flask-RESTX fields.* dictionaries, Namespace.model(...) exports, or @marshal_with(...) for migrated or new endpoints.
• Do not use @ns.expect(...) for GET query parameters. Flask-RESTX documents that as a request body.

Public System Features Contract

The Console and Web /system-features endpoints share SystemFeatureModel. They are unauthenticated and may be requested during root SSR, so treat this response as a minimal public bootstrap allowlist. It is not a general configuration endpoint, a feature registry, or a mirror of environment and Enterprise settings. Existing fields are legacy inventory and do not establish precedent for new fields.

A new field is eligible only when all of the following are true:

1. Both Console and Web have named production consumers for the field.
2. Both consumers need the value before authentication and tenant/workspace bootstrap to render initial state or choose an authentication flow.
3. The value varies at runtime or by deployment and cannot be safely derived from an existing public contract.
4. The value is non-sensitive, safe to disclose without authentication, and has stable public API semantics.
5. Sending the value on every root bootstrap is demonstrably clearer and cheaper than a consumer-owned query.

Do not add:

• Backend-only policy or enforcement inputs, including security decisions, upload limits, or integration toggles.
• Console-only or Web-only configuration.
• Tenant, workspace, account, permission, billing-detail, or other post-authentication state.
• Provider payloads, operational diagnostics, large nested objects, or values without active consumers.
• Speculative fields added for possible future use.

Route excluded values to their actual owner:

• Keep backend enforcement behind a narrow service method or domain policy.
• Serve post-authentication state from an authenticated domain endpoint.
• Serve surface-specific bootstrap state from a Console- or Web-specific endpoint and account for its SSR, caching, and failure cost explicitly.
• Load large, slow, or page-specific data lazily through a consumer-owned query.

Every pull request that adds a System Features field must:

• Name both production consumer paths and explain why they require the value before authentication.
• Document the root SSR request, payload, caching, and failure-mode impact.
• Update the Pydantic owner, regenerate OpenAPI Markdown and TypeScript/Zod contracts, and update shared fixtures.
• Add Console and Web schema regression coverage. Do not hand-edit generated contracts or add compatibility defaults.

Reviewers should reject a field when its owner, pre-authentication need, or consumers are unclear.

Naming

• Request body models: use a Payload suffix.
  • Example: WorkflowRunPayload, DatasourceVariablesPayload.
• Query parameter models: use a Query suffix.
  • Example: WorkflowRunListQuery, MessageListQuery.
• Response models: use a Response suffix and inherit from ResponseModel.
  • Example: WorkflowRunDetailResponse, WorkflowRunNodeExecutionListResponse.
• Use ListResponse or PaginationResponse for wrapper responses.
  • Example: WorkflowRunNodeExecutionListResponse, WorkflowRunPaginationResponse.
• Keep these models near the controller when they are endpoint-specific. Move them to fields/*_fields.py only when shared by multiple controllers.

Registering Models For Swagger

Use helpers from controllers.common.schema.

from controllers.common.schema import (
    query_params_from_model,
    register_response_schema_models,
    register_schema_models,
)
from libs.helper import dump_response

Register request payload and query models with register_schema_models(...):

register_schema_models(
    console_ns,
    WorkflowRunPayload,
    WorkflowRunListQuery,
)

Register response models with register_response_schema_models(...):

register_response_schema_models(
    console_ns,
    WorkflowRunDetailResponse,
    WorkflowRunPaginationResponse,
)

Response models are registered in Pydantic serialization mode. This matters when a response model uses validation_alias to read internal object attributes but emits public API field names. For example, a response model can validate from inputs_dict while documenting and serializing inputs.

Request Bodies

For non-GET request bodies:

1. Define a Pydantic Payload model.
2. Register it with register_schema_models(...).
3. Use @ns.expect(ns.models[Payload.__name__]) for Swagger documentation.
4. Validate from ns.payload or {} inside the controller.

class DraftWorkflowNodeRunPayload(BaseModel):
    inputs: dict[str, Any]
    query: str = ""


register_schema_models(console_ns, DraftWorkflowNodeRunPayload)


@console_ns.expect(console_ns.models[DraftWorkflowNodeRunPayload.__name__])
def post(self, app_model: App, node_id: str):
    payload = DraftWorkflowNodeRunPayload.model_validate(console_ns.payload or {})
    result = service.run(..., inputs=payload.inputs, query=payload.query)
    return dump_response(WorkflowRunNodeExecutionResponse, result)

Query Parameters

For GET query parameters:

1. Define a Pydantic Query model.
2. Register it with register_schema_models(...) if it is referenced elsewhere in docs, or only use query_params_from_model(...) if a body schema is not needed.
3. Use @ns.doc(params=query_params_from_model(QueryModel)).
4. Validate from request.args.to_dict(flat=True) or an explicit dict when type coercion is needed.

class WorkflowRunListQuery(BaseModel):
    last_id: str | None = Field(default=None, description="Last run ID for pagination")
    limit: int = Field(default=20, ge=1, le=100, description="Number of items per page (1-100)")


@console_ns.doc(params=query_params_from_model(WorkflowRunListQuery))
def get(self, app_model: App):
    query = WorkflowRunListQuery.model_validate(request.args.to_dict(flat=True))
    result = service.list(..., limit=query.limit, last_id=query.last_id)
    return dump_response(WorkflowRunPaginationResponse, result)

Do not do this for GET query parameters:

@console_ns.expect(console_ns.models[WorkflowRunListQuery.__name__])
def get(...):
    ...

That documents a GET request body and is not the expected contract.

Responses

Response models should inherit from ResponseModel:

class WorkflowRunNodeExecutionResponse(ResponseModel):
    id: str
    inputs: Any = Field(default=None, validation_alias="inputs_dict")
    process_data: Any = Field(default=None, validation_alias="process_data_dict")
    outputs: Any = Field(default=None, validation_alias="outputs_dict")

Document response models with @ns.response(...):

@console_ns.response(
    200,
    "Node run started successfully",
    console_ns.models[WorkflowRunNodeExecutionResponse.__name__],
)
def post(...):
    ...

Serialize explicitly:

return dump_response(WorkflowRunNodeExecutionResponse, workflow_node_execution)

dump_response(...) is the preferred response serialization helper for a single Pydantic response DTO. It validates with from_attributes=True and returns model_dump(mode="json"), so SQLAlchemy models, plain objects, dictionaries, Pydantic aliases, computed fields, and datetime values are serialized consistently.

For wrapper responses, pass a dictionary with the public wrapper fields:

return dump_response(
    WorkflowRunPaginationResponse,
    {
        "data": workflow_runs,
        "page": page,
        "limit": limit,
        "has_more": has_more,
    },
)

If the service can return None, translate that into the expected HTTP error before validation:

workflow_run = service.get_workflow_run(...)
if workflow_run is None:
    raise NotFound("Workflow run not found")

return dump_response(WorkflowRunDetailResponse, workflow_run)

Use manual model_validate(...).model_dump(...) only when the endpoint needs behavior that dump_response(...) does not provide, such as returning a non-dict payload, intentionally excluding fields, or composing a (body, status) tuple.

Legacy Flask-RESTX Patterns

Avoid adding these patterns to new or migrated endpoints:

• ns.model(...) for new request/response DTOs.
• Module-level exported RESTX model objects such as workflow_run_detail_model.
• fields.Nested({...}) with raw inline dict field maps.
• @marshal_with(...) for response serialization.
• @ns.expect(...) for GET query params.

Existing legacy field dictionaries may remain where an endpoint has not yet been migrated. Keep that compatibility local to the legacy area and avoid importing RESTX model objects from controllers.

Verifying Swagger

For schema and documentation changes, run focused tests and generate Swagger JSON:

uv run --project . pytest tests/unit_tests/controllers/common/test_schema.py
uv run --project . pytest tests/unit_tests/commands/test_generate_swagger_specs.py tests/unit_tests/controllers/test_swagger.py
uv run --project . dev/generate_swagger_specs.py --output-dir /tmp/dify-openapi-check

Inspect affected endpoints with jq. Check that:

• GET parameters are in: query.
• Request bodies appear only where the endpoint has a body.
• Responses reference the expected *Response schema.
• Response schemas use public serialized names, not internal validation aliases like inputs_dict.