Files
dify/api/models/agent_config_entities.py
zyssyz123 b1f0a11d84 feat: output declaration and inspector (#36618)
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
2026-05-25 10:08:58 +00:00

352 lines
13 KiB
Python

import re
from enum import StrEnum
from typing import Any, Final
from pydantic import BaseModel, ConfigDict, Field, field_validator, model_validator
class AgentKnowledgeQueryMode(StrEnum):
USER_QUERY = "user_query"
GENERATED_QUERY = "generated_query"
class WorkflowNodeJobMode(StrEnum):
LET_AGENT_FIGURE_IT_OUT = "let_agent_figure_it_out"
TELL_AGENT_WHAT_TO_DO = "tell_agent_what_to_do"
class DeclaredOutputType(StrEnum):
STRING = "string"
NUMBER = "number"
OBJECT = "object"
ARRAY = "array"
BOOLEAN = "boolean"
FILE = "file"
class OutputErrorStrategy(StrEnum):
"""Per-output failure handling strategy.
Mirrors ``graphon.ErrorStrategy`` but scoped to a single declared output of
a Workflow Agent Node. The runtime applies the strategy after type check or
output check fails and any configured retry attempts have been exhausted.
"""
STOP = "stop"
DEFAULT_VALUE = "default_value"
FAIL_BRANCH = "fail_branch"
# JSON-schema-friendly name pattern. Stage 4 §3.1 / §10.1.
_OUTPUT_NAME_PATTERN: Final[re.Pattern[str]] = re.compile(r"^[A-Za-z_][A-Za-z0-9_]*$")
class AgentSoulPromptConfig(BaseModel):
system_prompt: str = ""
class AgentSoulSkillsFilesConfig(BaseModel):
files: list[dict[str, Any]] = Field(default_factory=list)
skills: list[dict[str, Any]] = Field(default_factory=list)
class AgentSoulToolsConfig(BaseModel):
dify_tools: list[dict[str, Any]] = Field(default_factory=list)
cli_tools: list[dict[str, Any]] = Field(default_factory=list)
class AgentSoulKnowledgeConfig(BaseModel):
datasets: list[dict[str, Any]] = Field(default_factory=list)
query_mode: AgentKnowledgeQueryMode | None = None
query_config: dict[str, Any] = Field(default_factory=dict)
class AgentSoulHumanConfig(BaseModel):
contacts: list[dict[str, Any]] = Field(default_factory=list)
tools: list[dict[str, Any]] = Field(default_factory=list)
class AgentSoulEnvConfig(BaseModel):
variables: list[dict[str, Any]] = Field(default_factory=list)
secret_refs: list[dict[str, Any]] = Field(default_factory=list)
class AgentSoulSandboxConfig(BaseModel):
provider: str | None = None
config: dict[str, Any] = Field(default_factory=dict)
class AgentSoulMemoryConfig(BaseModel):
scope: str | None = None
budget: str | None = None
artifacts: list[dict[str, Any]] = Field(default_factory=list)
class AgentSoulModelCredentialRef(BaseModel):
"""Reference to model credentials resolved only at runtime."""
type: str = Field(min_length=1, max_length=64)
id: str | None = Field(default=None, max_length=255)
provider: str | None = Field(default=None, max_length=255)
class AgentSoulModelConfig(BaseModel):
"""Stable model selection for Agent runtime without storing secret values."""
plugin_id: str = Field(min_length=1, max_length=255)
model_provider: str = Field(min_length=1, max_length=255)
model: str = Field(min_length=1, max_length=255)
credential_ref: AgentSoulModelCredentialRef | None = None
model_settings: dict[str, Any] = Field(default_factory=dict)
class AppVariableConfig(BaseModel):
name: str = Field(min_length=1, max_length=255)
type: str = Field(min_length=1, max_length=64)
required: bool = False
default: Any = None
class AgentSoulConfig(BaseModel):
model_config = ConfigDict(extra="forbid")
schema_version: int = 1
prompt: AgentSoulPromptConfig = Field(default_factory=AgentSoulPromptConfig)
skills_files: AgentSoulSkillsFilesConfig = Field(default_factory=AgentSoulSkillsFilesConfig)
tools: AgentSoulToolsConfig = Field(default_factory=AgentSoulToolsConfig)
knowledge: AgentSoulKnowledgeConfig = Field(default_factory=AgentSoulKnowledgeConfig)
human: AgentSoulHumanConfig = Field(default_factory=AgentSoulHumanConfig)
env: AgentSoulEnvConfig = Field(default_factory=AgentSoulEnvConfig)
sandbox: AgentSoulSandboxConfig = Field(default_factory=AgentSoulSandboxConfig)
memory: AgentSoulMemoryConfig = Field(default_factory=AgentSoulMemoryConfig)
model: AgentSoulModelConfig | None = None
app_features: dict[str, Any] = Field(default_factory=dict)
app_variables: list[AppVariableConfig] = Field(default_factory=list)
misc_legacy: dict[str, Any] = Field(default_factory=dict)
class DeclaredOutputFileConfig(BaseModel):
"""File-type output metadata. Both lists empty means "any file accepted"."""
model_config = ConfigDict(extra="forbid")
extensions: list[str] = Field(default_factory=list)
mime_types: list[str] = Field(default_factory=list)
class DeclaredArrayItem(BaseModel):
"""Per-item shape for an ``array``-typed declared output.
PRD §OUTPUT 配置框 keeps arrays one level deep on first version; nested arrays
are rejected so the runtime type checker and JSON Schema stay easy to reason
about. Stage 4 §4.2.
"""
model_config = ConfigDict(extra="forbid")
type: DeclaredOutputType
description: str | None = None
@model_validator(mode="after")
def _reject_nested_array(self) -> "DeclaredArrayItem":
if self.type == DeclaredOutputType.ARRAY:
raise ValueError("nested arrays are not supported as array_item.type")
return self
class DeclaredOutputCheckConfig(BaseModel):
"""File-output content check via a model-based comparison against a benchmark file.
Per PRD §OUTPUT 配置框, output check is **file-only** and optional. Stage 4 §4.3.
"""
model_config = ConfigDict(extra="forbid")
enabled: bool = False
prompt: str | None = None
benchmark_file_ref: dict[str, Any] | None = None
# Reserved for stage 4.1: pick a different model than Agent Soul's for the check.
# Stage 4 leaves this Optional and unused by FileOutputCheckExecutor.
model_ref: dict[str, Any] | None = None
@model_validator(mode="after")
def _require_prompt_and_benchmark_when_enabled(self) -> "DeclaredOutputCheckConfig":
if self.enabled:
if not self.prompt or not self.prompt.strip():
raise ValueError("prompt is required when output check is enabled")
if self.benchmark_file_ref is None:
raise ValueError("benchmark_file_ref is required when output check is enabled")
return self
class DeclaredOutputRetryConfig(BaseModel):
"""Per-output retry configuration that mirrors ``graphon.RetryConfig`` shape."""
model_config = ConfigDict(extra="forbid")
enabled: bool = False
max_retries: int = Field(default=0, ge=0, le=10)
retry_interval_ms: int = Field(default=0, ge=0, le=60_000)
class DeclaredOutputFailureStrategy(BaseModel):
"""Per-output failure handling.
A single strategy applies to both ``type_check`` and ``output_check`` failures
(PRD does not distinguish them at the UX level). Stage 4 §4.4.
"""
model_config = ConfigDict(extra="forbid")
retry: DeclaredOutputRetryConfig = Field(default_factory=DeclaredOutputRetryConfig)
on_failure: OutputErrorStrategy = OutputErrorStrategy.STOP
# When ``on_failure == DEFAULT_VALUE`` this value replaces the failed output. The
# value's shape must match the owning ``DeclaredOutputConfig.type``; that match is
# enforced at ``DeclaredOutputConfig`` level so the strategy stays type-agnostic.
default_value: Any = None
@model_validator(mode="after")
def _require_default_value_when_default_strategy(self) -> "DeclaredOutputFailureStrategy":
if self.on_failure == OutputErrorStrategy.DEFAULT_VALUE and self.default_value is None:
raise ValueError(
"default_value must be provided when on_failure=default_value; None is reserved for 'not set'."
)
return self
class DeclaredOutputConfig(BaseModel):
"""One declared output of a Workflow Agent Node.
Stage 4 normalizes the shape: ``check`` is singular (was ``checks: list`` in
stage 3), and ``failure_strategy`` defaults to a populated value so runtime
code can call ``output.failure_strategy.on_failure`` without None-guards.
"""
model_config = ConfigDict(extra="forbid")
id: str | None = None
name: str = Field(min_length=1, max_length=255)
type: DeclaredOutputType
description: str | None = None
required: bool = True
file: DeclaredOutputFileConfig | None = None
array_item: DeclaredArrayItem | None = None
check: DeclaredOutputCheckConfig | None = None
failure_strategy: DeclaredOutputFailureStrategy = Field(default_factory=DeclaredOutputFailureStrategy)
@field_validator("failure_strategy", mode="before")
@classmethod
def _coerce_none_failure_strategy(cls, value: Any) -> Any:
# Backward compat: persisted JSON may carry ``failure_strategy: null``;
# treat it as "use defaults".
if value is None:
return DeclaredOutputFailureStrategy()
return value
@model_validator(mode="after")
def _validate_shape(self) -> "DeclaredOutputConfig":
if not _OUTPUT_NAME_PATTERN.fullmatch(self.name):
raise ValueError(
f"output name {self.name!r} must match {_OUTPUT_NAME_PATTERN.pattern} (JSON-schema-friendly identifier)"
)
if self.type == DeclaredOutputType.FILE:
if self.file is None:
self.file = DeclaredOutputFileConfig()
elif self.file is not None:
raise ValueError("file metadata is only allowed for file outputs")
if self.type == DeclaredOutputType.ARRAY:
if self.array_item is None:
# Backward compat for stage 3 fixtures: array without array_item
# defaults to array<object>, matching the prior JSON-Schema behavior.
self.array_item = DeclaredArrayItem(type=DeclaredOutputType.OBJECT)
elif self.array_item is not None:
raise ValueError("array_item is only allowed when type is array")
# Per PRD §OUTPUT 配置框: output check is file-only.
if self.check is not None and self.check.enabled and self.type != DeclaredOutputType.FILE:
raise ValueError("output check is only allowed for file outputs")
# If the strategy is DEFAULT_VALUE, validate the default's shape against the
# declared type so we fail at save-time rather than at runtime.
strategy = self.failure_strategy
if strategy.on_failure == OutputErrorStrategy.DEFAULT_VALUE and strategy.default_value is not None:
self._assert_default_value_matches_type(strategy.default_value)
return self
def _assert_default_value_matches_type(self, value: Any) -> None:
type_ = self.type
if type_ == DeclaredOutputType.STRING:
ok = isinstance(value, str)
elif type_ == DeclaredOutputType.NUMBER:
ok = isinstance(value, (int, float)) and not isinstance(value, bool)
elif type_ == DeclaredOutputType.BOOLEAN:
ok = isinstance(value, bool)
elif type_ == DeclaredOutputType.OBJECT:
ok = isinstance(value, dict)
elif type_ == DeclaredOutputType.ARRAY:
ok = isinstance(value, list)
elif type_ == DeclaredOutputType.FILE:
ok = isinstance(value, dict) and "file_id" in value
else:
ok = False
if not ok:
raise ValueError(
f"default_value shape does not match output type {type_.value!r}: got {type(value).__name__}"
)
# PRD §OUTPUT 配置框 0522 共识: "Output 如果没有配置,则 text, files, json"
# The runtime injects these when ``declared_outputs`` is empty (stage 4 §4.1, D-3).
# Not persisted; mutating this constant changes UI defaults globally.
DEFAULT_DECLARED_OUTPUTS: Final[tuple[DeclaredOutputConfig, ...]] = (
DeclaredOutputConfig(
name="text",
type=DeclaredOutputType.STRING,
required=False,
description="Free-form text answer.",
),
DeclaredOutputConfig(
name="files",
type=DeclaredOutputType.ARRAY,
required=False,
description="Files produced by the agent.",
array_item=DeclaredArrayItem(type=DeclaredOutputType.FILE),
),
DeclaredOutputConfig(
name="json",
type=DeclaredOutputType.OBJECT,
required=False,
description="Free-form JSON object.",
),
)
def effective_declared_outputs(
declared_outputs: list[DeclaredOutputConfig] | tuple[DeclaredOutputConfig, ...],
) -> tuple[DeclaredOutputConfig, ...]:
"""Return the outputs the runtime actually presents.
Returns ``declared_outputs`` unchanged when non-empty, otherwise the PRD
defaults from ``DEFAULT_DECLARED_OUTPUTS``. Shared helper so Composer load
responses, runtime request builder, and the Node Output Inspector all use
the same fallback (stage 4 §4.1, decision D-3).
"""
if declared_outputs:
return tuple(declared_outputs)
return DEFAULT_DECLARED_OUTPUTS
class WorkflowNodeJobConfig(BaseModel):
model_config = ConfigDict(extra="forbid")
schema_version: int = 1
mode: WorkflowNodeJobMode = WorkflowNodeJobMode.TELL_AGENT_WHAT_TO_DO
workflow_prompt: str = ""
previous_node_output_refs: list[dict[str, Any]] = Field(default_factory=list)
declared_outputs: list[DeclaredOutputConfig] = Field(default_factory=list)
human_contacts: list[dict[str, Any]] = Field(default_factory=list)
metadata: dict[str, Any] = Field(default_factory=dict)