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feat(agent): support cli tool scoped env (#37324)

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Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
This commit is contained in:
zyssyz123
2026-06-11 07:14:39 +00:00
committed by GitHub
co-authored by autofix-ci[bot]
parent c4a8d79be9
commit fb39df49c8
18 changed files with 406 additions and 91 deletions
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api/clients/agent_backend/request_builder.py
+35 -6
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@@ -11,6 +11,7 @@ composition-driven.
from __future__ import annotations
from collections.abc import Mapping
from typing import ClassVar, cast
from agenton.compositor import CompositorSessionSnapshot
@@ -142,6 +143,30 @@ class AgentBackendModelConfig(BaseModel):
model_config: ClassVar[ConfigDict] = ConfigDict(extra="forbid")
# ``DifyPluginLLMLayerConfig.model_settings`` is pydantic_ai's ``ModelSettings``
# TypedDict (closed: unknown keys are rejected, explicit ``None`` values fail the
# per-field type checks). Agent Soul model settings carry a wider, nullable shape
# (``stop`` / ``response_format`` plus null-padded fields), so the layer config
# only receives the keys the runtime contract accepts.
_AGENT_MODEL_SETTINGS_PASSTHROUGH_KEYS = (
"temperature",
"top_p",
"presence_penalty",
"frequency_penalty",
"max_tokens",
)
def _agent_model_settings(settings: Mapping[str, JsonValue]) -> dict[str, JsonValue] | None:
sanitized: dict[str, JsonValue] = {
key: settings[key] for key in _AGENT_MODEL_SETTINGS_PASSTHROUGH_KEYS if settings.get(key) is not None
}
stop = settings.get("stop")
if isinstance(stop, list) and stop:
sanitized["stop_sequences"] = stop
return sanitized or None
class AgentBackendOutputConfig(BaseModel):
"""API-side structured output declaration for the conventional output layer.
@@ -283,7 +308,7 @@ class AgentBackendRunRequestBuilder:
model_provider=run_input.model.model_provider,
model=run_input.model.model,
credentials=run_input.model.credentials,
model_settings=run_input.model.model_settings or None,
model_settings=_agent_model_settings(run_input.model.model_settings),
),
)
)
@@ -300,12 +325,14 @@ class AgentBackendRunRequestBuilder:
)
if run_input.include_shell:
# Sandboxed bash workspace (dify.shell). The layer declares NoLayerDeps,
# so the spec carries no deps; shellctl connection is server-injected.
# Sandboxed bash workspace (dify.shell). Depends on execution_context so
# the agent server can mint per-command Agent Stub env (back proxy);
# shellctl connection itself is server-injected.
layers.append(
RunLayerSpec(
name=DIFY_SHELL_LAYER_ID,
type=DIFY_SHELL_LAYER_TYPE_ID,
deps={"execution_context": DIFY_EXECUTION_CONTEXT_LAYER_ID},
metadata=run_input.metadata,
config=run_input.shell_config or DifyShellLayerConfig(),
)
@@ -437,7 +464,7 @@ class AgentBackendRunRequestBuilder:
model_provider=run_input.model.model_provider,
model=run_input.model.model,
credentials=run_input.model.credentials,
model_settings=run_input.model.model_settings or None,
model_settings=_agent_model_settings(run_input.model.model_settings),
),
),
]
@@ -455,12 +482,14 @@ class AgentBackendRunRequestBuilder:
)
if run_input.include_shell:
# Sandboxed bash workspace (dify.shell). The layer declares NoLayerDeps,
# so the spec carries no deps; shellctl connection is server-injected.
# Sandboxed bash workspace (dify.shell). Depends on execution_context so
# the agent server can mint per-command Agent Stub env (back proxy);
# shellctl connection itself is server-injected.
layers.append(
RunLayerSpec(
name=DIFY_SHELL_LAYER_ID,
type=DIFY_SHELL_LAYER_TYPE_ID,
deps={"execution_context": DIFY_EXECUTION_CONTEXT_LAYER_ID},
metadata=run_input.metadata,
config=run_input.shell_config or DifyShellLayerConfig(),
)