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refactor: clean CLI taxonomy — canonical subcommands, merged memory.update, no aliases

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- calendar: split write → create/read/update/delete/share
- contacts: rename lookup → read
- memory: merge write+forget → update (unified action field in operations)
- Remove all alias/normalization logic from adapter and handlers
- Update tool_postprocessor ui_hints builders to canonical keys
- Remove frontend legacy TOOL_CALL_START/ARGS/END events and ToolCallItem
- Update SKILL.md files and protocol docs
- Update tests and settings screens
This commit is contained in:
qzl
2026-04-23 12:12:41 +08:00
parent 91077a933d
commit 19e273a9e6
48 changed files with 1578 additions and 811 deletions
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backend/src/core/agentscope/runtime/runner.py
+68 -49
View File
@@ -22,6 +22,11 @@ from core.agentscope.utils import (
finalize_json_response,
patch_agentscope_json_repair_compat,
)
from core.auth.credential_issuer import create_credential_issuer
from core.auth.tool_credential_context import (
set_tool_credential,
reset_tool_credential,
)
from core.config.settings import config
from core.db.session import AsyncSessionLocal
from models.llm import Llm
@@ -37,7 +42,7 @@ from schemas.agent.runtime_models import (
RouterAgentOutput,
WorkerAgentOutputLite,
)
from schemas.agent.skill_config import SkillName
from schemas.agent.skill_config import ProjectCliCommand, SkillName
from schemas.agent.system_agent import (
AgentType,
SystemAgentLLMConfig,
@@ -107,7 +112,8 @@ class AgentScopeRunner:
agent_type=AgentType.WORKER,
)
worker_toolkit = self._build_toolkit(
enabled_skills=runtime_config.enabled_skills
enabled_skills=runtime_config.enabled_skills,
allowed_commands=runtime_config.allowed_commands,
)
router_output = await self._execute_router_step(
@@ -174,10 +180,13 @@ class AgentScopeRunner:
self,
*,
enabled_skills: list[SkillName],
allowed_commands: list[ProjectCliCommand],
) -> Any:
enabled_skill_names = {str(skill.value) for skill in enabled_skills}
allowed_command_names = {str(command.value) for command in allowed_commands}
return build_toolkit(
enabled_skill_names=enabled_skill_names if enabled_skill_names else None
enabled_skill_names=enabled_skill_names if enabled_skill_names else None,
allowed_commands=allowed_command_names if allowed_command_names else None,
)
async def _load_stage_config(
@@ -388,56 +397,66 @@ class AgentScopeRunner:
work_memory: WorkProfileContent | None,
requires_tool_evidence: bool = False,
) -> StageExecutionResult:
tracking_model = self._build_model(stage_config=stage_config)
emitter = PipelineStageEmitter(
pipeline=pipeline,
session_id=run_input.thread_id,
run_id=run_input.run_id,
stage=stage_config.agent_type.value,
runtime_mode=runtime_mode.value,
emit_text_events=True,
emit_tool_events=True,
issuer = create_credential_issuer()
credential = issuer.issue(
owner_id=str(user_context.id),
mode=runtime_mode.value,
)
agent = self._build_agent(
agent_name=stage_config.agent_type.value,
system_prompt=build_system_prompt(
agent_type=stage_config.agent_type,
llm_config=stage_config.llm_config,
user_context=user_context,
now_utc=datetime.now(timezone.utc),
runtime_client_time=runtime_client_time,
extra_context=stage_config.extra_context,
work_memory=work_memory,
),
toolkit=toolkit,
model=tracking_model,
emitter=emitter,
force_tool_on_first_reasoning=requires_tool_evidence,
)
async with self._active_agent_lock:
self._active_agent = agent
credential_token = set_tool_credential(credential)
try:
response_msg = await agent.reply_json(
input_messages, output_model=worker_output_model
tracking_model = self._build_model(stage_config=stage_config)
emitter = PipelineStageEmitter(
pipeline=pipeline,
session_id=run_input.thread_id,
run_id=run_input.run_id,
stage=stage_config.agent_type.value,
runtime_mode=runtime_mode.value,
emit_text_events=True,
emit_tool_events=True,
)
agent = self._build_agent(
agent_name=stage_config.agent_type.value,
system_prompt=build_system_prompt(
agent_type=stage_config.agent_type,
llm_config=stage_config.llm_config,
user_context=user_context,
now_utc=datetime.now(timezone.utc),
runtime_client_time=runtime_client_time,
extra_context=stage_config.extra_context,
work_memory=work_memory,
),
toolkit=toolkit,
model=tracking_model,
emitter=emitter,
force_tool_on_first_reasoning=requires_tool_evidence,
)
async with self._active_agent_lock:
self._active_agent = agent
try:
response_msg = await agent.reply_json(
input_messages, output_model=worker_output_model
)
finally:
async with self._active_agent_lock:
if self._active_agent is agent:
self._active_agent = None
worker_payload = worker_output_model.model_validate(response_msg.metadata or {})
response_metadata = self._llm_pricing_service.build_usage_metadata(
model=stage_config.model_code,
usage_summary=tracking_model.usage_summary(),
)
await emitter.emit_final_text_end(
worker_output=worker_payload.model_dump(mode="json", exclude_none=True),
response_metadata=response_metadata,
)
return StageExecutionResult(
message=response_msg,
payload=worker_payload.model_dump(mode="json", exclude_none=True),
response_metadata=response_metadata,
)
finally:
async with self._active_agent_lock:
if self._active_agent is agent:
self._active_agent = None
worker_payload = worker_output_model.model_validate(response_msg.metadata or {})
response_metadata = self._llm_pricing_service.build_usage_metadata(
model=stage_config.model_code,
usage_summary=tracking_model.usage_summary(),
)
await emitter.emit_final_text_end(
worker_output=worker_payload.model_dump(mode="json", exclude_none=True),
response_metadata=response_metadata,
)
return StageExecutionResult(
message=response_msg,
payload=worker_payload.model_dump(mode="json", exclude_none=True),
response_metadata=response_metadata,
)
reset_tool_credential(credential_token)
def _build_worker_input_messages(
self,