908705107/ai-agent-admin
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

fix: execute multica template agents

Browse Source
This commit is contained in:
cls_宁波本机
2026-06-13 12:07:51 +08:00
parent 9632c1b4a6
commit 47da899ff3
4 changed files with 225 additions and 20 deletions
Download Patch File Download Diff File Expand all files Collapse all files
backend-fastapi/ai_platform/nodes/builtin/template_node.py
+151
View File
@@ -2,8 +2,11 @@
模板渲染节点
"""
import logging
import time
from typing import Any, Dict
from sqlalchemy import select
from ..base import BaseNode, NodeContext, NodeResult
from ..registry import NodeRegistry
@@ -61,6 +64,144 @@ class TemplateNode(BaseNode):
success=False,
error=str(e),
)
async def execute_async(self, context: NodeContext) -> NodeResult:
"""配置 agent_code 时，以智能体身份执行当前模板任务。"""
agent_code = (self.config.get('agent_code') or '').strip()
if not agent_code:
return self.execute(context)
start_time = time.time()
try:
if not context.db_session:
return NodeResult(success=False, error='智能体模板节点需要数据库会话')
from ai_platform.models import Agent
from ai_platform.services.llm_service import LLMService
result = await context.db_session.execute(
select(Agent).where(
Agent.code == agent_code,
Agent.is_deleted == False,
Agent.status == 'published',
)
)
agent = result.scalar_one_or_none()
if not agent:
return NodeResult(success=False, error=f'智能体不存在或未发布: {agent_code}')
model_id = self.config.get('model_id') or agent.model_id
if not model_id:
return NodeResult(success=False, error=f'智能体未配置模型: {agent.name}({agent.code})')
template = self.config.get('template', '')
rendered_prompt = context.resolve_template(template)
if not rendered_prompt.strip():
return NodeResult(success=False, error='智能体模板节点缺少任务内容')
messages = [
{'role': 'system', 'content': self._build_agent_system_prompt(agent)},
{'role': 'user', 'content': self._build_agent_user_prompt(context, rendered_prompt)},
]
response = await LLMService(context.db_session).chat_async(
model_id=str(model_id),
messages=messages,
temperature=self.config.get(
'temperature',
agent.temperature if agent.temperature is not None else 0.7,
),
max_tokens=self.config.get('max_tokens', agent.max_tokens or 2048),
)
elapsed_time = int((time.time() - start_time) * 1000)
output_variable = self.config.get('output_variable') or f'{agent.code}_result'
output_variables = {
output_variable: response.content,
f'{output_variable}_agent_code': agent.code,
f'{output_variable}_agent_name': agent.name,
f'{output_variable}_tokens': response.total_tokens,
}
return NodeResult(
success=True,
output=response.content,
output_variables=output_variables,
tokens_used=response.total_tokens,
elapsed_time=elapsed_time,
metadata={
'agent_code': agent.code,
'agent_name': agent.name,
'model_id': str(model_id),
'model': response.model,
'prompt_tokens': response.prompt_tokens,
'completion_tokens': response.completion_tokens,
'output_variable': output_variable,
'frontend_output_variables': output_variables,
},
)
except Exception as e:
logger.exception(f'智能体模板节点执行失败: {e}')
return NodeResult(
success=False,
error=str(e),
elapsed_time=int((time.time() - start_time) * 1000),
)
@staticmethod
def _build_agent_system_prompt(agent: Any) -> str:
base_prompt = agent.system_prompt or ''
persona = agent.persona or {}
if not base_prompt and isinstance(persona, dict):
parts = []
if persona.get('role'):
parts.append(persona['role'])
if persona.get('skills'):
parts.append('你擅长：' + '、'.join(str(item) for item in persona['skills']) + '。')
if persona.get('constraints'):
parts.append('注意事项：\n' + '\n'.join(f'- {item}' for item in persona['constraints']))
if persona.get('background'):
parts.append(str(persona['background']))
base_prompt = '\n\n'.join(parts)
if not base_prompt:
base_prompt = '你是一个智能体，请用中文完成当前任务。'
return (
f'{base_prompt}\n\n'
'你正在作为流程编排中的协作智能体执行当前步骤。'
'请只输出本步骤的结论、交付证据、风险和下一步，避免空泛说明。'
)
@staticmethod
def _format_context_value(value: Any, max_length: int = 1200) -> str:
if isinstance(value, str):
text = value
else:
import json
try:
text = json.dumps(value, ensure_ascii=False, indent=2)
except TypeError:
text = str(value)
return text if len(text) <= max_length else f'{text[:max_length]}...'
def _build_agent_user_prompt(self, context: NodeContext, rendered_prompt: str) -> str:
context_lines = []
for key, value in context.variables.items():
if key.startswith('_') or key.endswith('_tokens') or key.endswith('_agent_code') or key.endswith('_agent_name'):
continue
context_lines.append(f'- {key}: {self._format_context_value(value)}')
if len('\n'.join(context_lines)) > 6000:
context_lines.append('- 其余上下文因长度限制已省略')
break
sections = [f'当前步骤任务：\n{rendered_prompt}']
if context.previous_output:
sections.append(f'上一节点输出：\n{self._format_context_value(context.previous_output, 2000)}')
if context_lines:
sections.append('可用工作流上下文：\n' + '\n'.join(context_lines))
return '\n\n'.join(sections)
@classmethod
def get_config_schema(cls) -> Dict[str, Any]:
@@ -79,6 +220,16 @@ class TemplateNode(BaseNode):
'title': '输出变量名',
'default': 'template_result',
},
'agent_code': {
'type': 'string',
'title': '智能体编码',
'description': '配置后会以该智能体身份调用模型执行模板任务',
},
'model_id': {
'type': 'string',
'title': '覆盖模型 ID',
'description': '为空时使用智能体默认模型',
},
},
'required': ['template'],
}
backend-fastapi/ai_platform/services/workflow_service.py
+12
View File
@@ -64,6 +64,10 @@ def _make_execution_log_entry(
}
def _node_result_metadata(result: NodeResult) -> dict:
return dict(result.metadata or {})
def _snapshot_node_inputs(context: NodeContext) -> dict:
return {
'variables': dict(context.variables),
@@ -535,6 +539,7 @@ class AIWorkflowService:
node_type,
status='completed',
output=result.output,
metadata=_node_result_metadata(result),
inputs=copy.deepcopy(node_inputs),
))
break
@@ -563,6 +568,7 @@ class AIWorkflowService:
error=result.error,
elapsed_time=elapsed,
tokens_used=result.tokens_used,
metadata=_node_result_metadata(result),
inputs=copy.deepcopy(node_inputs),
))
@@ -725,6 +731,7 @@ class AIWorkflowService:
'error': result.error,
'elapsed_time': elapsed,
'tokens_used': result.tokens_used,
'metadata': _node_result_metadata(result),
'branch': branch_start_id,
})
@@ -940,6 +947,7 @@ class AIWorkflowService:
'error': result.error,
'elapsed_time': elapsed,
'tokens_used': result.tokens_used,
'metadata': _node_result_metadata(result),
'branch': branch_id,
})
@@ -1228,6 +1236,7 @@ class AIWorkflowService:
'error': result.error,
'elapsed_time': elapsed,
'tokens_used': result.tokens_used,
'metadata': _node_result_metadata(result),
'loop_iteration': iteration,
})
@@ -1733,6 +1742,7 @@ class AIWorkflowService:
error=result.error,
elapsed_time=elapsed,
tokens_used=result.tokens_used,
metadata=_node_result_metadata(result),
inputs=copy.deepcopy(node_inputs),
)
logs.append(log_entry)
@@ -2201,6 +2211,7 @@ class AIWorkflowService:
'status': 'waiting',
'output': result.output,
'elapsed_time': elapsed,
'metadata': _node_result_metadata(result),
}
logs.append(log_entry)
@@ -2235,6 +2246,7 @@ class AIWorkflowService:
'error': result.error,
'elapsed_time': elapsed,
'tokens_used': result.tokens_used,
'metadata': _node_result_metadata(result),
}
logs.append(log_entry)