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ailine/backend/app/main_graph/subgraph_wrapper.py
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构建并部署 AI Agent 服务 / deploy (push) Successful in 12m9s
refactor: 单图方案重构 + 动态模型选择 + chat_services优化
## 核心改动

### 1. 单图方案重构
- 删除了多图(self.graphs),改为单图(self.graph)
- 新增 MainGraphState.current_model 字段用于运行时注入模型
- llm_call 节点改为动态选择模型(create_dynamic_llm_call_node)

### 2. chat_services 优化
- 添加 _cached_services 缓存,避免重复初始化
- 新增 get_cached_chat_services() 函数,用于单图注入
- 新增 _check_http_service_available() 统一HTTP探测逻辑
- 减少重复代码,LocalVLLMChatProvider和LocalSmallModelProvider共用探测方法

### 3. AIAgentService 重构
- initialize() 只构建一次图,传入 chat_services 字典
- 新增 _resolve_model() 模型回退逻辑
- 新增 _build_invocation() 统一构建调用参数
- process_message() 和 process_message_stream() 改为注入 current_model
- 流式处理代码拆分,增加可读性

### 4. 新增和删除文件
- 新增:backend/app/main_graph/main_graph_builder.py(图构建)
- 新增:backend/app/main_graph/subgraph_wrapper.py(子图封装)
- 新增:tools/test/test_tavily_search.py(测试)
- 删除:backend/app/main_graph/graph.py(旧图)
- 删除:backend/app/main_graph/utils/main_graph_builder.py(旧构建器)
- 删除:backend/app/main_graph/utils/__init__.py

### 5. 其他更新
- README.md:新增模型服务使用情况详解章节
- backend/app/model_services/__init__.py:新增 get_cached_chat_services 导出

## 方案优势

- 内存优化:N张图 → 1张图
- 灵活性:运行时动态选择模型,支持同会话不同模型
- 性能:模型服务缓存,初始化仅一次
- 可维护性:减少重复代码,统一HTTP探测逻辑
2026-05-05 17:30:55 +08:00

160 lines
5.7 KiB
Python

"""
子图包装器 - 为子图添加错误处理和事件追踪
"""
from typing import Dict, Any, Optional
from datetime import datetime
from .state import MainGraphState, ErrorRecord, ErrorSeverity
from ..logger import info
def wrap_subgraph_for_error_handling(subgraph, name: str):
"""
包装子图,使其错误能传递给主图
Args:
subgraph: 编译好的子图
name: 子图名称(用于错误标识)
Returns: 包装后的节点函数
"""
async def wrapped_node(state: MainGraphState, config: Optional[Dict[str, Any]] = None) -> MainGraphState:
# 发送子图开始事件
if config:
try:
from langchain_core.callbacks.manager import adispatch_custom_event
callbacks = config.get("callbacks")
if callbacks:
await adispatch_custom_event(
"react_reasoning",
{
"step": state.reasoning_step,
"action": f"{name}_subgraph_start",
"confidence": 1.0,
"reasoning": f"开始执行 {name} 子图..."
},
callbacks=callbacks
)
except Exception as e:
info(f"[{name}_subgraph] 无法发送开始事件: {e}")
try:
# 调用子图
result = subgraph.invoke(state)
# 更新主图状态
subgraph_result = None
if name == "contact":
state.contact_result = result
subgraph_result = result.get("final_result", "")
elif name == "dictionary":
state.dictionary_result = result
subgraph_result = result.get("final_result", "")
elif name == "news_analysis":
state.news_result = result
subgraph_result = result.get("final_result", "")
# 设置最终结果
if subgraph_result:
state.final_result = subgraph_result
else:
state.final_result = "子图执行完成"
# 标记成功
state.success = True
state.current_phase = "done"
state.reasoning_history.append({
"step": state.reasoning_step,
"action": "subgraph_completed",
"confidence": 1.0,
"reasoning": f"{name}子图执行完成",
"timestamp": datetime.now().isoformat()
})
# 发送子图完成事件
if config:
try:
from langchain_core.callbacks.manager import adispatch_custom_event
callbacks = config.get("callbacks")
if callbacks:
await adispatch_custom_event(
"react_reasoning",
{
"step": state.reasoning_step,
"action": f"{name}_subgraph_complete",
"confidence": 1.0,
"reasoning": f"{name} 子图执行完成"
},
callbacks=callbacks
)
except Exception as e:
info(f"[{name}_subgraph] 无法发送完成事件: {e}")
return state
except Exception as e:
# 捕获子图错误,传递给主图
error_record = ErrorRecord(
error_type=f"{name}SubgraphError",
error_message=str(e),
severity=ErrorSeverity.WARNING,
source=f"{name}_subgraph",
timestamp=datetime.now().isoformat(),
retry_count=0,
max_retries=1,
context={"user_query": state.user_query}
)
state.errors.append(error_record)
state.current_error = error_record
state.current_phase = "error_handling"
state.success = False
# 发送子图错误事件
if config:
try:
from langchain_core.callbacks.manager import adispatch_custom_event
callbacks = config.get("callbacks")
if callbacks:
await adispatch_custom_event(
"react_reasoning",
{
"step": state.reasoning_step,
"action": f"{name}_subgraph_error",
"confidence": 1.0,
"reasoning": f"{name} 子图执行失败: {str(e)}"
},
callbacks=callbacks
)
except Exception as e:
info(f"[{name}_subgraph] 无法发送错误事件: {e}")
return state
return wrapped_node
def create_subgraph_nodes(contact_graph, dictionary_graph, news_analysis_graph) -> Dict[str, Any]:
"""
创建所有子图节点的字典
Args:
contact_graph: 联系人子图
dictionary_graph: 词典子图
news_analysis_graph: 新闻分析子图
Returns:
子图节点字典 {name: wrapped_node}
"""
return {
"contact_subgraph": wrap_subgraph_for_error_handling(
contact_graph.compile(), "contact"
),
"dictionary_subgraph": wrap_subgraph_for_error_handling(
dictionary_graph.compile(), "dictionary"
),
"news_analysis_subgraph": wrap_subgraph_for_error_handling(
news_analysis_graph.compile(), "news_analysis"
),
}