vf/vf_react
4
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

update pay ui

Browse Source
This commit is contained in:
zzlgreat
2025-12-17 15:12:26 +08:00
parent f9163b1228
commit 413e327a19
2 changed files with 202 additions and 6 deletions
Download Patch File Download Diff File Expand all files Collapse all files

BIN
__pycache__/mcp_server.cpython-310.pyc
View File

Binary file not shown.

208
mcp_server.py
View File

@@ -2542,9 +2542,22 @@ A股交易时间: 上午 9:30-11:30，下午 13:00-15:00
assistant_message = response.choices[0].message
logger.info(f"[Agent Stream] LLM 响应: finish_reason={response.choices[0].finish_reason}")
# 检查是否有工具调用
if assistant_message.tool_calls:
logger.info(f"[Agent Stream] 检测到 {len(assistant_message.tool_calls)} 个工具调用")
# 获取工具调用（优先使用原生 tool_calls，其次解析文本格式）
native_tool_calls = assistant_message.tool_calls or []
text_tool_calls = []
# 如果没有原生工具调用，尝试从文本内容中解析
if not native_tool_calls and assistant_message.content:
content = assistant_message.content
# 检查是否包含工具调用标记
if '<tool_call>' in content or '```tool_call' in content or '"tool":' in content:
logger.info(f"[Agent Stream] 尝试从文本内容解析工具调用")
logger.info(f"[Agent Stream] 内容预览: {content[:500]}")
text_tool_calls = self._parse_text_tool_calls(content)
# 检查是否有工具调用（原生或文本格式）
if native_tool_calls:
logger.info(f"[Agent Stream] 检测到 {len(native_tool_calls)} 个原生工具调用")
# 将 assistant 消息添加到历史（包含 tool_calls）
messages.append(assistant_message)
@@ -2557,7 +2570,7 @@ A股交易时间: 上午 9:30-11:30，下午 13:00-15:00
"reasoning": "使用工具获取相关数据进行分析",
"steps": []
}
for tc in assistant_message.tool_calls:
for tc in native_tool_calls:
try:
args = json.loads(tc.function.arguments) if tc.function.arguments else {}
except:
@@ -2569,10 +2582,10 @@ A股交易时间: 上午 9:30-11:30，下午 13:00-15:00
})
yield self._format_sse("plan", plan_data)
yield self._format_sse("status", {"stage": "executing", "message": f"开始执行 {len(assistant_message.tool_calls)} 个工具调用"})
yield self._format_sse("status", {"stage": "executing", "message": f"开始执行 {len(native_tool_calls)} 个工具调用"})
# 执行每个工具调用
for tool_call in assistant_message.tool_calls:
for tool_call in native_tool_calls:
tool_name = tool_call.function.name
tool_call_id = tool_call.id
@@ -2675,6 +2688,120 @@ A股交易时间: 上午 9:30-11:30，下午 13:00-15:00
logger.info(f"[Tool Call] ========== 工具调用结束 ==========")
step_index += 1
elif text_tool_calls:
# 处理文本格式的工具调用
logger.info(f"[Agent Stream] 检测到 {len(text_tool_calls)} 个文本格式工具调用")
# 将 assistant 消息添加到历史
messages.append({"role": "assistant", "content": assistant_message.content})
# 如果是第一次工具调用，发送计划事件
if step_index == 0:
plan_data = {
"goal": f"分析用户问题：{user_query[:50]}...",
"reasoning": "使用工具获取相关数据进行分析",
"steps": [
{"tool": tc["name"], "arguments": tc["arguments"], "reason": f"调用 {tc['name']}"}
for tc in text_tool_calls
]
}
yield self._format_sse("plan", plan_data)
yield self._format_sse("status", {"stage": "executing", "message": f"开始执行 {len(text_tool_calls)} 个工具调用"})
# 执行每个工具调用
for tc in text_tool_calls:
tool_name = tc["name"]
arguments = tc["arguments"]
tool_call_id = f"text_call_{step_index}_{tool_name}"
logger.info(f"[Tool Call] ========== 文本工具调用开始 ==========")
logger.info(f"[Tool Call] 工具名: {tool_name}")
logger.info(f"[Tool Call] 参数内容: {json.dumps(arguments, ensure_ascii=False)}")
# 发送步骤开始事件
yield self._format_sse("step_start", {
"step_index": step_index,
"tool": tool_name,
"arguments": arguments,
"reason": f"调用 {tool_name}",
})
start_time = datetime.now()
try:
# 特殊处理 summarize_news
if tool_name == "summarize_news":
data_arg = arguments.get("data", "")
if data_arg in ["前面的新闻数据", "前面收集的所有数据", ""]:
arguments["data"] = json.dumps(collected_data, ensure_ascii=False, indent=2)
# 执行工具
result = await self.execute_tool(tool_name, arguments, tool_handlers)
execution_time = (datetime.now() - start_time).total_seconds()
# 记录结果
step_result = StepResult(
step_index=step_index,
tool=tool_name,
arguments=arguments,
status="success",
result=result,
execution_time=execution_time,
)
step_results.append(step_result)
collected_data[f"step_{step_index+1}_{tool_name}"] = result
plan_steps.append({"tool": tool_name, "arguments": arguments, "reason": f"调用 {tool_name}"})
# 发送步骤完成事件
yield self._format_sse("step_complete", {
"step_index": step_index,
"tool": tool_name,
"status": "success",
"result": result,
"execution_time": execution_time,
})
# 将工具结果添加到消息历史（简化格式，因为模型可能不支持标准 tool 消息）
result_str = json.dumps(result, ensure_ascii=False) if isinstance(result, (dict, list)) else str(result)
messages.append({
"role": "user",
"content": f"[工具调用结果] {tool_name}: {result_str[:3000]}"
})
logger.info(f"[Tool Call] 执行成功，耗时 {execution_time:.2f}s")
except Exception as e:
execution_time = (datetime.now() - start_time).total_seconds()
error_msg = str(e)
step_result = StepResult(
step_index=step_index,
tool=tool_name,
arguments=arguments,
status="failed",
error=error_msg,
execution_time=execution_time,
)
step_results.append(step_result)
yield self._format_sse("step_complete", {
"step_index": step_index,
"tool": tool_name,
"status": "failed",
"error": error_msg,
"execution_time": execution_time,
})
messages.append({
"role": "user",
"content": f"[工具调用失败] {tool_name}: {error_msg}"
})
logger.error(f"[Tool Call] 执行失败: {error_msg}")
logger.info(f"[Tool Call] ========== 文本工具调用结束 ==========")
step_index += 1
else:
# 没有工具调用，模型生成了最终回复
logger.info(f"[Agent Stream] 模型生成最终回复")
@@ -2813,6 +2940,75 @@ A股交易时间: 上午 9:30-11:30，下午 13:00-15:00
"""格式化 SSE 消息"""
return f"event: {event}\ndata: {json.dumps(data, ensure_ascii=False)}\n\n"
def _parse_text_tool_calls(self, content: str) -> List[Dict[str, Any]]:
"""
解析文本格式的工具调用
支持的格式：
1. <tool_call> <function=xxx> <parameter=yyy> value </parameter> </function> </tool_call>
2. ```tool_call\n{"name": "xxx", "arguments": {...}}\n```
返回: [{"name": "tool_name", "arguments": {...}}, ...]
"""
import re
tool_calls = []
# 格式1: <tool_call> 标签格式
# 例如: <tool_call> <function=get_stock_concepts> <parameter=seccode> 300274 </parameter> </function> </tool_call>
pattern1 = r'<tool_call>\s*<function=(\w+)>(.*?)</function>\s*</tool_call>'
matches1 = re.findall(pattern1, content, re.DOTALL)
for func_name, params_str in matches1:
arguments = {}
# 解析参数: <parameter=xxx> value </parameter>
param_pattern = r'<parameter=(\w+)>\s*(.*?)\s*</parameter>'
param_matches = re.findall(param_pattern, params_str, re.DOTALL)
for param_name, param_value in param_matches:
# 尝试解析 JSON 值，否则作为字符串
param_value = param_value.strip()
try:
arguments[param_name] = json.loads(param_value)
except:
arguments[param_name] = param_value
tool_calls.append({
"name": func_name,
"arguments": arguments
})
# 格式2: ```tool_call 代码块格式
pattern2 = r'```tool_call\s*\n?(.*?)\n?```'
matches2 = re.findall(pattern2, content, re.DOTALL)
for match in matches2:
try:
data = json.loads(match.strip())
if isinstance(data, dict) and "name" in data:
tool_calls.append({
"name": data["name"],
"arguments": data.get("arguments", {})
})
except:
pass
# 格式3: 直接 JSON 格式 {"tool": "xxx", "arguments": {...}}
pattern3 = r'\{\s*"tool"\s*:\s*"(\w+)"\s*,\s*"arguments"\s*:\s*(\{[^}]*\})\s*\}'
matches3 = re.findall(pattern3, content)
for tool_name, args_str in matches3:
try:
arguments = json.loads(args_str)
tool_calls.append({
"name": tool_name,
"arguments": arguments
})
except:
pass
logger.info(f"[Text Tool Call] 解析到 {len(tool_calls)} 个工具调用: {tool_calls}")
return tool_calls
# 创建 Agent 实例（全局）
agent = MCPAgentIntegrated()