feat: restore risk assessment workspace and improve page scrolling
This commit is contained in:
NathanAlex7
+150
-1
@@ -3,6 +3,7 @@
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import json
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import os
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import traceback
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from pathlib import Path
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from typing import AsyncGenerator
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from fastapi import APIRouter
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@@ -80,7 +81,7 @@ async def event_generator(message: str, session_id: str) -> AsyncGenerator[dict,
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segments: list[dict] = [] # finalized segments
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current_segment: dict = {"content": "", "tool_calls": []}
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async for event in agent_manager.astream(message, history):
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async for event in agent_manager.astream(message, history, session_id):
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event_type = event.get("type", "unknown")
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if event_type == "retrieval":
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@@ -186,3 +187,151 @@ async def chat(request: ChatRequest):
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# Non-streaming fallback
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result = await agent_manager.ainvoke(request.message, request.session_id)
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return {"reply": result}
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@router.get("/chat/raw-traces")
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async def get_raw_traces(session_id: str = "default", limit: int = 20):
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"""获取指定 session 的原始 LLM 调用报文
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Args:
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session_id: 会话 ID
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limit: 返回最近 N 条记录 (默认 20)
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Returns:
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{"traces": [...]} 原始报文列表，按时间倒序
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"""
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try:
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from graph.raw_trace import load_raw_traces
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# 从 agent_manager 获取 raw_logs_dir
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raw_logs_dir = agent_manager._raw_logs_dir
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if not raw_logs_dir:
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return {"traces": []}
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traces = load_raw_traces(session_id, raw_logs_dir, limit=limit)
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return {"traces": traces}
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except Exception as e:
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traceback.print_exc()
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return {"traces": [], "error": str(e)}
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@router.get("/chat/trajectory")
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async def get_trajectory(session_id: str = "default"):
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"""获取会话完整交互轨迹 - 包含完整的 human/assistant/tool 消息流
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Args:
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session_id: 会话 ID
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Returns:
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{
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"session_id": "...",
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"messages": [
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{"role": "human", "content": "...", "timestamp": ...},
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{"role": "assistant", "content": "...", "timestamp": ..., "tool_calls": [...]},
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{"role": "tool", "name": "...", "content": "...", "timestamp": ...},
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{"role": "assistant", "content": "...", "timestamp": ...}
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],
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"steps": [...] // 保留旧格式用于向后兼容
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}
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"""
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try:
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import json
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from graph.raw_trace import load_raw_traces
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raw_logs_dir = agent_manager._raw_logs_dir
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if not raw_logs_dir:
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# 无 raw_logs_dir，返回空
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return {"session_id": session_id, "messages": [], "steps": []}
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# 优先读取完整消息流日志文件
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msgs_log_file = raw_logs_dir / f"{session_id}.msgs.jsonl"
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messages = []
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if msgs_log_file.exists():
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# 从 msgs.jsonl 读取完整消息流（包含 tool 消息）
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with open(msgs_log_file, "r", encoding="utf-8") as f:
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for line in f:
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line = line.strip()
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if line:
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try:
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msg = json.loads(line)
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messages.append(msg)
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except json.JSONDecodeError:
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continue
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else:
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# 回退到旧逻辑：从 session 文件读取（无 tool 消息）
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session_messages = session_manager.load_session(session_id)
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for msg in session_messages:
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messages.append({
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"role": msg["role"],
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"content": msg["content"],
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"timestamp": None,
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})
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# 构建旧格式 steps（向后兼容）
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steps = []
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traces = load_raw_traces(session_id, raw_logs_dir, limit=1000)
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traces.sort(key=lambda x: x.get("timestamp_start", 0))
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# 按 user/assistant 消息构建 steps（忽略 tool 消息）
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session_messages = session_manager.load_session(session_id)
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assistant_count = sum(1 for m in session_messages if m["role"] == "assistant")
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for msg_idx, msg in enumerate(session_messages):
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step = {
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"role": msg["role"],
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"content": msg["content"],
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"timestamp": None,
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}
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if msg["role"] == "assistant":
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llm_calls = []
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assistant_seq = sum(1 for m in session_messages[:msg_idx+1] if m["role"] == "assistant")
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traces_per_assistant = len(traces) / max(assistant_count, 1)
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start_trace = int((assistant_seq - 1) * traces_per_assistant)
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end_trace = int(assistant_seq * traces_per_assistant)
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for i in range(start_trace, min(end_trace, len(traces))):
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trace = traces[i]
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llm_call = {
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"model": trace.get("request", {}).get("model", "unknown"),
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"finish_reason": trace.get("finish_reason", "unknown"),
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"request_messages": trace.get("request", {}).get("messages", []),
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"response_text": "",
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"tool_calls_list": [],
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"usage": trace.get("usage", {}),
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"duration_ms": trace.get("duration_ms", 0),
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}
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response_gens = trace.get("response", {}).get("generations", [])
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if response_gens:
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llm_call["response_text"] = response_gens[0].get("text", "")
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msg_data = response_gens[0].get("message", {})
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if isinstance(msg_data, dict) and "tool_calls" in msg_data:
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tool_calls = msg_data["tool_calls"]
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if tool_calls:
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llm_call["tool_calls_list"] = [
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{
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"name": tc.get("name", "") if isinstance(tc, dict) else getattr(tc, "name", ""),
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"args": tc.get("args", {}) if isinstance(tc, dict) else getattr(tc, "args", {}),
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}
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for tc in tool_calls
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]
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llm_calls.append(llm_call)
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if step["timestamp"] is None:
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step["timestamp"] = trace.get("timestamp_start")
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step["llm_calls"] = llm_calls
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steps.append(step)
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return {
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"session_id": session_id,
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"messages": messages, # 新格式：完整消息流（含 tool）
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"steps": steps, # 旧格式：向后兼容
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}
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except Exception as e:
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traceback.print_exc()
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return {"session_id": session_id, "messages": [], "steps": [], "error": str(e)}
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