新增对话接口

src/server/deep_agent/agents/init_llm.py

@@ -1,23 +0,0 @@
-from langchain_qwq import ChatQwen
-
-from src.core.config import settings
-
-llm = ChatQwen(
-    model="qwen3.5-flash",
-    max_tokens=3_000,
-    timeout=None,
-    max_retries=2,
-    enable_thinking=False,
-    api_key=settings.QWEN_API_KEY
-)
-
-title_llm = ChatQwen(
-    model="qwen-plus",
-    max_tokens=3_000,
-    timeout=None,
-    max_retries=2,
-    streaming=False,
-    temperature=0.1,
-    top_p=0.8,
-    api_key=settings.QWEN_API_KEY
-)

src/server/deep_agent/agents/main_agent.py

@@ -11,8 +11,8 @@ from src.core.config import MONGO_URI
 from src.server.deep_agent.agents.painter import painter_subagent
 from src.server.deep_agent.agents.researcher import research_subagent
 from src.server.deep_agent.agents.user_profile import user_profile_subagent
+from src.server.deep_agent.init_llm import main_llm
 from src.server.deep_agent.init_prompt import build_system_prompt
-from src.server.deep_agent.tools.report_generator_tool import llm
 
 TOOL_DIR = Path(__file__).resolve().parent
 PROJECT_ROOT = TOOL_DIR.parent
@@ -32,7 +32,7 @@ subagents = [
 
 def build_main_agent(use_report):
     main_agent = create_deep_agent(
-        model=llm,
+        model=main_llm,
         system_prompt=build_system_prompt(use_report=use_report),
         subagents=subagents,
         checkpointer=checkpointer,
@@ -42,7 +42,7 @@ def build_main_agent(use_report):
         ),
         middleware=[
             SummarizationMiddleware(
-                model=llm,
+                model=main_llm,
                 trigger=("tokens", 3000),
                 keep=("messages", 100),
             ),

src/server/deep_agent/agents/painter.py

@@ -1,6 +1,6 @@
 from langchain.agents.middleware import wrap_tool_call
 
-from src.server.deep_agent.agents.init_llm import llm
+from src.server.deep_agent.init_llm import llm
 from src.server.deep_agent.init_prompt import build_painter_prompt
 from src.server.deep_agent.tools.generate_furniture_sketch import generate_furniture
 

src/server/deep_agent/agents/researcher.py

@@ -1,4 +1,4 @@
-from src.server.deep_agent.agents.init_llm import llm
+from src.server.deep_agent.init_llm import llm
 from src.server.deep_agent.init_prompt import build_researcher_prompt
 from src.server.deep_agent.tools.crawl_tool import crawl4ai_batch
 from src.server.deep_agent.tools.report_generator_tool import report_generator

src/server/deep_agent/agents/user_profile.py

@@ -1,4 +1,4 @@
-from src.server.deep_agent.agents.init_llm import llm
+from src.server.deep_agent.init_llm import llm
 from src.server.deep_agent.init_prompt import build_user_persona_prompt
 from src.server.deep_agent.tools.user_persona_tool import query_report_profile, update_report_profile, check_profile_complete
 

src/server/deep_agent/init_llm.py

@@ -0,0 +1,51 @@
+from langchain_qwq import ChatQwen
+
+from src.core.config import settings
+
+llm = ChatQwen(
+    model="qwen3.5-flash",
+    max_tokens=3_000,
+    timeout=None,
+    max_retries=2,
+    enable_thinking=False,
+    api_key=settings.QWEN_API_KEY
+)
+
+title_llm = ChatQwen(
+    model="qwen-plus",
+    max_tokens=3_000,
+    timeout=None,
+    max_retries=2,
+    streaming=False,
+    temperature=0.1,
+    top_p=0.8,
+    api_key=settings.QWEN_API_KEY
+)
+
+main_llm = ChatQwen(
+    model="qwen3.5-flash",
+    temperature=0.2,
+    max_tokens=3_000,
+    timeout=None,
+    max_retries=2,
+    api_key=settings.QWEN_API_KEY)
+
+suggested_llm = ChatQwen(
+    model="qwen-plus",
+    max_tokens=3_000,
+    timeout=None,
+    max_retries=2,
+    streaming=False,
+    temperature=0.1,
+    top_p=0.8,
+    api_key=settings.QWEN_API_KEY
+)
+
+repoer_llm = ChatQwen(
+    enable_thinking=False,
+    model="qwen3.5-flash",
+    temperature=0.2,
+    max_tokens=3_000,
+    timeout=None,
+    max_retries=2,
+    api_key=settings.QWEN_API_KEY)

src/server/deep_agent/run_test.py

@@ -8,7 +8,7 @@ agent = build_main_agent(use_report=True)
 
 
 async def continuous_chat():
-    thread_id = str(uuid.uuid4())
+    thread_id = "c8e327fb-e208-4fab-83fd-b7b9c4d5fdd0"
     print("===== 家具设计助手（支持持续对话+记忆）=====")
     print("输入 'exit' 或 '退出' 结束对话\n")
 
@@ -25,13 +25,38 @@ async def continuous_chat():
 
         print("\n助手：正在处理你的需求...\n")
 
+        current_config = {
+            "recursion_limit": 120,
+            "configurable": {
+                "thread_id": thread_id,
+            }
+        }
+        source_config = {
+            "configurable": {
+                "thread_id": thread_id,
+                "checkpoint_id": '1f11dc17-be49-65a1-8000-96139f7c89cb'
+            }
+        }
+        initial_messages = []
+        older_state = await agent.aget_state(source_config)
+        combined_values = older_state.values.copy()
+        if initial_messages:
+            combined_values["messages"] = list(combined_values.get("messages", [])) + initial_messages
+        await agent.aupdate_state(current_config, combined_values)
+
         # 现在可以安全使用 async for
         async for stream in agent.astream(
                 {"messages": user_input},
                 stream_mode=["updates", "messages", "custom"],
                 subgraphs=True,
                 version="v2",
-                config={"configurable": {"thread_id": thread_id}}
+                config={
+                    "configurable": {
+                        "thread_id": thread_id,
+                        'checkpoint_id': '1f11dc17-be49-65a1-8000-96139f7c89cb'
+                    }
+
+                }
         ):
 
             print(stream)
@@ -61,7 +86,7 @@ async def continuous_chat():
 
             elif mode == "custom":
                 print(f"[report] {chunks.get('delta', '')}", end="")
-
+        print("end")
         # if chunk["type"] == "messages":
         #     token, metadata = chunk["data"]
         #     if not isinstance(token, AIMessageChunk):

src/server/deep_agent/tools/conversation_title_tool.py

@@ -1,6 +1,6 @@
 from langchain_core.prompts import PromptTemplate
 
-from src.server.deep_agent.agents.init_llm import title_llm
+from src.server.deep_agent.init_llm import title_llm
 
 
 def conversation_title(full_conversation):

src/server/deep_agent/tools/extract_suggested_questions.py

@@ -0,0 +1,75 @@
+import json
+from typing import List
+
+from langchain_core.messages import (
+    HumanMessage,
+    AIMessage,
+    ToolMessage,
+)
+
+from src.server.deep_agent.init_llm import suggested_llm
+
+
+def format_messages(messages, max_messages: int = 6) -> str:
+    """
+    将 LangGraph messages 转换为 LLM prompt 文本
+    """
+    messages = messages[-max_messages:]
+    lines: List[str] = []
+    for m in messages:
+        if isinstance(m, HumanMessage):
+            lines.append(f"User: {m.content}")
+        elif isinstance(m, AIMessage):
+            if m.content:
+                lines.append(f"Assistant: {m.content}")
+        elif isinstance(m, ToolMessage):
+            # Tool结果建议简单化
+            tool_output = str(m.content)
+            if len(tool_output) > 200:
+                tool_output = tool_output[:200] + "..."
+            lines.append(f"Tool Result: {tool_output}")
+    return "\n".join(lines)
+
+
+async def generate_suggested_questions(
+        agent,
+        thread_id: str,
+        max_messages: int = 6,
+) -> List[str]:
+    """
+    根据当前对话生成3条用户可能继续提问的问题
+    """
+    # 获取当前对话state
+    state = agent.get_state(
+        {"configurable": {"thread_id": thread_id}}
+    )
+    messages = state.values.get("messages", [])
+    if not messages:
+        return []
+    conversation = format_messages(messages, max_messages)
+
+    prompt = f"""
+    以下是用户与AI助手的对话：
+    {conversation}
+    请根据对话内容，生成3条用户可能继续提出的问题。
+    要求：
+    - 每条一句话
+    - 语言自然
+    - 不要解释
+    - 返回JSON数组
+    - 尽量与家具设计相关
+    示例：
+    ["问题1", "问题2", "问题3"]
+    """
+    result = await suggested_llm.ainvoke(prompt)
+
+    text = result.content.strip()
+
+    try:
+        questions = json.loads(text)
+
+        if isinstance(questions, list):
+            return questions[:3]
+    except Exception:
+        pass
+    return []

src/server/deep_agent/tools/report_generator_tool.py

@@ -2,27 +2,11 @@ import os
 import json
 import re
 from typing import Optional, List, Dict
-from langchain_qwq import ChatQwen
 from langgraph.config import get_stream_writer
 from pydantic import BaseModel, Field
 from langchain_core.tools import tool
 from langchain_core.messages import SystemMessage, HumanMessage
-
-from src.core.config import settings
-
-# =========================
-# LLM 初始化
-# =========================
-
-
-llm = ChatQwen(
-    enable_thinking=False,
-    model="qwen3.5-flash",
-    temperature=0.2,
-    max_tokens=3_000,
-    timeout=None,
-    max_retries=2,
-    api_key=settings.QWEN_API_KEY)
+from src.server.deep_agent.init_llm import repoer_llm
 
 
 # =========================
@@ -109,7 +93,7 @@ async def report_generator(
 
     full_report = ""
     try:
-        report_llm = llm.with_config(
+        report_llm = repoer_llm.with_config(
             callbacks=[]
         )
         async for chunk in report_llm.astream(