feat:任务执行结果性能优化

合并远程web分支更新

backend/AgentCoord/LLMAPI/LLMAPI.py

@@ -1,24 +1,35 @@
 import asyncio
-import openai
+
+import httpx
+from openai import OpenAI, AsyncOpenAI, max_retries
 import yaml
 from termcolor import colored
 import os
 
+# Helper function to avoid circular import
+def print_colored(text, text_color="green", background="on_white"):
+    print(colored(text, text_color, background))
+
 # load config (apikey, apibase, model)
 yaml_file = os.path.join(os.getcwd(), "config", "config.yaml")
 try:
     with open(yaml_file, "r", encoding="utf-8") as file:
         yaml_data = yaml.safe_load(file)
 except Exception:
-    yaml_file = {}
+    yaml_data = {}
 OPENAI_API_BASE = os.getenv("OPENAI_API_BASE") or yaml_data.get(
     "OPENAI_API_BASE", "https://api.openai.com"
 )
-openai.api_base = OPENAI_API_BASE
 OPENAI_API_KEY = os.getenv("OPENAI_API_KEY") or yaml_data.get(
     "OPENAI_API_KEY", ""
 )
-openai.api_key = OPENAI_API_KEY
+OPENAI_API_MODEL = os.getenv("OPENAI_API_MODEL") or yaml_data.get(
+    "OPENAI_API_MODEL", ""
+)
+
+# Initialize OpenAI clients
+client = OpenAI(api_key=OPENAI_API_KEY, base_url=OPENAI_API_BASE)
+async_client = AsyncOpenAI(api_key=OPENAI_API_KEY, base_url=OPENAI_API_BASE)
 MODEL: str = os.getenv("OPENAI_API_MODEL") or yaml_data.get(
     "OPENAI_API_MODEL", "gpt-4-turbo-preview"
 )
@@ -35,8 +46,11 @@ MISTRAL_API_KEY = os.getenv("MISTRAL_API_KEY") or yaml_data.get(
 
 # for LLM completion
 def LLM_Completion(
-    messages: list[dict], stream: bool = True, useGroq: bool = True
+    messages: list[dict], stream: bool = True, useGroq: bool = True,model_config: dict = None
 ) -> str:
+    if model_config:
+        print_colored(f"Using model config: {model_config}", "blue")
+        return _call_with_custom_config(messages,stream,model_config)
     if not useGroq or not FAST_DESIGN_MODE:
         force_gpt4 = True
         useGroq = False
@@ -69,16 +83,92 @@ def LLM_Completion(
         return _chat_completion(messages=messages)
 
 
+def _call_with_custom_config(messages: list[dict], stream: bool, model_config: dict) ->str:
+    "使用自定义配置调用API"
+    api_url = model_config.get("apiUrl", OPENAI_API_BASE)
+    api_key = model_config.get("apiKey", OPENAI_API_KEY)
+    api_model = model_config.get("apiModel", OPENAI_API_MODEL)
+
+    temp_client = OpenAI(api_key=api_key, base_url=api_url)
+    temp_async_client = AsyncOpenAI(api_key=api_key, base_url=api_url)
+
+    try:
+        if stream:
+            try:
+                loop = asyncio.get_event_loop()
+            except RuntimeError as ex:
+                if "There is no current event loop in thread" in str(ex):
+                    loop = asyncio.new_event_loop()
+                    asyncio.set_event_loop(loop)
+            return loop.run_until_complete(
+                _achat_completion_stream_custom(messages=messages, temp_async_client=temp_async_client, api_model=api_model)
+            )
+        else:
+            response = temp_client.chat.completions.create(
+                messages=messages,
+                model=api_model,
+                temperature=0.3,
+                max_tokens=4096,
+                timeout=180
+
+            )
+            full_reply_content = response.choices[0].message.content
+            print(colored(full_reply_content, "blue", "on_white"), end="")
+            return full_reply_content
+    except Exception as e:
+        print_colored(f"Custom API error for model {api_model} :{str(e)}","red")
+        raise
+
+
+async def _achat_completion_stream_custom(messages:list[dict], temp_async_client, api_model: str ) -> str:
+    max_retries=3
+    for attempt in range(max_retries):
+        try:
+            response = await temp_async_client.chat.completions.create(
+                messages=messages,
+                model=api_model,
+                temperature=0.3,
+                max_tokens=4096,
+                stream=True,
+                timeout=180
+            )
+
+            collected_chunks = []
+            collected_messages = []
+            async for chunk in response:
+                collected_chunks.append(chunk)
+                choices = chunk.choices
+                if len(choices) > 0:
+                    chunk_message = chunk.choices[0].delta
+                    collected_messages.append(chunk_message)
+                    if chunk_message.content:
+                        print(colored(chunk_message.content, "blue", "on_white"), end="")
+            print()
+            full_reply_content = "".join(
+                [m.content or "" for m in collected_messages if m is not None]
+            )
+            return full_reply_content
+        except httpx.RemoteProtocolError as e:
+            if attempt < max_retries - 1:
+                wait_time = (attempt + 1) *2
+                print_colored(f"⚠️ Stream connection interrupted (attempt {attempt+1}/{max_retries}). Retrying in {wait_time}s...", text_color="yellow")
+                await asyncio.sleep(wait_time)
+                continue
+        except Exception as e:
+            print_colored(f"Custom API stream error for model {api_model} :{str(e)}","red")
+            raise
+
+
 async def _achat_completion_stream_groq(messages: list[dict]) -> str:
     from groq import AsyncGroq
-    client = AsyncGroq(api_key=GROQ_API_KEY)
+    groq_client = AsyncGroq(api_key=GROQ_API_KEY)
 
     max_attempts = 5
 
     for attempt in range(max_attempts):
         print("Attempt to use Groq (Fase Design Mode):")
         try:
-            stream = await client.chat.completions.create(
+            response = await groq_client.chat.completions.create(
                 messages=messages,
                 # model='gemma-7b-it',
                 model="mixtral-8x7b-32768",
@@ -92,9 +182,9 @@ async def _achat_completion_stream_groq(messages: list[dict]) -> str:
             if attempt < max_attempts - 1:  # i is zero indexed
                 continue
             else:
-                raise "failed"
+                raise Exception("failed")
 
-    full_reply_content = stream.choices[0].message.content
+    full_reply_content = response.choices[0].message.content
     print(colored(full_reply_content, "blue", "on_white"), end="")
     print()
     return full_reply_content
@@ -103,14 +193,14 @@ async def _achat_completion_stream_groq(messages: list[dict]) -> str:
 async def _achat_completion_stream_mixtral(messages: list[dict]) -> str:
     from mistralai.client import MistralClient
     from mistralai.models.chat_completion import ChatMessage
-    client = MistralClient(api_key=MISTRAL_API_KEY)
+    mistral_client = MistralClient(api_key=MISTRAL_API_KEY)
     # client=AsyncGroq(api_key=GROQ_API_KEY)
     max_attempts = 5
 
     for attempt in range(max_attempts):
         try:
             messages[len(messages) - 1]["role"] = "user"
-            stream = client.chat(
+            stream = mistral_client.chat(
                 messages=[
                     ChatMessage(
                         role=message["role"], content=message["content"]
@@ -119,14 +209,13 @@ async def _achat_completion_stream_mixtral(messages: list[dict]) -> str:
                 ],
                 # model = "mistral-small-latest",
                 model="open-mixtral-8x7b",
-                # response_format={"type": "json_object"},
             )
             break  # If the operation is successful, break the loop
         except Exception:
             if attempt < max_attempts - 1:  # i is zero indexed
                 continue
             else:
-                raise "failed"
+                raise Exception("failed")
 
     full_reply_content = stream.choices[0].message.content
     print(colored(full_reply_content, "blue", "on_white"), end="")
@@ -135,15 +224,11 @@ async def _achat_completion_stream_mixtral(messages: list[dict]) -> str:
 
 
 async def _achat_completion_stream_gpt35(messages: list[dict]) -> str:
-    openai.api_key = OPENAI_API_KEY
+    response = await async_client.chat.completions.create(
-    openai.api_base = OPENAI_API_BASE
-    response = await openai.ChatCompletion.acreate(
         messages=messages,
         max_tokens=4096,
-        n=1,
-        stop=None,
         temperature=0.3,
-        timeout=3,
+        timeout=600,
         model="gpt-3.5-turbo-16k",
         stream=True,
     )
@@ -154,40 +239,32 @@ async def _achat_completion_stream_gpt35(messages: list[dict]) -> str:
     # iterate through the stream of events
     async for chunk in response:
         collected_chunks.append(chunk)  # save the event response
-        choices = chunk["choices"]
+        choices = chunk.choices
         if len(choices) > 0:
-            chunk_message = chunk["choices"][0].get(
+            chunk_message = chunk.choices[0].delta
-                "delta", {}
-            )  # extract the message
             collected_messages.append(chunk_message)  # save the message
-            if "content" in chunk_message:
+            if chunk_message.content:
                 print(
-                    colored(chunk_message["content"], "blue", "on_white"),
+                    colored(chunk_message.content, "blue", "on_white"),
                     end="",
                 )
     print()
 
     full_reply_content = "".join(
-        [m.get("content", "") for m in collected_messages]
+        [m.content or "" for m in collected_messages if m is not None]
     )
     return full_reply_content
 
 
-async def _achat_completion_json(messages: list[dict]) -> str:
+def _achat_completion_json(messages: list[dict] ) -> str:
-    openai.api_key = OPENAI_API_KEY
-    openai.api_base = OPENAI_API_BASE
-
     max_attempts = 5
-
     for attempt in range(max_attempts):
         try:
-            stream = await openai.ChatCompletion.acreate(
+            response =  async_client.chat.completions.create(
                 messages=messages,
                 max_tokens=4096,
-                n=1,
-                stop=None,
                 temperature=0.3,
-                timeout=3,
+                timeout=600,
                 model=MODEL,
                 response_format={"type": "json_object"},
             )
@@ -196,18 +273,17 @@ async def _achat_completion_json(messages: list[dict]) -> str:
             if attempt < max_attempts - 1:  # i is zero indexed
                 continue
             else:
-                raise "failed"
+                raise Exception("failed")
 
-    full_reply_content = stream.choices[0].message.content
+    full_reply_content = response.choices[0].message.content
     print(colored(full_reply_content, "blue", "on_white"), end="")
     print()
     return full_reply_content
 
 
 async def _achat_completion_stream(messages: list[dict]) -> str:
-    openai.api_key = OPENAI_API_KEY
+    try:
-    openai.api_base = OPENAI_API_BASE
+        response = await async_client.chat.completions.create(
-    response = await openai.ChatCompletion.acreate(
             **_cons_kwargs(messages), stream=True
         )
 
@@ -217,41 +293,42 @@ async def _achat_completion_stream(messages: list[dict]) -> str:
         # iterate through the stream of events
         async for chunk in response:
             collected_chunks.append(chunk)  # save the event response
-        choices = chunk["choices"]
+            choices = chunk.choices
             if len(choices) > 0:
-            chunk_message = chunk["choices"][0].get(
+                chunk_message = chunk.choices[0].delta
-                "delta", {}
-            )  # extract the message
                 collected_messages.append(chunk_message)  # save the message
-            if "content" in chunk_message:
+                if chunk_message.content:
                     print(
-                    colored(chunk_message["content"], "blue", "on_white"),
+                        colored(chunk_message.content, "blue", "on_white"),
                         end="",
                     )
         print()
 
         full_reply_content = "".join(
-        [m.get("content", "") for m in collected_messages]
+            [m.content or "" for m in collected_messages if m is not None]
         )
         return full_reply_content
+    except Exception as e:
+        print_colored(f"OpenAI API error in _achat_completion_stream: {str(e)}", "red")
+        raise
 
 
 def _chat_completion(messages: list[dict]) -> str:
-    print(messages, flush=True)
+    try:
-    rsp = openai.ChatCompletion.create(**_cons_kwargs(messages))
+        rsp = client.chat.completions.create(**_cons_kwargs(messages))
-    content = rsp["choices"][0]["message"]["content"]
+        content = rsp.choices[0].message.content
-    print(content, flush=True)
         return content
+    except Exception as e:
+        print_colored(f"OpenAI API error in _chat_completion: {str(e)}", "red")
+        raise
 
 
 def _cons_kwargs(messages: list[dict]) -> dict:
     kwargs = {
         "messages": messages,
-        "max_tokens": 4096,
+        "max_tokens": 2000,
-        "n": 1,
+        "temperature": 0.3,
-        "stop": None,
+        "timeout": 600,
-        "temperature": 0.5,
-        "timeout": 3,
     }
     kwargs_mode = {"model": MODEL}
     kwargs.update(kwargs_mode)

backend/AgentCoord/PlanEngine/AgentSelectModify.py

@@ -7,6 +7,8 @@ PROMPT_ABILITY_REQUIREMENT_GENERATION = """
 ## Instruction
 Based on "General Goal" and "Current Task", output a formatted "Ability Requirement" which lists at least 3 different ability requirement that is required by the "Current Task". The ability should be summarized concisely within a few words.
 
+**IMPORTANT LANGUAGE REQUIREMENT: You must respond in Chinese (中文) for all ability requirements.**
+
 ## General Goal (The general goal for the collaboration plan, "Current Task" is just one of its substep)
 {General_Goal}
 
@@ -49,6 +51,8 @@ PROMPT_AGENT_ABILITY_SCORING = """
 ## Instruction
 Based on "Agent Board" and "Ability Requirement", output a score for each agent to estimate the possibility that the agent can fulfil the "Ability Requirement". The score should be 1-5. Provide a concise reason before you assign the score.
 
+**IMPORTANT LANGUAGE REQUIREMENT: You must respond in Chinese (中文) for all reasons and explanations.**
+
 ## AgentBoard
 {Agent_Board}
 
@@ -133,5 +137,6 @@ def AgentSelectModify_init(stepTask, General_Goal, Agent_Board):
 
 
 def AgentSelectModify_addAspect(aspectList, Agent_Board):
-    scoreTable = agentAbilityScoring(Agent_Board, aspectList)
+    newAspect = aspectList[-1]
+    scoreTable = agentAbilityScoring(Agent_Board, [newAspect])
     return scoreTable

backend/AgentCoord/PlanEngine/AgentSelection_Generator.py

@@ -33,7 +33,9 @@ class JSON_ABILITY_REQUIREMENT_GENERATION(BaseModel):
 
 PROMPT_AGENT_SELECTION_GENERATION = """
 ## Instruction
-Based on "General Goal", "Current Task" and "Agent Board", output a formatted "Agent Selection Plan". Your selection should consider the ability needed for "Current Task" and the profile of each agent in "Agent Board". Agent Selection Plan ranks from high to low according to ability.
+Based on "General Goal", "Current Task" and "Agent Board", output a formatted "Agent Selection Plan". Your selection should consider the ability needed for "Current Task" and the profile of each agent in "Agent Board".
+
+**IMPORTANT LANGUAGE REQUIREMENT: You must respond in Chinese (中文) for all explanations and reasoning, though agent names should remain in their original form.**
 
 ## General Goal (Specify the general goal for the collaboration plan)
 {General_Goal}
@@ -80,6 +82,10 @@ def generate_AbilityRequirement(General_Goal, Current_Task):
 
 
 def generate_AgentSelection(General_Goal, Current_Task, Agent_Board):
+    # Check if Agent_Board is None or empty
+    if Agent_Board is None or len(Agent_Board) == 0:
+        raise ValueError("Agent_Board cannot be None or empty. Please ensure agents are set via /setAgents endpoint before generating a plan.")
+
     messages = [
         {
             "role": "system",

backend/AgentCoord/PlanEngine/basePlan_Generator.py

@@ -1,55 +1,53 @@
 from AgentCoord.PlanEngine.planOutline_Generator import generate_PlanOutline
-from AgentCoord.PlanEngine.AgentSelection_Generator import (
+# from AgentCoord.PlanEngine.AgentSelection_Generator import (
-    generate_AgentSelection,
+#     generate_AgentSelection,
-)
+# )
-from AgentCoord.PlanEngine.taskProcess_Generator import generate_TaskProcess
-import AgentCoord.util as util
 
 
 def generate_basePlan(
-    General_Goal, Agent_Board, AgentProfile_Dict, InitialObject_List, context
+    General_Goal, Agent_Board, AgentProfile_Dict, InitialObject_List
 ):
-    basePlan = {
+    """
-        "Initial Input Object": InitialObject_List,
+    优化模式：生成大纲 + 智能体选择，但不生成任务流程
-        "Collaboration Process": [],
+    优化用户体验：
-    }
+    1. 快速生成大纲和分配智能体
+    2. 用户可以看到完整的大纲和智能体图标
+    3. TaskProcess由前端通过 fillStepTask API 异步填充
+
+    """
+    # 参数保留以保持接口兼容性
+    _ = AgentProfile_Dict
     PlanOutline = generate_PlanOutline(
-        InitialObject_List=[], General_Goal=General_Goal + context
+        InitialObject_List=InitialObject_List, General_Goal=General_Goal
     )
+
+    basePlan = {
+        "General Goal": General_Goal,
+        "Initial Input Object": InitialObject_List,
+        "Collaboration Process": []
+    }
+
     for stepItem in PlanOutline:
-        Current_Task = {
+        # # 为每个步骤分配智能体
-            "TaskName": stepItem["StepName"],
+        # Current_Task = {
-            "InputObject_List": stepItem["InputObject_List"],
+        #     "TaskName": stepItem["StepName"],
-            "OutputObject": stepItem["OutputObject"],
+        #     "InputObject_List": stepItem["InputObject_List"],
-            "TaskContent": stepItem["TaskContent"],
+        #     "OutputObject": stepItem["OutputObject"],
+        #     "TaskContent": stepItem["TaskContent"],
+        # }
+        # AgentSelection = generate_AgentSelection(
+        #     General_Goal=General_Goal,
+        #     Current_Task=Current_Task,
+        #     Agent_Board=Agent_Board,
+        # )
+
+        # 添加智能体选择，但不添加任务流程
+        stepItem["AgentSelection"] = []
+        stepItem["TaskProcess"] = []  # 空数组，由前端异步填充
+        stepItem["Collaboration_Brief_frontEnd"] = {
+            "template": "",
+            "data": {}
         }
-        AgentSelection = generate_AgentSelection(
-            General_Goal=General_Goal,
-            Current_Task=Current_Task,
-            Agent_Board=Agent_Board,
-        )
-        Current_Task_Description = {
-            "TaskName": stepItem["StepName"],
-            "AgentInvolved": [
-                {"Name": name, "Profile": AgentProfile_Dict[name]}
-                for name in AgentSelection
-            ],
-            "InputObject_List": stepItem["InputObject_List"],
-            "OutputObject": stepItem["OutputObject"],
-            "CurrentTaskDescription": util.generate_template_sentence_for_CollaborationBrief(
-                stepItem["InputObject_List"],
-                stepItem["OutputObject"],
-                AgentSelection,
-                stepItem["TaskContent"],
-            ),
-        }
-        TaskProcess = generate_TaskProcess(
-            General_Goal=General_Goal + context,
-            Current_Task_Description=Current_Task_Description,
-        )
-        # add the generated AgentSelection and TaskProcess to the stepItem
-        stepItem["AgentSelection"] = AgentSelection
-        stepItem["TaskProcess"] = TaskProcess
         basePlan["Collaboration Process"].append(stepItem)
-    basePlan["General Goal"] = General_Goal
+
     return basePlan

backend/AgentCoord/PlanEngine/branch_PlanOutline.py

@@ -9,6 +9,8 @@ PROMPT_PLAN_OUTLINE_BRANCHING = """
 Based on "Existing Steps", your task is to comeplete the "Remaining Steps" for the plan for "General Goal".
 Note: "Modification Requirement" specifies how to modify the "Baseline Completion" for a better/alternative solution.
 
+**IMPORTANT LANGUAGE REQUIREMENT: You must respond in Chinese (中文) for all content, including StepName, TaskContent, and OutputObject fields.**
+
 ## General Goal (Specify the general goal for the plan)
 {General_Goal}
 

backend/AgentCoord/PlanEngine/branch_TaskProcess.py

@@ -29,6 +29,8 @@ PROMPT_TASK_PROCESS_BRANCHING = """
 Based on "Existing Steps", your task is to comeplete the "Remaining Steps" for the "Task for Current Step".
 Note: "Modification Requirement" specifies how to modify the "Baseline Completion" for a better/alternative solution.
 
+**IMPORTANT LANGUAGE REQUIREMENT: You must respond in Chinese (中文) for the Description field and all explanations, while keeping ID, ActionType, and AgentName in their original format.**
+
 ## General Goal (The general goal for the collaboration plan, you just design the plan for one of its step (i.e. "Task for Current Step"))
 {General_Goal}
 
@@ -55,27 +57,40 @@ Note: "Modification Requirement" specifies how to modify the "Baseline Completio
       "ID": "Action4",
       "ActionType": "Propose",
       "AgentName": "Mia",
-      "Description": "Propose psychological theories on love and attachment that could be applied to AI's emotional development.",
+      "Description": "提议关于人工智能情感发展的心理学理论，重点关注爱与依恋的概念。",
       "ImportantInput": [
         "InputObject:Story Outline"
       ]
     }},
     {{
       "ID": "Action5",
-      "ActionType": "Propose",
+      "ActionType": "Critique",
       "AgentName": "Noah",
-      "Description": "Propose ethical considerations and philosophical questions regarding AI's capacity for love.",
+      "Description": "对Mia提出的心理学理论进行批判性评估，分析其在AI情感发展场景中的适用性和局限性。",
-      "ImportantInput": []
+      "ImportantInput": [
+        "ActionResult:Action4"
+      ]
     }},
     {{
       "ID": "Action6",
-      "ActionType": "Finalize",
+      "ActionType": "Improve",
       "AgentName": "Liam",
-      "Description": "Combine the poetic elements and ethical considerations into a cohesive set of core love elements for the story.",
+      "Description": "基于Noah的批判性反馈，改进和完善心理学理论框架，使其更贴合AI情感发展的实际需求。",
       "ImportantInput": [
-        "ActionResult:Action1",
+        "ActionResult:Action4",
         "ActionResult:Action5"
       ]
+    }},
+    {{
+      "ID": "Action7",
+      "ActionType": "Finalize",
+      "AgentName": "Mia",
+      "Description": "综合所有提议、批判和改进意见，整合并提交最终的AI情感发展心理学理论框架。",
+      "ImportantInput": [
+        "ActionResult:Action4",
+        "ActionResult:Action5",
+        "ActionResult:Action6"
+      ]
     }}
   ]
 }}
@@ -84,7 +99,12 @@ Note: "Modification Requirement" specifies how to modify the "Baseline Completio
 ImportantInput: Specify if there is any previous result that should be taken special consideration during the execution the action. Should be of format "InputObject:xx" or "ActionResult:xx".
 InputObject_List: List existing objects that should be utilized in current step.
 AgentName: Specify the agent who will perform the action, You CAN ONLY USE THE NAME APPEARS IN "AgentInvolved".
-ActionType: Specify the type of action, note that only the last action can be of type "Finalize", and the last action must be "Finalize".
+ActionType: Specify the type of action. **CRITICAL REQUIREMENTS:**
+  1. The "Remaining Steps" MUST include ALL FOUR action types in the following order: Propose -> Critique -> Improve -> Finalize
+  2. Each action type (Propose, Critique, Improve, Finalize) MUST appear at least once
+  3. The actions must follow the sequence: Propose actions first, then Critique actions, then Improve actions, and Finalize must be the last action
+  4. Even if only one agent is involved in a phase, that phase must still have its corresponding action type
+  5. The last action must ALWAYS be of type "Finalize"
 
 """
 

backend/AgentCoord/PlanEngine/planOutline_Generator.py

@@ -5,7 +5,9 @@ import json
 
 PROMPT_PLAN_OUTLINE_GENERATION = """
 ## Instruction
-Based on "Output Format Example", "General Goal", and "Initial Key Object List", output a formatted "Plan_Outline". The number of steps in the Plan Outline cannot exceed 5.
+Based on "Output Format Example", "General Goal", and "Initial Key Object List", output a formatted "Plan_Outline".
+
+**IMPORTANT LANGUAGE REQUIREMENT: You must respond in Chinese (中文) for all content, including StepName, TaskContent, and OutputObject fields.**
 
 ## Initial Key Object List (Specify the list of initial key objects available, each initial key object should be the input object of at least one Step)
 {InitialObject_List}
@@ -51,7 +53,6 @@ TaskContent: Describe the task of the current step.
 InputObject_List: The list of the input obejects that will be used in current step.
 OutputObject: The name of the final output object of current step.
 
-请用中文回答
 """
 
 
@@ -84,4 +85,16 @@ def generate_PlanOutline(InitialObject_List, General_Goal):
             ),
         },
     ]
-    return read_LLM_Completion(messages)["Plan_Outline"]
+    result = read_LLM_Completion(messages)
+    if isinstance(result, dict) and "Plan_Outline" in result:
+        return result["Plan_Outline"]
+    else:
+        # 如果格式不正确，返回默认的计划大纲
+        return [
+            {
+                "StepName": "Default Step",
+                "TaskContent": "Generated default plan step due to format error",
+                "InputObject_List": [],
+                "OutputObject": "Default Output"
+            }
+        ]

backend/AgentCoord/PlanEngine/taskProcess_Generator.py

@@ -25,6 +25,8 @@ PROMPT_TASK_PROCESS_GENERATION = """
 ## Instruction
 Based on "General Goal", "Task for Current Step", "Action Set" and "Output Format Example", design a plan for "Task for Current Step", output a formatted "Task_Process_Plan".
 
+**IMPORTANT LANGUAGE REQUIREMENT: You must respond in Chinese (中文) for the Description field and all explanations, while keeping ID, ActionType, and AgentName in their original format.**
+
 ## General Goal (The general goal for the collaboration plan, you just design the plan for one of its step (i.e. "Task for Current Step"))
 {General_Goal}
 
@@ -90,7 +92,6 @@ InputObject_List: List existing objects that should be utilized in current step.
 AgentName: Specify the agent who will perform the action, You CAN ONLY USE THE NAME APPEARS IN "AgentInvolved".
 ActionType: Specify the type of action, note that only the last action can be of type "Finalize", and the last action must be "Finalize".
 
-请用中文回答
 """
 
 

backend/AgentCoord/RehearsalEngine_V2/Action/baseAction.py

@@ -9,6 +9,8 @@ You are within a multi-agent collaboration for the "Current Task".
 Now it's your turn to take action. Read the "Context Information" and take your action following "Instruction for Your Current Action".
 Note: Important Input for your action are marked with *Important Input*
 
+**IMPORTANT LANGUAGE REQUIREMENT: You must respond in Chinese (中文) for all your answers and outputs.**
+
 ## Context Information
 
 ### General Goal (The "Current Task" is indeed a substep of the general goal)
@@ -80,10 +82,34 @@ class BaseAction():
                 Important_Mark = ""
             action_Record += PROMPT_TEMPLATE_ACTION_RECORD.format(AgentName = actionInfo["AgentName"], Action_Description = actionInfo["AgentName"], Action_Result = actionInfo["Action_Result"], Important_Mark = Important_Mark)
 
-        prompt = PROMPT_TEMPLATE_TAKE_ACTION_BASE.format(agentName = agentName, agentProfile = AgentProfile_Dict[agentName], General_Goal = General_Goal, Current_Task_Description = TaskDescription, Input_Objects = inputObject_Record, History_Action = action_Record, Action_Description = self.info["Description"], Action_Custom_Note = self.Action_Custom_Note)
+        # Handle missing agent profiles gracefully
+        model_config = None
+        if agentName not in AgentProfile_Dict:
+            print_colored(text=f"Warning: Agent '{agentName}' not found in AgentProfile_Dict. Using default profile.", text_color="yellow")
+            agentProfile = f"AI Agent named {agentName}"
+        else:
+            # agentProfile = AgentProfile_Dict[agentName]
+            agent_config = AgentProfile_Dict[agentName]
+            agentProfile = agent_config.get("profile",f"AI Agent named {agentName}")
+            if agent_config.get("useCustomAPI",False):
+                model_config = {
+                    "apiModel":agent_config.get("apiModel"),
+                    "apiUrl":agent_config.get("apiUrl"),
+                    "apiKey":agent_config.get("apiKey"),
+                }
+        prompt = PROMPT_TEMPLATE_TAKE_ACTION_BASE.format(
+            agentName = agentName,
+            agentProfile = agentProfile,
+            General_Goal = General_Goal,
+            Current_Task_Description = TaskDescription,
+            Input_Objects = inputObject_Record,
+            History_Action = action_Record,
+            Action_Description = self.info["Description"],
+            Action_Custom_Note = self.Action_Custom_Note
+        )
         print_colored(text = prompt, text_color="red")
         messages = [{"role":"system", "content": prompt}]
-        ActionResult = LLM_Completion(messages,True,False)
+        ActionResult = LLM_Completion(messages,True,False,model_config=model_config)
         ActionInfo_with_Result = copy.deepcopy(self.info)
         ActionInfo_with_Result["Action_Result"] = ActionResult
 

backend/AgentCoord/RehearsalEngine_V2/Action/customAction_Critique.py

@@ -1,7 +1,7 @@
 from AgentCoord.RehearsalEngine_V2.Action import BaseAction
 
 ACTION_CUSTOM_NOTE = '''
-Note: Since you are in a conversation, your critique must be concise, clear and easy to read, don't overwhelm others. If you want to list some points, list at most 2 points. 
+注意：由于你在对话中，你的批评必须简洁、清晰且易于阅读，不要让人感到压力过大。如果你要列出一些观点，最多列出2点。
 
 '''
 

backend/AgentCoord/RehearsalEngine_V2/Action/customAction_Finalize.py

@@ -2,9 +2,9 @@ from AgentCoord.util.converter import read_outputObject_content
 from AgentCoord.RehearsalEngine_V2.Action import BaseAction
 
 ACTION_CUSTOM_NOTE = '''
-Note: You can say something before you give the final content of {OutputName}. When you decide to give the final content of {OutputName}, it should be enclosed like this:
+注意：你可以在给出{OutputName}的最终内容之前先说一些话。当你决定给出{OutputName}的最终内容时，应该这样包含：
 ```{OutputName}
-(the content of {OutputName})
+（{OutputName}的内容）
 ```
 '''
 

backend/AgentCoord/RehearsalEngine_V2/Action/customAction_Improve.py

@@ -1,12 +1,12 @@
 from AgentCoord.RehearsalEngine_V2.Action import BaseAction
 
 ACTION_CUSTOM_NOTE = '''
-Note: You can say something before you provide the improved version of the content.
+注意：你可以在提供改进版本的内容之前先说一些话。
-The improved version you provide must be a completed version (e.g. if you provide a improved story, you should give completed story content, rather than just reporting where you have improved).
+你提供的改进版本必须是完整的版本（例如，如果你提供改进的故事，你应该给出完整的故事内容，而不仅仅是报告你在哪里改进了）。
-When you decide to give the improved version of the content, it should be start like this:
+当你决定提供内容的改进版本时，应该这样开始：
 
 ## xxx的改进版本
-(the improved version of the content)
+（改进版本的内容）
 ```
 
 '''

backend/AgentCoord/RehearsalEngine_V2/ExecutePlan.py

@@ -4,7 +4,7 @@ from termcolor import colored
 
 
 # Accept inputs: num_StepToRun (the number of step to run, if None, run to the end), plan, RehearsalLog, AgentProfile_Dict
-def executePlan(plan, num_StepToRun, RehearsalLog, AgentProfile_Dict, context):
+def executePlan(plan, num_StepToRun, RehearsalLog, AgentProfile_Dict):
     # Prepare for execution
     KeyObjects = {}
     finishedStep_index = -1
@@ -85,9 +85,17 @@ def executePlan(plan, num_StepToRun, RehearsalLog, AgentProfile_Dict, context):
         # start the group chat
         util.print_colored(TaskDescription, text_color="green")
         ActionHistory = []
+        action_count = 0
+        total_actions = len(TaskProcess)
+
         for ActionInfo in TaskProcess:
+            action_count += 1
             actionType = ActionInfo["ActionType"]
             agentName = ActionInfo["AgentName"]
+
+            # 添加进度日志
+            util.print_colored(f"🔄 Executing action {action_count}/{total_actions}: {actionType} by {agentName}", text_color="yellow")
+
             if actionType in Action.customAction_Dict:
                 currentAction = Action.customAction_Dict[actionType](
                     info=ActionInfo,
@@ -101,7 +109,7 @@ def executePlan(plan, num_StepToRun, RehearsalLog, AgentProfile_Dict, context):
                     KeyObjects=KeyObjects,
                 )
             ActionInfo_with_Result = currentAction.run(
-                General_Goal=plan["General Goal"] + "\n\n### Useful Information (some information can help accomplish the task)\n如果使用该信息，请在回答中显示指出是来自数联网的数据。例如，基于数联网数据搜索结果。" + context,
+                General_Goal=plan["General Goal"],
                 TaskDescription=TaskDescription,
                 agentName=agentName,
                 AgentProfile_Dict=AgentProfile_Dict,
@@ -113,8 +121,6 @@ def executePlan(plan, num_StepToRun, RehearsalLog, AgentProfile_Dict, context):
             ActionHistory.append(ActionInfo_with_Result)
         # post processing for the group chat (finish)
         objectLogNode["content"] = KeyObjects[OutputName]
-        if StepRun_count == len(plan["Collaboration Process"][(finishedStep_index + 1): run_to]):
-            objectLogNode["content"] += context
         RehearsalLog.append(stepLogNode)
         RehearsalLog.append(objectLogNode)
         stepLogNode["ActionHistory"] = ActionHistory

backend/AgentCoord/util/converter.py

@@ -20,6 +20,8 @@ def camel_case_to_normal(s):
 def generate_template_sentence_for_CollaborationBrief(
     input_object_list, output_object, agent_list, step_task
 ):
+    # Ensure step_task is not None
+    step_task = step_task if step_task is not None else "perform the task"
     # Check if the names are in camel case (no spaces) and convert them to normal naming convention
     input_object_list = (
         [
@@ -31,29 +33,48 @@ def generate_template_sentence_for_CollaborationBrief(
     )
     output_object = (
         camel_case_to_normal(output_object)
-        if is_camel_case(output_object)
+        if output_object is not None and is_camel_case(output_object)
-        else output_object
+        else (output_object if output_object is not None else "unknown output")
     )
 
     # Format the agents into a string with proper grammar
+    if agent_list is None or len(agent_list) == 0:
+        agent_str = "Unknown agents"
+    elif all(agent is not None for agent in agent_list):
         agent_str = (
             " and ".join([", ".join(agent_list[:-1]), agent_list[-1]])
             if len(agent_list) > 1
             else agent_list[0]
         )
+    else:
+        # Filter out None values
+        filtered_agents = [agent for agent in agent_list if agent is not None]
+        if filtered_agents:
+            agent_str = (
+                " and ".join([", ".join(filtered_agents[:-1]), filtered_agents[-1]])
+                if len(filtered_agents) > 1
+                else filtered_agents[0]
+            )
+        else:
+            agent_str = "Unknown agents"
 
     if input_object_list is None or len(input_object_list) == 0:
         # Combine all the parts into the template sentence
         template_sentence = f"{agent_str} perform the task of {step_task} to obtain {output_object}."
     else:
         # Format the input objects into a string with proper grammar
+        # Filter out None values from input_object_list
+        filtered_input_list = [obj for obj in input_object_list if obj is not None]
+        if filtered_input_list:
             input_str = (
                 " and ".join(
-                [", ".join(input_object_list[:-1]), input_object_list[-1]]
+                    [", ".join(filtered_input_list[:-1]), filtered_input_list[-1]]
                 )
-            if len(input_object_list) > 1
+                if len(filtered_input_list) > 1
-            else input_object_list[0]
+                else filtered_input_list[0]
             )
+        else:
+            input_str = "unknown inputs"
         # Combine all the parts into the template sentence
         template_sentence = f"Based on {input_str}, {agent_str} perform the task of {step_task} to obtain {output_object}."
 
@@ -90,7 +111,7 @@ def read_LLM_Completion(messages, useGroq=True):
                 return json.loads(match.group(0).strip())
             except Exception:
                 pass
-    raise ("bad format!")
+    return {}  # 返回空对象而不是抛出异常
 
 
 def read_json_content(text):
@@ -111,7 +132,7 @@ def read_json_content(text):
     if match:
         return json.loads(match.group(0).strip())
 
-    raise ("bad format!")
+    return {}  # 返回空对象而不是抛出异常
 
 
 def read_outputObject_content(text, keyword):
@@ -127,4 +148,4 @@ def read_outputObject_content(text, keyword):
     if match:
         return match.group(1).strip()
     else:
-        raise ("bad format!")
+        return ""  # 返回空字符串而不是抛出异常

backend/AgentRepo/科创.json

@@ -1,97 +0,0 @@
-[
-    {
-        "Icon": "Hailey_Johnson.png",
-        "Name": "船舶设计师",
-        "Profile": "提供船舶制造中的实际需求和约束。"
-    },
-    {
-        "Icon": "Jennifer_Moore.png",
-        "Name": "防护工程专家",
-        "Profile": "专注于船舶腐蚀防护技术的设计与应用。在你的总结回答中，必须引用来自数联网的搜索数据，是搜索数据，不是数联网的研究成果。"
-    },
-    {
-        "Icon": "Jane_Moreno.png",
-        "Name": "病理生理学家",
-        "Profile": "专注于失血性休克的疾病机制，为药物研发提供理论靶点。"
-    },
-    {
-        "Icon": "Giorgio_Rossi.png",
-        "Name": "药物化学家",
-        "Profile": "负责将靶点概念转化为实际可合成的分子。"
-    },
-    {
-        "Icon": "Tamara_Taylor.png",
-        "Name": "制剂工程师",
-        "Profile": "负责将活性药物成分（API）变成稳定、可用、符合战场要求的剂型。"
-    },
-    {
-        "Icon": "Maria_Lopez.png",
-        "Name": "监管事务专家",
-        "Profile": "深谙药品审评法规，目标是找到最快的合法上市路径。"
-    },
-    {
-        "Icon": "Sam_Moore.png",
-        "Name": "物理学家",
-        "Profile": "从热力学与统计力学的基本原理出发，研究液态金属的自由能、焓、熵、比热等参数的理论建模。"
-    },
-    {
-        "Icon": "Yuriko_Yamamoto.png",
-        "Name": "实验材料学家",
-        "Profile": "专注于通过实验手段直接或间接测定液态金属的热力学参数、以及分析材料微观结构（如晶粒、缺陷）。"
-    },
-    {
-        "Icon": "Carlos_Gomez.png",
-        "Name": "计算模拟专家",
-        "Profile": "侧重于利用数值计算和模拟技术获取液态金属的热力学参数。"
-    },
-    {
-        "Icon": "John_Lin.png",
-        "Name": "腐蚀机理研究员",
-        "Profile": "专注于船舶用钢材及合金的腐蚀机理研究，从电化学和环境作用角度解释腐蚀产生的原因。在你的总结回答中，必须引用来自数联网的搜索数据，是搜索数据，不是数联网的研究成果。"
-    },
-    {
-        "Icon": "Arthur_Burton.png",
-        "Name": "先进材料研发员",
-        "Profile": "专注于开发和评估新型耐腐蚀材料、复合材料及固态电池材料。"
-    },
-    {
-        "Icon": "Eddy_Lin.png",
-        "Name": "肾脏病学家",
-        "Profile": "专注于慢性肾脏病的诊断、治疗和患者管理，能提供临床洞察。"
-    },
-    {
-        "Icon": "Isabella_Rodriguez.png",
-        "Name": "临床研究协调员",
-        "Profile": "负责受试者招募和临床试验流程优化。"
-    },
-    {
-        "Icon": "Latoya_Williams.png",
-        "Name": "中医药专家",
-        "Profile": "理解药物的中药成分和作用机制。"
-    },
-    {
-        "Icon": "Carmen_Ortiz.png",
-        "Name": "药物安全专家",
-        "Profile": "专注于药物不良反应数据收集、分析和报告。"
-    },    
-    {
-        "Icon": "Rajiv_Patel.png",
-        "Name": "二维材料科学家",
-        "Profile": "专注于二维材料（如石墨烯）的合成、性质和应用。"
-    },  
-    {
-        "Icon": "Tom_Moreno.png",
-        "Name": "光电物理学家",
-        "Profile": "研究材料的光电转换机制和关键影响因素。"
-    },
-    {
-        "Icon": "Ayesha_Khan.png",
-        "Name": "机器学习专家",
-        "Profile": "专注于开发和应用AI模型用于材料模拟。"
-    },
-    {
-        "Icon": "Mei_Lin.png",
-        "Name": "流体动力学专家",
-        "Profile": "专注于流体行为理论和模拟。"
-    }
-]

backend/config/config.yaml

@@ -1,12 +1,12 @@
 ## config for default LLM
-OPENAI_API_BASE: ""
+OPENAI_API_BASE: "https://ai.gitee.com/v1"
-OPENAI_API_KEY: ""
+OPENAI_API_KEY: "HYCNGM39GGFNSB1F8MBBMI9QYJR3P1CRSYS2PV1A"
-OPENAI_API_MODEL: "gpt-4-turbo-preview"
+OPENAI_API_MODEL: "DeepSeek-V3"
 
 ## config for fast mode
-FAST_DESIGN_MODE: True
+FAST_DESIGN_MODE: False
 GROQ_API_KEY: ""
 MISTRAL_API_KEY: ""
 
 ## options under experimentation, leave them as Fasle unless you know what it is for
-USE_CACHE: True
+USE_CACHE: False

backend/requirements.txt

@@ -1,5 +1,5 @@
 Flask==3.0.2
-openai==0.28.1
+openai==2.8.1
 PyYAML==6.0.1
 termcolor==2.4.0
 groq==0.4.2

backend/server.py

@@ -1,8 +1,8 @@
-from flask import Flask, request, jsonify
+from flask import Flask, request, jsonify, Response, stream_with_context
 import json
-import time
 from DataProcess import Add_Collaboration_Brief_FrontEnd
 from AgentCoord.RehearsalEngine_V2.ExecutePlan import executePlan
+from AgentCoord.RehearsalEngine_V2.ExecutePlan_Optimized import executePlan_streaming
 from AgentCoord.PlanEngine.basePlan_Generator import generate_basePlan
 from AgentCoord.PlanEngine.fill_stepTask import fill_stepTask
 from AgentCoord.PlanEngine.fill_stepTask_TaskProcess import (
@@ -32,56 +32,6 @@ else:
     USE_CACHE = USE_CACHE.lower() in ["true", "1", "yes"]
 AgentBoard = None
 AgentProfile_Dict = {}
-c1 = '''
-
-=====数联网搜索结果=====
-
-1. 论文
-
-- 《Surface Defect Detection and Evaluation for Marine Vessels using Multi-Stage Deep Learning》提出一个面向船舶制造与检修的多阶段深度学习流水线，用于船体表面缺陷检测与评估，重点识别和量化与船舶制造材料腐蚀相关的现象，包括腐蚀（rust）、附着物（fouling）、涂层剥离（delamination）等。研究特别关注船舶材料腐蚀在不同涂层颜色、光照条件和相机角度下的鲁棒性，有助于提高船舶制造过程中对材料腐蚀的检测与管理能力。论文强调其方法在船舶材料表面腐蚀监测和维修决策中的应用价值。链接：https://arxiv.org/abs/2203.09580
-论文复现链接：http://8.130.138.52:21001/#/view/reproduction?doid=newID/5a4fef68-a138-4adb-ba88-43aa4474c08c
-
-- 《Efficient Metal Corrosion Area Detection Model Combining Convolution and Transformer (MCD-Net)》提出了一种高效的金属腐蚀区域检测模型。该模型创新性地结合了卷积编码器与视觉Transformer序列编码器，利用注意力融合模块增强边界识别，并采用基于得分的多尺度增强机制来突出腐蚀区域。该方法在阴影、遮挡和复杂纹理条件下依然能保持高精度，在公开数据集上取得了优异的F1性能，特别适用于船舶制造与检修中对船体钢板和涂层腐蚀的自动化识别与量化分析。链接：https://www.mdpi.com/2076-3417/14/21/9900 
-论文复现链接：http://8.130.138.52:21001/#/view/reproduction?doid=newID/b200a489-e2c8-4dbd-8767-682d15dd4c04
-
-- 《Mechanical Failure and Metal Degradation of Ships and Marine Structures》系统探讨了船舶与海洋结构中金属材料（包括高强钢、不锈钢、铜合金、钛合金等）在海洋环境下的机械损伤与电化学腐蚀协同作用问题。重点分析了"机械载荷+腐蚀"耦合导致的疲劳、裂纹及腐蚀裂纹等失效机制，并对相应的检测、预警与保护措施进行了深入讨论。链接：https://doi.org/10.3390/met13020272
-
-- 《Research Progress of Marine Anti-Fouling Coatings》（2024）全面综述了海洋防污涂层的研究进展，涵盖自我抛光涂料、生物可降解涂料、低表面能涂层、仿生涂层和纳米涂层等新型涂层技术。虽然重点在于防污，但文中指出许多防污机制与防腐蚀机制相互关联，通过阻碍生物附着可有效减少微生物引起的腐蚀和表面破坏。链接：https://doi.org/10.3390/coatings14091227
-
-- 《Corrosion-Wear Behavior of Shipbuilding Steels (EH40, FH40, 921A) in Seawater》研究了三种常用船用钢（EH40、FH40、921A）在海水环境中磨损与腐蚀共同作用下的复合失效行为。通过机械-电化学方法系统测定了腐蚀磨损损失、表面形貌变化和耐腐蚀性能差异，发现在此类工况中921A钢表现最佳。《Journal of Chinese Society for Corrosion and Protection》, Vol 45(4): 894-904, 2025
-
-- 《Sulfur-Selenium Alloy Coatings for Universal Corrosion Resistance》设计了一种硫-硒合金涂层，能够在包括模拟海水和硫酸盐还原菌生物环境在内的各种条件下为钢材提供高效的防腐蚀保护（约99.9%效率），腐蚀速率比裸钢低6-7个数量级。该涂层具有良好的机械性能、非多孔结构，能有效阻碍多种扩散性腐蚀因子的渗透。arXiv:2009.02451
-
-2. 代码
-
-- CoaST - Anti-corrosive coatings research (DTU, Denmark)：丹麦技术大学的CoaST项目专注于抗腐蚀涂层的性能表征与失效机制分析。该项目采用电化学测试与表面/界面无损检测技术相结合的方法，系统评估涂层的保护效果与失效途径，为船舶腐蚀防护提供了重要的研究平台。链接：https://www.kt.dtu.dk/research/coast/research-areas/anti-corrosive-coatings
-
-- Surface Defect Detection 仓库：该仓库集成了多种表面缺陷检测算法，为实现船舶腐蚀检测提供了可靠的代码基础和参考架构。链接：https://github.com/Charmve/Surface-Defect-Detection
-
-- Hugging Face 预训练模型：平台提供了轻量级的腐蚀检测模型，可直接下载并微调，用于快速验证和部署。链接：https://huggingface.co/mahdavian/corrosion-model
-
-3. 数据集
-
-用于训练和验证MCD-Net模型的相关数据集包括：
-
-- iamcloud/Corrosion_Dataset：一个包含约2000多张标注图像的数据集（ImageFolder格式，Apache-2.0协议），专门收录材料腐蚀图像，适用于船舶腐蚀监测模型的训练。链接：https://huggingface.co/datasets/iamcloud/Corrosion_Dataset
-
-- Francesco/corrosion-bi3q3：此数据集提供了多种腐蚀实例，可用于支持船舶涂层损坏与基体腐蚀的自动化检测任务。链接：https://huggingface.co/datasets/Francesco/corrosion-bi3q3。
-
-4. 研究团队
-
-- 海洋腐蚀与防护全国重点实验室是我国在该领域最具权威性的国家级研究机构，依托于中国船舶集团旗下725所。实验室提供从材料、设计到运维的全生命周期腐蚀控制解决方案，其核心优势在于能够进行多技术（如“阴极保护+涂层”）的综合集成研发与验证。其研究成果广泛应用于船舶、海洋平台等国家重大工程，为保障我国海洋装备的安全与耐久性提供了关键支撑。
-
-- 水性船舶防腐涂层新材料项目团队是一支源自东北石油大学的创新创业团队，专注于推动船舶涂料行业的环保化转型。团队致力于攻克水性涂料在船舶高湿环境下干燥慢、早期耐水性差的技术瓶颈，旨在开发出兼具优异防腐性能和施工便利性的水性体系，以替代传统溶剂型涂料，其目标是实现进口产品替代并大幅减少船舶制造与维修过程中的VOCs排放。
-
-- 微纳一体化防腐耐磨技术研发团队是以广州航海学院青年技术骨干为核心的新锐力量。团队针对铝合金在极端海洋环境中的腐蚀-磨损难题，创新性地提出了“微米级氧化陶瓷层+纳米自润滑固化层+改性硅烷钝化层”的三层复合防护体系。该技术使防护层的结合强度、耐磨性（提升2000倍）和耐腐蚀性能（自腐蚀电流密度降低6个数量级）实现了质的飞跃。
-
-- 北京大学南京创新研究院BXCFD团队专注于自主可控的高性能计算流体力学软件研发。团队在船舶与海洋工程水动力学领域取得关键突破，其自主研发的软件在船舶兴波阻力预报精度上达到国际先进水平，并成功实现了对复杂的船-桨-舵6自由度运动的耦合高精度模拟，为船舶水动力性能研究与优化提供了强大的国产化工具。
-
-- 清华大学多相流与生物流动力学实验室由罗先武教授带领，长期专注于流体机械及工程领域。团队重点研究高速船舶喷水推进装置的基础理论与空化流动机理，其研究成果为攻克喷水推进系统中的空化、振动与噪声问题提供了坚实的理论依据和技术支持，对我国高性能船舶推进技术的发展具有重要意义。
-
-'''
-context = {"材料腐蚀":c1}
 Request_Cache: dict[str, str] = {}
 app = Flask(__name__)
 
@@ -99,7 +49,6 @@ def Handle_fill_stepTask_TaskProcess():
 
     if USE_CACHE:
         if requestIdentifier in Request_Cache:
-            time.sleep(1)
             return jsonify(Request_Cache[requestIdentifier])
 
     filled_stepTask = fill_stepTask_TaskProcess(
@@ -170,7 +119,6 @@ def Handle_fill_stepTask():
 
     if USE_CACHE:
         if requestIdentifier in Request_Cache:
-            time.sleep(1)
             return jsonify(Request_Cache[requestIdentifier])
 
     filled_stepTask = fill_stepTask(
@@ -264,16 +212,19 @@ def Handle_generate_basePlan():
 
     if USE_CACHE:
         if requestIdentifier in Request_Cache:
-            time.sleep(2)
             return jsonify(Request_Cache[requestIdentifier])
 
+    try:
         basePlan = generate_basePlan(
             General_Goal=incoming_data["General Goal"],
             Agent_Board=AgentBoard,
             AgentProfile_Dict=AgentProfile_Dict,
             InitialObject_List=incoming_data["Initial Input Object"],
-        context="\n请注意，目标是给出解决方案，而不是工程实现，不需要实验验证，也不需要推广计划。"
         )
+    except ValueError as e:
+        return jsonify({"error": str(e)}), 400
+    except Exception as e:
+        return jsonify({"error": f"An unexpected error occurred: {str(e)}"}), 500
     basePlan_withRenderSpec = Add_Collaboration_Brief_FrontEnd(basePlan)
     Request_Cache[requestIdentifier] = basePlan_withRenderSpec
     response = jsonify(basePlan_withRenderSpec)
@@ -283,10 +234,6 @@ def Handle_generate_basePlan():
 @app.route("/executePlan", methods=["post"])
 def Handle_executePlan():
     incoming_data = request.get_json()
-    cur_context = ""
-    if "材料腐蚀" in incoming_data["plan"]["General Goal"]:
-        cur_context = context["材料腐蚀"]
-
     requestIdentifier = str(
         (
             "/executePlan",
@@ -298,7 +245,6 @@ def Handle_executePlan():
 
     if USE_CACHE:
         if requestIdentifier in Request_Cache:
-            time.sleep(3)
             return jsonify(Request_Cache[requestIdentifier])
 
     RehearsalLog = executePlan(
@@ -306,43 +252,125 @@ def Handle_executePlan():
         incoming_data["num_StepToRun"],
         incoming_data["RehearsalLog"],
         AgentProfile_Dict,
-        context=cur_context
     )
     Request_Cache[requestIdentifier] = RehearsalLog
     response = jsonify(RehearsalLog)
     return response
 
 
-@app.route("/_saveRequestCashe", methods=["GET"])
+@app.route("/executePlanOptimized", methods=["post"])
+def Handle_executePlanOptimized():
+    """
+    优化版流式执行计划（阶段1+2：步骤级流式 + 动作级智能并行）
+
+    返回 SSE 流，每完成一个动作就返回结果
+    - 无依赖关系的动作并行执行
+    - 有依赖关系的动作串行执行
+
+    前端使用 EventSource 接收
+    """
+    incoming_data = request.get_json()
+
+    def generate():
+        try:
+            for chunk in executePlan_streaming(
+                plan=incoming_data["plan"],
+                num_StepToRun=incoming_data.get("num_StepToRun"),
+                RehearsalLog=incoming_data.get("RehearsalLog", []),
+                AgentProfile_Dict=AgentProfile_Dict,
+            ):
+                yield chunk
+        except Exception as e:
+            error_event = json.dumps({
+                "type": "error",
+                "message": str(e)
+            }, ensure_ascii=False)
+            yield f"data: {error_event}\n\n"
+
+    return Response(
+        stream_with_context(generate()),
+        mimetype="text/event-stream",
+        headers={
+            "Cache-Control": "no-cache",
+            "X-Accel-Buffering": "no",
+        }
+    )
+
+
+@app.route("/_saveRequestCashe", methods=["post"])
 def Handle_saveRequestCashe():
     with open(
         os.path.join(os.getcwd(), "RequestCache", "Request_Cache.json"), "w"
     ) as json_file:
         json.dump(Request_Cache, json_file, indent=4)
     response = jsonify(
-            {"code": 200, "content": "request cashe sucessfully saved: " + os.path.join(os.getcwd(), "RequestCache", "Request_Cache.json")}
+        {"code": 200, "content": "request cashe sucessfully saved"}
     )
     return response
 
 
 @app.route("/setAgents", methods=["POST"])
 def set_agents():
-    global AgentBoard, AgentProfile_Dict
+    global AgentBoard, AgentProfile_Dict,yaml_data
     AgentBoard = request.json
     AgentProfile_Dict = {}
     for item in AgentBoard:
         name = item["Name"]
-        profile = item["Profile"]
+        if all(item.get(field) for field in ["apiUrl","apiKey","apiModel"]):
-        AgentProfile_Dict[name] = profile
+            agent_config = {
+                "profile": item["Profile"],
+                "apiUrl": item["apiUrl"],
+                "apiKey": item["apiKey"],
+                "apiModel": item["apiModel"],
+                "useCustomAPI":True
+            }
+        else:
+            agent_config = {
+                "profile": item["Profile"],
+                "apiUrl": yaml_data.get("OPENAI_API_BASE"),
+                "apiKey": yaml_data.get("OPENAI_API_KEY"),
+                "apiModel": yaml_data.get("OPENAI_API_MODEL"),
+                "useCustomAPI":False
+            }
+        AgentProfile_Dict[name] = agent_config
+
     return jsonify({"code": 200, "content": "set agentboard successfully"})
 
 
 def init():
     global AgentBoard, AgentProfile_Dict, Request_Cache
+
+    # Load Request Cache
+    try:
         with open(
             os.path.join(os.getcwd(), "RequestCache", "Request_Cache.json"), "r"
         ) as json_file:
             Request_Cache = json.load(json_file)
+        print(f"✅ Loaded Request_Cache with {len(Request_Cache)} entries")
+    except Exception as e:
+        print(f"⚠️  Failed to load Request_Cache: {e}")
+        Request_Cache = {}
+
+    # Load Agent Board
+    try:
+        with open(
+            os.path.join(os.getcwd(), "AgentRepo", "agentBoard_v1.json"), "r", encoding="utf-8"
+        ) as json_file:
+            AgentBoard = json.load(json_file)
+        print(f"✅ Loaded AgentBoard with {len(AgentBoard)} agents")
+
+        # Build AgentProfile_Dict
+        AgentProfile_Dict = {}
+        for item in AgentBoard:
+            name = item["Name"]
+            profile = item["Profile"]
+            AgentProfile_Dict[name] = profile
+        print(f"✅ Built AgentProfile_Dict with {len(AgentProfile_Dict)} profiles")
+
+    except Exception as e:
+        print(f"⚠️  Failed to load AgentBoard: {e}")
+        AgentBoard = []
+        AgentProfile_Dict = {}
 
 
 if __name__ == "__main__":
@@ -352,8 +380,8 @@ if __name__ == "__main__":
     parser.add_argument(
         "--port",
         type=int,
-        default=8017,
+        default=8000,
-        help="set the port number, 8017 by defaul.",
+        help="set the port number, 8000 by defaul.",
     )
     args = parser.parse_args()
     init()

docker-compose.yml

@@ -21,12 +21,11 @@ services:
     ports:
       - "8000:8000"
     environment:
-      - OPENAI_API_BASE=https://api.moleapi.com/v1
+      - OPENAI_API_BASE=htts://api.openai.com
-      - OPENAI_API_KEY=sk-sps7FBCbEvu85DfPoS8SdnPwYLEoW7u5Dd8vCDTXqPLpHuyb
+      - OPENAI_API_KEY=
-      - OPENAI_API_MODEL=gpt-4.1-mini
+      - OPENAI_API_MODEL=gpt-4-turbo-preview
-      - FAST_DESIGN_MODE=False
+      - FAST_DESIGN_MODE=True
       - GROQ_API_KEY=
-      - USE_CACHE=True
     networks:
       - agentcoord-network
 

frontend-react/Dockerfile

@@ -15,9 +15,8 @@ FROM base AS runner
 WORKDIR /app
 EXPOSE 8080/tcp
 COPY .npmrc ./
-COPY src ./src
+RUN npm install @modern-js/app-tools @modern-js/runtime --no-optional --no-shrinkwrap && mkdir src
 COPY modern.config.ts package.json ./
 COPY --from=builder /app/dist ./dist
-COPY --from=builder /app/node_modules ./node_modules
 ENV API_BASE=
 CMD ["npm", "run", "serve"]

frontend-react/src/components/AgentAssignment/index.tsx

@@ -351,7 +351,7 @@ export default observer(({ style = {} }: IPlanModification) => {
             overflowY: 'auto',
           }}
         >
-          <Box sx={{ marginBottom: '6px', fontWeight: '600' }}>已选智能体</Box>
+          <Box sx={{ marginBottom: '6px', fontWeight: '600' }}>Assignment</Box>
           <Box>
             {Object.keys(agentSelections).map(selectionId => (
               <Box
@@ -405,7 +405,7 @@ export default observer(({ style = {} }: IPlanModification) => {
             overflowY: 'auto',
           }}
         >
-          <Box sx={{ marginBottom: '4px', fontWeight: '600' }}>候选智能体</Box>
+          <Box sx={{ marginBottom: '4px', fontWeight: '600' }}>Comparison</Box>
 
           <Box
             sx={{

frontend-react/src/components/AgentBoard/AgentCard.tsx

@@ -65,6 +65,7 @@ export default observer(({ agent, style = {} }: IAgentCardProps) => (
               userSelect: 'none',
             }}
           >
+            {agent.profile}
           </Box>
         </Box>
         <Box
@@ -104,7 +105,7 @@ export default observer(({ agent, style = {} }: IAgentCardProps) => (
               marginLeft: '2px',
             }}
           >
-            当前职责:
+            Current Duty:
           </Box>
           <Box>
             {agent.actions.map((action, index) => (

frontend-react/src/components/AgentBoard/DutyItem.tsx

@@ -4,7 +4,6 @@ import Box from '@mui/material/Box';
 import MoreHorizIcon from '@mui/icons-material/MoreHoriz';
 import UnfoldLessIcon from '@mui/icons-material/UnfoldLess';
 import { IAgentAction, globalStorage } from '@/storage';
-import { getActionTypeDisplayText } from '@/storage/plan/action'; // 导入映射函数
 
 export interface IDutyItem {
   action: IAgentAction;
@@ -39,7 +38,7 @@ export default React.memo<IDutyItem>(({ action, style = {} }) => {
           ..._style,
         }}
       >
-        {getActionTypeDisplayText(action.type)}
+        {action.type}
         <Box
           onClick={() => setExpand(true)}
           sx={{
@@ -84,7 +83,7 @@ export default React.memo<IDutyItem>(({ action, style = {} }) => {
           marginLeft: '2px',
         }}
       >
-        {getActionTypeDisplayText(action.type)}
+        {action.type}
       </Box>
       <Divider
         sx={{

frontend-react/src/components/AgentBoard/index.tsx

@@ -88,7 +88,7 @@ export default observer(({ style = {} }: IAgentBoardProps) => {
           '& > input': { display: 'none' },
         }}
       >
-        <Title title="智能体库" />
+        <Title title="Agent Board" />
         <Box
           sx={{
             flexGrow: 1,

frontend-react/src/components/AgentIcon/agents.ts

@@ -1,5 +1,4 @@
 import AbigailChen from '@/static/AgentIcons/Abigail_Chen.png';
-import AbigailChenMilitary from '@/static/AgentIcons/Abigail_Chen_military.png';
 import AdamSmith from '@/static/AgentIcons/Adam_Smith.png';
 import ArthurBurton from '@/static/AgentIcons/Arthur_Burton.png';
 import AyeshaKhan from '@/static/AgentIcons/Ayesha_Khan.png';
@@ -9,11 +8,9 @@ import EddyLin from '@/static/AgentIcons/Eddy_Lin.png';
 import FranciscoLopez from '@/static/AgentIcons/Francisco_Lopez.png';
 import GiorgioRossi from '@/static/AgentIcons/Giorgio_Rossi.png';
 import HaileyJohnson from '@/static/AgentIcons/Hailey_Johnson.png';
-import HaileyJohnsonMilitary from '@/static/AgentIcons/Hailey_Johnson_military.png';
 import IsabellaRodriguez from '@/static/AgentIcons/Isabella_Rodriguez.png';
 import JaneMoreno from '@/static/AgentIcons/Jane_Moreno.png';
 import JenniferMoore from '@/static/AgentIcons/Jennifer_Moore.png';
-import JenniferMooreMilitary from '@/static/AgentIcons/Jennifer_Moore_military.png';
 import JohnLin from '@/static/AgentIcons/John_Lin.png';
 import KlausMueller from '@/static/AgentIcons/Klaus_Mueller.png';
 import LatoyaWilliams from '@/static/AgentIcons/Latoya_Williams.png';
@@ -30,7 +27,6 @@ import Unknown from '@/static/AgentIcons/Unknow.png';
 
 export enum IconName {
   AbigailChen = 'Abigail_Chen',
-  AbigailChenMilitary = 'Abigail_Chen_military',
   AdamSmith = 'Adam_Smith',
   ArthurBurton = 'Arthur_Burton',
   AyeshaKhan = 'Ayesha_Khan',
@@ -49,11 +45,9 @@ export enum IconName {
   GabeSmith = 'Gabe_Smith',
   GiorgioRossi = 'Giorgio_Rossi',
   HaileyJohnson = 'Hailey_Johnson',
-  HaileyJohnsonMilitary = 'Hailey_Johnson_military',
   IsabellaRodriguez = 'Isabella_Rodriguez',
   JaneMoreno = 'Jane_Moreno',
   JenniferMoore = 'Jennifer_Moore',
-  JenniferMooreMilitary = 'Jennifer_Moore_military',
   JohnLin = 'John_Lin',
   KlausMueller = 'Klaus_Mueller',
   LatoyaWilliams = 'Latoya_Williams',
@@ -89,7 +83,6 @@ export const IconMap = new Proxy<{ [key: string]: IconName }>(
 export const IconUrl: { [key in IconName]: string } = {
   [IconName.Unknown]: Unknown,
   [IconName.AbigailChen]: AbigailChen,
-  [IconName.AbigailChenMilitary]: AbigailChenMilitary,
   [IconName.AdamSmith]: AdamSmith,
   [IconName.ArthurBurton]: ArthurBurton,
   [IconName.AyeshaKhan]: AyeshaKhan,
@@ -108,11 +101,9 @@ export const IconUrl: { [key in IconName]: string } = {
   [IconName.GabeSmith]: AbigailChen,
   [IconName.GiorgioRossi]: GiorgioRossi,
   [IconName.HaileyJohnson]: HaileyJohnson,
-  [IconName.HaileyJohnsonMilitary]: HaileyJohnsonMilitary,
   [IconName.IsabellaRodriguez]: IsabellaRodriguez,
   [IconName.JaneMoreno]: JaneMoreno,
   [IconName.JenniferMoore]: JenniferMoore,
-  [IconName.JenniferMooreMilitary]: JenniferMooreMilitary,
   [IconName.JohnLin]: JohnLin,
   [IconName.KlausMueller]: KlausMueller,
   [IconName.LatoyaWilliams]: LatoyaWilliams,

frontend-react/src/components/HeadBar/index.tsx

@@ -151,7 +151,7 @@ export default observer(({ style = {} }: { style?: SxProps }) => {
           >
             <LogoIcon />
             <Box sx={{ marginLeft: '6px', fontWeight: 800, fontSize: '20px' }}>
-              多智能体协同平台
+              AGENTCOORD
             </Box>
           </Box>
         ) : (

frontend-react/src/components/Outline/Cards.tsx

@@ -8,7 +8,6 @@ import RemoveIcon from '@mui/icons-material/Remove';
 import AdjustIcon from '@mui/icons-material/Adjust';
 import { ObjectProps, ProcessProps } from './interface';
 import AgentIcon from '@/components/AgentIcon';
-import DescriptionCard from '@/components/ProcessDiscription/DescriptionCard';
 import { globalStorage } from '@/storage';
 
 export interface IEditObjectProps {
@@ -330,13 +329,6 @@ export const ProcessCard: React.FC<IProcessCardProps> = React.memo(
                   // handleEditStep(step.name, { ...step, task: text });
                 }}
               />
-              {/* 这里直接渲染对应的 DescriptionCard */}
-              {/* {(() => {
-                const step = globalStorage.planManager.currentPlan.find(
-                  s => s.id === process.id
-                );
-                return step ? <DescriptionCard step={step} /> : null;
-              })()} */}
             </Box>
           )}
         </Box>

frontend-react/src/components/Outline/D3Graph.tsx

@@ -118,10 +118,10 @@ const D3Graph: React.FC<D3GraphProps> = ({
           stepName: stepCardName,
           objectName: objectCardName,
           type,
-          x1: stepRect.left + stepRect.width,
+          x1: objectRect.left + objectRect.width,
-          y1: stepRect.top + 0.5 * stepRect.height,
+          y1: objectRect.top + 0.5 * objectRect.height,
-          x2: objectRect.left,
+          x2: stepRect.left,
-          y2: objectRect.top + 0.5 * objectRect.height,
+          y2: stepRect.top + 0.5 * stepRect.height,
         };
       });
     const objectMetrics = calculateLineMetrics(cardRect, 'object');
@@ -154,14 +154,14 @@ const D3Graph: React.FC<D3GraphProps> = ({
     >
       <marker
         id="arrowhead"
-  markerWidth="2" 
+        markerWidth="4"
-  markerHeight="2" 
+        markerHeight="4"
-  refX="1"        
+        refX="2"
-  refY="1"
+        refY="2"
         orient="auto"
         markerUnits="strokeWidth"
       >
-  <path d="M0,0 L2,1 L0,2 z" fill="#E5E5E5" />
+        <path d="M0,0 L4,2 L0,4 z" fill="#E5E5E5" />
       </marker>
       <marker
         id="starter"
@@ -184,7 +184,7 @@ const D3Graph: React.FC<D3GraphProps> = ({
           fill="#898989"
           fontWeight="800"
         >
-          产出
+          Key Object
         </text>
         <line
           x1={objectLine.x}
@@ -204,7 +204,7 @@ const D3Graph: React.FC<D3GraphProps> = ({
           fill="#898989"
           fontWeight="800"
         >
-          流程
+          Process
         </text>
         <line
           x1={processLine.x}

frontend-react/src/components/Outline/OutlineView.tsx

@@ -53,7 +53,7 @@ export default observer(() => {
   const handleEditContent = (stepTaskId: string, newContent: string) => {
     globalStorage.setStepTaskContent(stepTaskId, newContent);
   };
-  const WidthRatio = ['35%', '10%', '50%'];
+  const WidthRatio = ['30%', '15%', '52.5%'];
 
   const [cardRefMapReady, setCardRefMapReady] = React.useState(false);
 
@@ -175,34 +175,6 @@ export default observer(() => {
                 sx={{ display: 'flex' }}
                 ref={ref}
               >
-                <Box
-                  sx={{
-                    // display: 'flex',
-                    alignItems: 'center',
-                    // width: WidthRatio[2],
-                    justifyContent: 'center',
-                    flex: `0 0 ${WidthRatio[2]}`,
-                  }}
-                >
-                  {name && (
-                    <ProcessCard
-                      process={{
-                        id,
-                        name,
-                        icons: agentIcons,
-                        agents,
-                        content,
-                        cardRef: getCardRef(`process.${name}`),
-                      }}
-                      handleProcessClick={handleProcessClick}
-                      isFocusing={focusingStepTaskId === id}
-                      isAddActive={id === activeProcessIdAdd}
-                      handleAddActive={handleProcessAdd}
-                      handleEditContent={handleEditContent}
-                    />
-                  )}
-                </Box>
-                <Box sx={{ flex: `0 0 ${WidthRatio[1]}` }} />
                 <Box
                   sx={{
                     display: 'flex',
@@ -237,6 +209,34 @@ export default observer(() => {
                     />
                   )}
                 </Box>
+                <Box sx={{ flex: `0 0 ${WidthRatio[1]}` }} />
+                <Box
+                  sx={{
+                    // display: 'flex',
+                    alignItems: 'center',
+                    // width: WidthRatio[2],
+                    justifyContent: 'center',
+                    flex: `0 0 ${WidthRatio[2]}`,
+                  }}
+                >
+                  {name && (
+                    <ProcessCard
+                      process={{
+                        id,
+                        name,
+                        icons: agentIcons,
+                        agents,
+                        content,
+                        cardRef: getCardRef(`process.${name}`),
+                      }}
+                      handleProcessClick={handleProcessClick}
+                      isFocusing={focusingStepTaskId === id}
+                      isAddActive={id === activeProcessIdAdd}
+                      handleAddActive={handleProcessAdd}
+                      handleEditContent={handleEditContent}
+                    />
+                  )}
+                </Box>
               </Box>
             ),
           )}

frontend-react/src/components/Outline/index.tsx

@@ -25,7 +25,7 @@ export default observer(({ style = {} }: { style?: SxProps }) => {
         ...style,
       }}
     >
-      <Title title="任务大纲" />
+      <Title title="Plan Outline" />
       <Box
         sx={{
           position: 'relative',

frontend-react/src/components/ProcessDiscription/index.tsx

@@ -19,7 +19,7 @@ export default observer(({ style = {} }: { style?: SxProps }) => {
         ...style,
       }}
     >
-      <Title title="任务流程" />
+      <Title title="Task Process" />
       <Stack
         spacing={1}
         sx={{

frontend-react/src/components/ProcessRehearsal/StepHistoryItem.tsx

@@ -1,6 +1,6 @@
-import React, { useState } from 'react';
+import React from 'react';
 import { observer } from 'mobx-react-lite';
-import { Divider, SxProps, Tooltip, Typography} from '@mui/material';
+import { Divider, SxProps } from '@mui/material';
 import Box from '@mui/material/Box';
 import UnfoldLessIcon from '@mui/icons-material/UnfoldLess';
 import MoreHorizIcon from '@mui/icons-material/MoreHoriz';
@@ -9,7 +9,6 @@ import { globalStorage } from '@/storage';
 import type { IExecuteStepHistoryItem } from '@/apis/execute-plan';
 import AgentIcon from '@/components/AgentIcon';
 import { getAgentActionStyle } from '@/storage/plan';
-import { getActionTypeDisplayText } from '@/storage/plan/action';
 
 export interface IStepHistoryItemProps {
   item: IExecuteStepHistoryItem;
@@ -47,170 +46,6 @@ export default observer(
         }, 10);
       }
     }, [expand]);
-    
-interface DataSpaceCard {
-  name: string;
-  data_space: string;
-  doId: string;
-  fromRepo: string;
-}
-
-interface DataSpaceIndicatorProps {
-  cards?: DataSpaceCard[];
-}
-
-const DataSpaceIndicator = ({ cards = [] }: DataSpaceIndicatorProps) => {
-  const [currentCard, setCurrentCard] = useState(0);
-
-  if (!cards || cards.length === 0) {
-    return null;
-  }
-
-  const tooltipContent = (
-    <>
-      {/* 添加标题 */}
-       <Box
-        sx={{
-          display: 'flex',
-          justifyContent: 'space-between',
-          alignItems: 'center',
-          padding: '8px 12px',
-          backgroundColor: '#1565c0',
-          color: 'white',
-          borderRadius: '4px 4px 0 0',
-          fontWeight: 'bold',
-          fontSize: '14px',
-        }}
-      >
-        <span>数联网搜索结果</span>
-        <Box sx={{ display: 'flex', alignItems: 'center', gap: '8px' }}>
-          <span style={{ fontSize: '12px', color: 'rgba(255,255,255,0.8)' }}>
-            {currentCard + 1}/{cards.length}
-          </span>
-          <button
-            onClick={(e) => {
-              e.stopPropagation();
-              setCurrentCard((prev) => (prev + 1) % cards.length);
-            }}
-            style={{
-              fontSize: '12px',
-              padding: '2px 8px',
-              backgroundColor: 'white',
-              color: '#1565c0',
-              border: 'none',
-              borderRadius: '3px',
-              cursor: 'pointer',
-              fontWeight: 'bold'
-            }}
-          >
-            下一个
-          </button>
-        </Box>
-      </Box>
-      <Box
-        sx={{
-          padding: '12px',
-          borderRadius: '4px',
-          backgroundColor: '#e3f2fd',
-          border: '1px solid #1565c0',
-          minWidth: '450px', // 设置卡片最小宽度
-        }}
-      >
-        <Box sx={{ display: 'flex', alignItems: 'flex-start', marginBottom: '4px' }}>
-          <Typography variant="caption" sx={{ fontWeight: 'bold', color: '#666', minWidth: '60px' }}>
-            名称:
-          </Typography>
-          <Typography variant="body2" sx={{ color: 'black' }}>
-            {cards[currentCard]?.name}
-          </Typography>
-        </Box>
-
-        <Box sx={{ display: 'flex', alignItems: 'flex-start', marginBottom: '4px' }}>
-          <Typography variant="caption" sx={{ fontWeight: 'bold', color: '#666', minWidth: '60px' }}>
-            数据空间:
-          </Typography>
-          <Typography variant="body2" sx={{ color: 'black' }}>
-            {cards[currentCard]?.data_space}
-          </Typography>
-        </Box>
-
-        <Box sx={{ display: 'flex', alignItems: 'flex-start', marginBottom: '4px' }}>
-          <Typography variant="caption" sx={{ fontWeight: 'bold', color: '#666', minWidth: '60px' }}>
-            DOID:
-          </Typography>
-          <Typography variant="body2" sx={{ color: 'black' }}>
-            {cards[currentCard]?.doId}
-          </Typography>
-        </Box>
-        
-        <Box sx={{ display: 'flex', alignItems: 'flex-start', marginBottom: '4px' }}>
-          <Typography variant="caption" sx={{ fontWeight: 'bold', color: '#666', minWidth: '60px' }}>
-            来源仓库:
-          </Typography>
-          <Typography variant="body2" sx={{ color: 'black' }}>
-            {cards[currentCard]?.fromRepo}
-          </Typography>
-        </Box>
-      </Box>
-    </>
-  );
-
-  return (
-    <Tooltip 
-      title={tooltipContent} 
-      arrow
-      slotProps={{
-        tooltip: {
-          sx: {
-            maxWidth: 500, // 只需要这一行来增加宽度
-          },
-        },
-      }}
-    >
-      <Box
-        sx={{
-          display: 'inline-flex',
-          alignItems: 'center',
-          justifyContent: 'center',
-          width: '20px',
-          height: '20px',
-          borderRadius: '50%',
-          backgroundColor: '#9e9e9e',
-          color: 'white',
-          fontSize: '12px',
-          fontWeight: '600',
-          cursor: 'pointer',
-          '&:hover': {
-            backgroundColor: '#1565c0',
-          }
-        }}
-      >
-        {cards.length}
-      </Box>
-    </Tooltip>
-  );
-};
-
-const cardData = [
-  {
-    name: "3D Semantic-Geometric Corrosion Mapping Implementations",
-    data_space: "江苏省产研院",
-    doId: "bdware.scenario/d8f3ff8c-3fb3-4573-88a6-5dd823627c37",
-    fromRepo: "https://arxiv.org/abs/2404.13691"
-  },
-  {
-    name: "RustSEG -- Automated segmentation of corrosion using deep learning",
-    data_space: "江苏省产研院",
-    doId: "bdware.scenario/67445299-110a-4a4e-9fda-42e4b5a493c2",
-    fromRepo: "https://arxiv.org/abs/2205.05426"
-  },
-  {
-    name: "Pixel-level Corrosion Detection on Metal Constructions by Fusion of Deep Learning Semantic and Contour Segmentation",
-    data_space: "江苏省产研院",
-    doId: "bdware.scenario/115d5135-85d3-4123-8b81-9eb9f07b6153",
-    fromRepo: "https://arxiv.org/abs/2008.05204"
-  },
-];
     const s = { ...getAgentActionStyle(item.type), ...style } as SxProps;
     React.useEffect(() => {
       console.log(item);
@@ -242,7 +77,7 @@ const cardData = [
             {item.agent}
           </Box>
           <Box component="span" sx={{ fontWeight: 400 }}>
-            : {getActionTypeDisplayText(item.type)}
+            : {item.type}
           </Box>
         </Box>
         {item.result ? (
@@ -268,14 +103,10 @@ const cardData = [
                     marginBottom: '4px',
                     color: '#0009',
                     fontWeight: 400,
-                    display: 'inline-flex',
-                    alignItems: 'center',
-                    gap: '8px',
                   }}
                 >
                   {item.description}
                 </Box>
-                <DataSpaceIndicator cards={cardData} />
                 <MarkdownBlock
                   text={item.result}
                   style={{

frontend-react/src/components/ProcessRehearsal/index.tsx

@@ -79,7 +79,7 @@ export default observer(({ style = {} }: { style?: SxProps }) => {
           alignItems: 'center',
         }}
       >
-        <Title title="执行结果" />
+        <Title title="Execution Result" />
         <Box
           sx={{
             flexGrow: 1,

frontend-react/src/components/UserGoalInput/index.tsx

@@ -4,8 +4,6 @@ import { SxProps } from '@mui/material';
 import Box from '@mui/material/Box';
 import IconButton from '@mui/material/IconButton';
 import FormControl from '@mui/material/FormControl';
-import Autocomplete from '@mui/material/Autocomplete';
-import TextField from '@mui/material/TextField';
 import FilledInput from '@mui/material/FilledInput';
 import TelegramIcon from '@mui/icons-material/Telegram';
 import CircularProgress from '@mui/material/CircularProgress';
@@ -18,18 +16,6 @@ export interface UserGoalInputProps {
 export default observer(({ style = {} }: UserGoalInputProps) => {
   const inputRef = React.useRef<string>('');
   const inputElementRef = React.useRef<HTMLInputElement>(null);
-  const goalOptions = [
-'如何快速筛选慢性肾脏病药物潜在受试者？',
-'如何补充“丹芍活血胶囊”不良反应数据？',
-'如何快速研发用于战场失血性休克的药物？',
-'二维材料的光电性质受哪些关键因素影响？',
-'如何通过AI模拟的方法分析材料的微观结构?',
-'如何分析获取液态金属热力学参数?',
-'如何解决固态电池的成本和寿命难题？',
-'如何解决船舶制造中的材料腐蚀难题？',
-'如何解决船舶制造中流体模拟和建模优化难题？',
-  ];
-
   React.useEffect(() => {
     if (inputElementRef.current) {
       if (globalStorage.planManager) {
@@ -46,53 +32,29 @@ export default observer(({ style = {} }: UserGoalInputProps) => {
         ...style,
       }}
     >
-      <Autocomplete
+      <FilledInput
-	freeSolo
-	disableClearable	
         disabled={
           globalStorage.api.busy ||
           !globalStorage.api.agentsReady ||
           globalStorage.api.planReady
         }
-	options={goalOptions}
+        placeholder="Yout Goal"
-        value={inputRef.current || (globalStorage.planManager ? globalStorage.planManager.goal : globalStorage.briefGoal)}
-        onChange={(event, newValue) => {
-          if (newValue) {
-            inputRef.current = newValue;
-          }
-        }}
-        onInputChange={(event, newInputValue) => {
-          inputRef.current = newInputValue;
-        }}
-	renderInput={(params) => (
-          <TextField
-            {...params}
-            variant="filled"
-            placeholder="请输入你的任务"
         fullWidth
-            size="small"
         inputRef={inputElementRef}
+        onChange={event => (inputRef.current = event.target.value)}
+        size="small"
         sx={{
           borderRadius: '10px',
           background: '#E1E1E1',
           borderBottom: 'none !important',
-              '& .MuiFilledInput-root': {
-		height: '45px',
-                borderRadius: '10px',
-                background: '#E1E1E1',
-		paddingTop: '5px',
-                borderBottom: 'none !important',
           '&::before': {
             borderBottom: 'none !important',
           },
-                '&::after': {
+          '& > input': {
-                  borderBottom: 'none !important',
+            padding: '10px',
-                },
           },
         }}
-            InputProps={{
+        startAdornment={
-              ...params.InputProps,
-              startAdornment: (
           <Box
             sx={{
               color: '#4A9C9E',
@@ -102,14 +64,10 @@ export default observer(({ style = {} }: UserGoalInputProps) => {
               userSelect: 'none',
             }}
           >
-                  任务
+            \General Goal:
           </Box>
-              ),
+        }
-            }}
       />
-        )}
-      />	
-
       {globalStorage.api.planGenerating ? (
         <CircularProgress
           sx={{

frontend-react/src/components/ViewConnector/index.tsx

@@ -88,24 +88,24 @@ export default observer(() => {
         setConnectors(<></>);
       }
       const outlinePosition =
-        ElementToLink[1]?.current?.getBoundingClientRect?.();
+        ElementToLink[0]?.current?.getBoundingClientRect?.();
       if (!outlinePosition) {
         return;
       }
-      const agentRects = ElementToLink[0]
+      const agentRects = ElementToLink[1]
         .map(ele => ele.current?.getBoundingClientRect?.() as DOMRect)
         .filter(rect => rect);
       if (agentRects.length === 0) {
         return;
       }
       const agentsPosition = mergeRects(...agentRects);
-      // const descriptionPosition =
+      const descriptionPosition =
-      //   ElementToLink[2]?.current?.getBoundingClientRect?.();
+        ElementToLink[2]?.current?.getBoundingClientRect?.();
-      // if (!descriptionPosition) {
+      if (!descriptionPosition) {
-      //   return;
+        return;
-      // }
+      }
 
-      const LogRects = ElementToLink[2]
+      const LogRects = ElementToLink[3]
         .map(ele => ele?.current?.getBoundingClientRect?.() as DOMRect)
         .filter(rect => rect);
       if (LogRects.length > 0) {
@@ -115,14 +115,15 @@ export default observer(() => {
 
         setConnectors(
           drawConnectors(
-            agentsPosition,
             outlinePosition,
+            agentsPosition,
+            descriptionPosition,
             logPosition,
           ),
         );
       } else {
         setConnectors(
-          drawConnectors(agentsPosition,outlinePosition),
+          drawConnectors(outlinePosition, agentsPosition, descriptionPosition),
         );
       }
     } catch (e) {

frontend-react/src/routes/layout.tsx

@@ -44,7 +44,7 @@ export default observer(() => {
       )}
       {globalStorage.agentAssigmentWindow ? (
         <FloatWindow
-          title="智能体选择"
+          title="Assignment Exploration"
           onClose={() => (globalStorage.agentAssigmentWindow = false)}
         >
           <AgentAssignment

frontend-react/src/routes/page.tsx

@@ -99,7 +99,16 @@ export default React.memo(() => {
             }}
           />
           <Box sx={{ height: 0, flexGrow: 1, display: 'flex' }}>
-            <ResizeableColumn columnWidth="19%">
+            <ResizeableColumn columnWidth="25%">
+              <Outline
+                style={{
+                  height: '100%',
+                  width: '100%',
+                  marginRight: '6px',
+                }}
+              />
+            </ResizeableColumn>
+            <ResizeableColumn columnWidth="25%">
               <AgentBoard
                 style={{
                   height: '100%',
@@ -109,16 +118,7 @@ export default React.memo(() => {
                 onAddAgent={() => setShowAgentHiring(true)}
               />
             </ResizeableColumn>
-            <ResizeableColumn columnWidth="26%">
+            <ResizeableColumn columnWidth="25%">
-              <Outline
-                style={{
-                  height: '100%',
-                  width: '100%',
-                  marginRight: '6px',
-                }}
-              />
-            </ResizeableColumn>
-            {/* <ResizeableColumn columnWidth="25%">
               <ProcessDiscrption
                 style={{
                   height: '100%',
@@ -126,7 +126,7 @@ export default React.memo(() => {
                   marginRight: '6px',
                 }}
               />
-            </ResizeableColumn> */}
+            </ResizeableColumn>
             <ProcessRehearsal
               style={{
                 height: '100%',

frontend-react/src/storage/index.ts

@@ -285,15 +285,17 @@ export class GlobalStorage {
   }
 
   public get ElementToLink(): [
+    React.RefObject<HTMLElement> | undefined,
     React.RefObject<HTMLElement>[],
     React.RefObject<HTMLElement> | undefined,
     (React.RefObject<HTMLElement> | undefined)[],
   ] {
     return [
+      this.refMap.OutlineCard.get(this.focusingStepTaskId ?? ''),
       this.focusingStepTask?.agentSelection?.agents?.map(
         agent => this.refMap.AgentCard.get(agent) ?? [],
       ) ?? ([] as any),
-      this.refMap.OutlineCard.get(this.focusingStepTaskId ?? ''),
+      this.refMap.DiscriptionCard.get(this.focusingStepTaskId ?? ''),
       this.logManager.outdate
         ? []
         : [

frontend-react/src/storage/plan/action.ts

@@ -11,17 +11,6 @@ export enum ActionType {
   Finalize = 'Finalize',
 }
 
-export const getActionTypeDisplayText = (actionType: ActionType | string): string => {
-  const displayMap: Record<string, string> = {
-    [ActionType.Propose]: '提议',
-    [ActionType.Critique]: '评审',
-    [ActionType.Improve]: '改进',
-    [ActionType.Finalize]: '总结',
-  };
-  
-  return displayMap[actionType] || actionType;
-};
-
 const AgentActionStyles = new Map<ActionType | '', SxProps>([
   [ActionType.Propose, { backgroundColor: '#B9EBF9', borderColor: '#94c2dc' }],
   [ActionType.Critique, { backgroundColor: '#EFF9B9', borderColor: '#c0dc94' }],

frontend-react/src/storage/plan/stepTask.ts

@@ -20,7 +20,7 @@ const nameJoin = (names: string[]) => {
   const last = tmp.pop()!;
   let t = tmp.join(', ');
   if (t.length > 0) {
-    t = `${t} 和 ${last}`;
+    t = `${t} and ${last}`;
   } else {
     t = last;
   }
@@ -102,14 +102,14 @@ export class StepTaskNode implements INodeBase {
         text: this.output,
         style: { background: '#FFCA8C' },
       };
-      outputSentence = `得到 !<${indexOffset}>!`;
+      outputSentence = `to obtain !<${indexOffset}>!`;
     }
     // Join them togeter
     let content = inputSentence;
     if (content) {
-      content = `基于${content}, ${nameSentence} 执行任务 !<${actionIndex}>!`;
+      content = `Based on ${content}, ${nameSentence} perform the task of !<${actionIndex}>!`;
     } else {
-      content = `${nameSentence} 执行任务 !<${actionIndex}>!`;
+      content = `${nameSentence} perform the task of !<${actionIndex}>!`;
     }
     if (outputSentence) {
       content = `${content}, ${outputSentence}.`;

frontend/.dockerignore

@@ -0,0 +1,6 @@
+node_modules
+dist
+.idea
+.vscode
+.git
+.gitignore

frontend/.editorconfig

@@ -0,0 +1,8 @@
+[*.{js,jsx,mjs,cjs,ts,tsx,mts,cts,vue,css,scss,sass,less,styl}]
+charset = utf-8
+indent_size = 2
+indent_style = space
+insert_final_newline = true
+trim_trailing_whitespace = true
+end_of_line = lf
+max_line_length = 100

frontend/.env

@@ -0,0 +1 @@
+API_BASE=http://127.0.0.1:8000

frontend/.eslintrc-auto-import.json

@@ -0,0 +1,79 @@
+{
+  "globals": {
+    "Component": true,
+    "ComponentPublicInstance": true,
+    "ComputedRef": true,
+    "DirectiveBinding": true,
+    "EffectScope": true,
+    "ExtractDefaultPropTypes": true,
+    "ExtractPropTypes": true,
+    "ExtractPublicPropTypes": true,
+    "InjectionKey": true,
+    "MaybeRef": true,
+    "MaybeRefOrGetter": true,
+    "PropType": true,
+    "Ref": true,
+    "ShallowRef": true,
+    "Slot": true,
+    "Slots": true,
+    "VNode": true,
+    "WritableComputedRef": true,
+    "computed": true,
+    "createApp": true,
+    "customRef": true,
+    "defineAsyncComponent": true,
+    "defineComponent": true,
+    "effectScope": true,
+    "getCurrentInstance": true,
+    "getCurrentScope": true,
+    "getCurrentWatcher": true,
+    "h": true,
+    "inject": true,
+    "isProxy": true,
+    "isReactive": true,
+    "isReadonly": true,
+    "isRef": true,
+    "isShallow": true,
+    "markRaw": true,
+    "nextTick": true,
+    "onActivated": true,
+    "onBeforeMount": true,
+    "onBeforeUnmount": true,
+    "onBeforeUpdate": true,
+    "onDeactivated": true,
+    "onErrorCaptured": true,
+    "onMounted": true,
+    "onRenderTracked": true,
+    "onRenderTriggered": true,
+    "onScopeDispose": true,
+    "onServerPrefetch": true,
+    "onUnmounted": true,
+    "onUpdated": true,
+    "onWatcherCleanup": true,
+    "provide": true,
+    "reactive": true,
+    "readonly": true,
+    "ref": true,
+    "resolveComponent": true,
+    "shallowReactive": true,
+    "shallowReadonly": true,
+    "shallowRef": true,
+    "toRaw": true,
+    "toRef": true,
+    "toRefs": true,
+    "toValue": true,
+    "triggerRef": true,
+    "unref": true,
+    "useAttrs": true,
+    "useCssModule": true,
+    "useCssVars": true,
+    "useId": true,
+    "useModel": true,
+    "useSlots": true,
+    "useTemplateRef": true,
+    "watch": true,
+    "watchEffect": true,
+    "watchPostEffect": true,
+    "watchSyncEffect": true
+  }
+}

frontend/.gitattributes

@@ -0,0 +1 @@
+* text=auto eol=lf

frontend/.gitignore

@@ -0,0 +1,36 @@
+# Logs
+logs
+*.log
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+pnpm-debug.log*
+lerna-debug.log*
+
+node_modules
+.DS_Store
+dist
+dist-ssr
+coverage
+*.local
+
+# Editor directories and files
+.vscode/*
+!.vscode/extensions.json
+.idea
+*.suo
+*.ntvs*
+*.njsproj
+*.sln
+*.sw?
+
+*.tsbuildinfo
+
+.eslintcache
+
+# Cypress
+/cypress/videos/
+/cypress/screenshots/
+
+# Vitest
+__screenshots__/

frontend/.prettierrc.json

@@ -0,0 +1,6 @@
+{
+  "$schema": "https://json.schemastore.org/prettierrc",
+  "semi": false,
+  "singleQuote": true,
+  "printWidth": 100
+}

frontend/.vscode/extensions.json

@@ -0,0 +1,9 @@
+{
+  "recommendations": [
+    "Vue.volar",
+    "vitest.explorer",
+    "dbaeumer.vscode-eslint",
+    "EditorConfig.EditorConfig",
+    "esbenp.prettier-vscode"
+  ]
+}

frontend/CLAUDE.md

@@ -0,0 +1,95 @@
+# CLAUDE.md
+
+This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
+
+## Development Commands
+
+```bash
+# Install dependencies
+pnpm install
+
+# Development server with hot reload
+pnpm dev
+
+# Build for production
+pnpm build
+
+# Type checking
+pnpm type-check
+
+# Lint and fix code
+pnpm lint
+
+# Format code
+pnpm format
+
+# Run unit tests
+pnpm test:unit
+```
+
+## Project Architecture
+
+This is a **Multi-Agent Coordination Platform** (多智能体协同平台) built with Vue 3, TypeScript, and Vite. The application enables users to create and manage AI agents with specialized roles and coordinate them to complete complex tasks through visual workflows.
+
+### Tech Stack
+- **Vue 3** with Composition API and TypeScript
+- **Vite** for build tooling and development
+- **Element Plus** for UI components
+- **Pinia** for state management
+- **Tailwind CSS** for styling
+- **Vue Router** for routing (minimal usage)
+- **JSPlumb** for visual workflow connections
+- **Axios** for API requests with custom interceptors
+
+### Key Architecture Components
+
+#### State Management (`src/stores/modules/agents.ts`)
+Central store managing:
+- Agent definitions with profiles and icons
+- Task workflow data structures (`IRawStepTask`, `TaskProcess`)
+- Search functionality and current task state
+- Raw plan responses with UUID generation for tasks
+
+#### Request Layer (`src/utils/request.ts`)
+Custom Axios wrapper with:
+- Proxy configuration for `/api` -> `http://localhost:8000`
+- Response interceptors for error handling
+- `useRequest` hook for reactive data fetching
+- Integrated Element Plus notifications
+
+#### Component Structure
+- **Layout System** (`src/layout/`): Main application layout with Header and Main sections
+- **Task Templates** (`src/layout/components/Main/TaskTemplate/`): Different task types including AgentRepo, TaskSyllabus, and TaskResult
+- **Visual Workflow**: JSPlumb integration for drag-and-drop agent coordination flows
+
+#### Icon System
+- SVG icons stored in `src/assets/icons/`
+- Custom `SvgIcon` component with vite-plugin-svg-icons
+- Icon categories include specialist roles (doctor, engineer, researcher, etc.)
+
+### Build Configuration
+
+#### Vite (`vite.config.ts`)
+- Element Plus auto-import and component resolution
+- SVG icon caching with custom symbol IDs
+- Proxy setup for API requests to backend
+- Path aliases: `@/` maps to `src/`
+
+#### Docker Deployment
+- Multi-stage build: Node.js build + Caddy web server
+- API proxy configured via Caddyfile
+- Environment variable support for different deployment modes
+
+### Data Models
+Key interfaces for the agent coordination system:
+- `Agent`: Name, Profile, Icon
+- `IRawStepTask`: Individual task steps with agent selection and inputs
+- `TaskProcess`: Action descriptions with important inputs
+- `IRichText`: Template-based content formatting with style support
+
+### Development Notes
+- Uses pnpm as package manager (required by package.json)
+- Node version constraint: ^20.19.0 or >=22.12.0
+- Dark theme enabled by default in App.vue
+- Auto-imports configured for Vue APIs
+- No traditional Vue routes - uses component-based navigation

frontend/Dockerfile

@@ -0,0 +1,27 @@
+ARG CADDY_VERSION=2.6
+ARG BUILD_ENV=prod
+
+FROM node:20.19.0 as base
+WORKDIR /app
+COPY . .
+RUN npm install -g pnpm
+RUN pnpm install
+RUN pnpm build
+
+
+# The base for mode ENVIRONMENT=prod
+FROM caddy:${CADDY_VERSION}-alpine as prod
+
+# Workaround for https://github.com/alpinelinux/docker-alpine/issues/98#issuecomment-679278499
+RUN sed -i 's/https/http/' /etc/apk/repositories \
+ && apk add --no-cache bash
+
+COPY docker/Caddyfile /etc/caddy/
+COPY --from=base /app/dist /frontend
+
+# Run stage
+FROM ${BUILD_ENV}
+
+EXPOSE 80 443
+VOLUME ["/data", "/etc/caddy"]
+CMD ["caddy", "run", "--config", "/etc/caddy/Caddyfile", "--adapter", "caddyfile"]

frontend/README.md

@@ -0,0 +1,106 @@
+# 多智能体协同平台 (Agent Coordination Platform)
+
+一个强大的可视化平台，用于创建和管理具有专门角色的AI智能体，通过直观的工作流程协调它们来完成复杂任务。
+
+## ✨ 功能特性
+
+- **多智能体系统**：创建具有专门角色和专业知识的AI智能体
+- **可视化工作流编辑器**：使用JSPlumb设计智能体协调流程的拖放界面
+- **任务管理**：定义、执行和跟踪复杂的多步骤任务
+- **实时通信**：无缝的智能体交互和协调
+- **丰富的模板系统**：支持样式的灵活内容格式化
+- **TypeScript支持**：整个应用程序的完整类型安全
+
+## 🚀 快速开始
+
+### 开发命令
+
+```bash
+# 安装依赖
+pnpm install
+
+# 开发服务器（热重载）
+pnpm dev
+
+# 生产构建
+pnpm build
+
+# 类型检查
+pnpm type-check
+
+# 代码检查和修复
+pnpm lint
+
+# 代码格式化
+pnpm format
+
+# 运行单元测试
+pnpm test:unit
+```
+
+### 系统要求
+
+- Node.js ^20.19.0 或 >=22.12.0
+- pnpm（必需的包管理器）
+
+## 🏗️ 架构设计
+
+### 技术栈
+
+- **Vue 3**：Composition API 和 TypeScript
+- **Vite**：构建工具和开发环境
+- **Element Plus**：UI组件库
+- **Pinia**：状态管理
+- **Tailwind CSS**：样式框架
+- **JSPlumb**：可视化工作流连接
+- **Axios**：API请求与自定义拦截器
+
+### 核心组件
+
+#### 状态管理
+中央存储管理智能体定义、任务工作流和协调状态
+
+#### 请求层
+自定义Axios包装器，具有代理配置和集成通知
+
+#### 可视化工作流
+JSPlumb集成，用于拖放智能体协调流程
+
+#### 图标系统
+基于SVG的图标，用于不同的智能体专业化和角色
+
+## 📁 项目结构
+
+```
+src/
+├── assets/           # 静态资源，包括智能体图标
+├── components/       # 可复用的Vue组件
+├── layout/          # 应用布局和主要组件
+├── stores/          # Pinia状态管理
+├── utils/           # 工具函数和请求层
+├── views/           # 页面组件
+└── App.vue          # 根组件
+```
+
+## 🎯 开发指南
+
+### IDE设置
+
+[VS Code](https://code.visualstudio.com/) + [Vue (Official)](https://marketplace.visualstudio.com/items?itemName=Vue.volar)（禁用Vetur）。
+
+### 浏览器开发工具
+
+- 基于Chromium的浏览器：
+  - [Vue.js devtools](https://chromewebstore.google.com/detail/vuejs-devtools/nhdogjmejiglipccpnnnanhbledajbpd)
+  - 在DevTools中启用自定义对象格式化程序
+- Firefox：
+  - [Vue.js devtools](https://addons.mozilla.org/en-US/firefox/addon/vue-js-devtools/)
+  - 在DevTools中启用自定义对象格式化程序
+
+## 🚀 部署
+
+应用程序支持Docker部署，使用多阶段构建过程：Node.js用于构建，Caddy作为Web服务器。
+
+## 📄 许可证
+
+MIT许可证 - 详见LICENSE文件

frontend/auto-imports.d.ts

@@ -0,0 +1,75 @@
+/* eslint-disable */
+/* prettier-ignore */
+// @ts-nocheck
+// noinspection JSUnusedGlobalSymbols
+// Generated by unplugin-auto-import
+// biome-ignore lint: disable
+export {}
+declare global {
+  const EffectScope: typeof import('vue').EffectScope
+  const ElMessage: typeof import('element-plus/es').ElMessage
+  const ElNotification: typeof import('element-plus/es').ElNotification
+  const computed: typeof import('vue').computed
+  const createApp: typeof import('vue').createApp
+  const customRef: typeof import('vue').customRef
+  const defineAsyncComponent: typeof import('vue').defineAsyncComponent
+  const defineComponent: typeof import('vue').defineComponent
+  const effectScope: typeof import('vue').effectScope
+  const getCurrentInstance: typeof import('vue').getCurrentInstance
+  const getCurrentScope: typeof import('vue').getCurrentScope
+  const getCurrentWatcher: typeof import('vue').getCurrentWatcher
+  const h: typeof import('vue').h
+  const inject: typeof import('vue').inject
+  const isProxy: typeof import('vue').isProxy
+  const isReactive: typeof import('vue').isReactive
+  const isReadonly: typeof import('vue').isReadonly
+  const isRef: typeof import('vue').isRef
+  const isShallow: typeof import('vue').isShallow
+  const markRaw: typeof import('vue').markRaw
+  const nextTick: typeof import('vue').nextTick
+  const onActivated: typeof import('vue').onActivated
+  const onBeforeMount: typeof import('vue').onBeforeMount
+  const onBeforeUnmount: typeof import('vue').onBeforeUnmount
+  const onBeforeUpdate: typeof import('vue').onBeforeUpdate
+  const onDeactivated: typeof import('vue').onDeactivated
+  const onErrorCaptured: typeof import('vue').onErrorCaptured
+  const onMounted: typeof import('vue').onMounted
+  const onRenderTracked: typeof import('vue').onRenderTracked
+  const onRenderTriggered: typeof import('vue').onRenderTriggered
+  const onScopeDispose: typeof import('vue').onScopeDispose
+  const onServerPrefetch: typeof import('vue').onServerPrefetch
+  const onUnmounted: typeof import('vue').onUnmounted
+  const onUpdated: typeof import('vue').onUpdated
+  const onWatcherCleanup: typeof import('vue').onWatcherCleanup
+  const provide: typeof import('vue').provide
+  const reactive: typeof import('vue').reactive
+  const readonly: typeof import('vue').readonly
+  const ref: typeof import('vue').ref
+  const resolveComponent: typeof import('vue').resolveComponent
+  const shallowReactive: typeof import('vue').shallowReactive
+  const shallowReadonly: typeof import('vue').shallowReadonly
+  const shallowRef: typeof import('vue').shallowRef
+  const toRaw: typeof import('vue').toRaw
+  const toRef: typeof import('vue').toRef
+  const toRefs: typeof import('vue').toRefs
+  const toValue: typeof import('vue').toValue
+  const triggerRef: typeof import('vue').triggerRef
+  const unref: typeof import('vue').unref
+  const useAttrs: typeof import('vue').useAttrs
+  const useCssModule: typeof import('vue').useCssModule
+  const useCssVars: typeof import('vue').useCssVars
+  const useId: typeof import('vue').useId
+  const useModel: typeof import('vue').useModel
+  const useSlots: typeof import('vue').useSlots
+  const useTemplateRef: typeof import('vue').useTemplateRef
+  const watch: typeof import('vue').watch
+  const watchEffect: typeof import('vue').watchEffect
+  const watchPostEffect: typeof import('vue').watchPostEffect
+  const watchSyncEffect: typeof import('vue').watchSyncEffect
+}
+// for type re-export
+declare global {
+  // @ts-ignore
+  export type { Component, Slot, Slots, ComponentPublicInstance, ComputedRef, DirectiveBinding, ExtractDefaultPropTypes, ExtractPropTypes, ExtractPublicPropTypes, InjectionKey, PropType, Ref, ShallowRef, MaybeRef, MaybeRefOrGetter, VNode, WritableComputedRef } from 'vue'
+  import('vue')
+}

frontend/claude_code_env.sh

@@ -0,0 +1,205 @@
+#!/bin/bash
+
+set -euo pipefail
+
+# ========================
+#       常量定义
+# ========================
+SCRIPT_NAME=$(basename "$0")
+NODE_MIN_VERSION=18
+NODE_INSTALL_VERSION=22
+NVM_VERSION="v0.40.3"
+CLAUDE_PACKAGE="@anthropic-ai/claude-code"
+CONFIG_DIR="$HOME/.claude"
+CONFIG_FILE="$CONFIG_DIR/settings.json"
+API_BASE_URL="https://open.bigmodel.cn/api/anthropic"
+API_KEY_URL="https://open.bigmodel.cn/usercenter/proj-mgmt/apikeys"
+API_TIMEOUT_MS=3000000
+
+# ========================
+#       工具函数
+# ========================
+
+log_info() {
+    echo "🔹 $*"
+}
+
+log_success() {
+    echo "✅ $*"
+}
+
+log_error() {
+    echo "❌ $*" >&2
+}
+
+ensure_dir_exists() {
+    local dir="$1"
+    if [ ! -d "$dir" ]; then
+        mkdir -p "$dir" || {
+            log_error "Failed to create directory: $dir"
+            exit 1
+        }
+    fi
+}
+
+# ========================
+#     Node.js 安装函数
+# ========================
+
+install_nodejs() {
+    local platform=$(uname -s)
+
+    case "$platform" in
+        Linux|Darwin)
+            log_info "Installing Node.js on $platform..."
+
+            # 安装 nvm
+            log_info "Installing nvm ($NVM_VERSION)..."
+            curl -s https://raw.githubusercontent.com/nvm-sh/nvm/"$NVM_VERSION"/install.sh | bash
+
+            # 加载 nvm
+            log_info "Loading nvm environment..."
+            \. "$HOME/.nvm/nvm.sh"
+
+            # 安装 Node.js
+            log_info "Installing Node.js $NODE_INSTALL_VERSION..."
+            nvm install "$NODE_INSTALL_VERSION"
+
+            # 验证安装
+            node -v &>/dev/null || {
+                log_error "Node.js installation failed"
+                exit 1
+            }
+            log_success "Node.js installed: $(node -v)"
+            log_success "npm version: $(npm -v)"
+            ;;
+        *)
+            log_error "Unsupported platform: $platform"
+            exit 1
+            ;;
+    esac
+}
+
+# ========================
+#     Node.js 检查函数
+# ========================
+
+check_nodejs() {
+    if command -v node &>/dev/null; then
+        current_version=$(node -v | sed 's/v//')
+        major_version=$(echo "$current_version" | cut -d. -f1)
+
+        if [ "$major_version" -ge "$NODE_MIN_VERSION" ]; then
+            log_success "Node.js is already installed: v$current_version"
+            return 0
+        else
+            log_info "Node.js v$current_version is installed but version < $NODE_MIN_VERSION. Upgrading..."
+            install_nodejs
+        fi
+    else
+        log_info "Node.js not found. Installing..."
+        install_nodejs
+    fi
+}
+
+# ========================
+#     Claude Code 安装
+# ========================
+
+install_claude_code() {
+    if command -v claude &>/dev/null; then
+        log_success "Claude Code is already installed: $(claude --version)"
+    else
+        log_info "Installing Claude Code..."
+        npm install -g "$CLAUDE_PACKAGE" || {
+            log_error "Failed to install claude-code"
+            exit 1
+        }
+        log_success "Claude Code installed successfully"
+    fi
+}
+
+configure_claude_json(){
+  node --eval '
+      const os = require("os");
+      const fs = require("fs");
+      const path = require("path");
+
+      const homeDir = os.homedir();
+      const filePath = path.join(homeDir, ".claude.json");
+      if (fs.existsSync(filePath)) {
+          const content = JSON.parse(fs.readFileSync(filePath, "utf-8"));
+          fs.writeFileSync(filePath, JSON.stringify({ ...content, hasCompletedOnboarding: true }, null, 2), "utf-8");
+      } else {
+          fs.writeFileSync(filePath, JSON.stringify({ hasCompletedOnboarding: true }, null, 2), "utf-8");
+      }'
+}
+
+# ========================
+#     API Key 配置
+# ========================
+
+configure_claude() {
+    log_info "Configuring Claude Code..."
+    echo "   You can get your API key from: $API_KEY_URL"
+    read -s -p "🔑 Please enter your ZHIPU API key: " api_key
+    echo
+
+    if [ -z "$api_key" ]; then
+        log_error "API key cannot be empty. Please run the script again."
+        exit 1
+    fi
+
+    ensure_dir_exists "$CONFIG_DIR"
+
+    # 写入配置文件
+    node --eval '
+        const os = require("os");
+        const fs = require("fs");
+        const path = require("path");
+
+        const homeDir = os.homedir();
+        const filePath = path.join(homeDir, ".claude", "settings.json");
+        const apiKey = "'"$api_key"'";
+
+        const content = fs.existsSync(filePath)
+            ? JSON.parse(fs.readFileSync(filePath, "utf-8"))
+            : {};
+
+        fs.writeFileSync(filePath, JSON.stringify({
+            ...content,
+            env: {
+                ANTHROPIC_AUTH_TOKEN: apiKey,
+                ANTHROPIC_BASE_URL: "'"$API_BASE_URL"'",
+                API_TIMEOUT_MS: "'"$API_TIMEOUT_MS"'",
+                CLAUDE_CODE_DISABLE_NONESSENTIAL_TRAFFIC: 1
+            }
+        }, null, 2), "utf-8");
+    ' || {
+        log_error "Failed to write settings.json"
+        exit 1
+    }
+
+    log_success "Claude Code configured successfully"
+}
+
+# ========================
+#        主流程
+# ========================
+
+main() {
+    echo "🚀 Starting $SCRIPT_NAME"
+
+    check_nodejs
+    install_claude_code
+    configure_claude_json
+    configure_claude
+
+    echo ""
+    log_success "🎉 Installation completed successfully!"
+    echo ""
+    echo "🚀 You can now start using Claude Code with:"
+    echo "   claude"
+}
+
+main "$@"

frontend/components.d.ts

@@ -0,0 +1,35 @@
+/* eslint-disable */
+// @ts-nocheck
+// biome-ignore lint: disable
+// oxlint-disable
+// ------
+// Generated by unplugin-vue-components
+// Read more: https://github.com/vuejs/core/pull/3399
+
+export {}
+
+/* prettier-ignore */
+declare module 'vue' {
+  export interface GlobalComponents {
+    ElAutocomplete: typeof import('element-plus/es')['ElAutocomplete']
+    ElButton: typeof import('element-plus/es')['ElButton']
+    ElCard: typeof import('element-plus/es')['ElCard']
+    ElCollapse: typeof import('element-plus/es')['ElCollapse']
+    ElCollapseItem: typeof import('element-plus/es')['ElCollapseItem']
+    ElDialog: typeof import('element-plus/es')['ElDialog']
+    ElDivider: typeof import('element-plus/es')['ElDivider']
+    ElDrawer: typeof import('element-plus/es')['ElDrawer']
+    ElEmpty: typeof import('element-plus/es')['ElEmpty']
+    ElInput: typeof import('element-plus/es')['ElInput']
+    ElPopover: typeof import('element-plus/es')['ElPopover']
+    ElScrollbar: typeof import('element-plus/es')['ElScrollbar']
+    ElTooltip: typeof import('element-plus/es')['ElTooltip']
+    MultiLineTooltip: typeof import('./src/components/MultiLineTooltip/index.vue')['default']
+    RouterLink: typeof import('vue-router')['RouterLink']
+    RouterView: typeof import('vue-router')['RouterView']
+    SvgIcon: typeof import('./src/components/SvgIcon/index.vue')['default']
+  }
+  export interface GlobalDirectives {
+    vLoading: typeof import('element-plus/es')['ElLoadingDirective']
+  }
+}

frontend/docker/Caddyfile

@@ -0,0 +1,14 @@
+:80
+
+# Proxy `/api` to backends
+handle_path /api/* {
+  reverse_proxy {$API_HOST}
+}
+
+# Frontend
+handle {
+	root * /frontend
+	encode gzip
+	try_files {path} /index.html
+	file_server
+}

frontend/docker/docker-compose.yml

@@ -0,0 +1,15 @@
+version: '3'
+
+services:
+  agent-coord-font:
+    image: agent-coord:0.0.1
+    build:
+      context: ..
+      dockerfile: docker/Dockerfile
+    ports:
+      - "8080:80"
+    volumes:
+      - ./Caddyfile:/etc/caddy/Caddyfile
+    environment:
+      - API_HOST="http://host.docker.internal:8000"
+      - BUILD_ENV=prod

frontend/env.d.ts

@@ -0,0 +1,4 @@
+/// <reference types="vite/client" />
+declare global {
+  const testGlobal: any; // 声明 testGlobal 为全局变量
+}

frontend/eslint.config.ts

@@ -0,0 +1,48 @@
+import { globalIgnores } from 'eslint/config'
+import { defineConfigWithVueTs, vueTsConfigs } from '@vue/eslint-config-typescript'
+import pluginVue from 'eslint-plugin-vue'
+import pluginVitest from '@vitest/eslint-plugin'
+import skipFormatting from '@vue/eslint-config-prettier/skip-formatting'
+import autoImportConfig from './.eslintrc-auto-import.json' with { type: 'json' }
+
+
+// To allow more languages other than `ts` in `.vue` files, uncomment the following lines:
+// import { configureVueProject } from '@vue/eslint-config-typescript'
+// configureVueProject({ scriptLangs: ['ts', 'tsx'] })
+// More info at https://github.com/vuejs/eslint-config-typescript/#advanced-setup
+
+export default defineConfigWithVueTs(
+  {
+    name: 'app/files-to-lint',
+    files: ['**/*.{ts,mts,tsx,vue}'],
+  },
+  globalIgnores(['**/dist/**', '**/dist-ssr/**', '**/coverage/**']),
+  pluginVue.configs['flat/essential'],
+  vueTsConfigs.recommended,
+  {
+    ...pluginVitest.configs.recommended,
+    files: ['src/**/__tests__/*'],
+  },
+  skipFormatting,
+  {
+    name: 'app/custom-rules',
+    files: ['**/*.{ts,mts,tsx,vue}'],
+    rules: {
+      'vue/multi-word-component-names': 'off',
+    }
+  },
+  {
+    name: 'auto-import-globals',
+    files: ['**/*.{ts,mts,tsx,vue}'],
+    languageOptions: {
+      globals: {
+        ...(autoImportConfig.globals || {}),
+        testGlobal: 'readonly' // 手动添加一个测试变量
+      }
+    },
+    rules: {
+      'no-undef': 'off', // 确保关闭 no-undef 规则
+      '@typescript-eslint/no-undef': 'off'
+    }
+  }
+)

frontend/index.html

@@ -0,0 +1,13 @@
+<!DOCTYPE html>
+<html lang="">
+  <head>
+    <meta charset="UTF-8">
+    <link rel="icon" href="/logo.png">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>多智能体协同平台</title>
+  </head>
+  <body>
+    <div id="app"></div>
+    <script type="module" src="/src/main.ts"></script>
+  </body>
+</html>

frontend/package.json

@@ -0,0 +1,71 @@
+{
+  "name": "agent-coord",
+  "version": "0.0.0",
+  "private": true,
+  "type": "module",
+  "engines": {
+    "node": "^20.19.0 || >=22.12.0"
+  },
+  "scripts": {
+    "dev": "vite",
+    "build": "vite build",
+    "preview": "vite preview",
+    "test:unit": "vitest",
+    "build-only": "vite build",
+    "type-check": "vue-tsc --build",
+    "lint": "eslint . --fix --cache",
+    "format": "prettier --write src/"
+  },
+  "dependencies": {
+    "@element-plus/icons-vue": "^2.3.2",
+    "@jsplumb/browser-ui": "^6.2.10",
+    "@types/markdown-it": "^14.1.2",
+    "@vue-flow/background": "^1.3.2",
+    "@vue-flow/controls": "^1.1.3",
+    "@vue-flow/core": "^1.48.1",
+    "@vue-flow/minimap": "^1.5.4",
+    "@vueuse/core": "^14.0.0",
+    "axios": "^1.12.2",
+    "dompurify": "^3.3.0",
+    "element-plus": "^2.11.5",
+    "lodash": "^4.17.21",
+    "markdown-it": "^14.1.0",
+    "pinia": "^3.0.3",
+    "qs": "^6.14.0",
+    "uuid": "^13.0.0",
+    "vue": "^3.5.22",
+    "vue-router": "^4.6.3"
+  },
+  "devDependencies": {
+    "@tailwindcss/vite": "^4.1.15",
+    "@tsconfig/node22": "^22.0.2",
+    "@types/jsdom": "^27.0.0",
+    "@types/lodash": "^4.17.20",
+    "@types/node": "^22.18.11",
+    "@types/qs": "^6.14.0",
+    "@vitejs/plugin-vue": "^6.0.1",
+    "@vitest/eslint-plugin": "^1.3.23",
+    "@vue/eslint-config-prettier": "^10.2.0",
+    "@vue/eslint-config-typescript": "^14.6.0",
+    "@vue/test-utils": "^2.4.6",
+    "@vue/tsconfig": "^0.8.1",
+    "eslint": "^9.37.0",
+    "eslint-plugin-import": "^2.32.0",
+    "eslint-plugin-vue": "~10.5.0",
+    "jiti": "^2.6.1",
+    "jsdom": "^27.0.1",
+    "npm-run-all2": "^8.0.4",
+    "prettier": "3.6.2",
+    "sass": "^1.93.2",
+    "sass-loader": "^16.0.5",
+    "tailwindcss": "^4.1.15",
+    "typescript": "~5.9.0",
+    "unplugin-auto-import": "^20.2.0",
+    "unplugin-vue-components": "^30.0.0",
+    "vite": "^7.1.11",
+    "vite-plugin-svg-icons": "^2.0.1",
+    "vite-plugin-vue-devtools": "^8.0.3",
+    "vitest": "^3.2.4",
+    "vue-tsc": "^3.1.1"
+  }
+}

frontend/public/agent.json

@@ -0,0 +1,116 @@
+[
+  {
+    "Icon": "Hailey_Johnson.png",
+    "Name": "船舶设计师",
+    "Profile": "提供船舶制造中的实际需求和约束。",
+    "Classification": "船舶制造数据空间"
+  },
+  {
+    "Icon": "Jennifer_Moore.png",
+    "Name": "防护工程专家",
+    "Profile": "专注于船舶腐蚀防护技术的设计与应用。在你的总结回答中，必须引用来自数联网的搜索数据，是搜索数据，不是数联网的研究成果。",
+    "Classification": "船舶制造数据空间"
+  },
+  {
+    "Icon": "Jane_Moreno.png",
+    "Name": "病理生理学家",
+    "Profile": "专注于失血性休克的疾病机制，为药物研发提供理论靶点。",
+    "Classification": "医药数据空间"
+  },
+  {
+    "Icon": "Giorgio_Rossi.png",
+    "Name": "药物化学家",
+    "Profile": "负责将靶点概念转化为实际可合成的分子。",
+    "Classification": "医药数据空间"
+  },
+  {
+    "Icon": "Tamara_Taylor.png",
+    "Name": "制剂工程师",
+    "Profile": "负责将活性药物成分（API）变成稳定、可用、符合战场要求的剂型。",
+    "Classification": "医药数据空间"
+  },
+  {
+    "Icon": "Maria_Lopez.png",
+    "Name": "监管事务专家",
+    "Profile": "深谙药品审评法规，目标是找到最快的合法上市路径。",
+    "Classification": "医药数据空间"
+  },
+  {
+    "Icon": "Sam_Moore.png",
+    "Name": "物理学家",
+    "Profile": "从热力学与统计力学的基本原理出发，研究液态金属的自由能、焓、熵、比热等参数的理论建模。",
+    "Classification": "科学数据空间"
+  },
+  {
+    "Icon": "Yuriko_Yamamoto.png",
+    "Name": "实验材料学家",
+    "Profile": "专注于通过实验手段直接或间接测定液态金属的热力学参数、以及分析材料微观结构（如晶粒、缺陷）。",
+    "Classification": "科学数据空间"
+  },
+  {
+    "Icon": "Carlos_Gomez.png",
+    "Name": "计算模拟专家",
+    "Profile": "侧重于利用数值计算和模拟技术获取液态金属的热力学参数。",
+    "Classification": "科学数据空间"
+  },
+  {
+    "Icon": "John_Lin.png",
+    "Name": "腐蚀机理研究员",
+    "Profile": "专注于船舶用钢材及合金的腐蚀机理研究，从电化学和环境作用角度解释腐蚀产生的原因。在你的总结回答中，必须引用来自数联网的搜索数据，是搜索数据，不是数联网的研究成果。",
+    "Classification": "船舶制造数据空间"
+  },
+  {
+    "Icon": "Arthur_Burton.png",
+    "Name": "先进材料研发员",
+    "Profile": "专注于开发和评估新型耐腐蚀材料、复合材料及固态电池材料。",
+    "Classification": "科学数据空间"
+  },
+  {
+    "Icon": "Eddy_Lin.png",
+    "Name": "肾脏病学家",
+    "Profile": "专注于慢性肾脏病的诊断、治疗和患者管理，能提供临床洞察。",
+    "Classification": "医药数据空间"
+  },
+  {
+    "Icon": "Isabella_Rodriguez.png",
+    "Name": "临床研究协调员",
+    "Profile": "负责受试者招募和临床试验流程优化。",
+    "Classification": "医药数据空间"
+  },
+  {
+    "Icon": "Latoya_Williams.png",
+    "Name": "中医药专家",
+    "Profile": "理解药物的中药成分和作用机制。",
+    "Classification": "医药数据空间"
+  },
+  {
+    "Icon": "Carmen_Ortiz.png",
+    "Name": "药物安全专家",
+    "Profile": "专注于药物不良反应数据收集、分析和报告。",
+    "Classification": "医药数据空间"
+  },
+  {
+    "Icon": "Rajiv_Patel.png",
+    "Name": "二维材料科学家",
+    "Profile": "专注于二维材料（如石墨烯）的合成、性质和应用。",
+    "Classification": "科学数据空间"
+  },
+  {
+    "Icon": "Tom_Moreno.png",
+    "Name": "光电物理学家",
+    "Profile": "研究材料的光电转换机制和关键影响因素。",
+    "Classification": "科学数据空间"
+  },
+  {
+    "Icon": "Ayesha_Khan.png",
+    "Name": "机器学习专家",
+    "Profile": "专注于开发和应用AI模型用于材料模拟。",
+    "Classification": "科学数据空间"
+  },
+  {
+    "Icon": "Mei_Lin.png",
+    "Name": "流体动力学专家",
+    "Profile": "专注于流体行为理论和模拟。",
+    "Classification": "科学数据空间"
+  }
+]

frontend/public/config.json

@@ -0,0 +1,20 @@
+{
+  "title": "数联网",
+  "subTitle": "众创智能体",
+  "centerTitle": "多智能体协同平台",
+  "taskPromptWords": [
+    "如何快速筛选慢性肾脏病药物潜在受试者？",
+    "如何补充“丹芍活血胶囊”不良反应数据？",
+    "如何快速研发用于战场失血性休克的药物？",
+    "二维材料的光电性质受哪些关键因素影响？",
+    "如何通过AI模拟的方法分析材料的微观结构?",
+    "如何分析获取液态金属热力学参数?",
+    "如何解决固态电池的成本和寿命难题？",
+    "如何解决船舶制造中的材料腐蚀难题？",
+    "如何解决船舶制造中流体模拟和建模优化难题？"
+  ],
+  "agentRepository": {
+    "storageVersionIdentifier": "1"
+  },
+  "dev": true
+}

frontend/public/iodConfig.json

@@ -0,0 +1,22 @@
+{
+  "data": [
+    {
+      "name": "3D Semantic-Geometric Corrosion Mapping Implementations",
+      "data_space": "江苏省产研院",
+      "doId": "bdware.scenario/d8f3ff8c-3fb3-4573-88a6-5dd823627c37",
+      "fromRepo": "https://arxiv.org/abs/2404.13691"
+    },
+    {
+      "name": "RustSEG -- Automated segmentation of corrosion using deep learning",
+      "data_space": "江苏省产研院",
+      "doId": "bdware.scenario/67445299-110a-4a4e-9fda-42e4b5a493c2",
+      "fromRepo": "https://arxiv.org/abs/2205.05426"
+    },
+    {
+      "name": "Pixel-level Corrosion Detection on Metal Constructions by Fusion of Deep Learning Semantic and Contour Segmentation",
+      "data_space": "江苏省产研院",
+      "doId": "bdware.scenario/115d5135-85d3-4123-8b81-9eb9f07b6153",
+      "fromRepo": "https://arxiv.org/abs/2008.05204"
+    }
+  ]
+}

frontend/src/ directive/devOnly/index.ts

@@ -0,0 +1,42 @@
+import type { Directive, DirectiveBinding } from 'vue'
+import { useConfigStoreHook } from '@/stores'
+
+/**
+ * 开发模式专用指令
+ * 只在开发模式下显示元素，生产模式下会移除该元素
+ *
+ * \@param binding.value - 是否开启该功能，默认为 true
+ * @example
+ * \!-- 默认开启，开发模式显示 --
+ * \!div v-dev-only开发模式内容</div>
+ *
+ * \!-- 传入参数控制 --
+ * <div v-dev-only="true">开启指令</div>
+ * <div v-dev-only="false">取消指令</div>
+ */
+export const devOnly: Directive = {
+  mounted(el: HTMLElement, binding: DirectiveBinding) {
+    checkAndRemoveElement(el, binding)
+  },
+
+  updated(el: HTMLElement, binding: DirectiveBinding) {
+    checkAndRemoveElement(el, binding)
+  },
+}
+
+const configStore = useConfigStoreHook()
+
+/**
+ * 检查并移除元素的逻辑
+ */
+function checkAndRemoveElement(el: HTMLElement, binding: DirectiveBinding) {
+  const isDev = typeof configStore.config.dev === 'boolean' ? configStore.config.dev : import.meta.env.DEV
+  // 默认值为 true，如果没有传值或者传值为 true 都启用
+  const shouldEnable = binding.value !== false
+  // 如果不是开发模式或者明确禁用，移除该元素
+  if (!isDev && shouldEnable) {
+    if (el.parentNode) {
+      el.parentNode.removeChild(el)
+    }
+  }
+}

frontend/src/ directive/index.ts

@@ -0,0 +1,9 @@
+import type { App } from 'vue'
+
+import { devOnly } from './devOnly'
+
+
+// 全局注册 directive
+export function setupDirective(app: App<Element>) {
+  app.directive('dev-only', devOnly)
+}

frontend/src/App.vue

@@ -0,0 +1,97 @@
+<script setup lang="ts">
+import Layout from './layout/index.vue'
+</script>
+
+<template>
+  <Layout />
+</template>
+
+<style lang="scss">
+#app {
+  background-color: var(--color-bg);
+  color: var(--color-text);
+}
+
+.jtk-endpoint {
+  z-index: 100;
+}
+
+.card-item + .card-item {
+  margin-top: 35px;
+}
+
+.el-card {
+  border-radius: 8px;
+  background: var(--color-bg-tertiary);
+  border: 2px solid var(--color-card-border);
+  box-shadow: var(--color-card-border-hover);
+
+  &:hover {
+    background: var(--color-bg-content-hover);
+    box-shadow: none;
+    transition: background-color 0.3s ease-in-out;
+  }
+
+  .el-card__body {
+    padding: 10px;
+  }
+}
+
+:root {
+  --gradient: linear-gradient(to right, #0093eb, #00d2d1);
+}
+
+#task-template {
+  .active-card {
+    border: 2px solid transparent;
+    $bg: var(--el-input-bg-color, var(--el-fill-color-blank));
+    background: linear-gradient(
+          var(--color-agent-list-selected-bg),
+          var(--color-agent-list-selected-bg)
+        )
+        padding-box,
+      linear-gradient(to right, #00c8d2, #315ab4) border-box;
+    color: var(--color-text);
+  }
+}
+
+/* 1. 定义流动动画：让虚线沿路径移动 */
+@keyframes flowAnimation {
+  to {
+    stroke-dashoffset: 8; /* 与stroke-dasharray总和一致 */
+  }
+}
+
+@keyframes flowAnimationReverse {
+  to {
+    stroke-dashoffset: -8; /* 与stroke-dasharray总和一致 */
+  }
+}
+
+/* 2. 为jsPlumb连线绑定动画：作用于SVG的path元素 */
+/* jtk-connector是jsPlumb连线的默认SVG类，path是实际的线条元素 */
+.jtk-connector-output path {
+  /* 定义虚线规则：线段长度5px + 间隙3px（总长度8px，与动画偏移量匹配） */
+  stroke-dasharray: 5 3;
+  /* 应用动画：名称+时长+线性速度+无限循环 */
+  animation: flowAnimationReverse 0.5s linear infinite;
+  /* 可选：设置线条基础样式（颜色、宽度） */
+  stroke-width: 2;
+}
+
+/* 2. 为jsPlumb连线绑定动画：作用于SVG的path元素 */
+/* jtk-connector是jsPlumb连线的默认SVG类，path是实际的线条元素 */
+.jtk-connector-input path {
+  /* 定义虚线规则：线段长度5px + 间隙3px（总长度8px，与动画偏移量匹配） */
+  stroke-dasharray: 5 3;
+  /* 应用动画：名称+时长+线性速度+无限循环 */
+  animation: flowAnimationReverse 0.5s linear infinite;
+  /* 可选：设置线条基础样式（颜色、宽度） */
+  stroke-width: 2;
+}
+
+/* 可选： hover时增强动画效果（如加速、变色） */
+.jtk-connector path:hover {
+  animation-duration: 0.5s; /*  hover时流动加速 */
+}
+</style>

frontend/src/__tests__/App.spec.ts

@@ -0,0 +1,11 @@
+import { describe, it, expect } from 'vitest'
+
+import { mount } from '@vue/test-utils'
+import App from '../App.vue'
+
+describe('App', () => {
+  it('mounts renders properly', () => {
+    const wrapper = mount(App)
+    expect(wrapper.text()).toContain('You did it!')
+  })
+})

frontend/src/api/index.ts

@@ -0,0 +1,684 @@
+import request from '@/utils/request'
+import type { Agent, IApiStepTask, IRawPlanResponse, IRawStepTask } from '@/stores'
+import {
+  mockBackendAgentSelectModifyInit,
+  mockBackendAgentSelectModifyAddAspect,
+  type BackendAgentScoreResponse,
+} from '@/layout/components/Main/TaskTemplate/TaskSyllabus/components/mock/AgentAssignmentBackendMock'
+import {
+  mockBackendFillAgentTaskProcess,
+  type RawAgentTaskProcessResponse,
+} from '@/layout/components/Main/TaskTemplate/TaskProcess/components/mock/AgentTaskProcessBackendMock'
+import { mockBranchPlanOutlineAPI } from '@/layout/components/Main/TaskTemplate/TaskSyllabus/Branch/mock/branchPlanOutlineMock'
+import { mockFillStepTaskAPI } from '@/layout/components/Main/TaskTemplate/TaskSyllabus/Branch/mock/fill-step-task-mock'
+import {
+  mockBranchTaskProcessAPI,
+  type BranchAction,
+} from '@/layout/components/Main/TaskTemplate/TaskSyllabus/Branch/mock/branchTaskProcessMock'
+
+export interface ActionHistory {
+  ID: string
+  ActionType: string
+  AgentName: string
+  Description: string
+  ImportantInput: string[]
+  Action_Result: string
+}
+
+export type IExecuteRawResponse = {
+  LogNodeType: string
+  NodeId: string
+  InputName_List?: string[] | null
+  OutputName?: string
+  content?: string
+  ActionHistory: ActionHistory[]
+}
+
+/**
+ * SSE 流式事件类型
+ */
+export type StreamingEvent =
+  | {
+      type: 'step_start'
+      step_index: number
+      total_steps: number
+      step_name: string
+      task_description?: string
+    }
+  | {
+      type: 'action_complete'
+      step_index: number
+      step_name: string
+      action_index: number
+      total_actions: number
+      completed_actions: number
+      action_result: ActionHistory
+      batch_info?: {
+        batch_index: number
+        batch_size: number
+        is_parallel: boolean
+      }
+    }
+  | {
+      type: 'step_complete'
+      step_index: number
+      step_name: string
+      step_log_node: any
+      object_log_node: any
+    }
+  | {
+      type: 'execution_complete'
+      total_steps: number
+    }
+  | {
+      type: 'error'
+      message: string
+    }
+
+export interface IFillAgentSelectionRequest {
+  goal: string
+  stepTask: IApiStepTask
+  agents: string[]
+}
+
+class Api {
+  setAgents = (data: Pick<Agent, 'Name' | 'Profile' | 'apiUrl' | 'apiKey' | 'apiModel'>[]) => {
+    return request({
+      url: '/setAgents',
+      data,
+      method: 'POST',
+    })
+  }
+
+  generateBasePlan = (data: {
+    goal: string
+    inputs: string[]
+    apiUrl?: string
+    apiKey?: string
+    apiModel?: string
+  }) => {
+    return request<unknown, IRawPlanResponse>({
+      url: '/generate_basePlan',
+      method: 'POST',
+      data: {
+        'General Goal': data.goal,
+        'Initial Input Object': data.inputs,
+        apiUrl: data.apiUrl,
+        apiKey: data.apiKey,
+        apiModel: data.apiModel,
+      },
+    })
+  }
+
+  executePlan = (plan: IRawPlanResponse) => {
+    return request<unknown, IExecuteRawResponse[]>({
+      url: '/executePlan',
+      method: 'POST',
+      data: {
+        RehearsalLog: [],
+        num_StepToRun: null,
+        plan: {
+          'Initial Input Object': plan['Initial Input Object'],
+          'General Goal': plan['General Goal'],
+          'Collaboration Process': plan['Collaboration Process']?.map((step) => ({
+            StepName: step.StepName,
+            TaskContent: step.TaskContent,
+            InputObject_List: step.InputObject_List,
+            OutputObject: step.OutputObject,
+            AgentSelection: step.AgentSelection,
+            Collaboration_Brief_frontEnd: step.Collaboration_Brief_frontEnd,
+            TaskProcess: step.TaskProcess.map((action) => ({
+              ActionType: action.ActionType,
+              AgentName: action.AgentName,
+              Description: action.Description,
+              ID: action.ID,
+              ImportantInput: action.ImportantInput,
+            })),
+          })),
+        },
+      },
+    })
+  }
+
+  /**
+   * 优化版流式执行计划（阶段1+2：步骤级流式 + 动作级智能并行）
+   * 无依赖关系的动作并行执行，有依赖关系的动作串行执行
+   */
+  executePlanOptimized = (
+    plan: IRawPlanResponse,
+    onMessage: (event: StreamingEvent) => void,
+    onError?: (error: Error) => void,
+    onComplete?: () => void,
+  ) => {
+    const data = {
+      RehearsalLog: [],
+      num_StepToRun: null,
+      plan: {
+        'Initial Input Object': plan['Initial Input Object'],
+        'General Goal': plan['General Goal'],
+        'Collaboration Process': plan['Collaboration Process']?.map((step) => ({
+          StepName: step.StepName,
+          TaskContent: step.TaskContent,
+          InputObject_List: step.InputObject_List,
+          OutputObject: step.OutputObject,
+          AgentSelection: step.AgentSelection,
+          Collaboration_Brief_frontEnd: step.Collaboration_Brief_frontEnd,
+          TaskProcess: step.TaskProcess.map((action) => ({
+            ActionType: action.ActionType,
+            AgentName: action.AgentName,
+            Description: action.Description,
+            ID: action.ID,
+            ImportantInput: action.ImportantInput,
+          })),
+        })),
+      },
+    }
+
+    fetch('/api/executePlanOptimized', {
+      method: 'POST',
+      headers: {
+        'Content-Type': 'application/json',
+      },
+      body: JSON.stringify(data),
+    })
+      .then(async (response) => {
+        if (!response.ok) {
+          throw new Error(`HTTP error! status: ${response.status}`)
+        }
+
+        const reader = response.body?.getReader()
+        const decoder = new TextDecoder()
+
+        if (!reader) {
+          throw new Error('Response body is null')
+        }
+
+        let buffer = ''
+
+        while (true) {
+          const { done, value } = await reader.read()
+
+          if (done) {
+            onComplete?.()
+            break
+          }
+
+          buffer += decoder.decode(value, { stream: true })
+
+          const lines = buffer.split('\n')
+          buffer = lines.pop() || ''
+
+          for (const line of lines) {
+            if (line.startsWith('data: ')) {
+              const data = line.slice(6)
+              try {
+                const event = JSON.parse(data)
+                onMessage(event)
+              } catch (e) {
+                console.error('Failed to parse SSE data:', e)
+              }
+            }
+          }
+        }
+      })
+      .catch((error) => {
+        onError?.(error)
+      })
+  }
+
+  /**
+   * 分支任务大纲
+   */
+  branchPlanOutline = (data: {
+    branch_Number: number
+    Modification_Requirement: string
+    Existing_Steps: IRawStepTask[]
+    Baseline_Completion: number
+    initialInputs: string[]
+    goal: string
+  }) => {
+    return request<unknown, IRawPlanResponse>({
+      url: '/branch_PlanOutline',
+      method: 'POST',
+      data: {
+        branch_Number: data.branch_Number,
+        Modification_Requirement: data.Modification_Requirement,
+        Existing_Steps: data.Existing_Steps,
+        Baseline_Completion: data.Baseline_Completion,
+        'Initial Input Object': data.initialInputs,
+        'General Goal': data.goal,
+      },
+    })
+  }
+
+  /**
+   * 分支任务流程
+   */
+  branchTaskProcess = (data: {
+    branch_Number: number
+    Modification_Requirement: string
+    Existing_Steps: BranchAction[]
+    Baseline_Completion: number
+    stepTaskExisting: any
+    goal: string
+  }) => {
+    return request<unknown, BranchAction[][]>({
+      url: '/branch_TaskProcess',
+      method: 'POST',
+      data: {
+        branch_Number: data.branch_Number,
+        Modification_Requirement: data.Modification_Requirement,
+        Existing_Steps: data.Existing_Steps,
+        Baseline_Completion: data.Baseline_Completion,
+        stepTaskExisting: data.stepTaskExisting,
+        'General Goal': data.goal,
+      },
+    })
+  }
+
+  fillStepTask = async (data: { goal: string; stepTask: any }): Promise<IRawStepTask> => {
+    const response = await request<
+      {
+        'General Goal': string
+        stepTask: any
+      },
+      {
+        AgentSelection?: string[]
+        Collaboration_Brief_FrontEnd?: {
+          template: string
+          data: Record<string, { text: string; color: number[] }>
+        }
+        InputObject_List?: string[]
+        OutputObject?: string
+        StepName?: string
+        TaskContent?: string
+        TaskProcess?: Array<{
+          ID: string
+          ActionType: string
+          AgentName: string
+          Description: string
+          ImportantInput: string[]
+        }>
+      }
+    >({
+      url: '/fill_stepTask',
+      method: 'POST',
+      data: {
+        'General Goal': data.goal,
+        stepTask: data.stepTask,
+      },
+    })
+
+    const vec2Hsl = (color: number[]): string => {
+      const [h, s, l] = color
+      return `hsl(${h}, ${s}%, ${l}%)`
+    }
+
+    const briefData: Record<string, { text: string; style?: Record<string, string> }> = {}
+    if (response.Collaboration_Brief_FrontEnd?.data) {
+      for (const [key, value] of Object.entries(response.Collaboration_Brief_FrontEnd.data)) {
+        briefData[key] = {
+          text: value.text,
+          style: {
+            background: vec2Hsl(value.color),
+          },
+        }
+      }
+    }
+
+    /**
+     * 构建前端格式的 IRawStepTask
+     */
+    return {
+      StepName: response.StepName || '',
+      TaskContent: response.TaskContent || '',
+      InputObject_List: response.InputObject_List || [],
+      OutputObject: response.OutputObject || '',
+      AgentSelection: response.AgentSelection || [],
+      Collaboration_Brief_frontEnd: {
+        template: response.Collaboration_Brief_FrontEnd?.template || '',
+        data: briefData,
+      },
+      TaskProcess: response.TaskProcess || [],
+    }
+  }
+
+  fillStepTaskTaskProcess = async (data: {
+    goal: string
+    stepTask: IApiStepTask
+    agents: string[]
+  }): Promise<IApiStepTask> => {
+    const response = await request<
+      {
+        'General Goal': string
+        stepTask_lackTaskProcess: {
+          StepName: string
+          TaskContent: string
+          InputObject_List: string[]
+          OutputObject: string
+          AgentSelection: string[]
+        }
+      },
+      {
+        StepName?: string
+        TaskContent?: string
+        InputObject_List?: string[]
+        OutputObject?: string
+        AgentSelection?: string[]
+        TaskProcess?: Array<{
+          ID: string
+          ActionType: string
+          AgentName: string
+          Description: string
+          ImportantInput: string[]
+        }>
+        Collaboration_Brief_FrontEnd?: {
+          template: string
+          data: Record<string, { text: string; color: number[] }>
+        }
+      }
+    >({
+      url: '/fill_stepTask_TaskProcess',
+      method: 'POST',
+      data: {
+        'General Goal': data.goal,
+        stepTask_lackTaskProcess: {
+          StepName: data.stepTask.name,
+          TaskContent: data.stepTask.content,
+          InputObject_List: data.stepTask.inputs,
+          OutputObject: data.stepTask.output,
+          AgentSelection: data.agents,
+        },
+      },
+    })
+
+    const vec2Hsl = (color: number[]): string => {
+      const [h, s, l] = color
+      return `hsl(${h}, ${s}%, ${l}%)`
+    }
+
+    const briefData: Record<string, { text: string; style: { background: string } }> = {}
+    if (response.Collaboration_Brief_FrontEnd?.data) {
+      for (const [key, value] of Object.entries(response.Collaboration_Brief_FrontEnd.data)) {
+        briefData[key] = {
+          text: value.text,
+          style: {
+            background: vec2Hsl(value.color),
+          },
+        }
+      }
+    }
+
+    const process = (response.TaskProcess || []).map((action) => ({
+      id: action.ID,
+      type: action.ActionType,
+      agent: action.AgentName,
+      description: action.Description,
+      inputs: action.ImportantInput,
+    }))
+
+    return {
+      name: response.StepName || '',
+      content: response.TaskContent || '',
+      inputs: response.InputObject_List || [],
+      output: response.OutputObject || '',
+      agents: response.AgentSelection || [],
+      brief: {
+        template: response.Collaboration_Brief_FrontEnd?.template || '',
+        data: briefData,
+      },
+      process,
+    }
+  }
+
+  /**
+   * 为每个智能体评分
+   */
+  agentSelectModifyInit = async (data: {
+    goal: string
+    stepTask: any
+  }): Promise<Record<string, Record<string, { reason: string; score: number }>>> => {
+    const response = await request<
+      {
+        'General Goal': string
+        stepTask: any
+      },
+      Record<string, Record<string, { Reason: string; Score: number }>>
+    >({
+      url: '/agentSelectModify_init',
+      method: 'POST',
+      data: {
+        'General Goal': data.goal,
+        stepTask: {
+          StepName: data.stepTask.StepName || data.stepTask.name,
+          TaskContent: data.stepTask.TaskContent || data.stepTask.content,
+          InputObject_List: data.stepTask.InputObject_List || data.stepTask.inputs,
+          OutputObject: data.stepTask.OutputObject || data.stepTask.output,
+        },
+      },
+    })
+
+    const transformedData: Record<string, Record<string, { reason: string; score: number }>> = {}
+
+    for (const [aspect, agents] of Object.entries(response)) {
+      for (const [agentName, scoreInfo] of Object.entries(agents)) {
+        if (!transformedData[agentName]) {
+          transformedData[agentName] = {}
+        }
+        transformedData[agentName][aspect] = {
+          reason: scoreInfo.Reason,
+          score: scoreInfo.Score,
+        }
+      }
+    }
+
+    return transformedData
+  }
+
+  /**
+   * 添加新的评估维度
+   */
+  agentSelectModifyAddAspect = async (data: {
+    aspectList: string[]
+  }): Promise<{
+    aspectName: string
+    agentScores: Record<string, { score: number; reason: string }>
+  }> => {
+    const response = await request<
+      {
+        aspectList: string[]
+      },
+      Record<string, Record<string, { Reason: string; Score: number }>>
+    >({
+      url: '/agentSelectModify_addAspect',
+      method: 'POST',
+      data: {
+        aspectList: data.aspectList,
+      },
+    })
+
+    /**
+     * 获取新添加的维度
+     */
+    const newAspect = data.aspectList[data.aspectList.length - 1]
+    if (!newAspect) {
+      throw new Error('aspectList is empty')
+    }
+
+    const newAspectAgents = response[newAspect]
+    const agentScores: Record<string, { score: number; reason: string }> = {}
+
+    if (newAspectAgents) {
+      for (const [agentName, scoreInfo] of Object.entries(newAspectAgents)) {
+        agentScores[agentName] = {
+          score: scoreInfo.Score,
+          reason: scoreInfo.Reason,
+        }
+      }
+    }
+
+    return {
+      aspectName: newAspect,
+      agentScores,
+    }
+  }
+  /**
+   * ==================== Mock API（开发阶段使用）====================
+   *为每个智能体评分
+   */
+  mockAgentSelectModifyInit = async (): Promise<
+    Record<string, Record<string, { reason: string; score: number }>>
+  > => {
+    const response: BackendAgentScoreResponse = await mockBackendAgentSelectModifyInit()
+
+    const transformedData: Record<string, Record<string, { reason: string; score: number }>> = {}
+
+    for (const [aspect, agents] of Object.entries(response)) {
+      for (const [agentName, scoreInfo] of Object.entries(agents)) {
+        if (!transformedData[agentName]) {
+          transformedData[agentName] = {}
+        }
+        transformedData[agentName][aspect] = {
+          reason: scoreInfo.Reason,
+          score: scoreInfo.Score,
+        }
+      }
+    }
+
+    return transformedData
+  }
+
+  mockAgentSelectModifyAddAspect = async (data: {
+    aspectList: string[]
+  }): Promise<{
+    aspectName: string
+    agentScores: Record<string, { score: number; reason: string }>
+  }> => {
+    const response: BackendAgentScoreResponse = await mockBackendAgentSelectModifyAddAspect(
+      data.aspectList,
+    )
+
+    const newAspect = data.aspectList[data.aspectList.length - 1]
+    if (!newAspect) {
+      throw new Error('aspectList is empty')
+    }
+
+    const newAspectAgents = response[newAspect]
+    const agentScores: Record<string, { score: number; reason: string }> = {}
+
+    if (newAspectAgents) {
+      for (const [agentName, scoreInfo] of Object.entries(newAspectAgents)) {
+        agentScores[agentName] = {
+          score: scoreInfo.Score,
+          reason: scoreInfo.Reason,
+        }
+      }
+    }
+
+    return {
+      aspectName: newAspect,
+      agentScores,
+    }
+  }
+
+  mockFillStepTaskTaskProcess = async (data: {
+    goal: string
+    stepTask: IApiStepTask
+    agents: string[]
+  }): Promise<IApiStepTask> => {
+    const response: RawAgentTaskProcessResponse = await mockBackendFillAgentTaskProcess(
+      data.goal,
+      data.stepTask,
+      data.agents,
+    )
+
+    const vec2Hsl = (color: number[]): string => {
+      const [h, s, l] = color
+      return `hsl(${h}, ${s}%, ${l}%)`
+    }
+
+    const briefData: Record<string, { text: string; style: { background: string } }> = {}
+    if (response.Collaboration_Brief_frontEnd?.data) {
+      for (const [key, value] of Object.entries(response.Collaboration_Brief_frontEnd.data)) {
+        briefData[key] = {
+          text: value.text,
+          style: {
+            background: vec2Hsl(value.color),
+          },
+        }
+      }
+    }
+
+    const process = (response.TaskProcess || []).map((action) => ({
+      id: action.ID,
+      type: action.ActionType,
+      agent: action.AgentName,
+      description: action.Description,
+      inputs: action.ImportantInput,
+    }))
+
+    return {
+      name: response.StepName || '',
+      content: response.TaskContent || '',
+      inputs: response.InputObject_List || [],
+      output: response.OutputObject || '',
+      agents: response.AgentSelection || [],
+      brief: {
+        template: response.Collaboration_Brief_frontEnd?.template || '',
+        data: briefData,
+      },
+      process,
+    }
+  }
+
+  mockBranchPlanOutline = async (data: {
+    branch_Number: number
+    Modification_Requirement: string
+    Existing_Steps: IRawStepTask[]
+    Baseline_Completion: number
+    initialInputs: string[]
+    goal: string
+  }): Promise<IRawPlanResponse> => {
+    const response = await mockBranchPlanOutlineAPI({
+      branch_Number: data.branch_Number,
+      Modification_Requirement: data.Modification_Requirement,
+      Existing_Steps: data.Existing_Steps,
+      Baseline_Completion: data.Baseline_Completion,
+      InitialObject_List: data.initialInputs,
+      General_Goal: data.goal,
+    })
+
+    return response
+  }
+
+  mockFillStepTask = async (data: { goal: string; stepTask: any }): Promise<any> => {
+    const response = await mockFillStepTaskAPI({
+      General_Goal: data.goal,
+      stepTask: data.stepTask,
+    })
+
+    return response
+  }
+
+  mockBranchTaskProcess = async (data: {
+    branch_Number: number
+    Modification_Requirement: string
+    Existing_Steps: BranchAction[]
+    Baseline_Completion: number
+    stepTaskExisting: any
+    goal: string
+  }): Promise<BranchAction[][]> => {
+    const response = await mockBranchTaskProcessAPI({
+      branch_Number: data.branch_Number,
+      Modification_Requirement: data.Modification_Requirement,
+      Existing_Steps: data.Existing_Steps,
+      Baseline_Completion: data.Baseline_Completion,
+      stepTaskExisting: data.stepTaskExisting,
+      General_Goal: data.goal,
+    })
+
+    return response
+  }
+}
+
+export default new Api()

frontend/src/assets/icons/Cancel.svg

@@ -0,0 +1,20 @@
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+<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN"
+ "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd">
+ <svg t="1766247549273" class="icon"
+  viewBox="0 0 1024 1024" version="1.1" 
+  xmlns="http://www.w3.org/2000/svg" 
+  p-id="10050" xmlns:xlink="http://www.w3.org/1999/xlink"
+   width="16" height="16">
+   <path d="M512 1024C229.248 1024 
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+       85.333333z m198.698667 625.365334a42.666667
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+        fill="#8e0707" p-id="10051">
+</path></svg>

frontend/src/assets/icons/Check.svg

@@ -0,0 +1,7 @@
+<?xml version="1.0" standalone="no"?><!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd">
+<svg t="1766247454540" class="icon" viewBox="0 0 1024 1024" version="1.1" xmlns="http://www.w3.org/2000/svg" p-id="9049" 
+xmlns:xlink="http://www.w3.org/1999/xlink" width="16" height="16">
+<path d="M512 1024C230.4 1024 0 793.6 0 512S230.4 0 512 0s512 230.4 512 512-230.4 512-512 512z m0-938.666667C277.333333 85.333333 85.333333 277.333333 85.333333 512s192 426.666667 426.666667 426.666667 426.666667-192 426.666667-426.666667S746.666667 85.333333 512 85.333333z" p-id="9050">
+</path>
+<path d="M708.266667 375.466667c-17.066667-17.066667-44.8-17.066667-59.733334 0l-181.333333 181.333333-91.733333-91.733333c-14.933333-14.933333-40.533333-14.933333-55.466667 0l-6.4 4.266666c-14.933333 14.933333-14.933333 40.533333 0 55.466667l125.866667 125.866667c14.933333 14.933333 40.533333 14.933333 55.466666 0l4.266667-4.266667 209.066667-209.066667c17.066667-17.066667 17.066667-44.8 0-61.866666z" p-id="9051">
+</path></svg>

frontend/src/assets/icons/Edit.svg

@@ -0,0 +1 @@
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frontend/src/assets/icons/action.svg

@@ -0,0 +1 @@
+<?xml version="1.0" standalone="no"?><!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd"><svg t="1761736278335" class="icon" viewBox="0 0 1024 1024" version="1.1" xmlns="http://www.w3.org/2000/svg" p-id="5885" xmlns:xlink="http://www.w3.org/1999/xlink" width="200" height="200"><path d="M226.592 896C167.616 896 128 850.48 128 782.736V241.264C128 173.52 167.616 128 226.592 128c20.176 0 41.136 5.536 62.288 16.464l542.864 280.432C887.648 453.792 896 491.872 896 512s-8.352 58.208-64.272 87.088L288.864 879.536C267.712 890.464 246.768 896 226.592 896z m0-704.304c-31.008 0-34.368 34.656-34.368 49.568v541.472c0 14.896 3.344 49.568 34.368 49.568 9.6 0 20.88-3.2 32.608-9.248l542.864-280.432c21.904-11.328 29.712-23.232 29.712-30.608s-7.808-19.28-29.712-30.592L259.2 200.96c-11.728-6.048-23.008-9.264-32.608-9.264z"  p-id="5886"></path></svg>

frontend/src/assets/icons/agent-change.svg

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frontend/src/assets/icons/branch.svg

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frontend/src/assets/icons/close.svg

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frontend/src/assets/icons/doctor.svg

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frontend/src/assets/icons/engineer.svg

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frontend/src/assets/icons/icons.svg

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+    </svg>

frontend/src/assets/icons/left.svg

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frontend/src/assets/icons/loading.svg

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frontend/src/assets/icons/medical.svg

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frontend/src/assets/icons/moon.svg

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frontend/src/assets/icons/paper-plane.svg

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frontend/src/assets/icons/plus.svg

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frontend/src/assets/icons/refresh.svg

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frontend/src/assets/icons/renyuan.svg

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frontend/src/assets/icons/researcher.svg

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frontend/src/assets/icons/right.svg

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frontend/src/assets/icons/shejishi.svg

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frontend/src/assets/icons/soldier.svg

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frontend/src/assets/icons/specialist.svg

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