fix: fix unittes & background investigation search logic

.env.example

@@ -13,12 +13,6 @@ TAVILY_API_KEY=tvly-xxx
 # BRAVE_SEARCH_API_KEY=xxx # Required only if SEARCH_API is brave_search
 # JINA_API_KEY=jina_xxx # Optional, default is None
 
-# Optional, RAG provider
-# RAG_PROVIDER=ragflow
-# RAGFLOW_API_URL="http://localhost:9388"
-# RAGFLOW_API_KEY="ragflow-xxx"
-# RAGFLOW_RETRIEVAL_SIZE=10
-
 # Optional, volcengine TTS for generating podcast
 VOLCENGINE_TTS_APPID=xxx
 VOLCENGINE_TTS_ACCESS_TOKEN=xxx

.github/workflows/lint.yaml

@@ -6,9 +6,6 @@ on:
   pull_request:
     branches: [ '*' ]
 
-permissions:
-  contents: read
-
 jobs:
   lint:
     runs-on: ubuntu-latest

.github/workflows/unittest.yaml

@@ -6,9 +6,6 @@ on:
   pull_request:
     branches: [ '*' ]
 
-permissions:
-  contents: read
-
 jobs:
   test:
     runs-on: ubuntu-latest

README.md

@@ -189,18 +189,6 @@ SEARCH_API=tavily
   - Crawling with Jina
   - Advanced content extraction
 
-- 📃 **RAG Integration**
-
-  - Supports mentioning files from [RAGFlow](https://github.com/infiniflow/ragflow) within the input box. [Start up RAGFlow server](https://ragflow.io/docs/dev/).
-
-  ```bash
-     # .env
-     RAG_PROVIDER=ragflow
-     RAGFLOW_API_URL="http://localhost:9388"
-     RAGFLOW_API_KEY="ragflow-xxx"
-     RAGFLOW_RETRIEVAL_SIZE=10
-  ```
-
 - 🔗 **MCP Seamless Integration**
   - Expand capabilities for private domain access, knowledge graph, web browsing and more
   - Facilitates integration of diverse research tools and methodologies
@@ -364,7 +352,6 @@ When you submit a research topic in the Studio UI, you'll be able to see the ent
 DeerFlow supports LangSmith tracing to help you debug and monitor your workflows. To enable LangSmith tracing:
 
 1. Make sure your `.env` file has the following configurations (see `.env.example`):
-
    ```bash
    LANGSMITH_TRACING=true
    LANGSMITH_ENDPOINT="https://api.smith.langchain.com"
@@ -551,8 +538,6 @@ We would like to extend our sincere appreciation to the following projects for t
 
 - **[LangChain](https://github.com/langchain-ai/langchain)**: Their exceptional framework powers our LLM interactions and chains, enabling seamless integration and functionality.
 - **[LangGraph](https://github.com/langchain-ai/langgraph)**: Their innovative approach to multi-agent orchestration has been instrumental in enabling DeerFlow's sophisticated workflows.
-- **[Novel](https://github.com/steven-tey/novel)**: Their Notion-style WYSIWYG editor supports our report editing and AI-assisted rewriting.
-- **[RAGFlow](https://github.com/infiniflow/ragflow)**: We have achieved support for research on users' private knowledge bases through integration with RAGFlow.
 
 These projects exemplify the transformative power of open-source collaboration, and we are proud to build upon their foundations.
 

docs/configuration_guide.md

@@ -49,7 +49,7 @@ BASIC_MODEL:
 BASIC_MODEL:
   base_url: "https://api.deepseek.com"
   model: "deepseek-chat"
-  api_key: YOUR_API_KEY
+  api_key: YOU_API_KEY
 
 # An example of Google Gemini models using OpenAI-Compatible interface
 BASIC_MODEL:

src/config/configuration.py

@@ -2,21 +2,16 @@
 # SPDX-License-Identifier: MIT
 
 import os
-from dataclasses import dataclass, field, fields
+from dataclasses import dataclass, fields
 from typing import Any, Optional
 
 from langchain_core.runnables import RunnableConfig
 
-from src.rag.retriever import Resource
-
 
 @dataclass(kw_only=True)
 class Configuration:
     """The configurable fields."""
 
-    resources: list[Resource] = field(
-        default_factory=list
-    )  # Resources to be used for the research
     max_plan_iterations: int = 1  # Maximum number of plan iterations
     max_step_num: int = 3  # Maximum number of steps in a plan
     max_search_results: int = 3  # Maximum number of search results

src/config/loader.py

@@ -18,8 +18,6 @@ def replace_env_vars(value: str) -> str:
 
 def process_dict(config: Dict[str, Any]) -> Dict[str, Any]:
     """Recursively process dictionary to replace environment variables."""
-    if not config:
-        return {}
     result = {}
     for key, value in config.items():
         if isinstance(value, dict):

src/config/tools.py

@@ -17,10 +17,3 @@ class SearchEngine(enum.Enum):
 
 # Tool configuration
 SELECTED_SEARCH_ENGINE = os.getenv("SEARCH_API", SearchEngine.TAVILY.value)
-
-
-class RAGProvider(enum.Enum):
-    RAGFLOW = "ragflow"
-
-
-SELECTED_RAG_PROVIDER = os.getenv("RAG_PROVIDER")

src/graph/builder.py

@@ -3,7 +3,6 @@
 
 from langgraph.graph import StateGraph, START, END
 from langgraph.checkpoint.memory import MemorySaver
-from src.prompts.planner_model import StepType
 
 from .types import State
 from .nodes import (
@@ -18,22 +17,6 @@ from .nodes import (
 )
 
 
-def continue_to_running_research_step(state: State):
-    current_plan = state.get("current_plan")
-    if not current_plan or not current_plan.steps:
-        return "planner"
-    if all(step.execution_res for step in current_plan.steps):
-        return "planner"
-    for step in current_plan.steps:
-        if not step.execution_res:
-            break
-    if step.step_type and step.step_type == StepType.RESEARCH:
-        return "researcher"
-    if step.step_type and step.step_type == StepType.PROCESSING:
-        return "coder"
-    return "planner"
-
-
 def _build_base_graph():
     """Build and return the base state graph with all nodes and edges."""
     builder = StateGraph(State)
@@ -46,12 +29,6 @@ def _build_base_graph():
     builder.add_node("researcher", researcher_node)
     builder.add_node("coder", coder_node)
     builder.add_node("human_feedback", human_feedback_node)
-    builder.add_edge("background_investigator", "planner")
-    builder.add_conditional_edges(
-        "research_team",
-        continue_to_running_research_step,
-        ["planner", "researcher", "coder"],
-    )
     builder.add_edge("reporter", END)
     return builder
 

src/graph/nodes.py

@@ -17,14 +17,13 @@ from src.tools.search import LoggedTavilySearch
 from src.tools import (
     crawl_tool,
     get_web_search_tool,
-    get_retriever_tool,
     python_repl_tool,
 )
 
 from src.config.agents import AGENT_LLM_MAP
 from src.config.configuration import Configuration
 from src.llms.llm import get_llm_by_type
-from src.prompts.planner_model import Plan
+from src.prompts.planner_model import Plan, StepType
 from src.prompts.template import apply_prompt_template
 from src.utils.json_utils import repair_json_output
 
@@ -45,24 +44,22 @@ def handoff_to_planner(
     return
 
 
-def background_investigation_node(state: State, config: RunnableConfig):
+def background_investigation_node(
+    state: State, config: RunnableConfig
+) -> Command[Literal["planner"]]:
     logger.info("background investigation node is running.")
     configurable = Configuration.from_runnable_config(config)
     query = state["messages"][-1].content
-    background_investigation_results = None
     if SELECTED_SEARCH_ENGINE == SearchEngine.TAVILY.value:
         searched_content = LoggedTavilySearch(
             max_results=configurable.max_search_results
         ).invoke(query)
+        background_investigation_results = None
         if isinstance(searched_content, list):
             background_investigation_results = [
-                f"## {elem['title']}\n\n{elem['content']}" for elem in searched_content
+                {"title": elem["title"], "content": elem["content"]}
+                for elem in searched_content
             ]
-            return {
-                "background_investigation_results": "\n\n".join(
-                    background_investigation_results
-                )
-            }
         else:
             logger.error(
                 f"Tavily search returned malformed response: {searched_content}"
@@ -71,11 +68,14 @@ def background_investigation_node(state: State, config: RunnableConfig):
         background_investigation_results = get_web_search_tool(
             configurable.max_search_results
         ).invoke(query)
-    return {
-        "background_investigation_results": json.dumps(
-            background_investigation_results, ensure_ascii=False
-        )
-    }
+    return Command(
+        update={
+            "background_investigation_results": json.dumps(
+                background_investigation_results, ensure_ascii=False
+            )
+        },
+        goto="planner",
+    )
 
 
 def planner_node(
@@ -206,11 +206,10 @@ def human_feedback_node(
 
 
 def coordinator_node(
-    state: State, config: RunnableConfig
+    state: State,
 ) -> Command[Literal["planner", "background_investigator", "__end__"]]:
     """Coordinator node that communicate with customers."""
     logger.info("Coordinator talking.")
-    configurable = Configuration.from_runnable_config(config)
     messages = apply_prompt_template("coordinator", state)
     response = (
         get_llm_by_type(AGENT_LLM_MAP["coordinator"])
@@ -243,7 +242,7 @@ def coordinator_node(
         logger.debug(f"Coordinator response: {response}")
 
     return Command(
-        update={"locale": locale, "resources": configurable.resources},
+        update={"locale": locale},
         goto=goto,
     )
 
@@ -286,10 +285,24 @@ def reporter_node(state: State):
     return {"final_report": response_content}
 
 
-def research_team_node(state: State):
+def research_team_node(
+    state: State,
+) -> Command[Literal["planner", "researcher", "coder"]]:
     """Research team node that collaborates on tasks."""
     logger.info("Research team is collaborating on tasks.")
-    pass
+    current_plan = state.get("current_plan")
+    if not current_plan or not current_plan.steps:
+        return Command(goto="planner")
+    if all(step.execution_res for step in current_plan.steps):
+        return Command(goto="planner")
+    for step in current_plan.steps:
+        if not step.execution_res:
+            break
+    if step.step_type and step.step_type == StepType.RESEARCH:
+        return Command(goto="researcher")
+    if step.step_type and step.step_type == StepType.PROCESSING:
+        return Command(goto="coder")
+    return Command(goto="planner")
 
 
 async def _execute_agent_step(
@@ -313,14 +326,14 @@ async def _execute_agent_step(
         logger.warning("No unexecuted step found")
         return Command(goto="research_team")
 
-    logger.info(f"Executing step: {current_step.title}, agent: {agent_name}")
+    logger.info(f"Executing step: {current_step.title}")
 
     # Format completed steps information
     completed_steps_info = ""
     if completed_steps:
         completed_steps_info = "# Existing Research Findings\n\n"
         for i, step in enumerate(completed_steps):
-            completed_steps_info += f"## Existing Finding {i + 1}: {step.title}\n\n"
+            completed_steps_info += f"## Existing Finding {i+1}: {step.title}\n\n"
             completed_steps_info += f"<finding>\n{step.execution_res}\n</finding>\n\n"
 
     # Prepare the input for the agent with completed steps info
@@ -334,19 +347,6 @@ async def _execute_agent_step(
 
     # Add citation reminder for researcher agent
     if agent_name == "researcher":
-        if state.get("resources"):
-            resources_info = "**The user mentioned the following resource files:**\n\n"
-            for resource in state.get("resources"):
-                resources_info += f"- {resource.title} ({resource.description})\n"
-
-            agent_input["messages"].append(
-                HumanMessage(
-                    content=resources_info
-                    + "\n\n"
-                    + "You MUST use the **local_search_tool** to retrieve the information from the resource files.",
-                )
-            )
-
         agent_input["messages"].append(
             HumanMessage(
                 content="IMPORTANT: DO NOT include inline citations in the text. Instead, track all sources and include a References section at the end using link reference format. Include an empty line between each citation for better readability. Use this format for each reference:\n- [Source Title](URL)\n\n- [Another Source](URL)",
@@ -377,7 +377,6 @@ async def _execute_agent_step(
         )
         recursion_limit = default_recursion_limit
 
-    logger.info(f"Agent input: {agent_input}")
     result = await agent.ainvoke(
         input=agent_input, config={"recursion_limit": recursion_limit}
     )
@@ -469,16 +468,11 @@ async def researcher_node(
     """Researcher node that do research"""
     logger.info("Researcher node is researching.")
     configurable = Configuration.from_runnable_config(config)
-    tools = [get_web_search_tool(configurable.max_search_results), crawl_tool]
-    retriever_tool = get_retriever_tool(state.get("resources", []))
-    if retriever_tool:
-        tools.insert(0, retriever_tool)
-    logger.info(f"Researcher tools: {tools}")
     return await _setup_and_execute_agent_step(
         state,
         config,
         "researcher",
-        tools,
+        [get_web_search_tool(configurable.max_search_results), crawl_tool],
     )
 
 

src/graph/types.py

@@ -1,10 +1,12 @@
 # Copyright (c) 2025 Bytedance Ltd. and/or its affiliates
 # SPDX-License-Identifier: MIT
 
+import operator
+from typing import Annotated
+
 from langgraph.graph import MessagesState
 
 from src.prompts.planner_model import Plan
-from src.rag import Resource
 
 
 class State(MessagesState):
@@ -13,7 +15,6 @@ class State(MessagesState):
     # Runtime Variables
     locale: str = "en-US"
     observations: list[str] = []
-    resources: list[Resource] = []
     plan_iterations: int = 0
     current_plan: Plan | str = None
     final_report: str = ""

src/llms/llm.py

@@ -3,7 +3,6 @@
 
 from pathlib import Path
 from typing import Any, Dict
-import os
 
 from langchain_openai import ChatOpenAI
 
@@ -14,40 +13,18 @@ from src.config.agents import LLMType
 _llm_cache: dict[LLMType, ChatOpenAI] = {}
 
 
-def _get_env_llm_conf(llm_type: str) -> Dict[str, Any]:
-    """
-    Get LLM configuration from environment variables.
-    Environment variables should follow the format: {LLM_TYPE}__{KEY}
-    e.g., BASIC_MODEL__api_key, BASIC_MODEL__base_url
-    """
-    prefix = f"{llm_type.upper()}_MODEL__"
-    conf = {}
-    for key, value in os.environ.items():
-        if key.startswith(prefix):
-            conf_key = key[len(prefix) :].lower()
-            conf[conf_key] = value
-    return conf
-
-
 def _create_llm_use_conf(llm_type: LLMType, conf: Dict[str, Any]) -> ChatOpenAI:
     llm_type_map = {
-        "reasoning": conf.get("REASONING_MODEL", {}),
-        "basic": conf.get("BASIC_MODEL", {}),
-        "vision": conf.get("VISION_MODEL", {}),
+        "reasoning": conf.get("REASONING_MODEL"),
+        "basic": conf.get("BASIC_MODEL"),
+        "vision": conf.get("VISION_MODEL"),
     }
     llm_conf = llm_type_map.get(llm_type)
+    if not llm_conf:
+        raise ValueError(f"Unknown LLM type: {llm_type}")
     if not isinstance(llm_conf, dict):
         raise ValueError(f"Invalid LLM Conf: {llm_type}")
-    # Get configuration from environment variables
-    env_conf = _get_env_llm_conf(llm_type)
-
-    # Merge configurations, with environment variables taking precedence
-    merged_conf = {**llm_conf, **env_conf}
-
-    if not merged_conf:
-        raise ValueError(f"Unknown LLM Conf: {llm_type}")
-
-    return ChatOpenAI(**merged_conf)
+    return ChatOpenAI(**llm_conf)
 
 
 def get_llm_by_type(

src/prompts/planner.md

@@ -57,15 +57,14 @@ Before creating a detailed plan, assess if there is sufficient context to answer
 
 Different types of steps have different web search requirements:
 
-1. **Research Steps** (`need_search: true`):
-   - Retrieve information from the file with the URL with `rag://` or `http://` prefix specified by the user
+1. **Research Steps** (`need_web_search: true`):
    - Gathering market data or industry trends
    - Finding historical information
    - Collecting competitor analysis
    - Researching current events or news
    - Finding statistical data or reports
 
-2. **Data Processing Steps** (`need_search: false`):
+2. **Data Processing Steps** (`need_web_search: false`):
    - API calls and data extraction
    - Database queries
    - Raw data collection from existing sources
@@ -75,10 +74,10 @@ Different types of steps have different web search requirements:
 ## Exclusions
 
 - **No Direct Calculations in Research Steps**:
-  - Research steps should only gather data and information
-  - All mathematical calculations must be handled by processing steps
-  - Numerical analysis must be delegated to processing steps
-  - Research steps focus on information gathering only
+    - Research steps should only gather data and information
+    - All mathematical calculations must be handled by processing steps
+    - Numerical analysis must be delegated to processing steps
+    - Research steps focus on information gathering only
 
 ## Analysis Framework
 
@@ -136,16 +135,16 @@ When planning information gathering, consider these key aspects and ensure COMPR
 - To begin with, repeat user's requirement in your own words as `thought`.
 - Rigorously assess if there is sufficient context to answer the question using the strict criteria above.
 - If context is sufficient:
-  - Set `has_enough_context` to true
-  - No need to create information gathering steps
+    - Set `has_enough_context` to true
+    - No need to create information gathering steps
 - If context is insufficient (default assumption):
-  - Break down the required information using the Analysis Framework
-  - Create NO MORE THAN {{ max_step_num }} focused and comprehensive steps that cover the most essential aspects
-  - Ensure each step is substantial and covers related information categories
-  - Prioritize breadth and depth within the {{ max_step_num }}-step constraint
-  - For each step, carefully assess if web search is needed:
-    - Research and external data gathering: Set `need_search: true`
-    - Internal data processing: Set `need_search: false`
+    - Break down the required information using the Analysis Framework
+    - Create NO MORE THAN {{ max_step_num }} focused and comprehensive steps that cover the most essential aspects
+    - Ensure each step is substantial and covers related information categories
+    - Prioritize breadth and depth within the {{ max_step_num }}-step constraint
+    - For each step, carefully assess if web search is needed:
+        - Research and external data gathering: Set `need_web_search: true`
+        - Internal data processing: Set `need_web_search: false`
 - Specify the exact data to be collected in step's `description`. Include a `note` if necessary.
 - Prioritize depth and volume of relevant information - limited information is not acceptable.
 - Use the same language as the user to generate the plan.
@@ -157,10 +156,10 @@ Directly output the raw JSON format of `Plan` without "```json". The `Plan` inte
 
 ```ts
 interface Step {
-  need_search: boolean; // Must be explicitly set for each step
+  need_web_search: boolean;  // Must be explicitly set for each step
   title: string;
-  description: string; // Specify exactly what data to collect. If the user input contains a link, please retain the full Markdown format when necessary.
-  step_type: "research" | "processing"; // Indicates the nature of the step
+  description: string;  // Specify exactly what data to collect
+  step_type: "research" | "processing";  // Indicates the nature of the step
 }
 
 interface Plan {
@@ -168,7 +167,7 @@ interface Plan {
   has_enough_context: boolean;
   thought: string;
   title: string;
-  steps: Step[]; // Research & Processing steps to get more context
+  steps: Step[];  // Research & Processing steps to get more context
 }
 ```
 
@@ -180,8 +179,8 @@ interface Plan {
 - Prioritize BOTH breadth (covering essential aspects) AND depth (detailed information on each aspect)
 - Never settle for minimal information - the goal is a comprehensive, detailed final report
 - Limited or insufficient information will lead to an inadequate final report
-- Carefully assess each step's web search or retrieve from URL requirement based on its nature:
-  - Research steps (`need_search: true`) for gathering information
-  - Processing steps (`need_search: false`) for calculations and data processing
+- Carefully assess each step's web search requirement based on its nature:
+    - Research steps (`need_web_search: true`) for gathering information
+    - Processing steps (`need_web_search: false`) for calculations and data processing
 - Default to gathering more information unless the strictest sufficient context criteria are met
-- Always use the language specified by the locale = **{{ locale }}**.
+- Always use the language specified by the locale = **{{ locale }}**.

src/prompts/planner_model.py

@@ -13,7 +13,9 @@ class StepType(str, Enum):
 
 
 class Step(BaseModel):
-    need_search: bool = Field(..., description="Must be explicitly set for each step")
+    need_web_search: bool = Field(
+        ..., description="Must be explicitly set for each step"
+    )
     title: str
     description: str = Field(..., description="Specify exactly what data to collect")
     step_type: StepType = Field(..., description="Indicates the nature of the step")
@@ -45,7 +47,7 @@ class Plan(BaseModel):
                     "title": "AI Market Research Plan",
                     "steps": [
                         {
-                            "need_search": True,
+                            "need_web_search": True,
                             "title": "Current AI Market Analysis",
                             "description": (
                                 "Collect data on market size, growth rates, major players, and investment trends in AI sector."

src/prompts/researcher.md

@@ -11,9 +11,6 @@ You are dedicated to conducting thorough investigations using search tools and p
 You have access to two types of tools:
 
 1. **Built-in Tools**: These are always available:
-   {% if resources %}
-   - **local_search_tool**: For retrieving information from the local knowledge base when user mentioned in the messages.
-   {% endif %}
    - **web_search_tool**: For performing web searches
    - **crawl_tool**: For reading content from URLs
 
@@ -37,7 +34,7 @@ You have access to two types of tools:
 3. **Plan the Solution**: Determine the best approach to solve the problem using the available tools.
 4. **Execute the Solution**:
    - Forget your previous knowledge, so you **should leverage the tools** to retrieve the information.
-   - Use the {% if resources %}**local_search_tool** or{% endif %}**web_search_tool** or other suitable search tool to perform a search with the provided keywords.
+   - Use the **web_search_tool** or other suitable search tool to perform a search with the provided keywords.
    - When the task includes time range requirements:
      - Incorporate appropriate time-based search parameters in your queries (e.g., "after:2020", "before:2023", or specific date ranges)
      - Ensure search results respect the specified time constraints.

src/rag/__init__.py

@@ -1,8 +0,0 @@
-# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates
-# SPDX-License-Identifier: MIT
-
-from .retriever import Retriever, Document, Resource
-from .ragflow import RAGFlowProvider
-from .builder import build_retriever
-
-__all__ = [Retriever, Document, Resource, RAGFlowProvider, build_retriever]

src/rag/builder.py

@@ -1,14 +0,0 @@
-# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates
-# SPDX-License-Identifier: MIT
-
-from src.config.tools import SELECTED_RAG_PROVIDER, RAGProvider
-from src.rag.ragflow import RAGFlowProvider
-from src.rag.retriever import Retriever
-
-
-def build_retriever() -> Retriever | None:
-    if SELECTED_RAG_PROVIDER == RAGProvider.RAGFLOW.value:
-        return RAGFlowProvider()
-    elif SELECTED_RAG_PROVIDER:
-        raise ValueError(f"Unsupported RAG provider: {SELECTED_RAG_PROVIDER}")
-    return None

src/rag/ragflow.py

@@ -1,133 +0,0 @@
-# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates
-# SPDX-License-Identifier: MIT
-
-import os
-import requests
-from src.rag.retriever import Chunk, Document, Resource, Retriever
-from urllib.parse import urlparse
-
-
-class RAGFlowProvider(Retriever):
-    """
-    RAGFlowProvider is a provider that uses RAGFlow to retrieve documents.
-    """
-
-    api_url: str
-    api_key: str
-    page_size: int = 10
-
-    def __init__(self):
-        api_url = os.getenv("RAGFLOW_API_URL")
-        if not api_url:
-            raise ValueError("RAGFLOW_API_URL is not set")
-        self.api_url = api_url
-
-        api_key = os.getenv("RAGFLOW_API_KEY")
-        if not api_key:
-            raise ValueError("RAGFLOW_API_KEY is not set")
-        self.api_key = api_key
-
-        page_size = os.getenv("RAGFLOW_PAGE_SIZE")
-        if page_size:
-            self.page_size = int(page_size)
-
-    def query_relevant_documents(
-        self, query: str, resources: list[Resource] = []
-    ) -> list[Document]:
-        headers = {
-            "Authorization": f"Bearer {self.api_key}",
-            "Content-Type": "application/json",
-        }
-
-        dataset_ids: list[str] = []
-        document_ids: list[str] = []
-
-        for resource in resources:
-            dataset_id, document_id = parse_uri(resource.uri)
-            dataset_ids.append(dataset_id)
-            if document_id:
-                document_ids.append(document_id)
-
-        payload = {
-            "question": query,
-            "dataset_ids": dataset_ids,
-            "document_ids": document_ids,
-            "page_size": self.page_size,
-        }
-
-        response = requests.post(
-            f"{self.api_url}/api/v1/retrieval", headers=headers, json=payload
-        )
-
-        if response.status_code != 200:
-            raise Exception(f"Failed to query documents: {response.text}")
-
-        result = response.json()
-        data = result.get("data", {})
-        doc_aggs = data.get("doc_aggs", [])
-        docs: dict[str, Document] = {
-            doc.get("doc_id"): Document(
-                id=doc.get("doc_id"),
-                title=doc.get("doc_name"),
-                chunks=[],
-            )
-            for doc in doc_aggs
-        }
-
-        for chunk in data.get("chunks", []):
-            doc = docs.get(chunk.get("document_id"))
-            if doc:
-                doc.chunks.append(
-                    Chunk(
-                        content=chunk.get("content"),
-                        similarity=chunk.get("similarity"),
-                    )
-                )
-
-        return list(docs.values())
-
-    def list_resources(self, query: str | None = None) -> list[Resource]:
-        headers = {
-            "Authorization": f"Bearer {self.api_key}",
-            "Content-Type": "application/json",
-        }
-
-        params = {}
-        if query:
-            params["name"] = query
-
-        response = requests.get(
-            f"{self.api_url}/api/v1/datasets", headers=headers, params=params
-        )
-
-        if response.status_code != 200:
-            raise Exception(f"Failed to list resources: {response.text}")
-
-        result = response.json()
-        resources = []
-
-        for item in result.get("data", []):
-            item = Resource(
-                uri=f"rag://dataset/{item.get('id')}",
-                title=item.get("name", ""),
-                description=item.get("description", ""),
-            )
-            resources.append(item)
-
-        return resources
-
-
-def parse_uri(uri: str) -> tuple[str, str]:
-    parsed = urlparse(uri)
-    if parsed.scheme != "rag":
-        raise ValueError(f"Invalid URI: {uri}")
-    return parsed.path.split("/")[1], parsed.fragment
-
-
-if __name__ == "__main__":
-    uri = "rag://dataset/123#abc"
-    parsed = urlparse(uri)
-    print(parsed.scheme)
-    print(parsed.netloc)
-    print(parsed.path)
-    print(parsed.fragment)

src/rag/retriever.py

@@ -1,80 +0,0 @@
-# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates
-# SPDX-License-Identifier: MIT
-
-import abc
-from pydantic import BaseModel, Field
-
-
-class Chunk:
-    content: str
-    similarity: float
-
-    def __init__(self, content: str, similarity: float):
-        self.content = content
-        self.similarity = similarity
-
-
-class Document:
-    """
-    Document is a class that represents a document.
-    """
-
-    id: str
-    url: str | None = None
-    title: str | None = None
-    chunks: list[Chunk] = []
-
-    def __init__(
-        self,
-        id: str,
-        url: str | None = None,
-        title: str | None = None,
-        chunks: list[Chunk] = [],
-    ):
-        self.id = id
-        self.url = url
-        self.title = title
-        self.chunks = chunks
-
-    def to_dict(self) -> dict:
-        d = {
-            "id": self.id,
-            "content": "\n\n".join([chunk.content for chunk in self.chunks]),
-        }
-        if self.url:
-            d["url"] = self.url
-        if self.title:
-            d["title"] = self.title
-        return d
-
-
-class Resource(BaseModel):
-    """
-    Resource is a class that represents a resource.
-    """
-
-    uri: str = Field(..., description="The URI of the resource")
-    title: str = Field(..., description="The title of the resource")
-    description: str | None = Field("", description="The description of the resource")
-
-
-class Retriever(abc.ABC):
-    """
-    Define a RAG provider, which can be used to query documents and resources.
-    """
-
-    @abc.abstractmethod
-    def list_resources(self, query: str | None = None) -> list[Resource]:
-        """
-        List resources from the rag provider.
-        """
-        pass
-
-    @abc.abstractmethod
-    def query_relevant_documents(
-        self, query: str, resources: list[Resource] = []
-    ) -> list[Document]:
-        """
-        Query relevant documents from the resources.
-        """
-        pass

src/server/app.py

@@ -5,22 +5,19 @@ import base64
 import json
 import logging
 import os
-from typing import Annotated, List, cast
+from typing import List, cast
 from uuid import uuid4
 
-from fastapi import FastAPI, HTTPException, Query
+from fastapi import FastAPI, HTTPException
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.responses import Response, StreamingResponse
 from langchain_core.messages import AIMessageChunk, ToolMessage, BaseMessage
 from langgraph.types import Command
 
-from src.config.tools import SELECTED_RAG_PROVIDER
 from src.graph.builder import build_graph_with_memory
 from src.podcast.graph.builder import build_graph as build_podcast_graph
 from src.ppt.graph.builder import build_graph as build_ppt_graph
 from src.prose.graph.builder import build_graph as build_prose_graph
-from src.rag.builder import build_retriever
-from src.rag.retriever import Resource
 from src.server.chat_request import (
     ChatMessage,
     ChatRequest,
@@ -31,17 +28,10 @@ from src.server.chat_request import (
 )
 from src.server.mcp_request import MCPServerMetadataRequest, MCPServerMetadataResponse
 from src.server.mcp_utils import load_mcp_tools
-from src.server.rag_request import (
-    RAGConfigResponse,
-    RAGResourceRequest,
-    RAGResourcesResponse,
-)
 from src.tools import VolcengineTTS
 
 logger = logging.getLogger(__name__)
 
-INTERNAL_SERVER_ERROR_DETAIL = "Internal Server Error"
-
 app = FastAPI(
     title="DeerFlow API",
     description="API for Deer",
@@ -69,7 +59,6 @@ async def chat_stream(request: ChatRequest):
         _astream_workflow_generator(
             request.model_dump()["messages"],
             thread_id,
-            request.resources,
             request.max_plan_iterations,
             request.max_step_num,
             request.max_search_results,
@@ -85,7 +74,6 @@ async def chat_stream(request: ChatRequest):
 async def _astream_workflow_generator(
     messages: List[ChatMessage],
     thread_id: str,
-    resources: List[Resource],
     max_plan_iterations: int,
     max_step_num: int,
     max_search_results: int,
@@ -113,7 +101,6 @@ async def _astream_workflow_generator(
         input_,
         config={
             "thread_id": thread_id,
-            "resources": resources,
             "max_plan_iterations": max_plan_iterations,
             "max_step_num": max_step_num,
             "max_search_results": max_search_results,
@@ -236,7 +223,7 @@ async def text_to_speech(request: TTSRequest):
         )
     except Exception as e:
         logger.exception(f"Error in TTS endpoint: {str(e)}")
-        raise HTTPException(status_code=500, detail=INTERNAL_SERVER_ERROR_DETAIL)
+        raise HTTPException(status_code=500, detail=str(e))
 
 
 @app.post("/api/podcast/generate")
@@ -250,7 +237,7 @@ async def generate_podcast(request: GeneratePodcastRequest):
         return Response(content=audio_bytes, media_type="audio/mp3")
     except Exception as e:
         logger.exception(f"Error occurred during podcast generation: {str(e)}")
-        raise HTTPException(status_code=500, detail=INTERNAL_SERVER_ERROR_DETAIL)
+        raise HTTPException(status_code=500, detail=str(e))
 
 
 @app.post("/api/ppt/generate")
@@ -269,14 +256,13 @@ async def generate_ppt(request: GeneratePPTRequest):
         )
     except Exception as e:
         logger.exception(f"Error occurred during ppt generation: {str(e)}")
-        raise HTTPException(status_code=500, detail=INTERNAL_SERVER_ERROR_DETAIL)
+        raise HTTPException(status_code=500, detail=str(e))
 
 
 @app.post("/api/prose/generate")
 async def generate_prose(request: GenerateProseRequest):
     try:
-        sanitized_prompt = request.prompt.replace("\r\n", "").replace("\n", "")
-        logger.info(f"Generating prose for prompt: {sanitized_prompt}")
+        logger.info(f"Generating prose for prompt: {request.prompt}")
         workflow = build_prose_graph()
         events = workflow.astream(
             {
@@ -293,7 +279,7 @@ async def generate_prose(request: GenerateProseRequest):
         )
     except Exception as e:
         logger.exception(f"Error occurred during prose generation: {str(e)}")
-        raise HTTPException(status_code=500, detail=INTERNAL_SERVER_ERROR_DETAIL)
+        raise HTTPException(status_code=500, detail=str(e))
 
 
 @app.post("/api/mcp/server/metadata", response_model=MCPServerMetadataResponse)
@@ -331,20 +317,5 @@ async def mcp_server_metadata(request: MCPServerMetadataRequest):
     except Exception as e:
         if not isinstance(e, HTTPException):
             logger.exception(f"Error in MCP server metadata endpoint: {str(e)}")
-            raise HTTPException(status_code=500, detail=INTERNAL_SERVER_ERROR_DETAIL)
+            raise HTTPException(status_code=500, detail=str(e))
         raise
-
-
-@app.get("/api/rag/config", response_model=RAGConfigResponse)
-async def rag_config():
-    """Get the config of the RAG."""
-    return RAGConfigResponse(provider=SELECTED_RAG_PROVIDER)
-
-
-@app.get("/api/rag/resources", response_model=RAGResourcesResponse)
-async def rag_resources(request: Annotated[RAGResourceRequest, Query()]):
-    """Get the resources of the RAG."""
-    retriever = build_retriever()
-    if retriever:
-        return RAGResourcesResponse(resources=retriever.list_resources(request.query))
-    return RAGResourcesResponse(resources=[])

src/server/chat_request.py

@@ -5,8 +5,6 @@ from typing import List, Optional, Union
 
 from pydantic import BaseModel, Field
 
-from src.rag.retriever import Resource
-
 
 class ContentItem(BaseModel):
     type: str = Field(..., description="The type of content (text, image, etc.)")
@@ -30,9 +28,6 @@ class ChatRequest(BaseModel):
     messages: Optional[List[ChatMessage]] = Field(
         [], description="History of messages between the user and the assistant"
     )
-    resources: Optional[List[Resource]] = Field(
-        [], description="Resources to be used for the research"
-    )
     debug: Optional[bool] = Field(False, description="Whether to enable debug logging")
     thread_id: Optional[str] = Field(
         "__default__", description="A specific conversation identifier"

src/server/rag_request.py

@@ -1,28 +0,0 @@
-# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates
-# SPDX-License-Identifier: MIT
-
-from pydantic import BaseModel, Field
-
-from src.rag.retriever import Resource
-
-
-class RAGConfigResponse(BaseModel):
-    """Response model for RAG config."""
-
-    provider: str | None = Field(
-        None, description="The provider of the RAG, default is ragflow"
-    )
-
-
-class RAGResourceRequest(BaseModel):
-    """Request model for RAG resource."""
-
-    query: str | None = Field(
-        None, description="The query of the resource need to be searched"
-    )
-
-
-class RAGResourcesResponse(BaseModel):
-    """Response model for RAG resources."""
-
-    resources: list[Resource] = Field(..., description="The resources of the RAG")

src/tools/__init__.py

@@ -5,7 +5,6 @@ import os
 
 from .crawl import crawl_tool
 from .python_repl import python_repl_tool
-from .retriever import get_retriever_tool
 from .search import get_web_search_tool
 from .tts import VolcengineTTS
 
@@ -13,6 +12,5 @@ __all__ = [
     "crawl_tool",
     "python_repl_tool",
     "get_web_search_tool",
-    "get_retriever_tool",
     "VolcengineTTS",
 ]

src/tools/retriever.py

@@ -1,77 +0,0 @@
-# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates
-# SPDX-License-Identifier: MIT
-
-import logging
-from typing import List, Optional, Type
-from langchain_core.tools import BaseTool
-from langchain_core.callbacks import (
-    AsyncCallbackManagerForToolRun,
-    CallbackManagerForToolRun,
-)
-from pydantic import BaseModel, Field
-
-from src.config.tools import SELECTED_RAG_PROVIDER
-from src.rag import Document, Retriever, Resource, build_retriever
-
-logger = logging.getLogger(__name__)
-
-
-class RetrieverInput(BaseModel):
-    keywords: str = Field(description="search keywords to look up")
-
-
-class RetrieverTool(BaseTool):
-    name: str = "local_search_tool"
-    description: str = (
-        "Useful for retrieving information from the file with `rag://` uri prefix, it should be higher priority than the web search or writing code. Input should be a search keywords."
-    )
-    args_schema: Type[BaseModel] = RetrieverInput
-
-    retriever: Retriever = Field(default_factory=Retriever)
-    resources: list[Resource] = Field(default_factory=list)
-
-    def _run(
-        self,
-        keywords: str,
-        run_manager: Optional[CallbackManagerForToolRun] = None,
-    ) -> list[Document]:
-        logger.info(
-            f"Retriever tool query: {keywords}", extra={"resources": self.resources}
-        )
-        documents = self.retriever.query_relevant_documents(keywords, self.resources)
-        if not documents:
-            return "No results found from the local knowledge base."
-        return [doc.to_dict() for doc in documents]
-
-    async def _arun(
-        self,
-        keywords: str,
-        run_manager: Optional[AsyncCallbackManagerForToolRun] = None,
-    ) -> list[Document]:
-        return self._run(keywords, run_manager.get_sync())
-
-
-def get_retriever_tool(resources: List[Resource]) -> RetrieverTool | None:
-    if not resources:
-        return None
-    logger.info(f"create retriever tool: {SELECTED_RAG_PROVIDER}")
-    retriever = build_retriever()
-
-    if not retriever:
-        return None
-    return RetrieverTool(retriever=retriever, resources=resources)
-
-
-if __name__ == "__main__":
-    resources = [
-        Resource(
-            uri="rag://dataset/1c7e2ea4362911f09a41c290d4b6a7f0",
-            title="西游记",
-            description="西游记是中国古代四大名著之一，讲述了唐僧师徒四人西天取经的故事。",
-        )
-    ]
-    retriever_tool = get_retriever_tool(resources)
-    print(retriever_tool.name)
-    print(retriever_tool.description)
-    print(retriever_tool.args)
-    print(retriever_tool.invoke("三打白骨精"))

src/tools/search.py

@@ -61,9 +61,5 @@ def get_web_search_tool(max_search_results: int):
 if __name__ == "__main__":
     results = LoggedDuckDuckGoSearch(
         name="web_search", max_results=3, output_format="list"
-    )
-    print(results.name)
-    print(results.description)
-    print(results.args)
-    # .invoke("cute panda")
-    # print(json.dumps(results, indent=2, ensure_ascii=False))
+    ).invoke("cute panda")
+    print(json.dumps(results, indent=2, ensure_ascii=False))

src/tools/tts.py

@@ -102,8 +102,7 @@ class VolcengineTTS:
         }
 
         try:
-            sanitized_text = text.replace("\r\n", "").replace("\n", "")
-            logger.debug(f"Sending TTS request for text: {sanitized_text[:50]}...")
+            logger.debug(f"Sending TTS request for text: {text[:50]}...")
             response = requests.post(
                 self.api_url, json.dumps(request_json), headers=self.header
             )

tests/integration/test_nodes.py

@@ -82,25 +82,27 @@ def test_background_investigation_node_tavily(
         result = background_investigation_node(mock_state, mock_config)
 
         # Verify the result structure
-        assert isinstance(result, dict)
+        assert isinstance(result, Command)
+        assert result.goto == "planner"
 
         # Verify the update contains background_investigation_results
-        assert "background_investigation_results" in result
+        update = result.update
+        assert "background_investigation_results" in update
 
         # Parse and verify the JSON content
-        results = result["background_investigation_results"]
+        results = json.loads(update["background_investigation_results"])
+        assert isinstance(results, list)
 
         if search_engine == SearchEngine.TAVILY.value:
             mock_tavily_search.return_value.invoke.assert_called_once_with("test query")
-            assert (
-                results
-                == "## Test Title 1\n\nTest Content 1\n\n## Test Title 2\n\nTest Content 2"
-            )
+            assert len(results) == 2
+            assert results[0]["title"] == "Test Title 1"
+            assert results[0]["content"] == "Test Content 1"
         else:
             mock_web_search_tool.return_value.invoke.assert_called_once_with(
                 "test query"
             )
-            assert len(json.loads(results)) == 2
+            assert len(results) == 2
 
 
 def test_background_investigation_node_malformed_response(
@@ -114,11 +116,13 @@ def test_background_investigation_node_malformed_response(
         result = background_investigation_node(mock_state, mock_config)
 
         # Verify the result structure
-        assert isinstance(result, dict)
+        assert isinstance(result, Command)
+        assert result.goto == "planner"
 
         # Verify the update contains background_investigation_results
-        assert "background_investigation_results" in result
+        update = result.update
+        assert "background_investigation_results" in update
 
         # Parse and verify the JSON content
-        results = result["background_investigation_results"]
-        assert json.loads(results) is None
+        results = json.loads(update["background_investigation_results"])
+        assert results is None

tests/test_state.py

@@ -14,8 +14,8 @@ class StepType:
 
 
 class Step:
-    def __init__(self, need_search, title, description, step_type):
-        self.need_search = need_search
+    def __init__(self, need_web_search, title, description, step_type):
+        self.need_web_search = need_web_search
         self.title = title
         self.description = description
         self.step_type = step_type
@@ -90,7 +90,7 @@ def test_state_initialization():
 def test_state_with_custom_values():
     """Test that State can be initialized with custom values."""
     test_step = Step(
-        need_search=True,
+        need_web_search=True,
         title="Test Step",
         description="Step description",
         step_type=StepType.RESEARCH,

web/package.json

@@ -6,7 +6,7 @@
   "scripts": {
     "build": "next build",
     "check": "next lint && tsc --noEmit",
-    "dev": "dotenv -e ../.env -- next dev --turbo",
+    "dev": "next dev --turbo",
     "scan": "next dev & npx react-scan@latest localhost:3000",
     "format:check": "prettier --check \"**/*.{ts,tsx,js,jsx,mdx}\" --cache",
     "format:write": "prettier --write \"**/*.{ts,tsx,js,jsx,mdx}\" --cache",
@@ -35,16 +35,12 @@
     "@radix-ui/react-switch": "^1.2.2",
     "@radix-ui/react-tabs": "^1.1.4",
     "@radix-ui/react-tooltip": "^1.2.0",
-    "@rc-component/mentions": "^1.2.0",
     "@t3-oss/env-nextjs": "^0.11.0",
     "@tailwindcss/typography": "^0.5.16",
-    "@tiptap/extension-document": "^2.12.0",
-    "@tiptap/extension-mention": "^2.12.0",
     "@tiptap/extension-table": "^2.11.7",
     "@tiptap/extension-table-cell": "^2.11.7",
     "@tiptap/extension-table-header": "^2.11.7",
     "@tiptap/extension-table-row": "^2.11.7",
-    "@tiptap/extension-text": "^2.12.0",
     "@tiptap/react": "^2.11.7",
     "@xyflow/react": "^12.6.0",
     "best-effort-json-parser": "^1.1.3",
@@ -74,7 +70,6 @@
     "remark-math": "^6.0.0",
     "sonner": "^2.0.3",
     "tailwind-merge": "^3.2.0",
-    "tippy.js": "^6.3.7",
     "tiptap-markdown": "^0.8.10",
     "tw-animate-css": "^1.2.5",
     "unist-util-visit": "^5.0.0",
@@ -91,7 +86,6 @@
     "@types/react": "^19.0.0",
     "@types/react-dom": "^19.0.0",
     "@types/react-syntax-highlighter": "^15.5.13",
-    "dotenv-cli": "^8.0.0",
     "eslint": "^9.23.0",
     "eslint-config-next": "^15.2.3",
     "postcss": "^8.5.3",
@@ -111,4 +105,4 @@
       "sharp"
     ]
   }
-}
+}

web/pnpm-lock.yaml

@@ -62,21 +62,12 @@ importers:
       '@radix-ui/react-tooltip':
         specifier: ^1.2.0
         version: 1.2.0(@types/react-dom@19.1.1(@types/react@19.1.2))(@types/react@19.1.2)(react-dom@19.1.0(react@19.1.0))(react@19.1.0)
-      '@rc-component/mentions':
-        specifier: ^1.2.0
-        version: 1.2.0(react-dom@19.1.0(react@19.1.0))(react@19.1.0)
       '@t3-oss/env-nextjs':
         specifier: ^0.11.0
         version: 0.11.1(typescript@5.8.3)(zod@3.24.3)
       '@tailwindcss/typography':
         specifier: ^0.5.16
         version: 0.5.16(tailwindcss@4.1.4)
-      '@tiptap/extension-document':
-        specifier: ^2.12.0
-        version: 2.12.0(@tiptap/core@2.11.7(@tiptap/pm@2.11.7))
-      '@tiptap/extension-mention':
-        specifier: ^2.12.0
-        version: 2.12.0(@tiptap/core@2.11.7(@tiptap/pm@2.11.7))(@tiptap/pm@2.11.7)(@tiptap/suggestion@2.11.7(@tiptap/core@2.11.7(@tiptap/pm@2.11.7))(@tiptap/pm@2.11.7))
       '@tiptap/extension-table':
         specifier: ^2.11.7
         version: 2.11.7(@tiptap/core@2.11.7(@tiptap/pm@2.11.7))(@tiptap/pm@2.11.7)
@@ -89,9 +80,6 @@ importers:
       '@tiptap/extension-table-row':
         specifier: ^2.11.7
         version: 2.11.7(@tiptap/core@2.11.7(@tiptap/pm@2.11.7))
-      '@tiptap/extension-text':
-        specifier: ^2.12.0
-        version: 2.12.0(@tiptap/core@2.11.7(@tiptap/pm@2.11.7))
       '@tiptap/react':
         specifier: ^2.11.7
         version: 2.11.7(@tiptap/core@2.11.7(@tiptap/pm@2.11.7))(@tiptap/pm@2.11.7)(react-dom@19.1.0(react@19.1.0))(react@19.1.0)
@@ -179,9 +167,6 @@ importers:
       tailwind-merge:
         specifier: ^3.2.0
         version: 3.2.0
-      tippy.js:
-        specifier: ^6.3.7
-        version: 6.3.7
       tiptap-markdown:
         specifier: ^0.8.10
         version: 0.8.10(@tiptap/core@2.11.7(@tiptap/pm@2.11.7))
@@ -225,9 +210,6 @@ importers:
       '@types/react-syntax-highlighter':
         specifier: ^15.5.13
         version: 15.5.13
-      dotenv-cli:
-        specifier: ^8.0.0
-        version: 8.0.0
       eslint:
         specifier: ^9.23.0
         version: 9.24.0(jiti@2.4.2)
@@ -1211,56 +1193,6 @@ packages:
   '@radix-ui/rect@1.1.1':
     resolution: {integrity: sha512-HPwpGIzkl28mWyZqG52jiqDJ12waP11Pa1lGoiyUkIEuMLBP0oeK/C89esbXrxsky5we7dfd8U58nm0SgAWpVw==}
 
-  '@rc-component/input@1.0.1':
-    resolution: {integrity: sha512-omxsjWpB+RamzDDB0NzgV6qI7Ok/U6nrN2KLL/hLZJcI7sZZgLYAN+Xs1pN7OYBnUeyn25PizcntEE0nofHv8Q==}
-    peerDependencies:
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-    engines: {node: '>=12.x'}
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-      react-dom: '>=18.0.0'
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-      react-dom: '>=16.9.0'
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-  '@rc-component/textarea@1.0.0':
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-      react-dom: '>=16.9.0'
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-    engines: {node: '>=8.x'}
-    peerDependencies:
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-      react-dom: '>=18.0.0'
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     peerDependencies:
@@ -1467,8 +1399,8 @@ packages:
       '@tiptap/core': ^2.7.0
       '@tiptap/extension-text-style': ^2.7.0
 
-  '@tiptap/extension-document@2.12.0':
-    resolution: {integrity: sha512-sA1Q+mxDIv0Y3qQTBkYGwknNbDcGFiJ/fyAFholXpqbrcRx3GavwR/o0chBdsJZlFht0x7AWGwUYWvIo7wYilA==}
+  '@tiptap/extension-document@2.11.7':
+    resolution: {integrity: sha512-95ouJXPjdAm9+VBRgFo4lhDoMcHovyl/awORDI8gyEn0Rdglt+ZRZYoySFzbVzer9h0cre+QdIwr9AIzFFbfdA==}
     peerDependencies:
       '@tiptap/core': ^2.7.0
 
@@ -1538,13 +1470,6 @@ packages:
     peerDependencies:
       '@tiptap/core': ^2.7.0
 
-  '@tiptap/extension-mention@2.12.0':
-    resolution: {integrity: sha512-+b/fqOU+pRWWAo0ZfyInkhkvV0Ub5RpNrYZ45v2nn5PjbXbxyxNQ51zT6cGk2F6Jmc6UBmlR8iqqNTIQY9ieEg==}
-    peerDependencies:
-      '@tiptap/core': ^2.7.0
-      '@tiptap/pm': ^2.7.0
-      '@tiptap/suggestion': ^2.7.0
-
   '@tiptap/extension-ordered-list@2.11.7':
     resolution: {integrity: sha512-bLGCHDMB0vbJk7uu8bRg8vES3GsvxkX7Cgjgm/6xysHFbK98y0asDtNxkW1VvuRreNGz4tyB6vkcVCfrxl4jKw==}
     peerDependencies:
@@ -1603,8 +1528,8 @@ packages:
     peerDependencies:
       '@tiptap/core': ^2.7.0
 
-  '@tiptap/extension-text@2.12.0':
-    resolution: {integrity: sha512-0ytN9V1tZYTXdiYDQg4FB2SQ56JAJC9r/65snefb9ztl+gZzDrIvih7CflHs1ic9PgyjexfMLeH+VzuMccNyZw==}
+  '@tiptap/extension-text@2.11.7':
+    resolution: {integrity: sha512-wObCn8qZkIFnXTLvBP+X8KgaEvTap/FJ/i4hBMfHBCKPGDx99KiJU6VIbDXG8d5ZcFZE0tOetK1pP5oI7qgMlQ==}
     peerDependencies:
       '@tiptap/core': ^2.7.0
 
@@ -2296,18 +2221,6 @@ packages:
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     engines: {node: '>=0.10.0'}
 
-  dotenv-cli@8.0.0:
-    resolution: {integrity: sha512-aLqYbK7xKOiTMIRf1lDPbI+Y+Ip/wo5k3eyp6ePysVaSqbyxjyK3dK35BTxG+rmd7djf5q2UPs4noPNH+cj0Qw==}
-    hasBin: true
-
-  dotenv-expand@10.0.0:
-    resolution: {integrity: sha512-GopVGCpVS1UKH75VKHGuQFqS1Gusej0z4FyQkPdwjil2gNIv+LNsqBlboOzpJFZKVT95GkCyWJbBSdFEFUWI2A==}
-    engines: {node: '>=12'}
-
-  dotenv@16.5.0:
-    resolution: {integrity: sha512-m/C+AwOAr9/W1UOIZUo232ejMNnJAJtYQjUbHoNTBNTJSvqzzDh7vnrei3o3r3m9blf6ZoDkvcw0VmozNRFJxg==}
-    engines: {node: '>=12'}
-
   dunder-proto@1.0.1:
     resolution: {integrity: sha512-KIN/nDJBQRcXw0MLVhZE9iQHmG68qAVIBg9CqmUYjmQIhgij9U5MFvrqkUL5FbtyyzZuOeOt0zdeRe4UY7ct+A==}
     engines: {node: '>= 0.4'}
@@ -3607,24 +3520,6 @@ packages:
     peerDependencies:
       webpack: ^4.0.0 || ^5.0.0
 
-  rc-overflow@1.4.1:
-    resolution: {integrity: sha512-3MoPQQPV1uKyOMVNd6SZfONi+f3st0r8PksexIdBTeIYbMX0Jr+k7pHEDvsXtR4BpCv90/Pv2MovVNhktKrwvw==}
-    peerDependencies:
-      react: '>=16.9.0'
-      react-dom: '>=16.9.0'
-
-  rc-resize-observer@1.4.3:
-    resolution: {integrity: sha512-YZLjUbyIWox8E9i9C3Tm7ia+W7euPItNWSPX5sCcQTYbnwDb5uNpnLHQCG1f22oZWUhLw4Mv2tFmeWe68CDQRQ==}
-    peerDependencies:
-      react: '>=16.9.0'
-      react-dom: '>=16.9.0'
-
-  rc-util@5.44.4:
-    resolution: {integrity: sha512-resueRJzmHG9Q6rI/DfK6Kdv9/Lfls05vzMs1Sk3M2P+3cJa+MakaZyWY8IPfehVuhPJFKrIY1IK4GqbiaiY5w==}
-    peerDependencies:
-      react: '>=16.9.0'
-      react-dom: '>=16.9.0'
-
   react-css-styled@1.1.9:
     resolution: {integrity: sha512-M7fJZ3IWFaIHcZEkoFOnkjdiUFmwd8d+gTh2bpqMOcnxy/0Gsykw4dsL4QBiKsxcGow6tETUa4NAUcmJF+/nfw==}
 
@@ -3744,9 +3639,6 @@ packages:
     resolution: {integrity: sha512-Xf0nWe6RseziFMu+Ap9biiUbmplq6S9/p+7w7YXP/JBHhrUDDUhwa+vANyubuqfZWTveU//DYVGsDG7RKL/vEw==}
     engines: {node: '>=0.10.0'}
 
-  resize-observer-polyfill@1.5.1:
-    resolution: {integrity: sha512-LwZrotdHOo12nQuZlHEmtuXdqGoOD0OhaxopaNFxWzInpEgaLWoVuAMbTzixuosCx2nEG58ngzW3vxdWoxIgdg==}
-
   resolve-from@4.0.0:
     resolution: {integrity: sha512-pb/MYmXstAkysRFx8piNI1tGFNQIFA3vkE3Gq4EuA1dF6gHp/+vgZqsCGJapvy8N3Q+4o7FwvquPJcnZ7RYy4g==}
     engines: {node: '>=4'}
@@ -5155,74 +5047,6 @@ snapshots:
 
   '@radix-ui/rect@1.1.1': {}
 
-  '@rc-component/input@1.0.1(react-dom@19.1.0(react@19.1.0))(react@19.1.0)':
-    dependencies:
-      '@rc-component/util': 1.2.1(react-dom@19.1.0(react@19.1.0))(react@19.1.0)
-      classnames: 2.5.1
-      react: 19.1.0
-      react-dom: 19.1.0(react@19.1.0)
-
-  '@rc-component/mentions@1.2.0(react-dom@19.1.0(react@19.1.0))(react@19.1.0)':
-    dependencies:
-      '@rc-component/input': 1.0.1(react-dom@19.1.0(react@19.1.0))(react@19.1.0)
-      '@rc-component/menu': 1.1.3(react-dom@19.1.0(react@19.1.0))(react@19.1.0)
-      '@rc-component/textarea': 1.0.0(react-dom@19.1.0(react@19.1.0))(react@19.1.0)
-      '@rc-component/trigger': 3.4.0(react-dom@19.1.0(react@19.1.0))(react@19.1.0)
-      '@rc-component/util': 1.2.1(react-dom@19.1.0(react@19.1.0))(react@19.1.0)
-      classnames: 2.5.1
-      react: 19.1.0
-      react-dom: 19.1.0(react@19.1.0)
-
-  '@rc-component/menu@1.1.3(react-dom@19.1.0(react@19.1.0))(react@19.1.0)':
-    dependencies:
-      '@rc-component/motion': 1.1.4(react-dom@19.1.0(react@19.1.0))(react@19.1.0)
-      '@rc-component/trigger': 3.4.0(react-dom@19.1.0(react@19.1.0))(react@19.1.0)
-      '@rc-component/util': 1.2.1(react-dom@19.1.0(react@19.1.0))(react@19.1.0)
-      classnames: 2.5.1
-      rc-overflow: 1.4.1(react-dom@19.1.0(react@19.1.0))(react@19.1.0)
-      react: 19.1.0
-      react-dom: 19.1.0(react@19.1.0)
-
-  '@rc-component/motion@1.1.4(react-dom@19.1.0(react@19.1.0))(react@19.1.0)':
-    dependencies:
-      '@rc-component/util': 1.2.1(react-dom@19.1.0(react@19.1.0))(react@19.1.0)
-      classnames: 2.5.1
-      react: 19.1.0
-      react-dom: 19.1.0(react@19.1.0)
-
-  '@rc-component/portal@2.0.0(react-dom@19.1.0(react@19.1.0))(react@19.1.0)':
-    dependencies:
-      '@rc-component/util': 1.2.1(react-dom@19.1.0(react@19.1.0))(react@19.1.0)
-      classnames: 2.5.1
-      react: 19.1.0
-      react-dom: 19.1.0(react@19.1.0)
-
-  '@rc-component/resize-observer@1.0.0(react-dom@19.1.0(react@19.1.0))(react@19.1.0)':
-    dependencies:
-      '@rc-component/util': 1.2.1(react-dom@19.1.0(react@19.1.0))(react@19.1.0)
-      classnames: 2.5.1
-      react: 19.1.0
-      react-dom: 19.1.0(react@19.1.0)
-
-  '@rc-component/textarea@1.0.0(react-dom@19.1.0(react@19.1.0))(react@19.1.0)':
-    dependencies:
-      '@rc-component/input': 1.0.1(react-dom@19.1.0(react@19.1.0))(react@19.1.0)
-      '@rc-component/resize-observer': 1.0.0(react-dom@19.1.0(react@19.1.0))(react@19.1.0)
-      '@rc-component/util': 1.2.1(react-dom@19.1.0(react@19.1.0))(react@19.1.0)
-      classnames: 2.5.1
-      react: 19.1.0
-      react-dom: 19.1.0(react@19.1.0)
-
-  '@rc-component/trigger@3.4.0(react-dom@19.1.0(react@19.1.0))(react@19.1.0)':
-    dependencies:
-      '@rc-component/motion': 1.1.4(react-dom@19.1.0(react@19.1.0))(react@19.1.0)
-      '@rc-component/portal': 2.0.0(react-dom@19.1.0(react@19.1.0))(react@19.1.0)
-      '@rc-component/resize-observer': 1.0.0(react-dom@19.1.0(react@19.1.0))(react@19.1.0)
-      '@rc-component/util': 1.2.1(react-dom@19.1.0(react@19.1.0))(react@19.1.0)
-      classnames: 2.5.1
-      react: 19.1.0
-      react-dom: 19.1.0(react@19.1.0)
-
   '@rc-component/util@1.2.1(react-dom@19.1.0(react@19.1.0))(react@19.1.0)':
     dependencies:
       react: 19.1.0
@@ -5392,7 +5216,7 @@ snapshots:
       '@tiptap/core': 2.11.7(@tiptap/pm@2.11.7)
       '@tiptap/extension-text-style': 2.11.7(@tiptap/core@2.11.7(@tiptap/pm@2.11.7))
 
-  '@tiptap/extension-document@2.12.0(@tiptap/core@2.11.7(@tiptap/pm@2.11.7))':
+  '@tiptap/extension-document@2.11.7(@tiptap/core@2.11.7(@tiptap/pm@2.11.7))':
     dependencies:
       '@tiptap/core': 2.11.7(@tiptap/pm@2.11.7)
 
@@ -5452,12 +5276,6 @@ snapshots:
     dependencies:
       '@tiptap/core': 2.11.7(@tiptap/pm@2.11.7)
 
-  '@tiptap/extension-mention@2.12.0(@tiptap/core@2.11.7(@tiptap/pm@2.11.7))(@tiptap/pm@2.11.7)(@tiptap/suggestion@2.11.7(@tiptap/core@2.11.7(@tiptap/pm@2.11.7))(@tiptap/pm@2.11.7))':
-    dependencies:
-      '@tiptap/core': 2.11.7(@tiptap/pm@2.11.7)
-      '@tiptap/pm': 2.11.7
-      '@tiptap/suggestion': 2.11.7(@tiptap/core@2.11.7(@tiptap/pm@2.11.7))(@tiptap/pm@2.11.7)
-
   '@tiptap/extension-ordered-list@2.11.7(@tiptap/core@2.11.7(@tiptap/pm@2.11.7))':
     dependencies:
       '@tiptap/core': 2.11.7(@tiptap/pm@2.11.7)
@@ -5505,7 +5323,7 @@ snapshots:
     dependencies:
       '@tiptap/core': 2.11.7(@tiptap/pm@2.11.7)
 
-  '@tiptap/extension-text@2.12.0(@tiptap/core@2.11.7(@tiptap/pm@2.11.7))':
+  '@tiptap/extension-text@2.11.7(@tiptap/core@2.11.7(@tiptap/pm@2.11.7))':
     dependencies:
       '@tiptap/core': 2.11.7(@tiptap/pm@2.11.7)
 
@@ -5558,7 +5376,7 @@ snapshots:
       '@tiptap/extension-bullet-list': 2.11.7(@tiptap/core@2.11.7(@tiptap/pm@2.11.7))
       '@tiptap/extension-code': 2.11.7(@tiptap/core@2.11.7(@tiptap/pm@2.11.7))
       '@tiptap/extension-code-block': 2.11.7(@tiptap/core@2.11.7(@tiptap/pm@2.11.7))(@tiptap/pm@2.11.7)
-      '@tiptap/extension-document': 2.12.0(@tiptap/core@2.11.7(@tiptap/pm@2.11.7))
+      '@tiptap/extension-document': 2.11.7(@tiptap/core@2.11.7(@tiptap/pm@2.11.7))
       '@tiptap/extension-dropcursor': 2.11.7(@tiptap/core@2.11.7(@tiptap/pm@2.11.7))(@tiptap/pm@2.11.7)
       '@tiptap/extension-gapcursor': 2.11.7(@tiptap/core@2.11.7(@tiptap/pm@2.11.7))(@tiptap/pm@2.11.7)
       '@tiptap/extension-hard-break': 2.11.7(@tiptap/core@2.11.7(@tiptap/pm@2.11.7))
@@ -5570,7 +5388,7 @@ snapshots:
       '@tiptap/extension-ordered-list': 2.11.7(@tiptap/core@2.11.7(@tiptap/pm@2.11.7))
       '@tiptap/extension-paragraph': 2.11.7(@tiptap/core@2.11.7(@tiptap/pm@2.11.7))
       '@tiptap/extension-strike': 2.11.7(@tiptap/core@2.11.7(@tiptap/pm@2.11.7))
-      '@tiptap/extension-text': 2.12.0(@tiptap/core@2.11.7(@tiptap/pm@2.11.7))
+      '@tiptap/extension-text': 2.11.7(@tiptap/core@2.11.7(@tiptap/pm@2.11.7))
       '@tiptap/extension-text-style': 2.11.7(@tiptap/core@2.11.7(@tiptap/pm@2.11.7))
       '@tiptap/pm': 2.11.7
 
@@ -6288,17 +6106,6 @@ snapshots:
     dependencies:
       esutils: 2.0.3
 
-  dotenv-cli@8.0.0:
-    dependencies:
-      cross-spawn: 7.0.6
-      dotenv: 16.5.0
-      dotenv-expand: 10.0.0
-      minimist: 1.2.8
-
-  dotenv-expand@10.0.0: {}
-
-  dotenv@16.5.0: {}
-
   dunder-proto@1.0.1:
     dependencies:
       call-bind-apply-helpers: 1.0.2
@@ -8009,31 +7816,6 @@ snapshots:
       schema-utils: 3.3.0
       webpack: 5.99.6
 
-  rc-overflow@1.4.1(react-dom@19.1.0(react@19.1.0))(react@19.1.0):
-    dependencies:
-      '@babel/runtime': 7.27.0
-      classnames: 2.5.1
-      rc-resize-observer: 1.4.3(react-dom@19.1.0(react@19.1.0))(react@19.1.0)
-      rc-util: 5.44.4(react-dom@19.1.0(react@19.1.0))(react@19.1.0)
-      react: 19.1.0
-      react-dom: 19.1.0(react@19.1.0)
-
-  rc-resize-observer@1.4.3(react-dom@19.1.0(react@19.1.0))(react@19.1.0):
-    dependencies:
-      '@babel/runtime': 7.27.0
-      classnames: 2.5.1
-      rc-util: 5.44.4(react-dom@19.1.0(react@19.1.0))(react@19.1.0)
-      react: 19.1.0
-      react-dom: 19.1.0(react@19.1.0)
-      resize-observer-polyfill: 1.5.1
-
-  rc-util@5.44.4(react-dom@19.1.0(react@19.1.0))(react@19.1.0):
-    dependencies:
-      '@babel/runtime': 7.27.0
-      react: 19.1.0
-      react-dom: 19.1.0(react@19.1.0)
-      react-is: 18.3.1
-
   react-css-styled@1.1.9:
     dependencies:
       css-styled: 1.0.8
@@ -8238,8 +8020,6 @@ snapshots:
 
   require-from-string@2.0.2: {}
 
-  resize-observer-polyfill@1.5.1: {}
-
   resolve-from@4.0.0: {}
 
   resolve-pkg-maps@1.0.0: {}

web/public/replay/github-top-trending-repo.txt

@@ -23,19 +23,19 @@ event: message_chunk
 data: {"thread_id": "LmC3xxJCFljoFXggnmvst", "agent": "planner", "id": "run-33af75e6-c1b5-4276-9749-7cfb7a967402", "role": "assistant", "content": " reason it's trending, and some key statistics (stars, forks, contributors, etc.).\",\n  \"title\": \"Research Plan: Top Trending GitHub Repository Today"}
 
 event: message_chunk
-data: {"thread_id": "LmC3xxJCFljoFXggnmvst", "agent": "planner", "id": "run-33af75e6-c1b5-4276-9749-7cfb7a967402", "role": "assistant", "content": "\",\n  \"steps\": [\n    {\n      \"need_search\": true,\n      \"title\": \"Identify and Profile the Top Trending Repository\",\n      \"description\": \"Identify the #1 trending repository on"}
+data: {"thread_id": "LmC3xxJCFljoFXggnmvst", "agent": "planner", "id": "run-33af75e6-c1b5-4276-9749-7cfb7a967402", "role": "assistant", "content": "\",\n  \"steps\": [\n    {\n      \"need_web_search\": true,\n      \"title\": \"Identify and Profile the Top Trending Repository\",\n      \"description\": \"Identify the #1 trending repository on"}
 
 event: message_chunk
 data: {"thread_id": "LmC3xxJCFljoFXggnmvst", "agent": "planner", "id": "run-33af75e6-c1b5-4276-9749-7cfb7a967402", "role": "assistant", "content": " GitHub today. Collect the following information: repository name, repository owner/organization, a short description of the repository's purpose, the primary programming language used, and the reason GitHub marks it as trending (e.g., 'X new stars today"}
 
 event: message_chunk
-data: {"thread_id": "LmC3xxJCFljoFXggnmvst", "agent": "planner", "id": "run-33af75e6-c1b5-4276-9749-7cfb7a967402", "role": "assistant", "content": "'). Note: ensure to filter for 'today' to get the current trending repo.\",\n      \"step_type\": \"research\"\n    },\n    {\n      \"need_search\": true,\n      \"title\": \"Gather Repository Statistics and Community Data\",\n      \"description\": \"Collect"}
+data: {"thread_id": "LmC3xxJCFljoFXggnmvst", "agent": "planner", "id": "run-33af75e6-c1b5-4276-9749-7cfb7a967402", "role": "assistant", "content": "'). Note: ensure to filter for 'today' to get the current trending repo.\",\n      \"step_type\": \"research\"\n    },\n    {\n      \"need_web_search\": true,\n      \"title\": \"Gather Repository Statistics and Community Data\",\n      \"description\": \"Collect"}
 
 event: message_chunk
 data: {"thread_id": "LmC3xxJCFljoFXggnmvst", "agent": "planner", "id": "run-33af75e6-c1b5-4276-9749-7cfb7a967402", "role": "assistant", "content": " detailed statistics for the top trending repository. This includes the total number of stars, forks, open issues, closed issues, contributors, and recent commit activity. Also, gather data about the community's involvement, such as the number of active contributors in the last month, and any available information on significant discussions or contributions happening"}
 
 event: message_chunk
-data: {"thread_id": "LmC3xxJCFljoFXggnmvst", "agent": "planner", "id": "run-33af75e6-c1b5-4276-9749-7cfb7a967402", "role": "assistant", "content": " within the project. Check for recent release notes or announcements.\",\n      \"step_type\": \"research\"\n    },\n    {\n      \"need_search\": true,\n      \"title\": \"Determine Context and Significance\",\n      \"description\": \"Research the broader context and significance of the trending"}
+data: {"thread_id": "LmC3xxJCFljoFXggnmvst", "agent": "planner", "id": "run-33af75e6-c1b5-4276-9749-7cfb7a967402", "role": "assistant", "content": " within the project. Check for recent release notes or announcements.\",\n      \"step_type\": \"research\"\n    },\n    {\n      \"need_web_search\": true,\n      \"title\": \"Determine Context and Significance\",\n      \"description\": \"Research the broader context and significance of the trending"}
 
 event: message_chunk
 data: {"thread_id": "LmC3xxJCFljoFXggnmvst", "agent": "planner", "id": "run-33af75e6-c1b5-4276-9749-7cfb7a967402", "role": "assistant", "content": " repository. Determine the repository's purpose or function. Investigate the project's background, the problem it solves, or the features it provides. Identify the industry, user base, or application area it serves. Search for recent news, articles, or blog posts mentioning the repository and its impact or potential. Identify its license"}

web/public/replay/nanjing-traditional-dishes.txt

@@ -20,16 +20,16 @@ event: message_chunk
 data: {"thread_id": "PDgExJb-Qsq2fNtO4B_sZ", "agent": "planner", "id": "run-f9561a11-723f-4d5f-917c-95f96601f87f", "role": "assistant", "content": " culinary scene and document its traditional dishes. I will create comprehensive steps to gather the most important data and create a good final report.\",\n  \"title\": \"Research"}
 
 event: message_chunk
-data: {"thread_id": "PDgExJb-Qsq2fNtO4B_sZ", "agent": "planner", "id": "run-f9561a11-723f-4d5f-917c-95f96601f87f", "role": "assistant", "content": " Plan: Nanjing's Culinary Scene and Traditional Dishes\",\n  \"steps\": [\n    {\n      \"need_search\": true,\n      "}
+data: {"thread_id": "PDgExJb-Qsq2fNtO4B_sZ", "agent": "planner", "id": "run-f9561a11-723f-4d5f-917c-95f96601f87f", "role": "assistant", "content": " Plan: Nanjing's Culinary Scene and Traditional Dishes\",\n  \"steps\": [\n    {\n      \"need_web_search\": true,\n      "}
 
 event: message_chunk
 data: {"thread_id": "PDgExJb-Qsq2fNtO4B_sZ", "agent": "planner", "id": "run-f9561a11-723f-4d5f-917c-95f96601f87f", "role": "assistant", "content": "\"title\": \"Identify and Document Key Traditional Nanjing Dishes\",\n      \"description\": \"Research and compile a comprehensive list of traditional Nanjing dishes, including their names (in both English and Chinese), detailed descriptions of ingredients and preparation methods, and historical origins"}
 
 event: message_chunk
-data: {"thread_id": "PDgExJb-Qsq2fNtO4B_sZ", "agent": "planner", "id": "run-f9561a11-723f-4d5f-917c-95f96601f87f", "role": "assistant", "content": ". Identify dishes that are representative of Nanjing's culinary heritage and those that are less well-known but still significant. Document the specific cooking techniques that characterize Nanjing cuisine.\",\n      \"step_type\": \"research\"\n    },\n    {\n      \"need_search\": true,\n      \"title\": \"Investigate the History and Cultural Significance of Nanjing Cuisine\",\n      \"description\": \"Explore the historical influences that have shaped Nanjing's culinary traditions, including its role as a former capital city. Document the cultural significance of specific dishes and"}
+data: {"thread_id": "PDgExJb-Qsq2fNtO4B_sZ", "agent": "planner", "id": "run-f9561a11-723f-4d5f-917c-95f96601f87f", "role": "assistant", "content": ". Identify dishes that are representative of Nanjing's culinary heritage and those that are less well-known but still significant. Document the specific cooking techniques that characterize Nanjing cuisine.\",\n      \"step_type\": \"research\"\n    },\n    {\n      \"need_web_search\": true,\n      \"title\": \"Investigate the History and Cultural Significance of Nanjing Cuisine\",\n      \"description\": \"Explore the historical influences that have shaped Nanjing's culinary traditions, including its role as a former capital city. Document the cultural significance of specific dishes and"}
 
 event: message_chunk
-data: {"thread_id": "PDgExJb-Qsq2fNtO4B_sZ", "agent": "planner", "id": "run-f9561a11-723f-4d5f-917c-95f96601f87f", "role": "assistant", "content": " their connection to local customs, festivals, and celebrations. Research the evolution of Nanjing cuisine over time, identifying key periods of change and the factors that contributed to them.\",\n      \"step_type\": \"research\"\n    },\n    {\n      \"need_search\": true,\n      \"title\":"}
+data: {"thread_id": "PDgExJb-Qsq2fNtO4B_sZ", "agent": "planner", "id": "run-f9561a11-723f-4d5f-917c-95f96601f87f", "role": "assistant", "content": " their connection to local customs, festivals, and celebrations. Research the evolution of Nanjing cuisine over time, identifying key periods of change and the factors that contributed to them.\",\n      \"step_type\": \"research\"\n    },\n    {\n      \"need_web_search\": true,\n      \"title\":"}
 
 event: message_chunk
 data: {"thread_id": "PDgExJb-Qsq2fNtO4B_sZ", "agent": "planner", "id": "run-f9561a11-723f-4d5f-917c-95f96601f87f", "role": "assistant", "content": " \"Analyze the Current State of Nanjing's Culinary Scene and Identify Key Restaurants\",\n      \"description\": \"Investigate the current state of Nanjing's culinary scene, identifying key restaurants that specialize in traditional Nanjing cuisine. Gather information on their menus, pricing, and customer reviews. Document any trends or changes in the local food"}

web/public/replay/rental-apartment-decoration.txt

@@ -83,7 +83,7 @@ event: message_chunk
 data: {"thread_id": "5CG_qm7snTVKbpVCrWTon", "agent": "planner", "id": "run-3006007c-5c06-4500-ba23-3fab94c70ae7", "role": "assistant", "content": "\": [\n    {\n      \""}
 
 event: message_chunk
-data: {"thread_id": "5CG_qm7snTVKbpVCrWTon", "agent": "planner", "id": "run-3006007c-5c06-4500-ba23-3fab94c70ae7", "role": "assistant", "content": "need_search\":"}
+data: {"thread_id": "5CG_qm7snTVKbpVCrWTon", "agent": "planner", "id": "run-3006007c-5c06-4500-ba23-3fab94c70ae7", "role": "assistant", "content": "need_web_search\":"}
 
 event: message_chunk
 data: {"thread_id": "5CG_qm7snTVKbpVCrWTon", "agent": "planner", "id": "run-3006007c-5c06-4500-ba23-3fab94c70ae7", "role": "assistant", "content": " true,\n      \""}
@@ -134,7 +134,7 @@ event: message_chunk
 data: {"thread_id": "5CG_qm7snTVKbpVCrWTon", "agent": "planner", "id": "run-3006007c-5c06-4500-ba23-3fab94c70ae7", "role": "assistant", "content": "    {\n      \""}
 
 event: message_chunk
-data: {"thread_id": "5CG_qm7snTVKbpVCrWTon", "agent": "planner", "id": "run-3006007c-5c06-4500-ba23-3fab94c70ae7", "role": "assistant", "content": "need_search\":"}
+data: {"thread_id": "5CG_qm7snTVKbpVCrWTon", "agent": "planner", "id": "run-3006007c-5c06-4500-ba23-3fab94c70ae7", "role": "assistant", "content": "need_web_search\":"}
 
 event: message_chunk
 data: {"thread_id": "5CG_qm7snTVKbpVCrWTon", "agent": "planner", "id": "run-3006007c-5c06-4500-ba23-3fab94c70ae7", "role": "assistant", "content": " true,\n      \"title"}
@@ -194,7 +194,7 @@ event: message_chunk
 data: {"thread_id": "5CG_qm7snTVKbpVCrWTon", "agent": "planner", "id": "run-3006007c-5c06-4500-ba23-3fab94c70ae7", "role": "assistant", "content": "\"\n    },\n    {\n      \""}
 
 event: message_chunk
-data: {"thread_id": "5CG_qm7snTVKbpVCrWTon", "agent": "planner", "id": "run-3006007c-5c06-4500-ba23-3fab94c70ae7", "role": "assistant", "content": "need_search\":"}
+data: {"thread_id": "5CG_qm7snTVKbpVCrWTon", "agent": "planner", "id": "run-3006007c-5c06-4500-ba23-3fab94c70ae7", "role": "assistant", "content": "need_web_search\":"}
 
 event: message_chunk
 data: {"thread_id": "5CG_qm7snTVKbpVCrWTon", "agent": "planner", "id": "run-3006007c-5c06-4500-ba23-3fab94c70ae7", "role": "assistant", "content": " true,\n      \"title"}

web/public/replay/review-of-the-professional.txt

@@ -140,7 +140,7 @@ event: message_chunk
 data: {"thread_id": "01uPkjxNhUsYZHQ1DrkhK", "agent": "planner", "id": "run-77b32288-ec82-4b8e-b815-d403687915bd", "role": "assistant", "content": "research\"\n    },\n    {\n"}
 
 event: message_chunk
-data: {"thread_id": "01uPkjxNhUsYZHQ1DrkhK", "agent": "planner", "id": "run-77b32288-ec82-4b8e-b815-d403687915bd", "role": "assistant", "content": "      \"need_search\":"}
+data: {"thread_id": "01uPkjxNhUsYZHQ1DrkhK", "agent": "planner", "id": "run-77b32288-ec82-4b8e-b815-d403687915bd", "role": "assistant", "content": "      \"need_web_search\":"}
 
 event: message_chunk
 data: {"thread_id": "01uPkjxNhUsYZHQ1DrkhK", "agent": "planner", "id": "run-77b32288-ec82-4b8e-b815-d403687915bd", "role": "assistant", "content": " true,\n      \"title"}
@@ -200,7 +200,7 @@ event: message_chunk
 data: {"thread_id": "01uPkjxNhUsYZHQ1DrkhK", "agent": "planner", "id": "run-77b32288-ec82-4b8e-b815-d403687915bd", "role": "assistant", "content": "research\"\n    },\n    {\n"}
 
 event: message_chunk
-data: {"thread_id": "01uPkjxNhUsYZHQ1DrkhK", "agent": "planner", "id": "run-77b32288-ec82-4b8e-b815-d403687915bd", "role": "assistant", "content": "      \"need_search\":"}
+data: {"thread_id": "01uPkjxNhUsYZHQ1DrkhK", "agent": "planner", "id": "run-77b32288-ec82-4b8e-b815-d403687915bd", "role": "assistant", "content": "      \"need_web_search\":"}
 
 event: message_chunk
 data: {"thread_id": "01uPkjxNhUsYZHQ1DrkhK", "agent": "planner", "id": "run-77b32288-ec82-4b8e-b815-d403687915bd", "role": "assistant", "content": " true,\n      \"title"}

web/src/app/chat/components/input-box.tsx

@@ -3,15 +3,18 @@
 
 import { AnimatePresence, motion } from "framer-motion";
 import { ArrowUp, X } from "lucide-react";
-import { useCallback, useRef } from "react";
+import {
+  type KeyboardEvent,
+  useCallback,
+  useEffect,
+  useRef,
+  useState,
+} from "react";
 
 import { Detective } from "~/components/deer-flow/icons/detective";
-import MessageInput, {
-  type MessageInputRef,
-} from "~/components/deer-flow/message-input";
 import { Tooltip } from "~/components/deer-flow/tooltip";
 import { Button } from "~/components/ui/button";
-import type { Option, Resource } from "~/core/messages";
+import type { Option } from "~/core/messages";
 import {
   setEnableBackgroundInvestigation,
   useSettingsStore,
@@ -20,6 +23,7 @@ import { cn } from "~/lib/utils";
 
 export function InputBox({
   className,
+  size,
   responding,
   feedback,
   onSend,
@@ -30,57 +34,78 @@ export function InputBox({
   size?: "large" | "normal";
   responding?: boolean;
   feedback?: { option: Option } | null;
-  onSend?: (
-    message: string,
-    options?: {
-      interruptFeedback?: string;
-      resources?: Array<Resource>;
-    },
-  ) => void;
+  onSend?: (message: string, options?: { interruptFeedback?: string }) => void;
   onCancel?: () => void;
   onRemoveFeedback?: () => void;
 }) {
+  const [message, setMessage] = useState("");
+  const [imeStatus, setImeStatus] = useState<"active" | "inactive">("inactive");
+  const [indent, setIndent] = useState(0);
   const backgroundInvestigation = useSettingsStore(
     (state) => state.general.enableBackgroundInvestigation,
   );
-  const containerRef = useRef<HTMLDivElement>(null);
-  const inputRef = useRef<MessageInputRef>(null);
+  const textareaRef = useRef<HTMLTextAreaElement>(null);
   const feedbackRef = useRef<HTMLDivElement>(null);
 
-  const handleSendMessage = useCallback(
-    (message: string, resources: Array<Resource>) => {
+  useEffect(() => {
+    if (feedback) {
+      setMessage("");
+
+      setTimeout(() => {
+        if (feedbackRef.current) {
+          setIndent(feedbackRef.current.offsetWidth);
+        }
+      }, 200);
+    }
+    setTimeout(() => {
+      textareaRef.current?.focus();
+    }, 0);
+  }, [feedback]);
+
+  const handleSendMessage = useCallback(() => {
+    if (responding) {
+      onCancel?.();
+    } else {
+      if (message.trim() === "") {
+        return;
+      }
+      if (onSend) {
+        onSend(message, {
+          interruptFeedback: feedback?.option.value,
+        });
+        setMessage("");
+        onRemoveFeedback?.();
+      }
+    }
+  }, [responding, onCancel, message, onSend, feedback, onRemoveFeedback]);
+
+  const handleKeyDown = useCallback(
+    (event: KeyboardEvent<HTMLTextAreaElement>) => {
       if (responding) {
-        onCancel?.();
-      } else {
-        if (message.trim() === "") {
-          return;
-        }
-        if (onSend) {
-          onSend(message, {
-            interruptFeedback: feedback?.option.value,
-            resources,
-          });
-          onRemoveFeedback?.();
-        }
+        return;
+      }
+      if (
+        event.key === "Enter" &&
+        !event.shiftKey &&
+        !event.metaKey &&
+        !event.ctrlKey &&
+        imeStatus === "inactive"
+      ) {
+        event.preventDefault();
+        handleSendMessage();
       }
     },
-    [responding, onCancel, onSend, feedback, onRemoveFeedback],
+    [responding, imeStatus, handleSendMessage],
   );
 
   return (
-    <div
-      className={cn(
-        "bg-card relative flex h-full w-full flex-col rounded-[24px] border",
-        className,
-      )}
-      ref={containerRef}
-    >
+    <div className={cn("bg-card relative rounded-[24px] border", className)}>
       <div className="w-full">
         <AnimatePresence>
           {feedback && (
             <motion.div
               ref={feedbackRef}
-              className="bg-background border-brand absolute top-0 left-0 mt-2 ml-4 flex items-center justify-center gap-1 rounded-2xl border px-2 py-0.5"
+              className="bg-background border-brand absolute top-0 left-0 mt-3 ml-2 flex items-center justify-center gap-1 rounded-2xl border px-2 py-0.5"
               initial={{ opacity: 0, scale: 0 }}
               animate={{ opacity: 1, scale: 1 }}
               exit={{ opacity: 0, scale: 0 }}
@@ -97,10 +122,25 @@ export function InputBox({
             </motion.div>
           )}
         </AnimatePresence>
-        <MessageInput
-          className={cn("h-24 px-4 pt-5", feedback && "pt-9")}
-          ref={inputRef}
-          onEnter={handleSendMessage}
+        <textarea
+          ref={textareaRef}
+          className={cn(
+            "m-0 w-full resize-none border-none px-4 py-3 text-lg",
+            size === "large" ? "min-h-32" : "min-h-4",
+          )}
+          style={{ textIndent: feedback ? `${indent}px` : 0 }}
+          placeholder={
+            feedback
+              ? `Describe how you ${feedback.option.text.toLocaleLowerCase()}?`
+              : "What can I do for you?"
+          }
+          value={message}
+          onCompositionStart={() => setImeStatus("active")}
+          onCompositionEnd={() => setImeStatus("inactive")}
+          onKeyDown={handleKeyDown}
+          onChange={(event) => {
+            setMessage(event.target.value);
+          }}
         />
       </div>
       <div className="flex items-center px-4 py-2">
@@ -126,6 +166,7 @@ export function InputBox({
                 backgroundInvestigation && "!border-brand !text-brand",
               )}
               variant="outline"
+              size="lg"
               onClick={() =>
                 setEnableBackgroundInvestigation(!backgroundInvestigation)
               }
@@ -140,7 +181,7 @@ export function InputBox({
               variant="outline"
               size="icon"
               className={cn("h-10 w-10 rounded-full")}
-              onClick={() => inputRef.current?.submit()}
+              onClick={handleSendMessage}
             >
               {responding ? (
                 <div className="flex h-10 w-10 items-center justify-center">

web/src/app/chat/components/message-list-view.tsx

@@ -173,15 +173,8 @@ function MessageListItem({
             )}
           >
             <MessageBubble message={message}>
-              <div className="flex w-full flex-col text-wrap break-words">
-                <Markdown
-                  className={cn(
-                    message.role === "user" &&
-                      "prose-invert not-dark:text-secondary dark:text-inherit",
-                  )}
-                >
-                  {message?.content}
-                </Markdown>
+              <div className="flex w-full flex-col">
+                <Markdown>{message?.content}</Markdown>
               </div>
             </MessageBubble>
           </div>
@@ -221,8 +214,9 @@ function MessageBubble({
   return (
     <div
       className={cn(
-        `group flex w-fit max-w-[85%] flex-col rounded-2xl px-4 py-3 text-nowrap shadow`,
-        message.role === "user" && "bg-brand rounded-ee-none",
+        `flex w-fit max-w-[85%] flex-col rounded-2xl px-4 py-3 shadow`,
+        message.role === "user" &&
+          "text-primary-foreground bg-brand rounded-ee-none",
         message.role === "assistant" && "bg-card rounded-es-none",
         className,
       )}

web/src/app/chat/components/messages-block.tsx

@@ -15,7 +15,7 @@ import {
 } from "~/components/ui/card";
 import { fastForwardReplay } from "~/core/api";
 import { useReplayMetadata } from "~/core/api/hooks";
-import type { Option, Resource } from "~/core/messages";
+import type { Option } from "~/core/messages";
 import { useReplay } from "~/core/replay";
 import { sendMessage, useMessageIds, useStore } from "~/core/store";
 import { env } from "~/env";
@@ -36,13 +36,7 @@ export function MessagesBlock({ className }: { className?: string }) {
   const abortControllerRef = useRef<AbortController | null>(null);
   const [feedback, setFeedback] = useState<{ option: Option } | null>(null);
   const handleSend = useCallback(
-    async (
-      message: string,
-      options?: {
-        interruptFeedback?: string;
-        resources?: Array<Resource>;
-      },
-    ) => {
+    async (message: string, options?: { interruptFeedback?: string }) => {
       const abortController = new AbortController();
       abortControllerRef.current = abortController;
       try {
@@ -51,7 +45,6 @@ export function MessagesBlock({ className }: { className?: string }) {
           {
             interruptFeedback:
               options?.interruptFeedback ?? feedback?.option.value,
-            resources: options?.resources,
           },
           {
             abortSignal: abortController.signal,
@@ -130,26 +123,8 @@ export function MessagesBlock({ className }: { className?: string }) {
               )}
             >
               <div className="flex items-center justify-between">
-                <div className="flex flex-grow items-center">
-                  {responding && (
-                    <motion.div
-                      className="ml-3"
-                      initial={{ opacity: 0, scale: 0.8 }}
-                      animate={{ opacity: 1, scale: 1 }}
-                      exit={{ opacity: 0, scale: 0.8 }}
-                      transition={{ duration: 0.3 }}
-                    >
-                      <video
-                        // Walking deer animation, designed by @liangzhaojun. Thank you for creating it!
-                        src="/images/walking_deer.webm"
-                        autoPlay
-                        loop
-                        muted
-                        className="h-[42px] w-[42px] object-contain"
-                      />
-                    </motion.div>
-                  )}
-                  <CardHeader className={cn("flex-grow", responding && "pl-3")}>
+                <div className="flex-grow">
+                  <CardHeader>
                     <CardTitle>
                       <RainbowText animated={responding}>
                         {responding ? "Replaying" : `${replayTitle}`}

web/src/app/chat/components/research-activities-block.tsx

@@ -4,7 +4,7 @@
 import { PythonOutlined } from "@ant-design/icons";
 import { motion } from "framer-motion";
 import { LRUCache } from "lru-cache";
-import { BookOpenText, FileText, PencilRuler, Search } from "lucide-react";
+import { BookOpenText, PencilRuler, Search } from "lucide-react";
 import { useTheme } from "next-themes";
 import { useMemo } from "react";
 import SyntaxHighlighter from "react-syntax-highlighter";
@@ -96,8 +96,6 @@ function ActivityListItem({ messageId }: { messageId: string }) {
           return <CrawlToolCall key={toolCall.id} toolCall={toolCall} />;
         } else if (toolCall.name === "python_repl_tool") {
           return <PythonToolCall key={toolCall.id} toolCall={toolCall} />;
-        } else if (toolCall.name === "local_search_tool") {
-          return <RetrieverToolCall key={toolCall.id} toolCall={toolCall} />;
         } else {
           return <MCPToolCall key={toolCall.id} toolCall={toolCall} />;
         }
@@ -120,7 +118,6 @@ type SearchResult =
       image_url: string;
       image_description: string;
     };
-
 function WebSearchToolCall({ toolCall }: { toolCall: ToolCallRuntime }) {
   const searching = useMemo(() => {
     return toolCall.result === undefined;
@@ -278,67 +275,9 @@ function CrawlToolCall({ toolCall }: { toolCall: ToolCallRuntime }) {
   );
 }
 
-function RetrieverToolCall({ toolCall }: { toolCall: ToolCallRuntime }) {
-  const searching = useMemo(() => {
-    return toolCall.result === undefined;
-  }, [toolCall.result]);
-  const documents = useMemo<
-    Array<{ id: string; title: string; content: string }>
-  >(() => {
-    return toolCall.result ? parseJSON(toolCall.result, []) : [];
-  }, [toolCall.result]);
-  return (
-    <section className="mt-4 pl-4">
-      <div className="font-medium italic">
-        <RainbowText className="flex items-center" animated={searching}>
-          <Search size={16} className={"mr-2"} />
-          <span>Retrieving documents from RAG&nbsp;</span>
-          <span className="max-w-[500px] overflow-hidden text-ellipsis whitespace-nowrap">
-            {(toolCall.args as { keywords: string }).keywords}
-          </span>
-        </RainbowText>
-      </div>
-      <div className="pr-4">
-        {documents && (
-          <ul className="mt-2 flex flex-wrap gap-4">
-            {searching &&
-              [...Array(2)].map((_, i) => (
-                <li
-                  key={`search-result-${i}`}
-                  className="flex h-40 w-40 gap-2 rounded-md text-sm"
-                >
-                  <Skeleton
-                    className="to-accent h-full w-full rounded-md bg-gradient-to-tl from-slate-400"
-                    style={{ animationDelay: `${i * 0.2}s` }}
-                  />
-                </li>
-              ))}
-            {documents.map((doc, i) => (
-              <motion.li
-                key={`search-result-${i}`}
-                className="text-muted-foreground bg-accent flex max-w-40 gap-2 rounded-md px-2 py-1 text-sm"
-                initial={{ opacity: 0, y: 10, scale: 0.66 }}
-                animate={{ opacity: 1, y: 0, scale: 1 }}
-                transition={{
-                  duration: 0.2,
-                  delay: i * 0.1,
-                  ease: "easeOut",
-                }}
-              >
-                <FileText size={32} />
-                {doc.title}
-              </motion.li>
-            ))}
-          </ul>
-        )}
-      </div>
-    </section>
-  );
-}
-
 function PythonToolCall({ toolCall }: { toolCall: ToolCallRuntime }) {
-  const code = useMemo<string | undefined>(() => {
-    return (toolCall.args as { code?: string }).code;
+  const code = useMemo<string>(() => {
+    return (toolCall.args as { code: string }).code;
   }, [toolCall.args]);
   const { resolvedTheme } = useTheme();
   return (
@@ -363,7 +302,7 @@ function PythonToolCall({ toolCall }: { toolCall: ToolCallRuntime }) {
               boxShadow: "none",
             }}
           >
-            {code?.trim() ?? ""}
+            {code.trim()}
           </SyntaxHighlighter>
         </div>
       </div>

web/src/app/chat/components/research-report-block.tsx

@@ -53,7 +53,10 @@ export function ResearchReportBlock({
   // }, [isCompleted]);
 
   return (
-    <div ref={contentRef} className={cn("w-full pt-4 pb-8", className)}>
+    <div
+      ref={contentRef}
+      className={cn("relative flex flex-col pt-4 pb-8", className)}
+    >
       {!isReplay && isCompleted && editing ? (
         <ReportEditor
           content={message?.content}

web/src/components/deer-flow/link.tsx

@@ -37,7 +37,7 @@ export const Link = ({
   }, [credibleLinks, href, responding, checkLinkCredibility]);
 
   return (
-    <span className="inline-flex items-center gap-1.5">
+    <span className="flex items-center gap-1.5">
       <a href={href} target="_blank" rel="noopener noreferrer">
         {children}
       </a>

web/src/components/deer-flow/message-input.tsx

@@ -1,211 +0,0 @@
-// Copyright (c) 2025 Bytedance Ltd. and/or its affiliates
-// SPDX-License-Identifier: MIT
-
-"use client";
-
-import Mention from "@tiptap/extension-mention";
-import { Editor, Extension, type Content } from "@tiptap/react";
-import {
-  EditorContent,
-  type EditorInstance,
-  EditorRoot,
-  type JSONContent,
-  StarterKit,
-  Placeholder,
-} from "novel";
-import { Markdown } from "tiptap-markdown";
-import { useDebouncedCallback } from "use-debounce";
-
-import "~/styles/prosemirror.css";
-import { resourceSuggestion } from "./resource-suggestion";
-import React, { forwardRef, useEffect, useMemo, useRef } from "react";
-import type { Resource } from "~/core/messages";
-import { useRAGProvider } from "~/core/api/hooks";
-import { LoadingOutlined } from "@ant-design/icons";
-
-export interface MessageInputRef {
-  focus: () => void;
-  submit: () => void;
-}
-
-export interface MessageInputProps {
-  className?: string;
-  placeholder?: string;
-  onChange?: (markdown: string) => void;
-  onEnter?: (message: string, resources: Array<Resource>) => void;
-}
-
-function formatMessage(content: JSONContent) {
-  if (content.content) {
-    const output: {
-      text: string;
-      resources: Array<Resource>;
-    } = {
-      text: "",
-      resources: [],
-    };
-    for (const node of content.content) {
-      const { text, resources } = formatMessage(node);
-      output.text += text;
-      output.resources.push(...resources);
-    }
-    return output;
-  } else {
-    return formatItem(content);
-  }
-}
-
-function formatItem(item: JSONContent): {
-  text: string;
-  resources: Array<Resource>;
-} {
-  if (item.type === "text") {
-    return { text: item.text ?? "", resources: [] };
-  }
-  if (item.type === "mention") {
-    return {
-      text: `[${item.attrs?.label}](${item.attrs?.id})`,
-      resources: [
-        { uri: item.attrs?.id ?? "", title: item.attrs?.label ?? "" },
-      ],
-    };
-  }
-  return { text: "", resources: [] };
-}
-
-const MessageInput = forwardRef<MessageInputRef, MessageInputProps>(
-  ({ className, onChange, onEnter }: MessageInputProps, ref) => {
-    const editorRef = useRef<Editor>(null);
-    const handleEnterRef = useRef<
-      ((message: string, resources: Array<Resource>) => void) | undefined
-    >(onEnter);
-    const debouncedUpdates = useDebouncedCallback(
-      async (editor: EditorInstance) => {
-        if (onChange) {
-          const markdown = editor.storage.markdown.getMarkdown();
-          onChange(markdown);
-        }
-      },
-      200,
-    );
-
-    React.useImperativeHandle(ref, () => ({
-      focus: () => {
-        editorRef.current?.view.focus();
-      },
-      submit: () => {
-        if (onEnter) {
-          const { text, resources } = formatMessage(
-            editorRef.current?.getJSON() ?? [],
-          );
-          onEnter(text, resources);
-        }
-      },
-    }));
-
-    useEffect(() => {
-      handleEnterRef.current = onEnter;
-    }, [onEnter]);
-
-    const { provider, loading } = useRAGProvider();
-
-    const extensions = useMemo(() => {
-      const extensions = [
-        StarterKit,
-        Markdown.configure({
-          html: true,
-          tightLists: true,
-          tightListClass: "tight",
-          bulletListMarker: "-",
-          linkify: false,
-          breaks: false,
-          transformPastedText: false,
-          transformCopiedText: false,
-        }),
-        Placeholder.configure({
-          showOnlyCurrent: false,
-          placeholder: provider
-            ? "What can I do for you? \nYou may refer to RAG resources by using @."
-            : "What can I do for you?",
-          emptyEditorClass: "placeholder",
-        }),
-        Extension.create({
-          name: "keyboardHandler",
-          addKeyboardShortcuts() {
-            return {
-              Enter: () => {
-                if (handleEnterRef.current) {
-                  const { text, resources } = formatMessage(
-                    this.editor.getJSON() ?? [],
-                  );
-                  handleEnterRef.current(text, resources);
-                }
-                return this.editor.commands.clearContent();
-              },
-            };
-          },
-        }),
-      ];
-      if (provider) {
-        extensions.push(
-          Mention.configure({
-            HTMLAttributes: {
-              class: "mention",
-            },
-            suggestion: resourceSuggestion,
-          }) as Extension,
-        );
-      }
-      return extensions;
-    }, [provider]);
-
-    if (loading) {
-      return (
-        <div className={className}>
-          <LoadingOutlined />
-        </div>
-      );
-    }
-
-    return (
-      <div className={className}>
-        <EditorRoot>
-          <EditorContent
-            immediatelyRender={false}
-            extensions={extensions}
-            className="border-muted h-full w-full overflow-auto"
-            editorProps={{
-              attributes: {
-                class:
-                  "prose prose-base dark:prose-invert inline-editor font-default focus:outline-none max-w-full",
-              },
-              transformPastedHTML: transformPastedHTML,
-            }}
-            onCreate={({ editor }) => {
-              editorRef.current = editor;
-            }}
-            onUpdate={({ editor }) => {
-              debouncedUpdates(editor);
-            }}
-          ></EditorContent>
-        </EditorRoot>
-      </div>
-    );
-  },
-);
-
-function transformPastedHTML(html: string) {
-  try {
-    // Strip HTML from user-pasted content
-    const tempEl = document.createElement("div");
-    tempEl.innerHTML = html;
-
-    return tempEl.textContent || tempEl.innerText || "";
-  } catch (error) {
-    console.error("Error transforming pasted HTML", error);
-
-    return "";
-  }
-}
-
-export default MessageInput;

web/src/components/deer-flow/resource-mentions.tsx

@@ -1,87 +0,0 @@
-// Copyright (c) 2025 Bytedance Ltd. and/or its affiliates
-// SPDX-License-Identifier: MIT
-
-import { forwardRef, useEffect, useImperativeHandle, useState } from "react";
-import type { Resource } from "~/core/messages";
-import { cn } from "~/lib/utils";
-
-export interface ResourceMentionsProps {
-  items: Array<Resource>;
-  command: (item: { id: string; label: string }) => void;
-}
-
-export const ResourceMentions = forwardRef<
-  { onKeyDown: (args: { event: KeyboardEvent }) => boolean },
-  ResourceMentionsProps
->((props, ref) => {
-  const [selectedIndex, setSelectedIndex] = useState(0);
-
-  const selectItem = (index: number) => {
-    const item = props.items[index];
-
-    if (item) {
-      props.command({ id: item.uri, label: item.title });
-    }
-  };
-
-  const upHandler = () => {
-    setSelectedIndex(
-      (selectedIndex + props.items.length - 1) % props.items.length,
-    );
-  };
-
-  const downHandler = () => {
-    setSelectedIndex((selectedIndex + 1) % props.items.length);
-  };
-
-  const enterHandler = () => {
-    selectItem(selectedIndex);
-  };
-
-  useEffect(() => setSelectedIndex(0), [props.items]);
-
-  useImperativeHandle(ref, () => ({
-    onKeyDown: ({ event }) => {
-      if (event.key === "ArrowUp") {
-        upHandler();
-        return true;
-      }
-
-      if (event.key === "ArrowDown") {
-        downHandler();
-        return true;
-      }
-
-      if (event.key === "Enter") {
-        enterHandler();
-        return true;
-      }
-
-      return false;
-    },
-  }));
-
-  return (
-    <div className="bg-card border-var(--border) relative flex flex-col gap-1 overflow-auto rounded-md border p-2 shadow">
-      {props.items.length ? (
-        props.items.map((item, index) => (
-          <button
-            className={cn(
-              "focus-visible:ring-ring hover:bg-accent hover:text-accent-foreground inline-flex h-9 w-full items-center justify-start gap-2 rounded-md px-4 py-2 text-sm whitespace-nowrap transition-colors focus-visible:ring-1 focus-visible:outline-none disabled:pointer-events-none disabled:opacity-50 [&_svg]:pointer-events-none [&_svg]:size-4 [&_svg]:shrink-0",
-              selectedIndex === index &&
-                "bg-secondary text-secondary-foreground",
-            )}
-            key={index}
-            onClick={() => selectItem(index)}
-          >
-            {item.title}
-          </button>
-        ))
-      ) : (
-        <div className="items-center justify-center text-gray-500">
-          No result
-        </div>
-      )}
-    </div>
-  );
-});

web/src/components/deer-flow/resource-suggestion.tsx

@@ -1,86 +0,0 @@
-// Copyright (c) 2025 Bytedance Ltd. and/or its affiliates
-// SPDX-License-Identifier: MIT
-
-import type { MentionOptions } from "@tiptap/extension-mention";
-import { ReactRenderer } from "@tiptap/react";
-import {
-  ResourceMentions,
-  type ResourceMentionsProps,
-} from "./resource-mentions";
-import type { Instance, Props } from "tippy.js";
-import tippy from "tippy.js";
-import { resolveServiceURL } from "~/core/api/resolve-service-url";
-import type { Resource } from "~/core/messages";
-
-export const resourceSuggestion: MentionOptions["suggestion"] = {
-  items: ({ query }) => {
-    return fetch(resolveServiceURL(`rag/resources?query=${query}`), {
-      method: "GET",
-    })
-      .then((res) => res.json())
-      .then((res) => {
-        return res.resources as Array<Resource>;
-      })
-      .catch((err) => {
-        return [];
-      });
-  },
-
-  render: () => {
-    let reactRenderer: ReactRenderer<
-      { onKeyDown: (args: { event: KeyboardEvent }) => boolean },
-      ResourceMentionsProps
-    >;
-    let popup: Instance<Props>[] | null = null;
-
-    return {
-      onStart: (props) => {
-        if (!props.clientRect) {
-          return;
-        }
-
-        reactRenderer = new ReactRenderer(ResourceMentions, {
-          props,
-          editor: props.editor,
-        });
-
-        popup = tippy("body", {
-          getReferenceClientRect: props.clientRect as any,
-          appendTo: () => document.body,
-          content: reactRenderer.element,
-          showOnCreate: true,
-          interactive: true,
-          trigger: "manual",
-          placement: "top-start",
-        });
-      },
-
-      onUpdate(props) {
-        reactRenderer.updateProps(props);
-
-        if (!props.clientRect) {
-          return;
-        }
-
-        popup?.[0]?.setProps({
-          getReferenceClientRect: props.clientRect as any,
-        });
-      },
-
-      onKeyDown(props) {
-        if (props.event.key === "Escape") {
-          popup?.[0]?.hide();
-
-          return true;
-        }
-
-        return reactRenderer.ref?.onKeyDown(props) ?? false;
-      },
-
-      onExit() {
-        popup?.[0]?.destroy();
-        reactRenderer.destroy();
-      },
-    };
-  },
-};

web/src/components/deer-flow/scroll-container.tsx

@@ -1,14 +1,7 @@
 // Copyright (c) 2025 Bytedance Ltd. and/or its affiliates
 // SPDX-License-Identifier: MIT
 
-import {
-  useEffect,
-  useImperativeHandle,
-  useLayoutEffect,
-  useRef,
-  type ReactNode,
-  type RefObject,
-} from "react";
+import { useEffect, useImperativeHandle, useRef, type ReactNode, type RefObject } from "react";
 import { useStickToBottom } from "use-stick-to-bottom";
 
 import { ScrollArea } from "~/components/ui/scroll-area";
@@ -33,16 +26,15 @@ export function ScrollContainer({
   scrollShadow = true,
   scrollShadowColor = "var(--background)",
   autoScrollToBottom = false,
-  ref,
+  ref
 }: ScrollContainerProps) {
-  const { scrollRef, contentRef, scrollToBottom, isAtBottom } =
-    useStickToBottom({ initial: "instant" });
+  const { scrollRef, contentRef, scrollToBottom, isAtBottom } = useStickToBottom({ initial: "instant" });
   useImperativeHandle(ref, () => ({
     scrollToBottom() {
       if (isAtBottom) {
         scrollToBottom();
       }
-    },
+    }
   }));
 
   const tempScrollRef = useRef<HTMLElement>(null);

web/src/components/editor/index.tsx

@@ -66,6 +66,17 @@ const ReportEditor = ({ content, onMarkdownChange }: ReportEditorProps) => {
 
   const debouncedUpdates = useDebouncedCallback(
     async (editor: EditorInstance) => {
+      // const json = editor.getJSON();
+      // // setCharsCount(editor.storage.characterCount.words());
+      // window.localStorage.setItem(
+      //   "html-content",
+      //   highlightCodeblocks(editor.getHTML()),
+      // );
+      // window.localStorage.setItem("novel-content", JSON.stringify(json));
+      // window.localStorage.setItem(
+      //   "markdown",
+      //   editor.storage.markdown.getMarkdown(),
+      // );
       if (onMarkdownChange) {
         const markdown = editor.storage.markdown.getMarkdown();
         onMarkdownChange(markdown);
@@ -75,6 +86,12 @@ const ReportEditor = ({ content, onMarkdownChange }: ReportEditorProps) => {
     500,
   );
 
+  // useEffect(() => {
+  //   const content = window.localStorage.getItem("novel-content");
+  //   if (content) setInitialContent(JSON.parse(content));
+  //   else setInitialContent(defaultEditorContent);
+  // }, []);
+
   if (!initialContent) return null;
 
   return (

web/src/core/api/chat.ts

@@ -4,7 +4,6 @@
 import { env } from "~/env";
 
 import type { MCPServerMetadata } from "../mcp";
-import type { Resource } from "../messages";
 import { extractReplayIdFromSearchParams } from "../replay/get-replay-id";
 import { fetchStream } from "../sse";
 import { sleep } from "../utils";
@@ -16,7 +15,6 @@ export async function* chatStream(
   userMessage: string,
   params: {
     thread_id: string;
-    resources?: Array<Resource>;
     auto_accepted_plan: boolean;
     max_plan_iterations: number;
     max_step_num: number;
@@ -103,8 +101,7 @@ async function* chatReplayStream(
   const text = await fetchReplay(replayFilePath, {
     abortSignal: options.abortSignal,
   });
-  const normalizedText = text.replace(/\r\n/g, "\n");
-  const chunks = normalizedText.split("\n\n");
+  const chunks = text.split("\n\n");
   for (const chunk of chunks) {
     const [eventRaw, dataRaw] = chunk.split("\n") as [string, string];
     const [, event] = eventRaw.split("event: ", 2) as [string, string];

web/src/core/api/hooks.ts

@@ -3,12 +3,9 @@
 
 import { useEffect, useRef, useState } from "react";
 
-import { env } from "~/env";
-
 import { useReplay } from "../replay";
 
 import { fetchReplayTitle } from "./chat";
-import { getRAGConfig } from "./rag";
 
 export function useReplayMetadata() {
   const { isReplay } = useReplay();
@@ -42,26 +39,3 @@ export function useReplayMetadata() {
   }, [isLoading, isReplay, title]);
   return { title, isLoading, hasError: error };
 }
-
-export function useRAGProvider() {
-  const [loading, setLoading] = useState(true);
-  const [provider, setProvider] = useState<string | null>(null);
-
-  useEffect(() => {
-    if (env.NEXT_PUBLIC_STATIC_WEBSITE_ONLY) {
-      setLoading(false);
-      return;
-    }
-    getRAGConfig()
-      .then(setProvider)
-      .catch((e) => {
-        setProvider(null);
-        console.error("Failed to get RAG provider", e);
-      })
-      .finally(() => {
-        setLoading(false);
-      });
-  }, []);
-
-  return { provider, loading };
-}

web/src/core/api/rag.ts

@@ -1,24 +0,0 @@
-import type { Resource } from "../messages";
-
-import { resolveServiceURL } from "./resolve-service-url";
-
-export function queryRAGResources(query: string) {
-  return fetch(resolveServiceURL(`rag/resources?query=${query}`), {
-    method: "GET",
-  })
-    .then((res) => res.json())
-    .then((res) => {
-      return res.resources as Array<Resource>;
-    })
-    .catch((err) => {
-      return [];
-    });
-}
-
-export function getRAGConfig() {
-  return fetch(resolveServiceURL(`rag/config`), {
-    method: "GET",
-  })
-    .then((res) => res.json())
-    .then((res) => res.provider);
-}

web/src/core/messages/types.ts

@@ -21,7 +21,6 @@ export interface Message {
   options?: Option[];
   finishReason?: "stop" | "interrupt" | "tool_calls";
   interruptFeedback?: string;
-  resources?: Array<Resource>;
 }
 
 export interface Option {
@@ -36,8 +35,3 @@ export interface ToolCallRuntime {
   argsChunks?: string[];
   result?: string;
 }
-
-export interface Resource {
-  uri: string;
-  title: string;
-}

web/src/core/store/store.ts

@@ -7,7 +7,7 @@ import { create } from "zustand";
 import { useShallow } from "zustand/react/shallow";
 
 import { chatStream, generatePodcast } from "../api";
-import type { Message, Resource } from "../messages";
+import type { Message } from "../messages";
 import { mergeMessage } from "../messages";
 import { parseJSON } from "../utils";
 
@@ -78,10 +78,8 @@ export async function sendMessage(
   content?: string,
   {
     interruptFeedback,
-    resources,
   }: {
     interruptFeedback?: string;
-    resources?: Array<Resource>;
   } = {},
   options: { abortSignal?: AbortSignal } = {},
 ) {
@@ -92,7 +90,6 @@ export async function sendMessage(
       role: "user",
       content: content,
       contentChunks: [content],
-      resources,
     });
   }
 
@@ -102,7 +99,6 @@ export async function sendMessage(
     {
       thread_id: THREAD_ID,
       interrupt_feedback: interruptFeedback,
-      resources,
       auto_accepted_plan: settings.autoAcceptedPlan,
       enable_background_investigation:
         settings.enableBackgroundInvestigation ?? true,

web/src/styles/globals.css

@@ -187,7 +187,7 @@
   --sidebar-accent-foreground: oklch(0.985 0 0);
   --sidebar-border: oklch(1 0 0 / 10%);
   --sidebar-ring: oklch(0.556 0 0);
-  --brand: rgb(17, 103, 234);
+  --brand: #5494f3;
 
   --novel-highlight-default: #000000;
   --novel-highlight-purple: #3f2c4b;

web/src/styles/prosemirror.css

@@ -1,19 +1,7 @@
+@import "./globals.css";
+
 .prose {
-  max-width: inherit;
-}
-
-.prose.inline-editor * {
-  margin: 0;
-}
-
-.prose.inline-editor .is-empty {
-  display: none;
-}
-
-.prose.inline-editor .is-empty.placeholder {
-  display: block;
-  opacity: 0.65;
-  font-size: 14px;
+  color: inherit;
 }
 
 .ProseMirror {
@@ -27,7 +15,6 @@
   pointer-events: none;
   height: 0;
 }
-
 .ProseMirror p.is-empty::before {
   content: attr(data-placeholder);
   float: left;
@@ -36,14 +23,6 @@
   height: 0;
 }
 
-.ProseMirror .mention {
-  background-color: var(--purple-light);
-  border-radius: 0.4rem;
-  box-decoration-break: clone;
-  color: var(--brand);
-  padding: 0.1rem 0.3rem;
-}
-
 /* Custom image styles */
 
 .ProseMirror img {