Doc: Updated Create dataset descriptions (#11742 )

### What problem does this PR solve? ### Type of change - [x] Documentation Update
Change docker container restart policy (#11695 )
2026-01-04 03:25:30 +08:00 · 2025-12-04 17:07:52 +08:00 · 2025-12-04 15:18:13 +08:00 · 2025-12-04 14:53:57 +08:00 · 2025-12-04 14:15:05 +08:00 · 2025-12-04 14:14:38 +08:00
47 changed files with 735 additions and 556093 deletions
--- a/3
+++ b/3
@ -10,11 +10,10 @@ WORKDIR /ragflow
 # Copy models downloaded via download_deps.py
 RUN mkdir -p /ragflow/rag/res/deepdoc /root/.ragflow
 RUN --mount=type=bind,from=infiniflow/ragflow_deps:latest,source=/huggingface.co,target=/huggingface.co \
-    cp /huggingface.co/InfiniFlow/huqie/huqie.txt.trie /ragflow/rag/res/ && \
    tar --exclude='.*' -cf - \
        /huggingface.co/InfiniFlow/text_concat_xgb_v1.0 \
        /huggingface.co/InfiniFlow/deepdoc \
-        | tar -xf - --strip-components=3 -C /ragflow/rag/res/deepdoc 
+        | tar -xf - --strip-components=3 -C /ragflow/rag/res/deepdoc

 # https://github.com/chrismattmann/tika-python
 # This is the only way to run python-tika without internet access. Without this set, the default is to check the tika version and pull latest every time from Apache.
--- a/agent/canvas.py
+++ b/agent/canvas.py
@ -91,9 +91,6 @@ class Graph:
    def load(self):
        self.components = self.dsl["components"]
        cpn_nms = set([])
-        for k, cpn in self.components.items():
-            cpn_nms.add(cpn["obj"]["component_name"])
-
        for k, cpn in self.components.items():
            cpn_nms.add(cpn["obj"]["component_name"])
            param = component_class(cpn["obj"]["component_name"] + "Param")()
--- a/agent/component/agent_with_tools.py
+++ b/agent/component/agent_with_tools.py
@ -18,7 +18,6 @@ import json
 import logging
 import os
 import re
-from concurrent.futures import ThreadPoolExecutor
 from copy import deepcopy
 from functools import partial
 from typing import Any
@ -30,8 +29,8 @@ from api.db.services.llm_service import LLMBundle
 from api.db.services.tenant_llm_service import TenantLLMService
 from api.db.services.mcp_server_service import MCPServerService
 from common.connection_utils import timeout
-from rag.prompts.generator import next_step, COMPLETE_TASK, analyze_task, \
-    citation_prompt, reflect, rank_memories, kb_prompt, citation_plus, full_question, message_fit_in, structured_output_prompt
+from rag.prompts.generator import next_step_async, COMPLETE_TASK, analyze_task_async, \
+    citation_prompt, reflect_async, kb_prompt, citation_plus, full_question, message_fit_in, structured_output_prompt
 from common.mcp_tool_call_conn import MCPToolCallSession, mcp_tool_metadata_to_openai_tool
 from agent.component.llm import LLMParam, LLM

@ -154,96 +153,19 @@ class Agent(LLM, ToolBase):

        return None

-    def _force_format_to_schema(self, text: str, schema_prompt: str) -> str:
+    async def _force_format_to_schema_async(self, text: str, schema_prompt: str) -> str:
        fmt_msgs = [
            {"role": "system", "content": schema_prompt + "\nIMPORTANT: Output ONLY valid JSON. No markdown, no extra text."},
            {"role": "user", "content": text},
        ]
        _, fmt_msgs = message_fit_in(fmt_msgs, int(self.chat_mdl.max_length * 0.97))
-        return self._generate(fmt_msgs)
+        return await self._generate_async(fmt_msgs)
+
+    def _invoke(self, **kwargs):
+        return asyncio.run(self._invoke_async(**kwargs))

    @timeout(int(os.environ.get("COMPONENT_EXEC_TIMEOUT", 20*60)))
-    def _invoke(self, **kwargs):
-        if self.check_if_canceled("Agent processing"):
-            return
-
-        if kwargs.get("user_prompt"):
-            usr_pmt = ""
-            if kwargs.get("reasoning"):
-                usr_pmt += "\nREASONING:\n{}\n".format(kwargs["reasoning"])
-            if kwargs.get("context"):
-                usr_pmt += "\nCONTEXT:\n{}\n".format(kwargs["context"])
-            if usr_pmt:
-                usr_pmt += "\nQUERY:\n{}\n".format(str(kwargs["user_prompt"]))
-            else:
-                usr_pmt = str(kwargs["user_prompt"])
-            self._param.prompts = [{"role": "user", "content": usr_pmt}]
-
-        if not self.tools:
-            if self.check_if_canceled("Agent processing"):
-                return
-            return LLM._invoke(self, **kwargs)
-
-        prompt, msg, user_defined_prompt = self._prepare_prompt_variables()
-        output_schema = self._get_output_schema()
-        schema_prompt = ""
-        if output_schema:
-            schema = json.dumps(output_schema, ensure_ascii=False, indent=2)
-            schema_prompt = structured_output_prompt(schema)
-
-        downstreams = self._canvas.get_component(self._id)["downstream"] if self._canvas.get_component(self._id) else []
-        ex = self.exception_handler()
-        if any([self._canvas.get_component_obj(cid).component_name.lower()=="message" for cid in downstreams]) and not (ex and ex["goto"]) and not output_schema:
-            self.set_output("content", partial(self.stream_output_with_tools, prompt, msg, user_defined_prompt))
-            return
-
-        _, msg = message_fit_in([{"role": "system", "content": prompt}, *msg], int(self.chat_mdl.max_length * 0.97))
-        use_tools = []
-        ans = ""
-        for delta_ans, tk in self._react_with_tools_streamly(prompt, msg, use_tools, user_defined_prompt,schema_prompt=schema_prompt):
-            if self.check_if_canceled("Agent processing"):
-                return
-            ans += delta_ans
-
-        if ans.find("**ERROR**") >= 0:
-            logging.error(f"Agent._chat got error. response: {ans}")
-            if self.get_exception_default_value():
-                self.set_output("content", self.get_exception_default_value())
-            else:
-                self.set_output("_ERROR", ans)
-            return
-
-        if output_schema:
-            error = ""
-            for _ in range(self._param.max_retries + 1):
-                try:
-                    def clean_formated_answer(ans: str) -> str:
-                        ans = re.sub(r"^.*</think>", "", ans, flags=re.DOTALL)
-                        ans = re.sub(r"^.*```json", "", ans, flags=re.DOTALL)
-                        return re.sub(r"```\n*$", "", ans, flags=re.DOTALL)
-                    obj = json_repair.loads(clean_formated_answer(ans))
-                    self.set_output("structured", obj)
-                    if use_tools:
-                        self.set_output("use_tools", use_tools)
-                    return obj
-                except Exception:
-                    error = "The answer cannot be parsed as JSON"
-                    ans = self._force_format_to_schema(ans, schema_prompt)
-                    if ans.find("**ERROR**") >= 0:
-                        continue
-
-            self.set_output("_ERROR", error)
-            return
-
-        self.set_output("content", ans)
-        if use_tools:
-            self.set_output("use_tools", use_tools)
-        return ans
-
    async def _invoke_async(self, **kwargs):
-        """
-        Async entry: reuse existing logic but offload heavy sync parts via async wrappers to reduce blocking.
-        """
        if self.check_if_canceled("Agent processing"):
            return

@ -262,7 +184,7 @@ class Agent(LLM, ToolBase):
        if not self.tools:
            if self.check_if_canceled("Agent processing"):
                return
-            return await asyncio.to_thread(LLM._invoke, self, **kwargs)
+            return await LLM._invoke_async(self, **kwargs)

        prompt, msg, user_defined_prompt = self._prepare_prompt_variables()
        output_schema = self._get_output_schema()
@ -274,13 +196,13 @@ class Agent(LLM, ToolBase):
        downstreams = self._canvas.get_component(self._id)["downstream"] if self._canvas.get_component(self._id) else []
        ex = self.exception_handler()
        if any([self._canvas.get_component_obj(cid).component_name.lower()=="message" for cid in downstreams]) and not (ex and ex["goto"]) and not output_schema:
-            self.set_output("content", partial(self.stream_output_with_tools_async, prompt, msg, user_defined_prompt))
+            self.set_output("content", partial(self.stream_output_with_tools_async, prompt, deepcopy(msg), user_defined_prompt))
            return

        _, msg = message_fit_in([{"role": "system", "content": prompt}, *msg], int(self.chat_mdl.max_length * 0.97))
        use_tools = []
        ans = ""
-        async for delta_ans, tk in self._react_with_tools_streamly_async(prompt, msg, use_tools, user_defined_prompt, schema_prompt=schema_prompt):
+        async for delta_ans, _tk in self._react_with_tools_streamly_async(prompt, msg, use_tools, user_defined_prompt,schema_prompt=schema_prompt):
            if self.check_if_canceled("Agent processing"):
                return
            ans += delta_ans
@ -308,7 +230,7 @@ class Agent(LLM, ToolBase):
                    return obj
                except Exception:
                    error = "The answer cannot be parsed as JSON"
-                    ans = self._force_format_to_schema(ans, schema_prompt)
+                    ans = await self._force_format_to_schema_async(ans, schema_prompt)
                    if ans.find("**ERROR**") >= 0:
                        continue

@ -320,28 +242,6 @@ class Agent(LLM, ToolBase):
            self.set_output("use_tools", use_tools)
        return ans

-    def stream_output_with_tools(self, prompt, msg, user_defined_prompt={}):
-        _, msg = message_fit_in([{"role": "system", "content": prompt}, *msg], int(self.chat_mdl.max_length * 0.97))
-        answer_without_toolcall = ""
-        use_tools = []
-        for delta_ans,_ in self._react_with_tools_streamly(prompt, msg, use_tools, user_defined_prompt):
-            if self.check_if_canceled("Agent streaming"):
-                return
-
-            if delta_ans.find("**ERROR**") >= 0:
-                if self.get_exception_default_value():
-                    self.set_output("content", self.get_exception_default_value())
-                    yield self.get_exception_default_value()
-                else:
-                    self.set_output("_ERROR", delta_ans)
-                    return
-            answer_without_toolcall += delta_ans
-            yield delta_ans
-
-        self.set_output("content", answer_without_toolcall)
-        if use_tools:
-            self.set_output("use_tools", use_tools)
-
    async def stream_output_with_tools_async(self, prompt, msg, user_defined_prompt={}):
        _, msg = message_fit_in([{"role": "system", "content": prompt}, *msg], int(self.chat_mdl.max_length * 0.97))
        answer_without_toolcall = ""
@ -365,64 +265,22 @@ class Agent(LLM, ToolBase):
            self.set_output("use_tools", use_tools)

    async def _react_with_tools_streamly_async(self, prompt, history: list[dict], use_tools, user_defined_prompt={}, schema_prompt: str = ""):
-        """
-        Async wrapper that offloads synchronous flow to a thread, yielding results without blocking the event loop.
-        """
-        loop = asyncio.get_running_loop()
-        queue: asyncio.Queue = asyncio.Queue()
-
-        def worker():
-            try:
-                for delta_ans, tk in self._react_with_tools_streamly(prompt, history, use_tools, user_defined_prompt, schema_prompt=schema_prompt):
-                    asyncio.run_coroutine_threadsafe(queue.put((delta_ans, tk)), loop)
-            except Exception as e:
-                asyncio.run_coroutine_threadsafe(queue.put(e), loop)
-            finally:
-                asyncio.run_coroutine_threadsafe(queue.put(StopAsyncIteration), loop)
-
-        await asyncio.to_thread(worker)
-
-        while True:
-            item = await queue.get()
-            if item is StopAsyncIteration:
-                break
-            if isinstance(item, Exception):
-                raise item
-            yield item
-
-    def _gen_citations(self, text):
-        retrievals = self._canvas.get_reference()
-        retrievals = {"chunks": list(retrievals["chunks"].values()), "doc_aggs": list(retrievals["doc_aggs"].values())}
-        formated_refer = kb_prompt(retrievals, self.chat_mdl.max_length, True)
-        for delta_ans in self._generate_streamly([{"role": "system", "content": citation_plus("\n\n".join(formated_refer))},
-                                                  {"role": "user", "content": text}
-                                                  ]):
-            yield delta_ans
-
-    def _react_with_tools_streamly(self, prompt, history: list[dict], use_tools, user_defined_prompt={}, schema_prompt: str = ""):
        token_count = 0
        tool_metas = self.tool_meta
        hist = deepcopy(history)
        last_calling = ""
        if len(hist) > 3:
            st = timer()
-            user_request = full_question(messages=history, chat_mdl=self.chat_mdl)
+            user_request = await asyncio.to_thread(full_question, messages=history, chat_mdl=self.chat_mdl)
            self.callback("Multi-turn conversation optimization", {}, user_request, elapsed_time=timer()-st)
        else:
            user_request = history[-1]["content"]

-        def use_tool(name, args):
-            nonlocal hist, use_tools, token_count,last_calling,user_request
+        async def use_tool_async(name, args):
+            nonlocal hist, use_tools, last_calling
            logging.info(f"{last_calling=} == {name=}")
-            # Summarize of function calling
-            #if all([
-            #    isinstance(self.toolcall_session.get_tool_obj(name), Agent),
-            #    last_calling,
-            #    last_calling != name
-            #]):
-            #    self.toolcall_session.get_tool_obj(name).add2system_prompt(f"The chat history with other agents are as following: \n" + self.get_useful_memory(user_request, str(args["user_prompt"]),user_defined_prompt))
            last_calling = name
-            tool_response = self.toolcall_session.tool_call(name, args)
+            tool_response = await self.toolcall_session.tool_call_async(name, args)
            use_tools.append({
                "name": name,
                "arguments": args,
@ -433,7 +291,7 @@ class Agent(LLM, ToolBase):

            return name, tool_response

-        def complete():
+        async def complete():
            nonlocal hist
            need2cite = self._param.cite and self._canvas.get_reference()["chunks"] and self._id.find("-->") < 0
            if schema_prompt:
@ -451,7 +309,7 @@ class Agent(LLM, ToolBase):
            if len(hist) > 12:
                _hist = [hist[0], hist[1], *hist[-10:]]
            entire_txt = ""
-            for delta_ans in self._generate_streamly(_hist):
+            async for delta_ans in self._generate_streamly_async(_hist):
                if not need2cite or cited:
                    yield delta_ans, 0
                entire_txt += delta_ans
@ -460,7 +318,7 @@ class Agent(LLM, ToolBase):

            st = timer()
            txt = ""
-            for delta_ans in self._gen_citations(entire_txt):
+            async for delta_ans in self._gen_citations_async(entire_txt):
                if self.check_if_canceled("Agent streaming"):
                    return
                yield delta_ans, 0
@ -475,14 +333,14 @@ class Agent(LLM, ToolBase):
                hist.append({"role": "user", "content": content})

        st = timer()
-        task_desc = analyze_task(self.chat_mdl, prompt, user_request, tool_metas, user_defined_prompt)
+        task_desc = await analyze_task_async(self.chat_mdl, prompt, user_request, tool_metas, user_defined_prompt)
        self.callback("analyze_task", {}, task_desc, elapsed_time=timer()-st)
        for _ in range(self._param.max_rounds + 1):
            if self.check_if_canceled("Agent streaming"):
                return
-            response, tk = next_step(self.chat_mdl, hist, tool_metas, task_desc, user_defined_prompt)
+            response, tk = await next_step_async(self.chat_mdl, hist, tool_metas, task_desc, user_defined_prompt)
            # self.callback("next_step", {}, str(response)[:256]+"...")
-            token_count += tk
+            token_count += tk or 0
            hist.append({"role": "assistant", "content": response})
            try:
                functions = json_repair.loads(re.sub(r"```.*", "", response))
@ -491,23 +349,24 @@ class Agent(LLM, ToolBase):
                for f in functions:
                    if not isinstance(f, dict):
                        raise TypeError(f"An object type should be returned, but `{f}`")
-                with ThreadPoolExecutor(max_workers=5) as executor:
-                    thr = []
-                    for func in functions:
-                        name = func["name"]
-                        args = func["arguments"]
-                        if name == COMPLETE_TASK:
-                            append_user_content(hist, f"Respond with a formal answer. FORGET(DO NOT mention) about `{COMPLETE_TASK}`. The language for the response MUST be as the same as the first user request.\n")
-                            for txt, tkcnt in complete():
-                                yield txt, tkcnt
-                            return

-                        thr.append(executor.submit(use_tool, name, args))
+                tool_tasks = []
+                for func in functions:
+                    name = func["name"]
+                    args = func["arguments"]
+                    if name == COMPLETE_TASK:
+                        append_user_content(hist, f"Respond with a formal answer. FORGET(DO NOT mention) about `{COMPLETE_TASK}`. The language for the response MUST be as the same as the first user request.\n")
+                        async for txt, tkcnt in complete():
+                            yield txt, tkcnt
+                        return

-                    st = timer()
-                    reflection = reflect(self.chat_mdl, hist, [th.result() for th in thr], user_defined_prompt)
-                    append_user_content(hist, reflection)
-                    self.callback("reflection", {}, str(reflection), elapsed_time=timer()-st)
+                    tool_tasks.append(asyncio.create_task(use_tool_async(name, args)))
+
+                results = await asyncio.gather(*tool_tasks) if tool_tasks else []
+                st = timer()
+                reflection = await reflect_async(self.chat_mdl, hist, results, user_defined_prompt)
+                append_user_content(hist, reflection)
+                self.callback("reflection", {}, str(reflection), elapsed_time=timer()-st)

            except Exception as e:
                logging.exception(msg=f"Wrong JSON argument format in LLM ReAct response: {e}")
@ -531,21 +390,17 @@ Respond immediately with your final comprehensive answer.
            return
        append_user_content(hist, final_instruction)

-        for txt, tkcnt in complete():
+        async for txt, tkcnt in complete():
            yield txt, tkcnt

-    def get_useful_memory(self, goal: str, sub_goal:str, topn=3, user_defined_prompt:dict={}) -> str:
-        # self.callback("get_useful_memory", {"topn": 3}, "...")
-        mems = self._canvas.get_memory()
-        rank = rank_memories(self.chat_mdl, goal, sub_goal, [summ for (user, assist, summ) in mems], user_defined_prompt)
-        try:
-            rank = json_repair.loads(re.sub(r"```.*", "", rank))[:topn]
-            mems = [mems[r] for r in rank]
-            return "\n\n".join([f"User: {u}\nAgent: {a}" for u, a,_ in mems])
-        except Exception as e:
-            logging.exception(e)
-
-        return "Error occurred."
+    async def _gen_citations_async(self, text):
+        retrievals = self._canvas.get_reference()
+        retrievals = {"chunks": list(retrievals["chunks"].values()), "doc_aggs": list(retrievals["doc_aggs"].values())}
+        formated_refer = kb_prompt(retrievals, self.chat_mdl.max_length, True)
+        async for delta_ans in self._generate_streamly_async([{"role": "system", "content": citation_plus("\n\n".join(formated_refer))},
+                                                  {"role": "user", "content": text}
+                                                  ]):
+            yield delta_ans

    def reset(self, only_output=False):
        """
--- a/agent/component/llm.py
+++ b/agent/component/llm.py
@ -327,7 +327,7 @@ class LLM(ComponentBase):
        self.set_output("content", answer)

    @timeout(int(os.environ.get("COMPONENT_EXEC_TIMEOUT", 10*60)))
-    def _invoke(self, **kwargs):
+    async def _invoke_async(self, **kwargs):
        if self.check_if_canceled("LLM processing"):
            return

@ -338,22 +338,25 @@ class LLM(ComponentBase):

        prompt, msg, _ = self._prepare_prompt_variables()
        error: str = ""
-        output_structure=None
+        output_structure = None
        try:
-            output_structure = self._param.outputs['structured']
+            output_structure = self._param.outputs["structured"]
        except Exception:
            pass
        if output_structure and isinstance(output_structure, dict) and output_structure.get("properties") and len(output_structure["properties"]) > 0:
-            schema=json.dumps(output_structure, ensure_ascii=False, indent=2)
-            prompt += structured_output_prompt(schema)
-            for _ in range(self._param.max_retries+1):
+            schema = json.dumps(output_structure, ensure_ascii=False, indent=2)
+            prompt_with_schema = prompt + structured_output_prompt(schema)
+            for _ in range(self._param.max_retries + 1):
                if self.check_if_canceled("LLM processing"):
                    return

-                _, msg = message_fit_in([{"role": "system", "content": prompt}, *msg], int(self.chat_mdl.max_length * 0.97))
+                _, msg_fit = message_fit_in(
+                    [{"role": "system", "content": prompt_with_schema}, *deepcopy(msg)],
+                    int(self.chat_mdl.max_length * 0.97),
+                )
                error = ""
-                ans = self._generate(msg)
-                msg.pop(0)
+                ans = await self._generate_async(msg_fit)
+                msg_fit.pop(0)
                if ans.find("**ERROR**") >= 0:
                    logging.error(f"LLM response error: {ans}")
                    error = ans
@ -362,7 +365,7 @@ class LLM(ComponentBase):
                    self.set_output("structured", json_repair.loads(clean_formated_answer(ans)))
                    return
                except Exception:
-                    msg.append({"role": "user", "content": "The answer can't not be parsed as JSON"})
+                    msg_fit.append({"role": "user", "content": "The answer can't not be parsed as JSON"})
                    error = "The answer can't not be parsed as JSON"
            if error:
                self.set_output("_ERROR", error)
@ -370,18 +373,23 @@ class LLM(ComponentBase):

        downstreams = self._canvas.get_component(self._id)["downstream"] if self._canvas.get_component(self._id) else []
        ex = self.exception_handler()
-        if any([self._canvas.get_component_obj(cid).component_name.lower()=="message" for cid in downstreams]) and not (ex and ex["goto"]):
-            self.set_output("content", partial(self._stream_output_async, prompt, msg))
+        if any([self._canvas.get_component_obj(cid).component_name.lower() == "message" for cid in downstreams]) and not (
+            ex and ex["goto"]
+        ):
+            self.set_output("content", partial(self._stream_output_async, prompt, deepcopy(msg)))
            return

-        for _ in range(self._param.max_retries+1):
+        error = ""
+        for _ in range(self._param.max_retries + 1):
            if self.check_if_canceled("LLM processing"):
                return

-            _, msg = message_fit_in([{"role": "system", "content": prompt}, *msg], int(self.chat_mdl.max_length * 0.97))
+            _, msg_fit = message_fit_in(
+                [{"role": "system", "content": prompt}, *deepcopy(msg)], int(self.chat_mdl.max_length * 0.97)
+            )
            error = ""
-            ans = self._generate(msg)
-            msg.pop(0)
+            ans = await self._generate_async(msg_fit)
+            msg_fit.pop(0)
            if ans.find("**ERROR**") >= 0:
                logging.error(f"LLM response error: {ans}")
                error = ans
@ -395,23 +403,9 @@ class LLM(ComponentBase):
            else:
                self.set_output("_ERROR", error)

-    def _stream_output(self, prompt, msg):
-        _, msg = message_fit_in([{"role": "system", "content": prompt}, *msg], int(self.chat_mdl.max_length * 0.97))
-        answer = ""
-        for ans in self._generate_streamly(msg):
-            if self.check_if_canceled("LLM streaming"):
-                return
-
-            if ans.find("**ERROR**") >= 0:
-                if self.get_exception_default_value():
-                    self.set_output("content", self.get_exception_default_value())
-                    yield self.get_exception_default_value()
-                else:
-                    self.set_output("_ERROR", ans)
-                return
-            yield ans
-            answer += ans
-        self.set_output("content", answer)
+    @timeout(int(os.environ.get("COMPONENT_EXEC_TIMEOUT", 10*60)))
+    def _invoke(self, **kwargs):
+        return asyncio.run(self._invoke_async(**kwargs))

    def add_memory(self, user:str, assist:str, func_name: str, params: dict, results: str, user_defined_prompt:dict={}):
        summ = tool_call_summary(self.chat_mdl, func_name, params, results, user_defined_prompt)
--- a/agent/tools/base.py
+++ b/agent/tools/base.py
@ -49,16 +49,19 @@ class LLMToolPluginCallSession(ToolCallSession):
        self.callback = callback

    def tool_call(self, name: str, arguments: dict[str, Any]) -> Any:
+        return asyncio.run(self.tool_call_async(name, arguments))
+
+    async def tool_call_async(self, name: str, arguments: dict[str, Any]) -> Any:
        assert name in self.tools_map, f"LLM tool {name} does not exist"
        st = timer()
        tool_obj = self.tools_map[name]
        if isinstance(tool_obj, MCPToolCallSession):
-            resp = tool_obj.tool_call(name, arguments, 60)
+            resp = await asyncio.to_thread(tool_obj.tool_call, name, arguments, 60)
        else:
            if hasattr(tool_obj, "invoke_async") and asyncio.iscoroutinefunction(tool_obj.invoke_async):
-                resp = asyncio.run(tool_obj.invoke_async(**arguments))
+                resp = await tool_obj.invoke_async(**arguments)
            else:
-                resp = asyncio.run(asyncio.to_thread(tool_obj.invoke, **arguments))
+                resp = await asyncio.to_thread(tool_obj.invoke, **arguments)

        self.callback(name, arguments, resp, elapsed_time=timer()-st)
        return resp
--- a/api/apps/sdk/doc.py
+++ b/api/apps/sdk/doc.py
@ -321,9 +321,7 @@ async def update_doc(tenant_id, dataset_id, document_id):
            try:
                if not DocumentService.update_by_id(doc.id, {"status": str(status)}):
                    return get_error_data_result(message="Database error (Document update)!")
-
                settings.docStoreConn.update({"doc_id": doc.id}, {"available_int": status}, search.index_name(kb.tenant_id), doc.kb_id)
-                return get_result(data=True)
            except Exception as e:
                return server_error_response(e)

@ -350,12 +348,10 @@ async def update_doc(tenant_id, dataset_id, document_id):
    }
    renamed_doc = {}
    for key, value in doc.to_dict().items():
-        if key == "run":
-            renamed_doc["run"] = run_mapping.get(str(value))
        new_key = key_mapping.get(key, key)
        renamed_doc[new_key] = value
        if key == "run":
-            renamed_doc["run"] = run_mapping.get(value)
+            renamed_doc["run"] = run_mapping.get(str(value))

    return get_result(data=renamed_doc)

--- a/common/constants.py
+++ b/common/constants.py
@ -148,6 +148,7 @@ class Storage(Enum):
    AWS_S3 = 4
    OSS = 5
    OPENDAL = 6
+    GCS = 7

 # environment
 # ENV_STRONG_TEST_COUNT = "STRONG_TEST_COUNT"
--- a/common/settings.py
+++ b/common/settings.py
@ -31,6 +31,7 @@ import rag.utils.ob_conn
 import rag.utils.opensearch_conn
 from rag.utils.azure_sas_conn import RAGFlowAzureSasBlob
 from rag.utils.azure_spn_conn import RAGFlowAzureSpnBlob
+from rag.utils.gcs_conn import RAGFlowGCS
 from rag.utils.minio_conn import RAGFlowMinio
 from rag.utils.opendal_conn import OpenDALStorage
 from rag.utils.s3_conn import RAGFlowS3
@ -109,6 +110,7 @@ MINIO = {}
 OB = {}
 OSS = {}
 OS = {}
+GCS = {}

 DOC_MAXIMUM_SIZE: int = 128 * 1024 * 1024
 DOC_BULK_SIZE: int = 4
@ -151,7 +153,8 @@ class StorageFactory:
        Storage.AZURE_SAS: RAGFlowAzureSasBlob,
        Storage.AWS_S3: RAGFlowS3,
        Storage.OSS: RAGFlowOSS,
-        Storage.OPENDAL: OpenDALStorage
+        Storage.OPENDAL: OpenDALStorage,
+        Storage.GCS: RAGFlowGCS,
    }

    @classmethod
@ -250,7 +253,7 @@ def init_settings():
    else:
        raise Exception(f"Not supported doc engine: {DOC_ENGINE}")

-    global AZURE, S3, MINIO, OSS
+    global AZURE, S3, MINIO, OSS, GCS
    if STORAGE_IMPL_TYPE in ['AZURE_SPN', 'AZURE_SAS']:
        AZURE = get_base_config("azure", {})
    elif STORAGE_IMPL_TYPE == 'AWS_S3':
@ -259,6 +262,8 @@ def init_settings():
        MINIO = decrypt_database_config(name="minio")
    elif STORAGE_IMPL_TYPE == 'OSS':
        OSS = get_base_config("oss", {})
+    elif STORAGE_IMPL_TYPE == 'GCS':
+        GCS = get_base_config("gcs", {})

    global STORAGE_IMPL
    STORAGE_IMPL = StorageFactory.create(Storage[STORAGE_IMPL_TYPE])
--- a/conf/service_conf.yaml
+++ b/conf/service_conf.yaml
@ -60,6 +60,8 @@ user_default_llm:
 #   access_key: 'access_key'
 #   secret_key: 'secret_key'
 #   region: 'region'
+#gcs:
+#  bucket: 'bridgtl-edm-d-bucket-ragflow'
 # oss:
 #   access_key: 'access_key'
 #   secret_key: 'secret_key'
--- a/deepdoc/parser/figure_parser.py
+++ b/deepdoc/parser/figure_parser.py
@ -25,6 +25,8 @@ from rag.prompts.generator import vision_llm_figure_describe_prompt


 def vision_figure_parser_figure_data_wrapper(figures_data_without_positions):
+    if not figures_data_without_positions:
+        return []
    return [
        (
            (figure_data[1], [figure_data[0]]),
@ -35,7 +37,9 @@ def vision_figure_parser_figure_data_wrapper(figures_data_without_positions):
    ]


-def vision_figure_parser_docx_wrapper(sections,tbls,callback=None,**kwargs):
+def vision_figure_parser_docx_wrapper(sections, tbls, callback=None,**kwargs):
+    if not tbls:
+        return []
    try:
        vision_model = LLMBundle(kwargs["tenant_id"], LLMType.IMAGE2TEXT)
        callback(0.7, "Visual model detected. Attempting to enhance figure extraction...")
@ -53,6 +57,8 @@ def vision_figure_parser_docx_wrapper(sections,tbls,callback=None,**kwargs):


 def vision_figure_parser_pdf_wrapper(tbls, callback=None, **kwargs):
+    if not tbls:
+        return []
    try:
        vision_model = LLMBundle(kwargs["tenant_id"], LLMType.IMAGE2TEXT)
        callback(0.7, "Visual model detected. Attempting to enhance figure extraction...")
--- a/docker/docker-compose-CN-oc9.yml
+++ b/docker/docker-compose-CN-oc9.yml
@ -23,7 +23,7 @@ services:
    env_file: .env
    networks:
      - ragflow
-    restart: on-failure
+    restart: unless-stopped
    # https://docs.docker.com/engine/daemon/prometheus/#create-a-prometheus-configuration
    # If you're using Docker Desktop, the --add-host flag is optional. This flag makes sure that the host's internal IP gets exposed to the Prometheus container.
    extra_hosts:
@ -48,7 +48,7 @@ services:
    env_file: .env
    networks:
      - ragflow
-    restart: on-failure
+    restart: unless-stopped
    # https://docs.docker.com/engine/daemon/prometheus/#create-a-prometheus-configuration
    # If you're using Docker Desktop, the --add-host flag is optional. This flag makes sure that the host's internal IP gets exposed to the Prometheus container.
    extra_hosts:
--- a/docker/docker-compose-base.yml
+++ b/docker/docker-compose-base.yml
@ -31,7 +31,7 @@ services:
      retries: 120
    networks:
      - ragflow
-    restart: on-failure
+    restart: unless-stopped

  opensearch01:
    profiles:
@ -67,12 +67,12 @@ services:
      retries: 120
    networks:
      - ragflow
-    restart: on-failure
+    restart: unless-stopped

  infinity:
    profiles:
      - infinity
-    image: infiniflow/infinity:v0.6.8
+    image: infiniflow/infinity:v0.6.10
    volumes:
      - infinity_data:/var/infinity
      - ./infinity_conf.toml:/infinity_conf.toml
@ -94,7 +94,7 @@ services:
      interval: 10s
      timeout: 10s
      retries: 120
-    restart: on-failure
+    restart: unless-stopped

  oceanbase:
    profiles:
@ -119,7 +119,7 @@ services:
      timeout: 10s
    networks:
      - ragflow
-    restart: on-failure
+    restart: unless-stopped

  sandbox-executor-manager:
    profiles:
@ -147,7 +147,7 @@ services:
      interval: 10s
      timeout: 10s
      retries: 120
-    restart: on-failure
+    restart: unless-stopped

  mysql:
    # mysql:5.7 linux/arm64 image is unavailable.
@ -175,7 +175,7 @@ services:
      interval: 10s
      timeout: 10s
      retries: 120
-    restart: on-failure
+    restart: unless-stopped

  minio:
    image: quay.io/minio/minio:RELEASE.2025-06-13T11-33-47Z
@ -191,7 +191,7 @@ services:
      - minio_data:/data
    networks:
      - ragflow
-    restart: on-failure
+    restart: unless-stopped
    healthcheck:
      test: ["CMD", "curl", "-f", "http://localhost:9000/minio/health/live"]
      interval: 10s
@ -209,7 +209,7 @@ services:
      - redis_data:/data
    networks:
      - ragflow
-    restart: on-failure
+    restart: unless-stopped
    healthcheck:
      test: ["CMD", "redis-cli", "-a", "${REDIS_PASSWORD}", "ping"]
      interval: 10s
@ -228,7 +228,7 @@ services:
    networks:
      - ragflow
    command: ["--model-id", "/data/${TEI_MODEL}", "--auto-truncate"]
-    restart: on-failure
+    restart: unless-stopped


  tei-gpu:
@ -249,7 +249,7 @@ services:
            - driver: nvidia
              count: all
              capabilities: [gpu]
-    restart: on-failure
+    restart: unless-stopped


  kibana:
@ -271,7 +271,7 @@ services:
      retries: 120
    networks:
      - ragflow
-    restart: on-failure
+    restart: unless-stopped


 volumes:
--- a/docker/docker-compose-macos.yml
+++ b/docker/docker-compose-macos.yml
@ -22,7 +22,7 @@ services:
    env_file: .env
    networks:
      - ragflow
-    restart: on-failure
+    restart: unless-stopped
    # https://docs.docker.com/engine/daemon/prometheus/#create-a-prometheus-configuration
    # If you're using Docker Desktop, the --add-host flag is optional. This flag makes sure that the host's internal IP gets exposed to the Prometheus container.
    extra_hosts:
@ -39,7 +39,7 @@ services:
  #   entrypoint: "/ragflow/entrypoint_task_executor.sh 1 3"
  #   networks:
  #     - ragflow
-  #   restart: on-failure
+  #   restart: unless-stopped
  #   # https://docs.docker.com/engine/daemon/prometheus/#create-a-prometheus-configuration
  #   # If you're using Docker Desktop, the --add-host flag is optional. This flag makes sure that the host's internal IP gets exposed to the Prometheus container.
  #   extra_hosts:
--- a/docker/docker-compose.yml
+++ b/docker/docker-compose.yml
@ -45,7 +45,7 @@ services:
    env_file: .env
    networks:
      - ragflow
-    restart: on-failure
+    restart: unless-stopped
    # https://docs.docker.com/engine/daemon/prometheus/#create-a-prometheus-configuration
    # If you use Docker Desktop, the --add-host flag is optional. This flag ensures that the host's internal IP is exposed to the Prometheus container.
    extra_hosts:
@ -94,7 +94,7 @@ services:
    env_file: .env
    networks:
      - ragflow
-    restart: on-failure
+    restart: unless-stopped
    # https://docs.docker.com/engine/daemon/prometheus/#create-a-prometheus-configuration
    # If you use Docker Desktop, the --add-host flag is optional. This flag ensures that the host's internal IP is exposed to the Prometheus container.
    extra_hosts:
@ -120,7 +120,7 @@ services:
  #   entrypoint: "/ragflow/entrypoint_task_executor.sh 1 3"
  #   networks:
  #     - ragflow
-  #   restart: on-failure
+  #   restart: unless-stopped
  #   # https://docs.docker.com/engine/daemon/prometheus/#create-a-prometheus-configuration
  #   # If you're using Docker Desktop, the --add-host flag is optional. This flag makes sure that the host's internal IP gets exposed to the Prometheus container.
  #   extra_hosts:
--- a/docker/infinity_conf.toml
+++ b/docker/infinity_conf.toml
@ -1,5 +1,5 @@
 [general]
-version                  = "0.6.8"
+version                  = "0.6.10"
 time_zone                = "utc-8"

 [network]
--- a/docs/references/http_api_reference.md
+++ b/docs/references/http_api_reference.md
@ -512,13 +512,16 @@ curl --request POST \
      - Maximum: `2048`
    - `"delimiter"`: `string`
      - Defaults to `"\n"`.
-    - `"html4excel"`: `bool` Indicates whether to convert Excel documents into HTML format.
+    - `"html4excel"`: `bool`
+      - Whether to convert Excel documents into HTML format.
      - Defaults to `false`
    - `"layout_recognize"`: `string`
      - Defaults to `DeepDOC`
-    - `"tag_kb_ids"`: `array<string>` refer to [Use tag set](https://ragflow.io/docs/dev/use_tag_sets)
-      - Must include a list of dataset IDs, where each dataset is parsed using the Tag Chunking Method
-    - `"task_page_size"`: `int` For PDF only.
+    - `"tag_kb_ids"`: `array<string>`
+      - IDs of datasets to be parsed using the Tag chunk method.
+      - Before setting this, ensure a tag set is created and properly configured. For details, see [Use tag set](https://ragflow.io/docs/dev/use_tag_sets).
+    - `"task_page_size"`: `int`
+      - For PDFs only.
      - Defaults to `12`
      - Minimum: `1`
    - `"raptor"`: `object` RAPTOR-specific settings.
--- a/download_deps.py
+++ b/download_deps.py
@ -43,7 +43,6 @@ def get_urls(use_china_mirrors=False) -> list[Union[str, list[str]]]:
 repos = [
    "InfiniFlow/text_concat_xgb_v1.0",
    "InfiniFlow/deepdoc",
-    "InfiniFlow/huqie",
 ]


--- a/helm/values.yaml
+++ b/helm/values.yaml
@ -96,7 +96,7 @@ ragflow:
 infinity:
  image:
    repository: infiniflow/infinity
-    tag: v0.6.8
+    tag: v0.6.10
    pullPolicy: IfNotPresent
    pullSecrets: []
  storage:
--- a/pyproject.toml
+++ b/pyproject.toml
@ -49,7 +49,7 @@ dependencies = [
    "html-text==0.6.2",
    "httpx[socks]>=0.28.1,<0.29.0",
    "huggingface-hub>=0.25.0,<0.26.0",
-    "infinity-sdk==0.6.8",
+    "infinity-sdk==0.6.10",
    "infinity-emb>=0.0.66,<0.0.67",
    "itsdangerous==2.1.2",
    "json-repair==0.35.0",
--- a/rag/app/presentation.py
+++ b/rag/app/presentation.py
@ -86,9 +86,11 @@ class Pdf(PdfParser):

        # (A) Add text
        for b in self.boxes:
-            if not (from_page < b["page_number"] <= to_page + from_page):
+            # b["page_number"] is relative page number，must + from_page
+            global_page_num = b["page_number"] + from_page
+            if not (from_page < global_page_num <= to_page + from_page):
                continue
-            page_items[b["page_number"]].append({
+            page_items[global_page_num].append({
                "top": b["top"],
                "x0": b["x0"],
                "text": b["text"],
@ -100,7 +102,6 @@ class Pdf(PdfParser):
            if not positions:
                continue

-            # Handle content type (list vs str)
            if isinstance(content, list):
                final_text = "\n".join(content)
            elif isinstance(content, str):
@ -109,10 +110,11 @@ class Pdf(PdfParser):
                final_text = str(content)

            try:
-                # Parse positions
                pn_index = positions[0][0]
                if isinstance(pn_index, list):
                    pn_index = pn_index[0]
+
+                # pn_index in tbls is absolute page number
                current_page_num = int(pn_index) + 1
            except Exception as e:
                print(f"Error parsing position: {e}")
--- a/rag/prompts/generator.py
+++ b/rag/prompts/generator.py
@ -343,7 +343,8 @@ def form_history(history, limit=-6):
    return context


-def analyze_task(chat_mdl, prompt, task_name, tools_description: list[dict], user_defined_prompts: dict={}):
+
+async def analyze_task_async(chat_mdl, prompt, task_name, tools_description: list[dict], user_defined_prompts: dict={}):
    tools_desc = tool_schema(tools_description)
    context = ""

@ -352,7 +353,7 @@ def analyze_task(chat_mdl, prompt, task_name, tools_description: list[dict], use
    else:
        template = PROMPT_JINJA_ENV.from_string(ANALYZE_TASK_SYSTEM + "\n\n" + ANALYZE_TASK_USER)
    context = template.render(task=task_name, context=context, agent_prompt=prompt, tools_desc=tools_desc)
-    kwd = chat_mdl.chat(context, [{"role": "user", "content": "Please analyze it."}])
+    kwd = await _chat_async(chat_mdl, context, [{"role": "user", "content": "Please analyze it."}])
    if isinstance(kwd, tuple):
        kwd = kwd[0]
    kwd = re.sub(r"^.*</think>", "", kwd, flags=re.DOTALL)
@ -361,13 +362,17 @@ def analyze_task(chat_mdl, prompt, task_name, tools_description: list[dict], use
    return kwd


-async def analyze_task_async(chat_mdl, prompt, task_name, tools_description: list[dict], user_defined_prompts: dict={}):
-    return await asyncio.to_thread(analyze_task, chat_mdl, prompt, task_name, tools_description, user_defined_prompts)
+async def _chat_async(chat_mdl, system: str, history: list, **kwargs):
+    chat_async = getattr(chat_mdl, "async_chat", None)
+    if chat_async and asyncio.iscoroutinefunction(chat_async):
+        return await chat_async(system, history, **kwargs)
+    return await asyncio.to_thread(chat_mdl.chat, system, history, **kwargs)


-def next_step(chat_mdl, history:list, tools_description: list[dict], task_desc, user_defined_prompts: dict={}):
+
+async def next_step_async(chat_mdl, history:list, tools_description: list[dict], task_desc, user_defined_prompts: dict={}):
    if not tools_description:
-        return ""
+        return "", 0
    desc = tool_schema(tools_description)
    template = PROMPT_JINJA_ENV.from_string(user_defined_prompts.get("plan_generation", NEXT_STEP))
    user_prompt = "\nWhat's the next tool to call? If ready OR IMPOSSIBLE TO BE READY, then call `complete_task`."
@ -376,18 +381,18 @@ def next_step(chat_mdl, history:list, tools_description: list[dict], task_desc,
        hist[-1]["content"] += user_prompt
    else:
        hist.append({"role": "user", "content": user_prompt})
-    json_str = chat_mdl.chat(template.render(task_analysis=task_desc, desc=desc, today=datetime.datetime.now().strftime("%Y-%m-%d")),
-                             hist[1:], stop=["<|stop|>"])
+    json_str = await _chat_async(
+        chat_mdl,
+        template.render(task_analysis=task_desc, desc=desc, today=datetime.datetime.now().strftime("%Y-%m-%d")),
+        hist[1:],
+        stop=["<|stop|>"],
+    )
    tk_cnt = num_tokens_from_string(json_str)
    json_str = re.sub(r"^.*</think>", "", json_str, flags=re.DOTALL)
    return json_str, tk_cnt


-async def next_step_async(chat_mdl, history:list, tools_description: list[dict], task_desc, user_defined_prompts: dict={}):
-    return await asyncio.to_thread(next_step, chat_mdl, history, tools_description, task_desc, user_defined_prompts)
-
-
-def reflect(chat_mdl, history: list[dict], tool_call_res: list[Tuple], user_defined_prompts: dict={}):
+async def reflect_async(chat_mdl, history: list[dict], tool_call_res: list[Tuple], user_defined_prompts: dict={}):
    tool_calls = [{"name": p[0], "result": p[1]} for p in tool_call_res]
    goal = history[1]["content"]
    template = PROMPT_JINJA_ENV.from_string(user_defined_prompts.get("reflection", REFLECT))
@ -398,7 +403,7 @@ def reflect(chat_mdl, history: list[dict], tool_call_res: list[Tuple], user_defi
    else:
        hist.append({"role": "user", "content": user_prompt})
    _, msg = message_fit_in(hist, chat_mdl.max_length)
-    ans = chat_mdl.chat(msg[0]["content"], msg[1:])
+    ans = await _chat_async(chat_mdl, msg[0]["content"], msg[1:])
    ans = re.sub(r"^.*</think>", "", ans, flags=re.DOTALL)
    return """
 **Observation**
@ -429,23 +434,15 @@ def tool_call_summary(chat_mdl, name: str, params: dict, result: str, user_defin
    return re.sub(r"^.*</think>", "", ans, flags=re.DOTALL)


-def rank_memories(chat_mdl, goal:str, sub_goal:str, tool_call_summaries: list[str], user_defined_prompts: dict={}):
+async def rank_memories_async(chat_mdl, goal:str, sub_goal:str, tool_call_summaries: list[str], user_defined_prompts: dict={}):
    template = PROMPT_JINJA_ENV.from_string(RANK_MEMORY)
    system_prompt = template.render(goal=goal, sub_goal=sub_goal, results=[{"i": i, "content": s} for i,s in enumerate(tool_call_summaries)])
    user_prompt = " → rank: "
    _, msg = message_fit_in(form_message(system_prompt, user_prompt), chat_mdl.max_length)
-    ans = chat_mdl.chat(msg[0]["content"], msg[1:], stop="<|stop|>")
+    ans = await _chat_async(chat_mdl, msg[0]["content"], msg[1:], stop="<|stop|>")
    return re.sub(r"^.*</think>", "", ans, flags=re.DOTALL)


-async def reflect_async(chat_mdl, history: list[dict], tool_call_res: list[Tuple], user_defined_prompts: dict={}):
-    return await asyncio.to_thread(reflect, chat_mdl, history, tool_call_res, user_defined_prompts)
-
-
-async def rank_memories_async(chat_mdl, goal:str, sub_goal:str, tool_call_summaries: list[str], user_defined_prompts: dict={}):
-    return await asyncio.to_thread(rank_memories, chat_mdl, goal, sub_goal, tool_call_summaries, user_defined_prompts)
-
-
 def gen_meta_filter(chat_mdl, meta_data:dict, query: str) -> dict:
    meta_data_structure = {}
    for key, values in meta_data.items():
@ -514,7 +511,7 @@ def toc_index_extractor(toc:list[dict], content:str, chat_mdl):

    The structure variable is the numeric system which represents the index of the hierarchy section in the table of contents. For example, the first section has structure index 1, the first subsection has structure index 1.1, the second subsection has structure index 1.2, etc.

-    The response should be in the following JSON format: 
+    The response should be in the following JSON format:
    [
        {
            "structure": <structure index, "x.x.x" or None> (string),
@ -641,8 +638,8 @@ def toc_transformer(toc_pages, chat_mdl):

    The `structure` is the numeric system which represents the index of the hierarchy section in the table of contents. For example, the first section has structure index 1, the first subsection has structure index 1.1, the second subsection has structure index 1.2, etc.
    The `title` is a short phrase or a several-words term.
-    
-    The response should be in the following JSON format: 
+
+    The response should be in the following JSON format:
    [
        {
            "structure": <structure index, "x.x.x" or None> (string),
@ -667,7 +664,7 @@ def toc_transformer(toc_pages, chat_mdl):
    while not (if_complete == "yes"):
        prompt = f"""
        Your task is to continue the table of contents json structure, directly output the remaining part of the json structure.
-        The response should be in the following JSON format: 
+        The response should be in the following JSON format:

        The raw table of contents json structure is:
        {toc_content}
@ -756,7 +753,7 @@ async def run_toc_from_text(chunks, chat_mdl, callback=None):

    for chunk in chunks_res:
        titles.extend(chunk.get("toc", []))
-        
+
    # Filter out entries with title == -1
    prune = len(titles) > 512
    max_len = 12 if prune else 22
--- a/rag/res/huqie.txt
+++ b/rag/res/huqie.txt
--- a/rag/utils/gcs_conn.py
+++ b/rag/utils/gcs_conn.py
@ -0,0 +1,207 @@
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+
+import logging
+import time
+import datetime
+from io import BytesIO
+from google.cloud import storage
+from google.api_core.exceptions import NotFound
+from common.decorator import singleton
+from common import settings
+
+
+@singleton
+class RAGFlowGCS:
+    def __init__(self):
+        self.client = None
+        self.bucket_name = None
+        self.__open__()
+
+    def __open__(self):
+        try:
+            if self.client:
+                self.client = None
+        except Exception:
+            pass
+
+        try:
+            self.client = storage.Client()
+            self.bucket_name = settings.GCS["bucket"]
+        except Exception:
+            logging.exception("Fail to connect to GCS")
+
+    def _get_blob_path(self, folder, filename):
+        """Helper to construct the path: folder/filename"""
+        if not folder:
+            return filename
+        return f"{folder}/{filename}"
+
+    def health(self):
+        folder, fnm, binary = "ragflow-health", "health_check", b"_t@@@1"
+        try:
+            bucket_obj = self.client.bucket(self.bucket_name)
+            if not bucket_obj.exists():
+                logging.error(f"Health check failed: Main bucket '{self.bucket_name}' does not exist.")
+                return False
+
+            blob_path = self._get_blob_path(folder, fnm)
+            blob = bucket_obj.blob(blob_path)
+            blob.upload_from_file(BytesIO(binary), content_type='application/octet-stream')
+            return True
+        except Exception as e:
+            logging.exception(f"Health check failed: {e}")
+            return False
+
+    def put(self, bucket, fnm, binary, tenant_id=None):
+        # RENAMED PARAMETER: bucket_name -> bucket (to match interface)
+        for _ in range(3):
+            try:
+                bucket_obj = self.client.bucket(self.bucket_name)
+                blob_path = self._get_blob_path(bucket, fnm)
+                blob = bucket_obj.blob(blob_path)
+
+                blob.upload_from_file(BytesIO(binary), content_type='application/octet-stream')
+                return True
+            except NotFound:
+                logging.error(f"Fail to put: Main bucket {self.bucket_name} does not exist.")
+                return False
+            except Exception:
+                logging.exception(f"Fail to put {bucket}/{fnm}:")
+                self.__open__()
+                time.sleep(1)
+        return False
+
+    def rm(self, bucket, fnm, tenant_id=None):
+        # RENAMED PARAMETER: bucket_name -> bucket
+        try:
+            bucket_obj = self.client.bucket(self.bucket_name)
+            blob_path = self._get_blob_path(bucket, fnm)
+            blob = bucket_obj.blob(blob_path)
+            blob.delete()
+        except NotFound:
+            pass
+        except Exception:
+            logging.exception(f"Fail to remove {bucket}/{fnm}:")
+
+    def get(self, bucket, filename, tenant_id=None):
+        # RENAMED PARAMETER: bucket_name -> bucket
+        for _ in range(1):
+            try:
+                bucket_obj = self.client.bucket(self.bucket_name)
+                blob_path = self._get_blob_path(bucket, filename)
+                blob = bucket_obj.blob(blob_path)
+                return blob.download_as_bytes()
+            except NotFound:
+                logging.warning(f"File not found {bucket}/{filename} in {self.bucket_name}")
+                return None
+            except Exception:
+                logging.exception(f"Fail to get {bucket}/{filename}")
+                self.__open__()
+                time.sleep(1)
+        return None
+
+    def obj_exist(self, bucket, filename, tenant_id=None):
+        # RENAMED PARAMETER: bucket_name -> bucket
+        try:
+            bucket_obj = self.client.bucket(self.bucket_name)
+            blob_path = self._get_blob_path(bucket, filename)
+            blob = bucket_obj.blob(blob_path)
+            return blob.exists()
+        except Exception:
+            logging.exception(f"obj_exist {bucket}/{filename} got exception")
+            return False
+
+    def bucket_exists(self, bucket):
+        # RENAMED PARAMETER: bucket_name -> bucket
+        try:
+            bucket_obj = self.client.bucket(self.bucket_name)
+            return bucket_obj.exists()
+        except Exception:
+            logging.exception(f"bucket_exist check for {self.bucket_name} got exception")
+            return False
+
+    def get_presigned_url(self, bucket, fnm, expires, tenant_id=None):
+        # RENAMED PARAMETER: bucket_name -> bucket
+        for _ in range(10):
+            try:
+                bucket_obj = self.client.bucket(self.bucket_name)
+                blob_path = self._get_blob_path(bucket, fnm)
+                blob = bucket_obj.blob(blob_path)
+
+                expiration = expires
+                if isinstance(expires, int):
+                    expiration = datetime.timedelta(seconds=expires)
+
+                url = blob.generate_signed_url(
+                    version="v4",
+                    expiration=expiration,
+                    method="GET"
+                )
+                return url
+            except Exception:
+                logging.exception(f"Fail to get_presigned {bucket}/{fnm}:")
+                self.__open__()
+                time.sleep(1)
+        return None
+
+    def remove_bucket(self, bucket):
+        # RENAMED PARAMETER: bucket_name -> bucket
+        try:
+            bucket_obj = self.client.bucket(self.bucket_name)
+            prefix = f"{bucket}/"
+
+            blobs = list(self.client.list_blobs(self.bucket_name, prefix=prefix))
+
+            if blobs:
+                bucket_obj.delete_blobs(blobs)
+        except Exception:
+            logging.exception(f"Fail to remove virtual bucket (folder) {bucket}")
+
+    def copy(self, src_bucket, src_path, dest_bucket, dest_path):
+        # RENAMED PARAMETERS to match original interface
+        try:
+            bucket_obj = self.client.bucket(self.bucket_name)
+
+            src_blob_path = self._get_blob_path(src_bucket, src_path)
+            dest_blob_path = self._get_blob_path(dest_bucket, dest_path)
+
+            src_blob = bucket_obj.blob(src_blob_path)
+
+            if not src_blob.exists():
+                logging.error(f"Source object not found: {src_blob_path}")
+                return False
+
+            bucket_obj.copy_blob(src_blob, bucket_obj, dest_blob_path)
+            return True
+
+        except NotFound:
+            logging.error(f"Copy failed: Main bucket {self.bucket_name} does not exist.")
+            return False
+        except Exception:
+            logging.exception(f"Fail to copy {src_bucket}/{src_path} -> {dest_bucket}/{dest_path}")
+            return False
+
+    def move(self, src_bucket, src_path, dest_bucket, dest_path):
+        try:
+            if self.copy(src_bucket, src_path, dest_bucket, dest_path):
+                self.rm(src_bucket, src_path)
+                return True
+            else:
+                logging.error(f"Copy failed, move aborted: {src_bucket}/{src_path}")
+                return False
+        except Exception:
+            logging.exception(f"Fail to move {src_bucket}/{src_path} -> {dest_bucket}/{dest_path}")
+            return False
--- a/uv.lock
+++ b/uv.lock
@ -445,25 +445,25 @@ wheels = [

 [[package]]
 name = "bce-python-sdk"
-version = "0.9.54"
+version = "0.9.55"
 source = { registry = "https://pypi.tuna.tsinghua.edu.cn/simple" }
 dependencies = [
    { name = "future" },
    { name = "pycryptodome" },
    { name = "six" },
 ]
-sdist = { url = "https://pypi.tuna.tsinghua.edu.cn/packages/b3/c8/1c3bc30aa745ad4c3d073f150bddaf1d43ee6ee33f0b8ec60068494f511e/bce_python_sdk-0.9.54.tar.gz", hash = "sha256:f68026f40f11ea38ef445f50a7756009d5b703c7253438b138b30fb3b83be275", size = 275698, upload-time = "2025-11-27T02:28:50.24Z" }
+sdist = { url = "https://pypi.tuna.tsinghua.edu.cn/packages/ff/ae/f31ee3ccae94e1a07d8886a413f08c1581349e6cb45bf8b3c608fbf173e4/bce_python_sdk-0.9.55.tar.gz", hash = "sha256:bed63f8a0975f2e9daecf53417c3d5b803232ad87f35a0b16e25850710ce209c", size = 275733, upload-time = "2025-12-02T12:02:38.041Z" }
 wheels = [
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+    { url = "https://pypi.tuna.tsinghua.edu.cn/packages/8f/01/1b13a627e5f0239f24b168138d9a948e876d4b387c03f59d31699578c960/bce_python_sdk-0.9.55-py3-none-any.whl", hash = "sha256:6045d19d783b548644cce50a2f41ef5242da6654fb91b2c21629f309ca6dbf4c", size = 390463, upload-time = "2025-12-02T12:02:36.417Z" },
 ]

 [[package]]
 name = "beartype"
-version = "0.22.7"
+version = "0.22.8"
 source = { registry = "https://pypi.tuna.tsinghua.edu.cn/simple" }
-sdist = { url = "https://pypi.tuna.tsinghua.edu.cn/packages/2c/49/e28a77f8a3868b1c9ff6a030678e84de24c4783bae4c12cec9443cf8fb54/beartype-0.22.7.tar.gz", hash = "sha256:c7269855b71e32b7c9f0fc662baade752eb525107266e053338c2f6e8873826b", size = 1599627, upload-time = "2025-11-29T06:49:56.751Z" }
+sdist = { url = "https://pypi.tuna.tsinghua.edu.cn/packages/8c/1d/794ae2acaa67c8b216d91d5919da2606c2bb14086849ffde7f5555f3a3a5/beartype-0.22.8.tar.gz", hash = "sha256:b19b21c9359722ee3f7cc433f063b3e13997b27ae8226551ea5062e621f61165", size = 1602262, upload-time = "2025-12-03T05:11:10.766Z" }
 wheels = [
-    { url = "https://pypi.tuna.tsinghua.edu.cn/packages/f6/0c/a764253610513295b7f57904b91fae1d99c7afd1b16b6eaae06fdfb71fb5/beartype-0.22.7-py3-none-any.whl", hash = "sha256:e13430ac07c61fa4bc54d375970438aeb9aa47a482c529a6f438ce52e18e6f50", size = 1330771, upload-time = "2025-11-29T06:49:54.545Z" },
+    { url = "https://pypi.tuna.tsinghua.edu.cn/packages/14/2a/fbcbf5a025d3e71ddafad7efd43e34ec4362f4d523c3c471b457148fb211/beartype-0.22.8-py3-none-any.whl", hash = "sha256:b832882d04e41a4097bab9f63e6992bc6de58c414ee84cba9b45b67314f5ab2e", size = 1331895, upload-time = "2025-12-03T05:11:08.373Z" },
 ]

 [[package]]
@ -1910,11 +1910,11 @@ wheels = [

 [[package]]
 name = "fsspec"
-version = "2025.10.0"
+version = "2025.12.0"
 source = { registry = "https://pypi.tuna.tsinghua.edu.cn/simple" }
-sdist = { url = "https://pypi.tuna.tsinghua.edu.cn/packages/24/7f/2747c0d332b9acfa75dc84447a066fdf812b5a6b8d30472b74d309bfe8cb/fsspec-2025.10.0.tar.gz", hash = "sha256:b6789427626f068f9a83ca4e8a3cc050850b6c0f71f99ddb4f542b8266a26a59", size = 309285, upload-time = "2025-10-30T14:58:44.036Z" }
+sdist = { url = "https://pypi.tuna.tsinghua.edu.cn/packages/b6/27/954057b0d1f53f086f681755207dda6de6c660ce133c829158e8e8fe7895/fsspec-2025.12.0.tar.gz", hash = "sha256:c505de011584597b1060ff778bb664c1bc022e87921b0e4f10cc9c44f9635973", size = 309748, upload-time = "2025-12-03T15:23:42.687Z" }
 wheels = [
-    { url = "https://pypi.tuna.tsinghua.edu.cn/packages/eb/02/a6b21098b1d5d6249b7c5ab69dde30108a71e4e819d4a9778f1de1d5b70d/fsspec-2025.10.0-py3-none-any.whl", hash = "sha256:7c7712353ae7d875407f97715f0e1ffcc21e33d5b24556cb1e090ae9409ec61d", size = 200966, upload-time = "2025-10-30T14:58:42.53Z" },
+    { url = "https://pypi.tuna.tsinghua.edu.cn/packages/51/c7/b64cae5dba3a1b138d7123ec36bb5ccd39d39939f18454407e5468f4763f/fsspec-2025.12.0-py3-none-any.whl", hash = "sha256:8bf1fe301b7d8acfa6e8571e3b1c3d158f909666642431cc78a1b7b4dbc5ec5b", size = 201422, upload-time = "2025-12-03T15:23:41.434Z" },
 ]

 [[package]]
@ -2022,16 +2022,21 @@ wheels = [

 [[package]]
 name = "google-auth"
-version = "2.41.1"
+version = "2.43.0"
 source = { registry = "https://pypi.tuna.tsinghua.edu.cn/simple" }
 dependencies = [
    { name = "cachetools" },
    { name = "pyasn1-modules" },
    { name = "rsa" },
 ]
-sdist = { url = "https://pypi.tuna.tsinghua.edu.cn/packages/a8/af/5129ce5b2f9688d2fa49b463e544972a7c82b0fdb50980dafee92e121d9f/google_auth-2.41.1.tar.gz", hash = "sha256:b76b7b1f9e61f0cb7e88870d14f6a94aeef248959ef6992670efee37709cbfd2", size = 292284, upload-time = "2025-09-30T22:51:26.363Z" }
+sdist = { url = "https://pypi.tuna.tsinghua.edu.cn/packages/ff/ef/66d14cf0e01b08d2d51ffc3c20410c4e134a1548fc246a6081eae585a4fe/google_auth-2.43.0.tar.gz", hash = "sha256:88228eee5fc21b62a1b5fe773ca15e67778cb07dc8363adcb4a8827b52d81483", size = 296359, upload-time = "2025-11-06T00:13:36.587Z" }
 wheels = [
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+    { url = "https://pypi.tuna.tsinghua.edu.cn/packages/6f/d1/385110a9ae86d91cc14c5282c61fe9f4dc41c0b9f7d423c6ad77038c4448/google_auth-2.43.0-py2.py3-none-any.whl", hash = "sha256:af628ba6fa493f75c7e9dbe9373d148ca9f4399b5ea29976519e0a3848eddd16", size = 223114, upload-time = "2025-11-06T00:13:35.209Z" },
+]
+
+[package.optional-dependencies]
+requests = [
+    { name = "requests" },
 ]

 [[package]]
@ -2049,15 +2054,15 @@ wheels = [

 [[package]]
 name = "google-auth-oauthlib"
-version = "1.2.3"
+version = "1.2.2"
 source = { registry = "https://pypi.tuna.tsinghua.edu.cn/simple" }
 dependencies = [
    { name = "google-auth" },
    { name = "requests-oauthlib" },
 ]
-sdist = { url = "https://pypi.tuna.tsinghua.edu.cn/packages/86/a6/c6336a6ceb682709a4aa39e2e6b5754a458075ca92359512b6cbfcb25ae3/google_auth_oauthlib-1.2.3.tar.gz", hash = "sha256:eb09e450d3cc789ecbc2b3529cb94a713673fd5f7a22c718ad91cf75aedc2ea4", size = 21265, upload-time = "2025-10-30T21:28:19.105Z" }
+sdist = { url = "https://pypi.tuna.tsinghua.edu.cn/packages/fb/87/e10bf24f7bcffc1421b84d6f9c3377c30ec305d082cd737ddaa6d8f77f7c/google_auth_oauthlib-1.2.2.tar.gz", hash = "sha256:11046fb8d3348b296302dd939ace8af0a724042e8029c1b872d87fabc9f41684", size = 20955, upload-time = "2025-04-22T16:40:29.172Z" }
 wheels = [
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+    { url = "https://pypi.tuna.tsinghua.edu.cn/packages/ac/84/40ee070be95771acd2f4418981edb834979424565c3eec3cd88b6aa09d24/google_auth_oauthlib-1.2.2-py3-none-any.whl", hash = "sha256:fd619506f4b3908b5df17b65f39ca8d66ea56986e5472eb5978fd8f3786f00a2", size = 19072, upload-time = "2025-04-22T16:40:28.174Z" },
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 [[package]]
@ -2177,11 +2182,11 @@ wheels = [

 [[package]]
 name = "google-genai"
-version = "1.52.0"
+version = "1.53.0"
 source = { registry = "https://pypi.tuna.tsinghua.edu.cn/simple" }
 dependencies = [
    { name = "anyio" },
-    { name = "google-auth" },
+    { name = "google-auth", extra = ["requests"] },
    { name = "httpx" },
    { name = "pydantic" },
    { name = "requests" },
@ -2189,9 +2194,9 @@ dependencies = [
    { name = "typing-extensions" },
    { name = "websockets" },
 ]
-sdist = { url = "https://pypi.tuna.tsinghua.edu.cn/packages/09/4e/0ad8585d05312074bb69711b2d81cfed69ce0ae441913d57bf169bed20a7/google_genai-1.52.0.tar.gz", hash = "sha256:a74e8a4b3025f23aa98d6a0f84783119012ca6c336fd68f73c5d2b11465d7fc5", size = 258743, upload-time = "2025-11-21T02:18:55.742Z" }
+sdist = { url = "https://pypi.tuna.tsinghua.edu.cn/packages/de/b3/36fbfde2e21e6d3bc67780b61da33632f495ab1be08076cf0a16af74098f/google_genai-1.53.0.tar.gz", hash = "sha256:938a26d22f3fd32c6eeeb4276ef204ef82884e63af9842ce3eac05ceb39cbd8d", size = 260102, upload-time = "2025-12-03T17:21:23.233Z" }
 wheels = [
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+    { url = "https://pypi.tuna.tsinghua.edu.cn/packages/40/f2/97fefdd1ad1f3428321bac819ae7a83ccc59f6439616054736b7819fa56c/google_genai-1.53.0-py3-none-any.whl", hash = "sha256:65a3f99e5c03c372d872cda7419f5940e723374bb12a2f3ffd5e3e56e8eb2094", size = 262015, upload-time = "2025-12-03T17:21:21.934Z" },
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 [[package]]
@ -2776,7 +2781,7 @@ wheels = [

 [[package]]
 name = "infinity-sdk"
-version = "0.6.8"
+version = "0.6.10"
 source = { registry = "https://pypi.tuna.tsinghua.edu.cn/simple" }
 dependencies = [
    { name = "datrie" },
@ -2795,9 +2800,9 @@ dependencies = [
    { name = "sqlglot", extra = ["rs"] },
    { name = "thrift" },
 ]
-sdist = { url = "https://pypi.tuna.tsinghua.edu.cn/packages/a3/2d/4b699d62202319e5cbbcb4a7d9e87a86dde7ba7c767d0af4ebbee3de8419/infinity_sdk-0.6.8.tar.gz", hash = "sha256:e91c1f6cdf2fa41bc615c72be2a9e981211bd05b34522c1d27f1b825b905b125", size = 72669, upload-time = "2025-12-02T05:09:29.377Z" }
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+    { url = "https://pypi.tuna.tsinghua.edu.cn/packages/97/99/8857ea0805bd83fe092f5dca914a31f9fcc731c3800264657bd3ba950a1d/infinity_sdk-0.6.10-py3-none-any.whl", hash = "sha256:8f605039ec73d1b05d219105fbabef186e0178fddbad058c2c06c4873be48651", size = 29722107, upload-time = "2025-12-04T02:42:04.101Z" },
 ]

 [[package]]
@ -3077,7 +3082,7 @@ wheels = [

 [[package]]
 name = "langfuse"
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+    { url = "https://pypi.tuna.tsinghua.edu.cn/packages/47/6f/6223a1946fe24a979b8af3c7ae2d16c5451d8f35f2468782bd4af2c122da/sqlglotrs-0.8.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:4da1480cc288e02bd459e4638f212fa86a1fef81eb2cd69e6fdbdeb64e3df729", size = 303385, upload-time = "2025-12-02T16:58:26.052Z" },
+    { url = "https://pypi.tuna.tsinghua.edu.cn/packages/a0/98/55050208ef839cad740df6ca86f2f3ca895d469f6ce2040cba32d0b6c4a0/sqlglotrs-0.8.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:dc4a77df178b0ba242aba0e7cd775c3f9aef0fa79dfc31c6e642431ce690f51f", size = 341580, upload-time = "2025-12-02T16:57:36.197Z" },
+    { url = "https://pypi.tuna.tsinghua.edu.cn/packages/eb/f2/6f1d207e629fd4810cc826cf419acc386f3d43d32987684730fbc2399503/sqlglotrs-0.8.0-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:a8647d20cc5a9ff39071786169b3f1acf56f266483fa55386111783bca335f04", size = 348451, upload-time = "2025-12-02T16:57:43.756Z" },
+    { url = "https://pypi.tuna.tsinghua.edu.cn/packages/df/1b/fa8a0907471fe7be3754bac683a21c984b17672eef6958206473f683b63a/sqlglotrs-0.8.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1afdd6a0fa915b3aef7c801cbdc815bb39b3d6aecc4d5b04c4ce54d3f73d0013", size = 475703, upload-time = "2025-12-02T16:58:02.843Z" },
+    { url = "https://pypi.tuna.tsinghua.edu.cn/packages/92/56/f020c9c48d68883f6e24d69d18fe386eafc5963bc3982cc45013ec9b1ba0/sqlglotrs-0.8.0-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3b4c1edeb80f572cf3586b9a23d15f18f48ac8dc481eceabdbb85dc7dbf8a2ce", size = 365842, upload-time = "2025-12-02T16:58:10.847Z" },
+    { url = "https://pypi.tuna.tsinghua.edu.cn/packages/61/7b/091464f8aa2232a2f33028f9c9a2cbea7c4e5719400656f203592d46264d/sqlglotrs-0.8.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9b6d819f2753804d55b10e4320df08350cd2739556572a97ed1b1d7fc939f194", size = 348397, upload-time = "2025-12-02T16:58:18.567Z" },
+    { url = "https://pypi.tuna.tsinghua.edu.cn/packages/b7/1b/1b0cf0d41e8412786d1e80695778db799520223acf85c3ddc53c1200731f/sqlglotrs-0.8.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:dcf2cce002969cefb1466f2837c716d20fc9eac62b05043523fda25b3de4c444", size = 369756, upload-time = "2025-12-02T16:57:53.85Z" },
+    { url = "https://pypi.tuna.tsinghua.edu.cn/packages/31/6e/d9e50472aa92736751abf3d6fcad1c793f0701f17a553ae787e4a7581a1d/sqlglotrs-0.8.0-cp312-cp312-win32.whl", hash = "sha256:5459235a25b30eae508bcaea8bc6ebc04610acd87e985ba4d602981a94078384", size = 187891, upload-time = "2025-12-02T16:58:41.57Z" },
+    { url = "https://pypi.tuna.tsinghua.edu.cn/packages/3b/a2/21d09ff2065a7e883f8f68dcea57fb23f6f04ba7a193f2ac2895b5dfafae/sqlglotrs-0.8.0-cp312-cp312-win_amd64.whl", hash = "sha256:1e0de4fa8e6c54419bd63a1205f3218feb5e2649d72f1bc69c5261b6c333e63b", size = 200842, upload-time = "2025-12-02T16:58:48.181Z" },
 ]

 [[package]]
--- a/web/src/components/document-preview/doc-preview.tsx
+++ b/web/src/components/document-preview/doc-preview.tsx
@ -10,6 +10,10 @@ interface DocPreviewerProps {
  url: string;
 }

+// Word document preview component. Behavior:
+// 1) Fetches the document as a Blob.
+// 2) Detects .docx input via a ZIP header probe.
+// 3) Renders .docx using Mammoth; presents a controlled "unsupported" notice for non-ZIP payloads.
 export const DocPreviewer: React.FC<DocPreviewerProps> = ({
  className,
  url,
@ -17,6 +21,33 @@ export const DocPreviewer: React.FC<DocPreviewerProps> = ({
  const [htmlContent, setHtmlContent] = useState<string>('');
  const [loading, setLoading] = useState(false);

+  // Determines whether the Blob represents a .docx document by checking for the ZIP
+  // file signature ("PK") in the initial bytes. A valid .docx file is a ZIP container
+  // and always begins with:
+  //     50 4B 03 04  ("PK..")
+  //
+  // Legacy .doc files use the CFBF binary format, commonly starting with:
+  //     D0 CF 11 E0 A1 B1 1A E1
+  //
+  // Note that some files distributed with a “.doc” extension may internally be .docx
+  // documents (e.g., renamed files or files produced by systems that export .docx
+  // content under a .doc filename). These files will still present the ZIP signature
+  // and are therefore treated as supported .docx payloads. The header inspection
+  // ensures correct routing regardless of filename or reported extension.
+  const isZipLikeBlob = async (blob: Blob): Promise<boolean> => {
+    try {
+      const headerSlice = blob.slice(0, 4);
+      const buf = await headerSlice.arrayBuffer();
+      const bytes = new Uint8Array(buf);
+
+      // ZIP files start with "PK" (0x50, 0x4B)
+      return bytes.length >= 2 && bytes[0] === 0x50 && bytes[1] === 0x4b;
+    } catch (e) {
+      console.error('Failed to inspect blob header', e);
+      return false;
+    }
+  };
+
  const fetchDocument = async () => {
    if (!url) return;

@ -36,24 +67,21 @@ export const DocPreviewer: React.FC<DocPreviewerProps> = ({
      const contentType: string =
        blob.type || (res as any).headers?.['content-type'] || '';

-      // ---- Detect legacy .doc via MIME or URL ----
-      const cleanUrl = url.split(/[?#]/)[0].toLowerCase();
-      const isDocMime = /application\/msword/i.test(contentType);
-      const isLegacyDocByUrl =
-        cleanUrl.endsWith('.doc') && !cleanUrl.endsWith('.docx');
-      const isLegacyDoc = isDocMime || isLegacyDocByUrl;
+      // Execution path selection: ZIP-like payloads are treated as .docx and rendered via Mammoth;
+      // non-ZIP payloads receive an explicit unsupported notice.
+      const looksLikeZip = await isZipLikeBlob(blob);

-      if (isLegacyDoc) {
-        // Do not call mammoth and do not throw an error; instead, show a note in the preview area
+      if (!looksLikeZip) {
+        // Non-ZIP payload (likely legacy .doc or another format): skip Mammoth processing.
        setHtmlContent(`
          <div class="flex h-full items-center justify-center">
            <div class="border border-dashed border-border-normal rounded-xl p-8 max-w-2xl text-center">
              <p class="text-2xl font-bold mb-4">
-                Preview not available for .doc files
+                Preview is not available for this Word document
              </p>
              <p class="italic text-sm text-muted-foreground leading-relaxed">
-                Mammoth does not support <code>.doc</code> documents.<br/>
-                Inline preview is unavailable.
+                Mammoth supports modern <code>.docx</code> files only.<br/>
+                The file header does not indicate a <code>.docx</code> ZIP archive.
              </p>
            </div>
          </div>
@ -61,7 +89,7 @@ export const DocPreviewer: React.FC<DocPreviewerProps> = ({
        return;
      }

-      // ---- Standard .docx preview path ----
+      // ZIP-like payload: parse as .docx with Mammoth
      const arrayBuffer = await blob.arrayBuffer();
      const result = await mammoth.convertToHtml(
        { arrayBuffer },
@ -74,8 +102,7 @@ export const DocPreviewer: React.FC<DocPreviewerProps> = ({

      setHtmlContent(styledContent);
    } catch (err) {
-      // Only errors from the mammoth conversion path should surface here
-      message.error('Document parsing failed');
+      message.error('Failed to parse document.');
      console.error('Error parsing document:', err);
    } finally {
      setLoading(false);
--- a/web/src/components/json-edit/index.tsx
+++ b/web/src/components/json-edit/index.tsx
@ -1,8 +1,9 @@
-import React, { useEffect, useRef } from 'react';
+import React, { useEffect, useRef, useState } from 'react';
 import { useTranslation } from 'react-i18next';
 import './css/cloud9_night.less';
 import './css/index.less';
 import { JsonEditorOptions, JsonEditorProps } from './interface';
+
 const defaultConfig: JsonEditorOptions = {
  mode: 'code',
  modes: ['tree', 'code'],
@ -14,6 +15,7 @@ const defaultConfig: JsonEditorOptions = {
  enableTransform: false,
  indentation: 2,
 };
+
 const JsonEditor: React.FC<JsonEditorProps> = ({
  value,
  onChange,
@ -25,43 +27,62 @@ const JsonEditor: React.FC<JsonEditorProps> = ({
  const editorRef = useRef<any>(null);
  const { i18n } = useTranslation();
  const currentLanguageRef = useRef<string>(i18n.language);
+  const [isLoading, setIsLoading] = useState(true);

  useEffect(() => {
-    if (typeof window !== 'undefined') {
-      const JSONEditor = require('jsoneditor');
-      import('jsoneditor/dist/jsoneditor.min.css');
+    let isMounted = true;

-      if (containerRef.current) {
-        // Default configuration options
-        const defaultOptions: JsonEditorOptions = {
-          ...defaultConfig,
-          language: i18n.language === 'zh' ? 'zh-CN' : 'en',
-          onChange: () => {
-            if (editorRef.current && onChange) {
-              try {
-                const updatedJson = editorRef.current.get();
-                onChange(updatedJson);
-              } catch (err) {
-                // Do not trigger onChange when parsing error occurs
-                console.error(err);
-              }
+    const initEditor = async () => {
+      if (typeof window !== 'undefined') {
+        try {
+          const JSONEditorModule = await import('jsoneditor');
+          const JSONEditor = JSONEditorModule.default || JSONEditorModule;
+
+          await import('jsoneditor/dist/jsoneditor.min.css');
+
+          if (isMounted && containerRef.current) {
+            // Default configuration options
+            const defaultOptions: JsonEditorOptions = {
+              ...defaultConfig,
+              language: i18n.language === 'zh' ? 'zh-CN' : 'en',
+              onChange: () => {
+                if (editorRef.current && onChange) {
+                  try {
+                    const updatedJson = editorRef.current.get();
+                    onChange(updatedJson);
+                  } catch (err) {
+                    // Do not trigger onChange when parsing error occurs
+                    console.error(err);
+                  }
+                }
+              },
+              ...options, // Merge user provided options with defaults
+            };
+
+            editorRef.current = new JSONEditor(
+              containerRef.current,
+              defaultOptions,
+            );
+
+            if (value) {
+              editorRef.current.set(value);
            }
-          },
-          ...options, // Merge user provided options with defaults
-        };

-        editorRef.current = new JSONEditor(
-          containerRef.current,
-          defaultOptions,
-        );
-
-        if (value) {
-          editorRef.current.set(value);
+            setIsLoading(false);
+          }
+        } catch (error) {
+          console.error('Failed to load jsoneditor:', error);
+          if (isMounted) {
+            setIsLoading(false);
+          }
        }
      }
-    }
+    };
+
+    initEditor();

    return () => {
+      isMounted = false;
      if (editorRef.current) {
        if (typeof editorRef.current.destroy === 'function') {
          editorRef.current.destroy();
@ -92,26 +113,38 @@ const JsonEditor: React.FC<JsonEditorProps> = ({
      }

      // Recreate the editor with new language
-      const JSONEditor = require('jsoneditor');
+      const initEditorWithNewLanguage = async () => {
+        try {
+          const JSONEditorModule = await import('jsoneditor');
+          const JSONEditor = JSONEditorModule.default || JSONEditorModule;

-      const newOptions: JsonEditorOptions = {
-        ...defaultConfig,
-        language: i18n.language === 'zh' ? 'zh-CN' : 'en',
-        onChange: () => {
-          if (editorRef.current && onChange) {
-            try {
-              const updatedJson = editorRef.current.get();
-              onChange(updatedJson);
-            } catch (err) {
-              // Do not trigger onChange when parsing error occurs
-            }
-          }
-        },
-        ...options, // Merge user provided options with defaults
+          const newOptions: JsonEditorOptions = {
+            ...defaultConfig,
+            language: i18n.language === 'zh' ? 'zh-CN' : 'en',
+            onChange: () => {
+              if (editorRef.current && onChange) {
+                try {
+                  const updatedJson = editorRef.current.get();
+                  onChange(updatedJson);
+                } catch (err) {
+                  // Do not trigger onChange when parsing error occurs
+                }
+              }
+            },
+            ...options, // Merge user provided options with defaults
+          };
+
+          editorRef.current = new JSONEditor(containerRef.current, newOptions);
+          editorRef.current.set(currentData);
+        } catch (error) {
+          console.error(
+            'Failed to reload jsoneditor with new language:',
+            error,
+          );
+        }
      };

-      editorRef.current = new JSONEditor(containerRef.current, newOptions);
-      editorRef.current.set(currentData);
+      initEditorWithNewLanguage();
    }
  }, [i18n.language, value, onChange, options]);

@ -135,7 +168,13 @@ const JsonEditor: React.FC<JsonEditorProps> = ({
      ref={containerRef}
      style={{ height }}
      className={`ace-tomorrow-night w-full border border-border-button rounded-lg overflow-hidden bg-bg-input ${className} `}
-    />
+    >
+      {isLoading && (
+        <div className="flex items-center justify-center h-full">
+          <div className="text-text-secondary">Loading editor...</div>
+        </div>
+      )}
+    </div>
  );
 };

--- a/web/src/custom.d.ts
+++ b/web/src/custom.d.ts
@ -2,3 +2,9 @@ declare module '*.md' {
  const content: string;
  export default content;
 }
+
+declare module 'jsoneditor' {
+  const JSONEditor: any;
+  export default JSONEditor;
+  export = JSONEditor;
+}
--- a/web/src/pages/agent/canvas/index.tsx
+++ b/web/src/pages/agent/canvas/index.tsx
@ -40,6 +40,7 @@ import { useDropdownManager } from './context';

 import { AgentBackground } from '@/components/canvas/background';
 import Spotlight from '@/components/spotlight';
+import { useNodeLoading } from '../hooks/use-node-loading';
 import {
  useHideFormSheetOnNodeDeletion,
  useShowDrawer,
@ -166,6 +167,8 @@ function AgentCanvas({ drawerVisible, hideDrawer }: IProps) {
  });
  const [lastSendLoading, setLastSendLoading] = useState(false);

+  const [currentSendLoading, setCurrentSendLoading] = useState(false);
+
  const { handleBeforeDelete } = useBeforeDelete();

  const { addCanvasNode, addNoteNode } = useAddNode(reactFlowInstance);
@ -182,6 +185,7 @@ function AgentCanvas({ drawerVisible, hideDrawer }: IProps) {
  }, [chatVisible, clearEventList, currentTaskId, stopMessage]);

  const setLastSendLoadingFunc = (loading: boolean, messageId: string) => {
+    setCurrentSendLoading(!!loading);
    if (messageId === currentMessageId) {
      setLastSendLoading(loading);
    } else {
@ -249,7 +253,10 @@ function AgentCanvas({ drawerVisible, hideDrawer }: IProps) {
    clearActiveDropdown,
    removePlaceholderNode,
  ]);
-
+  const { lastNode, setDerivedMessages, startButNotFinishedNodeIds } =
+    useNodeLoading({
+      currentEventListWithoutMessageById,
+    });
  return (
    <div className={cn(styles.canvasWrapper, 'px-5 pb-5')}>
      <svg
@ -285,7 +292,15 @@ function AgentCanvas({ drawerVisible, hideDrawer }: IProps) {
          </marker>
        </defs>
      </svg>
-      <AgentInstanceContext.Provider value={{ addCanvasNode, showFormDrawer }}>
+      <AgentInstanceContext.Provider
+        value={{
+          addCanvasNode,
+          showFormDrawer,
+          lastNode,
+          currentSendLoading,
+          startButNotFinishedNodeIds,
+        }}
+      >
        <ReactFlow
          connectionMode={ConnectionMode.Loose}
          nodes={nodes}
@ -380,9 +395,10 @@ function AgentCanvas({ drawerVisible, hideDrawer }: IProps) {
          ></FormSheet>
        </AgentInstanceContext.Provider>
      )}
+
      {chatVisible && (
        <AgentChatContext.Provider
-          value={{ showLogSheet, setLastSendLoadingFunc }}
+          value={{ showLogSheet, setLastSendLoadingFunc, setDerivedMessages }}
        >
          <AgentChatLogContext.Provider
            value={{ addEventList, setCurrentMessageId }}
--- a/web/src/pages/agent/canvas/node/agent-node.tsx
+++ b/web/src/pages/agent/canvas/node/agent-node.tsx
@ -44,7 +44,7 @@ function InnerAgentNode({

  return (
    <ToolBar selected={selected} id={id} label={data.label}>
-      <NodeWrapper selected={selected}>
+      <NodeWrapper selected={selected} id={id}>
        {isHeadAgent && (
          <>
            <LeftEndHandle></LeftEndHandle>
--- a/web/src/pages/agent/canvas/node/begin-node.tsx
+++ b/web/src/pages/agent/canvas/node/begin-node.tsx
@ -24,7 +24,7 @@ function InnerBeginNode({ data, id, selected }: NodeProps<IBeginNode>) {
  const inputs: Record<string, BeginQuery> = get(data, 'form.inputs', {});

  return (
-    <NodeWrapper selected={selected}>
+    <NodeWrapper selected={selected} id={id}>
      <CommonHandle
        type="source"
        position={Position.Right}
--- a/web/src/pages/agent/canvas/node/categorize-node.tsx
+++ b/web/src/pages/agent/canvas/node/categorize-node.tsx
@ -18,7 +18,7 @@ export function InnerCategorizeNode({
  const { positions } = useBuildCategorizeHandlePositions({ data, id });
  return (
    <ToolBar selected={selected} id={id} label={data.label}>
-      <NodeWrapper selected={selected}>
+      <NodeWrapper selected={selected} id={id}>
        <LeftEndHandle></LeftEndHandle>

        <NodeHeader id={id} name={data.name} label={data.label}></NodeHeader>
--- a/web/src/pages/agent/canvas/node/exit-loop-node.tsx
+++ b/web/src/pages/agent/canvas/node/exit-loop-node.tsx
@ -14,7 +14,7 @@ export function ExitLoopNode({ id, data, selected }: NodeProps<BaseNode<any>>) {
      showRun={false}
      showCopy={false}
    >
-      <NodeWrapper selected={selected}>
+      <NodeWrapper selected={selected} id={id}>
        <LeftEndHandle></LeftEndHandle>
        <NodeHeader id={id} name={data.name} label={data.label}></NodeHeader>
      </NodeWrapper>
--- a/web/src/pages/agent/canvas/node/file-node.tsx
+++ b/web/src/pages/agent/canvas/node/file-node.tsx
@ -23,7 +23,7 @@ function InnerFileNode({ data, id, selected }: NodeProps<IBeginNode>) {
  const inputs: Record<string, BeginQuery> = get(data, 'form.inputs', {});

  return (
-    <NodeWrapper selected={selected}>
+    <NodeWrapper selected={selected} id={id}>
      <CommonHandle
        type="source"
        position={Position.Right}
--- a/web/src/pages/agent/canvas/node/index.tsx
+++ b/web/src/pages/agent/canvas/node/index.tsx
@ -26,7 +26,7 @@ function InnerRagNode({
      showRun={needsSingleStepDebugging(data.label)}
      showCopy={showCopyIcon(data.label)}
    >
-      <NodeWrapper selected={selected}>
+      <NodeWrapper selected={selected} id={id}>
        <LeftEndHandle></LeftEndHandle>
        <CommonHandle
          type="source"
--- a/web/src/pages/agent/canvas/node/message-node.tsx
+++ b/web/src/pages/agent/canvas/node/message-node.tsx
@ -16,7 +16,7 @@ function InnerMessageNode({ id, data, selected }: NodeProps<IMessageNode>) {
  const messages: string[] = get(data, 'form.content', []);
  return (
    <ToolBar selected={selected} id={id} label={data.label}>
-      <NodeWrapper selected={selected}>
+      <NodeWrapper selected={selected} id={id}>
        <LeftEndHandle></LeftEndHandle>
        <NodeHeader
          id={id}
--- a/web/src/pages/agent/canvas/node/node-wrapper.tsx
+++ b/web/src/pages/agent/canvas/node/node-wrapper.tsx
@ -1,9 +1,13 @@
 import { cn } from '@/lib/utils';
-import { HTMLAttributes } from 'react';
+import { Loader } from 'lucide-react';
+import { HTMLAttributes, useContext } from 'react';
+import { AgentInstanceContext } from '../../context';

 type IProps = HTMLAttributes<HTMLDivElement> & { selected?: boolean };

-export function NodeWrapper({ children, className, selected }: IProps) {
+export function NodeWrapper({ children, className, selected, id }: IProps) {
+  const { currentSendLoading, startButNotFinishedNodeIds = [] } =
+    useContext(AgentInstanceContext);
  return (
    <section
      className={cn(
@ -12,6 +16,13 @@ export function NodeWrapper({ children, className, selected }: IProps) {
        className,
      )}
    >
+      {id &&
+        startButNotFinishedNodeIds.indexOf(id as string) > -1 &&
+        currentSendLoading && (
+          <div className=" absolute right-0 left-0 top-0 flex items-start justify-end p-2">
+            <Loader size={12} className=" animate-spin" />
+          </div>
+        )}
      {children}
    </section>
  );
--- a/web/src/pages/agent/canvas/node/parser-node.tsx
+++ b/web/src/pages/agent/canvas/node/parser-node.tsx
@ -19,7 +19,7 @@ function ParserNode({
 }: NodeProps<BaseNode<ParserFormSchemaType>>) {
  const { t } = useTranslation();
  return (
-    <NodeWrapper selected={selected}>
+    <NodeWrapper selected={selected} id={id}>
      <CommonHandle
        id={NodeHandleId.End}
        type="target"
--- a/web/src/pages/agent/canvas/node/retrieval-node.tsx
+++ b/web/src/pages/agent/canvas/node/retrieval-node.tsx
@ -27,7 +27,7 @@ function InnerRetrievalNode({

  return (
    <ToolBar selected={selected} id={id} label={data.label}>
-      <NodeWrapper selected={selected}>
+      <NodeWrapper selected={selected} id={id}>
        <LeftEndHandle></LeftEndHandle>
        <CommonHandle
          id={NodeHandleId.Start}
--- a/web/src/pages/agent/canvas/node/splitter-node.tsx
+++ b/web/src/pages/agent/canvas/node/splitter-node.tsx
@ -25,7 +25,7 @@ function InnerSplitterNode({
      showCopy={false}
      showRun={false}
    >
-      <NodeWrapper selected={selected}>
+      <NodeWrapper selected={selected} id={id}>
        <CommonHandle
          id={NodeHandleId.End}
          type="target"
--- a/web/src/pages/agent/canvas/node/switch-node.tsx
+++ b/web/src/pages/agent/canvas/node/switch-node.tsx
@ -65,7 +65,7 @@ function InnerSwitchNode({ id, data, selected }: NodeProps<ISwitchNode>) {
  const { positions } = useBuildSwitchHandlePositions({ data, id });
  return (
    <ToolBar selected={selected} id={id} label={data.label} showRun={false}>
-      <NodeWrapper selected={selected}>
+      <NodeWrapper selected={selected} id={id}>
        <LeftEndHandle></LeftEndHandle>
        <NodeHeader id={id} name={data.name} label={data.label}></NodeHeader>
        <section className="gap-2.5 flex flex-col">
--- a/web/src/pages/agent/canvas/node/tokenizer-node.tsx
+++ b/web/src/pages/agent/canvas/node/tokenizer-node.tsx
@ -27,7 +27,7 @@ function TokenizerNode({
      showRun={false}
      showCopy={false}
    >
-      <NodeWrapper selected={selected}>
+      <NodeWrapper selected={selected} id={id}>
        <CommonHandle
          id={NodeHandleId.End}
          type="target"
--- a/web/src/pages/agent/canvas/node/tool-node.tsx
+++ b/web/src/pages/agent/canvas/node/tool-node.tsx
@ -44,7 +44,7 @@ function InnerToolNode({
  );

  return (
-    <NodeWrapper selected={selected}>
+    <NodeWrapper selected={selected} id={id}>
      <Handle
        id={NodeHandleId.End}
        type="target"
--- a/web/src/pages/agent/chat/box.tsx
+++ b/web/src/pages/agent/chat/box.tsx
@ -13,8 +13,9 @@ import {
 } from '@/hooks/use-agent-request';
 import { useFetchUserInfo } from '@/hooks/use-user-setting-request';
 import { buildMessageUuidWithRole } from '@/utils/chat';
-import { memo, useCallback } from 'react';
+import { memo, useCallback, useContext } from 'react';
 import { useParams } from 'umi';
+import { AgentChatContext } from '../context';
 import DebugContent from '../debug-content';
 import { useAwaitCompentData } from '../hooks/use-chat-logic';
 import { useIsTaskMode } from '../hooks/use-get-begin-query';
@ -49,6 +50,9 @@ function AgentChatBox() {
    canvasId: canvasId as string,
  });

+  const { setDerivedMessages } = useContext(AgentChatContext);
+  setDerivedMessages?.(derivedMessages);
+
  const isTaskMode = useIsTaskMode();

  const handleUploadFile: NonNullable<FileUploadProps['onUpload']> =
--- a/web/src/pages/agent/context.ts
+++ b/web/src/pages/agent/context.ts
@ -1,6 +1,8 @@
+import { INodeEvent } from '@/hooks/use-send-message';
+import { IMessage } from '@/interfaces/database/chat';
 import { RAGFlowNodeType } from '@/interfaces/database/flow';
 import { HandleType, Position } from '@xyflow/react';
-import { createContext } from 'react';
+import { Dispatch, SetStateAction, createContext } from 'react';
 import { useAddNode } from './hooks/use-add-node';
 import { useCacheChatLog } from './hooks/use-cache-chat-log';
 import { useShowFormDrawer, useShowLogSheet } from './hooks/use-show-drawer';
@ -13,7 +15,11 @@ type AgentInstanceContextType = Pick<
  ReturnType<typeof useAddNode>,
  'addCanvasNode'
 > &
-  Pick<ReturnType<typeof useShowFormDrawer>, 'showFormDrawer'>;
+  Pick<ReturnType<typeof useShowFormDrawer>, 'showFormDrawer'> & {
+    lastNode: INodeEvent | null;
+    currentSendLoading: boolean;
+    startButNotFinishedNodeIds: string[];
+  };

 export const AgentInstanceContext = createContext<AgentInstanceContextType>(
  {} as AgentInstanceContextType,
@ -22,7 +28,10 @@ export const AgentInstanceContext = createContext<AgentInstanceContextType>(
 type AgentChatContextType = Pick<
  ReturnType<typeof useShowLogSheet>,
  'showLogSheet'
-> & { setLastSendLoadingFunc: (loading: boolean, messageId: string) => void };
+> & {
+  setLastSendLoadingFunc: (loading: boolean, messageId: string) => void;
+  setDerivedMessages: Dispatch<SetStateAction<IMessage[] | undefined>>;
+};

 export const AgentChatContext = createContext<AgentChatContextType>(
  {} as AgentChatContextType,
--- a/web/src/pages/agent/form-sheet/next.tsx
+++ b/web/src/pages/agent/form-sheet/next.tsx
@ -55,7 +55,7 @@ const FormSheet = ({
    <Sheet open={visible} modal={false}>
      <SheetContent
        className={cn('top-20 p-0 flex flex-col pb-20', {
-          'right-[620px]': chatVisible,
+          'right-[clamp(0px,34%,620px)]': chatVisible,
        })}
        closeIcon={false}
      >
--- a/web/src/pages/agent/hooks/use-node-loading.ts
+++ b/web/src/pages/agent/hooks/use-node-loading.ts
@ -0,0 +1,88 @@
+import {
+  INodeData,
+  INodeEvent,
+  MessageEventType,
+} from '@/hooks/use-send-message';
+import { IMessage } from '@/interfaces/database/chat';
+import { useCallback, useMemo, useState } from 'react';
+
+export const useNodeLoading = ({
+  currentEventListWithoutMessageById,
+}: {
+  currentEventListWithoutMessageById: (messageId: string) => INodeEvent[];
+}) => {
+  const [derivedMessages, setDerivedMessages] = useState<IMessage[]>();
+
+  const lastMessageId = useMemo(() => {
+    return derivedMessages?.[derivedMessages?.length - 1]?.id;
+  }, [derivedMessages]);
+
+  const currentEventListWithoutMessage = useMemo(() => {
+    if (!lastMessageId) {
+      return [];
+    }
+    return currentEventListWithoutMessageById(lastMessageId);
+  }, [currentEventListWithoutMessageById, lastMessageId]);
+
+  const startedNodeList = useMemo(() => {
+    const duplicateList = currentEventListWithoutMessage?.filter(
+      (x) => x.event === MessageEventType.NodeStarted,
+    ) as INodeEvent[];
+
+    // Remove duplicate nodes
+    return duplicateList?.reduce<Array<INodeEvent>>((pre, cur) => {
+      if (pre.every((x) => x.data.component_id !== cur.data.component_id)) {
+        pre.push(cur);
+      }
+      return pre;
+    }, []);
+  }, [currentEventListWithoutMessage]);
+
+  const filterFinishedNodeList = useCallback(() => {
+    const nodeEventList = currentEventListWithoutMessage
+      .filter(
+        (x) => x.event === MessageEventType.NodeFinished,
+        // x.event === MessageEventType.NodeFinished &&
+        // (x.data as INodeData)?.component_id === componentId,
+      )
+      .map((x) => x.data);
+
+    return nodeEventList;
+  }, [currentEventListWithoutMessage]);
+
+  const lastNode = useMemo(() => {
+    if (!startedNodeList) {
+      return null;
+    }
+    return startedNodeList[startedNodeList.length - 1];
+  }, [startedNodeList]);
+
+  const startNodeIds = useMemo(() => {
+    if (!startedNodeList) {
+      return [];
+    }
+    return startedNodeList.map((x) => x.data.component_id);
+  }, [startedNodeList]);
+
+  const finishNodeIds = useMemo(() => {
+    if (!lastNode) {
+      return [];
+    }
+    const nodeDataList = filterFinishedNodeList();
+    const finishNodeIdsTemp = nodeDataList.map(
+      (x: INodeData) => x.component_id,
+    );
+    return Array.from(new Set(finishNodeIdsTemp));
+  }, [lastNode, filterFinishedNodeList]);
+
+  const startButNotFinishedNodeIds = useMemo(() => {
+    return startNodeIds.filter((x) => !finishNodeIds.includes(x));
+  }, [finishNodeIds, startNodeIds]);
+
+  return {
+    lastNode,
+    startButNotFinishedNodeIds,
+    filterFinishedNodeList,
+    setDerivedMessages,
+  };
+};
--- a/web/src/pages/agent/log-sheet/index.tsx
+++ b/web/src/pages/agent/log-sheet/index.tsx
@ -26,7 +26,7 @@ export function LogSheet({
  return (
    <Sheet open onOpenChange={hideModal} modal={false}>
      <SheetContent
-        className={cn('top-20 right-[620px]')}
+        className={cn('top-20 right-[clamp(0px,34%,620px)]')}
        onInteractOutside={(e) => e.preventDefault()}
      >
        <SheetHeader>
Author	SHA1	Message	Date
writinwaters	6c2c447a72	Doc: Updated Create dataset descriptions (#11742 ) ### What problem does this PR solve? ### Type of change - [x] Documentation Update	2025-12-04 17:07:52 +08:00
Jin Hai	e7022db9a4	Change docker container restart policy (#11695 ) ### What problem does this PR solve? Change the restart policy from 'on-failure' to 'unless-stopped'. ### Type of change - [x] Refactoring Signed-off-by: Jin Hai <haijin.chn@gmail.com>	2025-12-04 15:18:13 +08:00
qinling0210	ca4a0ee1b2	Remove huqie.txt from RAGFflow and bump infinity to 0.6.10 (#11661 ) ### What problem does this PR solve? huqie.txt and huqie.txt.trie are put to infinity-sdk in https://github.com/infiniflow/infinity/pull/3127. Remove huqie.txt from ragflow and bump infinity to 0.6.10 in this PR. ### Type of change - [x] Refactoring	2025-12-04 14:53:57 +08:00
Yongteng Lei	27b0550876	Refa: cleanup synchronous functions in agent_with_tools (#11736 ) ### What problem does this PR solve? Cleanup synchronous functions in agent_with_tools. ### Type of change - [x] Refactoring	2025-12-04 14:15:05 +08:00
Kevin Hu	797e03f843	Fix: none type error. (#11735 ) ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue)	2025-12-04 14:14:38 +08:00
Magicbook1108	b4e06237ef	Feat: detect docx support via header-byte inspection (#11731 ) ## What problem does this PR solve? Feat: detect docx support via header-byte inspection, a further optimize based on #11684 Not all files with a .doc extension are truly legacy .doc formats, and some are internally valid .docx documents. The previous implementation relied on URL suffix checks, which misclassified these cases and was therefore not reliable. Doc file could be previewed: [en2zh.doc](https://github.com/user-attachments/files/23921131/en2zh.doc) Doc file could not be previewed: [file-sample_100kB.doc](https://github.com/user-attachments/files/23921134/file-sample_100kB.doc) ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue)	2025-12-04 13:41:18 +08:00
chanx	751a13fb64	Feature：Add a loading status to the agent canvas page. (#11733 ) ### What problem does this PR solve? Feature：Add a loading status to the agent canvas page. ### Type of change - [x] New Feature (non-breaking change which adds functionality)	2025-12-04 13:40:49 +08:00
shirukai	fa7b857aa9	fix: resolve "'bool' object has no attribute 'items'" in SDK enabled … (#11725 ) ### What problem does this PR solve? Fixes the `AttributeError: 'bool' object has no attribute 'items'` error when updating the `enabled` parameter of a document via the Python SDK (Issue #11721). Background: When calling `Document.update({"enabled": True/False})` through the SDK, the server-side API returned a boolean `data=True` in the response (instead of a dictionary). The SDK's `_update_from_dict` method (in `base.py`) expects a dictionary to iterate over with `.items()`, leading to an immediate AttributeError during response parsing. This prevented successful synchronization of the updated `enabled` status to the local SDK object, even if the server-side database/update index operations succeeded. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) ### Additional Context (optional, for clarity) - Root Cause: Server returned `data=True` (boolean) for `enabled` parameter updates, violating the SDK's expectation of a dictionary-type `data` field. - Fix Logic: 1. Removed the separate `return get_result(data=True)` in the `enabled` update branch to unify response flow. 2. - Backward Compatibility: No breaking changes—other update scenarios (e.g., renaming documents, modifying chunk methods) remain unaffected, and the response format stays consistent. Co-authored-by: shirukai <shirukai@hollysysdigital.com>	2025-12-04 11:24:01 +08:00
rommy2017	257af75ece	Fix: relative page_number in boxes (#11712 ) page_number in boxes is relative page number，must + from_page ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue)	2025-12-04 11:23:34 +08:00
Wiratama	cbdacf21f6	feat(gcs): Add support for Google Cloud Storage (GCS) integration (#11718 ) ### What problem does this PR solve? This Pull Request introduces native support for Google Cloud Storage (GCS) as an optional object storage backend. Currently, RAGFlow relies on a limited set of storage options. This feature addresses the need for seamless integration with GCP environments, allowing users to leverage a fully managed, highly durable, and scalable storage service (GCS) instead of needing to deploy and maintain third-party object storage solutions. This simplifies deployment, especially for users running on GCP infrastructure like GKE or Cloud Run. The implementation uses a single GCS bucket defined via configuration, mapping RAGFlow's internal logical storage units (or "buckets") to folder prefixes within that GCS container to maintain data separation. This architectural choice avoids the operational complexities associated with dynamically creating and managing unique GCS buckets for every logical unit. ### Type of change - [x] New Feature (non-breaking change which adds functionality)	2025-12-04 10:44:05 +08:00
Stephen Hu	b1f3130519	Refactor: Remove useless for and add (#11720 ) ### What problem does this PR solve? Remove useless for and add ### Type of change - [x] Refactoring	2025-12-04 10:43:24 +08:00