Fix: meta data filter with AND logic operations. (#9687)

### What problem does this PR solve?

Close #9648

### Type of change

- [x] Bug Fix (non-breaking change which fixes an issue)

agent/canvas.py

@@ -131,7 +131,16 @@ class Canvas:
 
         self.path = self.dsl["path"]
         self.history = self.dsl["history"]
-        self.globals = self.dsl["globals"]
+        if "globals" in self.dsl:
+            self.globals = self.dsl["globals"]
+        else:
+            self.globals = {
+            "sys.query": "",
+            "sys.user_id": "",
+            "sys.conversation_turns": 0,
+            "sys.files": []
+        }
+            
         self.retrieval = self.dsl["retrieval"]
         self.memory = self.dsl.get("memory", [])
 
@@ -417,7 +426,7 @@ class Canvas:
         convs = []
         if window_size <= 0:
             return convs
-        for role, obj in self.history[window_size * -1:]:
+        for role, obj in self.history[window_size * -2:]:
             if isinstance(obj, dict):
                 convs.append({"role": role, "content": obj.get("content", "")})
             else:

agent/component/base.py

@@ -36,7 +36,7 @@ _IS_RAW_CONF = "_is_raw_conf"
 
 class ComponentParamBase(ABC):
     def __init__(self):
-        self.message_history_window_size = 22
+        self.message_history_window_size = 13
         self.inputs = {}
         self.outputs = {}
         self.description = ""

agent/component/llm.py

@@ -18,11 +18,8 @@ import logging
 import os
 import re
 from typing import Any, Generator
-
 import json_repair
-from copy import deepcopy
 from functools import partial
-
 from api.db import LLMType
 from api.db.services.llm_service import LLMBundle
 from api.db.services.tenant_llm_service import TenantLLMService
@@ -130,7 +127,7 @@ class LLM(ComponentBase):
 
         args = {}
         vars = self.get_input_elements() if not self._param.debug_inputs else self._param.debug_inputs
-        prompt = self._param.sys_prompt
+        sys_prompt = self._param.sys_prompt
         for k, o in vars.items():
             args[k] = o["value"]
             if not isinstance(args[k], str):
@@ -141,14 +138,18 @@ class LLM(ComponentBase):
             self.set_input_value(k, args[k])
 
         msg = self._canvas.get_history(self._param.message_history_window_size)[:-1]
-        msg.extend(deepcopy(self._param.prompts))
-        prompt = self.string_format(prompt, args)
+        for p in self._param.prompts:
+            if msg and msg[-1]["role"] == p["role"]:
+                continue
+            msg.append(p)
+
+        sys_prompt = self.string_format(sys_prompt, args)
         for m in msg:
             m["content"] = self.string_format(m["content"], args)
         if self._param.cite and self._canvas.get_reference()["chunks"]:
-            prompt += citation_prompt()
+            sys_prompt += citation_prompt()
 
-        return prompt, msg
+        return sys_prompt, msg
 
     def _generate(self, msg:list[dict], **kwargs) -> str:
         if not self.imgs:

agent/tools/code_exec.py

@@ -79,7 +79,7 @@ def main() -> dict:
     return {
         "result": fibonacci_recursive(100),
     }
-    
+
 Here's a code example for Javascript(`main` function MUST be included and exported):
 const axios = require('axios');
 async function main(args) {
@@ -156,7 +156,7 @@ class CodeExec(ToolBase, ABC):
             self.set_output("_ERROR", "construct code request error: " + str(e))
 
         try:
-            resp = requests.post(url=f"http://{settings.SANDBOX_HOST}:9385/run", json=code_req, timeout=10)
+            resp = requests.post(url=f"http://{settings.SANDBOX_HOST}:9385/run", json=code_req, timeout=os.environ.get("COMPONENT_EXEC_TIMEOUT", 10*60))
             logging.info(f"http://{settings.SANDBOX_HOST}:9385/run", code_req, resp.status_code)
             if resp.status_code != 200:
                 resp.raise_for_status()

api/apps/sdk/chat.py

@@ -150,10 +150,10 @@ def update(tenant_id, chat_id):
     if not DialogService.query(tenant_id=tenant_id, id=chat_id, status=StatusEnum.VALID.value):
         return get_error_data_result(message="You do not own the chat")
     req = request.json
-    ids = req.get("dataset_ids")
+    ids = req.get("dataset_ids", [])
     if "show_quotation" in req:
         req["do_refer"] = req.pop("show_quotation")
-    if ids is not None:
+    if ids:
         for kb_id in ids:
             kbs = KnowledgebaseService.accessible(kb_id=kb_id, user_id=tenant_id)
             if not kbs:

api/apps/sdk/dify_retrieval.py

@@ -24,6 +24,7 @@ from api.db.services.llm_service import LLMBundle
 from api import settings
 from api.utils.api_utils import validate_request, build_error_result, apikey_required
 from rag.app.tag import label_question
+from api.db.services.dialog_service import meta_filter
 
 
 @manager.route('/dify/retrieval', methods=['POST'])  # noqa: F821
@@ -37,18 +38,23 @@ def retrieval(tenant_id):
     retrieval_setting = req.get("retrieval_setting", {})
     similarity_threshold = float(retrieval_setting.get("score_threshold", 0.0))
     top = int(retrieval_setting.get("top_k", 1024))
-
+    metadata_condition = req.get("metadata_condition",{})
+    metas = DocumentService.get_meta_by_kbs([kb_id])
+ 
+    doc_ids = []
     try:
 
         e, kb = KnowledgebaseService.get_by_id(kb_id)
         if not e:
             return build_error_result(message="Knowledgebase not found!", code=settings.RetCode.NOT_FOUND)
 
-        if kb.tenant_id != tenant_id:
-            return build_error_result(message="Knowledgebase not found!", code=settings.RetCode.NOT_FOUND)
-
         embd_mdl = LLMBundle(kb.tenant_id, LLMType.EMBEDDING.value, llm_name=kb.embd_id)
-
+        print(metadata_condition)
+        print("after",convert_conditions(metadata_condition))
+        doc_ids.extend(meta_filter(metas, convert_conditions(metadata_condition)))
+        print("doc_ids",doc_ids)
+        if not doc_ids and metadata_condition is not None:
+            doc_ids = ['-999']
         ranks = settings.retrievaler.retrieval(
             question,
             embd_mdl,
@@ -59,6 +65,7 @@ def retrieval(tenant_id):
             similarity_threshold=similarity_threshold,
             vector_similarity_weight=0.3,
             top=top,
+            doc_ids=doc_ids,
             rank_feature=label_question(question, [kb])
         )
 
@@ -67,6 +74,7 @@ def retrieval(tenant_id):
                                                    [tenant_id],
                                                    [kb_id],
                                                    embd_mdl,
+                                                   doc_ids,
                                                    LLMBundle(kb.tenant_id, LLMType.CHAT))
             if ck["content_with_weight"]:
                 ranks["chunks"].insert(0, ck)
@@ -93,3 +101,20 @@ def retrieval(tenant_id):
             )
         logging.exception(e)
         return build_error_result(message=str(e), code=settings.RetCode.SERVER_ERROR)
+
+def convert_conditions(metadata_condition):
+    if metadata_condition is None:
+        metadata_condition = {}
+    op_mapping = {
+        "is": "=",
+        "not is": "≠"
+    }
+    return [
+    {
+        "op": op_mapping.get(cond["comparison_operator"], cond["comparison_operator"]),
+        "key": cond["name"],
+        "value": cond["value"]
+    }
+    for cond in metadata_condition.get("conditions", [])
+]
+

api/apps/sdk/session.py

@@ -84,18 +84,10 @@ def create_agent_session(tenant_id, agent_id):
     session_id=get_uuid()
     canvas = Canvas(cvs.dsl, tenant_id, agent_id)
     canvas.reset()
-    conv = {
-        "id": session_id,
-        "dialog_id": cvs.id,
-        "user_id": user_id,
-        "message": [],
-        "source": "agent",
-        "dsl": cvs.dsl
-    }
-    API4ConversationService.save(**conv)
-
+    
     cvs.dsl = json.loads(str(canvas))
     conv = {"id": session_id, "dialog_id": cvs.id, "user_id": user_id, "message": [{"role": "assistant", "content": canvas.get_prologue()}], "source": "agent", "dsl": cvs.dsl}
+    API4ConversationService.save(**conv)
     conv["agent_id"] = conv.pop("dialog_id")
     return get_result(data=conv)
 
@@ -450,37 +442,26 @@ def agents_completion_openai_compatibility(tenant_id, agent_id):
 def agent_completions(tenant_id, agent_id):
     req = request.json
 
-    ans = {}
+
     if req.get("stream", True):
-
-        def generate():
-            for answer in agent_completion(tenant_id=tenant_id, agent_id=agent_id, **req):
-                if isinstance(answer, str):
-                    try:
-                        ans = json.loads(answer[5:])  # remove "data:"
-                    except Exception:
-                        continue
-
-                if ans.get("event") != "message":
-                    continue
-
-                yield answer
-
-            yield "data:[DONE]\n\n"
-
-        resp = Response(generate(), mimetype="text/event-stream")
+        resp = Response(agent_completion(tenant_id=tenant_id, agent_id=agent_id, **req), mimetype="text/event-stream")
         resp.headers.add_header("Cache-control", "no-cache")
         resp.headers.add_header("Connection", "keep-alive")
         resp.headers.add_header("X-Accel-Buffering", "no")
         resp.headers.add_header("Content-Type", "text/event-stream; charset=utf-8")
         return resp
-
+    result = {}
     for answer in agent_completion(tenant_id=tenant_id, agent_id=agent_id, **req):
         try:
             ans = json.loads(answer[5:])  # remove "data:"
+            if not result:
+                result = ans.copy()
+            else:
+                result["data"]["answer"] += ans["data"]["answer"]
+                result["data"]["reference"] = ans["data"].get("reference", [])
         except Exception as e:
-            return get_result(data=f"**ERROR**: {str(e)}")
-    return get_result(data=ans)
+            return get_error_data_result(str(e))
+    return result
 
 
 @manager.route("/chats/<chat_id>/sessions", methods=["GET"])  # noqa: F821
@@ -581,6 +562,9 @@ def list_agent_session(tenant_id, agent_id):
                             "chunks" in conv["reference"][chunk_num]):
                         chunks = conv["reference"][chunk_num]["chunks"]
                         for chunk in chunks:
+                            # Ensure chunk is a dictionary before calling get method
+                            if not isinstance(chunk, dict):
+                                continue
                             new_chunk = {
                                 "id": chunk.get("chunk_id", chunk.get("id")),
                                 "content": chunk.get("content_with_weight", chunk.get("content")),
@@ -909,7 +893,7 @@ def ask_about_embedded():
     def stream():
         nonlocal req, uid
         try:
-            for ans in ask(req["question"], req["kb_ids"], uid, search_config):
+            for ans in ask(req["question"], req["kb_ids"], uid, search_config=search_config):
                 yield "data:" + json.dumps({"code": 0, "message": "", "data": ans}, ensure_ascii=False) + "\n\n"
         except Exception as e:
             yield "data:" + json.dumps({"code": 500, "message": str(e), "data": {"answer": "**ERROR**: " + str(e), "reference": []}}, ensure_ascii=False) + "\n\n"

api/db/services/canvas_service.py

@@ -134,6 +134,25 @@ class UserCanvasService(CommonService):
             return False
         return True
 
+
+def structure_answer(conv, ans, message_id, session_id):
+    if not conv:
+        return ans
+    content = ""
+    if ans["event"] == "message":
+        if ans["data"].get("start_to_think") is True:
+            content = "<think>"
+        elif ans["data"].get("end_to_think") is True:
+            content = "</think>"
+        else:
+            content = ans["data"]["content"]
+
+    reference = ans["data"].get("reference")
+    result = {"id": message_id, "session_id": session_id, "answer": content}
+    if reference:
+        result["reference"] = [reference]
+    return result
+
 def completion(tenant_id, agent_id, session_id=None, **kwargs):
     query = kwargs.get("query", "") or kwargs.get("question", "")
     files = kwargs.get("files", [])
@@ -163,7 +182,8 @@ def completion(tenant_id, agent_id, session_id=None, **kwargs):
             "user_id": user_id,
             "message": [],
             "source": "agent",
-            "dsl": cvs.dsl
+            "dsl": cvs.dsl,
+            "reference": []
         }
         API4ConversationService.save(**conv)
         conv = API4Conversation(**conv)
@@ -176,13 +196,14 @@ def completion(tenant_id, agent_id, session_id=None, **kwargs):
     })
     txt = ""
     for ans in canvas.run(query=query, files=files, user_id=user_id, inputs=inputs):
-        ans["session_id"] = session_id
-        if ans["event"] == "message":
-            txt += ans["data"]["content"]
-        yield "data:" + json.dumps(ans, ensure_ascii=False) + "\n\n"
+        ans = structure_answer(conv, ans, message_id, session_id)
+        txt += ans["answer"]
+        if ans.get("answer") or ans.get("reference"):
+            yield "data:" + json.dumps({"code": 0, "data": ans},
+                                       ensure_ascii=False) + "\n\n"
 
     conv.message.append({"role": "assistant", "content": txt, "created_at": time.time(), "id": message_id})
-    conv.reference = canvas.get_reference()
+    conv.reference.append(canvas.get_reference())
     conv.errors = canvas.error
     conv.dsl = str(canvas)
     conv = conv.to_dict()
@@ -211,11 +232,9 @@ def completionOpenAI(tenant_id, agent_id, question, session_id=None, stream=True
                     except Exception as e:
                         logging.exception(f"Agent OpenAI-Compatible completionOpenAI parse answer failed: {e}")
                         continue
-
-                if ans.get("event") != "message":
+                if not ans["data"]["answer"]:
                     continue
-
-                content_piece = ans["data"]["content"]
+                content_piece = ans["data"]["answer"]
                 completion_tokens += len(tiktokenenc.encode(content_piece))
 
                 yield "data: " + json.dumps(
@@ -260,9 +279,9 @@ def completionOpenAI(tenant_id, agent_id, question, session_id=None, stream=True
             ):
                 if isinstance(ans, str):
                     ans = json.loads(ans[5:])
-                if ans.get("event") != "message":
+                if not ans["data"]["answer"]:
                     continue
-                all_content += ans["data"]["content"]
+                all_content += ans["data"]["answer"]
 
             completion_tokens = len(tiktokenenc.encode(all_content))
 

api/db/services/dialog_service.py

@@ -256,10 +256,10 @@ def repair_bad_citation_formats(answer: str, kbinfos: dict, idx: set):
 
 
 def meta_filter(metas: dict, filters: list[dict]):
-    doc_ids = []
+    doc_ids = set([])
 
     def filter_out(v2docs, operator, value):
-        nonlocal doc_ids
+        ids = []
         for input, docids in v2docs.items():
             try:
                 input = float(input)
@@ -284,16 +284,24 @@ def meta_filter(metas: dict, filters: list[dict]):
                 ]:
                 try:
                     if all(conds):
-                        doc_ids.extend(docids)
+                        ids.extend(docids)
+                        break
                 except Exception:
                     pass
+        return ids
 
     for k, v2docs in metas.items():
         for f in filters:
             if k != f["key"]:
                 continue
-            filter_out(v2docs, f["op"], f["value"])
-    return doc_ids
+            ids = filter_out(v2docs, f["op"], f["value"])
+            if not doc_ids:
+                doc_ids = set(ids)
+            else:
+                doc_ids = doc_ids & set(ids)
+            if not doc_ids:
+                return []
+    return list(doc_ids)
 
 
 def chat(dialog, messages, stream=True, **kwargs):

api/db/services/llm_service.py

@@ -152,7 +152,7 @@ class LLMBundle(LLM4Tenant):
 
     def describe_with_prompt(self, image, prompt):
         if self.langfuse:
-            generation = self.language.start_generation(trace_context=self.trace_context, name="describe_with_prompt", metadata={"model": self.llm_name, "prompt": prompt})
+            generation = self.langfuse.start_generation(trace_context=self.trace_context, name="describe_with_prompt", metadata={"model": self.llm_name, "prompt": prompt})
 
         txt, used_tokens = self.mdl.describe_with_prompt(image, prompt)
         if not TenantLLMService.increase_usage(self.tenant_id, self.llm_type, used_tokens):

api/utils/api_utils.py

@@ -17,6 +17,7 @@ import asyncio
 import functools
 import json
 import logging
+import os
 import queue
 import random
 import threading
@@ -667,7 +668,10 @@ def timeout(seconds: float | int = None, attempts: int = 2, *, exception: Option
 
             for a in range(attempts):
                 try:
-                    result = result_queue.get(timeout=seconds)
+                    if os.environ.get("ENABLE_TIMEOUT_ASSERTION"):
+                        result = result_queue.get(timeout=seconds)
+                    else:
+                        result = result_queue.get()
                     if isinstance(result, Exception):
                         raise result
                     return result
@@ -682,7 +686,10 @@ def timeout(seconds: float | int = None, attempts: int = 2, *, exception: Option
 
             for a in range(attempts):
                 try:
-                    with trio.fail_after(seconds):
+                    if os.environ.get("ENABLE_TIMEOUT_ASSERTION"):
+                        with trio.fail_after(seconds):
+                            return await func(*args, **kwargs)
+                    else:
                         return await func(*args, **kwargs)
                 except trio.TooSlowError:
                     if a < attempts - 1:

deepdoc/parser/__init__.py

@@ -14,13 +14,15 @@
 #  limitations under the License.
 #
 
-from .pdf_parser import RAGFlowPdfParser as PdfParser, PlainParser
 from .docx_parser import RAGFlowDocxParser as DocxParser
 from .excel_parser import RAGFlowExcelParser as ExcelParser
-from .ppt_parser import RAGFlowPptParser as PptParser
 from .html_parser import RAGFlowHtmlParser as HtmlParser
 from .json_parser import RAGFlowJsonParser as JsonParser
+from .markdown_parser import MarkdownElementExtractor
 from .markdown_parser import RAGFlowMarkdownParser as MarkdownParser
+from .pdf_parser import PlainParser
+from .pdf_parser import RAGFlowPdfParser as PdfParser
+from .ppt_parser import RAGFlowPptParser as PptParser
 from .txt_parser import RAGFlowTxtParser as TxtParser
 
 __all__ = [
@@ -33,4 +35,6 @@ __all__ = [
     "JsonParser",
     "MarkdownParser",
     "TxtParser",
-]
+    "MarkdownElementExtractor",
+]
+

deepdoc/parser/markdown_parser.py

@@ -17,8 +17,10 @@
 
 import re
 
+import mistune
 from markdown import markdown
 
+
 class RAGFlowMarkdownParser:
     def __init__(self, chunk_token_num=128):
         self.chunk_token_num = int(chunk_token_num)
@@ -35,40 +37,44 @@ class RAGFlowMarkdownParser:
                 table_list.append(raw_table)
                 if separate_tables:
                     # Skip this match (i.e., remove it)
-                    new_text += working_text[last_end:match.start()] + "\n\n"
+                    new_text += working_text[last_end : match.start()] + "\n\n"
                 else:
                     # Replace with rendered HTML
-                    html_table = markdown(raw_table, extensions=['markdown.extensions.tables']) if render else raw_table
-                    new_text += working_text[last_end:match.start()] + html_table + "\n\n"
+                    html_table = markdown(raw_table, extensions=["markdown.extensions.tables"]) if render else raw_table
+                    new_text += working_text[last_end : match.start()] + html_table + "\n\n"
                 last_end = match.end()
             new_text += working_text[last_end:]
             return new_text
 
-        if "|" in markdown_text: # for optimize performance
+        if "|" in markdown_text:  # for optimize performance
             # Standard Markdown table
             border_table_pattern = re.compile(
-                r'''
+                r"""
                 (?:\n|^)
                 (?:\|.*?\|.*?\|.*?\n)
                 (?:\|(?:\s*[:-]+[-| :]*\s*)\|.*?\n)
                 (?:\|.*?\|.*?\|.*?\n)+
-            ''', re.VERBOSE)
+            """,
+                re.VERBOSE,
+            )
             working_text = replace_tables_with_rendered_html(border_table_pattern, tables)
 
             # Borderless Markdown table
             no_border_table_pattern = re.compile(
-                r'''
+                r"""
                 (?:\n|^)
                 (?:\S.*?\|.*?\n)
                 (?:(?:\s*[:-]+[-| :]*\s*).*?\n)
                 (?:\S.*?\|.*?\n)+
-                ''', re.VERBOSE)
+                """,
+                re.VERBOSE,
+            )
             working_text = replace_tables_with_rendered_html(no_border_table_pattern, tables)
 
-        if "<table>" in working_text.lower(): # for optimize performance
-            #HTML table extraction - handle possible html/body wrapper tags
+        if "<table>" in working_text.lower():  # for optimize performance
+            # HTML table extraction - handle possible html/body wrapper tags
             html_table_pattern = re.compile(
-            r'''
+                r"""
             (?:\n|^)
             \s*
             (?:
@@ -83,9 +89,10 @@ class RAGFlowMarkdownParser:
             )
             \s*
             (?=\n|$)
-            ''',
-            re.VERBOSE | re.DOTALL | re.IGNORECASE
+            """,
+                re.VERBOSE | re.DOTALL | re.IGNORECASE,
             )
+
             def replace_html_tables():
                 nonlocal working_text
                 new_text = ""
@@ -94,9 +101,9 @@ class RAGFlowMarkdownParser:
                     raw_table = match.group()
                     tables.append(raw_table)
                     if separate_tables:
-                        new_text += working_text[last_end:match.start()] + "\n\n"
+                        new_text += working_text[last_end : match.start()] + "\n\n"
                     else:
-                        new_text += working_text[last_end:match.start()] + raw_table + "\n\n"
+                        new_text += working_text[last_end : match.start()] + raw_table + "\n\n"
                     last_end = match.end()
                 new_text += working_text[last_end:]
                 working_text = new_text
@@ -104,3 +111,163 @@ class RAGFlowMarkdownParser:
             replace_html_tables()
 
         return working_text, tables
+
+
+class MarkdownElementExtractor:
+    def __init__(self, markdown_content):
+        self.markdown_content = markdown_content
+        self.lines = markdown_content.split("\n")
+        self.ast_parser = mistune.create_markdown(renderer="ast")
+        self.ast_nodes = self.ast_parser(markdown_content)
+
+    def extract_elements(self):
+        """Extract individual elements (headers, code blocks, lists, etc.)"""
+        sections = []
+
+        i = 0
+        while i < len(self.lines):
+            line = self.lines[i]
+
+            if re.match(r"^#{1,6}\s+.*$", line):
+                # header
+                element = self._extract_header(i)
+                sections.append(element["content"])
+                i = element["end_line"] + 1
+            elif line.strip().startswith("```"):
+                # code block
+                element = self._extract_code_block(i)
+                sections.append(element["content"])
+                i = element["end_line"] + 1
+            elif re.match(r"^\s*[-*+]\s+.*$", line) or re.match(r"^\s*\d+\.\s+.*$", line):
+                # list block
+                element = self._extract_list_block(i)
+                sections.append(element["content"])
+                i = element["end_line"] + 1
+            elif line.strip().startswith(">"):
+                # blockquote
+                element = self._extract_blockquote(i)
+                sections.append(element["content"])
+                i = element["end_line"] + 1
+            elif line.strip():
+                # text block (paragraphs and inline elements until next block element)
+                element = self._extract_text_block(i)
+                sections.append(element["content"])
+                i = element["end_line"] + 1
+            else:
+                i += 1
+
+        sections = [section for section in sections if section.strip()]
+        return sections
+
+    def _extract_header(self, start_pos):
+        return {
+            "type": "header",
+            "content": self.lines[start_pos],
+            "start_line": start_pos,
+            "end_line": start_pos,
+        }
+
+    def _extract_code_block(self, start_pos):
+        end_pos = start_pos
+        content_lines = [self.lines[start_pos]]
+
+        # Find the end of the code block
+        for i in range(start_pos + 1, len(self.lines)):
+            content_lines.append(self.lines[i])
+            end_pos = i
+            if self.lines[i].strip().startswith("```"):
+                break
+
+        return {
+            "type": "code_block",
+            "content": "\n".join(content_lines),
+            "start_line": start_pos,
+            "end_line": end_pos,
+        }
+
+    def _extract_list_block(self, start_pos):
+        end_pos = start_pos
+        content_lines = []
+
+        i = start_pos
+        while i < len(self.lines):
+            line = self.lines[i]
+            # check if this line is a list item or continuation of a list
+            if (
+                re.match(r"^\s*[-*+]\s+.*$", line)
+                or re.match(r"^\s*\d+\.\s+.*$", line)
+                or (i > start_pos and not line.strip())
+                or (i > start_pos and re.match(r"^\s{2,}[-*+]\s+.*$", line))
+                or (i > start_pos and re.match(r"^\s{2,}\d+\.\s+.*$", line))
+                or (i > start_pos and re.match(r"^\s+\w+.*$", line))
+            ):
+                content_lines.append(line)
+                end_pos = i
+                i += 1
+            else:
+                break
+
+        return {
+            "type": "list_block",
+            "content": "\n".join(content_lines),
+            "start_line": start_pos,
+            "end_line": end_pos,
+        }
+
+    def _extract_blockquote(self, start_pos):
+        end_pos = start_pos
+        content_lines = []
+
+        i = start_pos
+        while i < len(self.lines):
+            line = self.lines[i]
+            if line.strip().startswith(">") or (i > start_pos and not line.strip()):
+                content_lines.append(line)
+                end_pos = i
+                i += 1
+            else:
+                break
+
+        return {
+            "type": "blockquote",
+            "content": "\n".join(content_lines),
+            "start_line": start_pos,
+            "end_line": end_pos,
+        }
+
+    def _extract_text_block(self, start_pos):
+        """Extract a text block (paragraphs, inline elements) until next block element"""
+        end_pos = start_pos
+        content_lines = [self.lines[start_pos]]
+
+        i = start_pos + 1
+        while i < len(self.lines):
+            line = self.lines[i]
+            # stop if we encounter a block element
+            if re.match(r"^#{1,6}\s+.*$", line) or line.strip().startswith("```") or re.match(r"^\s*[-*+]\s+.*$", line) or re.match(r"^\s*\d+\.\s+.*$", line) or line.strip().startswith(">"):
+                break
+            elif not line.strip():
+                # check if the next line is a block element
+                if i + 1 < len(self.lines) and (
+                    re.match(r"^#{1,6}\s+.*$", self.lines[i + 1])
+                    or self.lines[i + 1].strip().startswith("```")
+                    or re.match(r"^\s*[-*+]\s+.*$", self.lines[i + 1])
+                    or re.match(r"^\s*\d+\.\s+.*$", self.lines[i + 1])
+                    or self.lines[i + 1].strip().startswith(">")
+                ):
+                    break
+                else:
+                    content_lines.append(line)
+                    end_pos = i
+                    i += 1
+            else:
+                content_lines.append(line)
+                end_pos = i
+                i += 1
+
+        return {
+            "type": "text_block",
+            "content": "\n".join(content_lines),
+            "start_line": start_pos,
+            "end_line": end_pos,
+        }

docs/references/http_api_reference.md

@@ -3501,7 +3501,7 @@ Failure:
 
 ### Generate related questions
 
-**POST** `/v1/sessions/related_questions`
+**POST** `/api/v1/sessions/related_questions`
 
 Generates five to ten alternative question strings from the user's original query to retrieve more relevant search results.
 
@@ -3516,7 +3516,7 @@ The chat model autonomously determines the number of questions to generate based
 #### Request
 
 - Method: POST
-- URL: `/v1/sessions/related_questions`
+- URL: `/api/v1/sessions/related_questions`
 - Headers:
   - `'content-Type: application/json'`
   - `'Authorization: Bearer <YOUR_LOGIN_TOKEN>'`
@@ -3528,7 +3528,7 @@ The chat model autonomously determines the number of questions to generate based
 
 ```bash
 curl --request POST \
-     --url http://{address}/v1/sessions/related_questions \
+     --url http://{address}/api/v1/sessions/related_questions \
      --header 'Content-Type: application/json' \
      --header 'Authorization: Bearer <YOUR_LOGIN_TOKEN>' \
      --data '

graphrag/entity_resolution.py

@@ -15,6 +15,7 @@
 #
 import logging
 import itertools
+import os
 import re
 from dataclasses import dataclass
 from typing import Any, Callable
@@ -106,7 +107,8 @@ class EntityResolution(Extractor):
             nonlocal remain_candidates_to_resolve, callback
             async with semaphore:
                 try:
-                    with trio.move_on_after(280) as cancel_scope:
+                    enable_timeout_assertion = os.environ.get("ENABLE_TIMEOUT_ASSERTION")
+                    with trio.move_on_after(280 if enable_timeout_assertion else 1000000000) as cancel_scope:
                         await self._resolve_candidate(candidate_batch, result_set, result_lock)
                         remain_candidates_to_resolve = remain_candidates_to_resolve - len(candidate_batch[1])
                         callback(msg=f"Resolved {len(candidate_batch[1])} pairs, {remain_candidates_to_resolve} are remained to resolve. ")
@@ -169,7 +171,8 @@ class EntityResolution(Extractor):
         logging.info(f"Created resolution prompt {len(text)} bytes for {len(candidate_resolution_i[1])} entity pairs of type {candidate_resolution_i[0]}")
         async with chat_limiter:
             try:
-                with trio.move_on_after(240) as cancel_scope:
+                enable_timeout_assertion = os.environ.get("ENABLE_TIMEOUT_ASSERTION")
+                with trio.move_on_after(280 if enable_timeout_assertion else 1000000000) as cancel_scope:
                     response = await trio.to_thread.run_sync(self._chat, text, [{"role": "user", "content": "Output:"}], {})
                 if cancel_scope.cancelled_caught:
                     logging.warning("_resolve_candidate._chat timeout, skipping...")

graphrag/general/community_reports_extractor.py

@@ -7,6 +7,7 @@ Reference:
 
 import logging
 import json
+import os
 import re
 from typing import Callable
 from dataclasses import dataclass
@@ -51,6 +52,7 @@ class CommunityReportsExtractor(Extractor):
         self._max_report_length = max_report_length or 1500
 
     async def __call__(self, graph: nx.Graph, callback: Callable | None = None):
+        enable_timeout_assertion = os.environ.get("ENABLE_TIMEOUT_ASSERTION")
         for node_degree in graph.degree:
             graph.nodes[str(node_degree[0])]["rank"] = int(node_degree[1])
 
@@ -92,7 +94,7 @@ class CommunityReportsExtractor(Extractor):
             text = perform_variable_replacements(self._extraction_prompt, variables=prompt_variables)
             async with chat_limiter:
                 try:
-                    with trio.move_on_after(180) as cancel_scope:
+                    with trio.move_on_after(180 if enable_timeout_assertion else 1000000000) as cancel_scope:
                         response = await trio.to_thread.run_sync( self._chat, text, [{"role": "user", "content": "Output:"}], {})
                     if cancel_scope.cancelled_caught:
                         logging.warning("extract_community_report._chat timeout, skipping...")

graphrag/general/extractor.py

@@ -47,7 +47,7 @@ class Extractor:
         self._language = language
         self._entity_types = entity_types or DEFAULT_ENTITY_TYPES
 
-    @timeout(60*5)
+    @timeout(60*20)
     def _chat(self, system, history, gen_conf={}):
         hist = deepcopy(history)
         conf = deepcopy(gen_conf)

graphrag/general/index.py

@@ -15,6 +15,8 @@
 #
 import json
 import logging
+import os
+
 import networkx as nx
 import trio
 
@@ -49,6 +51,7 @@ async def run_graphrag(
     embedding_model,
     callback,
 ):
+    enable_timeout_assertion=os.environ.get("ENABLE_TIMEOUT_ASSERTION")
     start = trio.current_time()
     tenant_id, kb_id, doc_id = row["tenant_id"], str(row["kb_id"]), row["doc_id"]
     chunks = []
@@ -57,7 +60,7 @@ async def run_graphrag(
     ):
         chunks.append(d["content_with_weight"])
 
-    with trio.fail_after(max(120, len(chunks)*120)):
+    with trio.fail_after(max(120, len(chunks)*60*10) if enable_timeout_assertion else 10000000000):
         subgraph = await generate_subgraph(
             LightKGExt
             if "method" not in row["kb_parser_config"].get("graphrag", {}) or row["kb_parser_config"]["graphrag"]["method"] != "general"

graphrag/light/graph_prompt.py

@@ -130,7 +130,36 @@ Output:
 
 PROMPTS[
     "entiti_continue_extraction"
-] = """MANY entities were missed in the last extraction.  Add them below using the same format:
+] = """
+MANY entities and relationships were missed in the last extraction. Please find only the missing entities and relationships from previous text.
+
+---Remember Steps---
+
+1. Identify all entities. For each identified entity, extract the following information:
+- entity_name: Name of the entity, use same language as input text. If English, capitalized the name
+- entity_type: One of the following types: [{entity_types}]
+- entity_description: Provide a comprehensive description of the entity's attributes and activities *based solely on the information present in the input text*. **Do not infer or hallucinate information not explicitly stated.** If the text provides insufficient information to create a comprehensive description, state "Description not available in text."
+Format each entity as ("entity"{tuple_delimiter}<entity_name>{tuple_delimiter}<entity_type>{tuple_delimiter}<entity_description>)
+
+2. From the entities identified in step 1, identify all pairs of (source_entity, target_entity) that are *clearly related* to each other.
+For each pair of related entities, extract the following information:
+- source_entity: name of the source entity, as identified in step 1
+- target_entity: name of the target entity, as identified in step 1
+- relationship_description: explanation as to why you think the source entity and the target entity are related to each other
+- relationship_strength: a numeric score indicating strength of the relationship between the source entity and target entity
+- relationship_keywords: one or more high-level key words that summarize the overarching nature of the relationship, focusing on concepts or themes rather than specific details
+Format each relationship as ("relationship"{tuple_delimiter}<source_entity>{tuple_delimiter}<target_entity>{tuple_delimiter}<relationship_description>{tuple_delimiter}<relationship_keywords>{tuple_delimiter}<relationship_strength>)
+
+3. Identify high-level key words that summarize the main concepts, themes, or topics of the entire text. These should capture the overarching ideas present in the document.
+Format the content-level key words as ("content_keywords"{tuple_delimiter}<high_level_keywords>)
+
+4. Return output in {language} as a single list of all the entities and relationships identified in steps 1 and 2. Use **{record_delimiter}** as the list delimiter.
+
+5. When finished, output {completion_delimiter}
+
+---Output---
+
+Add new entities and relations below using the same format, and do not include entities and relations that have been previously extracted. :
 """
 
 PROMPTS[
@@ -252,4 +281,4 @@ When handling information with timestamps:
 - List up to 5 most important reference sources at the end under "References", clearly indicating whether each source is from Knowledge Graph (KG) or Vector Data (VD)
   Format: [KG/VD] Source content
 
-Add sections and commentary to the response as appropriate for the length and format. If the provided information is insufficient to answer the question, clearly state that you don't know or cannot provide an answer in the same language as the user's question."""
+Add sections and commentary to the response as appropriate for the length and format. If the provided information is insufficient to answer the question, clearly state that you don't know or cannot provide an answer in the same language as the user's question."""

graphrag/utils.py

@@ -307,6 +307,7 @@ def chunk_id(chunk):
 
 async def graph_node_to_chunk(kb_id, embd_mdl, ent_name, meta, chunks):
     global chat_limiter
+    enable_timeout_assertion=os.environ.get("ENABLE_TIMEOUT_ASSERTION")
     chunk = {
         "id": get_uuid(),
         "important_kwd": [ent_name],
@@ -324,7 +325,7 @@ async def graph_node_to_chunk(kb_id, embd_mdl, ent_name, meta, chunks):
     ebd = get_embed_cache(embd_mdl.llm_name, ent_name)
     if ebd is None:
         async with chat_limiter:
-            with trio.fail_after(3):
+            with trio.fail_after(3 if enable_timeout_assertion else 30000000):
                 ebd, _ = await trio.to_thread.run_sync(lambda: embd_mdl.encode([ent_name]))
         ebd = ebd[0]
         set_embed_cache(embd_mdl.llm_name, ent_name, ebd)
@@ -362,6 +363,7 @@ def get_relation(tenant_id, kb_id, from_ent_name, to_ent_name, size=1):
 
 
 async def graph_edge_to_chunk(kb_id, embd_mdl, from_ent_name, to_ent_name, meta, chunks):
+    enable_timeout_assertion=os.environ.get("ENABLE_TIMEOUT_ASSERTION")
     chunk = {
         "id": get_uuid(),
         "from_entity_kwd": from_ent_name,
@@ -380,7 +382,7 @@ async def graph_edge_to_chunk(kb_id, embd_mdl, from_ent_name, to_ent_name, meta,
     ebd = get_embed_cache(embd_mdl.llm_name, txt)
     if ebd is None:
         async with chat_limiter:
-            with trio.fail_after(3):
+            with trio.fail_after(3 if enable_timeout_assertion else 300000000):
                 ebd, _ = await trio.to_thread.run_sync(lambda: embd_mdl.encode([txt+f": {meta['description']}"]))
         ebd = ebd[0]
         set_embed_cache(embd_mdl.llm_name, txt, ebd)
@@ -514,9 +516,10 @@ async def set_graph(tenant_id: str, kb_id: str, embd_mdl, graph: nx.Graph, chang
         callback(msg=f"set_graph converted graph change to {len(chunks)} chunks in {now - start:.2f}s.")
     start = now
 
+    enable_timeout_assertion=os.environ.get("ENABLE_TIMEOUT_ASSERTION")
     es_bulk_size = 4
     for b in range(0, len(chunks), es_bulk_size):
-        with trio.fail_after(3):
+        with trio.fail_after(3 if enable_timeout_assertion else 30000000):
             doc_store_result = await trio.to_thread.run_sync(lambda: settings.docStoreConn.insert(chunks[b:b + es_bulk_size], search.index_name(tenant_id), kb_id))
         if b % 100 == es_bulk_size and callback:
             callback(msg=f"Insert chunks: {b}/{len(chunks)}")

mcp/server/server.py

@@ -16,6 +16,9 @@
 
 import json
 import logging
+import random
+import time
+from collections import OrderedDict
 from collections.abc import AsyncIterator
 from contextlib import asynccontextmanager
 from functools import wraps
@@ -53,6 +56,13 @@ JSON_RESPONSE = True
 
 
 class RAGFlowConnector:
+    _MAX_DATASET_CACHE = 32
+    _MAX_DOCUMENT_CACHE = 128
+    _CACHE_TTL = 300
+
+    _dataset_metadata_cache: OrderedDict[str, tuple[dict, float | int]] = OrderedDict()  # "dataset_id" -> (metadata, expiry_ts)
+    _document_metadata_cache: OrderedDict[str, tuple[list[tuple[str, dict]], float | int]] = OrderedDict()  # "dataset_id" -> ([(document_id, doc_metadata)], expiry_ts)
+
     def __init__(self, base_url: str, version="v1"):
         self.base_url = base_url
         self.version = version
@@ -72,6 +82,43 @@ class RAGFlowConnector:
         res = requests.get(url=self.api_url + path, params=params, headers=self.authorization_header, json=json)
         return res
 
+    def _is_cache_valid(self, ts):
+        return time.time() < ts
+
+    def _get_expiry_timestamp(self):
+        offset = random.randint(-30, 30)
+        return time.time() + self._CACHE_TTL + offset
+
+    def _get_cached_dataset_metadata(self, dataset_id):
+        entry = self._dataset_metadata_cache.get(dataset_id)
+        if entry:
+            data, ts = entry
+            if self._is_cache_valid(ts):
+                self._dataset_metadata_cache.move_to_end(dataset_id)
+                return data
+        return None
+
+    def _set_cached_dataset_metadata(self, dataset_id, metadata):
+        self._dataset_metadata_cache[dataset_id] = (metadata, self._get_expiry_timestamp())
+        self._dataset_metadata_cache.move_to_end(dataset_id)
+        if len(self._dataset_metadata_cache) > self._MAX_DATASET_CACHE:
+            self._dataset_metadata_cache.popitem(last=False)
+
+    def _get_cached_document_metadata_by_dataset(self, dataset_id):
+        entry = self._document_metadata_cache.get(dataset_id)
+        if entry:
+            data_list, ts = entry
+            if self._is_cache_valid(ts):
+                self._document_metadata_cache.move_to_end(dataset_id)
+                return {doc_id: doc_meta for doc_id, doc_meta in data_list}
+        return None
+
+    def _set_cached_document_metadata_by_dataset(self, dataset_id, doc_id_meta_list):
+        self._document_metadata_cache[dataset_id] = (doc_id_meta_list, self._get_expiry_timestamp())
+        self._document_metadata_cache.move_to_end(dataset_id)
+        if len(self._document_metadata_cache) > self._MAX_DOCUMENT_CACHE:
+            self._document_metadata_cache.popitem(last=False)
+
     def list_datasets(self, page: int = 1, page_size: int = 1000, orderby: str = "create_time", desc: bool = True, id: str | None = None, name: str | None = None):
         res = self._get("/datasets", {"page": page, "page_size": page_size, "orderby": orderby, "desc": desc, "id": id, "name": name})
         if not res:
@@ -87,10 +134,38 @@ class RAGFlowConnector:
         return ""
 
     def retrieval(
-        self, dataset_ids, document_ids=None, question="", page=1, page_size=30, similarity_threshold=0.2, vector_similarity_weight=0.3, top_k=1024, rerank_id: str | None = None, keyword: bool = False
+        self,
+        dataset_ids,
+        document_ids=None,
+        question="",
+        page=1,
+        page_size=30,
+        similarity_threshold=0.2,
+        vector_similarity_weight=0.3,
+        top_k=1024,
+        rerank_id: str | None = None,
+        keyword: bool = False,
+        force_refresh: bool = False,
     ):
         if document_ids is None:
             document_ids = []
+        
+        # If no dataset_ids provided or empty list, get all available dataset IDs
+        if not dataset_ids:
+            dataset_list_str = self.list_datasets()
+            dataset_ids = []
+            
+            # Parse the dataset list to extract IDs
+            if dataset_list_str:
+                for line in dataset_list_str.strip().split('\n'):
+                    if line.strip():
+                        try:
+                            dataset_info = json.loads(line.strip())
+                            dataset_ids.append(dataset_info["id"])
+                        except (json.JSONDecodeError, KeyError):
+                            # Skip malformed lines
+                            continue
+        
         data_json = {
             "page": page,
             "page_size": page_size,
@@ -110,12 +185,127 @@ class RAGFlowConnector:
 
         res = res.json()
         if res.get("code") == 0:
+            data = res["data"]
             chunks = []
-            for chunk_data in res["data"].get("chunks"):
-                chunks.append(json.dumps(chunk_data, ensure_ascii=False))
-            return [types.TextContent(type="text", text="\n".join(chunks))]
+
+            # Cache document metadata and dataset information
+            document_cache, dataset_cache = self._get_document_metadata_cache(dataset_ids, force_refresh=force_refresh)
+
+            # Process chunks with enhanced field mapping including per-chunk metadata
+            for chunk_data in data.get("chunks", []):
+                enhanced_chunk = self._map_chunk_fields(chunk_data, dataset_cache, document_cache)
+                chunks.append(enhanced_chunk)
+
+            # Build structured response (no longer need response-level document_metadata)
+            response = {
+                "chunks": chunks,
+                "pagination": {
+                    "page": data.get("page", page),
+                    "page_size": data.get("page_size", page_size),
+                    "total_chunks": data.get("total", len(chunks)),
+                    "total_pages": (data.get("total", len(chunks)) + page_size - 1) // page_size,
+                },
+                "query_info": {
+                    "question": question,
+                    "similarity_threshold": similarity_threshold,
+                    "vector_weight": vector_similarity_weight,
+                    "keyword_search": keyword,
+                    "dataset_count": len(dataset_ids),
+                },
+            }
+
+            return [types.TextContent(type="text", text=json.dumps(response, ensure_ascii=False))]
+
         raise Exception([types.TextContent(type="text", text=res.get("message"))])
 
+    def _get_document_metadata_cache(self, dataset_ids, force_refresh=False):
+        """Cache document metadata for all documents in the specified datasets"""
+        document_cache = {}
+        dataset_cache = {}
+
+        try:
+            for dataset_id in dataset_ids:
+                dataset_meta = None if force_refresh else self._get_cached_dataset_metadata(dataset_id)
+                if not dataset_meta:
+                    # First get dataset info for name
+                    dataset_res = self._get("/datasets", {"id": dataset_id, "page_size": 1})
+                    if dataset_res and dataset_res.status_code == 200:
+                        dataset_data = dataset_res.json()
+                        if dataset_data.get("code") == 0 and dataset_data.get("data"):
+                            dataset_info = dataset_data["data"][0]
+                            dataset_meta = {"name": dataset_info.get("name", "Unknown"), "description": dataset_info.get("description", "")}
+                            self._set_cached_dataset_metadata(dataset_id, dataset_meta)
+                if dataset_meta:
+                    dataset_cache[dataset_id] = dataset_meta
+
+                docs = None if force_refresh else self._get_cached_document_metadata_by_dataset(dataset_id)
+                if docs is None:
+                    docs_res = self._get(f"/datasets/{dataset_id}/documents")
+                    docs_data = docs_res.json()
+                    if docs_data.get("code") == 0 and docs_data.get("data", {}).get("docs"):
+                        doc_id_meta_list = []
+                        docs = {}
+                        for doc in docs_data["data"]["docs"]:
+                            doc_id = doc.get("id")
+                            if not doc_id:
+                                continue
+                            doc_meta = {
+                                "document_id": doc_id,
+                                "name": doc.get("name", ""),
+                                "location": doc.get("location", ""),
+                                "type": doc.get("type", ""),
+                                "size": doc.get("size"),
+                                "chunk_count": doc.get("chunk_count"),
+                                # "chunk_method": doc.get("chunk_method", ""),
+                                "create_date": doc.get("create_date", ""),
+                                "update_date": doc.get("update_date", ""),
+                                # "process_begin_at": doc.get("process_begin_at", ""),
+                                # "process_duration": doc.get("process_duration"),
+                                # "progress": doc.get("progress"),
+                                # "progress_msg": doc.get("progress_msg", ""),
+                                # "status": doc.get("status", ""),
+                                # "run": doc.get("run", ""),
+                                "token_count": doc.get("token_count"),
+                                # "source_type": doc.get("source_type", ""),
+                                "thumbnail": doc.get("thumbnail", ""),
+                                "dataset_id": doc.get("dataset_id", dataset_id),
+                                "meta_fields": doc.get("meta_fields", {}),
+                                # "parser_config": doc.get("parser_config", {})
+                            }
+                            doc_id_meta_list.append((doc_id, doc_meta))
+                            docs[doc_id] = doc_meta
+                        self._set_cached_document_metadata_by_dataset(dataset_id, doc_id_meta_list)
+                if docs:
+                    document_cache.update(docs)
+
+        except Exception:
+            # Gracefully handle metadata cache failures
+            pass
+
+        return document_cache, dataset_cache
+
+    def _map_chunk_fields(self, chunk_data, dataset_cache, document_cache):
+        """Preserve all original API fields and add per-chunk document metadata"""
+        # Start with ALL raw data from API (preserve everything like original version)
+        mapped = dict(chunk_data)
+
+        # Add dataset name enhancement
+        dataset_id = chunk_data.get("dataset_id") or chunk_data.get("kb_id")
+        if dataset_id and dataset_id in dataset_cache:
+            mapped["dataset_name"] = dataset_cache[dataset_id]["name"]
+        else:
+            mapped["dataset_name"] = "Unknown"
+
+        # Add document name convenience field
+        mapped["document_name"] = chunk_data.get("document_keyword", "")
+
+        # Add per-chunk document metadata
+        document_id = chunk_data.get("document_id")
+        if document_id and document_id in document_cache:
+            mapped["document_metadata"] = document_cache[document_id]
+
+        return mapped
+
 
 class RAGFlowCtx:
     def __init__(self, connector: RAGFlowConnector):
@@ -195,7 +385,58 @@ async def list_tools(*, connector) -> list[types.Tool]:
                         "items": {"type": "string"},
                         "description": "Optional array of document IDs to search within."
                     },
-                    "question": {"type": "string", "description": "The question or query to search for."},
+                    "question": {
+                        "type": "string",
+                        "description": "The question or query to search for."
+                    },
+                    "page": {
+                        "type": "integer",
+                        "description": "Page number for pagination",
+                        "default": 1,
+                        "minimum": 1,
+                    },
+                    "page_size": {
+                        "type": "integer",
+                        "description": "Number of results to return per page (default: 10, max recommended: 50 to avoid token limits)",
+                        "default": 10,
+                        "minimum": 1,
+                        "maximum": 100,
+                    },
+                    "similarity_threshold": {
+                        "type": "number",
+                        "description": "Minimum similarity threshold for results",
+                        "default": 0.2,
+                        "minimum": 0.0,
+                        "maximum": 1.0,
+                    },
+                    "vector_similarity_weight": {
+                        "type": "number",
+                        "description": "Weight for vector similarity vs term similarity",
+                        "default": 0.3,
+                        "minimum": 0.0,
+                        "maximum": 1.0,
+                    },
+                    "keyword": {
+                        "type": "boolean",
+                        "description": "Enable keyword-based search",
+                        "default": False,
+                    },
+                    "top_k": {
+                        "type": "integer",
+                        "description": "Maximum results to consider before ranking",
+                        "default": 1024,
+                        "minimum": 1,
+                        "maximum": 1024,
+                    },
+                    "rerank_id": {
+                        "type": "string",
+                        "description": "Optional reranking model identifier",
+                    },
+                    "force_refresh": {
+                        "type": "boolean",
+                        "description": "Set to true only if fresh dataset and document metadata is explicitly required. Otherwise, cached metadata is used (default: false).",
+                        "default": False,
+                    },
                 },
                 "required": ["question"],
             },
@@ -209,6 +450,16 @@ async def call_tool(name: str, arguments: dict, *, connector) -> list[types.Text
     if name == "ragflow_retrieval":
         document_ids = arguments.get("document_ids", [])
         dataset_ids = arguments.get("dataset_ids", [])
+        question = arguments.get("question", "")
+        page = arguments.get("page", 1)
+        page_size = arguments.get("page_size", 10)
+        similarity_threshold = arguments.get("similarity_threshold", 0.2)
+        vector_similarity_weight = arguments.get("vector_similarity_weight", 0.3)
+        keyword = arguments.get("keyword", False)
+        top_k = arguments.get("top_k", 1024)
+        rerank_id = arguments.get("rerank_id")
+        force_refresh = arguments.get("force_refresh", False)
+
         
         # If no dataset_ids provided or empty list, get all available dataset IDs
         if not dataset_ids:
@@ -229,7 +480,15 @@ async def call_tool(name: str, arguments: dict, *, connector) -> list[types.Text
         return connector.retrieval(
             dataset_ids=dataset_ids,
             document_ids=document_ids,
-            question=arguments["question"],
+            question=question,
+            page=page,
+            page_size=page_size,
+            similarity_threshold=similarity_threshold,
+            vector_similarity_weight=vector_similarity_weight,
+            keyword=keyword,
+            top_k=top_k,
+            rerank_id=rerank_id,
+            force_refresh=force_refresh,
         )
     raise ValueError(f"Tool not found: {name}")
 

pyproject.toml

@@ -45,7 +45,7 @@ dependencies = [
     "html-text==0.6.2",
     "httpx[socks]==0.27.2",
     "huggingface-hub>=0.25.0,<0.26.0",
-    "infinity-sdk==0.6.0-dev4",
+    "infinity-sdk==0.6.0.dev5",
     "infinity-emb>=0.0.66,<0.0.67",
     "itsdangerous==2.1.2",
     "json-repair==0.35.0",

rag/app/naive.py

@@ -30,7 +30,7 @@ from tika import parser
 
 from api.db import LLMType
 from api.db.services.llm_service import LLMBundle
-from deepdoc.parser import DocxParser, ExcelParser, HtmlParser, JsonParser, MarkdownParser, PdfParser, TxtParser
+from deepdoc.parser import DocxParser, ExcelParser, HtmlParser, JsonParser, MarkdownElementExtractor, MarkdownParser, PdfParser, TxtParser
 from deepdoc.parser.figure_parser import VisionFigureParser, vision_figure_parser_figure_data_wrapper
 from deepdoc.parser.pdf_parser import PlainParser, VisionParser
 from rag.nlp import concat_img, find_codec, naive_merge, naive_merge_with_images, naive_merge_docx, rag_tokenizer, tokenize_chunks, tokenize_chunks_with_images, tokenize_table
@@ -289,7 +289,7 @@ class Pdf(PdfParser):
             return [(b["text"], self._line_tag(b, zoomin)) for b in self.boxes], tbls, figures
         else:
             tbls = self._extract_table_figure(True, zoomin, True, True)
-            # self._naive_vertical_merge()
+            self._naive_vertical_merge()
             self._concat_downward()
             # self._filter_forpages()
             logging.info("layouts cost: {}s".format(timer() - first_start))
@@ -350,17 +350,14 @@ class Markdown(MarkdownParser):
         else:
             with open(filename, "r") as f:
                 txt = f.read()
+
         remainder, tables = self.extract_tables_and_remainder(f'{txt}\n', separate_tables=separate_tables)
-        sections = []
+
+        extractor = MarkdownElementExtractor(txt)
+        element_sections = extractor.extract_elements()
+        sections = [(element, "") for element in element_sections]
+
         tbls = []
-        for sec in remainder.split("\n"):
-            if sec.strip().find("#") == 0:
-                sections.append((sec, ""))
-            elif sections and sections[-1][0].strip().find("#") == 0:
-                sec_, _ = sections.pop(-1)
-                sections.append((sec_ + "\n" + sec, ""))
-            else:
-                sections.append((sec, ""))
         for table in tables:
             tbls.append(((None, markdown(table, extensions=['markdown.extensions.tables'])), ""))
         return sections, tbls

rag/llm/__init__.py

@@ -36,6 +36,7 @@ class SupportedLiteLLMProvider(StrEnum):
     Nvidia = "NVIDIA"
     TogetherAI = "TogetherAI"
     Anthropic = "Anthropic"
+    Ollama = "Ollama"
 
 
 FACTORY_DEFAULT_BASE_URL = {
@@ -59,6 +60,7 @@ LITELLM_PROVIDER_PREFIX = {
     SupportedLiteLLMProvider.Nvidia: "nvidia_nim/",
     SupportedLiteLLMProvider.TogetherAI: "together_ai/",
     SupportedLiteLLMProvider.Anthropic: "",  # don't need a prefix
+    SupportedLiteLLMProvider.Ollama: "ollama_chat/",
 }
 
 ChatModel = globals().get("ChatModel", {})

rag/llm/chat_model.py

@@ -29,7 +29,6 @@ import json_repair
 import litellm
 import openai
 import requests
-from ollama import Client
 from openai import OpenAI
 from openai.lib.azure import AzureOpenAI
 from strenum import StrEnum
@@ -112,6 +111,32 @@ class Base(ABC):
     def _clean_conf(self, gen_conf):
         if "max_tokens" in gen_conf:
             del gen_conf["max_tokens"]
+
+        allowed_conf = {
+            "temperature",
+            "max_completion_tokens",
+            "top_p",
+            "stream",
+            "stream_options",
+            "stop",
+            "n",
+            "presence_penalty",
+            "frequency_penalty",
+            "functions",
+            "function_call",
+            "logit_bias",
+            "user",
+            "response_format",
+            "seed",
+            "tools",
+            "tool_choice",
+            "logprobs",
+            "top_logprobs",
+            "extra_headers",
+        }
+
+        gen_conf = {k: v for k, v in gen_conf.items() if k in allowed_conf}
+
         return gen_conf
 
     def _chat(self, history, gen_conf, **kwargs):
@@ -657,73 +682,6 @@ class ZhipuChat(Base):
         return super().chat_streamly_with_tools(system, history, gen_conf)
 
 
-class OllamaChat(Base):
-    _FACTORY_NAME = "Ollama"
-
-    def __init__(self, key, model_name, base_url=None, **kwargs):
-        super().__init__(key, model_name, base_url=base_url, **kwargs)
-
-        self.client = Client(host=base_url) if not key or key == "x" else Client(host=base_url, headers={"Authorization": f"Bearer {key}"})
-        self.model_name = model_name
-        self.keep_alive = kwargs.get("ollama_keep_alive", int(os.environ.get("OLLAMA_KEEP_ALIVE", -1)))
-
-    def _clean_conf(self, gen_conf):
-        options = {}
-        if "max_tokens" in gen_conf:
-            options["num_predict"] = gen_conf["max_tokens"]
-        for k in ["temperature", "top_p", "presence_penalty", "frequency_penalty"]:
-            if k not in gen_conf:
-                continue
-            options[k] = gen_conf[k]
-        return options
-
-    def _chat(self, history, gen_conf={}, **kwargs):
-        # Calculate context size
-        ctx_size = self._calculate_dynamic_ctx(history)
-
-        gen_conf["num_ctx"] = ctx_size
-        response = self.client.chat(model=self.model_name, messages=history, options=gen_conf, keep_alive=self.keep_alive)
-        ans = response["message"]["content"].strip()
-        token_count = response.get("eval_count", 0) + response.get("prompt_eval_count", 0)
-        return ans, token_count
-
-    def chat_streamly(self, system, history, gen_conf={}, **kwargs):
-        if system:
-            history.insert(0, {"role": "system", "content": system})
-        if "max_tokens" in gen_conf:
-            del gen_conf["max_tokens"]
-        try:
-            # Calculate context size
-            ctx_size = self._calculate_dynamic_ctx(history)
-            options = {"num_ctx": ctx_size}
-            if "temperature" in gen_conf:
-                options["temperature"] = gen_conf["temperature"]
-            if "max_tokens" in gen_conf:
-                options["num_predict"] = gen_conf["max_tokens"]
-            if "top_p" in gen_conf:
-                options["top_p"] = gen_conf["top_p"]
-            if "presence_penalty" in gen_conf:
-                options["presence_penalty"] = gen_conf["presence_penalty"]
-            if "frequency_penalty" in gen_conf:
-                options["frequency_penalty"] = gen_conf["frequency_penalty"]
-
-            ans = ""
-            try:
-                response = self.client.chat(model=self.model_name, messages=history, stream=True, options=options, keep_alive=self.keep_alive)
-                for resp in response:
-                    if resp["done"]:
-                        token_count = resp.get("prompt_eval_count", 0) + resp.get("eval_count", 0)
-                        yield token_count
-                    ans = resp["message"]["content"]
-                    yield ans
-            except Exception as e:
-                yield ans + "\n**ERROR**: " + str(e)
-            yield 0
-        except Exception as e:
-            yield "**ERROR**: " + str(e)
-            yield 0
-
-
 class LocalAIChat(Base):
     _FACTORY_NAME = "LocalAI"
 
@@ -1396,7 +1354,7 @@ class Ai302Chat(Base):
 
 
 class LiteLLMBase(ABC):
-    _FACTORY_NAME = ["Tongyi-Qianwen", "Bedrock", "Moonshot", "xAI", "DeepInfra", "Groq", "Cohere", "Gemini", "DeepSeek", "NVIDIA", "TogetherAI", "Anthropic"]
+    _FACTORY_NAME = ["Tongyi-Qianwen", "Bedrock", "Moonshot", "xAI", "DeepInfra", "Groq", "Cohere", "Gemini", "DeepSeek", "NVIDIA", "TogetherAI", "Anthropic", "Ollama"]
 
     def __init__(self, key, model_name, base_url=None, **kwargs):
         self.timeout = int(os.environ.get("LM_TIMEOUT_SECONDS", 600))

rag/prompts/prompts.py

@@ -114,6 +114,8 @@ def kb_prompt(kbinfos, max_tokens, hash_id=False):
     docs = {d.id: d.meta_fields for d in docs}
 
     def draw_node(k, line):
+        if line is not None and not isinstance(line, str):
+            line = str(line)
         if not line:
             return ""
         return f"\n├── {k}: " + re.sub(r"\n+", " ", line, flags=re.DOTALL)

rag/raptor.py

@@ -42,9 +42,12 @@ class RecursiveAbstractiveProcessing4TreeOrganizedRetrieval:
         self._prompt = prompt
         self._max_token = max_token
 
-    @timeout(60)
+    @timeout(60*20)
     async def _chat(self, system, history, gen_conf):
-        response = get_llm_cache(self._llm_model.llm_name, system, history, gen_conf)
+        response = await trio.to_thread.run_sync(
+            lambda: get_llm_cache(self._llm_model.llm_name, system, history, gen_conf)
+        )
+
         if response:
             return response
         response = await trio.to_thread.run_sync(
@@ -53,19 +56,23 @@ class RecursiveAbstractiveProcessing4TreeOrganizedRetrieval:
         response = re.sub(r"^.*</think>", "", response, flags=re.DOTALL)
         if response.find("**ERROR**") >= 0:
             raise Exception(response)
-        set_llm_cache(self._llm_model.llm_name, system, response, history, gen_conf)
+        await trio.to_thread.run_sync(
+            lambda: set_llm_cache(self._llm_model.llm_name, system, response, history, gen_conf)
+        )
         return response
 
-    @timeout(2)
+    @timeout(20)
     async def _embedding_encode(self, txt):
-        response = get_embed_cache(self._embd_model.llm_name, txt)
+        response = await trio.to_thread.run_sync(
+            lambda: get_embed_cache(self._embd_model.llm_name, txt)
+        )
         if response is not None:
             return response
         embds, _ = await trio.to_thread.run_sync(lambda: self._embd_model.encode([txt]))
         if len(embds) < 1 or len(embds[0]) < 1:
             raise Exception("Embedding error: ")
         embds = embds[0]
-        set_embed_cache(self._embd_model.llm_name, txt, embds)
+        await trio.to_thread.run_sync(lambda: set_embed_cache(self._embd_model.llm_name, txt, embds))
         return embds
 
     def _get_optimal_clusters(self, embeddings: np.ndarray, random_state: int):
@@ -86,7 +93,7 @@ class RecursiveAbstractiveProcessing4TreeOrganizedRetrieval:
         layers = [(0, len(chunks))]
         start, end = 0, len(chunks)
 
-        @timeout(60)
+        @timeout(60*20)
         async def summarize(ck_idx: list[int]):
             nonlocal chunks
             texts = [chunks[i][0] for i in ck_idx]

rag/svr/task_executor.py

@@ -21,7 +21,7 @@ import sys
 import threading
 import time
 
-from api.utils.api_utils import timeout, is_strong_enough
+from api.utils.api_utils import timeout
 from api.utils.log_utils import init_root_logger, get_project_base_directory
 from graphrag.general.index import run_graphrag
 from graphrag.utils import get_llm_cache, set_llm_cache, get_tags_from_cache, set_tags_to_cache
@@ -478,8 +478,6 @@ async def embedding(docs, mdl, parser_config=None, callback=None):
 
 @timeout(3600)
 async def run_raptor(row, chat_mdl, embd_mdl, vector_size, callback=None):
-    # Pressure test for GraphRAG task
-    await is_strong_enough(chat_mdl, embd_mdl)
     chunks = []
     vctr_nm = "q_%d_vec"%vector_size
     for d in settings.retrievaler.chunk_list(row["doc_id"], row["tenant_id"], [str(row["kb_id"])],
@@ -553,7 +551,6 @@ async def do_handle_task(task):
     try:
         # bind embedding model
         embedding_model = LLMBundle(task_tenant_id, LLMType.EMBEDDING, llm_name=task_embedding_id, lang=task_language)
-        await is_strong_enough(None, embedding_model)
         vts, _ = embedding_model.encode(["ok"])
         vector_size = len(vts[0])
     except Exception as e:
@@ -568,7 +565,6 @@ async def do_handle_task(task):
     if task.get("task_type", "") == "raptor":
         # bind LLM for raptor
         chat_model = LLMBundle(task_tenant_id, LLMType.CHAT, llm_name=task_llm_id, lang=task_language)
-        await is_strong_enough(chat_model, None)
         # run RAPTOR
         async with kg_limiter:
             chunks, token_count = await run_raptor(task, chat_model, embedding_model, vector_size, progress_callback)
@@ -580,7 +576,6 @@ async def do_handle_task(task):
         graphrag_conf = task["kb_parser_config"].get("graphrag", {})
         start_ts = timer()
         chat_model = LLMBundle(task_tenant_id, LLMType.CHAT, llm_name=task_llm_id, lang=task_language)
-        await is_strong_enough(chat_model, None)
         with_resolution = graphrag_conf.get("resolution", False)
         with_community = graphrag_conf.get("community", False)
         async with kg_limiter:

sandbox/executor_manager/core/config.py

@@ -22,7 +22,7 @@ from util import format_timeout_duration, parse_timeout_duration
 from core.container import init_containers, teardown_containers
 from core.logger import logger
 
-TIMEOUT = 10
+TIMEOUT = parse_timeout_duration(os.getenv("SANDBOX_TIMEOUT", "10s"))
 
 
 @asynccontextmanager
@@ -39,6 +39,5 @@ async def _lifespan(app: FastAPI):
 
 
 def init():
-    TIMEOUT = parse_timeout_duration(os.getenv("SANDBOX_TIMEOUT"))
     logger.info(f"Global timeout: {format_timeout_duration(TIMEOUT)}")
     return _lifespan

uv.lock

@@ -2603,7 +2603,7 @@ wheels = [
 
 [[package]]
 name = "infinity-sdk"
-version = "0.6.0.dev4"
+version = "0.6.0.dev5"
 source = { registry = "https://mirrors.aliyun.com/pypi/simple" }
 dependencies = [
     { name = "numpy" },
@@ -2620,7 +2620,7 @@ dependencies = [
     { name = "thrift" },
 ]
 wheels = [
-    { url = "https://mirrors.aliyun.com/pypi/packages/d4/cc/645ed8de15952940c7308a788036376583a5fc29fdcf3e4bc75b5ad0c881/infinity_sdk-0.6.0.dev4-py3-none-any.whl", hash = "sha256:f8f4bd8a44e3fae7b4228b5c9e9a16559b4905f50d2d7d0a3d18f39974613e7a" },
+    { url = "https://mirrors.aliyun.com/pypi/packages/fe/a4/6079bf9790f16badc01e7b79a28c90bec407cfcaa8a2ed37e4a68120f87a/infinity_sdk-0.6.0.dev5-py3-none-any.whl", hash = "sha256:510ac408d5cd9d3d4df33c7c0877f55c5ae8a6019e465190c86d58012a319179" },
 ]
 
 [[package]]
@@ -5471,7 +5471,7 @@ requires-dist = [
     { name = "httpx", extras = ["socks"], specifier = "==0.27.2" },
     { name = "huggingface-hub", specifier = ">=0.25.0,<0.26.0" },
     { name = "infinity-emb", specifier = ">=0.0.66,<0.0.67" },
-    { name = "infinity-sdk", specifier = "==0.6.0.dev4" },
+    { name = "infinity-sdk", specifier = "==0.6.0.dev5" },
     { name = "itsdangerous", specifier = "==2.1.2" },
     { name = "json-repair", specifier = "==0.35.0" },
     { name = "langfuse", specifier = ">=2.60.0" },

web/.eslintrc.js

@@ -14,7 +14,7 @@ module.exports = {
       'error',
       {
         '**/*.{jsx,tsx}': 'KEBAB_CASE',
-        '**/*.{js,ts}': 'KEBAB_CASE',
+        '**/*.{js,ts}': '[a-z0-9.-]*',
       },
     ],
     'check-file/folder-naming-convention': [

web/src/app.tsx

@@ -2,7 +2,6 @@ import { Toaster as Sonner } from '@/components/ui/sonner';
 import { Toaster } from '@/components/ui/toaster';
 import i18n from '@/locales/config';
 import { QueryClient, QueryClientProvider } from '@tanstack/react-query';
-import { ReactQueryDevtools } from '@tanstack/react-query-devtools';
 import { App, ConfigProvider, ConfigProviderProps, theme } from 'antd';
 import pt_BR from 'antd/lib/locale/pt_BR';
 import deDE from 'antd/locale/de_DE';
@@ -85,7 +84,7 @@ function Root({ children }: React.PropsWithChildren) {
         <Sonner position={'top-right'} expand richColors closeButton></Sonner>
         <Toaster />
       </ConfigProvider>
-      <ReactQueryDevtools buttonPosition={'top-left'} />
+      {/* <ReactQueryDevtools buttonPosition={'top-left'} initialIsOpen={false} /> */}
     </>
   );
 }

web/src/components/file-upload-dialog/index.tsx

@@ -8,47 +8,93 @@ import {
 } from '@/components/ui/dialog';
 import { Tabs, TabsContent, TabsList, TabsTrigger } from '@/components/ui/tabs';
 import { IModalProps } from '@/interfaces/common';
-import { Dispatch, SetStateAction, useCallback, useState } from 'react';
+import { zodResolver } from '@hookform/resolvers/zod';
+import { TFunction } from 'i18next';
+import { useForm } from 'react-hook-form';
 import { useTranslation } from 'react-i18next';
+import { z } from 'zod';
 import { FileUploader } from '../file-uploader';
+import { RAGFlowFormItem } from '../ragflow-form';
+import { Form } from '../ui/form';
+import { Switch } from '../ui/switch';
 
-type UploaderTabsProps = {
-  setFiles: Dispatch<SetStateAction<File[]>>;
+function buildUploadFormSchema(t: TFunction) {
+  const FormSchema = z.object({
+    parseOnCreation: z.boolean().optional(),
+    fileList: z
+      .array(z.instanceof(File))
+      .min(1, { message: t('fileManager.pleaseUploadAtLeastOneFile') }),
+  });
+
+  return FormSchema;
+}
+
+export type UploadFormSchemaType = z.infer<
+  ReturnType<typeof buildUploadFormSchema>
+>;
+
+const UploadFormId = 'UploadFormId';
+
+type UploadFormProps = {
+  submit: (values?: UploadFormSchemaType) => void;
+  showParseOnCreation?: boolean;
 };
-
-export function UploaderTabs({ setFiles }: UploaderTabsProps) {
+function UploadForm({ submit, showParseOnCreation }: UploadFormProps) {
   const { t } = useTranslation();
+  const FormSchema = buildUploadFormSchema(t);
+
+  type UploadFormSchemaType = z.infer<typeof FormSchema>;
+  const form = useForm<UploadFormSchemaType>({
+    resolver: zodResolver(FormSchema),
+    defaultValues: {
+      parseOnCreation: false,
+      fileList: [],
+    },
+  });
 
   return (
-    <Tabs defaultValue="account">
-      <TabsList className="grid w-full grid-cols-2 mb-4">
-        <TabsTrigger value="account">{t('fileManager.local')}</TabsTrigger>
-        <TabsTrigger value="password">{t('fileManager.s3')}</TabsTrigger>
-      </TabsList>
-      <TabsContent value="account">
-        <FileUploader
-          maxFileCount={8}
-          maxSize={8 * 1024 * 1024}
-          onValueChange={setFiles}
-          accept={{ '*': [] }}
-        />
-      </TabsContent>
-      <TabsContent value="password">{t('common.comingSoon')}</TabsContent>
-    </Tabs>
+    <Form {...form}>
+      <form
+        onSubmit={form.handleSubmit(submit)}
+        id={UploadFormId}
+        className="space-y-4"
+      >
+        {showParseOnCreation && (
+          <RAGFlowFormItem
+            name="parseOnCreation"
+            label={t('fileManager.parseOnCreation')}
+          >
+            {(field) => (
+              <Switch
+                onCheckedChange={field.onChange}
+                checked={field.value}
+              ></Switch>
+            )}
+          </RAGFlowFormItem>
+        )}
+        <RAGFlowFormItem name="fileList" label={t('fileManager.file')}>
+          {(field) => (
+            <FileUploader
+              value={field.value}
+              onValueChange={field.onChange}
+              accept={{ '*': [] }}
+            />
+          )}
+        </RAGFlowFormItem>
+      </form>
+    </Form>
   );
 }
 
+type FileUploadDialogProps = IModalProps<UploadFormSchemaType> &
+  Pick<UploadFormProps, 'showParseOnCreation'>;
 export function FileUploadDialog({
   hideModal,
   onOk,
   loading,
-}: IModalProps<File[]>) {
+  showParseOnCreation = false,
+}: FileUploadDialogProps) {
   const { t } = useTranslation();
-  const [files, setFiles] = useState<File[]>([]);
-
-  const handleOk = useCallback(() => {
-    onOk?.(files);
-  }, [files, onOk]);
 
   return (
     <Dialog open onOpenChange={hideModal}>
@@ -56,9 +102,21 @@ export function FileUploadDialog({
         <DialogHeader>
           <DialogTitle>{t('fileManager.uploadFile')}</DialogTitle>
         </DialogHeader>
-        <UploaderTabs setFiles={setFiles}></UploaderTabs>
+        <Tabs defaultValue="account">
+          <TabsList className="grid w-full grid-cols-2 mb-4">
+            <TabsTrigger value="account">{t('fileManager.local')}</TabsTrigger>
+            <TabsTrigger value="password">{t('fileManager.s3')}</TabsTrigger>
+          </TabsList>
+          <TabsContent value="account">
+            <UploadForm
+              submit={onOk!}
+              showParseOnCreation={showParseOnCreation}
+            ></UploadForm>
+          </TabsContent>
+          <TabsContent value="password">{t('common.comingSoon')}</TabsContent>
+        </Tabs>
         <DialogFooter>
-          <ButtonLoading type="submit" onClick={handleOk} loading={loading}>
+          <ButtonLoading type="submit" loading={loading} form={UploadFormId}>
             {t('common.save')}
           </ButtonLoading>
         </DialogFooter>

web/src/components/file-uploader.tsx

@@ -15,6 +15,7 @@ import { Progress } from '@/components/ui/progress';
 import { ScrollArea } from '@/components/ui/scroll-area';
 import { useControllableState } from '@/hooks/use-controllable-state';
 import { cn, formatBytes } from '@/lib/utils';
+import { useTranslation } from 'react-i18next';
 
 function isFileWithPreview(file: File): file is File & { preview: string } {
   return 'preview' in file && typeof file.preview === 'string';
@@ -168,14 +169,14 @@ export function FileUploader(props: FileUploaderProps) {
     accept = {
       'image/*': [],
     },
-    maxSize = 1024 * 1024 * 2,
-    maxFileCount = 1,
+    maxSize = 1024 * 1024 * 10000000,
+    maxFileCount = 100000000000,
     multiple = false,
     disabled = false,
     className,
     ...dropzoneProps
   } = props;
-
+  const { t } = useTranslation();
   const [files, setFiles] = useControllableState({
     prop: valueProp,
     onChange: onValueChange,
@@ -267,7 +268,7 @@ export function FileUploader(props: FileUploaderProps) {
           <div
             {...getRootProps()}
             className={cn(
-              'group relative grid h-52 w-full cursor-pointer place-items-center rounded-lg border-2 border-dashed border-muted-foreground/25 px-5 py-2.5 text-center transition hover:bg-muted/25',
+              'group relative grid h-72 w-full cursor-pointer place-items-center rounded-lg border-2 border-dashed border-muted-foreground/25 px-5 py-2.5 text-center transition hover:bg-muted/25',
               'ring-offset-background focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-ring focus-visible:ring-offset-2',
               isDragActive && 'border-muted-foreground/50',
               isDisabled && 'pointer-events-none opacity-60',
@@ -298,14 +299,15 @@ export function FileUploader(props: FileUploaderProps) {
                 </div>
                 <div className="flex flex-col gap-px">
                   <p className="font-medium text-muted-foreground">
-                    Drag {`'n'`} drop files here, or click to select files
+                    {t('knowledgeDetails.uploadTitle')}
                   </p>
                   <p className="text-sm text-muted-foreground/70">
-                    You can upload
+                    {t('knowledgeDetails.uploadDescription')}
+                    {/* You can upload
                     {maxFileCount > 1
                       ? ` ${maxFileCount === Infinity ? 'multiple' : maxFileCount}
                       files (up to ${formatBytes(maxSize)} each)`
-                      : ` a file with ${formatBytes(maxSize)}`}
+                      : ` a file with ${formatBytes(maxSize)}`} */}
                   </p>
                 </div>
               </div>

web/src/components/home-card.tsx

@@ -1,6 +1,7 @@
 import { RAGFlowAvatar } from '@/components/ragflow-avatar';
 import { Card, CardContent } from '@/components/ui/card';
 import { formatDate } from '@/utils/date';
+import { ReactNode } from 'react';
 
 interface IProps {
   data: {
@@ -11,8 +12,9 @@ interface IProps {
   };
   onClick?: () => void;
   moreDropdown: React.ReactNode;
+  sharedBadge?: ReactNode;
 }
-export function HomeCard({ data, onClick, moreDropdown }: IProps) {
+export function HomeCard({ data, onClick, moreDropdown, sharedBadge }: IProps) {
   return (
     <Card
       className="bg-bg-card  border-colors-outline-neutral-standard"
@@ -31,7 +33,7 @@ export function HomeCard({ data, onClick, moreDropdown }: IProps) {
         </div>
         <div className="flex flex-col justify-between gap-1 flex-1 h-full w-[calc(100%-50px)]">
           <section className="flex justify-between">
-            <div className="text-[20px] font-bold w-80% leading-5">
+            <div className="text-[20px] font-bold w-80% leading-5 text-ellipsis overflow-hidden">
               {data.name}
             </div>
             {moreDropdown}
@@ -41,10 +43,11 @@ export function HomeCard({ data, onClick, moreDropdown }: IProps) {
             <div className="whitespace-nowrap overflow-hidden text-ellipsis">
               {data.description}
             </div>
-            <div>
+            <div className="flex justify-between items-center">
               <p className="text-sm opacity-80">
                 {formatDate(data.update_time)}
               </p>
+              {sharedBadge}
             </div>
           </section>
         </div>

web/src/components/layout-recognize-form-field.tsx

@@ -68,7 +68,7 @@ export function LayoutRecognizeFormField() {
             <div className="flex items-center">
               <FormLabel
                 tooltip={t('layoutRecognizeTip')}
-                className="text-sm text-muted-foreground whitespace-nowrap w-1/4"
+                className="text-sm text-muted-foreground whitespace-wrap w-1/4"
               >
                 {t('layoutRecognize')}
               </FormLabel>

web/src/components/list-filter-bar/index.tsx

@@ -1,5 +1,5 @@
 import { cn } from '@/lib/utils';
-import { ChevronDown } from 'lucide-react';
+import { Funnel } from 'lucide-react';
 import React, {
   ChangeEventHandler,
   PropsWithChildren,
@@ -25,20 +25,20 @@ export const FilterButton = React.forwardRef<
 >(({ count = 0, ...props }, ref) => {
   return (
     <Button variant="secondary" {...props} ref={ref}>
-      <span
+      {/* <span
         className={cn({
           'text-text-primary': count > 0,
           'text-text-sub-title-invert': count === 0,
         })}
       >
         Filter
-      </span>
+      </span> */}
       {count > 0 && (
         <span className="rounded-full bg-text-badge px-1 text-xs ">
           {count}
         </span>
       )}
-      <ChevronDown />
+      <Funnel />
     </Button>
   );
 });

web/src/components/llm-select/next.tsx

@@ -2,6 +2,7 @@ import { LlmModelType } from '@/constants/knowledge';
 import { useComposeLlmOptionsByModelTypes } from '@/hooks/llm-hooks';
 import * as SelectPrimitive from '@radix-ui/react-select';
 import { forwardRef, memo, useMemo, useState } from 'react';
+import { useTranslation } from 'react-i18next';
 import { LlmSettingFieldItems } from '../llm-setting-items/next';
 import { Popover, PopoverContent, PopoverTrigger } from '../ui/popover';
 import { Select, SelectTrigger, SelectValue } from '../ui/select';
@@ -20,6 +21,7 @@ const NextInnerLLMSelect = forwardRef<
   React.ElementRef<typeof SelectPrimitive.Trigger>,
   NextInnerLLMSelectProps
 >(({ value, disabled, filter, showSpeech2TextModel = false }, ref) => {
+  const { t } = useTranslation();
   const [isPopoverOpen, setIsPopoverOpen] = useState(false);
 
   const ttsModel = useMemo(() => {
@@ -49,7 +51,7 @@ const NextInnerLLMSelect = forwardRef<
             }}
             ref={ref}
           >
-            <SelectValue>
+            <SelectValue placeholder={t('common.pleaseSelect')}>
               {
                 modelOptions
                   .flatMap((x) => x.options)

web/src/components/llm-setting-items/slider.tsx

@@ -19,6 +19,7 @@ type SliderInputSwitchFormFieldProps = {
   name: string;
   label: string;
   defaultValue?: number;
+  onChange?: (value: number) => void;
   className?: string;
   checkName: string;
 };
@@ -30,6 +31,7 @@ export function SliderInputSwitchFormField({
   label,
   name,
   defaultValue,
+  onChange,
   className,
   checkName,
 }: SliderInputSwitchFormFieldProps) {
@@ -66,6 +68,10 @@ export function SliderInputSwitchFormField({
             <FormControl>
               <SingleFormSlider
                 {...field}
+                onChange={(value: number) => {
+                  onChange?.(value);
+                  field.onChange(value);
+                }}
                 max={max}
                 min={min}
                 step={step}
@@ -80,6 +86,10 @@ export function SliderInputSwitchFormField({
                 min={min}
                 step={step}
                 {...field}
+                onChange={(value: number) => {
+                  onChange?.(value);
+                  field.onChange(value);
+                }}
               ></NumberInput>
             </FormControl>
           </div>

web/src/components/metadata-filter/index.tsx

@@ -58,7 +58,10 @@ export function MetadataFilter({ prefix = '' }: MetadataFilterProps) {
           name={methodName}
           tooltip={t('metadataTip')}
         >
-          <SelectWithSearch options={MetadataOptions} />
+          <SelectWithSearch
+            options={MetadataOptions}
+            triggerClassName="!bg-bg-input"
+          />
         </RAGFlowFormItem>
       )}
       {hasKnowledge && metadata === DatasetMetadata.Manual && (

web/src/components/originui/select-with-search.tsx

@@ -28,6 +28,7 @@ import {
   PopoverTrigger,
 } from '@/components/ui/popover';
 import { cn } from '@/lib/utils';
+import { t } from 'i18next';
 import { RAGFlowSelectOptionType } from '../ui/select';
 import { Separator } from '../ui/separator';
 
@@ -114,7 +115,9 @@ export const SelectWithSearch = forwardRef<
                 <span className="leading-none truncate">{selectLabel}</span>
               </span>
             ) : (
-              <span className="text-muted-foreground">Select value</span>
+              <span className="text-muted-foreground">
+                {t('common.selectPlaceholder')}
+              </span>
             )}
             <div className="flex items-center justify-between">
               {value && allowClear && (

web/src/components/parse-configuration/raptor-form-fields.tsx

@@ -3,7 +3,7 @@ import { DocumentParserType } from '@/constants/knowledge';
 import { useTranslate } from '@/hooks/common-hooks';
 import random from 'lodash/random';
 import { Plus } from 'lucide-react';
-import { useCallback, useEffect } from 'react';
+import { useCallback } from 'react';
 import { useFormContext, useWatch } from 'react-hook-form';
 import { SliderInputFormField } from '../slider-input-form-field';
 import { Button } from '../ui/button';
@@ -57,15 +57,19 @@ const RaptorFormFields = () => {
   const form = useFormContext();
   const { t } = useTranslate('knowledgeConfiguration');
   const useRaptor = useWatch({ name: UseRaptorField });
-  useEffect(() => {
-    if (useRaptor) {
-      form.setValue(MaxTokenField, 256);
-      form.setValue(ThresholdField, 0.1);
-      form.setValue(MaxCluster, 64);
-      form.setValue(RandomSeedField, 0);
-      form.setValue(Prompt, t('promptText'));
-    }
-  }, [form, useRaptor, t]);
+
+  const changeRaptor = useCallback(
+    (isUseRaptor: boolean) => {
+      if (isUseRaptor) {
+        form.setValue(MaxTokenField, 256);
+        form.setValue(ThresholdField, 0.1);
+        form.setValue(MaxCluster, 64);
+        form.setValue(RandomSeedField, 0);
+        form.setValue(Prompt, t('promptText'));
+      }
+    },
+    [form],
+  );
 
   const handleGenerate = useCallback(() => {
     form.setValue(RandomSeedField, random(10000));
@@ -97,7 +101,10 @@ const RaptorFormFields = () => {
                   <FormControl>
                     <Switch
                       checked={field.value}
-                      onCheckedChange={field.onChange}
+                      onCheckedChange={(e) => {
+                        changeRaptor(e);
+                        field.onChange(e);
+                      }}
                     ></Switch>
                   </FormControl>
                 </div>
@@ -127,7 +134,13 @@ const RaptorFormFields = () => {
                     </FormLabel>
                     <div className="w-3/4">
                       <FormControl>
-                        <Textarea {...field} rows={8} />
+                        <Textarea
+                          {...field}
+                          rows={8}
+                          onChange={(e) => {
+                            field.onChange(e?.target?.value);
+                          }}
+                        />
                       </FormControl>
                     </div>
                   </div>

web/src/components/ragflow-form.tsx

@@ -5,6 +5,7 @@ import {
   FormLabel,
   FormMessage,
 } from '@/components/ui/form';
+import { cn } from '@/lib/utils';
 import { ReactNode, cloneElement, isValidElement } from 'react';
 import { ControllerRenderProps, useFormContext } from 'react-hook-form';
 
@@ -13,6 +14,7 @@ type RAGFlowFormItemProps = {
   label: ReactNode;
   tooltip?: ReactNode;
   children: ReactNode | ((field: ControllerRenderProps) => ReactNode);
+  horizontal?: boolean;
 };
 
 export function RAGFlowFormItem({
@@ -20,6 +22,7 @@ export function RAGFlowFormItem({
   label,
   tooltip,
   children,
+  horizontal = false,
 }: RAGFlowFormItemProps) {
   const form = useFormContext();
   return (
@@ -27,8 +30,14 @@ export function RAGFlowFormItem({
       control={form.control}
       name={name}
       render={({ field }) => (
-        <FormItem>
-          <FormLabel tooltip={tooltip}>{label}</FormLabel>
+        <FormItem
+          className={cn({
+            'flex items-center': horizontal,
+          })}
+        >
+          <FormLabel tooltip={tooltip} className={cn({ 'w-1/4': horizontal })}>
+            {label}
+          </FormLabel>
           <FormControl>
             {typeof children === 'function'
               ? children(field)

web/src/components/shared-badge.tsx

@@ -8,9 +8,5 @@ export function SharedBadge({ children }: PropsWithChildren) {
     return null;
   }
 
-  return (
-    <span className="bg-text-secondary rounded-sm px-1 text-bg-base text-xs">
-      {children}
-    </span>
-  );
+  return <span className="bg-bg-card rounded-sm px-1 text-xs">{children}</span>;
 }

web/src/components/ui/button.tsx

@@ -17,7 +17,7 @@ const buttonVariants = cva(
         outline:
           'border bg-background shadow-xs hover:bg-accent hover:text-accent-foreground dark:bg-input/30 dark:border-input dark:hover:bg-input/50',
         secondary:
-          'bg-secondary text-secondary-foreground shadow-xs hover:bg-secondary/80',
+          'bg-bg-input text-secondary-foreground shadow-xs hover:bg-bg-input/80',
         ghost:
           'hover:bg-accent hover:text-accent-foreground dark:hover:bg-accent/50',
         link: 'text-primary underline-offset-4 hover:underline',

web/src/components/ui/input.tsx

@@ -116,7 +116,10 @@ export { ExpandedInput, Input, SearchInput };
 
 type NumberInputProps = { onChange?(value: number): void } & InputProps;
 
-export const NumberInput = ({ onChange, ...props }: NumberInputProps) => {
+export const NumberInput = React.forwardRef<
+  HTMLInputElement,
+  NumberInputProps & { value: Value; onChange(value: Value): void }
+>(function NumberInput({ onChange, ...props }, ref) {
   return (
     <Input
       type="number"
@@ -125,6 +128,7 @@ export const NumberInput = ({ onChange, ...props }: NumberInputProps) => {
         onChange?.(value === '' ? 0 : Number(value)); // convert to number
       }}
       {...props}
+      ref={ref}
     ></Input>
   );
-};
+});

web/src/components/ui/multi-select.tsx

@@ -209,8 +209,16 @@ export const MultiSelect = React.forwardRef<
     const [isAnimating, setIsAnimating] = React.useState(false);
 
     React.useEffect(() => {
-      setSelectedValues(defaultValue);
-    }, [defaultValue]);
+      if (!selectedValues && props.value) {
+        setSelectedValues(props.value as string[]);
+      }
+    }, [props.value, selectedValues]);
+
+    React.useEffect(() => {
+      if (!selectedValues && !props.value && defaultValue) {
+        setSelectedValues(defaultValue);
+      }
+    }, [defaultValue, props.value, selectedValues]);
 
     const flatOptions = React.useMemo(() => {
       return options.flatMap((option) =>
@@ -291,15 +299,18 @@ export const MultiSelect = React.forwardRef<
                         variant="secondary"
                         className={cn(
                           isAnimating ? 'animate-bounce' : '',
+                          'px-1',
                           multiSelectVariants({ variant }),
                         )}
                         style={{ animationDuration: `${animation}s` }}
                       >
-                        <div className="flex items-center gap-1">
+                        <div className="flex justify-between items-center gap-1">
                           {IconComponent && (
                             <IconComponent className="h-4 w-4" />
                           )}
-                          <div>{option?.label}</div>
+                          <div className="max-w-28 text-ellipsis overflow-hidden">
+                            {option?.label}
+                          </div>
                           <XCircle
                             className="h-4 w-4 cursor-pointer"
                             onClick={(event) => {

web/src/components/ui/progress.tsx

@@ -12,13 +12,13 @@ const Progress = React.forwardRef<
   <ProgressPrimitive.Root
     ref={ref}
     className={cn(
-      'relative h-4 w-full overflow-hidden rounded-full bg-secondary',
+      'relative h-4 w-full overflow-hidden rounded-full bg-bg-accent',
       className,
     )}
     {...props}
   >
     <ProgressPrimitive.Indicator
-      className="h-full w-full flex-1 bg-primary transition-all"
+      className="h-full w-full flex-1 bg-accent-primary transition-all"
       style={{ transform: `translateX(-${100 - (value || 0)}%)` }}
     />
   </ProgressPrimitive.Root>

web/src/components/ui/segmented.tsx

@@ -23,6 +23,7 @@ export interface SegmentedProps
   prefixCls?: string;
   direction?: 'ltr' | 'rtl';
   motionName?: string;
+  activeClassName?: string;
 }
 
 export function Segmented({
@@ -30,6 +31,7 @@ export function Segmented({
   value,
   onChange,
   className,
+  activeClassName,
 }: SegmentedProps) {
   const [selectedValue, setSelectedValue] = React.useState<
     SegmentedValue | undefined
@@ -57,9 +59,12 @@ export function Segmented({
             className={cn(
               'inline-flex items-center px-6 py-2 text-base font-normal rounded-3xl cursor-pointer',
               {
-                'bg-text-primary': selectedValue === actualValue,
-                'text-bg-base': selectedValue === actualValue,
+                'text-bg-base bg-metallic-gradient border-b-[#00BEB4] border-b-2':
+                  selectedValue === actualValue,
               },
+              activeClassName && selectedValue === actualValue
+                ? activeClassName
+                : '',
             )}
             onClick={() => handleOnChange(actualValue)}
           >

web/src/components/ui/textarea.tsx

@@ -54,7 +54,7 @@ const Textarea = forwardRef<HTMLTextAreaElement, TextareaProps>(
     return (
       <textarea
         className={cn(
-          'flex min-h-[80px] w-full bg-bg-card rounded-md border border-input px-3 py-2 text-base ring-offset-background placeholder:text-muted-foreground focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-ring focus-visible:ring-offset-2 disabled:cursor-not-allowed disabled:opacity-50 md:text-sm overflow-hidden',
+          'flex min-h-[80px] w-full bg-bg-input rounded-md border border-input px-3 py-2 text-base ring-offset-background placeholder:text-muted-foreground focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-ring focus-visible:ring-offset-2 disabled:cursor-not-allowed disabled:opacity-50 md:text-sm overflow-hidden',
           className,
         )}
         rows={autoSize?.minRows ?? props.rows ?? undefined}

web/src/constants/permission.ts

@@ -0,0 +1,4 @@
+export enum PermissionRole {
+  Me = 'me',
+  Team = 'team',
+}

web/src/hooks/use-document-request.ts

@@ -1,4 +1,5 @@
 import { useHandleFilterSubmit } from '@/components/list-filter-bar/use-handle-filter-submit';
+import { ResponseType } from '@/interfaces/database/base';
 import {
   IDocumentInfo,
   IDocumentInfoFilter,
@@ -45,9 +46,9 @@ export const useUploadNextDocument = () => {
     data,
     isPending: loading,
     mutateAsync,
-  } = useMutation({
+  } = useMutation<ResponseType<IDocumentInfo[]>, Error, File[]>({
     mutationKey: [DocumentApiAction.UploadDocument],
-    mutationFn: async (fileList: File[]) => {
+    mutationFn: async (fileList) => {
       const formData = new FormData();
       formData.append('kb_id', id!);
       fileList.forEach((file: any) => {

web/src/hooks/use-llm-request.ts

@@ -8,9 +8,13 @@ import {
 } from '@/interfaces/database/llm';
 import { buildLlmUuid } from '@/utils/llm-util';
 
+export const enum LLMApiAction {
+  LlmList = 'llmList',
+}
+
 export const useFetchLlmList = (modelType?: LlmModelType) => {
   const { data } = useQuery<IThirdAiModelCollection>({
-    queryKey: ['llmList'],
+    queryKey: [LLMApiAction.LlmList],
     initialData: {},
     queryFn: async () => {
       const { data } = await userService.llm_list({ model_type: modelType });

web/src/hooks/use-user-setting-request.tsx

@@ -0,0 +1,464 @@
+import message from '@/components/ui/message';
+import { LanguageTranslationMap } from '@/constants/common';
+import { ResponseGetType } from '@/interfaces/database/base';
+import { IToken } from '@/interfaces/database/chat';
+import { ITenantInfo } from '@/interfaces/database/knowledge';
+import { ILangfuseConfig } from '@/interfaces/database/system';
+import {
+  ISystemStatus,
+  ITenant,
+  ITenantUser,
+  IUserInfo,
+} from '@/interfaces/database/user-setting';
+import { ISetLangfuseConfigRequestBody } from '@/interfaces/request/system';
+import userService, {
+  addTenantUser,
+  agreeTenant,
+  deleteTenantUser,
+  listTenant,
+  listTenantUser,
+} from '@/services/user-service';
+import { useMutation, useQuery, useQueryClient } from '@tanstack/react-query';
+import { Modal } from 'antd';
+import DOMPurify from 'dompurify';
+import { isEmpty } from 'lodash';
+import { useCallback, useMemo, useState } from 'react';
+import { useTranslation } from 'react-i18next';
+import { history } from 'umi';
+
+export const enum UserSettingApiAction {
+  UserInfo = 'userInfo',
+  TenantInfo = 'tenantInfo',
+  SaveSetting = 'saveSetting',
+  FetchManualSystemTokenList = 'fetchManualSystemTokenList',
+  FetchSystemTokenList = 'fetchSystemTokenList',
+  RemoveSystemToken = 'removeSystemToken',
+  CreateSystemToken = 'createSystemToken',
+  ListTenantUser = 'listTenantUser',
+  AddTenantUser = 'addTenantUser',
+  DeleteTenantUser = 'deleteTenantUser',
+  ListTenant = 'listTenant',
+  AgreeTenant = 'agreeTenant',
+  SetLangfuseConfig = 'setLangfuseConfig',
+  DeleteLangfuseConfig = 'deleteLangfuseConfig',
+  FetchLangfuseConfig = 'fetchLangfuseConfig',
+}
+
+export const useFetchUserInfo = (): ResponseGetType<IUserInfo> => {
+  const { i18n } = useTranslation();
+
+  const { data, isFetching: loading } = useQuery({
+    queryKey: [UserSettingApiAction.UserInfo],
+    initialData: {},
+    gcTime: 0,
+    queryFn: async () => {
+      const { data } = await userService.user_info();
+      if (data.code === 0) {
+        i18n.changeLanguage(
+          LanguageTranslationMap[
+            data.data.language as keyof typeof LanguageTranslationMap
+          ],
+        );
+      }
+      return data?.data ?? {};
+    },
+  });
+
+  return { data, loading };
+};
+
+export const useFetchTenantInfo = (
+  showEmptyModelWarn = false,
+): ResponseGetType<ITenantInfo> => {
+  const { t } = useTranslation();
+  const { data, isFetching: loading } = useQuery({
+    queryKey: [UserSettingApiAction.TenantInfo],
+    initialData: {},
+    gcTime: 0,
+    queryFn: async () => {
+      const { data: res } = await userService.get_tenant_info();
+      if (res.code === 0) {
+        // llm_id is chat_id
+        // asr_id is speech2txt
+        const { data } = res;
+        if (
+          showEmptyModelWarn &&
+          (isEmpty(data.embd_id) || isEmpty(data.llm_id))
+        ) {
+          Modal.warning({
+            title: t('common.warn'),
+            content: (
+              <div
+                dangerouslySetInnerHTML={{
+                  __html: DOMPurify.sanitize(t('setting.modelProvidersWarn')),
+                }}
+              ></div>
+            ),
+            onOk() {
+              history.push('/user-setting/model');
+            },
+          });
+        }
+        data.chat_id = data.llm_id;
+        data.speech2text_id = data.asr_id;
+
+        return data;
+      }
+
+      return res;
+    },
+  });
+
+  return { data, loading };
+};
+
+export const useSelectParserList = (): Array<{
+  value: string;
+  label: string;
+}> => {
+  const { data: tenantInfo } = useFetchTenantInfo(true);
+
+  const parserList = useMemo(() => {
+    const parserArray: Array<string> = tenantInfo?.parser_ids?.split(',') ?? [];
+    return parserArray.map((x) => {
+      const arr = x.split(':');
+      return { value: arr[0], label: arr[1] };
+    });
+  }, [tenantInfo]);
+
+  return parserList;
+};
+
+export const useSaveSetting = () => {
+  const queryClient = useQueryClient();
+  const { t } = useTranslation();
+  const {
+    data,
+    isPending: loading,
+    mutateAsync,
+  } = useMutation({
+    mutationKey: [UserSettingApiAction.SaveSetting],
+    mutationFn: async (
+      userInfo: { new_password: string } | Partial<IUserInfo>,
+    ) => {
+      const { data } = await userService.setting(userInfo);
+      if (data.code === 0) {
+        message.success(t('message.modified'));
+        queryClient.invalidateQueries({ queryKey: ['userInfo'] });
+      }
+      return data?.code;
+    },
+  });
+
+  return { data, loading, saveSetting: mutateAsync };
+};
+
+export const useFetchSystemVersion = () => {
+  const [version, setVersion] = useState('');
+  const [loading, setLoading] = useState(false);
+
+  const fetchSystemVersion = useCallback(async () => {
+    try {
+      setLoading(true);
+      const { data } = await userService.getSystemVersion();
+      if (data.code === 0) {
+        setVersion(data.data);
+        setLoading(false);
+      }
+    } catch (error) {
+      setLoading(false);
+    }
+  }, []);
+
+  return { fetchSystemVersion, version, loading };
+};
+
+export const useFetchSystemStatus = () => {
+  const [systemStatus, setSystemStatus] = useState<ISystemStatus>(
+    {} as ISystemStatus,
+  );
+  const [loading, setLoading] = useState(false);
+
+  const fetchSystemStatus = useCallback(async () => {
+    setLoading(true);
+    const { data } = await userService.getSystemStatus();
+    if (data.code === 0) {
+      setSystemStatus(data.data);
+      setLoading(false);
+    }
+  }, []);
+
+  return {
+    systemStatus,
+    fetchSystemStatus,
+    loading,
+  };
+};
+
+export const useFetchManualSystemTokenList = () => {
+  const {
+    data,
+    isPending: loading,
+    mutateAsync,
+  } = useMutation({
+    mutationKey: [UserSettingApiAction.FetchManualSystemTokenList],
+    mutationFn: async () => {
+      const { data } = await userService.listToken();
+
+      return data?.data ?? [];
+    },
+  });
+
+  return { data, loading, fetchSystemTokenList: mutateAsync };
+};
+
+export const useFetchSystemTokenList = () => {
+  const {
+    data,
+    isFetching: loading,
+    refetch,
+  } = useQuery<IToken[]>({
+    queryKey: [UserSettingApiAction.FetchSystemTokenList],
+    initialData: [],
+    gcTime: 0,
+    queryFn: async () => {
+      const { data } = await userService.listToken();
+
+      return data?.data ?? [];
+    },
+  });
+
+  return { data, loading, refetch };
+};
+
+export const useRemoveSystemToken = () => {
+  const queryClient = useQueryClient();
+  const { t } = useTranslation();
+
+  const {
+    data,
+    isPending: loading,
+    mutateAsync,
+  } = useMutation({
+    mutationKey: [UserSettingApiAction.RemoveSystemToken],
+    mutationFn: async (token: string) => {
+      const { data } = await userService.removeToken({}, token);
+      if (data.code === 0) {
+        message.success(t('message.deleted'));
+        queryClient.invalidateQueries({
+          queryKey: [UserSettingApiAction.FetchSystemTokenList],
+        });
+      }
+      return data?.data ?? [];
+    },
+  });
+
+  return { data, loading, removeToken: mutateAsync };
+};
+
+export const useCreateSystemToken = () => {
+  const queryClient = useQueryClient();
+
+  const {
+    data,
+    isPending: loading,
+    mutateAsync,
+  } = useMutation({
+    mutationKey: [UserSettingApiAction.CreateSystemToken],
+    mutationFn: async (params: Record<string, any>) => {
+      const { data } = await userService.createToken(params);
+      if (data.code === 0) {
+        queryClient.invalidateQueries({
+          queryKey: [UserSettingApiAction.FetchSystemTokenList],
+        });
+      }
+      return data?.data ?? [];
+    },
+  });
+
+  return { data, loading, createToken: mutateAsync };
+};
+
+export const useListTenantUser = () => {
+  const { data: tenantInfo } = useFetchTenantInfo();
+  const tenantId = tenantInfo.tenant_id;
+  const {
+    data,
+    isFetching: loading,
+    refetch,
+  } = useQuery<ITenantUser[]>({
+    queryKey: [UserSettingApiAction.ListTenantUser, tenantId],
+    initialData: [],
+    gcTime: 0,
+    enabled: !!tenantId,
+    queryFn: async () => {
+      const { data } = await listTenantUser(tenantId);
+
+      return data?.data ?? [];
+    },
+  });
+
+  return { data, loading, refetch };
+};
+
+export const useAddTenantUser = () => {
+  const { data: tenantInfo } = useFetchTenantInfo();
+  const queryClient = useQueryClient();
+  const {
+    data,
+    isPending: loading,
+    mutateAsync,
+  } = useMutation({
+    mutationKey: [UserSettingApiAction.AddTenantUser],
+    mutationFn: async (email: string) => {
+      const { data } = await addTenantUser(tenantInfo.tenant_id, email);
+      if (data.code === 0) {
+        queryClient.invalidateQueries({
+          queryKey: [UserSettingApiAction.ListTenantUser],
+        });
+      }
+      return data?.code;
+    },
+  });
+
+  return { data, loading, addTenantUser: mutateAsync };
+};
+
+export const useDeleteTenantUser = () => {
+  const { data: tenantInfo } = useFetchTenantInfo();
+  const queryClient = useQueryClient();
+  const { t } = useTranslation();
+
+  const {
+    data,
+    isPending: loading,
+    mutateAsync,
+  } = useMutation({
+    mutationKey: [UserSettingApiAction.DeleteTenantUser],
+    mutationFn: async ({
+      userId,
+      tenantId,
+    }: {
+      userId: string;
+      tenantId?: string;
+    }) => {
+      const { data } = await deleteTenantUser({
+        tenantId: tenantId ?? tenantInfo.tenant_id,
+        userId,
+      });
+      if (data.code === 0) {
+        message.success(t('message.deleted'));
+        queryClient.invalidateQueries({
+          queryKey: [UserSettingApiAction.ListTenantUser],
+        });
+        queryClient.invalidateQueries({
+          queryKey: [UserSettingApiAction.ListTenant],
+        });
+      }
+      return data?.data ?? [];
+    },
+  });
+
+  return { data, loading, deleteTenantUser: mutateAsync };
+};
+
+export const useListTenant = () => {
+  const { data: tenantInfo } = useFetchTenantInfo();
+  const tenantId = tenantInfo.tenant_id;
+  const {
+    data,
+    isFetching: loading,
+    refetch,
+  } = useQuery<ITenant[]>({
+    queryKey: [UserSettingApiAction.ListTenant, tenantId],
+    initialData: [],
+    gcTime: 0,
+    enabled: !!tenantId,
+    queryFn: async () => {
+      const { data } = await listTenant();
+
+      return data?.data ?? [];
+    },
+  });
+
+  return { data, loading, refetch };
+};
+
+export const useAgreeTenant = () => {
+  const queryClient = useQueryClient();
+  const { t } = useTranslation();
+
+  const {
+    data,
+    isPending: loading,
+    mutateAsync,
+  } = useMutation({
+    mutationKey: [UserSettingApiAction.AgreeTenant],
+    mutationFn: async (tenantId: string) => {
+      const { data } = await agreeTenant(tenantId);
+      if (data.code === 0) {
+        message.success(t('message.operated'));
+        queryClient.invalidateQueries({
+          queryKey: [UserSettingApiAction.ListTenant],
+        });
+      }
+      return data?.data ?? [];
+    },
+  });
+
+  return { data, loading, agreeTenant: mutateAsync };
+};
+
+export const useSetLangfuseConfig = () => {
+  const { t } = useTranslation();
+  const {
+    data,
+    isPending: loading,
+    mutateAsync,
+  } = useMutation({
+    mutationKey: [UserSettingApiAction.SetLangfuseConfig],
+    mutationFn: async (params: ISetLangfuseConfigRequestBody) => {
+      const { data } = await userService.setLangfuseConfig(params);
+      if (data.code === 0) {
+        message.success(t('message.operated'));
+      }
+      return data?.code;
+    },
+  });
+
+  return { data, loading, setLangfuseConfig: mutateAsync };
+};
+
+export const useDeleteLangfuseConfig = () => {
+  const { t } = useTranslation();
+  const {
+    data,
+    isPending: loading,
+    mutateAsync,
+  } = useMutation({
+    mutationKey: [UserSettingApiAction.DeleteLangfuseConfig],
+    mutationFn: async () => {
+      const { data } = await userService.deleteLangfuseConfig();
+      if (data.code === 0) {
+        message.success(t('message.deleted'));
+      }
+      return data?.code;
+    },
+  });
+
+  return { data, loading, deleteLangfuseConfig: mutateAsync };
+};
+
+export const useFetchLangfuseConfig = () => {
+  const { data, isFetching: loading } = useQuery<ILangfuseConfig>({
+    queryKey: [UserSettingApiAction.FetchLangfuseConfig],
+    gcTime: 0,
+    queryFn: async () => {
+      const { data } = await userService.getLangfuseConfig();
+
+      return data?.data;
+    },
+  });
+
+  return { data, loading };
+};

web/src/layouts/bell-button.tsx

@@ -0,0 +1,28 @@
+import { Button } from '@/components/ui/button';
+import { useNavigateWithFromState } from '@/hooks/route-hook';
+import { useListTenant } from '@/hooks/use-user-setting-request';
+import { TenantRole } from '@/pages/user-setting/constants';
+import { BellRing } from 'lucide-react';
+import { useCallback, useMemo } from 'react';
+
+export function BellButton() {
+  const { data } = useListTenant();
+  const navigate = useNavigateWithFromState();
+
+  const showBell = useMemo(() => {
+    return data.some((x) => x.role === TenantRole.Invite);
+  }, [data]);
+
+  const handleBellClick = useCallback(() => {
+    navigate('/user-setting/team');
+  }, [navigate]);
+
+  return showBell ? (
+    <Button variant={'ghost'} onClick={handleBellClick}>
+      <div className="relative">
+        <BellRing className="size-4 " />
+        <span className="absolute size-1 rounded -right-1 -top-1 bg-red-600"></span>
+      </div>
+    </Button>
+  ) : null;
+}

web/src/layouts/next-header.tsx

@@ -31,6 +31,7 @@ import {
 import React, { useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
 import { useLocation } from 'umi';
+import { BellButton } from './bell-button';
 
 const handleDocHelpCLick = () => {
   window.open('https://ragflow.io/docs/dev/category/guides', 'target');
@@ -53,12 +54,6 @@ export function Header() {
     changeLanguage(key);
   };
 
-  // const { data } = useListTenant();
-
-  // const showBell = useMemo(() => {
-  //   return data.some((x) => x.role === TenantRole.Invite);
-  // }, [data]);
-
   const items = LanguageList.map((x) => ({
     key: x,
     label: <span>{LanguageMap[x as keyof typeof LanguageMap]}</span>,
@@ -68,10 +63,6 @@ export function Header() {
     setTheme(theme === ThemeEnum.Dark ? ThemeEnum.Light : ThemeEnum.Dark);
   }, [setTheme, theme]);
 
-  // const handleBellClick = useCallback(() => {
-  //   navigate('/user-setting/team');
-  // }, [navigate]);
-
   const tagsData = useMemo(
     () => [
       { path: Routes.Root, name: t('header.Root'), icon: House },
@@ -160,6 +151,7 @@ export function Header() {
         <Button variant={'ghost'} onClick={onThemeClick}>
           {theme === 'light' ? <Sun /> : <Moon />}
         </Button>
+        <BellButton></BellButton>
         <div className="relative">
           <RAGFlowAvatar
             name={nickname}

web/src/locales/en.ts

@@ -1,6 +1,7 @@
 export default {
   translation: {
     common: {
+      selectPlaceholder: 'select value',
       delete: 'Delete',
       deleteModalTitle: 'Are you sure to delete this item?',
       ok: 'Yes',
@@ -70,7 +71,7 @@ export default {
       review: 'from 500+ reviews',
     },
     header: {
-      knowledgeBase: 'Knowledge Base',
+      knowledgeBase: 'Dataset',
       chat: 'Chat',
       register: 'Register',
       signin: 'Sign in',
@@ -86,7 +87,7 @@ export default {
     knowledgeList: {
       welcome: 'Welcome back',
       description: 'Which knowledge bases will you use today?',
-      createKnowledgeBase: 'Create knowledge base',
+      createKnowledgeBase: 'Create Dataset',
       name: 'Name',
       namePlaceholder: 'Please input name!',
       doc: 'Docs',
@@ -94,6 +95,16 @@ export default {
       noMoreData: `That's all. Nothing more.`,
     },
     knowledgeDetails: {
+      created: 'Created',
+      learnMore: 'Learn More',
+      general: 'General',
+      chunkMethodTab: 'Chunk Method',
+      testResults: 'Test Results',
+      testSetting: 'Test Setting',
+      retrievalTesting: 'Retrieval Testing',
+      retrievalTestingDescription:
+        'Conduct a retrieval test to check if RAGFlow can recover the intended content for the LLM.',
+      Parse: 'Parse',
       dataset: 'Dataset',
       testing: 'Retrieval testing',
       files: 'files',
@@ -479,6 +490,7 @@ This auto-tagging feature enhances retrieval by adding another layer of domain-s
       improvise: 'Improvise',
       precise: 'Precise',
       balance: 'Balance',
+      custom: 'Custom',
       freedomTip: `A shortcut to 'Temperature', 'Top P', 'Presence penalty', and 'Frequency penalty' settings, indicating the freedom level of the model. This parameter has three options: Select 'Improvise' to produce more creative responses; select 'Precise' (default) to produce more conservative responses; 'Balance' is a middle ground between 'Improvise' and 'Precise'.`,
       temperature: 'Temperature',
       temperatureMessage: 'Temperature is required',
@@ -845,6 +857,7 @@ This auto-tagging feature enhances retrieval by adding another layer of domain-s
       uploadLimit:
         'Each file must not exceed 10MB, and the total number of files must not exceed 128.',
       destinationFolder: 'Destination folder',
+      pleaseUploadAtLeastOneFile: 'Please upload at least one file',
     },
     flow: {
       cite: 'Cite',
@@ -1441,6 +1454,7 @@ This delimiter is used to split the input text into several text pieces echo of
       showQueryMindmap: 'Show Query Mindmap',
       embedApp: 'Embed App',
       relatedSearch: 'Related Search',
+      descriptionValue: 'You are an intelligent assistant.',
       okText: 'Save',
       cancelText: 'Cancel',
     },

web/src/locales/fr.ts

@@ -240,9 +240,8 @@ export default {
       promptTip:
         'Décrivez la tâche attendue du LLM, ses réponses, ses exigences, etc. Utilisez `/` pour afficher les variables disponibles.',
       promptMessage: 'Le prompt est requis',
-      promptText: `Veuillez résumer les paragraphes suivants. Attention aux chiffres, ne pas inventer. Paragraphes suivants : {cluster_content
-      }
-    Le contenu à résumer est ci-dessus.`,
+      promptText: `Veuillez résumer les paragraphes suivants. Attention aux chiffres, ne pas inventer. Paragraphes suivants : {cluster_content}
+  Le contenu à résumer est ci-dessus.`,
       maxToken: 'Nombre maximal de tokens',
       maxTokenTip: 'Nombre maximal de tokens générés par résumé.',
       maxTokenMessage: 'Nombre maximal de tokens requis',

web/src/locales/zh-traditional.ts

@@ -454,6 +454,7 @@ export default {
       improvise: '即興創作',
       precise: '精確',
       balance: '平衡',
+      custom: '自定義',
       freedomTip: `“精確”意味著法學碩士會保守並謹慎地回答你的問題。“即興發揮”意味著你希望法學碩士能夠自由地暢所欲言。“平衡”是謹慎與自由之間的平衡。`,
       temperature: '溫度',
       temperatureMessage: '溫度是必填項',

web/src/locales/zh.ts

@@ -1,6 +1,7 @@
 export default {
   translation: {
     common: {
+      selectPlaceholder: '请选择',
       delete: '删除',
       deleteModalTitle: '确定删除吗?',
       ok: '是',
@@ -86,6 +87,16 @@ export default {
       noMoreData: '没有更多数据了',
     },
     knowledgeDetails: {
+      created: '创建于',
+      learnMore: '了解更多',
+      general: '通用',
+      chunkMethodTab: '切片方法',
+      testResults: '测试结果',
+      testSetting: '测试设置',
+      retrievalTesting: '知识检索测试',
+      retrievalTestingDescription:
+        '进行检索测试，检查 RAGFlow 是否能够为大语言模型（LLM）恢复预期的内容。',
+      Parse: '解析',
       dataset: '数据集',
       testing: '检索测试',
       configuration: '配置',
@@ -477,6 +488,7 @@ General：实体和关系提取提示来自 GitHub - microsoft/graphrag：基于
       improvise: '即兴创作',
       precise: '精确',
       balance: '平衡',
+      custom: '自定义',
       freedomTip: `“精确”意味着大语言模型会保守并谨慎地回答你的问题。 “即兴发挥”意味着你希望大语言模型能够自由地畅所欲言。 “平衡”是谨慎与自由之间的平衡。`,
       temperature: '温度',
       temperatureMessage: '温度是必填项',
@@ -799,6 +811,7 @@ General：实体和关系提取提示来自 GitHub - microsoft/graphrag：基于
       fileError: '文件错误',
       uploadLimit: '文件大小不能超过10M，文件总数不超过128个',
       destinationFolder: '目标文件夹',
+      pleaseUploadAtLeastOneFile: '请上传至少一个文件',
     },
     flow: {
       flow: '工作流',
@@ -1344,6 +1357,7 @@ General：实体和关系提取提示来自 GitHub - microsoft/graphrag：基于
       showQueryMindmap: '显示查询思维导图',
       embedApp: '嵌入网站',
       relatedSearch: '相关搜索',
+      descriptionValue: '你是一位智能助手。',
       okText: '保存',
       cancelText: '返回',
     },

web/src/pages/agent/chat/use-send-agent-message.ts

@@ -4,6 +4,7 @@ import {
   useHandleMessageInputChange,
   useSelectDerivedMessages,
 } from '@/hooks/logic-hooks';
+import { useFetchAgent } from '@/hooks/use-agent-request';
 import {
   IEventList,
   IInputEvent,
@@ -188,11 +189,7 @@ export const useSendAgentMessage = (
     return answerList[0]?.message_id;
   }, [answerList]);
 
-  useEffect(() => {
-    if (answerList[0]?.session_id) {
-      setSessionId(answerList[0]?.session_id);
-    }
-  }, [answerList]);
+  const { refetch } = useFetchAgent();
 
   const { findReferenceByMessageId } = useFindMessageReference(answerList);
   const prologue = useGetBeginNodePrologue();
@@ -250,7 +247,7 @@ export const useSendAgentMessage = (
           setValue(message.content);
           removeLatestMessage();
         } else {
-          // refetch(); // pull the message list after sending the message successfully
+          refetch(); // pull the message list after sending the message successfully
         }
       } catch (error) {
         console.log('🚀 ~ useSendAgentMessage ~ error:', error);
@@ -258,28 +255,30 @@ export const useSendAgentMessage = (
     },
     [
       agentId,
-      sessionId,
-      send,
-      clearUploadResponseList,
       inputs,
       beginParams,
       uploadResponseList,
+      sessionId,
+      send,
+      clearUploadResponseList,
       setValue,
       removeLatestMessage,
+      refetch,
     ],
   );
 
   const sendFormMessage = useCallback(
-    (body: { id?: string; inputs: Record<string, BeginQuery> }) => {
-      send({ ...body, session_id: sessionId });
+    async (body: { id?: string; inputs: Record<string, BeginQuery> }) => {
       addNewestOneQuestion({
         content: Object.entries(body.inputs)
           .map(([key, val]) => `${key}: ${val.value}`)
           .join('<br/>'),
         role: MessageType.User,
       });
+      await send({ ...body, session_id: sessionId });
+      refetch();
     },
-    [addNewestOneQuestion, send, sessionId],
+    [addNewestOneQuestion, refetch, send, sessionId],
   );
 
   // reset session
@@ -346,6 +345,12 @@ export const useSendAgentMessage = (
     }
   }, [addEventList, answerList, addEventListFun, messageId]);
 
+  useEffect(() => {
+    if (answerList[0]?.session_id) {
+      setSessionId(answerList[0]?.session_id);
+    }
+  }, [answerList]);
+
   return {
     value,
     sendLoading: !done,

web/src/pages/agent/index.tsx

@@ -210,7 +210,9 @@ export default function Agent() {
         ></EmbedDialog>
       )}
       {versionDialogVisible && (
-        <VersionDialog hideModal={hideVersionDialog}></VersionDialog>
+        <DropdownProvider>
+          <VersionDialog hideModal={hideVersionDialog}></VersionDialog>
+        </DropdownProvider>
       )}
       {settingDialogVisible && (
         <SettingDialog hideModal={hideSettingDialog}></SettingDialog>

web/src/pages/agent/upload-agent-dialog/upload-agent-form.tsx

@@ -63,7 +63,6 @@ export function UploadAgentForm({ hideModal, onOk }: IModalProps<any>) {
                   value={field.value}
                   onValueChange={field.onChange}
                   maxFileCount={1}
-                  maxSize={4 * 1024 * 1024}
                   accept={{ '*.json': [FileMimeType.Json] }}
                 />
               </FormControl>

web/src/pages/chunk/parsed-result/add-knowledge/components/knowledge-chunk/index.less

@@ -35,7 +35,7 @@
 
   .documentPreview {
     // width: 40%;
-    height: calc(100vh - 130px);
+    height: calc(100vh - 180px);
     overflow: auto;
   }
 

web/src/pages/dataset/dataset/constant.ts

@@ -3,15 +3,15 @@ import { RunningStatus } from '@/constants/knowledge';
 export const RunningStatusMap = {
   [RunningStatus.UNSTART]: {
     label: 'UNSTART',
-    color: 'cyan',
+    color: 'var(--accent-primary)',
   },
   [RunningStatus.RUNNING]: {
     label: 'Parsing',
-    color: 'blue',
+    color: 'var(--team-member)',
   },
-  [RunningStatus.CANCEL]: { label: 'CANCEL', color: 'orange' },
-  [RunningStatus.DONE]: { label: 'SUCCESS', color: 'blue' },
-  [RunningStatus.FAIL]: { label: 'FAIL', color: 'red' },
+  [RunningStatus.CANCEL]: { label: 'CANCEL', color: 'var(--state-warning)' },
+  [RunningStatus.DONE]: { label: 'SUCCESS', color: 'var(--state-success)' },
+  [RunningStatus.FAIL]: { label: 'FAIL', color: 'var(--state-error' },
 };
 
 export * from '@/constants/knowledge';

web/src/pages/dataset/dataset/dataset-action-cell.tsx

@@ -11,7 +11,7 @@ import { IDocumentInfo } from '@/interfaces/database/document';
 import { formatFileSize } from '@/utils/common-util';
 import { formatDate } from '@/utils/date';
 import { downloadDocument } from '@/utils/file-util';
-import { ArrowDownToLine, FolderPen, ScrollText, Trash2 } from 'lucide-react';
+import { Download, Eye, PenLine, Trash2 } from 'lucide-react';
 import { useCallback } from 'react';
 import { UseRenameDocumentShowType } from './use-rename-document';
 import { isParserRunning } from './utils';
@@ -57,12 +57,12 @@ export function DatasetActionCell({
         disabled={isRunning}
         onClick={handleRename}
       >
-        <FolderPen />
+        <PenLine />
       </Button>
       <HoverCard>
         <HoverCardTrigger>
           <Button variant="ghost" disabled={isRunning} size={'sm'}>
-            <ScrollText />
+            <Eye />
           </Button>
         </HoverCardTrigger>
         <HoverCardContent className="w-[40vw] max-h-[40vh] overflow-auto">
@@ -93,7 +93,7 @@ export function DatasetActionCell({
           disabled={isRunning}
           size={'sm'}
         >
-          <ArrowDownToLine />
+          <Download />
         </Button>
       )}
       <ConfirmDeleteDialog onOk={handleRemove}>

web/src/pages/dataset/dataset/dataset-table.tsx

@@ -164,7 +164,7 @@ export function DatasetTable({
           )}
         </TableBody>
       </Table>
-      <div className="flex items-center justify-end  py-4">
+      <div className="flex items-center justify-end  py-4 absolute bottom-3 right-3">
         <div className="space-x-2">
           <RAGFlowPagination
             {...pick(pagination, 'current', 'pageSize')}

web/src/pages/dataset/dataset/index.tsx

@@ -111,6 +111,7 @@ export default function Dataset() {
           hideModal={hideDocumentUploadModal}
           onOk={onDocumentUploadOk}
           loading={documentUploadLoading}
+          showParseOnCreation
         ></FileUploadDialog>
       )}
       {createVisible && (

web/src/pages/dataset/dataset/parsing-card.tsx

@@ -17,7 +17,7 @@ function Dot({ run }: { run: RunningStatus }) {
   const runningStatus = RunningStatusMap[run];
   return (
     <span
-      className={'size-2 inline-block rounded'}
+      className={'size-1 inline-block rounded'}
       style={{ backgroundColor: runningStatus.color }}
     ></span>
   );
@@ -89,7 +89,7 @@ export function ParsingCard({ record }: IProps) {
   return (
     <HoverCard>
       <HoverCardTrigger asChild>
-        <Button variant={'ghost'} size={'sm'}>
+        <Button variant={'transparent'} className="border-none" size={'sm'}>
           <Dot run={record.run}></Dot>
         </Button>
       </HoverCardTrigger>

web/src/pages/dataset/dataset/parsing-status-cell.tsx

@@ -14,7 +14,7 @@ import {
 import { Progress } from '@/components/ui/progress';
 import { Separator } from '@/components/ui/separator';
 import { IDocumentInfo } from '@/interfaces/database/document';
-import { CircleX, Play, RefreshCw } from 'lucide-react';
+import { CircleX, RefreshCw } from 'lucide-react';
 import { useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 import { RunningStatus } from './constant';
@@ -24,11 +24,13 @@ import { useHandleRunDocumentByIds } from './use-run-document';
 import { UseSaveMetaShowType } from './use-save-meta';
 import { isParserRunning } from './utils';
 const IconMap = {
-  [RunningStatus.UNSTART]: <Play />,
-  [RunningStatus.RUNNING]: <CircleX />,
-  [RunningStatus.CANCEL]: <RefreshCw />,
-  [RunningStatus.DONE]: <RefreshCw />,
-  [RunningStatus.FAIL]: <RefreshCw />,
+  [RunningStatus.UNSTART]: (
+    <div className="w-0 h-0 border-l-[10px] border-l-accent-primary border-t-8 border-r-4 border-b-8 border-transparent"></div>
+  ),
+  [RunningStatus.RUNNING]: <CircleX size={14} color="var(--state-error)" />,
+  [RunningStatus.CANCEL]: <RefreshCw size={14} color="var(--accent-primary)" />,
+  [RunningStatus.DONE]: <RefreshCw size={14} color="var(--accent-primary)" />,
+  [RunningStatus.FAIL]: <RefreshCw size={14} color="var(--accent-primary)" />,
 };
 
 export function ParsingStatusCell({
@@ -60,11 +62,11 @@ export function ParsingStatusCell({
   }, [record, showSetMetaModal]);
 
   return (
-    <section className="flex gap-2 items-center">
-      <div className="w-28 flex items-center justify-between">
+    <section className="flex gap-8 items-center">
+      <div className="w-fit flex items-center justify-between">
         <DropdownMenu>
           <DropdownMenuTrigger asChild>
-            <Button variant={'ghost'} size={'sm'}>
+            <Button variant={'transparent'} className="border-none" size={'sm'}>
               {parser_id === 'naive' ? 'general' : parser_id}
             </Button>
           </DropdownMenuTrigger>
@@ -77,7 +79,6 @@ export function ParsingStatusCell({
             </DropdownMenuItem>
           </DropdownMenuContent>
         </DropdownMenu>
-        <Separator orientation="vertical" className="h-2.5" />
       </div>
       <ConfirmDeleteDialog
         title={t(`knowledgeDetails.redo`, { chunkNum: chunk_num })}
@@ -85,17 +86,17 @@ export function ParsingStatusCell({
         onOk={handleOperationIconClick(true)}
         onCancel={handleOperationIconClick(false)}
       >
-        <Button
-          variant={'ghost'}
-          size={'sm'}
+        <div
+          className="cursor-pointer flex items-center gap-3"
           onClick={
             isZeroChunk || isRunning
               ? handleOperationIconClick(false)
               : () => {}
           }
         >
+          <Separator orientation="vertical" className="h-2.5" />
           {operationIcon}
-        </Button>
+        </div>
       </ConfirmDeleteDialog>
       {isParserRunning(run) ? (
         <HoverCard>

web/src/pages/dataset/dataset/use-dataset-table-columns.tsx

@@ -65,7 +65,8 @@ export function useDatasetTableColumns({
       header: ({ column }) => {
         return (
           <Button
-            variant="ghost"
+            variant="transparent"
+            className="border-none"
             onClick={() => column.toggleSorting(column.getIsSorted() === 'asc')}
           >
             {t('name')}
@@ -103,7 +104,8 @@ export function useDatasetTableColumns({
       header: ({ column }) => {
         return (
           <Button
-            variant="ghost"
+            variant="transparent"
+            className="border-none"
             onClick={() => column.toggleSorting(column.getIsSorted() === 'asc')}
           >
             {t('uploadDate')}
@@ -141,7 +143,7 @@ export function useDatasetTableColumns({
     },
     {
       accessorKey: 'run',
-      header: t('parsingStatus'),
+      header: t('Parse'),
       // meta: { cellClassName: 'min-w-[20vw]' },
       cell: ({ row }) => {
         return (

web/src/pages/dataset/dataset/use-upload-document.ts

@@ -1,5 +1,9 @@
+import { UploadFormSchemaType } from '@/components/file-upload-dialog';
 import { useSetModalState } from '@/hooks/common-hooks';
-import { useUploadNextDocument } from '@/hooks/use-document-request';
+import {
+  useRunDocument,
+  useUploadNextDocument,
+} from '@/hooks/use-document-request';
 import { getUnSupportedFilesCount } from '@/utils/document-util';
 import { useCallback } from 'react';
 
@@ -10,14 +14,24 @@ export const useHandleUploadDocument = () => {
     showModal: showDocumentUploadModal,
   } = useSetModalState();
   const { uploadDocument, loading } = useUploadNextDocument();
+  const { runDocumentByIds } = useRunDocument();
 
   const onDocumentUploadOk = useCallback(
-    async (fileList: File[]): Promise<number | undefined> => {
+    async ({ fileList, parseOnCreation }: UploadFormSchemaType) => {
       if (fileList.length > 0) {
-        const ret: any = await uploadDocument(fileList);
+        const ret = await uploadDocument(fileList);
         if (typeof ret?.message !== 'string') {
           return;
         }
+
+        if (ret.code === 0 && parseOnCreation) {
+          runDocumentByIds({
+            documentIds: ret.data.map((x) => x.id),
+            run: 1,
+            shouldDelete: false,
+          });
+        }
+
         const count = getUnSupportedFilesCount(ret?.message);
         /// 500 error code indicates that some file types are not supported
         let code = ret?.code;
@@ -31,7 +45,7 @@ export const useHandleUploadDocument = () => {
         return code;
       }
     },
-    [uploadDocument, hideDocumentUploadModal],
+    [uploadDocument, runDocumentByIds, hideDocumentUploadModal],
   );
 
   return {

web/src/pages/dataset/index.tsx

@@ -19,7 +19,7 @@ export default function DatasetWrapper() {
   const { data } = useFetchKnowledgeBaseConfiguration();
 
   return (
-    <section>
+    <section className="flex h-full flex-col w-full">
       <PageHeader>
         <Breadcrumb>
           <BreadcrumbList>
@@ -30,12 +30,14 @@ export default function DatasetWrapper() {
             </BreadcrumbItem>
             <BreadcrumbSeparator />
             <BreadcrumbItem>
-              <BreadcrumbPage>{data.name}</BreadcrumbPage>
+              <BreadcrumbPage className="w-28 whitespace-nowrap text-ellipsis overflow-hidden">
+                {data.name}
+              </BreadcrumbPage>
             </BreadcrumbItem>
           </BreadcrumbList>
         </Breadcrumb>
       </PageHeader>
-      <div className="flex flex-1">
+      <div className="flex flex-1 min-h-0">
         <SideBar></SideBar>
         <div className="flex-1">
           <Outlet />

web/src/pages/dataset/setting/chunk-method-form.tsx

@@ -66,10 +66,10 @@ export function ChunkMethodForm() {
   }, [finalParserId]);
 
   return (
-    <>
-      <section className="overflow-auto max-h-[76vh]">
+    <section className="h-full flex flex-col">
+      <div className="overflow-auto flex-1 min-h-0">
         <ConfigurationComponent></ConfigurationComponent>
-      </section>
+      </div>
       <div className="text-right pt-4 flex justify-end gap-3">
         <Button
           type="reset"
@@ -112,6 +112,6 @@ export function ChunkMethodForm() {
           {t('knowledgeConfiguration.save')}
         </Button>
       </div>
-    </>
+    </section>
   );
 }

web/src/pages/dataset/setting/chunk-method-learn-more.tsx

@@ -1,4 +1,6 @@
 import { Button } from '@/components/ui/button';
+import { cn } from '@/lib/utils';
+import { t } from 'i18next';
 import { X } from 'lucide-react';
 import { useState } from 'react';
 import CategoryPanel from './category-panel';
@@ -14,20 +16,22 @@ export default ({
 
   return (
     <div
-      style={{
-        display: tab === 'chunkMethodForm' ? 'block' : 'none',
-      }}
+      className={cn('hidden flex-1', {
+        'flex flex-col': tab === 'chunkMethodForm',
+      })}
     >
-      <Button
-        variant="outline"
-        onClick={() => {
-          setVisible(!visible);
-        }}
-      >
-        Learn More
-      </Button>
+      <div>
+        <Button
+          variant="outline"
+          onClick={() => {
+            setVisible(!visible);
+          }}
+        >
+          {t('knowledgeDetails.learnMore')}
+        </Button>
+      </div>
       <div
-        className="bg-[#FFF]/10 p-[20px] rounded-[12px] mt-[10px] relative"
+        className="bg-[#FFF]/10 p-[20px] rounded-[12px] mt-[10px] relative flex-1 overflow-auto"
         style={{ display: visible ? 'block' : 'none' }}
       >
         <CategoryPanel chunkMethod={parserId}></CategoryPanel>

web/src/pages/dataset/setting/configuration/common-item.tsx

@@ -29,7 +29,7 @@ export function ChunkMethodItem() {
           <div className="flex items-center">
             <FormLabel
               tooltip={t('chunkMethodTip')}
-              className="text-sm text-muted-foreground whitespace-nowrap w-1/4"
+              className="text-sm text-muted-foreground whitespace-wrap w-1/4"
             >
               {t('chunkMethod')}
             </FormLabel>
@@ -69,7 +69,7 @@ export function EmbeddingModelItem() {
           <div className="flex items-center">
             <FormLabel
               tooltip={t('embeddingModelTip')}
-              className="text-sm text-muted-foreground whitespace-nowrap w-1/4"
+              className="text-sm text-muted-foreground whitespace-wrap w-1/4"
             >
               {t('embeddingModel')}
             </FormLabel>

web/src/pages/dataset/setting/general-form.tsx

@@ -1,6 +1,8 @@
 import { FormContainer } from '@/components/form-container';
+import { SelectWithSearch } from '@/components/originui/select-with-search';
+import { RAGFlowFormItem } from '@/components/ragflow-form';
 import { Avatar, AvatarFallback, AvatarImage } from '@/components/ui/avatar';
-import { Button } from '@/components/ui/button';
+import { Button, ButtonLoading } from '@/components/ui/button';
 import {
   FormControl,
   FormField,
@@ -9,9 +11,10 @@ import {
   FormMessage,
 } from '@/components/ui/form';
 import { Input } from '@/components/ui/input';
+import { PermissionRole } from '@/constants/permission';
 import { useUpdateKnowledge } from '@/hooks/knowledge-hooks';
 import { transformFile2Base64 } from '@/utils/file-util';
-import { Loader2Icon, Pencil, Upload } from 'lucide-react';
+import { Pencil, Upload } from 'lucide-react';
 import { useEffect, useMemo, useState } from 'react';
 import { useFormContext } from 'react-hook-form';
 import { useTranslation } from 'react-i18next';
@@ -33,6 +36,13 @@ export function GeneralForm() {
   const parser_id = defaultValues['parser_id'];
   const { id: kb_id } = useParams();
 
+  const teamOptions = useMemo(() => {
+    return Object.values(PermissionRole).map((x) => ({
+      label: t('knowledgeConfiguration.' + x),
+      value: x,
+    }));
+  }, [t]);
+
   // init avatar file if it exists in defaultValues
   useEffect(() => {
     if (!avatarFile) {
@@ -171,24 +181,35 @@ export function GeneralForm() {
             );
           }}
         />
+        <RAGFlowFormItem
+          name="permission"
+          label={t('knowledgeConfiguration.permissions')}
+          tooltip={t('knowledgeConfiguration.permissionsTip')}
+          horizontal
+        >
+          <SelectWithSearch
+            options={teamOptions}
+            triggerClassName="w-3/4"
+          ></SelectWithSearch>
+        </RAGFlowFormItem>
       </FormContainer>
       <div className="text-right pt-4 flex justify-end gap-3">
         <Button
           type="reset"
-          className="bg-transparent text-color-white hover:bg-transparent border-gray-500 border-[1px]"
+          variant={'outline'}
           onClick={() => {
             form.reset();
           }}
         >
           {t('knowledgeConfiguration.cancel')}
         </Button>
-        <Button
+        <ButtonLoading
           type="button"
-          disabled={submitLoading}
+          loading={submitLoading}
           onClick={() => {
             (async () => {
-              let isValidate = await form.formControl.trigger('name');
-              const { name, description } = form.formState.values;
+              let isValidate = await form.trigger('name');
+              const { name, description, permission } = form.getValues();
               const avatar = avatarBase64Str;
 
               if (isValidate) {
@@ -198,14 +219,14 @@ export function GeneralForm() {
                   name,
                   description,
                   avatar,
+                  permission,
                 });
               }
             })();
           }}
         >
-          {submitLoading && <Loader2Icon className="animate-spin" />}
           {t('knowledgeConfiguration.save')}
-        </Button>
+        </ButtonLoading>
       </div>
     </>
   );

web/src/pages/dataset/setting/index.tsx

@@ -6,6 +6,7 @@ import {
   TabsTrigger,
 } from '@/components/ui/tabs-underlined';
 import { DocumentParserType } from '@/constants/knowledge';
+import { PermissionRole } from '@/constants/permission';
 import { zodResolver } from '@hookform/resolvers/zod';
 import { useState } from 'react';
 import { useForm, useWatch } from 'react-hook-form';
@@ -43,7 +44,7 @@ export default function DatasetSettings() {
     defaultValues: {
       name: '',
       parser_id: DocumentParserType.Naive,
-      permission: 'me',
+      permission: PermissionRole.Me,
       parser_config: {
         layout_recognize: DocumentType.DeepDOC,
         chunk_token_num: 512,
@@ -81,22 +82,23 @@ export default function DatasetSettings() {
   }
 
   return (
-    <section className="p-5 ">
+    <section className="p-5 h-full flex flex-col">
       <TopTitle
         title={t('knowledgeDetails.configuration')}
         description={t('knowledgeConfiguration.titleDescription')}
       ></TopTitle>
-      <div className="flex gap-14">
+      <div className="flex gap-14 flex-1 min-h-0">
         <Form {...form}>
           <form
             onSubmit={form.handleSubmit(onSubmit)}
-            className="space-y-6 basis-full min-w-[1000px] max-w-[1000px]"
+            className="space-y-6 flex-1"
           >
             <Tabs
               defaultValue="generalForm"
               onValueChange={(val) => {
                 setCurrentTab(val);
               }}
+              className="h-full flex flex-col"
             >
               <TabsList className="grid bg-transparent grid-cols-2 rounded-none text-foreground">
                 <TabsTrigger
@@ -105,7 +107,7 @@ export default function DatasetSettings() {
                 >
                   <div className="flex w-full h-full justify-center	items-center">
                     <span className="h-full group-data-[state=active]:border-b-2 border-foreground	">
-                      General
+                      {t('knowledgeDetails.general')}
                     </span>
                   </div>
                 </TabsTrigger>
@@ -115,15 +117,15 @@ export default function DatasetSettings() {
                 >
                   <div className="flex w-full h-full justify-center	items-center">
                     <span className="h-full group-data-[state=active]:border-b-2 border-foreground	">
-                      Chunk Method
+                      {t('knowledgeDetails.chunkMethodTab')}
                     </span>
                   </div>
                 </TabsTrigger>
               </TabsList>
-              <TabsContent value="generalForm">
+              <TabsContent value="generalForm" className="flex-1 min-h-0">
                 <GeneralForm></GeneralForm>
               </TabsContent>
-              <TabsContent value="chunkMethodForm">
+              <TabsContent value="chunkMethodForm" className="flex-1 min-h-0">
                 <ChunkMethodForm></ChunkMethodForm>
               </TabsContent>
             </Tabs>

web/src/pages/dataset/sidebar/index.tsx

@@ -62,15 +62,19 @@ export function SideBar({ refreshCount }: PropType) {
           name={data.name}
           className="size-16"
         ></RAGFlowAvatar>
-        <div className=" text-text-secondary text-xs space-y-1">
-          <h3 className="text-lg font-semibold line-clamp-1 text-text-primary">
+        <div className=" text-text-secondary text-xs space-y-1 overflow-hidden">
+          <h3 className="text-lg font-semibold line-clamp-1 text-text-primary text-ellipsis overflow-hidden">
             {data.name}
           </h3>
           <div className="flex justify-between">
-            <span>{data.doc_num} files</span>
+            <span>
+              {data.doc_num} {t('knowledgeDetails.files')}
+            </span>
             <span>{formatBytes(data.size)}</span>
           </div>
-          <div>Created {formatPureDate(data.create_time)}</div>
+          <div>
+            {t('knowledgeDetails.created')} {formatPureDate(data.create_time)}
+          </div>
         </div>
       </div>
 

web/src/pages/dataset/testing/index.tsx

@@ -1,4 +1,5 @@
 import { useTestRetrieval } from '@/hooks/use-knowledge-request';
+import { t } from 'i18next';
 import { useState } from 'react';
 import { TopTitle } from '../dataset-title';
 import TestingForm from './testing-form';
@@ -23,8 +24,8 @@ export default function RetrievalTesting() {
     <div className="p-5">
       <section className="flex justify-between items-center">
         <TopTitle
-          title={'Retrieval testing'}
-          description={`Conduct a retrieval test to check if RAGFlow can recover the intended content for the LLM.`}
+          title={t('knowledgeDetails.retrievalTesting')}
+          description={t('knowledgeDetails.retrievalTestingDescription')}
         ></TopTitle>
         {/* <Button>Save as Preset</Button> */}
       </section>
@@ -33,7 +34,7 @@ export default function RetrievalTesting() {
           <div className="p-4 flex-1">
             <div className="flex justify-between pb-2.5">
               <span className="text-text-primary font-semibold text-2xl">
-                Test setting
+                {t('knowledgeDetails.testSetting')}
               </span>
               {/* <Button variant={'outline'} onClick={addCount}>
                 <Plus /> Add New Test

web/src/pages/dataset/testing/testing-result.tsx

@@ -6,6 +6,7 @@ import { RAGFlowPagination } from '@/components/ui/ragflow-pagination';
 import { useTranslate } from '@/hooks/common-hooks';
 import { useTestRetrieval } from '@/hooks/use-knowledge-request';
 import { ITestingChunk } from '@/interfaces/database/knowledge';
+import { t } from 'i18next';
 import camelCase from 'lodash/camelCase';
 import { useMemo } from 'react';
 
@@ -66,7 +67,7 @@ export function TestingResult({
     <div className="p-4 flex-1">
       <div className="flex justify-between pb-2.5">
         <span className="text-text-primary font-semibold text-2xl">
-          Test results
+          {t('knowledgeDetails.testResults')}
         </span>
         <FilterPopover
           filters={filters}

web/src/pages/datasets/dataset-card.tsx

@@ -1,11 +1,11 @@
 import { HomeCard } from '@/components/home-card';
 import { MoreButton } from '@/components/more-button';
+import { SharedBadge } from '@/components/shared-badge';
 import { Card, CardContent } from '@/components/ui/card';
 import { useNavigatePage } from '@/hooks/logic-hooks/navigate-hooks';
 import { IKnowledge } from '@/interfaces/database/knowledge';
 import { ChevronRight } from 'lucide-react';
 import { DatasetDropdown } from './dataset-dropdown';
-import { useDisplayOwnerName } from './use-display-owner';
 import { useRenameDataset } from './use-rename-dataset';
 
 export type DatasetCardProps = {
@@ -17,9 +17,6 @@ export function DatasetCard({
   showDatasetRenameModal,
 }: DatasetCardProps) {
   const { navigateToDataset } = useNavigatePage();
-  const displayOwnerName = useDisplayOwnerName();
-
-  const owner = displayOwnerName(dataset.tenant_id, dataset.nickname);
 
   return (
     <HomeCard
@@ -32,6 +29,7 @@ export function DatasetCard({
           <MoreButton></MoreButton>
         </DatasetDropdown>
       }
+      sharedBadge={<SharedBadge>{dataset.nickname}</SharedBadge>}
       onClick={navigateToDataset(dataset.id)}
     />
   );
@@ -41,7 +39,7 @@ export function SeeAllCard() {
   const { navigateToDatasetList } = useNavigatePage();
 
   return (
-    <Card className="w-40" onClick={navigateToDatasetList}>
+    <Card className="w-40 flex-none h-full" onClick={navigateToDatasetList}>
       <CardContent className="p-2.5 pt-1 w-full h-full flex items-center justify-center gap-1.5 text-text-secondary">
         See All <ChevronRight className="size-4" />
       </CardContent>

web/src/pages/datasets/dataset-creating-dialog.tsx

@@ -1,4 +1,4 @@
-import { Button } from '@/components/ui/button';
+import { ButtonLoading } from '@/components/ui/button';
 import {
   Dialog,
   DialogContent,
@@ -74,7 +74,11 @@ export function InputForm({ onOk }: IModalProps<any>) {
   );
 }
 
-export function DatasetCreatingDialog({ hideModal, onOk }: IModalProps<any>) {
+export function DatasetCreatingDialog({
+  hideModal,
+  onOk,
+  loading,
+}: IModalProps<any>) {
   const { t } = useTranslation();
 
   return (
@@ -85,9 +89,9 @@ export function DatasetCreatingDialog({ hideModal, onOk }: IModalProps<any>) {
         </DialogHeader>
         <InputForm onOk={onOk}></InputForm>
         <DialogFooter>
-          <Button type="submit" form={FormId}>
+          <ButtonLoading type="submit" form={FormId} loading={loading}>
             {t('common.save')}
-          </Button>
+          </ButtonLoading>
         </DialogFooter>
       </DialogContent>
     </Dialog>

web/src/pages/files/use-upload-file.ts

@@ -1,3 +1,4 @@
+import { UploadFormSchemaType } from '@/components/file-upload-dialog';
 import { useSetModalState } from '@/hooks/common-hooks';
 import { useUploadFile } from '@/hooks/use-file-request';
 import { useCallback } from 'react';
@@ -13,7 +14,7 @@ export const useHandleUploadFile = () => {
   const id = useGetFolderId();
 
   const onFileUploadOk = useCallback(
-    async (fileList: File[]): Promise<number | undefined> => {
+    async ({ fileList }: UploadFormSchemaType): Promise<number | undefined> => {
       if (fileList.length > 0) {
         const ret: number = await uploadFile({ fileList, parentId: id });
         if (ret === 0) {

web/src/pages/home/applications.tsx

@@ -51,7 +51,8 @@ export function Applications() {
           options={options}
           value={val}
           onChange={handleChange}
-          className="bg-transparent"
+          className="bg-bg-card border border-border-button rounded-full"
+          activeClassName="bg-text-primary border-none"
         ></Segmented>
       </div>
       <div className="flex flex-wrap gap-4">

web/src/pages/home/datasets.tsx

@@ -30,17 +30,21 @@ export function Datasets() {
             <CardSkeleton />
           </div>
         ) : (
-          <div className="flex gap-4 flex-1">
-            {kbs.slice(0, 6).map((dataset) => (
-              <DatasetCard
-                key={dataset.id}
-                dataset={dataset}
-                showDatasetRenameModal={showDatasetRenameModal}
-              ></DatasetCard>
-            ))}
+          <div className="grid gap-6 sm:grid-cols-1 md:grid-cols-2 lg:grid-cols-4 xl:grid-cols-6 2xl:grid-cols-8 max-h-[78vh] overflow-auto">
+            {kbs
+              ?.slice(0, 6)
+              .map((dataset) => (
+                <DatasetCard
+                  key={dataset.id}
+                  dataset={dataset}
+                  showDatasetRenameModal={showDatasetRenameModal}
+                ></DatasetCard>
+              ))}
+            <div className="min-h-24">
+              <SeeAllCard></SeeAllCard>
+            </div>
           </div>
         )}
-        <SeeAllCard></SeeAllCard>
       </div>
       {datasetRenameVisible && (
         <RenameDialog

web/src/pages/next-chats/chat/app-settings/chat-basic-settings.tsx

@@ -14,6 +14,7 @@ import {
 } from '@/components/ui/form';
 import { Input } from '@/components/ui/input';
 import { Textarea } from '@/components/ui/textarea';
+import { Select, SelectContent, SelectItem, SelectTrigger, SelectValue } from '@/components/ui/select';
 import { useTranslate } from '@/hooks/common-hooks';
 import { useFormContext } from 'react-hook-form';
 
@@ -21,6 +22,17 @@ export default function ChatBasicSetting() {
   const { t } = useTranslate('chat');
   const form = useFormContext();
 
+  const languageOptions = [
+    { value: 'English', label: 'English' },
+    { value: 'Chinese', label: 'Chinese' },
+    { value: 'Spanish', label: 'Spanish' },
+    { value: 'French', label: 'French' },
+    { value: 'German', label: 'German' },
+    { value: 'Japanese', label: 'Japanese' },
+    { value: 'Korean', label: 'Korean' },
+    { value: 'Vietnamese', label: 'Vietnamese' },
+  ];
+
   return (
     <div className="space-y-8">
       <FormField
@@ -35,7 +47,6 @@ export default function ChatBasicSetting() {
                   value={field.value}
                   onValueChange={field.onChange}
                   maxFileCount={1}
-                  maxSize={4 * 1024 * 1024}
                 />
               </FormControl>
               <FormMessage />
@@ -56,6 +67,30 @@ export default function ChatBasicSetting() {
           </FormItem>
         )}
       />
+      <FormField
+        control={form.control}
+        name="language"
+        render={({ field }) => (
+          <FormItem>
+            <FormLabel>{t('language')}</FormLabel>
+            <Select onValueChange={field.onChange} defaultValue={field.value}>
+              <FormControl>
+                <SelectTrigger>
+                  <SelectValue placeholder={t('common.languagePlaceholder')} />
+                </SelectTrigger>
+              </FormControl>
+              <SelectContent>
+                {languageOptions.map((option) => (
+                  <SelectItem key={option.value} value={option.value}>
+                    {option.label}
+                  </SelectItem>
+                ))}
+              </SelectContent>
+            </Select>
+            <FormMessage />
+          </FormItem>
+        )}
+      />
       <FormField
         control={form.control}
         name="description"

web/src/pages/next-chats/chat/app-settings/chat-settings.tsx

@@ -9,6 +9,7 @@ import {
   setLLMSettingEnabledValues,
 } from '@/utils/form';
 import { zodResolver } from '@hookform/resolvers/zod';
+import { omit } from 'lodash';
 import { X } from 'lucide-react';
 import { useEffect } from 'react';
 import { useForm } from 'react-hook-form';
@@ -35,13 +36,18 @@ export function ChatSettings({ switchSettingVisible }: ChatSettingsProps) {
     shouldUnregister: true,
     defaultValues: {
       name: '',
+      icon: [],
       language: 'English',
+      description: '',
+      kb_ids: [],
       prompt_config: {
         quote: true,
         keyword: false,
         tts: false,
         use_kg: false,
         refine_multiturn: true,
+        system: '',
+        parameters: [],
       },
       top_n: 8,
       vector_similarity_weight: 0.2,
@@ -64,7 +70,7 @@ export function ChatSettings({ switchSettingVisible }: ChatSettingsProps) {
         ? await transformFile2Base64(icon[0])
         : '';
     setDialog({
-      ...data,
+      ...omit(data, 'operator_permission'),
       ...nextValues,
       icon: avatar,
       dialog_id: id,
@@ -89,25 +95,28 @@ export function ChatSettings({ switchSettingVisible }: ChatSettingsProps) {
   }, [data, form]);
 
   return (
-    <section className="p-5  w-[440px] border-l">
+    <section className="p-5  w-[440px] border-l flex flex-col">
       <div className="flex justify-between items-center text-base pb-2">
         {t('chat.chatSetting')}
         <X className="size-4 cursor-pointer" onClick={switchSettingVisible} />
       </div>
       <Form {...form}>
-        <form onSubmit={form.handleSubmit(onSubmit, onInvalid)}>
-          <section className="space-y-6 overflow-auto max-h-[82vh] pr-4">
+        <form
+          onSubmit={form.handleSubmit(onSubmit, onInvalid)}
+          className="flex-1 flex flex-col min-h-0"
+        >
+          <section className="space-y-6 overflow-auto flex-1 pr-4 min-h-0">
             <ChatBasicSetting></ChatBasicSetting>
             <Separator />
             <ChatPromptEngine></ChatPromptEngine>
             <Separator />
             <ChatModelSettings></ChatModelSettings>
           </section>
-          <div className="space-x-5 text-right">
+          <div className="space-x-5 text-right pt-4">
             <Button variant={'outline'} onClick={switchSettingVisible}>
               {t('chat.cancel')}
             </Button>
-            <ButtonLoading className=" my-4" type="submit" loading={loading}>
+            <ButtonLoading type="submit" loading={loading}>
               {t('common.save')}
             </ButtonLoading>
           </div>

web/src/pages/next-chats/chat/app-settings/use-chat-setting-schema.tsx

@@ -34,11 +34,11 @@ export function useChatSettingSchema() {
     name: z.string().min(1, { message: t('assistantNameMessage') }),
     icon: z.array(z.instanceof(File)),
     language: z.string().min(1, {
-      message: 'Username must be at least 2 characters.',
+      message: t('languageMessage'),
     }),
-    description: z.string(),
+    description: z.string().optional(),
     kb_ids: z.array(z.string()).min(0, {
-      message: 'Username must be at least 1 characters.',
+      message: t('knowledgeBasesMessage'),
     }),
     prompt_config: promptConfigSchema,
     ...rerankFormSchema,

web/src/pages/next-chats/chat/chat-box/multiple-chat-box.tsx

@@ -2,6 +2,8 @@ import { LargeModelFormFieldWithoutFilter } from '@/components/large-model-form-
 import { LlmSettingSchema } from '@/components/llm-setting-items/next';
 import { NextMessageInput } from '@/components/message-input/next';
 import MessageItem from '@/components/message-item';
+import PdfDrawer from '@/components/pdf-drawer';
+import { useClickDrawer } from '@/components/pdf-drawer/hooks';
 import { Button } from '@/components/ui/button';
 import { Card, CardContent, CardHeader, CardTitle } from '@/components/ui/card';
 import { Form } from '@/components/ui/form';
@@ -54,7 +56,8 @@ type ChatCardProps = {
 } & Pick<
   MultipleChatBoxProps,
   'controller' | 'removeChatBox' | 'addChatBox' | 'chatBoxIds'
->;
+> &
+  Pick<ReturnType<typeof useClickDrawer>, 'clickDocumentButton'>;
 
 const ChatCard = forwardRef(function ChatCard(
   {
@@ -66,6 +69,7 @@ const ChatCard = forwardRef(function ChatCard(
     chatBoxIds,
     derivedMessages,
     sendLoading,
+    clickDocumentButton,
   }: ChatCardProps,
   ref,
 ) {
@@ -178,6 +182,7 @@ const ChatCard = forwardRef(function ChatCard(
                   removeMessageById={removeMessageById}
                   regenerateMessage={regenerateMessage}
                   sendLoading={sendLoading}
+                  clickDocumentButton={clickDocumentButton}
                 ></MessageItem>
               );
             })}
@@ -211,6 +216,8 @@ export function MultipleChatBox({
   const { conversationId } = useGetChatSearchParams();
   const disabled = useGetSendButtonDisabled();
   const sendDisabled = useSendButtonDisabled(value);
+  const { visible, hideModal, documentId, selectedChunk, clickDocumentButton } =
+    useClickDrawer();
 
   return (
     <section className="h-full flex flex-col px-5">
@@ -227,6 +234,7 @@ export function MultipleChatBox({
             derivedMessages={messageRecord[id]}
             ref={setFormRef(id)}
             sendLoading={sendLoading}
+            clickDocumentButton={clickDocumentButton}
           ></ChatCard>
         ))}
       </div>
@@ -246,6 +254,14 @@ export function MultipleChatBox({
           onUpload={handleUploadFile}
         />
       </div>
+      {visible && (
+        <PdfDrawer
+          visible={visible}
+          hideModal={hideModal}
+          documentId={documentId}
+          chunk={selectedChunk}
+        ></PdfDrawer>
+      )}
     </section>
   );
 }

web/src/pages/next-chats/chat/chat-box/single-chat-box.tsx

@@ -1,5 +1,7 @@
 import { NextMessageInput } from '@/components/message-input/next';
 import MessageItem from '@/components/message-item';
+import PdfDrawer from '@/components/pdf-drawer';
+import { useClickDrawer } from '@/components/pdf-drawer/hooks';
 import { MessageType } from '@/constants/chat';
 import {
   useFetchConversation,
@@ -43,6 +45,8 @@ export function SingleChatBox({ controller }: IProps) {
   const { data: conversation } = useFetchConversation();
   const disabled = useGetSendButtonDisabled();
   const sendDisabled = useSendButtonDisabled(value);
+  const { visible, hideModal, documentId, selectedChunk, clickDocumentButton } =
+    useClickDrawer();
 
   return (
     <section className="flex flex-col p-5 h-full">
@@ -68,7 +72,7 @@ export function SingleChatBox({ controller }: IProps) {
                   },
                   message,
                 )}
-                // clickDocumentButton={clickDocumentButton}
+                clickDocumentButton={clickDocumentButton}
                 index={i}
                 removeMessageById={removeMessageById}
                 regenerateMessage={regenerateMessage}
@@ -94,6 +98,14 @@ export function SingleChatBox({ controller }: IProps) {
         onUpload={handleUploadFile}
         isUploading={isUploading}
       />
+      {visible && (
+        <PdfDrawer
+          visible={visible}
+          hideModal={hideModal}
+          documentId={documentId}
+          chunk={selectedChunk}
+        ></PdfDrawer>
+      )}
     </section>
   );
 }

web/src/pages/next-chats/chat/index.tsx

@@ -109,13 +109,12 @@ export default function Chat() {
 
         <Card className="flex-1 min-w-0 bg-transparent border h-full">
           <CardContent className="flex p-0 h-full">
-            <Card className="flex flex-col flex-1 bg-transparent">
+            <Card className="flex flex-col flex-1 bg-transparent min-w-0">
               <CardHeader
                 className={cn('p-5', { 'border-b': hasSingleChatBox })}
               >
                 <CardTitle className="flex justify-between items-center text-base">
-                  <div>{conversation.name}</div>
-
+                  <div className="truncate">{conversation.name}</div>
                   <Button
                     variant={'ghost'}
                     onClick={switchDebugMode}

web/src/pages/next-chats/chat/sessions.tsx

@@ -90,8 +90,8 @@ export function Sessions({
               'bg-bg-card': conversationId === x.id,
             })}
           >
-            <CardContent className="px-3 py-2 flex justify-between items-center group">
-              {x.name}
+            <CardContent className="px-3 py-2 flex justify-between items-center group gap-1">
+              <div className="truncate">{x.name}</div>
               <ConversationDropdown conversation={x}>
                 <MoreButton></MoreButton>
               </ConversationDropdown>

web/src/pages/next-chats/hooks/use-rename-chat.ts

@@ -1,5 +1,6 @@
 import { useSetModalState } from '@/hooks/common-hooks';
 import { useSetDialog } from '@/hooks/use-chat-request';
+import { useFetchTenantInfo } from '@/hooks/use-user-setting-request';
 import { IDialog } from '@/interfaces/database/chat';
 import { isEmpty, omit } from 'lodash';
 import { useCallback, useMemo, useState } from 'react';
@@ -14,6 +15,7 @@ export const useRenameChat = () => {
   } = useSetModalState();
   const { setDialog, loading } = useSetDialog();
   const { t } = useTranslation();
+  const tenantInfo = useFetchTenantInfo();
 
   const InitialData = useMemo(
     () => ({
@@ -32,13 +34,13 @@ export const useRenameChat = () => {
         reasoning: false,
         parameters: [{ key: 'knowledge', optional: false }],
       },
-      llm_id: '',
+      llm_id: tenantInfo.data.llm_id,
       llm_setting: {},
       similarity_threshold: 0.2,
       vector_similarity_weight: 0.30000000000000004,
       top_n: 8,
     }),
-    [t],
+    [t, tenantInfo.data.llm_id],
   );
 
   const onChatRenameOk = useCallback(
@@ -46,7 +48,10 @@ export const useRenameChat = () => {
       const nextChat = {
         ...(isEmpty(chat)
           ? InitialData
-          : { ...omit(chat, 'nickname', 'tenant_avatar'), dialog_id: chat.id }),
+          : {
+              ...omit(chat, 'nickname', 'tenant_avatar', 'operator_permission'),
+              dialog_id: chat.id,
+            }),
         name,
       };
       const ret = await setDialog(nextChat);

web/src/pages/next-chats/hooks/use-send-multiple-message.ts

@@ -1,3 +1,4 @@
+import showMessage from '@/components/ui/message';
 import { MessageType } from '@/constants/chat';
 import {
   useHandleMessageInputChange,
@@ -159,7 +160,7 @@ export function useSendMultipleChatMessage(
       if (res && (res?.response.status !== 200 || res?.data?.code !== 0)) {
         // cancel loading
         setValue(message.content);
-        console.info('removeLatestMessage111');
+        showMessage.error(res.data.message);
         removeLatestMessage(chatBoxId);
       }
     },

web/src/pages/next-search/index.tsx

@@ -128,7 +128,7 @@ export default function SearchPage() {
       </div>
       <div className="absolute right-5 top-4 ">
         <Button
-          className="bg-text-primary  text-bg-base border-b-[#00BEB4] border-b-2"
+          className="bg-text-primary  text-bg-base border-b-accent-primary border-b-2"
           onClick={() => {
             handleOperate().then((res) => {
               console.log(res, 'res');

web/src/pages/next-search/search-home.tsx

@@ -27,7 +27,7 @@ export default function SearchPage({
       <div className="relative z-10 px-8 pt-8 flex  text-transparent flex-col justify-center items-center w-[780px]">
         <h1
           className={cn(
-            'text-4xl font-bold bg-gradient-to-r from-sky-600 from-30% via-sky-500 via-60% to-emerald-500 bg-clip-text',
+            'text-4xl font-bold bg-gradient-to-l from-[#40EBE3] to-[#4A51FF] bg-clip-text',
           )}
         >
           RAGFlow

web/src/pages/next-search/search-setting-aisummery-config.tsx

@@ -21,7 +21,7 @@ import {
 } from '@/constants/knowledge';
 import { useTranslate } from '@/hooks/common-hooks';
 import { useComposeLlmOptionsByModelTypes } from '@/hooks/llm-hooks';
-import { camelCase } from 'lodash';
+import { camelCase, isEqual } from 'lodash';
 import { useCallback } from 'react';
 import { useFormContext } from 'react-hook-form';
 import { z } from 'zod';
@@ -61,20 +61,15 @@ export function LlmSettingFieldItems({
 
   const handleChange = useCallback(
     (parameter: string) => {
-      const currentValues = { ...form.getValues() };
-      console.log('currentValues', currentValues);
       const values =
         settledModelVariableMap[
           parameter as keyof typeof settledModelVariableMap
         ];
       const enabledKeys = Object.keys(LlmSettingEnableSchema);
 
-      // const nextValues = { ...currentValues, ...values };
-
       for (const key in values) {
         if (Object.prototype.hasOwnProperty.call(values, key)) {
-          const element = values[key];
-
+          const element = values[key as keyof typeof values];
           form.setValue(`${prefix}.${key}`, element);
         }
       }
@@ -90,7 +85,11 @@ export function LlmSettingFieldItems({
   const parameterOptions = Object.values(ModelVariableType).map((x) => ({
     label: t(camelCase(x)),
     value: x,
-  }));
+  })) as unknown as { label: string; value: ModelVariableType | 'Custom' }[];
+  parameterOptions.push({
+    label: t(camelCase('Custom')),
+    value: 'Custom',
+  });
 
   const getFieldWithPrefix = useCallback(
     (name: string) => {
@@ -99,6 +98,35 @@ export function LlmSettingFieldItems({
     [prefix],
   );
 
+  const checkParameterIsEquel = () => {
+    const [
+      parameter,
+      topPValue,
+      frequencyPenaltyValue,
+      temperatureValue,
+      presencePenaltyValue,
+    ] = form.getValues([
+      getFieldWithPrefix('parameter'),
+      getFieldWithPrefix('temperature'),
+      getFieldWithPrefix('top_p'),
+      getFieldWithPrefix('frequency_penalty'),
+      getFieldWithPrefix('presence_penalty'),
+    ]);
+    if (parameter && parameter !== 'Custom') {
+      const parameterValue =
+        settledModelVariableMap[parameter as keyof typeof ModelVariableType];
+      const parameterRealValue = {
+        top_p: topPValue,
+        temperature: temperatureValue,
+        frequency_penalty: frequencyPenaltyValue,
+        presence_penalty: presencePenaltyValue,
+      };
+      if (!isEqual(parameterValue, parameterRealValue)) {
+        form.setValue(getFieldWithPrefix('parameter'), 'Custom');
+      }
+    }
+  };
+
   return (
     <div className="space-y-5">
       <FormField
@@ -113,7 +141,7 @@ export function LlmSettingFieldItems({
             <FormControl>
               <SelectWithSearch
                 options={options || modelOptions}
-                triggerClassName="bg-bg-card"
+                triggerClassName="!bg-bg-input"
                 {...field}
               ></SelectWithSearch>
             </FormControl>
@@ -159,6 +187,9 @@ export function LlmSettingFieldItems({
         label="temperature"
         max={1}
         step={0.01}
+        onChange={() => {
+          checkParameterIsEquel();
+        }}
       ></SliderInputSwitchFormField>
       <SliderInputSwitchFormField
         name={getFieldWithPrefix('top_p')}
@@ -166,6 +197,9 @@ export function LlmSettingFieldItems({
         label="topP"
         max={1}
         step={0.01}
+        onChange={() => {
+          checkParameterIsEquel();
+        }}
       ></SliderInputSwitchFormField>
       <SliderInputSwitchFormField
         name={getFieldWithPrefix('presence_penalty')}
@@ -173,6 +207,9 @@ export function LlmSettingFieldItems({
         label="presencePenalty"
         max={1}
         step={0.01}
+        onChange={() => {
+          checkParameterIsEquel();
+        }}
       ></SliderInputSwitchFormField>
       <SliderInputSwitchFormField
         name={getFieldWithPrefix('frequency_penalty')}
@@ -180,6 +217,9 @@ export function LlmSettingFieldItems({
         label="frequencyPenalty"
         max={1}
         step={0.01}
+        onChange={() => {
+          checkParameterIsEquel();
+        }}
       ></SliderInputSwitchFormField>
       {/* <SliderInputSwitchFormField
         name={getFieldWithPrefix('max_tokens')}

web/src/pages/next-search/search-setting.tsx

@@ -114,8 +114,8 @@ const SearchSetting: React.FC<SearchSettingProps> = ({
   const [avatarBase64Str, setAvatarBase64Str] = useState(''); // Avatar Image base64
   const [datasetList, setDatasetList] = useState<MultiSelectOptionType[]>([]);
   const [datasetSelectEmbdId, setDatasetSelectEmbdId] = useState('');
-  const descriptionDefaultValue = 'You are an intelligent assistant.';
   const { t } = useTranslation();
+  const descriptionDefaultValue = t('search.descriptionValue');
   const resetForm = useCallback(() => {
     formMethods.reset({
       search_id: data?.id,
@@ -136,9 +136,9 @@ const SearchSetting: React.FC<SearchSettingProps> = ({
         use_rerank: search_config?.rerank_id ? true : false,
         top_k: search_config?.top_k || 1024,
         summary: search_config?.summary || false,
-        chat_id: '',
+        chat_id: search_config?.chat_id || '',
         llm_setting: {
-          llm_id: llm_setting?.llm_id || '',
+          llm_id: search_config?.chat_id || '',
           parameter: llm_setting?.parameter,
           temperature: llm_setting?.temperature,
           top_p: llm_setting?.top_p,
@@ -159,7 +159,7 @@ const SearchSetting: React.FC<SearchSettingProps> = ({
         meta_data_filter: search_config?.meta_data_filter,
       },
     });
-  }, [data, search_config, llm_setting, formMethods]);
+  }, [data, search_config, llm_setting, formMethods, descriptionDefaultValue]);
 
   useEffect(() => {
     resetForm();
@@ -255,7 +255,7 @@ const SearchSetting: React.FC<SearchSettingProps> = ({
         ...other_config
       } = search_config;
       const llmSetting = {
-        llm_id: llm_setting.llm_id,
+        // llm_id: llm_setting.llm_id,
         parameter: llm_setting.parameter,
         temperature: llm_setting.temperature,
         top_p: llm_setting.top_p,
@@ -263,22 +263,11 @@ const SearchSetting: React.FC<SearchSettingProps> = ({
         presence_penalty: llm_setting.presence_penalty,
       } as IllmSettingProps;
 
-      if (!llm_setting.frequencyPenaltyEnabled) {
-        delete llmSetting.frequency_penalty;
-      }
-      if (!llm_setting.presencePenaltyEnabled) {
-        delete llmSetting.presence_penalty;
-      }
-      if (!llm_setting.temperatureEnabled) {
-        delete llmSetting.temperature;
-      }
-      if (!llm_setting.topPEnabled) {
-        delete llmSetting.top_p;
-      }
       await updateSearch({
         ...other_formdata,
         search_config: {
           ...other_config,
+          chat_id: llm_setting.llm_id,
           vector_similarity_weight: 1 - vector_similarity_weight,
           rerank_id: use_rerank ? rerank_id : '',
           llm_setting: { ...llmSetting },
@@ -415,7 +404,7 @@ const SearchSetting: React.FC<SearchSettingProps> = ({
                   <FormLabel>{t('search.description')}</FormLabel>
                   <FormControl>
                     <Textarea
-                      placeholder="You are an intelligent assistant."
+                      placeholder={descriptionDefaultValue}
                       {...field}
                       onFocus={() => {
                         if (field.value === descriptionDefaultValue) {
@@ -444,7 +433,7 @@ const SearchSetting: React.FC<SearchSettingProps> = ({
                     <span className="text-destructive mr-1"> *</span>
                     {t('search.datasets')}
                   </FormLabel>
-                  <FormControl>
+                  <FormControl className="bg-bg-input">
                     <MultiSelect
                       options={datasetList}
                       onValueChange={(value) => {
@@ -452,7 +441,6 @@ const SearchSetting: React.FC<SearchSettingProps> = ({
                       }}
                       showSelectAll={false}
                       placeholder={t('chat.knowledgeBasesMessage')}
-                      variant="inverted"
                       maxCount={10}
                       defaultValue={field.value}
                       {...field}
@@ -568,6 +556,7 @@ const SearchSetting: React.FC<SearchSettingProps> = ({
                         <RAGFlowSelect
                           {...field}
                           options={rerankModelOptions}
+                          triggerClassName={'bg-bg-input'}
                           // disabled={disabled}
                           placeholder={'model'}
                         />

web/src/pages/next-search/search-view.tsx

@@ -83,7 +83,7 @@ export default function SearchingView({
       >
         <h1
           className={cn(
-            'text-4xl font-bold bg-gradient-to-r from-sky-600 from-30% via-sky-500 via-60% to-emerald-500 bg-clip-text cursor-pointer',
+            'text-4xl font-bold bg-gradient-to-l from-[#40EBE3] to-[#4A51FF] bg-clip-text cursor-pointer',
           )}
           onClick={() => {
             setIsSearching?.(false);