temp

scripts/milvus/standalone_embed.sh

@@ -0,0 +1,143 @@
+#!/usr/bin/env bash
+
+# Licensed to the LF AI & Data foundation under one
+# or more contributor license agreements. See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership. The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License. You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+run_embed() {
+    cat << EOF > embedEtcd.yaml
+listen-client-urls: http://0.0.0.0:2379
+advertise-client-urls: http://0.0.0.0:2379
+quota-backend-bytes: 4294967296
+auto-compaction-mode: revision
+auto-compaction-retention: '1000'
+EOF
+
+    cat << EOF > user.yaml
+# Extra config to override default milvus.yaml
+EOF
+
+    sudo docker run -d \
+        --name milvus-standalone \
+        --security-opt seccomp:unconfined \
+        -e ETCD_USE_EMBED=true \
+        -e ETCD_DATA_DIR=/var/lib/milvus/etcd \
+        -e ETCD_CONFIG_PATH=/milvus/configs/embedEtcd.yaml \
+        -e COMMON_STORAGETYPE=local \
+        -v $(pwd)/volumes/milvus:/var/lib/milvus \
+        -v $(pwd)/embedEtcd.yaml:/milvus/configs/embedEtcd.yaml \
+        -v $(pwd)/user.yaml:/milvus/configs/user.yaml \
+        -p 19530:19530 \
+        -p 9091:9091 \
+        -p 2379:2379 \
+        --health-cmd="curl -f http://localhost:9091/healthz" \
+        --health-interval=30s \
+        --health-start-period=90s \
+        --health-timeout=20s \
+        --health-retries=3 \
+        milvusdb/milvus:v2.4.5 \
+        milvus run standalone  1> /dev/null
+}
+
+wait_for_milvus_running() {
+    echo "Wait for Milvus Starting..."
+    while true
+    do
+        res=`sudo docker ps|grep milvus-standalone|grep healthy|wc -l`
+        if [ $res -eq 1 ]
+        then
+            echo "Start successfully."
+            echo "To change the default Milvus configuration, add your settings to the user.yaml file and then restart the service."
+            break
+        fi
+        sleep 1
+    done
+}
+
+start() {
+    res=`sudo docker ps|grep milvus-standalone|grep healthy|wc -l`
+    if [ $res -eq 1 ]
+    then
+        echo "Milvus is running."
+        exit 0
+    fi
+
+    res=`sudo docker ps -a|grep milvus-standalone|wc -l`
+    if [ $res -eq 1 ]
+    then
+        sudo docker start milvus-standalone 1> /dev/null
+    else
+        run_embed
+    fi
+
+    if [ $? -ne 0 ]
+    then
+        echo "Start failed."
+        exit 1
+    fi
+
+    wait_for_milvus_running
+}
+
+stop() {
+    sudo docker stop milvus-standalone 1> /dev/null
+
+    if [ $? -ne 0 ]
+    then
+        echo "Stop failed."
+        exit 1
+    fi
+    echo "Stop successfully."
+
+}
+
+delete() {
+    res=`sudo docker ps|grep milvus-standalone|wc -l`
+    if [ $res -eq 1 ]
+    then
+        echo "Please stop Milvus service before delete."
+        exit 1
+    fi
+    sudo docker rm milvus-standalone 1> /dev/null
+    if [ $? -ne 0 ]
+    then
+        echo "Delete failed."
+        exit 1
+    fi
+    sudo rm -rf $(pwd)/volumes
+    sudo rm -rf $(pwd)/embedEtcd.yaml
+    sudo rm -rf $(pwd)/user.yaml
+    echo "Delete successfully."
+}
+
+
+case $1 in
+    restart)
+        stop
+        start
+        ;;
+    start)
+        start
+        ;;
+    stop)
+        stop
+        ;;
+    delete)
+        delete
+        ;;
+    *)
+        echo "please use bash standalone_embed.sh restart|start|stop|delete"
+        ;;
+esac

src/core/database.py

@@ -64,6 +64,7 @@ class DataBaseManager:
 
     def get_databases(self):
         self._update_database()
+        assert self.config.enable_knowledge_base, "知识库未启用"
         knowledge_base_collections = self.knowledge_base.get_collection_names()
         if len(self.data["databases"]) != len(knowledge_base_collections):
             logger.warning(f"Database number not match, {knowledge_base_collections}")

src/main.py

@@ -0,0 +1,32 @@
+import uvicorn
+from dotenv import load_dotenv
+from fastapi import FastAPI
+from fastapi.middleware.cors import CORSMiddleware
+from src.routers import router
+from src.utils.logging_config import setup_logger
+
+load_dotenv()
+
+import os
+
+os.environ["ZHIPUAI_API_KEY"] = "270ea71e9560c0ff406acbcdd48bfd97.e3XOMdWKuZb7Q1Sk"
+
+app = FastAPI()
+app.include_router(router)
+
+# CORS 设置
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+
+logger = setup_logger("server:main")
+
+
+if __name__ == "__main__":
+    uvicorn.run(app, host="0.0.0.0", port=5000)
+

src/models/chat_model.py

@@ -58,7 +58,7 @@ class DeepSeek(OpenAIBase):
 class Zhipu(OpenAIBase):
     def __init__(self, model_name=None):
         model_name = model_name or "glm-4-flash"
-        api_key = os.getenv("ZHIPUAI_API_KEY")
+        api_key = os.getenv("ZHIPUAI_API_KEY", "270ea71e9560c0ff406acbcdd48bfd97.e3XOMdWKuZb7Q1Sk")
         base_url = "https://open.bigmodel.cn/api/paas/v4/"
         super().__init__(api_key=api_key, base_url=base_url, model_name=model_name)
 

src/routers/__init__.py

@@ -0,0 +1,11 @@
+from fastapi import APIRouter
+from src.routers.chat_router import chat
+from src.routers.data_router import data
+from src.routers.base_router import base
+from src.routers.tool_router import tool
+
+router = APIRouter()
+router.include_router(base)
+router.include_router(chat)
+router.include_router(data)
+router.include_router(tool)

src/routers/base_router.py

@@ -0,0 +1,45 @@
+from fastapi import APIRouter
+
+base = APIRouter()
+
+from fastapi import FastAPI, HTTPException
+from fastapi.responses import JSONResponse
+from fastapi import Request
+from src.core import HistoryManager
+from src.utils.logging_config import setup_logger
+from src.core.startup import startup
+
+logger = setup_logger("server-base")
+
+@base.get("/")
+async def route_index():
+    return {"message": "You Got It!"}
+
+@base.get("/config")
+async def get_config():
+    return startup.config
+
+@base.post("/config")
+async def update_config(request: Request):
+    request_data = await request.json()
+    startup.config.update(request_data)
+    startup.config.save()
+    return startup.config
+
+@base.post("/restart")
+async def restart():
+    startup.restart()
+    return {"message": "Restarted!"}
+
+@base.get("/log")
+async def get_log():
+    from src.utils.logging_config import LOG_FILE
+    from collections import deque
+
+    with open(LOG_FILE, 'r') as f:
+        last_lines = deque(f, maxlen=1000)
+
+    log = ''.join(last_lines)
+    return {"log": log}
+
+

src/routers/chat_router.py

@@ -0,0 +1,55 @@
+from fastapi import APIRouter, HTTPException, Request
+from fastapi.responses import StreamingResponse
+import json
+from src.core import HistoryManager
+from src.core.startup import startup
+from src.utils.logging_config import setup_logger
+
+chat = APIRouter(prefix="/chat")
+logger = setup_logger("server-chat")
+
+@chat.get("/")
+async def chat_get():
+    return "Chat Get!"
+
+@chat.post("/")
+async def chat_post(request: Request):
+    request_data = await request.json()
+    query = request_data['query']
+    meta = request_data.get('meta')
+    history_manager = HistoryManager(request_data['history'])
+
+    new_query, refs = startup.retriever(query, history_manager.messages, meta)
+
+    messages = history_manager.get_history_with_msg(new_query, max_rounds=meta.get('history_round'))
+    history_manager.add_user(query)
+    logger.debug(f"Web history: {history_manager.messages}")
+
+    async def generate_response():
+        content = ""
+        for delta in startup.model.predict(messages, stream=True):
+            if not delta.content:
+                continue
+
+            if hasattr(delta, 'is_full') and delta.is_full:
+                content = delta.content
+            else:
+                content += delta.content
+
+            response_chunk = json.dumps({
+                "history": history_manager.update_ai(content),
+                "response": content,
+                "refs": refs  # TODO: 优化 refs，不需要每次都返回
+            }, ensure_ascii=False).encode('utf8') + b'\n'
+            yield response_chunk
+
+    return StreamingResponse(generate_response(), media_type='application/json')
+
+@chat.post("/call")
+async def call(request: Request):
+    request_data = await request.json()
+    query = request_data['query']
+    response = startup.model.predict(query)
+    logger.debug({"query": query, "response": response.content})
+
+    return {"response": response.content}

src/routers/data_router.py

@@ -0,0 +1,120 @@
+import os
+from typing import List, Optional
+from fastapi import APIRouter, File, UploadFile, HTTPException, Depends, Body
+from pydantic import BaseModel
+
+from src.utils import setup_logger, hashstr
+from src.core.startup import startup
+
+data = APIRouter(prefix="/data")
+
+logger = setup_logger("server-database")
+
+@data.get("/")
+async def get_databases():
+    try:
+        database = startup.dbm.get_databases()
+    except Exception as e:
+        return {"message": f"获取数据库列表失败 {e}", "databases": []}
+    return database
+
+@data.post("/")
+async def create_database(
+    database_name: str = Body(...),
+    description: str = Body(...),
+    db_type: str = Body(...),
+    dimension: int = Body(None)
+):
+    logger.debug(f"Create database {database_name}")
+    database_info = startup.dbm.create_database(
+        database_name,
+        description,
+        db_type,
+        dimension=dimension
+    )
+    return database_info
+
+@data.delete("/")
+async def delete_database(db_id: str = Body(...)):
+    logger.debug(f"Delete database {db_id}")
+    startup.dbm.delete_database(db_id)
+    return {"message": "删除成功"}
+
+@data.post("/query-test")
+async def query_test(query: str = Body(...), meta: dict = Body(...)):
+    logger.debug(f"Query test in {meta}: {query}")
+    result = startup.retriever.query_knowledgebase(query, history=None, refs={"meta": meta})
+    return result
+
+@data.post("/add-by-file")
+async def create_document_by_file(db_id: str = Body(...), files: List[str] = Body(...)):
+    logger.debug(f"Add document in {db_id} by file: {files}")
+    msg = startup.dbm.add_files(db_id, files)
+    return msg
+
+@data.get("/database-info")
+async def get_database_info(db_id: str):
+    logger.debug(f"Get database {db_id} info")
+    database = startup.dbm.get_database_info(db_id)
+    if database is None:
+        raise HTTPException(status_code=404, detail="Database not found")
+    return database
+
+@data.delete("/document")
+async def delete_document(db_id: str = Body(...), file_id: str = Body(...)):
+    logger.debug(f"DELETE document {file_id} info in {db_id}")
+    startup.dbm.delete_file(db_id, file_id)
+    return {"message": "删除成功"}
+
+@data.get("/document")
+async def get_document_info(db_id: str, file_id: str):
+    logger.debug(f"GET document {file_id} info in {db_id}")
+    info = startup.dbm.get_file_info(db_id, file_id)
+    return info
+
+@data.post("/upload")
+async def upload_file(file: UploadFile = File(...)):
+    if not file.filename:
+        raise HTTPException(status_code=400, detail="No selected file")
+
+    upload_dir = os.path.join(startup.config.save_dir, "data/uploads")
+    os.makedirs(upload_dir, exist_ok=True)
+    filename = f"{hashstr(file.filename, 4, with_salt=True)}_{file.filename}".lower()
+    file_path = os.path.join(upload_dir, filename)
+
+    with open(file_path, "wb") as buffer:
+        buffer.write(await file.read())
+
+    return {"message": "File successfully uploaded", "file_path": file_path}
+
+@data.get("/graph")
+async def get_graph_info():
+    graph_info = startup.dbm.get_graph()
+    return graph_info
+
+@data.get("/graph/node")
+async def get_graph_node(entity_name: str):
+    logger.debug(f"Get graph node {entity_name}")
+    result = startup.dbm.graph_base.query_node(entity_name=entity_name)
+    return {"result": startup.retriever.format_query_results(result), "message": "success"}
+
+@data.get("/graph/nodes")
+async def get_graph_nodes(kgdb_name: str, num: int):
+    if not startup.config.enable_knowledge_graph:
+        raise HTTPException(status_code=400, detail="Knowledge graph is not enabled")
+
+    logger.debug(f"Get graph nodes in {kgdb_name} with {num} nodes")
+    result = startup.dbm.graph_base.get_sample_nodes(kgdb_name, num)
+    return {"result": startup.retriever.format_general_results(result), "message": "success"}
+
+@data.post("/graph/add")
+async def add_graph_entity(kgdb_name: str = Body(...), file_path: str = Body(...)):
+    if not startup.config.enable_knowledge_graph:
+        raise HTTPException(status_code=400, detail="Knowledge graph is not enabled")
+
+    if not file_path.endswith('.jsonl'):
+        raise HTTPException(status_code=400, detail="file_path must be a jsonl file")
+
+    startup.dbm.graph_base.jsonl_file_add_entity(file_path, kgdb_name)
+    return {"message": "Entity successfully added"}
+

src/routers/tool_router.py

@@ -0,0 +1,50 @@
+import os
+from fastapi import APIRouter, Body
+from pydantic import BaseModel
+from typing import List, Dict, Any, Optional
+
+from src.utils import setup_logger
+
+tool = APIRouter(prefix="/tool")
+
+logger = setup_logger("server-tools")
+
+class Tool(BaseModel):
+    name: str
+    title: str
+    description: str
+    url: str
+    method: str
+
+@tool.get("/", response_model=List[Tool])
+async def route_index():
+    tools = [
+        Tool(
+            name="text-chunking",
+            title="文本分块",
+            description="将文本分块以更好地理解。可以输入文本或者上传文件。",
+            url="/tools/text-chunking",
+            method="POST",
+        ),
+        Tool(
+            name="pdf2txt",
+            title="PDF转文本",
+            description="将PDF文件转换为文本文件。",
+            url="/tools/pdf2txt",
+            method="POST",
+        )
+    ]
+
+    return tools
+
+@tool.post("/text-chunking")
+async def text_chunking(text: str = Body(...), params: Dict[str, Any] = Body(...)):
+    from src.core.indexing import chunk
+    nodes = chunk(text, params=params)
+    return {"nodes": [node.to_dict() for node in nodes]}
+
+@tool.post("/pdf2txt")
+async def handle_pdf2txt(file: str = Body(...)):
+    from src.plugins import pdf2txt
+    text = pdf2txt(file, return_text=True)
+    return {"text": text}

web/src/components/ChatComponent.vue

@@ -351,7 +351,7 @@ const updateStatus = (id, status) => {
 
 const simpleCall = (message) => {
   return new Promise((resolve, reject) => {
-    fetch('/api/call', {
+    fetch('/api/chat/call', {
       method: 'POST',
       body: JSON.stringify({ query: message, }),
       headers: { 'Content-Type': 'application/json' }
@@ -363,7 +363,7 @@ const simpleCall = (message) => {
 }
 
 const loadDatabases = () => {
-  fetch('/api/database/', { method: "GET", })
+  fetch('/api/data/', { method: "GET", })
     .then(response => response.json())
     .then(data => {
       console.log(data)
@@ -371,63 +371,74 @@ const loadDatabases = () => {
     })
 }
 
-const sendMessage = () => {
-  const user_input = conv.value.inputText.trim()
-  if (user_input) {
-    isStreaming.value = true
-    appendUserMessage(user_input)
-    appendAiMessage("", null)
-    const cur_res_id = conv.value.messages[conv.value.messages.length - 1].id
-    conv.value.inputText = ''
-    meta.db_name = opts.databases[meta.selectedKB]?.metaname
-    fetch('/api/chat', {
-      method: 'POST',
-      body: JSON.stringify({
-        query: user_input,
-        history: conv.value.history,
-        meta: meta
-      }),
-      headers: {
-        'Content-Type': 'application/json'
-      }
-    }).then((response) => {const reader = response.body.getReader()
-      const decoder = new TextDecoder()
-      let buffer = ''
-      // 逐步读取响应文本
-      const readChunk = () => {
-        return reader.read().then(({ done, value }) => {
-          if (done) {
-            console.log(conv.value)
-            console.log('Finished')
-            updateStatus(cur_res_id, "finished")
-            isStreaming.value = false
-            if (conv.value.messages.length === 2) { renameTitle() }
-            return
-          }
+// 新函数用于处理 fetch 请求
+const fetchChatResponse = (user_input, cur_res_id) => {
+  fetch('/api/chat', {
+    method: 'POST',
+    body: JSON.stringify({
+      query: user_input,
+      history: conv.value.history,
+      meta: meta
+    }),
+    headers: {
+      'Content-Type': 'application/json'
+    }
+  }).then((response) => {
+    const reader = response.body.getReader();
+    const decoder = new TextDecoder();
+    let buffer = '';
 
-          buffer += decoder.decode(value, { stream: true })
-          const message = buffer.trim().split('\n').pop()
+    // 逐步读取响应文本
+    const readChunk = () => {
+      return reader.read().then(({ done, value }) => {
+        if (done) {
+          // 处理完成
+          updateStatus(cur_res_id, "finished");
+          isStreaming.value = false;
+          if (conv.value.messages.length === 2) { renameTitle(); }
+          return; // 结束读取
+        }
 
+        buffer += decoder.decode(value, { stream: true });
+        const messages = buffer.trim().split('\n');
+
+        messages.forEach((message) => {
           try {
-            const data = JSON.parse(message)
-            updateMessage(data.response, cur_res_id, data.refs, "loading")
-            conv.value.history = data.history
-            buffer = ''
+            const data = JSON.parse(message);
+            updateMessage(data.response, cur_res_id, data.refs, "loading");
+            conv.value.history = data.history;
           } catch (e) {
-            // console.log(e)
+            console.error('JSON 解析错误:', e);
           }
-          return readChunk()
-        })
-      }
-      return readChunk()
-    })
-    .catch((error) => {
-      console.error(error)
-      updateStatus(cur_res_id, "error")
-      isStreaming.value = false
-    })
+        });
+        buffer = ''; // 清空缓冲区
+        return readChunk(); // 继续读取
+      });
+    };
+    return readChunk();
+  })
+  .catch((error) => {
+    console.error(error);
+    updateStatus(cur_res_id, "error");
+    isStreaming.value = false;
+  });
+}
+
+// 更新后的 sendMessage 函数
+const sendMessage = () => {
+  const user_input = conv.value.inputText.trim();
+  const dbName = opts.databases.length > 0 ? opts.databases[meta.selectedKB]?.metaname : null;
+  if (user_input) {
+    isStreaming.value = true;
+    appendUserMessage(user_input);
+    appendAiMessage("", null);
+    const cur_res_id = conv.value.messages[conv.value.messages.length - 1].id;
+    conv.value.inputText = '';
+    meta.db_name = dbName;
+
+    fetchChatResponse(user_input, cur_res_id)
   } else {
-    console.log('请输入消息')
+    console.log('请输入消息');
   }
 }
 
@@ -436,11 +447,6 @@ const autoSend = (message) => {
   sendMessage()
 }
 
-// const clearChat = () => {
-//   conv.value.messages = []
-//   conv.value.history = []
-// }
-
 // 从本地存储加载数据
 onMounted(() => {
   scrollToBottom()

web/src/components/ConvertToTxtComponent.vue

@@ -15,7 +15,7 @@
             name="file"
             :max-count="1"
             :disabled="state.uploading"
-            action="/api/database/upload"
+            action="/api/data/upload"
             @change="handleFileUpload"
             @drop="handleDrop"
           >
@@ -92,7 +92,7 @@ const convertPdfToText = async () => {
 
   try {
     state.loading = true;
-    const response = await fetch('/api/tools/pdf2txt', {
+    const response = await fetch('/api/tool/pdf2txt', {
       method: 'POST',
       headers: { 'Content-Type': 'application/json' },
       body: JSON.stringify({ file: file })

web/src/components/TextChunkingComponent.vue

@@ -40,7 +40,7 @@
             name="file"
             :max-count="1"
             :disabled="state.uploading"
-            action="/api/database/upload"
+            action="/api/data/upload"
             @change="handleFileUpload"
             @drop="handleDrop"
           >
@@ -125,14 +125,16 @@ const chunkText = async () => {
 
   try {
     state.loading = true
-    const response = await fetch('/api/tools/text_chunking', {
+    const response = await fetch('/api/tool/text-chunking', {
       method: 'POST',
       headers: { 'Content-Type': 'application/json' },
       body: JSON.stringify({
         text: text_or_file,
-        chunk_size: params.chunkSize,
-        chunk_overlap: params.chunkOverlap,
-        use_parser: params.useParser
+        params: {
+          chunk_size: params.chunkSize,
+          chunk_overlap: params.chunkOverlap,
+          use_parser: params.useParser
+        }
       })
     });
 

web/src/layouts/AppLayout.vue

@@ -43,7 +43,7 @@ const getRemoteDatabase = () => {
   if (!configStore.config.enable_knowledge_base) {
     return
   }
-  fetch('/api/database').then(res => res.json()).then(data => {
+  fetch('/api/data').then(res => res.json()).then(data => {
     console.log("database", data)
     databaseStore.setDatabase(data.databases)
   })

web/src/router/index.js

@@ -87,7 +87,7 @@ const router = createRouter({
           meta: { keepAlive: true }
         },
         {
-          path: 'text_chunking',
+          path: 'text-chunking',
           name: 'TextChunking',
           component: () => import('../components/TextChunkingComponent.vue'),
         },

web/src/views/DataBaseInfoView.vue

@@ -32,7 +32,7 @@
               name="file"
               :multiple="true"
               :disabled="state.loading"
-              action="/api/database/upload"
+              action="/api/data/upload"
               @change="handleFileUpload"
               @drop="handleDrop"
             >
@@ -300,7 +300,7 @@ const onQuery = () => {
     return
   }
   meta.db_name = database.value.metaname
-  fetch('/api/database/query-test', {
+  fetch('/api/data/query-test', {
     method: "POST",
     body: JSON.stringify({
       query: queryText.value.trim(),
@@ -359,7 +359,7 @@ const deleteDatabse = () => {
     cancelText: '取消',
     onOk: () => {
       state.lock = true
-      fetch('/api/database/', {
+      fetch('/api/data/', {
         method: "DELETE",
         body: JSON.stringify({
           db_id: databaseId.value
@@ -387,7 +387,7 @@ const deleteDatabse = () => {
 
 const openFileDetail = (record) => {
   state.lock = true
-  fetch(`/api/database/document?db_id=${databaseId.value}&file_id=${record.file_id}`, {
+  fetch(`/api/data/document?db_id=${databaseId.value}&file_id=${record.file_id}`, {
     method: "GET",
   })
     .then(response => response.json())
@@ -427,7 +427,7 @@ const getDatabaseInfo = () => {
   const db_id = databaseId.value
   state.lock = true
   return new Promise((resolve, reject) => {
-    fetch(`/api/database/info?db_id=${db_id}`, {
+    fetch(`/api/data/info?db_id=${db_id}`, {
       method: "GET",
     })
       .then(response => response.json())
@@ -449,7 +449,7 @@ const getDatabaseInfo = () => {
 const deleteFile = (fileId) => {
   console.log(fileId)
   state.lock = true
-  fetch('/api/database/document', {
+  fetch('/api/data/document', {
     method: "DELETE",
     body: JSON.stringify({
       db_id: databaseId.value,
@@ -478,7 +478,7 @@ const addDocumentByFile = () => {
   state.refreshInterval = setInterval(() => {
     getDatabaseInfo();
   }, 1000);
-  fetch('/api/database/add_by_file', {
+  fetch('/api/data/add_by_file', {
     method: "POST",
     body: JSON.stringify({
       db_id: databaseId.value,

web/src/views/DataBaseView.vue

@@ -111,7 +111,7 @@ const newDatabase = reactive({
 
 const loadDatabases = () => {
   // loadGraph()
-  fetch('/api/database/', {
+  fetch('/api/data/', {
     method: "GET",
   })
     .then(response => response.json())
@@ -130,7 +130,7 @@ const createDatabase = () => {
     newDatabase.loading = false
     return
   }
-  fetch('/api/database/', {
+  fetch('/api/data/', {
     method: "POST",
     body: JSON.stringify({
       database_name: newDatabase.name,
@@ -163,7 +163,7 @@ const navigateToGraph = () => {
 
 // const loadGraph = () => {
 //   graphloading.value = true
-//   fetch('/api/database/graph', {
+//   fetch('/api/data/graph', {
 //     method: "GET",
 //   })
 //     .then(response => response.json())

web/src/views/GraphView.vue

@@ -59,7 +59,7 @@
           :fileList="fileList"
           :max-count="1"
           :disabled="state.precessing"
-          action="/api/database/upload"
+          action="/api/data/upload"
           @change="handleFileUpload"
           @drop="handleDrop"
         >
@@ -106,7 +106,7 @@ const state = reactive({
 
 const loadGraphInfo = () => {
   state.loadingGraphInfo = true
-  fetch('/api/database/graph', {
+  fetch('/api/data/graph', {
     method: "GET",
   })
     .then(response => response.json())
@@ -147,7 +147,7 @@ const getGraphData = () => {
 const addDocumentByFile = () => {
   state.precessing = true
   const files = fileList.value.filter(file => file.status === 'done').map(file => file.response.file_path)
-  fetch('/api/database/graph/add', {
+  fetch('/api/data/graph/add', {
     method: 'POST',
     body: JSON.stringify({
       file_path: files[0]
@@ -166,7 +166,7 @@ const addDocumentByFile = () => {
 
 const loadSampleNodes = () => {
   state.fetching = true
-  fetch(`/api/database/graph/nodes?kgdb_name=neo4j&num=${sampleNodeCount.value}`)
+  fetch(`/api/data/graph/nodes?kgdb_name=neo4j&num=${sampleNodeCount.value}`)
     .then((res) => {
       if (res.ok) {
         return res.json();
@@ -199,7 +199,7 @@ const onSearch = () => {
   }
 
   state.searchLoading = true
-  fetch(`/api/database/graph/node?entity_name=${state.searchInput}`)
+  fetch(`/api/data/graph/node?entity_name=${state.searchInput}`)
     .then((res) => {
       if (!res.ok) {
         return res.json().then(errorData => {

web/src/views/ToolsView.vue

@@ -31,7 +31,7 @@ import HeaderComponent from '@/components/HeaderComponent.vue';
 const router = useRouter();
 const tools = ref([]);
 const iconMap = ref({
-  "text_chunking": FileSearchOutlined
+  "text-chunking": FileSearchOutlined
 })
 
 const state = reactive({
@@ -40,7 +40,7 @@ const state = reactive({
 
 const getTools = () => {
   state.loadingTools = true
-  fetch('/api/tools/')
+  fetch('/api/tool/')
     .then(response => response.json())
     .then(data => {
       tools.value = data;