Merge branch 'llm_framework' into dev_ty_06_end

# Conflicts:
#	pilot/memory/chat_history/duckdb_history.py
#	pilot/openapi/api_v1/api_v1.py
#	pilot/scene/base.py
#	pilot/scene/base_chat.py
#	pilot/scene/chat_execution/example.py

datacenter/app/datastores/documents/page.tsx

@@ -2,14 +2,60 @@
 
 import { useRouter, useSearchParams } from 'next/navigation'
 import React, { useState, useEffect } from 'react'
-import { Button, Table } from '@/lib/mui'
+import {
+  Button,
+  Table,
+  Sheet,
+  Modal,
+  Box,
+  Stack,
+  Input,
+  styled
+} from '@/lib/mui'
 import moment from 'moment'
 import { message } from 'antd'
 
+const stepsOfAddingDocument = [
+  'Choose a Datasource type',
+  'Setup the Datasource'
+]
+const documentTypeList = [
+  {
+    type: 'text',
+    title: 'Text',
+    subTitle: 'Paste some text'
+  },
+  {
+    type: 'webPage',
+    title: 'Web Page',
+    subTitle: 'Crawl text from a web page'
+  },
+  {
+    type: 'file',
+    title: 'File',
+    subTitle: 'It can be: PDF, CSV, JSON, Text, PowerPoint, Word, Excel'
+  }
+]
+const Item = styled(Sheet)(({ theme }) => ({
+  width: '50%',
+  backgroundColor:
+    theme.palette.mode === 'dark' ? theme.palette.background.level1 : '#fff',
+  ...theme.typography.body2,
+  padding: theme.spacing(1),
+  textAlign: 'center',
+  borderRadius: 4,
+  color: theme.vars.palette.text.secondary
+}))
+
 const Documents = () => {
   const router = useRouter()
   const spaceName = useSearchParams().get('name')
+  const [isAddDocumentModalShow, setIsAddDocumentModalShow] =
+    useState<boolean>(false)
+  const [activeStep, setActiveStep] = useState<number>(0)
   const [documents, setDocuments] = useState<any>([])
+  const [webPageUrl, setWebPageUrl] = useState<string>('')
+  const [documentName, setDocumentName] = useState<string>('')
   useEffect(() => {
     async function fetchDocuments() {
       const res = await fetch(
@@ -31,6 +77,19 @@ const Documents = () => {
   }, [])
   return (
     <div className="p-4">
+      <Sheet
+        sx={{
+          display: 'flex',
+          flexDirection: 'row-reverse'
+        }}
+      >
+        <Button
+          variant="outlined"
+          onClick={() => setIsAddDocumentModalShow(true)}
+        >
+          + Add Datasource
+        </Button>
+      </Sheet>
       <Table sx={{ '& thead th:nth-child(1)': { width: '40%' } }}>
         <thead>
           <tr>
@@ -70,9 +129,9 @@ const Documents = () => {
                         )
                         const data = await res.json()
                         if (data.success) {
-                          message.success('success');
+                          message.success('success')
                         } else {
-                          message.error(data.err_msg || 'failed');
+                          message.error(data.err_msg || 'failed')
                         }
                       }}
                     >
@@ -95,6 +154,137 @@ const Documents = () => {
           ))}
         </tbody>
       </Table>
+      <Modal
+        sx={{
+          display: 'flex',
+          justifyContent: 'center',
+          alignItems: 'center',
+          'z-index': 1000
+        }}
+        open={isAddDocumentModalShow}
+        onClose={() => setIsAddDocumentModalShow(false)}
+      >
+        <Sheet
+          variant="outlined"
+          sx={{
+            width: 800,
+            borderRadius: 'md',
+            p: 3,
+            boxShadow: 'lg'
+          }}
+        >
+          <Box sx={{ width: '100%' }}>
+            <Stack spacing={2} direction="row">
+              {stepsOfAddingDocument.map((item: any, index: number) => (
+                <Item
+                  key={item}
+                  sx={{ fontWeight: activeStep === index ? 'bold' : '' }}
+                >
+                  {item}
+                </Item>
+              ))}
+            </Stack>
+          </Box>
+          {activeStep === 0 ? (
+            <>
+              <Box sx={{ margin: '30px auto' }}>
+                {documentTypeList.map((item: any) => (
+                  <Sheet
+                    key={item.type}
+                    sx={{
+                      boxSizing: 'border-box',
+                      height: '80px',
+                      padding: '12px',
+                      display: 'flex',
+                      flexDirection: 'column',
+                      justifyContent: 'space-between',
+                      border: '1px solid gray',
+                      borderRadius: '6px',
+                      marginBottom: '20px',
+                      cursor: 'pointer'
+                    }}
+                    onClick={() => {
+                      if (item.type === 'webPage') {
+                        setActiveStep(1)
+                      }
+                    }}
+                  >
+                    <Sheet sx={{ fontSize: '20px', fontWeight: 'bold' }}>
+                      {item.title}
+                    </Sheet>
+                    <Sheet>{item.subTitle}</Sheet>
+                  </Sheet>
+                ))}
+              </Box>
+            </>
+          ) : (
+            <>
+              <Box sx={{ margin: '30px auto' }}>
+                Name:
+                <Input
+                  placeholder="Please input the name"
+                  onChange={(e: any) => setDocumentName(e.target.value)}
+                  sx={{ marginBottom: '20px' }}
+                />
+                Web Page URL:
+                <Input
+                  placeholder="Please input the Web Page URL"
+                  onChange={(e: any) => setWebPageUrl(e.target.value)}
+                />
+              </Box>
+              <Button
+                onClick={async () => {
+                  if (documentName === '') {
+                    message.error('Please input the name')
+                    return
+                  }
+                  if (webPageUrl === '') {
+                    message.error('Please input the Web Page URL')
+                    return
+                  }
+                  const res = await fetch(
+                    `http://localhost:8000/knowledge/${spaceName}/document/add`,
+                    {
+                      method: 'POST',
+                      headers: {
+                        'Content-Type': 'application/json'
+                      },
+                      body: JSON.stringify({
+                        doc_name: documentName,
+                        content: webPageUrl,
+                        doc_type: 'URL'
+                      })
+                    }
+                  )
+                  const data = await res.json()
+                  if (data.success) {
+                    message.success('success')
+                    setIsAddDocumentModalShow(false)
+                    const res = await fetch(
+                      `http://localhost:8000/knowledge/${spaceName}/document/list`,
+                      {
+                        method: 'POST',
+                        headers: {
+                          'Content-Type': 'application/json'
+                        },
+                        body: JSON.stringify({})
+                      }
+                    )
+                    const data = await res.json()
+                    if (data.success) {
+                      setDocuments(data.data)
+                    }
+                  } else {
+                    message.error(data.err_msg || 'failed')
+                  }
+                }}
+              >
+                Finish
+              </Button>
+            </>
+          )}
+        </Sheet>
+      </Modal>
     </div>
   )
 }

datacenter/app/datastores/page.tsx

@@ -1,8 +1,7 @@
 'use client'
 
 import { useRouter } from 'next/navigation'
-import type { ProFormInstance } from '@ant-design/pro-components'
+import React, { useState, useEffect } from 'react'
-import React, { useState, useRef, useEffect } from 'react'
 import { message } from 'antd'
 import {
   Modal,
@@ -31,16 +30,33 @@ const stepsOfAddingSpace = [
   'Choose a Datasource type',
   'Setup the Datasource'
 ]
+const documentTypeList = [
+  {
+    type: 'text',
+    title: 'Text',
+    subTitle: 'Paste some text'
+  },
+  {
+    type: 'webPage',
+    title: 'Web Page',
+    subTitle: 'Crawl text from a web page'
+  },
+  {
+    type: 'file',
+    title: 'File',
+    subTitle: 'It can be: PDF, CSV, JSON, Text, PowerPoint, Word, Excel'
+  }
+]
 
 const Index = () => {
   const router = useRouter()
-  const formRef = useRef<ProFormInstance>()
   const [activeStep, setActiveStep] = useState<number>(0)
   const [knowledgeSpaceList, setKnowledgeSpaceList] = useState<any>([])
   const [isAddKnowledgeSpaceModalShow, setIsAddKnowledgeSpaceModalShow] =
     useState<boolean>(false)
   const [knowledgeSpaceName, setKnowledgeSpaceName] = useState<string>('')
   const [webPageUrl, setWebPageUrl] = useState<string>('')
+  const [documentName, setDocumentName] = useState<string>('')
   useEffect(() => {
     async function fetchData() {
       const res = await fetch('http://localhost:8000/knowledge/space/list', {
@@ -59,15 +75,21 @@ const Index = () => {
   }, [])
   return (
     <>
-      <div className="page-header p-4">
+      <Sheet sx={{
-        <div className="page-header-title">Knowledge Spaces</div>
+        display: "flex",
+        justifyContent: "space-between"
+      }} className="p-4">
+        <Sheet sx={{
+          fontSize: '30px',
+          fontWeight: 'bold'
+        }}>Knowledge Spaces</Sheet>
         <Button
           onClick={() => setIsAddKnowledgeSpaceModalShow(true)}
           variant="outlined"
         >
           + New Knowledge Space
         </Button>
-      </div>
+      </Sheet>
       <div className="page-body p-4">
         <Table sx={{ '& thead th:nth-child(1)': { width: '40%' } }}>
           <thead>
@@ -100,7 +122,6 @@ const Index = () => {
         </Table>
       </div>
       <Modal
-        title="Add Knowledge Space"
         sx={{
           display: 'flex',
           justifyContent: 'center',
@@ -191,14 +212,42 @@ const Index = () => {
           ) : activeStep === 1 ? (
             <>
               <Box sx={{ margin: '30px auto' }}>
-                <Button variant="outlined" onClick={() => setActiveStep(2)}>
+                {documentTypeList.map((item: any) => (
-                  Web Page
+                  <Sheet
-                </Button>
+                    key={item.type}
+                    sx={{
+                      boxSizing: 'border-box',
+                      height: '80px',
+                      padding: '12px',            
+                      display: 'flex',
+                      flexDirection: 'column',
+                      justifyContent: 'space-between',
+                      border: '1px solid gray',
+                      borderRadius: '6px',
+                      marginBottom: '20px',
+                      cursor: 'pointer'
+                    }}
+                    onClick={() => {
+                      if (item.type === 'webPage') {
+                        setActiveStep(2);
+                      }
+                    }}
+                  >
+                    <Sheet sx={{ fontSize: '20px', fontWeight: 'bold' }}>{item.title}</Sheet>
+                    <Sheet>{item.subTitle}</Sheet>
+                  </Sheet>
+                ))}
               </Box>
             </>
           ) : (
             <>
               <Box sx={{ margin: '30px auto' }}>
+                Name:
+                <Input
+                  placeholder="Please input the name"
+                  onChange={(e: any) => setDocumentName(e.target.value)}
+                  sx={{ marginBottom: '20px'}}
+                />
                 Web Page URL:
                 <Input
                   placeholder="Please input the Web Page URL"
@@ -207,6 +256,14 @@ const Index = () => {
               </Box>
               <Button
                 onClick={async () => {
+                  if (documentName === '') {
+                    message.error('Please input the name');
+                    return;
+                  }
+                  if (webPageUrl === '') {
+                    message.error('Please input the Web Page URL');
+                    return;
+                  }
                   const res = await fetch(
                     `http://localhost:8000/knowledge/${knowledgeSpaceName}/document/add`,
                     {
@@ -215,7 +272,8 @@ const Index = () => {
                         'Content-Type': 'application/json'
                       },
                       body: JSON.stringify({
-                        doc_name: webPageUrl,
+                        doc_name: documentName,
+                        content: webPageUrl,
                         doc_type: 'URL'
                       })
                     }
@@ -235,24 +293,6 @@ const Index = () => {
           )}
         </Sheet>
       </Modal>
-      <style jsx>{`
-        .page-header {
-          display: flex;
-          justify-content: space-between;
-          .page-header-title {
-            font-size: 30px;
-            font-weight: bold;
-          }
-        }
-        .datasource-type-wrap {
-          height: 100px;
-          line-height: 100px;
-          border: 1px solid black;
-          border-radius: 20px;
-          margin-bottom: 20px;
-          cursor: pointer;
-        }
-      `}</style>
     </>
   )
 }

pilot/common/formatting.py

@@ -43,7 +43,7 @@ class MyEncoder(json.JSONEncoder):
     def default(self, obj):
         if isinstance(obj, set):
             return list(obj)
-        elif hasattr(obj, '__dict__'):
+        elif hasattr(obj, "__dict__"):
             return obj.__dict__
         else:
             return json.JSONEncoder.default(self, obj)

pilot/common/plugins.py

@@ -78,6 +78,7 @@ def load_native_plugins(cfg: Config):
     if not cfg.plugins_auto_load:
         print("not auto load_native_plugins")
         return
+
     def load_from_git(cfg: Config):
         print("async load_native_plugins")
         branch_name = cfg.plugins_git_branch
@@ -85,16 +86,20 @@ def load_native_plugins(cfg: Config):
         url = "https://github.com/csunny/{repo}/archive/{branch}.zip"
         try:
             session = requests.Session()
-            response = session.get(url.format(repo=native_plugin_repo, branch=branch_name),
+            response = session.get(
-                                    headers={'Authorization': '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'})
+                url.format(repo=native_plugin_repo, branch=branch_name),
+                headers={"Authorization": "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"},
+            )
 
             if response.status_code == 200:
                 plugins_path_path = Path(PLUGINS_DIR)
-                files = glob.glob(os.path.join(plugins_path_path, f'{native_plugin_repo}*'))
+                files = glob.glob(
+                    os.path.join(plugins_path_path, f"{native_plugin_repo}*")
+                )
                 for file in files:
                     os.remove(file)
                 now = datetime.datetime.now()
-                time_str = now.strftime('%Y%m%d%H%M%S')
+                time_str = now.strftime("%Y%m%d%H%M%S")
                 file_name = f"{plugins_path_path}/{native_plugin_repo}-{branch_name}-{time_str}.zip"
                 print(file_name)
                 with open(file_name, "wb") as f:
@@ -110,7 +115,6 @@ def load_native_plugins(cfg: Config):
     t.start()
 
 
-
 def scan_plugins(cfg: Config, debug: bool = False) -> List[AutoGPTPluginTemplate]:
     """Scan the plugins directory for plugins and loads them.
 

pilot/common/schema.py

@@ -8,6 +8,7 @@ class SeparatorStyle(Enum):
     THREE = auto()
     FOUR = auto()
 
+
 class ExampleType(Enum):
     ONE_SHOT = "one_shot"
     FEW_SHOT = "few_shot"

pilot/connections/rdbms/py_study/test_cls_1.py

@@ -5,8 +5,8 @@ from test_cls_base import TestBase
 
 class Test1(TestBase):
     mode: str = "456"
+
     def write(self):
         self.test_values.append("x")
         self.test_values.append("y")
         self.test_values.append("g")
-

pilot/connections/rdbms/py_study/test_cls_2.py

@@ -3,9 +3,11 @@ from pydantic import BaseModel
 from test_cls_base import TestBase
 from typing import Any, Callable, Dict, List, Mapping, Optional, Set, Union
 
+
 class Test2(TestBase):
     test_2_values: List = []
     mode: str = "789"
+
     def write(self):
         self.test_values.append(1)
         self.test_values.append(2)

pilot/embedding_engine/knowledge_embedding.py

@@ -39,7 +39,9 @@ class KnowledgeEmbedding:
         return self.knowledge_embedding_client.read_batch()
 
     def init_knowledge_embedding(self):
-        return get_knowledge_embedding(self.knowledge_type, self.knowledge_source, self.vector_store_config)
+        return get_knowledge_embedding(
+            self.knowledge_type, self.knowledge_source, self.vector_store_config
+        )
 
     def similar_search(self, text, topk):
         vector_client = VectorStoreConnector(
@@ -56,3 +58,9 @@ class KnowledgeEmbedding:
             CFG.VECTOR_STORE_TYPE, self.vector_store_config
         )
         return vector_client.vector_name_exists()
+
+    def delete_by_ids(self, ids):
+        vector_client = VectorStoreConnector(
+            CFG.VECTOR_STORE_TYPE, self.vector_store_config
+        )
+        vector_client.delete_by_ids(ids=ids)

pilot/memory/chat_history/base.py

@@ -33,8 +33,6 @@ class BaseChatHistoryMemory(ABC):
     def clear(self) -> None:
         """Clear session memory from the local file"""
 
-
     def conv_list(self, user_name: str = None) -> None:
         """get user's conversation list"""
         pass
-

pilot/memory/chat_history/mem_history.py

@@ -19,7 +19,6 @@ CFG = Config()
 class MemHistoryMemory(BaseChatHistoryMemory):
     histroies_map = FixedSizeDict(100)
 
-
     def __init__(self, chat_session_id: str):
         self.chat_seesion_id = chat_session_id
         self.histroies_map.update({chat_session_id: []})

pilot/model/cache/base.py

@@ -3,8 +3,8 @@ import hashlib
 from typing import Any, Dict
 from abc import ABC, abstractmethod
 
-class Cache(ABC):
 
+class Cache(ABC):
     def create(self, key: str) -> bool:
         pass
 

pilot/model/cache/disk_cache.py

@@ -3,15 +3,15 @@ import diskcache
 import platformdirs
 from pilot.model.cache import Cache
 
+
 class DiskCache(Cache):
     """DiskCache is a cache that uses diskcache lib.
     https://github.com/grantjenks/python-diskcache
     """
+
     def __init__(self, llm_name: str):
         self._diskcache = diskcache.Cache(
-            os.path.join(
+            os.path.join(platformdirs.user_cache_dir("dbgpt"), f"_{llm_name}.diskcache")
-                platformdirs.user_cache_dir("dbgpt"), f"_{llm_name}.diskcache"
-            )
         )
 
     def __getitem__(self, key: str) -> str:

pilot/model/cache/gpt_cache.py

@@ -9,6 +9,7 @@ try:
 except ImportError:
     pass
 
+
 class GPTCache(Cache):
 
     """
@@ -24,7 +25,7 @@ class GPTCache(Cache):
                 data_dir=os.path.join(
                     platformdirs.user_cache_dir("dbgpt"), f"_{cache}.gptcache"
                 ),
-                cache_obj=_cache
+                cache_obj=_cache,
             )
         else:
             _cache = cache

pilot/model/cache/memory_cache.py

@@ -1,8 +1,8 @@
 from typing import Dict, Any
 from pilot.model.cache import Cache
 
-class InMemoryCache(Cache):
 
+class InMemoryCache(Cache):
     def __init__(self) -> None:
         "Initialize that stores things in memory."
         self._cache: Dict[str, Any] = {}
@@ -21,4 +21,3 @@ class InMemoryCache(Cache):
 
     def __contains__(self, key: str) -> bool:
         return self._cache.get(key, None) is not None
-

pilot/openapi/api_v1/api_v1.py

@@ -2,7 +2,7 @@ import uuid
 import json
 import asyncio
 import time
-from fastapi import APIRouter, Request, Body, status, HTTPException, Response, BackgroundTasks
+from fastapi import APIRouter, Request, Body, status, HTTPException, Response
 
 from fastapi.responses import JSONResponse
 from fastapi.responses import StreamingResponse
@@ -16,12 +16,13 @@ from pilot.openapi.api_v1.api_view_model import Result, ConversationVo, MessageV
 from pilot.configs.config import Config
 from pilot.openapi.knowledge.knowledge_service import KnowledgeService
 from pilot.openapi.knowledge.request.knowledge_request import KnowledgeSpaceRequest
+
 from pilot.scene.base_chat import BaseChat
 from pilot.scene.base import ChatScene
 from pilot.scene.chat_factory import ChatFactory
-from pilot.configs.model_config import (LOGDIR)
+from pilot.configs.model_config import LOGDIR
 from pilot.utils import build_logger
-from pilot.scene.base_message import (BaseMessage)
+from pilot.scene.base_message import BaseMessage
 from pilot.memory.chat_history.duckdb_history import DuckdbHistoryMemory
 from pilot.scene.message import OnceConversation
 
@@ -42,19 +43,19 @@ async def validation_exception_handler(request: Request, exc: RequestValidationE
 
 
 def __get_conv_user_message(conversations: dict):
-    messages = conversations['messages']
+    messages = conversations["messages"]
     for item in messages:
-        if item['type'] == "human":
+        if item["type"] == "human":
-            return item['data']['content']
+            return item["data"]["content"]
     return ""
 
 
-@router.get('/v1/chat/dialogue/list', response_model=Result[ConversationVo])
+@router.get("/v1/chat/dialogue/list", response_model=Result[ConversationVo])
 async def dialogue_list(response: Response, user_id: str = None):
     # 设置CORS头部信息
-    response.headers['Access-Control-Allow-Origin'] = '*'
+    response.headers["Access-Control-Allow-Origin"] = "*"
-    response.headers['Access-Control-Allow-Methods'] = 'GET'
+    response.headers["Access-Control-Allow-Methods"] = "GET"
-    response.headers['Access-Control-Request-Headers'] = 'content-type'
+    response.headers["Access-Control-Request-Headers"] = "content-type"
 
     dialogues: List = []
     datas = DuckdbHistoryMemory.conv_list(user_id)
@@ -65,26 +66,44 @@ async def dialogue_list(response: Response, user_id: str = None):
         conversations = json.loads(messages)
 
         first_conv: OnceConversation = conversations[0]
-        conv_vo: ConversationVo = ConversationVo(conv_uid=conv_uid, user_input=__get_conv_user_message(first_conv),
+        conv_vo: ConversationVo = ConversationVo(
-                                                 chat_mode=first_conv['chat_mode'])
+            conv_uid=conv_uid,
+            user_input=__get_conv_user_message(first_conv),
+            chat_mode=first_conv["chat_mode"],
+        )
         dialogues.append(conv_vo)
 
     return Result[ConversationVo].succ(dialogues)
 
 
-@router.post('/v1/chat/dialogue/scenes', response_model=Result[List[ChatSceneVo]])
+@router.post("/v1/chat/dialogue/scenes", response_model=Result[List[ChatSceneVo]])
 async def dialogue_scenes():
     scene_vos: List[ChatSceneVo] = []
-    new_modes:List[ChatScene] = [ChatScene.ChatDb, ChatScene.ChatData, ChatScene.ChatDashboard, ChatScene.ChatKnowledge, ChatScene.ChatExecution]
+    new_modes: List[ChatScene] = [
+        ChatScene.ChatDb,
+        ChatScene.ChatData,
+        ChatScene.ChatDashboard,
+        ChatScene.ChatKnowledge,
+        ChatScene.ChatExecution,
+    ]
     for scene in new_modes:
-        if not scene.value in [ChatScene.ChatNormal.value, ChatScene.InnerChatDBSummary.value]:
+        if not scene.value in [
-            scene_vo = ChatSceneVo(chat_scene=scene.value, scene_name=scene.name, param_title="Selection Param")
+            ChatScene.ChatNormal.value,
+            ChatScene.InnerChatDBSummary.value,
+        ]:
+            scene_vo = ChatSceneVo(
+                chat_scene=scene.value,
+                scene_name=scene.name,
+                param_title="Selection Param",
+            )
             scene_vos.append(scene_vo)
     return Result.succ(scene_vos)
 
 
-@router.post('/v1/chat/dialogue/new', response_model=Result[ConversationVo])
+@router.post("/v1/chat/dialogue/new", response_model=Result[ConversationVo])
-async def dialogue_new(chat_mode: str = ChatScene.ChatNormal.value, user_id: str = None):
+async def dialogue_new(
+    chat_mode: str = ChatScene.ChatNormal.value, user_id: str = None
+):
     unique_id = uuid.uuid1()
     return Result.succ(ConversationVo(conv_uid=str(unique_id), chat_mode=chat_mode))
 
@@ -106,11 +125,16 @@ def plugins_select_info():
 
 
 def knowledge_list():
+    """return knowledge space list"""
+    params: dict = {}
     request = KnowledgeSpaceRequest()
-    return knowledge_service.get_knowledge_space(request)
+    spaces = knowledge_service.get_knowledge_space(request)
+    for space in spaces:
+        params.update({space.name: space.name})
+    return params
 
 
-@router.post('/v1/chat/mode/params/list', response_model=Result[dict])
+@router.post("/v1/chat/mode/params/list", response_model=Result[dict])
 async def params_list(chat_mode: str = ChatScene.ChatNormal.value):
     if ChatScene.ChatWithDbQA.value == chat_mode:
         return Result.succ(get_db_list())
@@ -126,14 +150,14 @@ async def params_list(chat_mode: str = ChatScene.ChatNormal.value):
         return Result.succ(None)
 
 
-@router.post('/v1/chat/dialogue/delete')
+@router.post("/v1/chat/dialogue/delete")
 async def dialogue_delete(con_uid: str):
     history_mem = DuckdbHistoryMemory(con_uid)
     history_mem.delete()
     return Result.succ(None)
 
 
-@router.get('/v1/chat/dialogue/messages/history', response_model=Result[MessageVo])
+@router.get("/v1/chat/dialogue/messages/history", response_model=Result[MessageVo])
 async def dialogue_history_messages(con_uid: str):
     print(f"dialogue_history_messages:{con_uid}")
     message_vos: List[MessageVo] = []
@@ -142,12 +166,14 @@ async def dialogue_history_messages(con_uid: str):
     history_messages: List[OnceConversation] = history_mem.get_messages()
     if history_messages:
         for once in history_messages:
-            once_message_vos = [message2Vo(element, once['chat_order']) for element in once['messages']]
+            once_message_vos = [
+                message2Vo(element, once["chat_order"]) for element in once["messages"]
+            ]
             message_vos.extend(once_message_vos)
     return Result.succ(message_vos)
 
 
-@router.post('/v1/chat/completions')
+@router.post("/v1/chat/completions")
 async def chat_completions(dialogue: ConversationVo = Body()):
     print(f"chat_completions:{dialogue.chat_mode},{dialogue.select_param}")
     global model_semaphore, global_counter
@@ -157,7 +183,9 @@ async def chat_completions(dialogue: ConversationVo = Body()):
     await model_semaphore.acquire()
 
     if not ChatScene.is_valid_mode(dialogue.chat_mode):
-        raise StopAsyncIteration(Result.faild("Unsupported Chat Mode," + dialogue.chat_mode + "!"))
+        raise StopAsyncIteration(
+            Result.faild("Unsupported Chat Mode," + dialogue.chat_mode + "!")
+        )
 
     chat_param = {
         "chat_session_id": dialogue.conv_uid,

pilot/openapi/api_v1/api_view_model.py

@@ -1,7 +1,7 @@
 from pydantic import BaseModel, Field
 from typing import TypeVar, Union, List, Generic, Any
 
-T = TypeVar('T')
+T = TypeVar("T")
 
 
 class Result(Generic[T], BaseModel):
@@ -28,10 +28,12 @@ class ChatSceneVo(BaseModel):
     scene_name: str = Field(..., description="chat_scene name show for user")
     param_title: str = Field(..., description="chat_scene required parameter title")
 
+
 class ConversationVo(BaseModel):
     """
     dialogue_uid
     """
+
     conv_uid: str = Field(..., description="dialogue uid")
     """ 
     user input 
@@ -52,11 +54,11 @@ class ConversationVo(BaseModel):
     select_param: str = None
 
 
-
 class MessageVo(BaseModel):
     """
     role that sends out the current message
     """
+
     role: str
     """
     current message 
@@ -70,4 +72,3 @@ class MessageVo(BaseModel):
     time the current message was sent 
     """
     time_stamp: Any = None
-

pilot/openapi/knowledge/document_chunk_dao.py

@@ -10,8 +10,10 @@ from pilot.configs.config import Config
 CFG = Config()
 
 Base = declarative_base()
+
+
 class DocumentChunkEntity(Base):
-    __tablename__ = 'document_chunk'
+    __tablename__ = "document_chunk"
     id = Column(Integer, primary_key=True)
     document_id = Column(Integer)
     doc_name = Column(String(100))
@@ -29,8 +31,9 @@ class DocumentChunkDao:
     def __init__(self):
         database = "knowledge_management"
         self.db_engine = create_engine(
-            f'mysql+pymysql://{CFG.LOCAL_DB_USER}:{CFG.LOCAL_DB_PASSWORD}@{CFG.LOCAL_DB_HOST}:{CFG.LOCAL_DB_PORT}/{database}',
+            f"mysql+pymysql://{CFG.LOCAL_DB_USER}:{CFG.LOCAL_DB_PASSWORD}@{CFG.LOCAL_DB_HOST}:{CFG.LOCAL_DB_PORT}/{database}",
-            echo=True)
+            echo=True,
+        )
         self.Session = sessionmaker(bind=self.db_engine)
 
     def create_documents_chunks(self, documents: List):
@@ -43,9 +46,10 @@ class DocumentChunkDao:
                 content=document.content or "",
                 meta_info=document.meta_info or "",
                 gmt_created=datetime.now(),
-            gmt_modified=datetime.now()
+                gmt_modified=datetime.now(),
             )
-        for document in documents]
+            for document in documents
+        ]
         session.add_all(docs)
         session.commit()
         session.close()
@@ -56,16 +60,26 @@ class DocumentChunkDao:
         if query.id is not None:
             document_chunks = document_chunks.filter(DocumentChunkEntity.id == query.id)
         if query.document_id is not None:
-            document_chunks = document_chunks.filter(DocumentChunkEntity.document_id == query.document_id)
+            document_chunks = document_chunks.filter(
+                DocumentChunkEntity.document_id == query.document_id
+            )
         if query.doc_type is not None:
-            document_chunks = document_chunks.filter(DocumentChunkEntity.doc_type == query.doc_type)
+            document_chunks = document_chunks.filter(
+                DocumentChunkEntity.doc_type == query.doc_type
+            )
         if query.doc_name is not None:
-            document_chunks = document_chunks.filter(DocumentChunkEntity.doc_name == query.doc_name)
+            document_chunks = document_chunks.filter(
+                DocumentChunkEntity.doc_name == query.doc_name
+            )
         if query.meta_info is not None:
-            document_chunks = document_chunks.filter(DocumentChunkEntity.meta_info == query.meta_info)
+            document_chunks = document_chunks.filter(
+                DocumentChunkEntity.meta_info == query.meta_info
+            )
 
         document_chunks = document_chunks.order_by(DocumentChunkEntity.id.desc())
-        document_chunks = document_chunks.offset((page - 1) * page_size).limit(page_size)
+        document_chunks = document_chunks.offset((page - 1) * page_size).limit(
+            page_size
+        )
         result = document_chunks.all()
         return result
 

pilot/openapi/knowledge/knowledge_controller.py

@@ -13,7 +13,11 @@ from pilot.embedding_engine.knowledge_embedding import KnowledgeEmbedding
 from pilot.openapi.knowledge.knowledge_service import KnowledgeService
 from pilot.openapi.knowledge.request.knowledge_request import (
     KnowledgeQueryRequest,
-    KnowledgeQueryResponse, KnowledgeDocumentRequest, DocumentSyncRequest, ChunkQueryRequest, DocumentQueryRequest,
+    KnowledgeQueryResponse,
+    KnowledgeDocumentRequest,
+    DocumentSyncRequest,
+    ChunkQueryRequest,
+    DocumentQueryRequest,
 )
 
 from pilot.openapi.knowledge.request.knowledge_request import KnowledgeSpaceRequest
@@ -62,16 +66,15 @@ def document_add(space_name: str, request: KnowledgeDocumentRequest):
 def document_list(space_name: str, query_request: DocumentQueryRequest):
     print(f"/document/list params: {space_name}, {query_request}")
     try:
-        return Result.succ(knowledge_space_service.get_knowledge_documents(
+        return Result.succ(
-                space_name,
+            knowledge_space_service.get_knowledge_documents(space_name, query_request)
-                query_request
+        )
-            ))
     except Exception as e:
         return Result.faild(code="E000X", msg=f"document list error {e}")
 
 
 @router.post("/knowledge/{space_name}/document/upload")
-def document_sync(space_name: str, file: UploadFile = File(...)):
+async def document_sync(space_name: str, file: UploadFile = File(...)):
     print(f"/document/upload params: {space_name}")
     try:
         with NamedTemporaryFile(delete=False) as tmp:
@@ -92,7 +95,7 @@ def document_sync(space_name: str, request: DocumentSyncRequest):
         knowledge_space_service.sync_knowledge_document(
             space_name=space_name, doc_ids=request.doc_ids
         )
-        Result.succ([])
+        return Result.succ([])
     except Exception as e:
         return Result.faild(code="E000X", msg=f"document sync error {e}")
 
@@ -101,9 +104,7 @@ def document_sync(space_name: str, request: DocumentSyncRequest):
 def document_list(space_name: str, query_request: ChunkQueryRequest):
     print(f"/document/list params: {space_name}, {query_request}")
     try:
-        return Result.succ(knowledge_space_service.get_document_chunks(
+        return Result.succ(knowledge_space_service.get_document_chunks(query_request))
-                query_request
-            ))
     except Exception as e:
         return Result.faild(code="E000X", msg=f"document chunk list error {e}")
 

pilot/openapi/knowledge/knowledge_document_dao.py

@@ -12,7 +12,7 @@ Base = declarative_base()
 
 
 class KnowledgeDocumentEntity(Base):
-    __tablename__ = 'knowledge_document'
+    __tablename__ = "knowledge_document"
     id = Column(Integer, primary_key=True)
     doc_name = Column(String(100))
     doc_type = Column(String(100))
@@ -21,20 +21,22 @@ class KnowledgeDocumentEntity(Base):
     status = Column(String(100))
     last_sync = Column(String(100))
     content = Column(Text)
+    result = Column(Text)
     vector_ids = Column(Text)
     gmt_created = Column(DateTime)
     gmt_modified = Column(DateTime)
 
     def __repr__(self):
-        return f"KnowledgeDocumentEntity(id={self.id}, doc_name='{self.doc_name}', doc_type='{self.doc_type}', chunk_size='{self.chunk_size}', status='{self.status}', last_sync='{self.last_sync}', content='{self.content}', gmt_created='{self.gmt_created}', gmt_modified='{self.gmt_modified}')"
+        return f"KnowledgeDocumentEntity(id={self.id}, doc_name='{self.doc_name}', doc_type='{self.doc_type}', chunk_size='{self.chunk_size}', status='{self.status}', last_sync='{self.last_sync}', content='{self.content}', result='{self.result}', gmt_created='{self.gmt_created}', gmt_modified='{self.gmt_modified}')"
 
 
 class KnowledgeDocumentDao:
     def __init__(self):
         database = "knowledge_management"
         self.db_engine = create_engine(
-            f'mysql+pymysql://{CFG.LOCAL_DB_USER}:{CFG.LOCAL_DB_PASSWORD}@{CFG.LOCAL_DB_HOST}:{CFG.LOCAL_DB_PORT}/{database}',
+            f"mysql+pymysql://{CFG.LOCAL_DB_USER}:{CFG.LOCAL_DB_PASSWORD}@{CFG.LOCAL_DB_HOST}:{CFG.LOCAL_DB_PORT}/{database}",
-            echo=True)
+            echo=True,
+        )
         self.Session = sessionmaker(bind=self.db_engine)
 
     def create_knowledge_document(self, document: KnowledgeDocumentEntity):
@@ -47,9 +49,10 @@ class KnowledgeDocumentDao:
             status=document.status,
             last_sync=document.last_sync,
             content=document.content or "",
+            result=document.result or "",
             vector_ids=document.vector_ids,
             gmt_created=datetime.now(),
-            gmt_modified=datetime.now()
+            gmt_modified=datetime.now(),
         )
         session.add(knowledge_document)
         session.commit()
@@ -60,18 +63,32 @@ class KnowledgeDocumentDao:
         session = self.Session()
         knowledge_documents = session.query(KnowledgeDocumentEntity)
         if query.id is not None:
-            knowledge_documents = knowledge_documents.filter(KnowledgeDocumentEntity.id == query.id)
+            knowledge_documents = knowledge_documents.filter(
+                KnowledgeDocumentEntity.id == query.id
+            )
         if query.doc_name is not None:
-            knowledge_documents = knowledge_documents.filter(KnowledgeDocumentEntity.doc_name == query.doc_name)
+            knowledge_documents = knowledge_documents.filter(
+                KnowledgeDocumentEntity.doc_name == query.doc_name
+            )
         if query.doc_type is not None:
-            knowledge_documents = knowledge_documents.filter(KnowledgeDocumentEntity.doc_type == query.doc_type)
+            knowledge_documents = knowledge_documents.filter(
+                KnowledgeDocumentEntity.doc_type == query.doc_type
+            )
         if query.space is not None:
-            knowledge_documents = knowledge_documents.filter(KnowledgeDocumentEntity.space == query.space)
+            knowledge_documents = knowledge_documents.filter(
+                KnowledgeDocumentEntity.space == query.space
+            )
         if query.status is not None:
-            knowledge_documents = knowledge_documents.filter(KnowledgeDocumentEntity.status == query.status)
+            knowledge_documents = knowledge_documents.filter(
+                KnowledgeDocumentEntity.status == query.status
+            )
 
-        knowledge_documents = knowledge_documents.order_by(KnowledgeDocumentEntity.id.desc())
+        knowledge_documents = knowledge_documents.order_by(
-        knowledge_documents = knowledge_documents.offset((page - 1) * page_size).limit(page_size)
+            KnowledgeDocumentEntity.id.desc()
+        )
+        knowledge_documents = knowledge_documents.offset((page - 1) * page_size).limit(
+            page_size
+        )
         result = knowledge_documents.all()
         return result
 

pilot/openapi/knowledge/knowledge_service.py

@@ -4,17 +4,24 @@ from datetime import datetime
 from pilot.configs.config import Config
 from pilot.configs.model_config import LLM_MODEL_CONFIG
 from pilot.embedding_engine.knowledge_embedding import KnowledgeEmbedding
-from pilot.embedding_engine.knowledge_type import KnowledgeType
 from pilot.logs import logger
-from pilot.openapi.knowledge.document_chunk_dao import DocumentChunkEntity, DocumentChunkDao
+from pilot.openapi.knowledge.document_chunk_dao import (
+    DocumentChunkEntity,
+    DocumentChunkDao,
+)
 from pilot.openapi.knowledge.knowledge_document_dao import (
     KnowledgeDocumentDao,
     KnowledgeDocumentEntity,
 )
-from pilot.openapi.knowledge.knowledge_space_dao import KnowledgeSpaceDao, KnowledgeSpaceEntity
+from pilot.openapi.knowledge.knowledge_space_dao import (
+    KnowledgeSpaceDao,
+    KnowledgeSpaceEntity,
+)
 from pilot.openapi.knowledge.request.knowledge_request import (
     KnowledgeSpaceRequest,
-    KnowledgeDocumentRequest, DocumentQueryRequest, ChunkQueryRequest,
+    KnowledgeDocumentRequest,
+    DocumentQueryRequest,
+    ChunkQueryRequest,
 )
 from enum import Enum
 
@@ -53,10 +60,7 @@ class KnowledgeService:
     """create knowledge document"""
 
     def create_knowledge_document(self, space, request: KnowledgeDocumentRequest):
-        query = KnowledgeDocumentEntity(
+        query = KnowledgeDocumentEntity(doc_name=request.doc_name, space=space)
-            doc_name=request.doc_name,
-            space=space
-        )
         documents = knowledge_document_dao.get_knowledge_documents(query)
         if len(documents) > 0:
             raise Exception(f"document name:{request.doc_name} have already named")
@@ -76,9 +80,7 @@ class KnowledgeService:
 
     def get_knowledge_space(self, request: KnowledgeSpaceRequest):
         query = KnowledgeSpaceEntity(
-            name=request.name,
+            name=request.name, vector_type=request.vector_type, owner=request.owner
-            vector_type=request.vector_type,
-            owner=request.owner
         )
         return knowledge_space_dao.get_knowledge_space(query)
 
@@ -91,9 +93,12 @@ class KnowledgeService:
             space=space,
             status=request.status,
         )
-        return knowledge_document_dao.get_knowledge_documents(query, page=request.page, page_size=request.page_size)
+        return knowledge_document_dao.get_knowledge_documents(
+            query, page=request.page, page_size=request.page_size
+        )
 
     """sync knowledge document chunk into vector store"""
+
     def sync_knowledge_document(self, space_name, doc_ids):
         for doc_id in doc_ids:
             query = KnowledgeDocumentEntity(
@@ -101,12 +106,14 @@ class KnowledgeService:
                 space=space_name,
             )
             doc = knowledge_document_dao.get_knowledge_documents(query)[0]
-            client = KnowledgeEmbedding(knowledge_source=doc.content,
+            client = KnowledgeEmbedding(
+                knowledge_source=doc.content,
                 knowledge_type=doc.doc_type.upper(),
                 model_name=LLM_MODEL_CONFIG[CFG.EMBEDDING_MODEL],
                 vector_store_config={
                     "vector_store_name": space_name,
-                                        })
+                },
+            )
             chunk_docs = client.read()
             # update document status
             doc.status = SyncStatus.RUNNING.name
@@ -114,8 +121,11 @@ class KnowledgeService:
             doc.gmt_modified = datetime.now()
             knowledge_document_dao.update_knowledge_document(doc)
             # async doc embeddings
-            thread = threading.Thread(target=self.async_doc_embedding(client, chunk_docs, doc))
+            thread = threading.Thread(
+                target=self.async_doc_embedding, args=(client, chunk_docs, doc)
+            )
             thread.start()
+            logger.info(f"begin save document chunks, doc:{doc.doc_name}")
             # save chunk details
             chunk_entities = [
                 DocumentChunkEntity(
@@ -125,9 +135,10 @@ class KnowledgeService:
                     content=chunk_doc.page_content,
                     meta_info=str(chunk_doc.metadata),
                     gmt_created=datetime.now(),
-                    gmt_modified=datetime.now()
+                    gmt_modified=datetime.now(),
                 )
-                for chunk_doc in chunk_docs]
+                for chunk_doc in chunk_docs
+            ]
             document_chunk_dao.create_documents_chunks(chunk_entities)
 
         return True
@@ -145,26 +156,30 @@ class KnowledgeService:
         return knowledge_space_dao.delete_knowledge_space(space_id)
 
     """get document chunks"""
+
     def get_document_chunks(self, request: ChunkQueryRequest):
         query = DocumentChunkEntity(
             id=request.id,
             document_id=request.document_id,
             doc_name=request.doc_name,
-            doc_type=request.doc_type
+            doc_type=request.doc_type,
+        )
+        return document_chunk_dao.get_document_chunks(
+            query, page=request.page, page_size=request.page_size
         )
-        return document_chunk_dao.get_document_chunks(query, page=request.page, page_size=request.page_size)
 
     def async_doc_embedding(self, client, chunk_docs, doc):
-        logger.info(f"async_doc_embedding, doc:{doc.doc_name}, chunk_size:{len(chunk_docs)}, begin embedding to vector store-{CFG.VECTOR_STORE_TYPE}")
+        logger.info(
+            f"async_doc_embedding, doc:{doc.doc_name}, chunk_size:{len(chunk_docs)}, begin embedding to vector store-{CFG.VECTOR_STORE_TYPE}"
+        )
         try:
             vector_ids = client.knowledge_embedding_batch(chunk_docs)
             doc.status = SyncStatus.FINISHED.name
-            doc.content = "embedding success"
+            doc.result = "document embedding success"
             doc.vector_ids = ",".join(vector_ids)
+            logger.info(f"async document embedding, success:{doc.doc_name}")
         except Exception as e:
             doc.status = SyncStatus.FAILED.name
-            doc.content = str(e)
+            doc.result = "document embedding failed" + str(e)
-
+            logger.error(f"document embedding, failed:{doc.doc_name}, {str(e)}")
         return knowledge_document_dao.update_knowledge_document(doc)
-
-

pilot/openapi/knowledge/knowledge_space_dao.py

@@ -10,8 +10,10 @@ from sqlalchemy.orm import sessionmaker
 
 CFG = Config()
 Base = declarative_base()
+
+
 class KnowledgeSpaceEntity(Base):
-    __tablename__ = 'knowledge_space'
+    __tablename__ = "knowledge_space"
     id = Column(Integer, primary_key=True)
     name = Column(String(100))
     vector_type = Column(String(100))
@@ -27,7 +29,10 @@ class KnowledgeSpaceEntity(Base):
 class KnowledgeSpaceDao:
     def __init__(self):
         database = "knowledge_management"
-        self.db_engine = create_engine(f'mysql+pymysql://{CFG.LOCAL_DB_USER}:{CFG.LOCAL_DB_PASSWORD}@{CFG.LOCAL_DB_HOST}:{CFG.LOCAL_DB_PORT}/{database}', echo=True)
+        self.db_engine = create_engine(
+            f"mysql+pymysql://{CFG.LOCAL_DB_USER}:{CFG.LOCAL_DB_PASSWORD}@{CFG.LOCAL_DB_HOST}:{CFG.LOCAL_DB_PORT}/{database}",
+            echo=True,
+        )
         self.Session = sessionmaker(bind=self.db_engine)
 
     def create_knowledge_space(self, space: KnowledgeSpaceRequest):
@@ -38,7 +43,7 @@ class KnowledgeSpaceDao:
             desc=space.desc,
             owner=space.owner,
             gmt_created=datetime.now(),
-            gmt_modified=datetime.now()
+            gmt_modified=datetime.now(),
         )
         session.add(knowledge_space)
         session.commit()
@@ -49,28 +54,46 @@ class KnowledgeSpaceDao:
         session = self.Session()
         knowledge_spaces = session.query(KnowledgeSpaceEntity)
         if query.id is not None:
-            knowledge_spaces = knowledge_spaces.filter(KnowledgeSpaceEntity.id == query.id)
+            knowledge_spaces = knowledge_spaces.filter(
+                KnowledgeSpaceEntity.id == query.id
+            )
         if query.name is not None:
-            knowledge_spaces = knowledge_spaces.filter(KnowledgeSpaceEntity.name == query.name)
+            knowledge_spaces = knowledge_spaces.filter(
+                KnowledgeSpaceEntity.name == query.name
+            )
         if query.vector_type is not None:
-            knowledge_spaces = knowledge_spaces.filter(KnowledgeSpaceEntity.vector_type == query.vector_type)
+            knowledge_spaces = knowledge_spaces.filter(
+                KnowledgeSpaceEntity.vector_type == query.vector_type
+            )
         if query.desc is not None:
-            knowledge_spaces = knowledge_spaces.filter(KnowledgeSpaceEntity.desc == query.desc)
+            knowledge_spaces = knowledge_spaces.filter(
+                KnowledgeSpaceEntity.desc == query.desc
+            )
         if query.owner is not None:
-            knowledge_spaces = knowledge_spaces.filter(KnowledgeSpaceEntity.owner == query.owner)
+            knowledge_spaces = knowledge_spaces.filter(
+                KnowledgeSpaceEntity.owner == query.owner
+            )
         if query.gmt_created is not None:
-            knowledge_spaces = knowledge_spaces.filter(KnowledgeSpaceEntity.gmt_created == query.gmt_created)
+            knowledge_spaces = knowledge_spaces.filter(
+                KnowledgeSpaceEntity.gmt_created == query.gmt_created
+            )
         if query.gmt_modified is not None:
-            knowledge_spaces = knowledge_spaces.filter(KnowledgeSpaceEntity.gmt_modified == query.gmt_modified)
+            knowledge_spaces = knowledge_spaces.filter(
+                KnowledgeSpaceEntity.gmt_modified == query.gmt_modified
+            )
 
-        knowledge_spaces = knowledge_spaces.order_by(KnowledgeSpaceEntity.gmt_created.desc())
+        knowledge_spaces = knowledge_spaces.order_by(
+            KnowledgeSpaceEntity.gmt_created.desc()
+        )
         result = knowledge_spaces.all()
         return result
 
     def update_knowledge_space(self, space_id: int, space: KnowledgeSpaceEntity):
         cursor = self.conn.cursor()
         query = "UPDATE knowledge_space SET name = %s, vector_type = %s, desc = %s, owner = %s WHERE id = %s"
-        cursor.execute(query, (space.name, space.vector_type, space.desc, space.owner, space_id))
+        cursor.execute(
+            query, (space.name, space.vector_type, space.desc, space.owner, space_id)
+        )
         self.conn.commit()
         cursor.close()
 

pilot/openapi/knowledge/request/knowledge_request.py

@@ -30,12 +30,14 @@ class KnowledgeDocumentRequest(BaseModel):
     """doc_type: doc type"""
     doc_type: str
     """content: content"""
-    content: str
+    content: str = None
     """text_chunk_size: text_chunk_size"""
     # text_chunk_size: int
 
+
 class DocumentQueryRequest(BaseModel):
     """doc_name: doc path"""
+
     doc_name: str = None
     """doc_type: doc type"""
     doc_type: str = None
@@ -49,10 +51,13 @@ class DocumentQueryRequest(BaseModel):
 
 class DocumentSyncRequest(BaseModel):
     """doc_ids: doc ids"""
+
     doc_ids: List
 
+
 class ChunkQueryRequest(BaseModel):
     """id: id"""
+
     id: int = None
     """document_id: doc id"""
     document_id: int = None

pilot/prompts/example_base.py

@@ -4,6 +4,7 @@ from typing import Any, Callable, Dict, List, Mapping, Optional, Set, Union
 
 from pilot.common.schema import ExampleType
 
+
 class ExampleSelector(BaseModel, ABC):
     examples: List[List]
     use_example: bool = False

pilot/prompts/prompt_new.py

@@ -9,6 +9,7 @@ from pilot.out_parser.base import BaseOutputParser
 from pilot.common.schema import SeparatorStyle
 from pilot.prompts.example_base import ExampleSelector
 
+
 def jinja2_formatter(template: str, **kwargs: Any) -> str:
     """Format a template using jinja2."""
     try:

pilot/scene/base.py

@@ -1,11 +1,13 @@
 from enum import Enum
 
+
 class Scene:
     def __init__(self, code, describe, is_inner):
         self.code = code
         self.describe = describe
         self.is_inner = is_inner
 
+
 class ChatScene(Enum):
     ChatWithDbExecute = "chat_with_db_execute"
     ChatWithDbQA = "chat_with_db_qa"
@@ -24,4 +26,3 @@ class ChatScene(Enum):
     @staticmethod
     def is_valid_mode(mode):
         return any(mode == item.value for item in ChatScene)
-

pilot/scene/chat_dashboard/chat.py

@@ -12,7 +12,10 @@ from pilot.common.markdown_text import (
     generate_htm_table,
 )
 from pilot.scene.chat_db.auto_execute.prompt import prompt
-from pilot.scene.chat_dashboard.data_preparation.report_schma import ChartData, ReportData
+from pilot.scene.chat_dashboard.data_preparation.report_schma import (
+    ChartData,
+    ReportData,
+)
 
 CFG = Config()
 
@@ -22,9 +25,7 @@ class ChatDashboard(BaseChat):
     report_name: str
     """Number of results to return from the query"""
 
-    def __init__(
+    def __init__(self, chat_session_id, db_name, user_input, report_name):
-        self, chat_session_id, db_name, user_input, report_name
-    ):
         """ """
         super().__init__(
             chat_mode=ChatScene.ChatWithDbExecute,
@@ -68,7 +69,6 @@ class ChatDashboard(BaseChat):
                 # TODO 修复流程
                 print(str(e))
 
-
             chart_datas.append(chart_data)
 
         report_data.conv_uid = self.chat_session_id
@@ -77,5 +77,3 @@ class ChatDashboard(BaseChat):
         report_data.charts = chart_datas
 
         return report_data
-
-

pilot/scene/chat_dashboard/data_preparation/report_schma.py

@@ -16,7 +16,3 @@ class ReportData(BaseModel):
     template_name: str
     template_introduce: str
     charts: List[ChartData]
-
-
-
-

pilot/scene/chat_dashboard/out_parser.py

@@ -28,7 +28,11 @@ class ChatDashboardOutputParser(BaseOutputParser):
         response = json.loads(clean_str)
         chart_items = List[ChartItem]
         for item in response:
-            chart_items.append(ChartItem(item["sql"], item["title"], item["thoughts"], item["showcase"]))
+            chart_items.append(
+                ChartItem(
+                    item["sql"], item["title"], item["thoughts"], item["showcase"]
+                )
+            )
         return chart_items
 
     def parse_view_response(self, speak, data) -> str:

pilot/scene/chat_dashboard/prompt.py

@@ -24,12 +24,14 @@ give {dialect} data analysis SQL, analysis title, display method and analytical
 Ensure the response is correct json and can be parsed by Python json.loads
 """
 
-RESPONSE_FORMAT = [{
+RESPONSE_FORMAT = [
+    {
         "sql": "data analysis SQL",
         "title": "Data Analysis Title",
         "showcase": "What type of charts to show",
-    "thoughts": "Current thinking and value of data analysis"
+        "thoughts": "Current thinking and value of data analysis",
-}]
+    }
+]
 
 PROMPT_SEP = SeparatorStyle.SINGLE.value
 

pilot/scene/chat_db/auto_execute/chat.py

@@ -21,9 +21,7 @@ class ChatWithDbAutoExecute(BaseChat):
 
     """Number of results to return from the query"""
 
-    def __init__(
+    def __init__(self, chat_session_id, db_name, user_input):
-        self, chat_session_id, db_name, user_input
-    ):
         """ """
         super().__init__(
             chat_mode=ChatScene.ChatWithDbExecute,

pilot/scene/chat_db/professional_qa/chat.py

@@ -19,9 +19,7 @@ class ChatWithDbQA(BaseChat):
 
     """Number of results to return from the query"""
 
-    def __init__(
+    def __init__(self, chat_session_id, db_name, user_input):
-        self, chat_session_id, db_name, user_input
-    ):
         """ """
         super().__init__(
             chat_mode=ChatScene.ChatWithDbQA,
@@ -63,5 +61,3 @@ class ChatWithDbQA(BaseChat):
             "table_info": table_info,
         }
         return input_values
-
-

pilot/scene/chat_execution/prompt.py

@@ -34,7 +34,6 @@ RESPONSE_FORMAT = {
 }
 
 
-
 EXAMPLE_TYPE = ExampleType.ONE_SHOT
 PROMPT_SEP = SeparatorStyle.SINGLE.value
 ### Whether the model service is streaming output
@@ -47,8 +46,10 @@ prompt = PromptTemplate(
     template_define=PROMPT_SCENE_DEFINE,
     template=_DEFAULT_TEMPLATE,
     stream_out=PROMPT_NEED_STREAM_OUT,
-    output_parser=PluginChatOutputParser(sep=PROMPT_SEP, is_stream_out=PROMPT_NEED_STREAM_OUT),
+    output_parser=PluginChatOutputParser(
-    example=example
+        sep=PROMPT_SEP, is_stream_out=PROMPT_NEED_STREAM_OUT
+    ),
+    example=example,
 )
 
 CFG.prompt_templates.update({prompt.template_scene: prompt})

pilot/scene/chat_knowledge/custom/chat.py

@@ -27,9 +27,7 @@ class ChatNewKnowledge(BaseChat):
 
     """Number of results to return from the query"""
 
-    def __init__(
+    def __init__(self, chat_session_id, user_input, knowledge_name):
-        self,  chat_session_id, user_input, knowledge_name
-    ):
         """ """
         super().__init__(
             chat_mode=ChatScene.ChatNewKnowledge,
@@ -56,7 +54,6 @@ class ChatNewKnowledge(BaseChat):
         input_values = {"context": context, "question": self.current_user_input}
         return input_values
 
-
     @property
     def chat_type(self) -> str:
         return ChatScene.ChatNewKnowledge.value

pilot/scene/chat_knowledge/default/chat.py

@@ -59,8 +59,6 @@ class ChatDefaultKnowledge(BaseChat):
             )
         return input_values
 
-
-
     @property
     def chat_type(self) -> str:
         return ChatScene.ChatDefaultKnowledge.value

pilot/scene/chat_knowledge/inner_db_summary/chat.py

@@ -36,7 +36,6 @@ class InnerChatDBSummary(BaseChat):
         }
         return input_values
 
-
     @property
     def chat_type(self) -> str:
         return ChatScene.InnerChatDBSummary.value

pilot/scene/chat_knowledge/url/chat.py

@@ -61,7 +61,6 @@ class ChatUrlKnowledge(BaseChat):
         input_values = {"context": context, "question": self.current_user_input}
         return input_values
 
-
     @property
     def chat_type(self) -> str:
         return ChatScene.ChatUrlKnowledge.value

pilot/scene/chat_knowledge/v1/chat.py

@@ -59,8 +59,6 @@ class ChatKnowledge(BaseChat):
             )
         return input_values
 
-
-
     @property
     def chat_type(self) -> str:
         return ChatScene.ChatKnowledge.value

pilot/scene/message.py

@@ -85,7 +85,6 @@ class OnceConversation:
         self.messages.clear()
         self.session_id = None
 
-
     def get_user_message(self):
         for once in self.messages:
             if isinstance(once, HumanMessage):

pilot/server/__init__.py

@@ -13,5 +13,3 @@ if "pytest" in sys.argv or "pytest" in sys.modules or os.getenv("CI"):
 load_dotenv(verbose=True, override=True)
 
 del load_dotenv
-
-

pilot/server/llmserver.py

@@ -122,7 +122,7 @@ app.add_middleware(
     allow_origins=origins,
     allow_credentials=True,
     allow_methods=["*"],
-    allow_headers=["*"]
+    allow_headers=["*"],
 )
 
 

pilot/server/webserver.py

@@ -107,12 +107,16 @@ knowledge_qa_type_list = [
     add_knowledge_base_dialogue,
 ]
 
+
 def swagger_monkey_patch(*args, **kwargs):
     return get_swagger_ui_html(
-        *args, **kwargs,
+        *args,
-        swagger_js_url='https://cdn.bootcdn.net/ajax/libs/swagger-ui/4.10.3/swagger-ui-bundle.js',
+        **kwargs,
-        swagger_css_url='https://cdn.bootcdn.net/ajax/libs/swagger-ui/4.10.3/swagger-ui.css'
+        swagger_js_url="https://cdn.bootcdn.net/ajax/libs/swagger-ui/4.10.3/swagger-ui-bundle.js",
+        swagger_css_url="https://cdn.bootcdn.net/ajax/libs/swagger-ui/4.10.3/swagger-ui.css",
     )
+
+
 applications.get_swagger_ui_html = swagger_monkey_patch
 
 app = FastAPI()
@@ -360,14 +364,18 @@ def http_bot(
             response = chat.stream_call()
             for chunk in response.iter_lines(decode_unicode=False, delimiter=b"\0"):
                 if chunk:
-                    msg = chat.prompt_template.output_parser.parse_model_stream_resp_ex(chunk, chat.skip_echo_len)
+                    msg = chat.prompt_template.output_parser.parse_model_stream_resp_ex(
+                        chunk, chat.skip_echo_len
+                    )
                     state.messages[-1][-1] = msg
                     chat.current_message.add_ai_message(msg)
                     yield (state, state.to_gradio_chatbot()) + (enable_btn,) * 5
             chat.memory.append(chat.current_message)
         except Exception as e:
             print(traceback.format_exc())
-            state.messages[-1][-1] = f"""<span style=\"color:red\">ERROR!</span>{str(e)} """
+            state.messages[-1][
+                -1
+            ] = f"""<span style=\"color:red\">ERROR!</span>{str(e)} """
             yield (state, state.to_gradio_chatbot()) + (enable_btn,) * 5
 
 
@@ -693,8 +701,12 @@ def signal_handler(sig, frame):
 
 if __name__ == "__main__":
     parser = argparse.ArgumentParser()
-    parser.add_argument("--model_list_mode", type=str, default="once", choices=["once", "reload"])
+    parser.add_argument(
-    parser.add_argument('-new', '--new', action='store_true', help='enable new http mode')
+        "--model_list_mode", type=str, default="once", choices=["once", "reload"]
+    )
+    parser.add_argument(
+        "-new", "--new", action="store_true", help="enable new http mode"
+    )
 
     # old version server config
     parser.add_argument("--host", type=str, default="0.0.0.0")
@@ -702,27 +714,24 @@ if __name__ == "__main__":
     parser.add_argument("--concurrency-count", type=int, default=10)
     parser.add_argument("--share", default=False, action="store_true")
 
-
     # init server config
     args = parser.parse_args()
     server_init(args)
 
     if args.new:
         import uvicorn
+
         uvicorn.run(app, host="0.0.0.0", port=5000)
     else:
         ### Compatibility mode starts the old version server by default
         demo = build_webdemo()
         demo.queue(
-            concurrency_count=args.concurrency_count, status_update_rate=10, api_open=False
+            concurrency_count=args.concurrency_count,
+            status_update_rate=10,
+            api_open=False,
         ).launch(
             server_name=args.host,
             server_port=args.port,
             share=args.share,
             max_threads=200,
         )
-
-
-
-
-

pilot/source_embedding/knowledge_embedding.py

@@ -38,7 +38,9 @@ class KnowledgeEmbedding:
         return self.knowledge_embedding_client.read_batch()
 
     def init_knowledge_embedding(self):
-        return get_knowledge_embedding(self.file_type.upper(), self.file_path, self.vector_store_config)
+        return get_knowledge_embedding(
+            self.file_type.upper(), self.file_path, self.vector_store_config
+        )
 
     def similar_search(self, text, topk):
         vector_client = VectorStoreConnector(