Feat/note book

.env.template

@@ -329,3 +329,6 @@ DBGPT_LOG_LEVEL=INFO
 #**                     FINANCIAL CHAT Config                     **#
 #*******************************************************************#
 # FIN_REPORT_MODEL=/app/models/bge-large-zh
+
+## Turn off notebook display Python flow , which is enabled by default
+NOTE_BOOK_ENABLE=False

dbgpt/_private/config.py

@@ -336,6 +336,10 @@ def __init__(self) -> None:
         self.SCHEDULER_ENABLED = (
             os.getenv("SCHEDULER_ENABLED", "True").lower() == "true"
         )
+        self.NOTE_BOOK_ENABLE: bool = (
+            os.getenv("NOTE_BOOK_ENABLE", "True").lower() == "true"
+        )
+        self.NOTE_BOOK_ROOT: str = os.getenv("NOTE_BOOK_ROOT", os.path.expanduser("~"))
 
     @property
     def local_db_manager(self) -> "ConnectorManager":

dbgpt/agent/core/plan/awel/agent_operator.py

@@ -124,6 +124,12 @@ async def map(self, input_value: AgentGenerateContext) -> AgentGenerateContext:
             # Default single step transfer of information
             rely_messages=now_rely_messages,
             silent=input_value.silent,
+            memory=input_value.memory.structure_clone() if input_value.memory else None,
+            agent_context=input_value.agent_context,
+            llm_client=input_value.llm_client,
+            begin_agent=None,
+            last_speaker=self.agent,
+            already_started=True,
         )
 
 
@@ -291,6 +297,7 @@ async def get_agent(
         prompt_template = None
         if self.awel_agent.agent_prompt:
             from dbgpt.serve.prompt.api.endpoints import get_service
+
             prompt_service = get_service()
             prompt_template = prompt_service.get_template(
                 self.awel_agent.agent_prompt.code

dbgpt/agent/core/plan/awel/agent_operator_resource.py

@@ -12,6 +12,7 @@
     ResourceCategory,
     register_resource,
 )
+
 from ....resource.base import AgentResource, ResourceType
 from ....resource.manage import get_resource_manager
 from ....util.llm.llm import LLMConfig, LLMStrategyType
@@ -20,6 +21,7 @@
 
 def _agent_resource_prompt_values() -> List[OptionValue]:
     from dbgpt.serve.prompt.api.endpoints import get_service
+
     prompt_service = get_service()
     prompts = prompt_service.get_target_prompt()
     return [

dbgpt/agent/core/plan/awel/team_awel_layout.py

@@ -165,16 +165,15 @@ async def act(
             )
             last_message = final_generate_context.rely_messages[-1]
             last_message.rounds = last_message.rounds + 1
-            if not final_generate_context.last_speaker:
-                raise ValueError("Dont have last speaker agent!")
-            await final_generate_context.last_speaker.send(
-                last_message,
-                sender,
-                start_message_context.reviewer,
-                False,
-                is_retry_chat=is_retry_chat,
-                last_speaker_name=last_speaker_name,
-            )
+            if final_generate_context.last_speaker:
+                await final_generate_context.last_speaker.send(
+                    last_message,
+                    sender,
+                    start_message_context.reviewer,
+                    False,
+                    is_retry_chat=is_retry_chat,
+                    last_speaker_name=last_speaker_name,
+                )
 
             view_message = None
             if last_message.action_report:
@@ -269,16 +268,15 @@ async def act(
 
             last_message = final_generate_context.rely_messages[-1]
             last_message.rounds = last_message.rounds + 1
-            if not final_generate_context.last_speaker:
-                raise ValueError("Not have last speaker!")
-            await final_generate_context.last_speaker.send(
-                last_message,
-                sender,
-                start_message_context.reviewer,
-                False,
-                is_retry_chat=is_retry_chat,
-                last_speaker_name=last_speaker_name,
-            )
+            if final_generate_context.last_speaker:
+                await final_generate_context.last_speaker.send(
+                    last_message,
+                    sender,
+                    start_message_context.reviewer,
+                    False,
+                    is_retry_chat=is_retry_chat,
+                    last_speaker_name=last_speaker_name,
+                )
 
             view_message = None
             if last_message.action_report:

dbgpt/app/dbgpt_server.py

@@ -28,7 +28,7 @@
     STATIC_MESSAGE_IMG_PATH,
 )
 from dbgpt.serve.core import add_exception_handler
-from dbgpt.util.fastapi import create_app, replace_router
+from dbgpt.util.fastapi import create_app, register_event_handler, replace_router
 from dbgpt.util.i18n_utils import _, set_default_language
 from dbgpt.util.parameter_utils import _get_dict_from_obj
 from dbgpt.util.system_utils import get_system_info
@@ -43,7 +43,6 @@
 ROOT_PATH = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 sys.path.append(ROOT_PATH)
 
-
 CFG = Config()
 set_default_language(CFG.LANGUAGE)
 
@@ -61,7 +60,6 @@
 # Use custom router to support priority
 replace_router(app)
 
-
 system_app = SystemApp(app)
 
 

dbgpt/app/initialization/serve_initialization.py

@@ -123,10 +123,16 @@ def register_serve_apps(system_app: SystemApp, cfg: Config, webserver_port: int)
 
     # ################################ File Serve Register End ########################################
 
-    # ################################ Evaluate Serve Register Begin #######################################
+    # ################################ Evaluate Serve Register Begin ##################################
     from dbgpt.serve.evaluate.serve import Serve as EvaluateServe
 
     # Register serve Evaluate
     system_app.register(EvaluateServe)
+    # ################################ Evaluate Serve Register End ####################################
 
-    # ################################ Evaluate Serve Register End ########################################
+    # ################################ Libro Serve Register Begin #####################################
+    from dbgpt.serve.libro.serve import Serve as LibroServe
+
+    # Register serve libro
+    system_app.register(LibroServe)
+    # ################################ Libro Serve Register End #######################################

dbgpt/app/knowledge/api.py

@@ -2,10 +2,10 @@
 import os
 import shutil
 import tempfile
-from typing import List
 from pathlib import Path
+from typing import List
 
-from fastapi import APIRouter, Depends, File, Form, UploadFile, HTTPException
+from fastapi import APIRouter, Depends, File, Form, HTTPException, UploadFile
 
 from dbgpt._private.config import Config
 from dbgpt.app.knowledge.request.request import (
@@ -333,70 +333,72 @@ def document_delete(space_name: str, query_request: DocumentQueryRequest):
 
 @router.post("/knowledge/{space_name}/document/upload")
 async def document_upload(
-   space_name: str,
-   doc_name: str = Form(...),
-   doc_type: str = Form(...),
-   doc_file: UploadFile = File(...),
+    space_name: str,
+    doc_name: str = Form(...),
+    doc_type: str = Form(...),
+    doc_file: UploadFile = File(...),
 ):
-   print(f"/document/upload params: {space_name}")
-   try:
-       if doc_file:
-           # Sanitize inputs to prevent path traversal
-           safe_space_name = os.path.basename(space_name)
-           safe_filename = os.path.basename(doc_file.filename)
-
-           # Create absolute paths and verify they are within allowed directory
-           upload_dir = os.path.abspath(os.path.join(KNOWLEDGE_UPLOAD_ROOT_PATH, safe_space_name))
-           target_path = os.path.abspath(os.path.join(upload_dir, safe_filename))
-
-           if not os.path.abspath(KNOWLEDGE_UPLOAD_ROOT_PATH) in target_path:
-               raise HTTPException(status_code=400, detail="Invalid path detected")
-
-           if not os.path.exists(upload_dir):
-               os.makedirs(upload_dir)
-
-           # Create temp file
-           tmp_fd, tmp_path = tempfile.mkstemp(dir=upload_dir)
-
-           try:
-               with os.fdopen(tmp_fd, "wb") as tmp:
-                   tmp.write(await doc_file.read())
-
-               shutil.move(tmp_path, target_path)
-
-               request = KnowledgeDocumentRequest()
-               request.doc_name = doc_name 
-               request.doc_type = doc_type
-               request.content = target_path
-
-               space_res = knowledge_space_service.get_knowledge_space(
-                   KnowledgeSpaceRequest(name=safe_space_name)
-               )
-               if len(space_res) == 0:
-                   # create default space
-                   if "default" != safe_space_name:
-                       raise Exception(f"you have not create your knowledge space.")
-                   knowledge_space_service.create_knowledge_space(
-                       KnowledgeSpaceRequest(
-                           name=safe_space_name,
-                           desc="first db-gpt rag application",
-                           owner="dbgpt",
-                       )
-                   )
-               return Result.succ(
-                   knowledge_space_service.create_knowledge_document(
-                       space=safe_space_name, request=request
-                   )
-               )
-           except Exception as e:
-               # Clean up temp file if anything goes wrong
-               if os.path.exists(tmp_path):
-                   os.unlink(tmp_path)
-               raise e
-
-       return Result.failed(code="E000X", msg=f"doc_file is None")
-   except Exception as e:
-       return Result.failed(code="E000X", msg=f"document add error {e}")
+    print(f"/document/upload params: {space_name}")
+    try:
+        if doc_file:
+            # Sanitize inputs to prevent path traversal
+            safe_space_name = os.path.basename(space_name)
+            safe_filename = os.path.basename(doc_file.filename)
+
+            # Create absolute paths and verify they are within allowed directory
+            upload_dir = os.path.abspath(
+                os.path.join(KNOWLEDGE_UPLOAD_ROOT_PATH, safe_space_name)
+            )
+            target_path = os.path.abspath(os.path.join(upload_dir, safe_filename))
+
+            if not os.path.abspath(KNOWLEDGE_UPLOAD_ROOT_PATH) in target_path:
+                raise HTTPException(status_code=400, detail="Invalid path detected")
+
+            if not os.path.exists(upload_dir):
+                os.makedirs(upload_dir)
+
+            # Create temp file
+            tmp_fd, tmp_path = tempfile.mkstemp(dir=upload_dir)
+
+            try:
+                with os.fdopen(tmp_fd, "wb") as tmp:
+                    tmp.write(await doc_file.read())
+
+                shutil.move(tmp_path, target_path)
+
+                request = KnowledgeDocumentRequest()
+                request.doc_name = doc_name
+                request.doc_type = doc_type
+                request.content = target_path
+
+                space_res = knowledge_space_service.get_knowledge_space(
+                    KnowledgeSpaceRequest(name=safe_space_name)
+                )
+                if len(space_res) == 0:
+                    # create default space
+                    if "default" != safe_space_name:
+                        raise Exception(f"you have not create your knowledge space.")
+                    knowledge_space_service.create_knowledge_space(
+                        KnowledgeSpaceRequest(
+                            name=safe_space_name,
+                            desc="first db-gpt rag application",
+                            owner="dbgpt",
+                        )
+                    )
+                return Result.succ(
+                    knowledge_space_service.create_knowledge_document(
+                        space=safe_space_name, request=request
+                    )
+                )
+            except Exception as e:
+                # Clean up temp file if anything goes wrong
+                if os.path.exists(tmp_path):
+                    os.unlink(tmp_path)
+                raise e
+
+        return Result.failed(code="E000X", msg=f"doc_file is None")
+    except Exception as e:
+        return Result.failed(code="E000X", msg=f"document add error {e}")
 
 
 @router.post("/knowledge/{space_name}/document/sync")

dbgpt/app/scene/chat_dashboard/data_preparation/report_schma.py

@@ -5,7 +5,7 @@
 
 class ValueItem(BaseModel):
     name: str
-    type: str = None
+    type: Optional[str] = None
     value: float
 
     def dict(self, *args, **kwargs):

dbgpt/app/static/web/404.html

@@ -1 +1 @@
-<!DOCTYPE html><html lang="en"><head><meta charSet="utf-8"/><meta name="viewport" content="width=device-width"/><meta name="next-head-count" content="2"/><link rel="icon" href="/favicon.ico"/><meta name="description" content="Revolutionizing Database Interactions with Private LLM Technology"/><meta property="og:description" content="eosphoros-ai"/><meta property="og:title" content="DB-GPT"/><link rel="preload" href="/_next/static/css/56abd552837c60f9.css" as="style"/><link rel="stylesheet" href="/_next/static/css/56abd552837c60f9.css" data-n-g=""/><noscript data-n-css=""></noscript><script defer="" nomodule="" src="/_next/static/chunks/polyfills-78c92fac7aa8fdd8.js"></script><script src="/_next/static/chunks/webpack-3257fddca97289f9.js" defer=""></script><script src="/_next/static/chunks/framework-fb9c0d50ace2b075.js" defer=""></script><script src="/_next/static/chunks/main-fd0d7e13da40ad83.js" defer=""></script><script src="/_next/static/chunks/pages/_app-e3c58054813ebb2b.js" defer=""></script><script src="/_next/static/chunks/pages/_error-4fa9991a75118e6f.js" defer=""></script><script src="/_next/static/ujdCH5HCMF0OXSAWRqVTP/_buildManifest.js" defer=""></script><script src="/_next/static/ujdCH5HCMF0OXSAWRqVTP/_ssgManifest.js" defer=""></script><link rel="stylesheet" href="/_next/static/css/antd-output/antd.min.7d5365b5.css"/></head><body><div id="__next"><div></div></div><script id="__NEXT_DATA__" type="application/json">{"props":{"pageProps":{"statusCode":404}},"page":"/_error","query":{},"buildId":"ujdCH5HCMF0OXSAWRqVTP","nextExport":true,"isFallback":false,"gip":true,"scriptLoader":[]}</script></body></html>
+<!DOCTYPE html><html lang="en"><head><meta charSet="utf-8"/><meta name="viewport" content="width=device-width"/><meta name="next-head-count" content="2"/><link rel="icon" href="/favicon.ico"/><meta name="description" content="Revolutionizing Database Interactions with Private LLM Technology"/><meta property="og:description" content="eosphoros-ai"/><meta property="og:title" content="DB-GPT"/><link rel="preload" href="/_next/static/css/56abd552837c60f9.css" as="style"/><link rel="stylesheet" href="/_next/static/css/56abd552837c60f9.css" data-n-g=""/><noscript data-n-css=""></noscript><script defer="" nomodule="" src="/_next/static/chunks/polyfills-78c92fac7aa8fdd8.js"></script><script src="/_next/static/chunks/webpack-f9489bc48c5d1540.js" defer=""></script><script src="/_next/static/chunks/framework-8b06d32cbb857e0e.js" defer=""></script><script src="/_next/static/chunks/main-6c4c7f5b8c9b1320.js" defer=""></script><script src="/_next/static/chunks/pages/_app-7c76237d5662964a.js" defer=""></script><script src="/_next/static/chunks/pages/_error-8095ba9e1bf12f30.js" defer=""></script><script src="/_next/static/oyFmgKTpzOHc-wyB30CA1/_buildManifest.js" defer=""></script><script src="/_next/static/oyFmgKTpzOHc-wyB30CA1/_ssgManifest.js" defer=""></script><link rel="stylesheet" href="/_next/static/css/antd-output/antd.min.7d5365b5.css"/></head><body><div id="__next"><div></div></div><script id="__NEXT_DATA__" type="application/json">{"props":{"pageProps":{"statusCode":404}},"page":"/_error","query":{},"buildId":"oyFmgKTpzOHc-wyB30CA1","nextExport":true,"isFallback":false,"gip":true,"scriptLoader":[]}</script></body></html>

dbgpt/app/static/web/404/index.html

@@ -1 +1 @@
-<!DOCTYPE html><html lang="en"><head><meta charSet="utf-8"/><meta name="viewport" content="width=device-width"/><meta name="next-head-count" content="2"/><link rel="icon" href="/favicon.ico"/><meta name="description" content="Revolutionizing Database Interactions with Private LLM Technology"/><meta property="og:description" content="eosphoros-ai"/><meta property="og:title" content="DB-GPT"/><link rel="preload" href="/_next/static/css/56abd552837c60f9.css" as="style"/><link rel="stylesheet" href="/_next/static/css/56abd552837c60f9.css" data-n-g=""/><noscript data-n-css=""></noscript><script defer="" nomodule="" src="/_next/static/chunks/polyfills-78c92fac7aa8fdd8.js"></script><script src="/_next/static/chunks/webpack-3257fddca97289f9.js" defer=""></script><script src="/_next/static/chunks/framework-fb9c0d50ace2b075.js" defer=""></script><script src="/_next/static/chunks/main-fd0d7e13da40ad83.js" defer=""></script><script src="/_next/static/chunks/pages/_app-e3c58054813ebb2b.js" defer=""></script><script src="/_next/static/chunks/pages/_error-4fa9991a75118e6f.js" defer=""></script><script src="/_next/static/ujdCH5HCMF0OXSAWRqVTP/_buildManifest.js" defer=""></script><script src="/_next/static/ujdCH5HCMF0OXSAWRqVTP/_ssgManifest.js" defer=""></script><link rel="stylesheet" href="/_next/static/css/antd-output/antd.min.7d5365b5.css"/></head><body><div id="__next"><div></div></div><script id="__NEXT_DATA__" type="application/json">{"props":{"pageProps":{"statusCode":404}},"page":"/_error","query":{},"buildId":"ujdCH5HCMF0OXSAWRqVTP","nextExport":true,"isFallback":false,"gip":true,"scriptLoader":[]}</script></body></html>
+<!DOCTYPE html><html lang="en"><head><meta charSet="utf-8"/><meta name="viewport" content="width=device-width"/><meta name="next-head-count" content="2"/><link rel="icon" href="/favicon.ico"/><meta name="description" content="Revolutionizing Database Interactions with Private LLM Technology"/><meta property="og:description" content="eosphoros-ai"/><meta property="og:title" content="DB-GPT"/><link rel="preload" href="/_next/static/css/56abd552837c60f9.css" as="style"/><link rel="stylesheet" href="/_next/static/css/56abd552837c60f9.css" data-n-g=""/><noscript data-n-css=""></noscript><script defer="" nomodule="" src="/_next/static/chunks/polyfills-78c92fac7aa8fdd8.js"></script><script src="/_next/static/chunks/webpack-f9489bc48c5d1540.js" defer=""></script><script src="/_next/static/chunks/framework-8b06d32cbb857e0e.js" defer=""></script><script src="/_next/static/chunks/main-6c4c7f5b8c9b1320.js" defer=""></script><script src="/_next/static/chunks/pages/_app-7c76237d5662964a.js" defer=""></script><script src="/_next/static/chunks/pages/_error-8095ba9e1bf12f30.js" defer=""></script><script src="/_next/static/oyFmgKTpzOHc-wyB30CA1/_buildManifest.js" defer=""></script><script src="/_next/static/oyFmgKTpzOHc-wyB30CA1/_ssgManifest.js" defer=""></script><link rel="stylesheet" href="/_next/static/css/antd-output/antd.min.7d5365b5.css"/></head><body><div id="__next"><div></div></div><script id="__NEXT_DATA__" type="application/json">{"props":{"pageProps":{"statusCode":404}},"page":"/_error","query":{},"buildId":"oyFmgKTpzOHc-wyB30CA1","nextExport":true,"isFallback":false,"gip":true,"scriptLoader":[]}</script></body></html>