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fix(prompt): add missing response_schema field in to_request method

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WangzJi 2025-07-16 21:25:53 +08:00
commit 78bcc41b4a
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93 changed files with 153 additions and 134 deletions
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2
packages/dbgpt-app/src/dbgpt_app/knowledge/api.py
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@ -563,7 +563,7 @@ async def document_summary(request: DocumentSummaryRequest):
if not chat.prompt_template.stream_out: if not chat.prompt_template.stream_out:
return StreamingResponse( return StreamingResponse(
no_stream_generator(chat), no_stream_generator(chat, request.model_name),
headers=headers, headers=headers,
media_type="text/event-stream", media_type="text/event-stream",
) )

55
packages/dbgpt-app/src/dbgpt_app/openapi/api_v1/api_v1.py
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@ -17,14 +17,14 @@ from dbgpt.configs import TAG_KEY_KNOWLEDGE_CHAT_DOMAIN_TYPE
from dbgpt.core import ModelOutput from dbgpt.core import ModelOutput
from dbgpt.core.awel import BaseOperator, CommonLLMHttpRequestBody from dbgpt.core.awel import BaseOperator, CommonLLMHttpRequestBody
from dbgpt.core.awel.dag.dag_manager import DAGManager from dbgpt.core.awel.dag.dag_manager import DAGManager
from dbgpt.core.awel.util.chat_util import safe_chat_stream_with_dag_task from dbgpt.core.awel.util.chat_util import (
_v1_create_completion_response,
safe_chat_stream_with_dag_task,
)
from dbgpt.core.interface.file import FileStorageClient from dbgpt.core.interface.file import FileStorageClient
from dbgpt.core.schema.api import ( from dbgpt.core.schema.api import (
ChatCompletionResponse,
ChatCompletionResponseChoice,
ChatCompletionResponseStreamChoice, ChatCompletionResponseStreamChoice,
ChatCompletionStreamResponse, ChatCompletionStreamResponse,
ChatMessage,
DeltaMessage, DeltaMessage,
UsageInfo, UsageInfo,
) )
@ -545,10 +545,6 @@ async def chat_completions(
model=dialogue.model_name, model=dialogue.model_name,
messages=dialogue.user_input, messages=dialogue.user_input,
stream=True, stream=True,
# context=flow_ctx,
# temperature=
# max_new_tokens=
# enable_vis=
conv_uid=dialogue.conv_uid, conv_uid=dialogue.conv_uid,
span_id=root_tracer.get_current_span_id(), span_id=root_tracer.get_current_span_id(),
chat_mode=dialogue.chat_mode, chat_mode=dialogue.chat_mode,
@ -577,7 +573,7 @@ async def chat_completions(
if not chat.prompt_template.stream_out: if not chat.prompt_template.stream_out:
return StreamingResponse( return StreamingResponse(
no_stream_generator(chat), no_stream_generator(chat, dialogue.model_name, dialogue.conv_uid),
headers=headers, headers=headers,
media_type="text/event-stream", media_type="text/event-stream",
) )
@ -699,10 +695,11 @@ async def flow_stream_generator(func, incremental: bool, model_name: str):
yield "data: [DONE]\n\n" yield "data: [DONE]\n\n"
async def no_stream_generator(chat): async def no_stream_generator(chat, model_name: str, conv_uid: Optional[str] = None):
with root_tracer.start_span("no_stream_generator"): with root_tracer.start_span("no_stream_generator"):
msg = await chat.nostream_call() msg = await chat.nostream_call()
yield f"data: {msg}\n\n" stream_id = conv_uid or f"chatcmpl-{str(uuid.uuid1())}"
yield _v1_create_completion_response(msg, None, model_name, stream_id)
async def stream_generator( async def stream_generator(
@ -711,7 +708,7 @@ async def stream_generator(
model_name: str, model_name: str,
text_output: bool = True, text_output: bool = True,
openai_format: bool = False, openai_format: bool = False,
conv_uid: str = None, conv_uid: Optional[str] = None,
): ):
"""Generate streaming responses """Generate streaming responses
@ -766,32 +763,20 @@ async def stream_generator(
) )
yield f"data: {_content}\n\n" yield f"data: {_content}\n\n"
else: else:
choice_data = ChatCompletionResponseChoice(
index=0,
message=ChatMessage(
role="assistant",
content=output.text,
reasoning_content=output.thinking_text,
),
)
if output.usage: if output.usage:
usage = UsageInfo(**output.usage) usage = UsageInfo(**output.usage)
else: else:
usage = UsageInfo() usage = UsageInfo()
_content = ChatCompletionResponse( _content = _v1_create_completion_response(
id=stream_id, text, think_text, model_name, stream_id, usage
choices=[choice_data],
model=model_name,
usage=usage,
) )
_content = json.dumps( yield _content
chunk.dict(exclude_unset=True), ensure_ascii=False
)
yield f"data: {_content}\n\n"
else: else:
msg = chunk.replace("\ufffd", "") msg = chunk.replace("\ufffd", "")
msg = msg.replace("\n", "\\n") _content = _v1_create_completion_response(
yield f"data:{msg}\n\n" msg, None, model_name, stream_id
)
yield _content
await asyncio.sleep(0.02) await asyncio.sleep(0.02)
if incremental: if incremental:
yield "data: [DONE]\n\n" yield "data: [DONE]\n\n"
@ -866,7 +851,11 @@ async def chat_with_domain_flow(dialogue: ConversationVo, domain_type: str):
if text: if text:
text = text.replace("\n", "\\n") text = text.replace("\n", "\\n")
if output.error_code != 0: if output.error_code != 0:
yield f"data:[SERVER_ERROR]{text}\n\n" yield _v1_create_completion_response(
f"[SERVER_ERROR]{text}", None, dialogue.model_name, dialogue.conv_uid
)
break break
else: else:
yield f"data:{text}\n\n" yield _v1_create_completion_response(
text, None, dialogue.model_name, dialogue.conv_uid
)

4
packages/dbgpt-app/src/dbgpt_app/scene/base_chat.py
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@ -435,8 +435,6 @@ class BaseChat(ABC):
text_msg = model_output.text if model_output.has_text else "" text_msg = model_output.text if model_output.has_text else ""
view_msg = self.stream_plugin_call(text_msg) view_msg = self.stream_plugin_call(text_msg)
view_msg = model_output.gen_text_with_thinking(new_text=view_msg) view_msg = model_output.gen_text_with_thinking(new_text=view_msg)
view_msg = view_msg.replace("\n", "\\n")
if text_output: if text_output:
full_text = view_msg full_text = view_msg
# Return the incremental text # Return the incremental text
@ -603,7 +601,7 @@ class BaseChat(ABC):
view_message = parsed_output.gen_text_with_thinking( view_message = parsed_output.gen_text_with_thinking(
new_text=view_message new_text=view_message
) )
return ai_response_text, view_message.replace("\n", "\\n") return ai_response_text, view_message
except BaseAppException as e: except BaseAppException as e:
raise ContextAppException(e.message, e.view, model_output) from e raise ContextAppException(e.message, e.view, model_output) from e

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packages/dbgpt-app/src/dbgpt_app/static/web/404.html
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@ -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/c09ab2c056586552.css" as="style"/><link rel="stylesheet" href="/_next/static/css/c09ab2c056586552.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-1ecaa69ebaff403b.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-c55d3a6bbd1fd609.js" defer=""></script><script src="/_next/static/chunks/pages/_error-8095ba9e1bf12f30.js" defer=""></script><script src="/_next/static/AFpptyKx8zPgsLS_So3BR/_buildManifest.js" defer=""></script><script src="/_next/static/AFpptyKx8zPgsLS_So3BR/_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":"AFpptyKx8zPgsLS_So3BR","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/c09ab2c056586552.css" as="style"/><link rel="stylesheet" href="/_next/static/css/c09ab2c056586552.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-0026ba7f9cd5bba9.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-b5031b53afa0df7e.js" defer=""></script><script src="/_next/static/chunks/pages/_error-8095ba9e1bf12f30.js" defer=""></script><script src="/_next/static/gv0k09BrvWkKGZ4Em_Hmf/_buildManifest.js" defer=""></script><script src="/_next/static/gv0k09BrvWkKGZ4Em_Hmf/_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":"gv0k09BrvWkKGZ4Em_Hmf","nextExport":true,"isFallback":false,"gip":true,"scriptLoader":[]}</script></body></html>

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packages/dbgpt-app/src/dbgpt_app/static/web/404/index.html
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@ -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/c09ab2c056586552.css" as="style"/><link rel="stylesheet" href="/_next/static/css/c09ab2c056586552.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-1ecaa69ebaff403b.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-c55d3a6bbd1fd609.js" defer=""></script><script src="/_next/static/chunks/pages/_error-8095ba9e1bf12f30.js" defer=""></script><script src="/_next/static/AFpptyKx8zPgsLS_So3BR/_buildManifest.js" defer=""></script><script src="/_next/static/AFpptyKx8zPgsLS_So3BR/_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":"AFpptyKx8zPgsLS_So3BR","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/c09ab2c056586552.css" as="style"/><link rel="stylesheet" href="/_next/static/css/c09ab2c056586552.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-0026ba7f9cd5bba9.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-b5031b53afa0df7e.js" defer=""></script><script src="/_next/static/chunks/pages/_error-8095ba9e1bf12f30.js" defer=""></script><script src="/_next/static/gv0k09BrvWkKGZ4Em_Hmf/_buildManifest.js" defer=""></script><script src="/_next/static/gv0k09BrvWkKGZ4Em_Hmf/_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":"gv0k09BrvWkKGZ4Em_Hmf","nextExport":true,"isFallback":false,"gip":true,"scriptLoader":[]}</script></body></html>

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packages/dbgpt-app/src/dbgpt_app/static/web/_next/static/AFpptyKx8zPgsLS_So3BR/_ssgManifest.js → packages/dbgpt-app/src/dbgpt_app/static/web/_next/static/gv0k09BrvWkKGZ4Em_Hmf/_ssgManifest.js
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packages/dbgpt-app/src/dbgpt_app/static/web/construct/app/extra/components/NativeApp/index.html
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packages/dbgpt-app/src/dbgpt_app/static/web/construct/app/extra/components/RecommendQuestions/index.html
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packages/dbgpt-app/src/dbgpt_app/static/web/construct/app/extra/components/auto-plan/DetailsCard/index.html
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packages/dbgpt-app/src/dbgpt_app/static/web/mobile/chat/components/ChatDialog/index.html
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packages/dbgpt-app/src/dbgpt_app/static/web/mobile/chat/components/Content/index.html
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packages/dbgpt-app/src/dbgpt_app/static/web/mobile/chat/components/InputContainer/index.html
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packages/dbgpt-app/src/dbgpt_app/static/web/mobile/chat/components/ModelSelector/index.html
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<!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/c09ab2c056586552.css" as="style"/><link rel="stylesheet" href="/_next/static/css/c09ab2c056586552.css" data-n-g=""/><link rel="preload" href="/_next/static/css/9b601b4de5d78ac2.css" as="style"/><link rel="stylesheet" href="/_next/static/css/9b601b4de5d78ac2.css" data-n-p=""/><noscript data-n-css=""></noscript><script defer="" nomodule="" src="/_next/static/chunks/polyfills-78c92fac7aa8fdd8.js"></script><script src="/_next/static/chunks/webpack-1ecaa69ebaff403b.js" defer=""></script><script src="/_next/static/chunks/framework-8b06d32cbb857e0e.js" 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packages/dbgpt-app/src/dbgpt_app/static/web/mobile/chat/components/OptionIcon/index.html
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<!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/c09ab2c056586552.css" as="style"/><link rel="stylesheet" href="/_next/static/css/c09ab2c056586552.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-1ecaa69ebaff403b.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-c55d3a6bbd1fd609.js" defer=""></script><script src="/_next/static/chunks/pages/mobile/chat/components/OptionIcon-9b7b2b198d5ee1f1.js" defer=""></script><script src="/_next/static/AFpptyKx8zPgsLS_So3BR/_buildManifest.js" defer=""></script><script src="/_next/static/AFpptyKx8zPgsLS_So3BR/_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":{}},"page":"/mobile/chat/components/OptionIcon","query":{},"buildId":"AFpptyKx8zPgsLS_So3BR","nextExport":true,"autoExport":true,"isFallback":false,"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/c09ab2c056586552.css" as="style"/><link rel="stylesheet" href="/_next/static/css/c09ab2c056586552.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-0026ba7f9cd5bba9.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-b5031b53afa0df7e.js" defer=""></script><script src="/_next/static/chunks/pages/mobile/chat/components/OptionIcon-9b7b2b198d5ee1f1.js" defer=""></script><script src="/_next/static/gv0k09BrvWkKGZ4Em_Hmf/_buildManifest.js" defer=""></script><script src="/_next/static/gv0k09BrvWkKGZ4Em_Hmf/_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":{}},"page":"/mobile/chat/components/OptionIcon","query":{},"buildId":"gv0k09BrvWkKGZ4Em_Hmf","nextExport":true,"autoExport":true,"isFallback":false,"scriptLoader":[]}</script></body></html>

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packages/dbgpt-app/src/dbgpt_app/static/web/mobile/chat/components/Resource/index.html
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packages/dbgpt-app/src/dbgpt_app/static/web/mobile/chat/components/Thermometer/index.html
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<!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/c09ab2c056586552.css" as="style"/><link rel="stylesheet" href="/_next/static/css/c09ab2c056586552.css" data-n-g=""/><link rel="preload" href="/_next/static/css/9b601b4de5d78ac2.css" as="style"/><link rel="stylesheet" href="/_next/static/css/9b601b4de5d78ac2.css" data-n-p=""/><noscript data-n-css=""></noscript><script defer="" nomodule="" src="/_next/static/chunks/polyfills-78c92fac7aa8fdd8.js"></script><script src="/_next/static/chunks/webpack-1ecaa69ebaff403b.js" defer=""></script><script src="/_next/static/chunks/framework-8b06d32cbb857e0e.js" 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packages/dbgpt-app/src/dbgpt_app/static/web/mobile/chat/index.html
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<!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/c09ab2c056586552.css" as="style"/><link rel="stylesheet" href="/_next/static/css/c09ab2c056586552.css" data-n-g=""/><link rel="preload" href="/_next/static/css/9b601b4de5d78ac2.css" as="style"/><link rel="stylesheet" href="/_next/static/css/9b601b4de5d78ac2.css" data-n-p=""/><noscript data-n-css=""></noscript><script defer="" nomodule="" src="/_next/static/chunks/polyfills-78c92fac7aa8fdd8.js"></script><script src="/_next/static/chunks/webpack-1ecaa69ebaff403b.js" defer=""></script><script src="/_next/static/chunks/framework-8b06d32cbb857e0e.js" 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1
packages/dbgpt-core/src/dbgpt/agent/util/llm/llm_client.py
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@ -217,7 +217,6 @@ class AIWrapper:
if not model_output: if not model_output:
raise ValueError("LLM generate stream is null!") raise ValueError("LLM generate stream is null!")
parsed_output = model_output.gen_text_with_thinking() parsed_output = model_output.gen_text_with_thinking()
parsed_output = parsed_output.strip().replace("\\n", "\n")
if verbose: if verbose:
print("\n", "-" * 80, flush=True, sep="") print("\n", "-" * 80, flush=True, sep="")

33
packages/dbgpt-core/src/dbgpt/core/awel/util/chat_util.py
View File

@ -5,7 +5,13 @@ import traceback
from typing import Any, AsyncIterator, Dict, Optional from typing import Any, AsyncIterator, Dict, Optional
from ...interface.llm import ModelInferenceMetrics, ModelOutput from ...interface.llm import ModelInferenceMetrics, ModelOutput
from ...schema.api import ChatCompletionResponseStreamChoice from ...schema.api import (
ChatCompletionResponse,
ChatCompletionResponseChoice,
ChatCompletionResponseStreamChoice,
ChatMessage,
UsageInfo,
)
from ..operators.base import BaseOperator from ..operators.base import BaseOperator
from ..trigger.http_trigger import CommonLLMHttpResponseBody from ..trigger.http_trigger import CommonLLMHttpResponseBody
@ -379,3 +385,28 @@ def parse_sse_data(output: str) -> Optional[str]:
return output return output
else: else:
return None return None
def _v1_create_completion_response(
text: str,
think_text: Optional[str],
model_name: str,
stream_id: str,
usage: Optional[UsageInfo] = None,
):
choice_data = ChatCompletionResponseChoice(
index=0,
message=ChatMessage(
role="assistant",
content=text or "",
reasoning_content=think_text,
),
)
_content = ChatCompletionResponse(
id=stream_id,
choices=[choice_data],
model=model_name,
usage=usage or UsageInfo(),
)
_content = json.dumps(_content.model_dump(exclude_unset=True), ensure_ascii=False)
return f"data: {_content}\n\n"

12
packages/dbgpt-serve/src/dbgpt_serve/flow/service/service.py
View File

@ -19,6 +19,7 @@ from dbgpt.core.awel.flow.flow_factory import (
) )
from dbgpt.core.awel.trigger.http_trigger import CommonLLMHttpTrigger from dbgpt.core.awel.trigger.http_trigger import CommonLLMHttpTrigger
from dbgpt.core.awel.util.chat_util import ( from dbgpt.core.awel.util.chat_util import (
_v1_create_completion_response,
is_chat_flow_type, is_chat_flow_type,
safe_chat_stream_with_dag_task, safe_chat_stream_with_dag_task,
safe_chat_with_dag_task, safe_chat_with_dag_task,
@ -448,10 +449,17 @@ class Service(BaseService[ServeEntity, ServeRequest, ServerResponse]):
if text: if text:
text = text.replace("\n", "\\n") text = text.replace("\n", "\\n")
if output.error_code != 0: if output.error_code != 0:
yield f"data:[SERVER_ERROR]{text}\n\n" yield _v1_create_completion_response(
f"[SERVER_ERROR]{text}",
None,
model_name=request.model,
stream_id=request.conv_uid,
)
break break
else: else:
yield f"data:{text}\n\n" yield _v1_create_completion_response(
text, None, model_name=request.model, stream_id=request.conv_uid
)
async def chat_stream_openai( async def chat_stream_openai(
self, flow_uid: str, request: CommonLLMHttpRequestBody self, flow_uid: str, request: CommonLLMHttpRequestBody

5
web/components/chat/chat-content/index.tsx
View File

@ -58,10 +58,7 @@ const pluginViewStatusMapper: Record<DBGPTView['status'], { bgClass: string; ico
}; };
function formatMarkdownVal(val: string) { function formatMarkdownVal(val: string) {
return val return val.replace(/<table(\w*=[^>]+)>/gi, '<table $1>').replace(/<tr(\w*=[^>]+)>/gi, '<tr $1>');
.replaceAll('\\n', '\n')
.replace(/<table(\w*=[^>]+)>/gi, '<table $1>')
.replace(/<tr(\w*=[^>]+)>/gi, '<tr $1>');
} }
function ChatContent({ children, content, isChartChat, onLinkClick }: PropsWithChildren<Props>) { function ChatContent({ children, content, isChartChat, onLinkClick }: PropsWithChildren<Props>) {

3
web/hooks/use-chat.ts
View File

@ -90,7 +90,8 @@ const useChat = ({ queryAgentURL = '/api/v1/chat/completions', app_code }: Props
if (scene === 'chat_agent') { if (scene === 'chat_agent') {
message = JSON.parse(message).vis; message = JSON.parse(message).vis;
} else { } else {
message = JSON.parse(message); data = JSON.parse(event.data);
message = data.choices?.[0]?.message?.content;
} }
} catch { } catch {
message.replaceAll('\\n', '\n'); message.replaceAll('\\n', '\n');

10
web/new-components/chat/ChatContentContainer.tsx
View File

@ -79,7 +79,8 @@ const ChatContentContainer = ({ className }: { className?: string }, ref: React.
currentScrollRef.removeEventListener('scroll', handleScroll); currentScrollRef.removeEventListener('scroll', handleScroll);
} }
}; };
}, [handleScroll]); const scrollToBottomSmooth = useCallback((forceScroll = false) => { }, [handleScroll]);
const scrollToBottomSmooth = useCallback((forceScroll = false) => {
if (!scrollRef.current) return; if (!scrollRef.current) return;
// For force scroll (new messages), bypass allowAutoScroll check // For force scroll (new messages), bypass allowAutoScroll check
@ -117,7 +118,7 @@ const ChatContentContainer = ({ className }: { className?: string }, ref: React.
const lastMessage = useMemo(() => { const lastMessage = useMemo(() => {
const last = history[history.length - 1]; const last = history[history.length - 1];
return last ? { context: last.context, thinking: last.thinking } : null; return last ? { context: last.context, thinking: last.thinking } : null;
}, [history]); // Track previous history length to detect new messages }, [history]); // Track previous history length to detect new messages
const prevHistoryLengthRef = useRef(history.length); const prevHistoryLengthRef = useRef(history.length);
useEffect(() => { useEffect(() => {
@ -149,7 +150,8 @@ const ChatContentContainer = ({ className }: { className?: string }, ref: React.
cancelAnimationFrame(animationFrameRef.current); cancelAnimationFrame(animationFrameRef.current);
} }
}; };
}, []); const scrollToTop = useCallback(() => { }, []);
const scrollToTop = useCallback(() => {
if (scrollRef.current) { if (scrollRef.current) {
scrollRef.current.scrollTo({ scrollRef.current.scrollTo({
top: 0, top: 0,
@ -200,4 +202,4 @@ const ChatContentContainer = ({ className }: { className?: string }, ref: React.
); );
}; };
export default forwardRef(ChatContentContainer); export default forwardRef(ChatContentContainer);

5
web/new-components/chat/content/ChatContent.tsx
View File

@ -69,10 +69,7 @@ const pluginViewStatusMapper: Record<DBGPTView['status'], { bgClass: string; ico
}; };
const formatMarkdownVal = (val: string) => { const formatMarkdownVal = (val: string) => {
return val return val.replace(/<table(\w*=[^>]+)>/gi, '<table $1>').replace(/<tr(\w*=[^>]+)>/gi, '<tr $1>');
.replaceAll('\\n', '\n')
.replace(/<table(\w*=[^>]+)>/gi, '<table $1>')
.replace(/<tr(\w*=[^>]+)>/gi, '<tr $1>');
}; };
const formatMarkdownValForAgent = (val: string) => { const formatMarkdownValForAgent = (val: string) => {

5
web/pages/mobile/chat/components/ChatDialog.tsx
View File

@ -69,10 +69,7 @@ const ChatDialog: React.FC<{
}, [context]); }, [context]);
const formatMarkdownVal = (val: string) => { const formatMarkdownVal = (val: string) => {
return val return val.replace(/<table(\w*=[^>]+)>/gi, '<table $1>').replace(/<tr(\w*=[^>]+)>/gi, '<tr $1>');
.replaceAll('\\n', '\n')
.replace(/<table(\w*=[^>]+)>/gi, '<table $1>')
.replace(/<tr(\w*=[^>]+)>/gi, '<tr $1>');
}; };
const formatMarkdownValForAgent = (val: string) => { const formatMarkdownValForAgent = (val: string) => {

2
web/utils/constants.ts
View File

@ -298,7 +298,7 @@ export const dbMapper: Record<DBType, { label: string; icon: string; desc: strin
gaussdb: { gaussdb: {
label: 'GaussDB', label: 'GaussDB',
icon: '/icons/gaussdb.png', icon: '/icons/gaussdb.png',
desc: 'Huawei\'s distributed database with PostgreSQL compatibility', desc: "Huawei's distributed database with PostgreSQL compatibility",
}, },
vertica: { vertica: {
label: 'Vertica', label: 'Vertica',