diff --git a/examples/client/client_openai_chat.py b/examples/client/client_openai_chat.py new file mode 100644 index 000000000..86f51cdf6 --- /dev/null +++ b/examples/client/client_openai_chat.py @@ -0,0 +1,165 @@ +# /// script +# dependencies = [ +# "openai", +# ] +# [tool.uv] +# exclude-newer = "2025-03-07T00:00:00Z" +# /// +"""Chat With Your DB-GPT's API by OpenAI Client + +Sample Usage: +```bash +uv run examples/client/client_openai_chat.py -m Qwen/QwQ-32B --input "Hello" +``` + +More examples: + +1. Chat Normal Mode: +```bash +uv run examples/client/client_openai_chat.py -m Qwen/QwQ-32B \ + --input "Which is bigger, 9.8 or 9.11?" +``` + +2. Chat Database Mode(chat_with_db_qa): + +```bash +uv run examples/client/client_openai_chat.py -m Qwen/QwQ-32B \ + --chat-mode chat_with_db_qa \ + --param "sqlite_dbgpt" \ + --input "Which table stores database connection information?" +``` + +3. Chat With Your Data(chat_data): +```bash +uv run examples/client/client_openai_chat.py -m Qwen/QwQ-32B \ + --chat-mode chat_data \ + --param "sqlite_dbgpt" \ + --input "Which database can I currently connect to? What is its name and type?" +``` + +4. Chat With Knowledge(chat_knowledge): +```bash +uv run examples/client/client_openai_chat.py -m Qwen/QwQ-32B \ + --chat-mode chat_knowledge \ + --param "awel" \ + --input "What is AWEL?" +``` + + +5. Chat With Third-party API(chat_third_party): +```bash +uv run examples/client/client_openai_chat.py -m deepseek-chat \ + --input "Which is bigger, 9.8 or 9.11?" \ + --chat-mode none \ + --api-key $DEEPSEEK_API_KEY \ + --api-base https://api.deepseek.com/v1 +``` + +""" # noqa + +import argparse + +from openai import OpenAI + +DBGPT_API_KEY = "dbgpt" + + +def handle_output(response): + has_thinking = False + print("=" * 80) + reasoning_content = "" + for chunk in response: + delta_content = chunk.choices[0].delta.content + if hasattr(chunk.choices[0].delta, "reasoning_content"): + reasoning_content = chunk.choices[0].delta.reasoning_content + if reasoning_content: + if not has_thinking: + print("", flush=True) + print(reasoning_content, end="", flush=True) + has_thinking = True + if delta_content: + if has_thinking: + print("", flush=True) + print(delta_content, end="", flush=True) + has_thinking = False + + +def main(): + parser = argparse.ArgumentParser(description="OpenAI Chat Client") + parser.add_argument( + "-m", + "--model", + type=str, + default="deepseek-chat", + help="Model name", + ) + parser.add_argument( + "-c", + "--chat-mode", + type=str, + default="chat_normal", + help="Chat mode. Default is chat_normal", + ) + parser.add_argument( + "-p", + "--param", + type=str, + default=None, + help="Chat param", + ) + parser.add_argument( + "--input", + type=str, + default="Hello, how are you?", + help="User input", + ) + parser.add_argument( + "--api-key", + type=str, + default=DBGPT_API_KEY, + help="API key", + ) + parser.add_argument( + "--api-base", + type=str, + default="http://localhost:5670/api/v2", + help="Base URL", + ) + parser.add_argument( + "--max-tokens", + type=int, + default=4096, + help="Max tokens", + ) + args = parser.parse_args() + + client = OpenAI( + api_key=args.api_key, + base_url=args.api_base, + ) + + messages = [ + { + "role": "user", + "content": args.input, + }, + ] + + extra_body = {} + if args.chat_mode != "none": + extra_body["chat_mode"] = args.chat_mode + if args.param: + extra_body["chat_param"] = args.param + + response = client.chat.completions.create( + model=args.model, + messages=messages, + extra_body=extra_body, + stream=True, + max_tokens=args.max_tokens, + ) + handle_output(response) + + +if __name__ == "__main__": + main() diff --git a/packages/dbgpt-app/src/dbgpt_app/openapi/api_v1/api_v1.py b/packages/dbgpt-app/src/dbgpt_app/openapi/api_v1/api_v1.py index 62633ec74..d446d35f6 100644 --- a/packages/dbgpt-app/src/dbgpt_app/openapi/api_v1/api_v1.py +++ b/packages/dbgpt-app/src/dbgpt_app/openapi/api_v1/api_v1.py @@ -14,9 +14,19 @@ from fastapi.responses import StreamingResponse from dbgpt._private.config import Config from dbgpt.component import ComponentType from dbgpt.configs import TAG_KEY_KNOWLEDGE_CHAT_DOMAIN_TYPE +from dbgpt.core import ModelOutput from dbgpt.core.awel import BaseOperator, CommonLLMHttpRequestBody 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.schema.api import ( + ChatCompletionResponse, + ChatCompletionResponseChoice, + ChatCompletionResponseStreamChoice, + ChatCompletionStreamResponse, + ChatMessage, + DeltaMessage, + UsageInfo, +) from dbgpt.model.base import FlatSupportedModel from dbgpt.model.cluster import BaseModelController, WorkerManager, WorkerManagerFactory from dbgpt.util.executor_utils import ( @@ -29,11 +39,8 @@ from dbgpt.util.tracer import SpanType, root_tracer from dbgpt_app.knowledge.request.request import KnowledgeSpaceRequest from dbgpt_app.knowledge.service import KnowledgeService from dbgpt_app.openapi.api_view_model import ( - ChatCompletionResponseStreamChoice, - ChatCompletionStreamResponse, ChatSceneVo, ConversationVo, - DeltaMessage, MessageVo, Result, ) @@ -397,7 +404,7 @@ async def file_read( def get_hist_messages(conv_uid: str, user_name: str = None): - from dbgpt_serve.conversation.serve import Service as ConversationService + from dbgpt_serve.conversation.service.service import Service as ConversationService instance: ConversationService = ConversationService.get_instance(CFG.SYSTEM_APP) return instance.get_history_messages({"conv_uid": conv_uid, "user_name": user_name}) @@ -540,7 +547,12 @@ async def chat_completions( ) else: return StreamingResponse( - stream_generator(chat, dialogue.incremental, dialogue.model_name), + stream_generator( + chat, + dialogue.incremental, + dialogue.model_name, + openai_format=dialogue.incremental, + ), headers=headers, media_type="text/plain", ) @@ -657,7 +669,14 @@ async def no_stream_generator(chat): yield f"data: {msg}\n\n" -async def stream_generator(chat, incremental: bool, model_name: str): +async def stream_generator( + chat, + incremental: bool, + model_name: str, + text_output: bool = True, + openai_format: bool = False, + conv_uid: str = None, +): """Generate streaming responses Our goal is to generate an openai-compatible streaming responses. @@ -676,33 +695,76 @@ async def stream_generator(chat, incremental: bool, model_name: str): span = root_tracer.start_span("stream_generator") msg = "[LLM_ERROR]: llm server has no output, maybe your prompt template is wrong." - stream_id = f"chatcmpl-{str(uuid.uuid1())}" - previous_response = "" - async for chunk in chat.stream_call(): - if chunk: - msg = chunk.replace("\ufffd", "") - if incremental: - incremental_output = msg[len(previous_response) :] - choice_data = ChatCompletionResponseStreamChoice( - index=0, - delta=DeltaMessage(role="assistant", content=incremental_output), - ) - chunk = ChatCompletionStreamResponse( - id=stream_id, choices=[choice_data], model=model_name - ) - _content = json.dumps( - chunk.dict(exclude_unset=True), ensure_ascii=False - ) - yield f"data:{_content}\n\n" + stream_id = conv_uid or f"chatcmpl-{str(uuid.uuid1())}" + try: + if incremental and not openai_format: + raise ValueError("Incremental response must be openai-compatible format.") + async for chunk in chat.stream_call( + text_output=text_output, incremental=incremental + ): + if not chunk: + await asyncio.sleep(0.02) + continue + + if openai_format: + # Must be ModelOutput + output: ModelOutput = cast(ModelOutput, chunk) + text = None + think_text = None + if output.has_text: + text = output.text + if output.has_thinking: + think_text = output.thinking_text + if incremental: + choice_data = ChatCompletionResponseStreamChoice( + index=0, + delta=DeltaMessage( + role="assistant", content=text, reasoning_content=think_text + ), + ) + chunk = ChatCompletionStreamResponse( + id=stream_id, choices=[choice_data], model=model_name + ) + _content = json.dumps( + chunk.dict(exclude_unset=True), ensure_ascii=False + ) + yield f"data: {_content}\n\n" + else: + choice_data = ChatCompletionResponseChoice( + index=0, + message=ChatMessage( + role="assistant", + content=output.text, + reasoning_content=output.thinking_text, + ), + ) + if output.usage: + usage = UsageInfo(**output.usage) + else: + usage = UsageInfo() + _content = ChatCompletionResponse( + id=stream_id, + choices=[choice_data], + model=model_name, + usage=usage, + ) + _content = json.dumps( + chunk.dict(exclude_unset=True), ensure_ascii=False + ) + yield f"data: {_content}\n\n" else: - # TODO generate an openai-compatible streaming responses + msg = chunk.replace("\ufffd", "") msg = msg.replace("\n", "\\n") yield f"data:{msg}\n\n" - previous_response = msg await asyncio.sleep(0.02) - if incremental: - yield "data: [DONE]\n\n" - span.end() + if incremental: + yield "data: [DONE]\n\n" + span.end() + except Exception as e: + logger.exception("stream_generator error") + yield f"data: [SERVER_ERROR]{str(e)}\n\n" + if incremental: + yield "data: [DONE]\n\n" def message2Vo(message: dict, order, model_name) -> MessageVo: @@ -764,7 +826,7 @@ async def chat_with_domain_flow(dialogue: ConversationVo, domain_type: str): incremental=dialogue.incremental, ) async for output in safe_chat_stream_with_dag_task(end_task, request, False): - text = output.text + text = output.gen_text_with_thinking() if text: text = text.replace("\n", "\\n") if output.error_code != 0: diff --git a/packages/dbgpt-app/src/dbgpt_app/openapi/api_v2.py b/packages/dbgpt-app/src/dbgpt_app/openapi/api_v2.py index 9295e18d5..11874c983 100644 --- a/packages/dbgpt-app/src/dbgpt_app/openapi/api_v2.py +++ b/packages/dbgpt-app/src/dbgpt_app/openapi/api_v2.py @@ -10,7 +10,6 @@ from starlette.responses import JSONResponse, StreamingResponse from dbgpt._private.pydantic import model_to_dict, model_to_json from dbgpt.component import SystemApp, logger -from dbgpt.core.awel import CommonLLMHttpRequestBody from dbgpt.core.schema.api import ( ChatCompletionResponse, ChatCompletionResponseChoice, @@ -128,6 +127,7 @@ async def chat_completions( or request.chat_mode == ChatMode.CHAT_NORMAL.value or request.chat_mode == ChatMode.CHAT_KNOWLEDGE.value or request.chat_mode == ChatMode.CHAT_DATA.value + or request.chat_mode == ChatMode.CHAT_DB_QA.value ): with root_tracer.start_span( "get_chat_instance", @@ -137,12 +137,19 @@ async def chat_completions( chat: BaseChat = await get_chat_instance(request, service.system_app) if not request.stream: + # TODO: Adapt to the new chat interface return await no_stream_wrapper(request, chat) else: return StreamingResponse( - stream_generator(chat, request.incremental, request.model), + stream_generator( + chat, + request.incremental, + request.model, + text_output=False, + openai_format=True, + ), headers=headers, - media_type="text/plain", + media_type="text/event-stream", ) else: raise HTTPException( @@ -185,7 +192,7 @@ async def get_chat_instance( "chat_session_id": dialogue.conv_uid, "user_name": dialogue.user_name, "sys_code": dialogue.sys_code, - "current_user_input": dialogue.messages, + "current_user_input": dialogue.single_prompt(), "select_param": dialogue.chat_param, "model_name": dialogue.model, "temperature": dialogue.temperature, @@ -232,7 +239,7 @@ async def chat_app_stream_wrapper(request: ChatCompletionRequestBody = None): async for output in multi_agents.app_agent_chat( conv_uid=request.conv_uid, gpts_name=request.chat_param, - user_query=request.messages, + user_query=request.single_prompt(), user_code=request.user_name, sys_code=request.sys_code, ): @@ -262,7 +269,7 @@ async def chat_app_stream_wrapper(request: ChatCompletionRequestBody = None): async def chat_flow_wrapper(request: ChatCompletionRequestBody): flow_service = get_chat_flow() - flow_req = CommonLLMHttpRequestBody(**model_to_dict(request)) + flow_req = request.to_common_llm_http_request_body() flow_uid = request.chat_param output = await flow_service.safe_chat_flow(flow_uid, flow_req) if not output.success: @@ -273,7 +280,11 @@ async def chat_flow_wrapper(request: ChatCompletionRequestBody): else: choice_data = ChatCompletionResponseChoice( index=0, - message=ChatMessage(role="assistant", content=output.text), + message=ChatMessage( + role="assistant", + content=output.text, + reasoning_content=output.thinking_text, + ), ) if output.usage: usage = UsageInfo(**output.usage) @@ -292,7 +303,7 @@ async def chat_flow_stream_wrapper( request (OpenAPIChatCompletionRequest): request """ flow_service = get_chat_flow() - flow_req = CommonLLMHttpRequestBody(**model_to_dict(request)) + flow_req = request.to_common_llm_http_request_body() flow_uid = request.chat_param async for output in flow_service.chat_stream_openai(flow_uid, flow_req): diff --git a/packages/dbgpt-app/src/dbgpt_app/openapi/api_view_model.py b/packages/dbgpt-app/src/dbgpt_app/openapi/api_view_model.py index f888d4d58..4fe593e4a 100644 --- a/packages/dbgpt-app/src/dbgpt_app/openapi/api_view_model.py +++ b/packages/dbgpt-app/src/dbgpt_app/openapi/api_view_model.py @@ -1,8 +1,6 @@ import socket -import time -import uuid from enum import Enum -from typing import Any, Dict, Generic, List, Literal, Optional, TypeVar +from typing import Any, Dict, Generic, Optional, TypeVar from dbgpt._private.pydantic import BaseModel, ConfigDict, Field, model_to_dict @@ -117,24 +115,6 @@ class MessageVo(BaseModel): model_name: str -class DeltaMessage(BaseModel): - role: Optional[str] = None - content: Optional[str] = None - - -class ChatCompletionResponseStreamChoice(BaseModel): - index: Optional[int] - delta: Optional[DeltaMessage] - finish_reason: Optional[Literal["stop", "length"]] = None - - -class ChatCompletionStreamResponse(BaseModel): - id: Optional[str] = Field(default_factory=lambda: f"chatcmpl-{str(uuid.uuid1())}") - created: Optional[int] = Field(default_factory=lambda: int(time.time())) - model: Optional[str] = None - choices: Optional[List[ChatCompletionResponseStreamChoice]] - - class ChatContext(BaseModel): model: Optional[str] = Field( ..., description="The model name", examples=["gpt-3.5-turbo", "proxyllm"] diff --git a/packages/dbgpt-app/src/dbgpt_app/scene/base_chat.py b/packages/dbgpt-app/src/dbgpt_app/scene/base_chat.py index 24362d543..47ea95c6c 100644 --- a/packages/dbgpt-app/src/dbgpt_app/scene/base_chat.py +++ b/packages/dbgpt-app/src/dbgpt_app/scene/base_chat.py @@ -2,7 +2,7 @@ import datetime import logging import traceback from abc import ABC, abstractmethod -from typing import Any, AsyncIterator, Dict +from typing import Any, AsyncIterator, Dict, Optional, Union from dbgpt._private.config import Config from dbgpt.component import ComponentType, SystemApp @@ -291,7 +291,9 @@ class BaseChat(ABC): ) return metadata - async def stream_call(self): + async def stream_call( + self, text_output: bool = True, incremental: bool = False + ) -> AsyncIterator[Union[ModelOutput, str]]: # TODO Retry when server connection error payload = await self._build_model_request() @@ -301,11 +303,16 @@ class BaseChat(ABC): "BaseChat.stream_call", metadata=payload.to_dict() ) payload.span_id = span.span_id + full_text = "" + full_thinking_text = "" + previous_text = "" + previous_thinking_text = "" try: msg = "ERROR! No response from model" - view_msg = msg + final_output: Optional[ModelOutput] = None async for output in self.call_streaming_operator(payload): # Plugin research in result generation + final_output = output model_output = ( self.prompt_template.output_parser.parse_model_stream_resp_ex( output, @@ -315,18 +322,91 @@ class BaseChat(ABC): msg = model_output.gen_text_with_thinking() view_msg = self.stream_plugin_call(msg) view_msg = view_msg.replace("\n", "\\n") - yield view_msg - self.current_message.add_ai_message(msg) - view_msg = self.stream_call_reinforce_fn(view_msg) + + if text_output: + full_text = view_msg + # Return the incremental text + delta_text = full_text[len(previous_text) :] + previous_text = ( + full_text + if len(full_text) > len(previous_text) + else previous_text + ) + yield delta_text if incremental else full_text + else: + if model_output.has_thinking: + full_thinking_text = model_output.thinking_text + if model_output.has_text: + full_text = model_output.text + if not incremental: + yield ModelOutput.build( + full_text, + full_thinking_text, + error_code=model_output.error_code, + usage=model_output.usage, + finish_reason=model_output.finish_reason, + metrics=model_output.metrics, + ) + else: + # Return the incremental text + delta_text = full_text[len(previous_text) :] + previous_text = ( + full_text + if len(full_text) > len(previous_text) + else previous_text + ) + delta_thinking_text = full_thinking_text[ + len(previous_thinking_text) : + ] + previous_thinking_text = ( + full_thinking_text + if len(full_thinking_text) > len(previous_thinking_text) + else previous_thinking_text + ) + yield ModelOutput.build( + delta_text, + delta_thinking_text, + error_code=model_output.error_code, + usage=model_output.usage, + finish_reason=model_output.finish_reason, + metrics=model_output.metrics, + ) + ai_response_text, view_message = await self._handle_final_output( + final_output, incremental=incremental + ) + if text_output: + full_text = view_message + # Return the incremental text + delta_text = full_text[len(previous_text) :] + yield delta_text if incremental else full_text + else: + yield ModelOutput.build( + view_message, + "", + error_code=final_output.error_code, + usage=final_output.usage, + finish_reason=final_output.finish_reason, + metrics=final_output.metrics, + ) + + self.current_message.add_ai_message(ai_response_text) + view_msg = self.stream_call_reinforce_fn(view_message) self.current_message.add_view_message(view_msg) span.end() except Exception as e: print(traceback.format_exc()) logger.error("model response parse failed！" + str(e)) - self.current_message.add_view_message( - f"""ERROR!{str(e)} -{ai_response_text} """ - ) + if not text_output: + yield ModelOutput.build( + f"{str(e)}", + "", + error_code=-1, + ) + else: + err_view_meg = ( + f'ERROR!{str(e)}\n{ai_response_text}' + ) + yield err_view_meg ### store current conversation span.end(metadata={"error": str(e)}) await blocking_func_to_async( @@ -370,7 +450,12 @@ class BaseChat(ABC): async def _no_streaming_call_with_retry(self, payload): with root_tracer.start_span("BaseChat.invoke_worker_manager.generate"): model_output = await self.call_llm_operator(payload) + return await self._handle_final_output(model_output) + async def _handle_final_output( + self, final_output: ModelOutput, incremental: bool = False + ): + model_output = final_output parsed_output = self.prompt_template.output_parser.parse_model_nostream_resp( model_output, text_output=False ) @@ -399,7 +484,7 @@ class BaseChat(ABC): result, prompt_define_response, ) - if parsed_output.has_thinking: + if parsed_output.has_thinking and not incremental: view_message = parsed_output.gen_text_with_thinking( new_text=view_message ) diff --git a/packages/dbgpt-app/src/dbgpt_app/scene/chat_dashboard/prompt.py b/packages/dbgpt-app/src/dbgpt_app/scene/chat_dashboard/prompt.py index b2e23db7b..28fae5f5e 100644 --- a/packages/dbgpt-app/src/dbgpt_app/scene/chat_dashboard/prompt.py +++ b/packages/dbgpt-app/src/dbgpt_app/scene/chat_dashboard/prompt.py @@ -64,7 +64,7 @@ prompt = ChatPromptTemplate( prompt_adapter = AppScenePromptTemplateAdapter( prompt=prompt, template_scene=ChatScene.ChatDashboard.value(), - stream_out=PROMPT_NEED_STREAM_OUT, + stream_out=True, output_parser=ChatDashboardOutputParser(is_stream_out=PROMPT_NEED_STREAM_OUT), need_historical_messages=False, ) diff --git a/packages/dbgpt-app/src/dbgpt_app/scene/chat_db/auto_execute/chat.py b/packages/dbgpt-app/src/dbgpt_app/scene/chat_db/auto_execute/chat.py index c0e99b85b..4baecac1d 100644 --- a/packages/dbgpt-app/src/dbgpt_app/scene/chat_db/auto_execute/chat.py +++ b/packages/dbgpt-app/src/dbgpt_app/scene/chat_db/auto_execute/chat.py @@ -76,11 +76,6 @@ class ChatWithDbAutoExecute(BaseChat): } return input_values - def stream_plugin_call(self, text): - text = text.replace("\n", " ") - print(f"stream_plugin_call:{text}") - return self.api_call.display_sql_llmvis(text, self.database.run_to_df) - def do_action(self, prompt_response): print(f"do_action:{prompt_response}") return self.database.run_to_df diff --git a/packages/dbgpt-app/src/dbgpt_app/scene/chat_db/auto_execute/prompt.py b/packages/dbgpt-app/src/dbgpt_app/scene/chat_db/auto_execute/prompt.py index b7cce0eab..a45dac679 100644 --- a/packages/dbgpt-app/src/dbgpt_app/scene/chat_db/auto_execute/prompt.py +++ b/packages/dbgpt-app/src/dbgpt_app/scene/chat_db/auto_execute/prompt.py @@ -123,7 +123,7 @@ prompt = ChatPromptTemplate( prompt_adapter = AppScenePromptTemplateAdapter( prompt=prompt, template_scene=ChatScene.ChatWithDbExecute.value(), - stream_out=PROMPT_NEED_STREAM_OUT, + stream_out=True, output_parser=DbChatOutputParser(is_stream_out=PROMPT_NEED_STREAM_OUT), temperature=PROMPT_TEMPERATURE, need_historical_messages=False, diff --git a/packages/dbgpt-app/src/dbgpt_app/scene/chat_knowledge/v1/chat.py b/packages/dbgpt-app/src/dbgpt_app/scene/chat_knowledge/v1/chat.py index ad1dc64b6..114a24d11 100644 --- a/packages/dbgpt-app/src/dbgpt_app/scene/chat_knowledge/v1/chat.py +++ b/packages/dbgpt-app/src/dbgpt_app/scene/chat_knowledge/v1/chat.py @@ -10,6 +10,7 @@ from dbgpt.core import ( MessagesPlaceholder, SystemPromptTemplate, ) +from dbgpt.core.interface.llm import ModelOutput from dbgpt.rag.retriever.rerank import RerankEmbeddingsRanker from dbgpt.rag.retriever.rewrite import QueryRewrite from dbgpt.util.tracer import root_tracer, trace @@ -107,14 +108,16 @@ class ChatKnowledge(BaseChat): if len(documents) > 0: self.document_ids = [document.id for document in documents] - async def stream_call(self): - last_output = None - async for output in super().stream_call(): - last_output = output - yield output + async def _handle_final_output( + self, final_output: ModelOutput, incremental: bool = False + ): reference = f"\n\n{self.parse_source_view(self.chunks_with_score)}" - last_output = last_output + reference - yield last_output + view_message = final_output.text + view_message = view_message + reference + + if final_output.has_thinking and not incremental: + view_message = final_output.gen_text_with_thinking(new_text=view_message) + return final_output.text, view_message def stream_call_reinforce_fn(self, text): """return reference""" diff --git a/packages/dbgpt-app/src/dbgpt_app/static/web/404.html b/packages/dbgpt-app/src/dbgpt_app/static/web/404.html index 461619997..96a426d3f 100644 --- a/packages/dbgpt-app/src/dbgpt_app/static/web/404.html +++ b/packages/dbgpt-app/src/dbgpt_app/static/web/404.html @@ -1 +1 @@ -
\ No newline at end of file +
\ No newline at end of file diff --git a/packages/dbgpt-app/src/dbgpt_app/static/web/404/index.html b/packages/dbgpt-app/src/dbgpt_app/static/web/404/index.html index 461619997..96a426d3f 100644 --- a/packages/dbgpt-app/src/dbgpt_app/static/web/404/index.html +++ b/packages/dbgpt-app/src/dbgpt_app/static/web/404/index.html @@ -1 +1 @@ -
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\ No newline at end of file diff --git a/packages/dbgpt-app/src/dbgpt_app/static/web/_next/data/K-FTPWVGbeMjNlLvdeDU_/construct/prompt/add.json b/packages/dbgpt-app/src/dbgpt_app/static/web/_next/data/md_K8sr0fWvzPAGETuvui/construct/prompt/add.json similarity index 100% rename from packages/dbgpt-app/src/dbgpt_app/static/web/_next/data/K-FTPWVGbeMjNlLvdeDU_/construct/prompt/add.json rename to packages/dbgpt-app/src/dbgpt_app/static/web/_next/data/md_K8sr0fWvzPAGETuvui/construct/prompt/add.json diff --git a/packages/dbgpt-app/src/dbgpt_app/static/web/_next/data/K-FTPWVGbeMjNlLvdeDU_/construct/prompt/edit.json b/packages/dbgpt-app/src/dbgpt_app/static/web/_next/data/md_K8sr0fWvzPAGETuvui/construct/prompt/edit.json similarity index 100% rename from packages/dbgpt-app/src/dbgpt_app/static/web/_next/data/K-FTPWVGbeMjNlLvdeDU_/construct/prompt/edit.json rename to packages/dbgpt-app/src/dbgpt_app/static/web/_next/data/md_K8sr0fWvzPAGETuvui/construct/prompt/edit.json diff --git 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\ No newline at end of file diff --git a/packages/dbgpt-client/src/dbgpt_client/_cli.py b/packages/dbgpt-client/src/dbgpt_client/_cli.py index 269c83c40..8bc492ced 100644 --- a/packages/dbgpt-client/src/dbgpt_client/_cli.py +++ b/packages/dbgpt-client/src/dbgpt_client/_cli.py @@ -245,7 +245,7 @@ def _run_flow_cmd_local( if not out.success: cl.error(out.text) else: - cl.print(out.text, end="") + cl.print(out.gen_text_with_thinking(), end="") except Exception as e: cl.error(f"Failed to run flow: {e}", exit_code=1) finally: @@ -436,7 +436,7 @@ def _run_flow_chat_local( cl.error(f"Error: {out.text}") raise Exception(out.text) else: - yield out.text + yield out.gen_text_with_thinking() async def _call(_call_body: Dict[str, Any]): nonlocal dag, dag_metadata @@ -466,6 +466,9 @@ def _run_flow_chat_stream( async for out in client.chat_stream(**_call_body): if out.choices: text = out.choices[0].delta.content + reasoning_content = out.choices[0].delta.reasoning_content + if reasoning_content: + yield reasoning_content if text: yield text @@ -482,6 +485,13 @@ def _run_flow_chat( res = await client.chat(**_call_body) if res.choices: text = res.choices[0].message.content + if res.choices[0].message.reasoning_content: + reasoning_content = res.choices[0].message.reasoning_content + # For each line, add '>' at the beginning + reasoning_content = "\n".join( + [f"> {line}" for line in reasoning_content.split("\n")] + ) + text = reasoning_content + "\n\n" + text return text loop.run_until_complete(_chat(_call, interactive, json_data)) diff --git a/packages/dbgpt-client/src/dbgpt_client/schema.py b/packages/dbgpt-client/src/dbgpt_client/schema.py index fb59302c2..ed9d86f3e 100644 --- a/packages/dbgpt-client/src/dbgpt_client/schema.py +++ b/packages/dbgpt-client/src/dbgpt_client/schema.py @@ -7,32 +7,20 @@ from typing import Any, Dict, List, Optional, Union from fastapi import File, UploadFile -from dbgpt._private.pydantic import BaseModel, ConfigDict, Field +from dbgpt._private.pydantic import BaseModel, ConfigDict, Field, model_validator +from dbgpt.core.awel import CommonLLMHttpRequestBody +from dbgpt.core.schema.api import APIChatCompletionRequest from dbgpt_ext.rag.chunk_manager import ChunkParameters -class ChatCompletionRequestBody(BaseModel): +class ChatCompletionRequestBody(APIChatCompletionRequest): """ChatCompletion LLM http request body.""" - model: str = Field( - ..., description="The model name", examples=["gpt-3.5-turbo", "proxyllm"] - ) - messages: Union[str, List[str]] = Field( - ..., description="User input messages", examples=["Hello", "How are you?"] - ) - stream: bool = Field(default=True, description="Whether return stream") - - temperature: Optional[float] = Field( - default=None, - description="What sampling temperature to use, between 0 and 2. Higher values " - "like 0.8 will make the output more random, " - "while lower values like 0.2 will " - "make it more focused and deterministic.", - ) max_new_tokens: Optional[int] = Field( default=None, description="The maximum number of tokens that can be generated in the chat " "completion.", + deprecated="'max_new_tokens' is deprecated. Use 'max_tokens' instead.", ) conv_uid: Optional[str] = Field( default=None, description="The conversation id of the model inference" @@ -65,6 +53,37 @@ class ChatCompletionRequestBody(BaseModel): default=True, description="response content whether to output vis label" ) + @model_validator(mode="before") + @classmethod + def pre_fill(cls, values: Dict[str, Any]) -> Dict[str, Any]: + """Pre fill the messages.""" + if not isinstance(values, dict): + return values + max_tokens = values.get("max_tokens") + max_new_tokens = values.get("max_new_tokens") + if max_tokens is None and max_new_tokens is not None: + values["max_tokens"] = max_new_tokens + return values + + def to_common_llm_http_request_body(self) -> CommonLLMHttpRequestBody: + """Convert to CommonLLMHttpRequestBody.""" + max_new_tokens = self.max_tokens + return CommonLLMHttpRequestBody( + model=self.model, + messages=self.single_prompt(), + stream=self.stream, + temperature=self.temperature, + max_new_tokens=max_new_tokens, + conv_uid=self.conv_uid, + span_id=self.span_id, + chat_mode=self.chat_mode, + chat_param=self.chat_param, + user_name=self.user_name, + sys_code=self.sys_code, + incremental=self.incremental, + enable_vis=self.enable_vis, + ) + class ChatMode(Enum): """Chat mode.""" @@ -74,6 +93,7 @@ class ChatMode(Enum): CHAT_AWEL_FLOW = "chat_flow" CHAT_KNOWLEDGE = "chat_knowledge" CHAT_DATA = "chat_data" + CHAT_DB_QA = "chat_with_db_qa" class AWELTeamModel(BaseModel): diff --git a/packages/dbgpt-core/src/dbgpt/core/awel/util/chat_util.py b/packages/dbgpt-core/src/dbgpt/core/awel/util/chat_util.py index e7af31084..9302a6df0 100644 --- a/packages/dbgpt-core/src/dbgpt/core/awel/util/chat_util.py +++ b/packages/dbgpt-core/src/dbgpt/core/awel/util/chat_util.py @@ -47,6 +47,7 @@ async def safe_chat_with_dag_task( metrics = None error_code = 0 text = "" + thinking_text = "" async for output in safe_chat_stream_with_dag_task( task, request, False, covert_to_str=covert_to_str ): @@ -54,10 +55,14 @@ async def safe_chat_with_dag_task( usage = output.usage metrics = output.metrics error_code = output.error_code - text = output.text - return ModelOutput( + if output.has_text: + text = output.text + if output.has_thinking: + thinking_text = output.thinking_text + return ModelOutput.build( + text, + thinking_text, error_code=error_code, - text=text, metrics=metrics, usage=usage, finish_reason=finish_reason, @@ -147,18 +152,31 @@ async def chat_stream_with_dag_task( task, OpenAIStreamingOutputOperator ): full_text = "" + full_thinking_text = "" async for output in await task.call_stream(request): model_output = parse_openai_output(output) # The output of the OpenAI streaming API is incremental - full_text += model_output.text + if model_output.has_thinking: + full_thinking_text += model_output.thinking_text + if model_output.has_text: + full_text += model_output.text model_output.incremental = incremental - model_output.text = model_output.text if incremental else full_text + if not incremental: + model_output = ModelOutput.build( + full_text, + full_thinking_text, + error_code=model_output.error_code, + usage=model_output.usage, + finish_reason=model_output.finish_reason, + ) yield model_output if not model_output.success: break else: full_text = "" + full_thinking_text = "" previous_text = "" + previous_thinking_text = "" async for output in await task.call_stream(request): model_output = parse_single_output( output, is_sse, covert_to_str=covert_to_str @@ -166,13 +184,26 @@ async def chat_stream_with_dag_task( model_output.incremental = incremental if task.incremental_output: # Output is incremental, append the text - full_text += model_output.text + if model_output.has_thinking: + full_thinking_text += model_output.thinking_text + if model_output.has_text: + full_text += model_output.text else: # Output is not incremental, last output is the full text - full_text = model_output.text + if model_output.has_thinking: + full_thinking_text = model_output.thinking_text + + if model_output.has_text: + full_text = model_output.text if not incremental: # Return the full text - model_output.text = full_text + model_output = ModelOutput.build( + full_text, + full_thinking_text, + error_code=model_output.error_code, + usage=model_output.usage, + finish_reason=model_output.finish_reason, + ) else: # Return the incremental text delta_text = full_text[len(previous_text) :] @@ -181,7 +212,21 @@ async def chat_stream_with_dag_task( if len(full_text) > len(previous_text) else previous_text ) - model_output.text = delta_text + delta_thinking_text = full_thinking_text[ + len(previous_thinking_text) : + ] + previous_thinking_text = ( + full_thinking_text + if len(full_thinking_text) > len(previous_thinking_text) + else previous_thinking_text + ) + model_output = ModelOutput.build( + delta_text, + delta_thinking_text, + error_code=model_output.error_code, + usage=model_output.usage, + finish_reason=model_output.finish_reason, + ) yield model_output if not model_output.success: break @@ -221,11 +266,12 @@ def parse_single_output( error_code = 0 text = output elif isinstance(output, ModelOutput): - error_code = output.error_code - text = output.text - finish_reason = output.finish_reason - usage = output.usage - metrics = output.metrics + # error_code = output.error_code + # text = output.text + # finish_reason = output.finish_reason + # usage = output.usage + # metrics = output.metrics + return output elif isinstance(output, CommonLLMHttpResponseBody): error_code = output.error_code text = output.text @@ -288,13 +334,16 @@ def parse_openai_output(output: Any) -> ModelOutput: ) choices = dict_data["choices"] finish_reason: Optional[str] = None + reasoning_content: Optional[str] = None if choices: choice = choices[0] delta_data = ChatCompletionResponseStreamChoice(**choice) if delta_data.delta.content: text = delta_data.delta.content + if delta_data.delta.reasoning_content: + reasoning_content = delta_data.delta.reasoning_content finish_reason = delta_data.finish_reason - return ModelOutput(error_code=0, text=text, finish_reason=finish_reason) + return ModelOutput.build(text, reasoning_content, finish_reason=finish_reason) def parse_sse_data(output: str) -> Optional[str]: diff --git a/packages/dbgpt-core/src/dbgpt/core/interface/llm.py b/packages/dbgpt-core/src/dbgpt/core/interface/llm.py index 7ca6fa9ab..98b296a57 100644 --- a/packages/dbgpt-core/src/dbgpt/core/interface/llm.py +++ b/packages/dbgpt-core/src/dbgpt/core/interface/llm.py @@ -448,6 +448,7 @@ class ModelOutput: usage: Optional[Dict[str, Any]] = None, finish_reason: Optional[str] = None, is_reasoning_model: bool = False, + metrics: Optional[ModelInferenceMetrics] = None, ) -> "ModelOutput": if thinking and text: # Has thinking and text @@ -471,6 +472,7 @@ class ModelOutput: content=content, usage=usage, finish_reason=finish_reason, + metrics=metrics, ) diff --git a/packages/dbgpt-core/src/dbgpt/core/interface/output_parser.py b/packages/dbgpt-core/src/dbgpt/core/interface/output_parser.py index 0ccaa622f..8fbbfccb4 100644 --- a/packages/dbgpt-core/src/dbgpt/core/interface/output_parser.py +++ b/packages/dbgpt-core/src/dbgpt/core/interface/output_parser.py @@ -237,8 +237,8 @@ class BaseOutputParser(MapOperator[ModelOutput, Any], ABC): .replace("\r\n", " ") .replace("\\n", " ") .replace("\n", " ") - .replace("\\", " ") - .replace("\\_", "_") + # .replace("\\", " ") + # .replace("\\_", "_") ) cleaned_output = self._illegal_json_ends(cleaned_output) return cleaned_output diff --git a/packages/dbgpt-core/src/dbgpt/core/schema/api.py b/packages/dbgpt-core/src/dbgpt/core/schema/api.py index 437cbfa22..76fbf88d0 100644 --- a/packages/dbgpt-core/src/dbgpt/core/schema/api.py +++ b/packages/dbgpt-core/src/dbgpt/core/schema/api.py @@ -47,12 +47,21 @@ class Result(BaseModel, Generic[T]): return model_to_dict(self, **kwargs) +_ChatCompletionMessageType = Union[str, List[Dict[str, str]], List[str]] + + class APIChatCompletionRequest(BaseModel): """Chat completion request entity.""" model: str = Field(..., description="Model name") - messages: Union[str, List[Dict[str, str]]] = Field(..., description="Messages") - temperature: Optional[float] = Field(0.7, description="Temperature") + messages: _ChatCompletionMessageType = Field(..., description="User input messages") + temperature: Optional[float] = Field( + 0.7, + description="What sampling temperature to use, between 0 and 2. Higher values " + "like 0.8 will make the output more random, " + "while lower values like 0.2 will " + "make it more focused and deterministic.", + ) top_p: Optional[float] = Field(1.0, description="Top p") top_k: Optional[int] = Field(-1, description="Top k") n: Optional[int] = Field(1, description="Number of completions") @@ -64,6 +73,19 @@ class APIChatCompletionRequest(BaseModel): frequency_penalty: Optional[float] = Field(0.0, description="Frequency penalty") presence_penalty: Optional[float] = Field(0.0, description="Presence penalty") + def single_prompt(self) -> str: + """Get single prompt from messages.""" + if isinstance(self.messages, str): + return self.messages + elif isinstance(self.messages, list): + if not self.messages: + raise ValueError("Empty messages") + if isinstance(self.messages[0], str): + return self.messages[0] + return self.messages[0]["content"] + else: + raise ValueError("Invalid messages type") + class UsageInfo(BaseModel): """Usage info entity.""" @@ -78,6 +100,7 @@ class DeltaMessage(BaseModel): role: Optional[str] = None content: Optional[str] = None + reasoning_content: Optional[str] = None class ChatCompletionResponseStreamChoice(BaseModel): @@ -111,6 +134,7 @@ class ChatMessage(BaseModel): role: str = Field(..., description="Role of the message") content: str = Field(..., description="Content of the message") + reasoning_content: Optional[str] = Field(None, description="Reasoning content") class ChatCompletionResponseChoice(BaseModel): diff --git a/packages/dbgpt-core/src/dbgpt/model/utils/chatgpt_utils.py b/packages/dbgpt-core/src/dbgpt/model/utils/chatgpt_utils.py index c8e68f36d..4f2ec1807 100644 --- a/packages/dbgpt-core/src/dbgpt/model/utils/chatgpt_utils.py +++ b/packages/dbgpt-core/src/dbgpt/model/utils/chatgpt_utils.py @@ -215,8 +215,10 @@ async def _to_openai_stream( id=id, choices=[choice_data], model=model or "" ) yield transform_to_sse(chunk) - + delta_text = "" previous_text = "" + thinking_text = "" + previous_thinking_text = "" finish_stream_events = [] async for model_output in output_iter: if model_caller is not None: @@ -229,23 +231,34 @@ async def _to_openai_stream( yield transform_to_sse(model_output.to_dict()) yield transform_to_sse("[DONE]") return - decoded_unicode = model_output.text.replace("\ufffd", "") - delta_text = decoded_unicode[len(previous_text) :] - previous_text = ( - decoded_unicode - if len(decoded_unicode) > len(previous_text) - else previous_text - ) + if model_output.has_text: + decoded_unicode = model_output.text.replace("\ufffd", "") + delta_text = decoded_unicode[len(previous_text) :] + previous_text = ( + decoded_unicode + if len(decoded_unicode) > len(previous_text) + else previous_text + ) + if model_output.has_thinking: + decoded_unicode = model_output.thinking_text.replace("\ufffd", "") + thinking_text = decoded_unicode[len(previous_thinking_text) :] + previous_thinking_text = ( + decoded_unicode + if len(decoded_unicode) > len(previous_thinking_text) + else previous_thinking_text + ) - if len(delta_text) == 0: + if not delta_text: delta_text = None + if not thinking_text: + thinking_text = None choice_data = ChatCompletionResponseStreamChoice( index=0, - delta=DeltaMessage(content=delta_text), + delta=DeltaMessage(content=delta_text, reasoning_content=thinking_text), finish_reason=model_output.finish_reason, ) chunk = ChatCompletionStreamResponse(id=id, choices=[choice_data], model=model) - if delta_text is None: + if delta_text is None and thinking_text is None: if model_output.finish_reason is not None: finish_stream_events.append(chunk) continue diff --git a/packages/dbgpt-ext/src/dbgpt_ext/rag/retriever/db_schema.py b/packages/dbgpt-ext/src/dbgpt_ext/rag/retriever/db_schema.py index 60258698e..10faf0c1c 100644 --- a/packages/dbgpt-ext/src/dbgpt_ext/rag/retriever/db_schema.py +++ b/packages/dbgpt-ext/src/dbgpt_ext/rag/retriever/db_schema.py @@ -246,7 +246,7 @@ class DBSchemaRetriever(BaseRetriever): if not table_name: return chunk - create_statement = f'CREATE TABLE "{table_name}"\r\n(\r\n ' + create_statement = f"CREATE TABLE `{table_name}`\r\n(\r\n " create_statement += field_part create_statement += "\r\n)" if table_comment: diff --git a/packages/dbgpt-serve/src/dbgpt_serve/flow/service/service.py b/packages/dbgpt-serve/src/dbgpt_serve/flow/service/service.py index 3f6b7dfb9..777832b5d 100644 --- a/packages/dbgpt-serve/src/dbgpt_serve/flow/service/service.py +++ b/packages/dbgpt-serve/src/dbgpt_serve/flow/service/service.py @@ -460,7 +460,7 @@ class Service(BaseService[ServeEntity, ServeRequest, ServerResponse]): # Must be non-incremental request.incremental = False async for output in self.safe_chat_stream_flow(flow_uid, request): - text = output.text + text = output.gen_text_with_thinking() if text: text = text.replace("\n", "\\n") if output.error_code != 0: @@ -491,9 +491,14 @@ class Service(BaseService[ServeEntity, ServeRequest, ServerResponse]): yield f"data: {json.dumps(output.to_dict(), ensure_ascii=False)}\n\n" yield "data: [DONE]\n\n" return + text = output.text if output.has_text else "" choice_data = ChatCompletionResponseStreamChoice( index=0, - delta=DeltaMessage(role="assistant", content=output.text), + delta=DeltaMessage( + role="assistant", + content=text, + reasoning_content=output.thinking_text, + ), ) chunk = ChatCompletionStreamResponse( id=conv_uid, diff --git a/web/components/chat/chat-container.tsx b/web/components/chat/chat-container.tsx index 744afb02f..c6eb65ac1 100644 --- a/web/components/chat/chat-container.tsx +++ b/web/components/chat/chat-container.tsx @@ -184,37 +184,54 @@ const ChatContainer = () => { ); return ( - <> +
-
{ - setModel(newModel); - }} - /> -
+ +
+
{ + setModel(newModel); + }} + /> +
+ + {/* Use flex-auto to ensure the remaining height is filled */} +
+ {/* Left chart area */} {!!chartsData?.length && ( -
+
)} - {!chartsData?.length && scene === 'chat_dashboard' && } - {/** chat panel */} + {!chartsData?.length && scene === 'chat_dashboard' && ( +
+ +
+ )} +
- + {/* Wrap the Completion component in a container with a specific height */} +
+ +
- +
); }; diff --git a/web/components/chat/completion.tsx b/web/components/chat/completion.tsx index 290ebcd45..1469111bf 100644 --- a/web/components/chat/completion.tsx +++ b/web/components/chat/completion.tsx @@ -169,7 +169,7 @@ const Completion = ({ messages, onSubmit, onFormatContent }: Props) => { return ( <> {contextHolder} -
+
{showMessages.length ? ( showMessages.map((content, index) => { @@ -230,7 +230,7 @@ const Completion = ({ messages, onSubmit, onFormatContent }: Props) => {