feat: (0.6)New UI (#1855)

Co-authored-by: 夏姜 <wenfengjiang.jwf@digital-engine.com> Co-authored-by: aries_ckt <916701291@qq.com> Co-authored-by: wb-lh513319 <wb-lh513319@alibaba-inc.com> Co-authored-by: csunny <cfqsunny@163.com>
2025-09-14 21:51:25 +00:00 · 2024-08-21 17:37:45 +08:00
parent 3fc82693ba
commit b124ecc10b
824 changed files with 93371 additions and 2515 deletions
--- a/dbgpt/serve/prompt/service/service.py
+++ b/dbgpt/serve/prompt/service/service.py
@@ -1,14 +1,29 @@
-from typing import List, Optional
+import json
+import logging
+from typing import Dict, List, Optional, Type

-from dbgpt.component import BaseComponent, SystemApp
+from dbgpt.agent import ConversableAgent, get_agent_manager
+from dbgpt.component import BaseComponent, ComponentType, SystemApp
+from dbgpt.core import ModelMetadata, ModelRequest, PromptTemplate
+from dbgpt.core.interface.prompt import (
+    SystemPromptTemplate,
+    _get_string_template_vars,
+    get_template_vars,
+)
+from dbgpt.model import DefaultLLMClient
+from dbgpt.model.cluster import WorkerManagerFactory
 from dbgpt.serve.core import BaseService
 from dbgpt.storage.metadata import BaseDao
+from dbgpt.util.json_utils import compare_json_properties_ex, find_json_objects
 from dbgpt.util.pagination_utils import PaginationResult
+from dbgpt.util.tracer import root_tracer

-from ..api.schemas import ServeRequest, ServerResponse
+from ..api.schemas import PromptDebugInput, PromptType, ServeRequest, ServerResponse
 from ..config import SERVE_CONFIG_KEY_PREFIX, SERVE_SERVICE_COMPONENT_NAME, ServeConfig
 from ..models.models import ServeDao, ServeEntity

+logger = logging.getLogger(__name__)
+

 class Service(BaseService[ServeEntity, ServeRequest, ServerResponse]):
    """The service class for Prompt"""
@@ -27,8 +42,6 @@ class Service(BaseService[ServeEntity, ServeRequest, ServerResponse]):
        Args:
            system_app (SystemApp): The system app
        """
-        super().init_app(system_app)
-
        self._serve_config = ServeConfig.from_app_config(
            system_app.config, SERVE_CONFIG_KEY_PREFIX
        )
@@ -72,7 +85,7 @@ class Service(BaseService[ServeEntity, ServeRequest, ServerResponse]):
        """
        # Build the query request from the request
        query_request = {
-            "prompt_name": request.prompt_name,
+            "prompt_code": request.prompt_code,
            "sys_code": request.sys_code,
        }
        return self.dao.update(query_request, update_request=request)
@@ -86,7 +99,6 @@ class Service(BaseService[ServeEntity, ServeRequest, ServerResponse]):
        Returns:
            ServerResponse: The response
        """
-        # TODO: implement your own logic here
        # Build the query request from the request
        query_request = request
        return self.dao.get_one(query_request)
@@ -134,4 +146,267 @@ class Service(BaseService[ServeEntity, ServeRequest, ServerResponse]):
            List[ServerResponse]: The response
        """
        query_request = request
-        return self.dao.get_list_page(query_request, page, page_size)
+        return self.dao.get_list_page(
+            query_request, page, page_size, ServeEntity.id.name
+        )
+
+    def get_prompt_template(self, prompt_type: str, target: Optional[str] = None):
+        request = ServeRequest()
+        request.prompt_type = prompt_type
+        request.chat_scene = target
+
+        return self.get_list(request)
+
+    def get_target_prompt(
+        self, target: Optional[str] = None, language: Optional[str] = None
+    ):
+        logger.info(f"get_target_prompt:{target}")
+        request = ServeRequest()
+        if target:
+            request.chat_scene = target
+        if language:
+            request.prompt_language = language
+        return self.get_list(request)
+
+    def get_type_targets(self, prompt_type: str):
+        type = PromptType(prompt_type)
+        if type == PromptType.AGENT:
+            agent_manage = get_agent_manager()
+            return agent_manage.list_agents()
+
+        elif type == PromptType.SCENE:
+            from dbgpt.app.scene import ChatScene
+
+            return [
+                {"name": item.value(), "desc": item.describe()} for item in ChatScene
+            ]
+        elif type == PromptType.EVALUATE:
+            from dbgpt.rag.evaluation.answer import LLMEvaluationMetric
+
+            return [
+                {"name": item.name, "desc": item.prompt_template}
+                for item in LLMEvaluationMetric.__subclasses__()
+            ]
+        else:
+            return None
+
+    def get_template(self, prompt_code: str) -> Optional[PromptTemplate]:
+        if not prompt_code:
+            return None
+        query_request = ServeRequest(prompt_code=prompt_code)
+        template = self.get(query_request)
+        if not template:
+            return None
+        return PromptTemplate(
+            template=template.content,
+            template_scene=template.chat_scene,
+            input_variables=get_template_vars(template.content),
+            response_format=template.response_schema,
+        )
+
+    def load_template(
+        self,
+        prompt_type: str,
+        target: Optional[str] = None,
+        language: Optional[str] = "en",
+    ):
+        logger.info(f"load_template:{prompt_type},{target}")
+        type = PromptType(prompt_type)
+        if type == PromptType.AGENT:
+            if not target:
+                raise ValueError("请选择一个Agent用来加载模版")
+            agent_manage = get_agent_manager()
+            target_agent_cls: Type[ConversableAgent] = agent_manage.get_by_name(target)
+            target_agent = target_agent_cls()
+            base_template = target_agent.prompt_template()
+
+            return PromptTemplate(
+                template=base_template,
+                input_variables=get_template_vars(base_template),
+                response_format=target_agent.actions[0].ai_out_schema_json,
+            )
+        elif type == PromptType.SCENE:
+            if not target:
+                raise ValueError("请选择一个场景用来加载模版")
+            from dbgpt._private.config import Config
+
+            cfg = Config()
+            from dbgpt.app.scene import AppScenePromptTemplateAdapter
+
+            try:
+                app_prompt: AppScenePromptTemplateAdapter = (
+                    cfg.prompt_template_registry.get_prompt_template(
+                        target, cfg.LANGUAGE, None
+                    )
+                )
+                for item in app_prompt.prompt.messages:
+                    if isinstance(item, SystemPromptTemplate):
+                        return item.prompt
+                raise ValueError(f"当前场景没有找到可用的Prompt模版，{target}")
+            except Exception as e:
+                raise ValueError(f"当前场景没有找到可用的Prompt模版，{target}")
+        elif type == PromptType.EVALUATE:
+            if not target:
+                raise ValueError("请选择一个场景用来加载模版")
+            try:
+                from dbgpt.rag.evaluation.answer import (
+                    AnswerRelevancyMetric,
+                    LLMEvaluationMetric,
+                )
+
+                prompts = [
+                    item.prompt_template
+                    for item in LLMEvaluationMetric.__subclasses__()
+                    if target == item.name
+                ]
+                if len(prompts) == 0:
+                    raise ValueError(f"当前场景没有找到可用的Prompt模版，{target}")
+                prompt = prompts[0]
+                return PromptTemplate(
+                    template=prompt, input_variables=get_template_vars(prompt)
+                )
+
+            except Exception as e:
+                raise ValueError(f"当前场景没有找到可用的Prompt模版，{target}")
+        else:
+            return None
+
+    async def debug_prompt(self, debug_input: PromptDebugInput):
+        logger.info(f"debug_prompt:{debug_input}")
+        if not debug_input.user_input:
+            raise ValueError("请输入你的提问!")
+        try:
+            worker_manager = self._system_app.get_component(
+                ComponentType.WORKER_MANAGER_FACTORY, WorkerManagerFactory
+            ).create()
+            llm_client = DefaultLLMClient(worker_manager, auto_convert_message=True)
+        except Exception as e:
+            raise ValueError("LLM prepare failed!", e)
+
+        try:
+            debug_messages = []
+            from dbgpt.core import ModelMessageRoleType
+
+            prompt = debug_input.content
+
+            prompt_vars = debug_input.input_values
+            type = PromptType(debug_input.prompt_type)
+            if type == PromptType.AGENT:
+                if debug_input.response_schema:
+                    prompt_vars.update(
+                        {
+                            "out_schema": f"请确保按照以下json格式回复:\n{debug_input.response_schema}\n确保响应是正确的json,并且可以被Python json.loads 解析。"
+                        }
+                    )
+            elif type == PromptType.SCENE:
+                if debug_input.response_schema:
+                    prompt_vars.update({"response": debug_input.response_schema})
+
+            if debug_input.input_values:
+                prompt = prompt.format(**prompt_vars)
+
+            debug_messages.append(
+                {"role": ModelMessageRoleType.SYSTEM, "content": prompt}
+            )
+            debug_messages.append(
+                {"role": ModelMessageRoleType.HUMAN, "content": debug_input.user_input}
+            )
+            metadata: ModelMetadata = await llm_client.get_model_metadata(
+                debug_input.debug_model
+            )
+            payload = {
+                "model": debug_input.debug_model,
+                "messages": debug_messages,
+                "temperature": debug_input.temperature,
+                "max_new_tokens": metadata.context_length,
+                "echo": metadata.ext_metadata.prompt_sep,
+                "stop": None,
+                "stop_token_ids": None,
+                "context_len": None,
+                "span_id": None,
+                "context": None,
+            }
+            logger.info(f"Request: \n{payload}")
+            span = root_tracer.start_span(
+                "Agent.llm_client.no_streaming_call",
+                metadata=self._get_span_metadata(payload),
+            )
+            payload["span_id"] = span.span_id
+
+            # if params.get("context") is not None:
+            #     payload["context"] = ModelRequestContext(extra=params["context"])
+
+        except Exception as e:
+            raise ValueError("参数准备失败！" + str(e))
+
+        try:
+            model_request = ModelRequest(**payload)
+
+            async for output in llm_client.generate_stream(model_request.copy()):  # type: ignore
+                yield f"data:{output.text}\n\n"
+            yield f"data:[DONE]\n\n"
+        except Exception as e:
+            logger.error(f"Call LLMClient error, {str(e)}, detail: {payload}")
+            raise ValueError(e)
+        finally:
+            span.end()
+
+    def _get_span_metadata(self, payload: Dict) -> Dict:
+        metadata = {k: v for k, v in payload.items()}
+
+        metadata["messages"] = list(
+            map(lambda m: m if isinstance(m, dict) else m.dict(), metadata["messages"])
+        )
+        return metadata
+
+    def verify_response(
+        self, llm_out: str, prompt_type: str, target: Optional[str] = None
+    ):
+        logger.info(f"verify_response:{llm_out},{prompt_type},{target}")
+        type = PromptType(prompt_type)
+        ai_json = find_json_objects(llm_out)
+        if type == PromptType.AGENT:
+            try:
+                if not target:
+                    raise ValueError("请选择一个Agent用来加载模版")
+                from dbgpt.agent.core import agent_manage
+
+                target_agent_cls: Type[ConversableAgent] = agent_manage.get_by_name(
+                    target
+                )
+                target_agent = target_agent_cls()
+
+                return compare_json_properties_ex(
+                    ai_json, json.loads(target_agent.actions[0].ai_out_schema_json)
+                )
+
+            except Exception as e:
+                raise ValueError(f"模型返回不符合[{target}]输出定义，请调整prompt！")
+
+        elif type == PromptType.SCENE:
+            if not target:
+                raise ValueError("请选择一个场景用来加载模版")
+            from dbgpt._private.config import Config
+
+            cfg = Config()
+            from dbgpt.app.scene import AppScenePromptTemplateAdapter
+
+            try:
+                app_prompt: AppScenePromptTemplateAdapter = (
+                    cfg.prompt_template_registry.get_prompt_template(
+                        target, cfg.LANGUAGE, None
+                    )
+                )
+
+                sys_prompt = None
+                for item in app_prompt.prompt.messages:
+                    if isinstance(item, SystemPromptTemplate):
+                        sys_prompt = item.prompt
+                if sys_prompt:
+                    return compare_json_properties_ex(
+                        ai_json, json.loads(sys_prompt.response_format)
+                    )
+            except Exception as e:
+                raise ValueError(f"当前场景没有找到可用的Prompt模版，{target}")
+        else:
+            return True