WEB API independent

.gitignore

@@ -7,6 +7,7 @@ __pycache__/
 *.so
 
 message/
+static/
 
 .env
 .idea

pilot/openapi/api_v1/api_v1.py

@@ -2,7 +2,7 @@ import uuid
 import json
 import asyncio
 import time
-from fastapi import APIRouter, Request, Body, status, HTTPException, Response
+from fastapi import APIRouter, Request, Body, status, HTTPException, Response, BackgroundTasks
 
 from fastapi.responses import JSONResponse
 from fastapi.responses import StreamingResponse
@@ -35,6 +35,7 @@ knowledge_service = KnowledgeService()
 model_semaphore = None
 global_counter = 0
 
+
 async def validation_exception_handler(request: Request, exc: RequestValidationError):
     message = ""
     for error in exc.errors():
@@ -176,6 +177,11 @@ async def dialogue_history_messages(con_uid: str):
 @router.post("/v1/chat/completions")
 async def chat_completions(dialogue: ConversationVo = Body()):
     print(f"chat_completions:{dialogue.chat_mode},{dialogue.select_param}")
+    if not dialogue.chat_mode:
+        dialogue.chat_mode = ChatScene.ChatNormal.value
+    if not dialogue.conv_uid:
+        dialogue.conv_uid = str(uuid.uuid1())
+
     global model_semaphore, global_counter
     global_counter += 1
     if model_semaphore is None:
@@ -204,30 +210,51 @@ async def chat_completions(dialogue: ConversationVo = Body()):
         chat_param.update({"knowledge_space": dialogue.select_param})
 
     chat: BaseChat = CHAT_FACTORY.get_implementation(dialogue.chat_mode, **chat_param)
-    if not chat.prompt_template.stream_out:
-        return chat.nostream_call()
-    else:
     background_tasks = BackgroundTasks()
     background_tasks.add_task(release_model_semaphore)
-        return StreamingResponse(stream_generator(chat), background=background_tasks)
+    headers = {
+        # "Content-Type": "text/event-stream",
+        "Cache-Control": "no-cache",
+        "Connection": "keep-alive",
+        # "Transfer-Encoding": "chunked",
+    }
+
+    if not chat.prompt_template.stream_out:
+        return StreamingResponse(no_stream_generator(chat), headers=headers, media_type='text/event-stream',
+                                 background=background_tasks)
+    else:
+        return StreamingResponse(stream_generator(chat), headers=headers, media_type='text/plain',
+                                 background=background_tasks)
+
 
 def release_model_semaphore():
     model_semaphore.release()
 
-def stream_generator(chat):
+
+async def no_stream_generator(chat):
+    msg = chat.nostream_call()
+    msg = msg.replace("\n", "\\n")
+    yield f"data: {msg}\n\n"
+
+async def stream_generator(chat):
     model_response = chat.stream_call()
     if not CFG.NEW_SERVER_MODE:
         for chunk in model_response.iter_lines(decode_unicode=False, delimiter=b"\0"):
             if chunk:
                 msg = chat.prompt_template.output_parser.parse_model_stream_resp_ex(chunk, chat.skip_echo_len)
                 chat.current_message.add_ai_message(msg)
-                yield msg
+                msg = msg.replace("\n", "\\n")
+                yield f"data:{msg}\n\n"
+                await asyncio.sleep(0.1)
     else:
         for chunk in model_response:
             if chunk:
                 msg = chat.prompt_template.output_parser.parse_model_stream_resp_ex(chunk, chat.skip_echo_len)
                 chat.current_message.add_ai_message(msg)
-                yield msg
+
+                msg = msg.replace("\n", "\\n")
+                yield f"data:{msg}\n\n"
+                await asyncio.sleep(0.1)
     chat.memory.append(chat.current_message)
 
 

pilot/prompts/example_base.py

@@ -6,7 +6,7 @@ from pilot.common.schema import ExampleType
 
 
 class ExampleSelector(BaseModel, ABC):
-    examples: List[List]
+    examples_record: List[List]
     use_example: bool = False
     type: str = ExampleType.ONE_SHOT.value
 
@@ -16,17 +16,13 @@ class ExampleSelector(BaseModel, ABC):
         else:
             return self.__few_shot_context(count)
 
-    def __examples_text(self, used_examples):
-
-
-
     def __few_shot_context(self, count: int = 2) -> List[List]:
         """
         Use 2 or more examples, default 2
         Returns: example text
         """
         if self.use_example:
-            need_use = self.examples[:count]
+            need_use = self.examples_record[:count]
             return need_use
         return None
 
@@ -37,7 +33,7 @@ class ExampleSelector(BaseModel, ABC):
 
         """
         if self.use_example:
-            need_use = self.examples[:1]
+            need_use = self.examples_record[:1]
             return need_use
 
         return None

pilot/prompts/prompt_new.py

@@ -46,7 +46,10 @@ class PromptTemplate(BaseModel, ABC):
     output_parser: BaseOutputParser = None
     """"""
     sep: str = SeparatorStyle.SINGLE.value
-    example: ExampleSelector = None
+
+    example_selector: ExampleSelector = None
+
+    need_historical_messages: bool = False
 
     class Config:
         """Configuration for this pydantic object."""

pilot/scene/base_chat.py

@@ -52,7 +52,7 @@ class BaseChat(ABC):
     temperature: float = 0.6
     max_new_tokens: int = 1024
     # By default, keep the last two rounds of conversation records as the context
-    chat_retention_rounds: int = 2
+    chat_retention_rounds: int = 1
 
     class Config:
         """Configuration for this pydantic object."""
@@ -79,8 +79,6 @@ class BaseChat(ABC):
         self.history_message: List[OnceConversation] = self.memory.messages()
         self.current_message: OnceConversation = OnceConversation(chat_mode.value)
         self.current_tokens_used: int = 0
-        ### load chat_session_id's chat historys
-        self._load_history(self.chat_session_id)
 
     class Config:
         """Configuration for this pydantic object."""
@@ -107,18 +105,9 @@ class BaseChat(ABC):
         self.current_message.start_date = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
         # TODO
         self.current_message.tokens = 0
-        current_prompt = None
 
         if self.prompt_template.template:
             current_prompt = self.prompt_template.format(**input_values)
-
-        ### 构建当前对话， 是否安第一次对话prompt构造？ 是否考虑切换库
-        if self.history_message:
-            ## TODO 带历史对话记录的场景需要确定切换库后怎么处理
-            logger.info(
-                f"There are already {len(self.history_message)} rounds of conversations!"
-            )
-        if current_prompt:
             self.current_message.add_system_message(current_prompt)
 
         payload = {
@@ -155,7 +144,7 @@ class BaseChat(ABC):
             self.current_message.add_view_message(
                 f"""<span style=\"color:red\">ERROR!</span>{str(e)}\n  {ai_response_text} """
             )
-        ### 对话记录存储
+        ### store current conversation
         self.memory.append(self.current_message)
 
     def nostream_call(self):
@@ -165,7 +154,6 @@ class BaseChat(ABC):
         try:
             rsp_str = ""
             if not CFG.NEW_SERVER_MODE:
-                ### 走非流式的模型服务接口
                 rsp_str = requests.post(
                     urljoin(CFG.MODEL_SERVER, "generate"),
                     headers=headers,
@@ -212,7 +200,7 @@ class BaseChat(ABC):
             self.current_message.add_view_message(
                 f"""<span style=\"color:red\">ERROR!</span>{str(e)}\n  {ai_response_text} """
             )
-        ### 对话记录存储
+        ### store dialogue
         self.memory.append(self.current_message)
         return self.current_ai_response()
 
@@ -224,15 +212,61 @@ class BaseChat(ABC):
 
     def generate_llm_text(self) -> str:
         text = ""
+        ### Load scene setting or character definition
         if self.prompt_template.template_define:
-            text = self.prompt_template.template_define + self.prompt_template.sep
+            text += self.prompt_template.template_define + self.prompt_template.sep
+        ### Load prompt
+        text += self.__load_system_message()
 
-        ### 处理历史信息
+        ### Load examples
+        text += self.__load_example_messages()
+
+        ### Load History
+        text += self.__load_histroy_messages()
+
+        ### Load User Input
+        text += self.__load_user_message()
+        return text
+
+    def __load_system_message(self):
+        system_convs = self.current_message.get_system_conv()
+        system_text = ""
+        for system_conv in system_convs:
+            system_text += system_conv.type + ":" + system_conv.content + self.prompt_template.sep
+        return system_text
+
+    def __load_user_message(self):
+        user_conv = self.current_message.get_user_conv()
+        if user_conv:
+            return user_conv.type + ":" + user_conv.content + self.prompt_template.sep
+        else:
+            raise ValueError("Hi! What do you want to talk about？")
+
+    def __load_example_messages(self):
+        example_text = ""
+        if self.prompt_template.example_selector:
+            for round_conv in self.prompt_template.example_selector.examples():
+                for round_message in round_conv['messages']:
+                    if not round_message['type'] in [SystemMessage.type, ViewMessage.type]:
+                        example_text += (
+                                round_message['type']
+                                + ":"
+                                + round_message['data']['content']
+                                + self.prompt_template.sep
+                        )
+        return example_text
+
+    def __load_histroy_messages(self):
+        history_text = ""
+        if self.prompt_template.need_historical_messages:
+            if self.history_message:
+                logger.info(
+                    f"There are already {len(self.history_message)} rounds of conversations! Will use {self.chat_retention_rounds} rounds of content as history!"
+                )
             if len(self.history_message) > self.chat_retention_rounds:
-            ### 使用历史信息的第一轮和最后n轮数据合并成历史对话记录, 做上下文提示时，用户展示消息需要过滤掉
                 for first_message in self.history_message[0]['messages']:
                     if not first_message['type'] in [ViewMessage.type, SystemMessage.type]:
-                    text += (
+                        history_text += (
                                 first_message['type']
                                 + ":"
                                 + first_message['data']['content']
@@ -242,8 +276,8 @@ class BaseChat(ABC):
                 index = self.chat_retention_rounds - 1
                 for round_conv in self.history_message[-index:]:
                     for round_message in round_conv['messages']:
-                    if not isinstance(round_message, ViewMessage):
-                        text += (
+                        if not round_message['type'] in [SystemMessage.type, ViewMessage.type]:
+                            history_text += (
                                     round_message['type']
                                     + ":"
                                     + round_message['data']['content']
@@ -251,41 +285,26 @@ class BaseChat(ABC):
                             )
 
             else:
-            ### 直接历史记录拼接
+                ### user all history
                 for conversation in self.history_message:
                     for message in conversation['messages']:
-                    if not isinstance(message, ViewMessage):
-                        text += (
+                        ### histroy message not have promot and view info
+                        if not message['type'] in [SystemMessage.type, ViewMessage.type]:
+                            history_text += (
                                     message['type']
                                     + ":"
                                     + message['data']['content']
                                     + self.prompt_template.sep
                             )
-        ### current conversation
 
-        for now_message in self.current_message.messages:
-            text += (
-                    now_message.type + ":" + now_message.content + self.prompt_template.sep
-            )
+        return history_text
 
-        return text
-
-    # 暂时为了兼容前端
     def current_ai_response(self) -> str:
         for message in self.current_message.messages:
             if message.type == "view":
                 return message.content
         return None
 
-    def _load_history(self, session_id: str) -> List[OnceConversation]:
-        """
-        load chat history by session_id
-        Args:
-            session_id:
-        Returns:
-        """
-        return self.memory.messages()
-
     def generate(self, p) -> str:
         """
         generate context for LLM input

pilot/scene/chat_execution/example.py

@@ -6,4 +6,4 @@ EXAMPLES = [
     [{"system": "123"},{"system":"xxx"},{"human":"xxx"},{"assistant":"xxx"}]
 ]
 
-example = ExampleSelector(examples=EXAMPLES, use_example=True)
+plugin_example = ExampleSelector(examples_record=EXAMPLES, use_example=True)

pilot/scene/chat_execution/prompt.py

@@ -5,7 +5,7 @@ from pilot.scene.base import ChatScene
 from pilot.common.schema import SeparatorStyle, ExampleType
 
 from pilot.scene.chat_execution.out_parser import PluginChatOutputParser
-from pilot.scene.chat_execution.example import example
+from pilot.scene.chat_execution.example import plugin_example
 
 CFG = Config()
 
@@ -49,7 +49,7 @@ prompt = PromptTemplate(
     output_parser=PluginChatOutputParser(
         sep=PROMPT_SEP, is_stream_out=PROMPT_NEED_STREAM_OUT
     ),
-    example=example,
+    example_selector=plugin_example,
 )
 
 CFG.prompt_templates.update({prompt.template_scene: prompt})

pilot/scene/message.py

@@ -85,12 +85,18 @@ class OnceConversation:
         self.messages.clear()
         self.session_id = None
 
-    def get_user_message(self):
-        for once in self.messages:
-            if isinstance(once, HumanMessage):
-                return once.content
-        return ""
+    def get_user_conv(self):
+        for message in self.messages:
+            if isinstance(message, HumanMessage):
+                return message
+        return None
 
+    def get_system_conv(self):
+        system_convs = []
+        for message in self.messages:
+            if isinstance(message, SystemMessage):
+                system_convs.append(message)
+        return system_convs
 
 def _conversation_to_dic(once: OnceConversation) -> dict:
     start_str: str = ""

pilot/server/dbgpt_server.py

@@ -18,6 +18,7 @@ from pilot.utils import build_logger
 
 from pilot.server.webserver_base import server_init
 
+from fastapi.staticfiles import StaticFiles
 from fastapi import FastAPI, applications
 from fastapi.openapi.docs import get_swagger_ui_html
 from fastapi.exceptions import RequestValidationError
@@ -25,6 +26,7 @@ from fastapi.middleware.cors import CORSMiddleware
 
 from pilot.openapi.api_v1.api_v1 import router as api_v1, validation_exception_handler
 
+static_file_path = os.path.join(os.getcwd(), "server/static")
 
 CFG = Config()
 logger = build_logger("webserver", LOGDIR + "webserver.log")
@@ -52,7 +54,9 @@ app.add_middleware(
     allow_headers=["*"],
 )
 
-# app.mount("static", StaticFiles(directory="static"), name="static")
+app.mount("/static", StaticFiles(directory=static_file_path), name="static")
+app.add_route("/test",  "static/test.html")
+
 app.include_router(api_v1)
 app.add_exception_handler(RequestValidationError, validation_exception_handler)
 

pilot/server/static/test.html

@@ -0,0 +1,19 @@
+<!DOCTYPE html>
+<html>
+<head>
+    <meta charset="UTF-8">
+    <title>Streaming Demo</title>
+    <script src="https://code.jquery.com/jquery-3.6.0.min.js"></script>
+</head>
+<body>
+    <div id="output"></div>
+    <script>
+        $(document).ready(function() {
+            var source = new EventSource("/v1/chat/completions");
+            source.onmessage = function(event) {
+                $("#output").append(event.data);
+            }
+        });
+    </script>
+</body>
+</html>