删除掉一些没用的注释，已经不需要todo了

configs/server_config.py.example

@@ -132,12 +132,6 @@ FSCHAT_MODEL_WORKERS = {
     },
 }
 
-# fastchat multi model worker server
-FSCHAT_MULTI_MODEL_WORKERS = {
-    # TODO:
-}
-
-# fastchat controller server
 FSCHAT_CONTROLLER = {
     "host": DEFAULT_BIND_HOST,
     "port": 20001,

document_loaders/mypdfloader.py

@@ -16,11 +16,8 @@ class RapidOCRPDFLoader(UnstructuredFileLoader):
 
             b_unit = tqdm.tqdm(total=doc.page_count, desc="RapidOCRPDFLoader context page index: 0")
             for i, page in enumerate(doc):
-                # 更新描述
                 b_unit.set_description("RapidOCRPDFLoader context page index: {}".format(i))
-                # 立即显示进度条更新结果
                 b_unit.refresh()
-                # TODO: 依据文本与图片顺序调整处理方式
                 text = page.get_text("")
                 resp += text + "\n"
 

server/embeddings_api.py

@@ -16,7 +16,6 @@ def embed_texts(
 ) -> BaseResponse:
     '''
     对文本进行向量化。返回数据格式：BaseResponse(data=List[List[float]])
-    TODO: 也许需要加入缓存机制，减少 token 消耗
     '''
     try:
         if embed_model in list_embed_models():  # 使用本地Embeddings模型

server/knowledge_base/kb_cache/faiss_cache.py

@@ -55,8 +55,6 @@ class _FaissPool(CachePool):
         embed_model: str = EMBEDDING_MODEL,
         embed_device: str = embedding_device(),
     ) -> FAISS:
-        # TODO: 整个Embeddings加载逻辑有些混乱，待清理
-        # create an empty vector store
         embeddings = EmbeddingsFunAdapter(embed_model)
         doc = Document(page_content="init", metadata={})
         vector_store = FAISS.from_documents([doc], embeddings, normalize_L2=True,distance_strategy="METRIC_INNER_PRODUCT")

server/knowledge_base/kb_doc_api.py

@@ -95,7 +95,6 @@ def _save_files_in_thread(files: List[UploadFile],
                     and not override
                     and os.path.getsize(file_path) == len(file_content)
             ):
-                # TODO: filesize 不同后的处理
                 file_status = f"文件 {filename} 已存在。"
                 logger.warn(file_status)
                 return dict(code=404, msg=file_status, data=data)
@@ -116,7 +115,6 @@ def _save_files_in_thread(files: List[UploadFile],
         yield result
 
 
-# TODO: 等langchain.document_loaders支持内存文件的时候再开通
 # def files2docs(files: List[UploadFile] = File(..., description="上传文件，支持多文件"),
 #                 knowledge_base_name: str = Form(..., description="知识库名称", examples=["samples"]),
 #                 override: bool = Form(False, description="覆盖已有文件"),

server/knowledge_base/kb_service/base.py

@@ -191,7 +191,6 @@ class KBService(ABC):
         '''
         传入参数为： {doc_id: Document, ...}
         如果对应 doc_id 的值为 None，或其 page_content 为空，则删除该文档
-        TODO：是否要支持新增 docs ？
         '''
         self.del_doc_by_ids(list(docs.keys()))
         docs = []

server/knowledge_base/kb_service/milvus_kb_service.py

@@ -70,7 +70,6 @@ class MilvusKBService(KBService):
         return score_threshold_process(score_threshold, top_k, docs)
 
     def do_add_doc(self, docs: List[Document], **kwargs) -> List[Dict]:
-        # TODO: workaround for bug #10492 in langchain
         for doc in docs:
             for k, v in doc.metadata.items():
                 doc.metadata[k] = str(v)

server/knowledge_base/kb_service/pg_kb_service.py

@@ -32,8 +32,6 @@ class PGKBService(KBService):
             results = [Document(page_content=row[0], metadata=row[1]) for row in
                        session.execute(stmt, {'ids': ids}).fetchall()]
             return results
-
-    # TODO:
     def del_doc_by_ids(self, ids: List[str]) -> bool:
         return super().del_doc_by_ids(ids)
 

server/knowledge_base/kb_summary/base.py

@@ -13,7 +13,6 @@ from server.db.repository.knowledge_metadata_repository import add_summary_to_db
 from langchain.docstore.document import Document
 
 
-# TODO 暂不考虑文件更新，需要重新删除相关文档，再重新添加
 class KBSummaryService(ABC):
     kb_name: str
     embed_model: str

server/knowledge_base/kb_summary/summary_chunk.py

@@ -112,12 +112,6 @@ class SummaryAdapter:
                          docs: List[DocumentWithVSId] = []) -> List[Document]:
 
         logger.info("start summary")
-        # TODO 暂不处理文档中涉及语义重复、上下文缺失、document was longer than the context length 的问题
-        # merge_docs = self._drop_overlap(docs)
-        # # 将merge_docs中的句子合并成一个文档
-        # text = self._join_docs(merge_docs)
-        # 根据段落于句子的分隔符，将文档分成chunk，每个chunk长度小于token_max长度
-
         """
         这个过程分成两个部分：
         1. 对每个文档进行处理，得到每个文档的摘要

server/knowledge_base/utils.py

@@ -174,7 +174,6 @@ def get_loader(loader_name: str, file_path: str, loader_kwargs: Dict = None):
             if encode_detect is None:
                 encode_detect = {"encoding": "utf-8"}
             loader_kwargs["encoding"] = encode_detect["encoding"]
-        ## TODO：支持更多的自定义CSV读取逻辑
 
     elif loader_name == "JSONLoader":
         loader_kwargs.setdefault("jq_schema", ".")

server/model_workers/azure.py

@@ -67,12 +67,10 @@ class AzureWorker(ApiModelWorker):
                         self.logger.error(f"请求 Azure API 时发生错误：{resp}")
 
     def get_embeddings(self, params):
-        # TODO: 支持embeddings
         print("embedding")
         print(params)
 
     def make_conv_template(self, conv_template: str = None, model_path: str = None) -> Conversation:
-        # TODO: 确认模板是否需要修改
         return conv.Conversation(
             name=self.model_names[0],
             system_message="You are a helpful, respectful and honest assistant.",

server/model_workers/baichuan.py

@@ -88,12 +88,10 @@ class BaiChuanWorker(ApiModelWorker):
                         yield data
 
     def get_embeddings(self, params):
-        # TODO: 支持embeddings
         print("embedding")
         print(params)
 
     def make_conv_template(self, conv_template: str = None, model_path: str = None) -> Conversation:
-        # TODO: 确认模板是否需要修改
         return conv.Conversation(
             name=self.model_names[0],
             system_message="",

server/model_workers/base.py

@@ -125,8 +125,6 @@ class ApiModelWorker(BaseModelWorker):
 
 
     def count_token(self, params):
-        # TODO：需要完善
-        # print("count token")
         prompt = params["prompt"]
         return {"count": len(str(prompt)), "error_code": 0}
 

server/model_workers/fangzhou.py

@@ -12,16 +12,16 @@ class FangZhouWorker(ApiModelWorker):
     """
 
     def __init__(
-        self,
+            self,
-        *,
+            *,
-        model_names: List[str] = ["fangzhou-api"],
+            model_names: List[str] = ["fangzhou-api"],
-        controller_addr: str = None,
+            controller_addr: str = None,
-        worker_addr: str = None,
+            worker_addr: str = None,
-        version: Literal["chatglm-6b-model"] = "chatglm-6b-model",
+            version: Literal["chatglm-6b-model"] = "chatglm-6b-model",
-        **kwargs,
+            **kwargs,
     ):
         kwargs.update(model_names=model_names, controller_addr=controller_addr, worker_addr=worker_addr)
-        kwargs.setdefault("context_len", 16384) # TODO: 不同的模型有不同的大小
+        kwargs.setdefault("context_len", 16384)
         super().__init__(**kwargs)
         self.version = version
 
@@ -53,15 +53,15 @@ class FangZhouWorker(ApiModelWorker):
             if error := resp.error:
                 if error.code_n > 0:
                     data = {
-                            "error_code": error.code_n,
+                        "error_code": error.code_n,
-                            "text": error.message,
+                        "text": error.message,
-                            "error": {
+                        "error": {
-                                "message": error.message,
+                            "message": error.message,
-                                "type": "invalid_request_error",
+                            "type": "invalid_request_error",
-                                "param": None,
+                            "param": None,
-                                "code": None,
+                            "code": None,
-                            }
                         }
+                    }
                     self.logger.error(f"请求方舟 API 时发生错误：{data}")
                     yield data
                 elif chunk := resp.choice.message.content:
@@ -77,7 +77,6 @@ class FangZhouWorker(ApiModelWorker):
                 break
 
     def get_embeddings(self, params):
-        # TODO: 支持embeddings
         print("embedding")
         print(params)
 

server/model_workers/gemini.py

@@ -95,7 +95,6 @@ class GeminiWorker(ApiModelWorker):
                 print("Invalid JSON string:", json_string)
 
     def get_embeddings(self, params):
-        # TODO: 支持embeddings
         print("embedding")
         print(params)
 

server/model_workers/minimax.py

@@ -37,7 +37,6 @@ class MiniMaxWorker(ApiModelWorker):
 
     def do_chat(self, params: ApiChatParams) -> Dict:
         # 按照官网推荐，直接调用abab 5.5模型
-        # TODO: 支持指定回复要求，支持指定用户名称、AI名称
         params.load_config(self.model_names[0])
 
         url = 'https://api.minimax.chat/v1/text/chatcompletion{pro}?GroupId={group_id}'
@@ -55,7 +54,7 @@ class MiniMaxWorker(ApiModelWorker):
             "temperature": params.temperature,
             "top_p": params.top_p,
             "tokens_to_generate": params.max_tokens or 1024,
-            # TODO: 以下参数为minimax特有，传入空值会出错。
+            # 以下参数为minimax特有，传入空值会出错。
             # "prompt": params.system_message or self.conv.system_message,
             # "bot_setting": [],
             # "role_meta": params.role_meta,
@@ -143,12 +142,10 @@ class MiniMaxWorker(ApiModelWorker):
             return {"code": 200, "data": result}
 
     def get_embeddings(self, params):
-        # TODO: 支持embeddings
         print("embedding")
         print(params)
 
     def make_conv_template(self, conv_template: str = None, model_path: str = None) -> Conversation:
-        # TODO: 确认模板是否需要修改
         return conv.Conversation(
             name=self.model_names[0],
             system_message="你是MiniMax自主研发的大型语言模型，回答问题简洁有条理。",

server/model_workers/qianfan.py

@@ -187,14 +187,11 @@ class QianFanWorker(ApiModelWorker):
                 i += batch_size
             return {"code": 200, "data": result}
 
-    # TODO: qianfan支持续写模型
     def get_embeddings(self, params):
-        # TODO: 支持embeddings
         print("embedding")
         print(params)
 
     def make_conv_template(self, conv_template: str = None, model_path: str = None) -> Conversation:
-        # TODO: 确认模板是否需要修改
         return conv.Conversation(
             name=self.model_names[0],
             system_message="你是一个聪明的助手，请根据用户的提示来完成任务",

server/model_workers/qwen.py

@@ -100,12 +100,10 @@ class QwenWorker(ApiModelWorker):
         return {"code": 200, "data": result}
 
     def get_embeddings(self, params):
-        # TODO: 支持embeddings
         print("embedding")
         print(params)
 
     def make_conv_template(self, conv_template: str = None, model_path: str = None) -> Conversation:
-        # TODO: 确认模板是否需要修改
         return conv.Conversation(
             name=self.model_names[0],
             system_message="你是一个聪明、对人类有帮助的人工智能，你可以对人类提出的问题给出有用、详细、礼貌的回答。",

server/model_workers/tiangong.py

@@ -70,12 +70,10 @@ class TianGongWorker(ApiModelWorker):
                     yield data
 
     def get_embeddings(self, params):
-        # TODO: 支持embeddings
         print("embedding")
         print(params)
 
     def make_conv_template(self, conv_template: str = None, model_path: str = None) -> Conversation:
-        # TODO: 确认模板是否需要修改
         return conv.Conversation(
             name=self.model_names[0],
             system_message="",

server/model_workers/xinghuo.py

@@ -42,7 +42,6 @@ class XingHuoWorker(ApiModelWorker):
         self.version = version
 
     def do_chat(self, params: ApiChatParams) -> Dict:
-        # TODO: 当前每次对话都要重新连接websocket，确认是否可以保持连接
         params.load_config(self.model_names[0])
 
         version_mapping = {
@@ -73,12 +72,10 @@ class XingHuoWorker(ApiModelWorker):
                 yield {"error_code": 0, "text": text}
 
     def get_embeddings(self, params):
-        # TODO: 支持embeddings
         print("embedding")
         print(params)
 
     def make_conv_template(self, conv_template: str = None, model_path: str = None) -> Conversation:
-        # TODO: 确认模板是否需要修改
         return conv.Conversation(
             name=self.model_names[0],
             system_message="你是一个聪明的助手，请根据用户的提示来完成任务",

server/utils.py

@@ -36,7 +36,6 @@ async def wrap_done(fn: Awaitable, event: asyncio.Event):
         await fn
     except Exception as e:
         logging.exception(e)
-        # TODO: handle exception
         msg = f"Caught exception: {e}"
         logger.error(f'{e.__class__.__name__}: {msg}',
                      exc_info=e if log_verbose else None)
@@ -404,7 +403,7 @@ def fschat_controller_address() -> str:
 
 
 def fschat_model_worker_address(model_name: str = LLM_MODELS[0]) -> str:
-    if model := get_model_worker_config(model_name):  # TODO: depends fastchat
+    if model := get_model_worker_config(model_name):
         host = model["host"]
         if host == "0.0.0.0":
             host = "127.0.0.1"
@@ -449,7 +448,7 @@ def get_prompt_template(type: str, name: str) -> Optional[str]:
 
     from configs import prompt_config
     import importlib
-    importlib.reload(prompt_config)  # TODO: 检查configs/prompt_config.py文件有修改再重新加载
+    importlib.reload(prompt_config)
     return prompt_config.PROMPT_TEMPLATES[type].get(name)
 
 
@@ -550,7 +549,7 @@ def run_in_thread_pool(
             thread = pool.submit(func, **kwargs)
             tasks.append(thread)
 
-        for obj in as_completed(tasks):  # TODO: Ctrl+c无法停止
+        for obj in as_completed(tasks):
             yield obj.result()
 
 

startup.py

@@ -418,7 +418,7 @@ def run_openai_api(log_level: str = "INFO", started_event: mp.Event = None):
     set_httpx_config()
 
     controller_addr = fschat_controller_address()
-    app = create_openai_api_app(controller_addr, log_level=log_level)  # TODO: not support keys yet.
+    app = create_openai_api_app(controller_addr, log_level=log_level)
     _set_app_event(app, started_event)
 
     host = FSCHAT_OPENAI_API["host"]

webui_pages/dialogue/dialogue.py

@@ -126,7 +126,6 @@ def dialogue_page(api: ApiRequest, is_lite: bool = False):
         chat_box.use_chat_name(conversation_name)
         conversation_id = st.session_state["conversation_ids"][conversation_name]
 
-        # TODO: 对话模型与会话绑定
         def on_mode_change():
             mode = st.session_state.dialogue_mode
             text = f"已切换到 {mode} 模式。"