升级到langchain==0.0.287,fschat==0.0.28;处理langchain.Milvus bug(#10492) (#1454)

* 修复milvus_kb_service中一些bug，添加文档后将数据同步到数据库
* 升级到langchain==0.0.287,fschat==0.0.28;处理langchain.Milvus bug(#10492)
* 修复切换模型BUG: 从在线API切换模型时出错

configs/server_config.py.example

@@ -59,6 +59,7 @@ FSCHAT_MODEL_WORKERS = {
         # "limit_worker_concurrency": 5,
         # "stream_interval": 2,
         # "no_register": False,
+        # "embed_in_truncate": False,
     },
     "baichuan-7b": { # 使用default中的IP和端口
         "device": "cpu",

requirements.txt

@@ -1,8 +1,8 @@
-langchain==0.0.266
+langchain==0.0.287
+fschat[model_worker]==0.2.28
 openai
 zhipuai
 sentence_transformers
-fschat==0.2.24
 transformers>=4.31.0
 torch~=2.0.0
 fastapi~=0.99.1

requirements_api.txt

@@ -1,7 +1,7 @@
-langchain==0.0.266
+langchain==0.0.287
+fschat[model_worker]==0.2.28
 openai
 sentence_transformers
-fschat==0.2.24
 transformers>=4.31.0
 torch~=2.0.0
 fastapi~=0.99.1

server/knowledge_base/kb_service/milvus_kb_service.py

@@ -68,10 +68,14 @@ class MilvusKBService(KBService):
         return score_threshold_process(score_threshold, top_k, self.milvus.similarity_search_with_score(query, top_k))
 
     def do_add_doc(self, docs: List[Document], **kwargs) -> List[Dict]:
-        # TODO: workaround for bug #10492 in langchain==0.0.286
+        # TODO: workaround for bug #10492 in langchain
         for doc in docs:
+            for k, v in doc.metadata.items():
+                doc.metadata[k] = str(v)
             for field in self.milvus.fields:
                 doc.metadata.setdefault(field, "")
+            doc.metadata.pop(self.milvus._text_field, None)
+            doc.metadata.pop(self.milvus._vector_field, None)
 
         ids = self.milvus.add_documents(docs)
         doc_infos = [{"id": id, "metadata": doc.metadata} for id, doc in zip(ids, docs)]

server/knowledge_base/utils.py

@@ -82,16 +82,16 @@ SUPPORTED_EXTS = [ext for sublist in LOADER_DICT.values() for ext in sublist]
 
 class CustomJSONLoader(langchain.document_loaders.JSONLoader):
     '''
-    langchain的JSONLoader需要jq，在win上使用不便，进行替代。
+    langchain的JSONLoader需要jq，在win上使用不便，进行替代。针对langchain==0.0.286
     '''
 
     def __init__(
-            self,
-            file_path: Union[str, Path],
-            content_key: Optional[str] = None,
-            metadata_func: Optional[Callable[[Dict, Dict], Dict]] = None,
-            text_content: bool = True,
-            json_lines: bool = False,
+        self,
+        file_path: Union[str, Path],
+        content_key: Optional[str] = None,
+        metadata_func: Optional[Callable[[Dict, Dict], Dict]] = None,
+        text_content: bool = True,
+        json_lines: bool = False,
     ):
         """Initialize the JSONLoader.
 
@@ -113,21 +113,6 @@ class CustomJSONLoader(langchain.document_loaders.JSONLoader):
         self._text_content = text_content
         self._json_lines = json_lines
 
-    # TODO: langchain's JSONLoader.load has a encoding bug, raise gbk encoding error on windows.
-    # This is a workaround for langchain==0.0.266. I have make a pr(#9785) to langchain, it should be deleted after langchain upgraded.
-    def load(self) -> List[Document]:
-        """Load and return documents from the JSON file."""
-        docs: List[Document] = []
-        if self._json_lines:
-            with self.file_path.open(encoding="utf-8") as f:
-                for line in f:
-                    line = line.strip()
-                    if line:
-                        self._parse(line, docs)
-        else:
-            self._parse(self.file_path.read_text(encoding="utf-8"), docs)
-        return docs
-
     def _parse(self, content: str, docs: List[Document]) -> None:
         """Convert given content to documents."""
         data = json.loads(content)
@@ -137,13 +122,14 @@ class CustomJSONLoader(langchain.document_loaders.JSONLoader):
         # and prevent the user from getting a cryptic error later on.
         if self._content_key is not None:
             self._validate_content_key(data)
+        if self._metadata_func is not None:
+            self._validate_metadata_func(data)
 
         for i, sample in enumerate(data, len(docs) + 1):
-            metadata = dict(
-                source=str(self.file_path),
-                seq_num=i,
+            text = self._get_text(sample=sample)
+            metadata = self._get_metadata(
+                sample=sample, source=str(self.file_path), seq_num=i
             )
-            text = self._get_text(sample=sample, metadata=metadata)
             docs.append(Document(page_content=text, metadata=metadata))
 
 

startup.py

@@ -88,6 +88,7 @@ def create_model_worker_app(log_level: str = "INFO", **kwargs) -> FastAPI:
     args.limit_worker_concurrency = 5
     args.stream_interval = 2
     args.no_register = False
+    args.embed_in_truncate = False
 
     for k, v in kwargs.items():
         setattr(args, k, v)
@@ -148,6 +149,7 @@ def create_model_worker_app(log_level: str = "INFO", **kwargs) -> FastAPI:
             awq_config=awq_config,
             stream_interval=args.stream_interval,
             conv_template=args.conv_template,
+            embed_in_truncate=args.embed_in_truncate,
         )
         sys.modules["fastchat.serve.model_worker"].args = args
         sys.modules["fastchat.serve.model_worker"].gptq_config = gptq_config

tests/api/test_kb_api_request.py

@@ -14,7 +14,7 @@ from pprint import pprint
 
 
 api_base_url = api_address()
-api: ApiRequest = ApiRequest(api_base_url, no_remote_api=True)
+api: ApiRequest = ApiRequest(api_base_url, no_remote_api=False)
 
 
 kb = "kb_for_api_test"

tests/api/test_llm_api.py

@@ -7,7 +7,7 @@ root_path = Path(__file__).parent.parent.parent
 sys.path.append(str(root_path))
 from configs.server_config import FSCHAT_MODEL_WORKERS
 from configs.model_config import LLM_MODEL, llm_model_dict
-from server.utils import api_address
+from server.utils import api_address, get_model_worker_config
 
 from pprint import pprint
 import random
@@ -65,7 +65,8 @@ def test_change_model(api="/llm_model/change"):
     assert len(availabel_new_models) > 0
     print(availabel_new_models)
 
-    model_name = random.choice(running_models)
+    local_models = [x for x in running_models if not get_model_worker_config(x).get("online_api")]
+    model_name = random.choice(local_models)
     new_model_name = random.choice(availabel_new_models)
     print(f"\n尝试将模型从 {model_name} 切换到 {new_model_name}")
     r = requests.post(url, json={"model_name": model_name, "new_model_name": new_model_name})

webui_pages/dialogue/dialogue.py

@@ -80,7 +80,7 @@ def dialogue_page(api: ApiRequest):
             if x in config_models:
                 config_models.remove(x)
         llm_models = running_models + config_models
-        cur_model = st.session_state.get("prev_llm_model", LLM_MODEL)
+        cur_model = st.session_state.get("cur_llm_model", LLM_MODEL)
         index = llm_models.index(cur_model)
         llm_model = st.selectbox("选择LLM模型：",
                                 llm_models,
@@ -93,7 +93,7 @@ def dialogue_page(api: ApiRequest):
             and not get_model_worker_config(llm_model).get("online_api")):
             with st.spinner(f"正在加载模型： {llm_model}，请勿进行操作或刷新页面"):
                 r = api.change_llm_model(st.session_state.get("prev_llm_model"), llm_model)
-            st.session_state["prev_llm_model"] = llm_model
+        st.session_state["cur_llm_model"] = llm_model
 
         history_len = st.number_input("历史对话轮数：", 0, 10, HISTORY_LEN)