删除本地fschat配置,pydantic升级到2

server/agent/agent_factory/__init__.py

@@ -1,2 +1,2 @@
-from .glm3_agent import create_structured_glm3_chat_agent
+# from .glm3_agent import create_structured_glm3_chat_agent
 from .qwen_agent import create_structured_qwen_chat_agent

server/agent/agent_factory/agents_registry.py

@@ -8,8 +8,7 @@ from langchain_core.messages import SystemMessage
 from langchain_core.prompts import ChatPromptTemplate
 from langchain_core.tools import BaseTool
 
-from server.agent.agent_factory import (create_structured_glm3_chat_agent,
-                                        create_structured_qwen_chat_agent)
+from server.agent.agent_factory import ( create_structured_qwen_chat_agent)
 
 
 def agents_registry(
@@ -24,7 +23,8 @@ def agents_registry(
     # Write any optimized method here.
     if "glm3" in llm.model_name.lower():
         # An optimized method of langchain Agent that uses the glm3 series model
-        agent = create_structured_glm3_chat_agent(llm=llm, tools=tools)
+        # agent = create_structured_glm3_chat_agent(llm=llm, tools=tools)
+        pass
     elif "qwen" in llm.model_name.lower():
         agent = create_structured_qwen_chat_agent(llm=llm, tools=tools)
     else:

server/embeddings_api.py

@@ -1,6 +1,6 @@
 from langchain.docstore.document import Document
 from configs import EMBEDDING_MODEL, logger
-from server.model_workers.base import ApiEmbeddingsParams
+# from server.model_workers.base import ApiEmbeddingsParams
 from server.utils import BaseResponse, get_model_worker_config, list_embed_models, list_online_embed_models
 from fastapi import Body
 from fastapi.concurrency import run_in_threadpool
@@ -30,8 +30,8 @@ def embed_texts(
             embed_model = config.get("embed_model")
             worker = worker_class()
             if worker_class.can_embedding():
-                params = ApiEmbeddingsParams(texts=texts, to_query=to_query, embed_model=embed_model)
-                resp = worker.do_embeddings(params)
+                # params = ApiEmbeddingsParams(texts=texts, to_query=to_query)
+                resp = worker.do_embeddings(None)
                 return BaseResponse(**resp)
 
         return BaseResponse(code=500, msg=f"指定的模型 {embed_model} 不支持 Embeddings 功能。")

startup.py

@@ -147,7 +147,6 @@ def parse_args() -> argparse.ArgumentParser:
 def dump_server_info(after_start=False, args=None):
     import platform
     import langchain
-    import fastchat
     from server.utils import api_address, webui_address
 
     print("\n")
@@ -155,7 +154,7 @@ def dump_server_info(after_start=False, args=None):
     print(f"操作系统：{platform.platform()}.")
     print(f"python版本：{sys.version}")
     print(f"项目版本：{VERSION}")
-    print(f"langchain版本：{langchain.__version__}. fastchat版本：{fastchat.__version__}")
+    print(f"langchain版本：{langchain.__version__}")
     print("\n")
 
     print(f"当前使用的分词器：{TEXT_SPLITTER_NAME}")