RYDE-WORK/Langchain-Chatchat
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删除本地fschat配置,pydantic升级到2

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glide-the 2024-01-21 18:24:33 +08:00 committed by liunux4odoo
parent 777b7c3499
commit 175db6710e
4 changed files with 8 additions and 9 deletions
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2
server/agent/agent_factory/__init__.py
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@ -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 from .qwen_agent import create_structured_qwen_chat_agent

6
server/agent/agent_factory/agents_registry.py
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@ -8,8 +8,7 @@ from langchain_core.messages import SystemMessage
from langchain_core.prompts import ChatPromptTemplate from langchain_core.prompts import ChatPromptTemplate
from langchain_core.tools import BaseTool from langchain_core.tools import BaseTool
from server.agent.agent_factory import (create_structured_glm3_chat_agent, from server.agent.agent_factory import ( create_structured_qwen_chat_agent)
create_structured_qwen_chat_agent)
def agents_registry( def agents_registry(
@ -24,7 +23,8 @@ def agents_registry(
# Write any optimized method here. # Write any optimized method here.
if "glm3" in llm.model_name.lower(): if "glm3" in llm.model_name.lower():
# An optimized method of langchain Agent that uses the glm3 series model # 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(): elif "qwen" in llm.model_name.lower():
agent = create_structured_qwen_chat_agent(llm=llm, tools=tools) agent = create_structured_qwen_chat_agent(llm=llm, tools=tools)
else: else:

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

3
startup.py
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@ -147,7 +147,6 @@ def parse_args() -> argparse.ArgumentParser:
def dump_server_info(after_start=False, args=None): def dump_server_info(after_start=False, args=None):
import platform import platform
import langchain import langchain
import fastchat
from server.utils import api_address, webui_address from server.utils import api_address, webui_address
print("\n") 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"操作系统：{platform.platform()}.")
print(f"python版本：{sys.version}") print(f"python版本：{sys.version}")
print(f"项目版本：{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("\n")
print(f"当前使用的分词器：{TEXT_SPLITTER_NAME}") print(f"当前使用的分词器：{TEXT_SPLITTER_NAME}")