mirror of
https://github.com/RYDE-WORK/Langchain-Chatchat.git
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9b62b1c72b
* dev分支解决pydantic版本冲突问题，增加ollama配置，支持ollama会话和向量接口 1、因dev版本的pydantic升级到了v2版本，由于在class History(BaseModel)中使用了from server.pydantic_v1，而fastapi的引用已变为pydantic的v2版本，所以fastapi用v2版本去校验用v1版本定义的对象，当会话历史histtory不为空的时候，会报错：TypeError: BaseModel.validate() takes 2 positional arguments but 3 were given。经测试，解方法为在class History(BaseModel)中也使用v2版本即可; 2、配置文件参照其它平台配置，增加了ollama平台相关配置，会话模型用户可根据实际情况自行添加，向量模型目前支持nomic-embed-text（必须升级ollama到0.1.29以上）。 3、因ollama官方只在会话部分对openai api做了兼容，向量api暂未适配，好在langchain官方库支持OllamaEmbeddings，因而在get_Embeddings方法中添加了相关支持代码。 * 修复 pydantic 升级到 v2 后 DocumentWithVsID 和 /v1/embeddings 兼容性问题 --------- Co-authored-by: srszzw <srszzw@163.com> Co-authored-by: liunux4odoo <liunux@qq.com>
89 lines
3.1 KiB
Python
89 lines
3.1 KiB
Python
from __future__ import annotations
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from typing import List
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from fastapi import APIRouter, Request
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from server.chat.file_chat import upload_temp_docs
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from server.knowledge_base.kb_api import list_kbs, create_kb, delete_kb
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from server.knowledge_base.kb_doc_api import (list_files, upload_docs, delete_docs,
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update_docs, download_doc, recreate_vector_store,
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search_docs, update_info)
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from server.knowledge_base.kb_summary_api import (summary_file_to_vector_store, recreate_summary_vector_store,
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summary_doc_ids_to_vector_store)
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from server.utils import BaseResponse, ListResponse
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kb_router = APIRouter(prefix="/knowledge_base", tags=["Knowledge Base Management"])
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kb_router.get("/list_knowledge_bases",
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response_model=ListResponse,
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summary="获取知识库列表")(list_kbs)
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kb_router.post("/create_knowledge_base",
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response_model=BaseResponse,
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summary="创建知识库"
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)(create_kb)
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kb_router.post("/delete_knowledge_base",
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response_model=BaseResponse,
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summary="删除知识库"
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)(delete_kb)
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kb_router.get("/list_files",
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response_model=ListResponse,
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summary="获取知识库内的文件列表"
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)(list_files)
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kb_router.post("/search_docs",
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response_model=List[dict],
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summary="搜索知识库"
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)(search_docs)
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kb_router.post("/upload_docs",
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response_model=BaseResponse,
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summary="上传文件到知识库，并/或进行向量化"
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)(upload_docs)
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kb_router.post("/delete_docs",
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response_model=BaseResponse,
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summary="删除知识库内指定文件"
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)(delete_docs)
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kb_router.post("/update_info",
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response_model=BaseResponse,
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summary="更新知识库介绍"
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)(update_info)
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kb_router.post("/update_docs",
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response_model=BaseResponse,
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summary="更新现有文件到知识库"
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)(update_docs)
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kb_router.get("/download_doc",
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summary="下载对应的知识文件")(download_doc)
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kb_router.post("/recreate_vector_store",
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summary="根据content中文档重建向量库，流式输出处理进度。"
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)(recreate_vector_store)
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kb_router.post("/upload_temp_docs",
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summary="上传文件到临时目录，用于文件对话。"
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)(upload_temp_docs)
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summary_router = APIRouter(prefix="/kb_summary_api")
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summary_router.post("/summary_file_to_vector_store",
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summary="单个知识库根据文件名称摘要"
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)(summary_file_to_vector_store)
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summary_router.post("/summary_doc_ids_to_vector_store",
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summary="单个知识库根据doc_ids摘要",
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response_model=BaseResponse,
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)(summary_doc_ids_to_vector_store)
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summary_router.post("/recreate_summary_vector_store",
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summary="重建单个知识库文件摘要"
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)(recreate_summary_vector_store)
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kb_router.include_router(summary_router)
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