mirror of
https://github.com/RYDE-WORK/Langchain-Chatchat.git
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* update ApiRequest: 删除no_remote_api本地调用模式;支持同步/异步调用 * 实现API和WEBUI的分离: - API运行服务器上的配置通过/llm_model/get_model_config、/server/configs接口提供,WEBUI运行机器上的配置项仅作为代码内部默认值使用 - 服务器可用的搜索引擎通过/server/list_search_engines提供 - WEBUI可选LLM列表中只列出在FSCHAT_MODEL_WORKERS中配置的模型 - 修改WEBUI中默认LLM_MODEL获取方式,改为从api端读取 - 删除knowledge_base_chat中`local_doc_url`参数 其它修改: - 删除多余的kb_config.py.exmaple(名称错误) - server_config中默认关闭vllm - server_config中默认注释除智谱AI之外的在线模型 - 修改requests从系统获取的代理,避免model worker注册错误 * 修正: - api.list_config_models返回模型原始配置 - api.list_config_models和api.get_model_config中过滤online api模型的敏感信息 - 将GPT等直接访问的模型列入WEBUI可选模型列表 其它: - 指定langchain==0.3.313, fschat==0.2.30, langchain-experimental==0.0.30
162 lines
4.6 KiB
Python
162 lines
4.6 KiB
Python
import requests
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import json
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import sys
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from pathlib import Path
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root_path = Path(__file__).parent.parent.parent
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sys.path.append(str(root_path))
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from server.utils import api_address
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from configs import VECTOR_SEARCH_TOP_K
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from server.knowledge_base.utils import get_kb_path, get_file_path
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from webui_pages.utils import ApiRequest
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from pprint import pprint
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api_base_url = api_address()
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api: ApiRequest = ApiRequest(api_base_url)
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kb = "kb_for_api_test"
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test_files = {
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"FAQ.MD": str(root_path / "docs" / "FAQ.MD"),
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"README.MD": str(root_path / "README.MD"),
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"test.txt": get_file_path("samples", "test.txt"),
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}
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print("\n\nApiRquest调用\n")
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def test_delete_kb_before():
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if not Path(get_kb_path(kb)).exists():
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return
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data = api.delete_knowledge_base(kb)
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pprint(data)
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assert data["code"] == 200
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assert isinstance(data["data"], list) and len(data["data"]) > 0
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assert kb not in data["data"]
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def test_create_kb():
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print(f"\n尝试用空名称创建知识库:")
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data = api.create_knowledge_base(" ")
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pprint(data)
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assert data["code"] == 404
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assert data["msg"] == "知识库名称不能为空,请重新填写知识库名称"
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print(f"\n创建新知识库: {kb}")
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data = api.create_knowledge_base(kb)
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pprint(data)
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assert data["code"] == 200
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assert data["msg"] == f"已新增知识库 {kb}"
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print(f"\n尝试创建同名知识库: {kb}")
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data = api.create_knowledge_base(kb)
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pprint(data)
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assert data["code"] == 404
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assert data["msg"] == f"已存在同名知识库 {kb}"
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def test_list_kbs():
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data = api.list_knowledge_bases()
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pprint(data)
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assert isinstance(data, list) and len(data) > 0
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assert kb in data
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def test_upload_docs():
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files = list(test_files.values())
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print(f"\n上传知识文件")
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data = {"knowledge_base_name": kb, "override": True}
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data = api.upload_kb_docs(files, **data)
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pprint(data)
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assert data["code"] == 200
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assert len(data["data"]["failed_files"]) == 0
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print(f"\n尝试重新上传知识文件, 不覆盖")
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data = {"knowledge_base_name": kb, "override": False}
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data = api.upload_kb_docs(files, **data)
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pprint(data)
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assert data["code"] == 200
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assert len(data["data"]["failed_files"]) == len(test_files)
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print(f"\n尝试重新上传知识文件, 覆盖,自定义docs")
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docs = {"FAQ.MD": [{"page_content": "custom docs", "metadata": {}}]}
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data = {"knowledge_base_name": kb, "override": True, "docs": docs}
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data = api.upload_kb_docs(files, **data)
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pprint(data)
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assert data["code"] == 200
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assert len(data["data"]["failed_files"]) == 0
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def test_list_files():
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print("\n获取知识库中文件列表:")
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data = api.list_kb_docs(knowledge_base_name=kb)
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pprint(data)
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assert isinstance(data, list)
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for name in test_files:
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assert name in data
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def test_search_docs():
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query = "介绍一下langchain-chatchat项目"
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print("\n检索知识库:")
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print(query)
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data = api.search_kb_docs(query, kb)
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pprint(data)
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assert isinstance(data, list) and len(data) == VECTOR_SEARCH_TOP_K
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def test_update_docs():
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print(f"\n更新知识文件")
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data = api.update_kb_docs(knowledge_base_name=kb, file_names=list(test_files))
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pprint(data)
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assert data["code"] == 200
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assert len(data["data"]["failed_files"]) == 0
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def test_delete_docs():
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print(f"\n删除知识文件")
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data = api.delete_kb_docs(knowledge_base_name=kb, file_names=list(test_files))
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pprint(data)
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assert data["code"] == 200
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assert len(data["data"]["failed_files"]) == 0
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query = "介绍一下langchain-chatchat项目"
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print("\n尝试检索删除后的检索知识库:")
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print(query)
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data = api.search_kb_docs(query, kb)
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pprint(data)
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assert isinstance(data, list) and len(data) == 0
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def test_recreate_vs():
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print("\n重建知识库:")
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r = api.recreate_vector_store(kb)
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for data in r:
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assert isinstance(data, dict)
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assert data["code"] == 200
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print(data["msg"])
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query = "本项目支持哪些文件格式?"
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print("\n尝试检索重建后的检索知识库:")
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print(query)
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data = api.search_kb_docs(query, kb)
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pprint(data)
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assert isinstance(data, list) and len(data) == VECTOR_SEARCH_TOP_K
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def test_delete_kb_after():
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print("\n删除知识库")
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data = api.delete_knowledge_base(kb)
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pprint(data)
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# check kb not exists anymore
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print("\n获取知识库列表:")
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data = api.list_knowledge_bases()
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pprint(data)
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assert isinstance(data, list) and len(data) > 0
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assert kb not in data
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