ColossalAI/applications/ColossalQA/tests/test_retrieval_qa.py
YeAnbang e53e729d8e
[Feature] Add document retrieval QA (#5020)
* add langchain

* add langchain

* Add files via upload

* add langchain

* fix style

* fix style: remove extra space

* add pytest; modified retriever

* add pytest; modified retriever

* add tests to build_on_pr.yml

* fix build_on_pr.yml

* fix build on pr; fix environ vars

* seperate unit tests for colossalqa from build from pr

* fix container setting; fix environ vars

* commented dev code

* add incremental update

* remove stale code

* fix style

* change to sha3 224

* fix retriever; fix style; add unit test for document loader

* fix ci workflow config

* fix ci workflow config

* add set cuda visible device script in ci

* fix doc string

* fix style; update readme; refactored

* add force log info

* change build on pr, ignore colossalqa

* fix docstring, captitalize all initial letters

* fix indexing; fix text-splitter

* remove debug code, update reference

* reset previous commit

* update LICENSE update README add key-value mode, fix bugs

* add files back

* revert force push

* remove junk file

* add test files

* fix retriever bug, add intent classification

* change conversation chain design

* rewrite prompt and conversation chain

* add ui v1

* ui v1

* fix atavar

* add header

* Refactor the RAG Code and support Pangu

* Refactor the ColossalQA chain to Object-Oriented Programming and the UI demo.

* resolved conversation. tested scripts under examples. web demo still buggy

* fix ci tests

* Some modifications to add ChatGPT api

* modify llm.py and remove unnecessary files

* Delete applications/ColossalQA/examples/ui/test_frontend_input.json

* Remove OpenAI api key

* add colossalqa

* move files

* move files

* move files

* move files

* fix style

* Add Readme and fix some bugs.

* Add something to readme and modify some code

* modify a directory name for clarity

* remove redundant directory

* Correct a type in  llm.py

* fix AI prefix

* fix test_memory.py

* fix conversation

* fix some erros and typos

* Fix a missing import in RAG_ChatBot.py

* add colossalcloud LLM wrapper, correct issues in code review

---------

Co-authored-by: YeAnbang <anbangy2@outlook.com>
Co-authored-by: Orion-Zheng <zheng_zian@u.nus.edu>
Co-authored-by: Zian(Andy) Zheng <62330719+Orion-Zheng@users.noreply.github.com>
Co-authored-by: Orion-Zheng <zhengzian@u.nus.edu>
2023-11-23 10:33:48 +08:00

63 lines
2.9 KiB
Python

import os
from colossalqa.retrieval_conversation_universal import UniversalRetrievalConversation
def test_en_retrievalQA():
data_path_en = os.environ.get('TEST_DATA_PATH_EN')
data_path_zh = os.environ.get('TEST_DATA_PATH_ZH')
en_model_path = os.environ.get('EN_MODEL_PATH')
zh_model_path = os.environ.get('ZH_MODEL_PATH')
zh_model_name = os.environ.get('ZH_MODEL_NAME')
en_model_name = os.environ.get('EN_MODEL_NAME')
sql_file_path = os.environ.get('SQL_FILE_PATH')
qa_session = UniversalRetrievalConversation(files_en=[{
'data_path': data_path_en,
'name': 'company information',
'separator': '\n'
}],
files_zh=[{
'data_path': data_path_zh,
'name': 'company information',
'separator': '\n'
}],
zh_model_path=zh_model_path,
en_model_path=en_model_path,
zh_model_name=zh_model_name,
en_model_name=en_model_name,
sql_file_path=sql_file_path)
ans = qa_session.run("which company runs business in hotel industry?", which_language='en')
print(ans)
def test_zh_retrievalQA():
data_path_en = os.environ.get('TEST_DATA_PATH_EN')
data_path_zh = os.environ.get('TEST_DATA_PATH_ZH')
en_model_path = os.environ.get('EN_MODEL_PATH')
zh_model_path = os.environ.get('ZH_MODEL_PATH')
zh_model_name = os.environ.get('ZH_MODEL_NAME')
en_model_name = os.environ.get('EN_MODEL_NAME')
sql_file_path = os.environ.get('SQL_FILE_PATH')
qa_session = UniversalRetrievalConversation(files_en=[{
'data_path': data_path_en,
'name': 'company information',
'separator': '\n'
}],
files_zh=[{
'data_path': data_path_zh,
'name': 'company information',
'separator': '\n'
}],
zh_model_path=zh_model_path,
en_model_path=en_model_path,
zh_model_name=zh_model_name,
en_model_name=en_model_name,
sql_file_path=sql_file_path)
ans = qa_session.run("哪家公司在经营酒店业务?", which_language='zh')
print(ans)
if __name__ == "__main__":
test_en_retrievalQA()
test_zh_retrievalQA()