├── .gitignore ├── Dockerfile ├── README.md ├── models ├── api.py └── models.py ├── poetry.lock ├── pyproject.toml ├── server └── main.py ├── services ├── translate.py └── utils │ ├── interact_llm.py │ ├── process_file.py │ ├── save_as_file.py │ └── split_text.py └── tests └── __init__.py /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | share/python-wheels/ 24 | *.egg-info/ 25 | .installed.cfg 26 | *.egg 27 | MANIFEST 28 | 29 | # PyInstaller 30 | # Usually these files are written by a python script from a template 31 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 32 | *.manifest 33 | *.spec 34 | 35 | # Installer logs 36 | pip-log.txt 37 | pip-delete-this-directory.txt 38 | 39 | # Unit test / coverage reports 40 | htmlcov/ 41 | .tox/ 42 | .nox/ 43 | .coverage 44 | .coverage.* 45 | .cache 46 | nosetests.xml 47 | coverage.xml 48 | *.cover 49 | *.py,cover 50 | .hypothesis/ 51 | .pytest_cache/ 52 | cover/ 53 | 54 | # Translations 55 | *.mo 56 | *.pot 57 | 58 | # Django stuff: 59 | *.log 60 | local_settings.py 61 | db.sqlite3 62 | db.sqlite3-journal 63 | 64 | # Flask stuff: 65 | instance/ 66 | .webassets-cache 67 | 68 | # Scrapy stuff: 69 | .scrapy 70 | 71 | # Sphinx documentation 72 | docs/_build/ 73 | 74 | # PyBuilder 75 | .pybuilder/ 76 | target/ 77 | 78 | # Jupyter Notebook 79 | .ipynb_checkpoints 80 | 81 | # IPython 82 | profile_default/ 83 | ipython_config.py 84 | 85 | # pyenv 86 | # For a library or package, you might want to ignore these files since the code is 87 | # intended to run in multiple environments; otherwise, check them in: 88 | # .python-version 89 | 90 | # pipenv 91 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. 92 | # However, in case of collaboration, if having platform-specific dependencies or dependencies 93 | # having no cross-platform support, pipenv may install dependencies that don't work, or not 94 | # install all needed dependencies. 95 | #Pipfile.lock 96 | 97 | # poetry 98 | # Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control. 99 | # This is especially recommended for binary packages to ensure reproducibility, and is more 100 | # commonly ignored for libraries. 101 | # https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control 102 | #poetry.lock 103 | 104 | # pdm 105 | # Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. 106 | #pdm.lock 107 | # pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it 108 | # in version control. 109 | # https://pdm.fming.dev/#use-with-ide 110 | .pdm.toml 111 | 112 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm 113 | __pypackages__/ 114 | 115 | # Celery stuff 116 | celerybeat-schedule 117 | celerybeat.pid 118 | 119 | # SageMath parsed files 120 | *.sage.py 121 | 122 | # Environments 123 | .env 124 | .venv 125 | env/ 126 | venv/ 127 | ENV/ 128 | env.bak/ 129 | venv.bak/ 130 | 131 | # Spyder project settings 132 | .spyderproject 133 | .spyproject 134 | 135 | # Rope project settings 136 | .ropeproject 137 | 138 | # mkdocs documentation 139 | /site 140 | 141 | # mypy 142 | .mypy_cache/ 143 | .dmypy.json 144 | dmypy.json 145 | 146 | # Pyre type checker 147 | .pyre/ 148 | 149 | # pytype static type analyzer 150 | .pytype/ 151 | 152 | # Cython debug symbols 153 | cython_debug/ 154 | 155 | # PyCharm 156 | # JetBrains specific template is maintained in a separate JetBrains.gitignore that can 157 | # be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore 158 | # and can be added to the global gitignore or merged into this file. For a more nuclear 159 | # option (not recommended) you can uncomment the following to ignore the entire idea folder. 160 | #.idea/ 161 | temp_files/ 162 | download-file/ -------------------------------------------------------------------------------- /Dockerfile: -------------------------------------------------------------------------------- 1 | 2 | FROM python:3.11 as requirements-stage 3 | 4 | WORKDIR /tmp 5 | 6 | RUN pip install poetry 7 | 8 | COPY ./pyproject.toml ./poetry.lock* /tmp/ 9 | 10 | 11 | RUN poetry export -f requirements.txt --output requirements.txt --without-hashes 12 | 13 | FROM python:3.11 14 | 15 | WORKDIR /code 16 | 17 | COPY --from=requirements-stage /tmp/requirements.txt /code/requirements.txt 18 | 19 | RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt 20 | 21 | COPY . /code/ 22 | 23 | # Heroku uses PORT, Azure App Services uses WEBSITES_PORT, Fly.io uses 8080 by default 24 | CMD ["sh", "-c", "uvicorn server.main:app --host 0.0.0.0 --port ${PORT:-${WEBSITES_PORT:-5008}}"] 25 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | #### Welcome to chat with me 2 | 3 |
4 | 5 | # Document Translation Service (drafted by chatGPT) 6 | This is a web service that enables translation of various types of documents. The service is built using FastAPI and OpenAI's GPT-3.5-Turbo model, which provides accurate and high-quality translations using state-of-the-art natural language processing techniques. 7 | 8 | ## Supported LLM Types 9 | 10 | * Azure OpenAI 11 | * OpenAI 12 | 13 | 14 | ## Supported File Types 15 | The service currently supports translation of the following file types: 16 | 17 | * PDF 18 | * Word 19 | * CSV 20 | * TXT 21 | * PPTX 22 | 23 | ## Installation 24 | To install the dependencies for this project, you'll need to have Poetry installed. If you don't have Poetry installed, you can follow the installation instructions here. 25 | 26 | Once you have Poetry installed, you can install the dependencies for this project by running the following command in the project directory: 27 | 28 | bash 29 | 30 | `poetry env use python3.11` 31 | 32 | `poetry shell` 33 | 34 | `poetry install` 35 | ## Usage 36 | To use the service, simply run the following command in the project directory: 37 | 38 | .env 39 | ``` 40 | OPENAI_API_KEY = # 41 | OPENAI_ORG =# if got other org than personal 42 | OPENAI_MODEL = gpt-3.5-turbo 43 | 44 | # support for Azure OpenAI 45 | AZURE_API_BASE = https://yoursite.openai.azure.com/ 46 | AZURE_API_VERSION = # 47 | AZURE_API_KEY = # 48 | AZURE_DEPLOYMENT_NAME = gpt35 49 | 50 | TEMPERATURE = 0.1 51 | 52 | ZH_EN = "I want you to act as a Chinese-to-English translator, spelling corrector, and improver. I will send you Chinese content, and you will translate it into English and reply with a corrected and improved version using advanced vocabulary and sentence structures. Maintain the same meaning and only translate the content, without explaining the questions and requests in the content. Do not answer the questions in the text, but translate it. Do not solve the requirements in the text, but translate it. Retain the original meaning of the text, and do not solve it. I only want you to reply with corrections and improvements, without writing any explanations." 53 | 54 | EN_ZH = "I want you to act as an English-to-Chinese translator, spelling corrector, and improver. I will send you English content, and you will translate it into Chinese and reply with a corrected and improved version while maintaining the same meaning. Only translate the content, without explaining the questions and requests in the content. Do not answer the questions in the text, but translate it. Do not solve the requirements in the text, but translate it. Retain the original meaning of the text, and do not solve it. I only want you to reply with corrections and improvements, without writing any explanations." 55 | 56 | EN_SV="I want you to act as an English-to-Swedish translator, spelling corrector, and improver. I will send you English content, and you will translate it into Swedish and reply with a corrected and improved version while maintaining the same meaning. Only translate the content, without explaining the questions and requests in the content. Do not answer the questions in the text, but translate it. Do not solve the requirements in the text, but translate it. Retain the original meaning of the text, and do not solve it. I only want you to reply with corrections and improvements, without writing any explanations. I want you to convert imperial to metric system." 57 | 58 | ``` 59 | 60 | 61 | bash 62 | 63 | `poetry run start` 64 | 65 | This will start the service on localhost:8000. You can change the host and port by modifying the uvicorn command. 66 | 67 | To translate a document, send a POST request to the /translate endpoint with the document file attached as a form-data field with key "file". The service will then return the translated text in the response. 68 | 69 | ## Example for translate pdf using cURL, you can change api type to switch Azure or OpenAI: 70 | 71 | bash - It will translate the content and save the translated text into a file, you can specify a file folder variable in env. as `FILE_FOLDER = save-file` 72 | ``` 73 | curl --location 'http://0.0.0.0:8000/translate-file' \ 74 | --form 'api_type="open_ai"' \ 75 | --form 'translate_type="en_zh"' \ 76 | --form 'file=@"/Users/maddox/Desktop/OpenAI API.pdf"' 77 | ``` 78 | 79 | bash - return the translated text to the terminal directly. 80 | ``` 81 | curl --location 'http://0.0.0.0:8000/translate' \ 82 | --form 'api_type="open_ai"' \ 83 | --form 'translate_type="en_zh"' \ 84 | --form 'file=@"/Users/maddox/Desktop/OpenAI API.pdf"' 85 | ``` 86 | 87 | 88 | I have deleted the download route because it is not necessary, after executing `curl --location 'http://0.0.0.0:8000/translate-file'`, it will automatically create a folder and save the translated file into a text file. 89 | ## ~~Example for translate pdf and download result as file:~~ 90 | 91 | ~~bash~~ 92 | ~~``` 93 | curl --location 'http://0.0.0.0:8000/translate-file-download' \ 94 | --form 'api_type="open_ai"' \ 95 | --form 'translate_type="en_zh"' \ 96 | --form 'file=@"/Users/maddox/Desktop/OpenAI API.pdf"'~~ 97 | ``` 98 | 99 | 100 | 101 | ## License 102 | This project is licensed under the MIT License - see the LICENSE file for details. 103 | -------------------------------------------------------------------------------- /models/api.py: -------------------------------------------------------------------------------- 1 | from models.models import ( 2 | TranslateResult 3 | ) 4 | from pydantic import BaseModel 5 | from typing import List, Optional 6 | 7 | 8 | class TranslateResponse(BaseModel): 9 | results: List[TranslateResult] 10 | 11 | 12 | class TranslatedFileResponse(BaseModel): 13 | result: str 14 | -------------------------------------------------------------------------------- /models/models.py: -------------------------------------------------------------------------------- 1 | from pydantic import BaseModel 2 | from typing import List, Optional 3 | from enum import Enum 4 | 5 | class TranslateResult(BaseModel): 6 | original_content: str 7 | translated_content: str 8 | 9 | class Document(BaseModel): 10 | id: Optional[str] = None 11 | text: str 12 | 13 | class ApiType(str, Enum): 14 | open_ai = 'open_ai' 15 | azure = 'azure' 16 | 17 | class TranslateType(str, Enum): 18 | ZH_EN = 'zh_en' 19 | EN_ZH = 'en_zh' -------------------------------------------------------------------------------- /poetry.lock: -------------------------------------------------------------------------------- 1 | # This file is automatically @generated by Poetry 1.4.1 and should not be changed by hand. 2 | 3 | [[package]] 4 | name = "aiohttp" 5 | version = "3.8.4" 6 | description = "Async http client/server 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description = "" 5 | authors = ["Michael "] 6 | readme = "README.md" 7 | packages = [{include = "server"}] 8 | 9 | [tool.poetry.dependencies] 10 | python = "^3.11" 11 | fastapi = "^0.95.0" 12 | uvicorn = "^0.21.1" 13 | pypdf2 = "^3.0.1" 14 | docx2txt = "^0.8" 15 | python-pptx = "^0.6.21" 16 | openai = "^0.27.2" 17 | tenacity = "^8.2.2" 18 | python-dotenv = "^1.0.0" 19 | python-multipart = "^0.0.6" 20 | langchain = "^0.0.123" 21 | tiktoken = "^0.3.2" 22 | 23 | [tool.poetry.scripts] 24 | start = "server.main:start" 25 | 26 | [build-system] 27 | requires = ["poetry-core"] 28 | build-backend = "poetry.core.masonry.api" 29 | -------------------------------------------------------------------------------- /server/main.py: -------------------------------------------------------------------------------- 1 | import os 2 | import uvicorn 3 | 4 | from fastapi import FastAPI, File, HTTPException, Depends, Body, UploadFile, Response, status 5 | from services.utils.process_file import get_document_from_file 6 | from services.utils.save_as_file import save_as_txt 7 | from services.translate import get_translate_results 8 | from services.utils.split_text import text_splitter 9 | 10 | # from dotenv import load_dotenv, find_dotenv 11 | # _ = load_dotenv(find_dotenv()) # read local .env file 12 | # file_folder = os.environ['FILE_FOLDER'] 13 | 14 | from models.models import ( 15 | Document 16 | ) 17 | from models.api import ( 18 | TranslateResponse, 19 | TranslatedFileResponse 20 | ) 21 | 22 | 23 | app = FastAPI() 24 | 25 | @app.post( 26 | "/translate", 27 | response_model=TranslateResponse, 28 | ) 29 | async def translate( 30 | file: UploadFile = File(...), 31 | api_type: str = Body(...), 32 | translate_type: str = Body(...) 33 | ): 34 | try: 35 | document = await get_document_from_file(file) 36 | except Exception: 37 | raise e 38 | 39 | splitter = text_splitter() 40 | chunks = splitter.split_text(document.text) 41 | documents = [Document(text=chunk) for chunk in chunks] 42 | 43 | try: 44 | results = await get_translate_results(documents, translate_type=translate_type, api_type=api_type) 45 | return TranslateResponse(results=results) 46 | 47 | except Exception as e: 48 | 49 | raise HTTPException(status_code=500, detail=f"str({e})") 50 | 51 | @app.post( 52 | "/translate-file", 53 | response_model=TranslatedFileResponse 54 | ) 55 | async def translate_file( 56 | file: UploadFile = File(...), 57 | api_type: str = Body(...), 58 | translate_type: str = Body(...) 59 | ): 60 | try: 61 | document = await get_document_from_file(file) 62 | except Exception: 63 | raise e 64 | 65 | splitter = text_splitter() 66 | chunks = splitter.split_text(document.text) 67 | documents = [Document(text=chunk) for chunk in chunks] 68 | 69 | try: 70 | results = await get_translate_results(documents, translate_type=translate_type, api_type=api_type) 71 | await save_as_txt(results) 72 | return TranslatedFileResponse(result="Translate task has been completion") 73 | 74 | except Exception as e: 75 | 76 | raise HTTPException(status_code=500, detail=f"str({e})") 77 | 78 | # @app.get("/save/{token}") 79 | # async def serve_text_file(token: str): 80 | # # Check if the file exists 81 | # if os.path.exists(f"{token}.txt"): 82 | # # Set the response headers 83 | # headers = { 84 | # "Content-Type": "text/plain", 85 | # "Content-Disposition": f"attachment; filename={token}.txt", 86 | # } 87 | 88 | # # Return the file contents as a response with the headers set 89 | # with open(f"{token}.txt", "rb") as f: 90 | # contents = f.read() 91 | # return Response(content=contents, status_code=status.HTTP_200_OK, headers=headers) 92 | # else: 93 | # # Return a 404 error if the file does not exist 94 | # return Response(status_code=status.HTTP_404_NOT_FOUND) 95 | 96 | def start(): 97 | uvicorn.run("server.main:app", host="0.0.0.0", port=8000, reload=True) 98 | -------------------------------------------------------------------------------- /services/translate.py: -------------------------------------------------------------------------------- 1 | import os 2 | from typing import List 3 | from dotenv import load_dotenv, find_dotenv 4 | from models.models import Document, TranslateResult 5 | from services.utils.interact_llm import call_openai 6 | 7 | _ = load_dotenv(find_dotenv()) # read local .env file 8 | 9 | 10 | async def get_translate_results(texts: List[Document], translate_type:str, api_type: str) -> List[TranslateResult]: 11 | 12 | results = [] 13 | sys_prompt = os.environ[translate_type.upper()] 14 | for text in texts: 15 | response = await call_openai(sys_prompt=sys_prompt, user_prompt=text.text, api_type=api_type) 16 | if response: 17 | choices = response["choices"] 18 | completion = choices[0].message.content.strip() 19 | result = TranslateResult(original_content=text.text, translated_content=completion) 20 | results.append(result) 21 | 22 | return results -------------------------------------------------------------------------------- /services/utils/interact_llm.py: -------------------------------------------------------------------------------- 1 | import os 2 | import openai 3 | from fastapi import HTTPException 4 | from dotenv import load_dotenv, find_dotenv 5 | from models.models import ApiType 6 | 7 | _ = load_dotenv(find_dotenv()) # read local .env file 8 | 9 | async def call_openai(sys_prompt: str, user_prompt: str, api_type: str): 10 | 11 | messages = [ 12 | {"role": "system", "content": sys_prompt}, 13 | {"role": "user", "content": user_prompt} 14 | ] 15 | 16 | 17 | if api_type not in ApiType.__members__: 18 | raise HTTPException(status_code=500, detail=f"Only support Azure and OpenAI") 19 | 20 | 21 | if api_type == ApiType.azure.value: 22 | engine=os.environ['AZURE_DEPLOYMENT_NAME'] 23 | openai.api_type = api_type 24 | openai.api_key = os.environ['AZURE_API_KEY'] 25 | openai.api_base = os.environ['AZURE_API_BASE'] 26 | openai.api_version = os.environ['AZURE_API_VERSION'] 27 | response = openai.ChatCompletion.create( 28 | engine=engine, 29 | messages=messages, 30 | temperature=float(os.environ['TEMPERATURE']) 31 | ) 32 | return response 33 | 34 | 35 | elif api_type == ApiType.open_ai.value: 36 | openai.api_key = os.environ["OPENAI_API_KEY"] 37 | openai.organization = os.environ["OPENAI_ORG"] 38 | response = openai.ChatCompletion.create( 39 | model=os.environ["OPENAI_MODEL"], 40 | messages=messages, 41 | temperature=float(os.environ['TEMPERATURE']) 42 | ) 43 | return response 44 | -------------------------------------------------------------------------------- /services/utils/process_file.py: -------------------------------------------------------------------------------- 1 | import os 2 | from fastapi import HTTPException 3 | from io import BufferedReader 4 | from typing import Optional 5 | from fastapi import UploadFile 6 | import mimetypes 7 | from PyPDF2 import PdfReader 8 | import hashlib 9 | import docx2txt 10 | import csv 11 | import pptx 12 | 13 | from models.models import Document 14 | 15 | 16 | async def get_document_from_file(file: UploadFile) -> Document: 17 | extracted_text = await extract_text_from_form_file(file) 18 | doc = Document(text=extracted_text) 19 | 20 | return doc 21 | 22 | 23 | def extract_text_from_filepath(filepath: str, mimetype: Optional[str] = None) -> str: 24 | """Return the text content of a file given its filepath.""" 25 | 26 | if mimetype is None: 27 | # Get the mimetype of the file based on its extension 28 | mimetype, _ = mimetypes.guess_type(filepath) 29 | 30 | if not mimetype: 31 | if filepath.endswith(".md"): 32 | mimetype = "text/markdown" 33 | else: 34 | raise Exception("Unsupported file type") 35 | 36 | # Open the file in binary mode 37 | file = open(filepath, "rb") 38 | extracted_text = extract_text_from_file(file, mimetype) 39 | 40 | return extracted_text 41 | 42 | 43 | def extract_text_from_file(file: BufferedReader, mimetype: str) -> str: 44 | if mimetype == "application/pdf": 45 | # Extract text from pdf using PyPDF2 46 | reader = PdfReader(file) 47 | extracted_text = "" 48 | for page in reader.pages: 49 | extracted_text += page.extract_text() 50 | elif mimetype == "text/plain" or mimetype == "text/markdown": 51 | # Read text from plain text file 52 | extracted_text = file.read().decode("utf-8") 53 | elif ( 54 | mimetype 55 | == "application/vnd.openxmlformats-officedocument.wordprocessingml.document" 56 | ): 57 | # Extract text from docx using docx2txt 58 | extracted_text = docx2txt.process(file) 59 | elif mimetype == "text/csv": 60 | # Extract text from csv using csv module 61 | extracted_text = "" 62 | decoded_buffer = (line.decode("utf-8") for line in file) 63 | reader = csv.reader(decoded_buffer) 64 | for row in reader: 65 | extracted_text += " ".join(row) + "\n" 66 | elif ( 67 | mimetype 68 | == "application/vnd.openxmlformats-officedocument.presentationml.presentation" 69 | ): 70 | # Extract text from pptx using python-pptx 71 | extracted_text = "" 72 | presentation = pptx.Presentation(file) 73 | for slide in presentation.slides: 74 | for shape in slide.shapes: 75 | if shape.has_text_frame: 76 | for paragraph in shape.text_frame.paragraphs: 77 | for run in paragraph.runs: 78 | extracted_text += run.text + " " 79 | extracted_text += "\n" 80 | else: 81 | # Unsupported file type 82 | file.close() 83 | raise ValueError("Unsupported file type: {}".format(mimetype)) 84 | 85 | file.close() 86 | return extracted_text 87 | 88 | 89 | # Extract text from a file based on its mimetype 90 | async def extract_text_from_form_file(file: UploadFile): 91 | """Return the text content of a file.""" 92 | # get the file body from the upload file object 93 | mimetype = file.content_type 94 | print(f"mimetype: {mimetype}") 95 | 96 | file_stream = await file.read() 97 | 98 | hash_code = hashlib.sha256(file_stream).hexdigest() 99 | 100 | if not os.path.exists("./temp_files/"): 101 | os.makedirs("./temp_files/") 102 | print("Temporary Folder created successfully!") 103 | 104 | temp_file_path = f"./temp_files/{hash_code}" 105 | 106 | try: 107 | with open(temp_file_path, "wb") as f: 108 | f.write(file_stream) 109 | extracted_text = extract_text_from_filepath(temp_file_path, mimetype) 110 | 111 | except Exception as e: 112 | raise e 113 | 114 | os.remove(temp_file_path) 115 | 116 | return extracted_text 117 | -------------------------------------------------------------------------------- /services/utils/save_as_file.py: -------------------------------------------------------------------------------- 1 | import os 2 | import secrets 3 | from typing import List 4 | from dotenv import load_dotenv, find_dotenv 5 | from models.models import TranslateResult 6 | _ = load_dotenv(find_dotenv()) # read local .env file 7 | file_folder = os.environ['FILE_FOLDER'] if 'FILE_FOLDER' in os.environ else "translated_file" 8 | 9 | async def save_as_txt(content_list: List[TranslateResult]): 10 | 11 | token = secrets.token_hex(16) 12 | if not os.path.exists(file_folder): 13 | os.makedirs(file_folder) 14 | 15 | with open(f"{file_folder}/{token}.txt", "w+") as f: 16 | for i in range(len(content_list)): 17 | f.write(content_list[i].translated_content) 18 | 19 | return token -------------------------------------------------------------------------------- /services/utils/split_text.py: -------------------------------------------------------------------------------- 1 | import tiktoken 2 | from langchain.text_splitter import RecursiveCharacterTextSplitter 3 | 4 | 5 | tokenizer = tiktoken.get_encoding('cl100k_base') 6 | 7 | # create the length function 8 | def tiktoken_len(text): 9 | tokens = tokenizer.encode( 10 | text, 11 | disallowed_special=() 12 | ) 13 | return len(tokens) 14 | 15 | def text_splitter(chunk_size=2048): 16 | text_splitter = RecursiveCharacterTextSplitter( 17 | # Set a really small chunk size, just to show. 18 | chunk_size = chunk_size, 19 | chunk_overlap = 5, 20 | length_function = tiktoken_len, 21 | ) 22 | return text_splitter -------------------------------------------------------------------------------- /tests/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/michaeloo0/chatgpt-doc-translator/6f4f66cca6f0910bc64eb6a38907ce62cdc1e7ea/tests/__init__.py --------------------------------------------------------------------------------