├── model_it └── README.md ├── model_es └── README.md ├── instructions.txt ├── test-en-it.py ├── README.md ├── test-en-es.py ├── st-yourTranslationApp.py └── LICENSE /model_it/README.md: -------------------------------------------------------------------------------- 1 | Your translation model here 2 | -------------------------------------------------------------------------------- /model_es/README.md: -------------------------------------------------------------------------------- 1 | your tensorflow weighs files here 2 | -------------------------------------------------------------------------------- /instructions.txt: -------------------------------------------------------------------------------- 1 | python3.10 -m venv venv 2 | source venv/bin/activate 3 | 4 | python -m pip install --upgrade pip 5 | pip install mkl mkl-include # required for CPU usage on Mac users 224 Mb 6 | pip install torch==1.11.0 torchvision==0.12.0 torchaudio==0.11.0 # The core 7 | 8 | pip install --upgrade pip 9 | 10 | pip install transformers 11 | 12 | pip install langchain==0.0.173 13 | 14 | pip install faiss-cpu==1.7.4 unstructured==0.6.8 pytesseract==0.3.10 pypdf==3.9.0 pdf2image==1.16.3 15 | 16 | pip install sentence_transformers==2.2.2 accelerate==0.19.0 17 | 18 | pip install streamlit 19 | 20 | pip install streamlit-extras 21 | 22 | pip install chainlit 23 | -------------------------------------------------------------------------------- /test-en-it.py: -------------------------------------------------------------------------------- 1 | import torch 2 | from transformers import AutoTokenizer, AutoModelForSeq2SeqLM 3 | from transformers import pipeline 4 | import datetime 5 | 6 | 7 | # 🈚🆗✅💬🇮🇹🇺🇸 8 | #LOCAL MODEL EN-IT 9 | #--------------------------------- 10 | # Helsinki-NLP/opus-mt-en-it 11 | Model_IT = './model_it/' #torch 12 | #--------------------------------- 13 | English = "Another common struggle that Python programmers face with pip is package installation errors. Some errors may come because the library you are installing requires compiling on your local computer: others can happen when there are issues with the package itself or when there are network or permission issues." 14 | from transformers import AutoTokenizer, AutoModelForSeq2SeqLM 15 | # INITIALIZE TRANSLATION FROM ENGLISH TO ITALIAN TORCH MODEL 16 | tokenizer_tt0it = AutoTokenizer.from_pretrained(Model_IT) 17 | print(' Initializing AI Model & pipeline...') 18 | model_tt0it = AutoModelForSeq2SeqLM.from_pretrained(Model_IT) #Helsinki-NLP/opus-mt-en-it or #Helsinki-NLP/opus-mt-it-en 19 | print("pipeline") 20 | TToIT = pipeline("translation", model=model_tt0it, tokenizer=tokenizer_tt0it) 21 | # ITERATE OVER CHUNKS AND JOIN THE TRANSLATIONS 22 | print("translation in progress") 23 | start = datetime.datetime.now() #not used now but useful 24 | finaltext = TToIT(English) 25 | stop = datetime.datetime.now() #not used now but useful 26 | elapsed = stop - start 27 | print(f'Translation generated in {elapsed}...') 28 | print(finaltext[0]['translation_text']) 29 | print(f"Translated number {len(English.split(' '))} of words") -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # AItranslationMedium 2 | Repocode for Medium Article 3 | 4 | This code is tested on Mac Intel 5 | For troubleshooting on installing pytorch refer to the troubleshooting section of my medium article 6 | - https://medium.com/@fabio.matricardi/the-struggles-python-programmers-face-with-development-tools-926df7503f3b 7 | - https://artificialcorner.com/a-7-steps-guide-to-install-and-run-lamini-lm-on-your-computer-7841ea94522b in Section 2 8 | 9 | There is a folder called model_it 10 | Change the name at your convenience according to oyur target language 11 | remember to change as well the path in the .py file in the `checkpoint` 12 | ## Create wirtual environment 13 | ``` 14 | python3.10 -m venv venv #version 3.10 is reccomended 15 | source venv/bin/activate #for mac 16 | venv\Scripts\activate #for windows users 17 | ``` 18 | 19 | ## Install packages 20 | With venv activated (see point above)
21 | ``` 22 | python3.10 -m pip install --upgrade pip 23 | pip install mkl mkl-include # required for CPU usage on Mac users 224 Mb 24 | pip install torch==1.11.0 torchvision==0.12.0 torchaudio==0.11.0 # The core 25 | ``` 26 | 27 | Other packages required for this project 28 | 29 | ``` 30 | pip install --upgrade pip 31 | pip install transformers 32 | pip install langchain==0.0.173 33 | pip install streamlit 34 | pip install streamlit-extras 35 | ``` 36 | 37 | ## In case your model is not a torch weight but Tesnorflow 38 | In case the weights of the model are in .h5 format you need to install tensorflow (like in the example above) 39 | ``` 40 | pip install tensorflow 41 | ``` 42 | 43 | 44 | 45 | -------------------------------------------------------------------------------- /test-en-es.py: -------------------------------------------------------------------------------- 1 | import tensorflow 2 | from transformers import AutoTokenizer, AutoModelForSeq2SeqLM 3 | from transformers import pipeline 4 | import datetime 5 | 6 | # 🈚🆗✅💬🇮🇹🇺🇸 7 | #LOCAL MODEL EN-ES 8 | #--------------------------------- 9 | # Helsinki-NLP/opus-mt-tc-big-en-es 10 | #--------------------------------- 11 | Model_ES = './model_es/' # tensorflow 12 | #--------------------------------- 13 | English = "Another common struggle that Python programmers face with pip is package installation errors. Some errors may come because the library you are installing requires compiling on your local computer: others can happen when there are issues with the package itself or when there are network or permission issues." 14 | from transformers import AutoTokenizer, AutoModelForSeq2SeqLM 15 | # INITIALIZE TRANSLATION FROM ENGLISH TO ENGLISH with TENSORFLOW MODEL 16 | tokenizer_tt0es = AutoTokenizer.from_pretrained(Model_ES) 17 | print(' Initializing AI Model & pipeline...') 18 | model_tt0es = AutoModelForSeq2SeqLM.from_pretrained(Model_ES, from_tf=True) #Helsinki-NLP/opus-mt-en-it or #Helsinki-NLP/opus-mt-it-en 19 | print("pipeline") 20 | TToES = pipeline("translation", model=model_tt0es, tokenizer=tokenizer_tt0es) 21 | start = datetime.datetime.now() #not used now but useful 22 | print('Translation in progress...') 23 | finaltext = TToES(English) 24 | stop = datetime.datetime.now() #not used now but useful 25 | elapsed = stop - start 26 | print(f'Translation generated in {elapsed}...') 27 | print('*'*50) 28 | print(finaltext[0]['translation_text']) 29 | print('*'*50) 30 | print(f"Translated number {len(English.split(' '))} of words") -------------------------------------------------------------------------------- /st-yourTranslationApp.py: -------------------------------------------------------------------------------- 1 | import streamlit as st 2 | import torch 3 | from transformers import AutoTokenizer, AutoModelForSeq2SeqLM 4 | from transformers import pipeline 5 | from langchain.text_splitter import CharacterTextSplitter 6 | import datetime 7 | import os 8 | import sys 9 | 10 | ############# Displaying images on the front end ################# 11 | st.set_page_config(page_title="Your AI translation App", 12 | page_icon='♾️', 13 | layout="centered", #or wide 14 | initial_sidebar_state="expanded", 15 | menu_items={ 16 | 'Get Help': 'https://docs.streamlit.io/library/api-reference', 17 | 'Report a bug': "https://www.extremelycoolapp.com/bug", 18 | 'About': "# This is a header. This is an *extremely* cool app!" 19 | }, 20 | ) 21 | 22 | # 🈚🆗✅💬🇮🇹🇺🇸 23 | #LOCAL MODEL EN-IT 24 | #--------------------------------- 25 | # Helsinki-NLP/opus-mt-en-it 26 | Model_IT = './model_it/' #torch 27 | #--------------------------------- 28 | 29 | ### HEADER section 30 | st.title("Your AI powered Text Translator 💬 ") 31 | st.header("Translate your English text to Italian") 32 | #st.image('Headline.jpg', width=750) 33 | English = st.text_area("Paste here the English text...", height=300, key="original") 34 | col1, col2, col3 = st.columns([2,5,2]) 35 | btn_translate = col2.button("✅ Start Translation", use_container_width=True, type="primary", key='start') 36 | if btn_translate: 37 | if English: 38 | Model_IT = './model_it/' #torch 39 | with st.spinner('Initializing pipelines...'): 40 | st.success(' AI Translation started', icon="🆗") 41 | from langchain.text_splitter import CharacterTextSplitter 42 | # TEXT SPLITTER FUNCTION FOR CHUNKING 43 | text_splitter = CharacterTextSplitter( 44 | separator = "\n\n", 45 | chunk_size = 300, 46 | chunk_overlap = 0, 47 | length_function = len, 48 | ) 49 | # CHUNK THE DOCUMENT 50 | st.success(' Chunking text...', icon="🆗") 51 | texts = text_splitter.create_documents([English]) 52 | #print('[bold red] Inizialize AI toknizer...') 53 | from transformers import AutoTokenizer, AutoModelForSeq2SeqLM 54 | # INITIALIZE TRANSLATION FROM ENGLISH TO ITALIAN 55 | tokenizer_tt0it = AutoTokenizer.from_pretrained(Model_IT) #google/byt5-small #facebook/m2m100_418M 56 | st.success(' Initializing AI Model & pipeline...', icon="🆗") 57 | model_tt0it = AutoModelForSeq2SeqLM.from_pretrained(Model_IT) #Helsinki-NLP/opus-mt-en-it or #Helsinki-NLP/opus-mt-it-en 58 | #print("pipeline") 59 | TToIT = pipeline("translation", model=model_tt0it, tokenizer=tokenizer_tt0it) 60 | # ITERATE OVER CHUNKS AND JOIN THE TRANSLATIONS 61 | finaltext = '' 62 | start = datetime.datetime.now() #not used now but useful 63 | print('[bold yellow] Translation in progress...') 64 | for item in texts: 65 | line = TToIT(item.page_content)[0]['translation_text'] 66 | finaltext = finaltext+line+'\n' 67 | stop = datetime.datetime.now() #not used now but useful 68 | elapsed = stop - start 69 | st.success(f'Translation completed in {elapsed}', icon="🆗") 70 | print(f'[bold underline green1] Translation generated in [reverse dodger_blue2]{elapsed}[/reverse dodger_blue2]...') 71 | st.text_area(label="Translated text in Italian:", value=finaltext, height=350) 72 | st.markdown(f'Translation completed in **{elapsed}**') 73 | st.markdown(f"Translated number **{len(English.split(' '))}** of words") 74 | 75 | else: 76 | st.warning("You need some text to be translated!", icon="⚠️") -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | Apache License 2 | Version 2.0, January 2004 3 | http://www.apache.org/licenses/ 4 | 5 | TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 6 | 7 | 1. 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