Update app.py

app.py

@@ -1,3 +1,7 @@
+"raw
+history
+blame
+5.44 kB
 """
 🗣️ Translator - Translate text from one language to another.
 Application file made with Streamlit.
@@ -15,23 +19,44 @@ from available_models import MODELS
 
 st.set_page_config(page_title="Translator", page_icon="🗣️")
 st.title("🗣️ Translator")
-
+st.subheader("Translation made fast and easy.")
+st.markdown("""
+[![GitHub](https://img.shields.io/badge/-%23121011.svg?style=for-the-badge&logo=github&logoColor=white)](https://github.com/ChainYo)
+[![HuggingFace](https://img.shields.io/badge/-yellow.svg?style=for-the-badge&logo=data:image/svg+xml;base64,PD94bWwgdmVyc2lvbj0iMS4wIiBzdGFuZGFsb25lPSJubyI/Pgo8IURPQ1RZUEUgc3ZnIFBVQkxJQyAiLS8vVzNDLy9EVEQgU1ZHIDIwMDEwOTA0Ly9FTiIKICJodHRwOi8vd3d3LnczLm9yZy9UUi8yMDAxL1JFQy1TVkctMjAwMTA5MDQvRFREL3N2ZzEwLmR0ZCI+CjxzdmcgdmVyc2lvbj0iMS4wIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciCiB3aWR0aD0iMTc1LjAwMDAwMHB0IiBoZWlnaHQ9IjE3NS4wMDAwMDBwdCIgdmlld0JveD0iMCAwIDE3NS4wMDAwMDAgMTc1LjAwMDAwMCIKIHByZXNlcnZlQXNwZWN0UmF0aW89InhNaWRZTWlkIG1lZXQiPgoKPGcgdHJhbnNmb3JtPSJ0cmFuc2xhdGUoMC4wMDAwMDAsMTc1LjAwMDAwMCkgc2NhbGUoMC4xMDAwMDAsLTAuMTAwMDAwKSIKZmlsbD0iIzAwMDAwMCIgc3Ryb2tlPSJub25lIj4KPHBhdGggZD0iTTU2MyAxMjM2IGMtMjkgLTEzIC02MyAtNTkgLTYzIC04NiAwIC0yNiAzMyAtODAgNTIgLTg2IDE1IC00IDI2IDEKNDMgMjEgMjAgMjYgMjQgMjcgNTMgMTcgMjggLTkgMzMgLTggNDIgOCAxNyAzMiAxMSA2OSAtMTcgOTkgLTM0IDM3IC02OCA0NQotMTEwIDI3eiIvPgo8cGF0aCBkPSJNMTA2NCAxMjQwIGMtNTAgLTIwIC03NyAtODYgLTU0IC0xMzAgOSAtMTYgMTQgLTE3IDQyIC04IDI5IDEwIDMzIDkKNTUgLTE3IDIxIC0yNCAyNyAtMjYgNDggLTE3IDMxIDE0IDUxIDc2IDM2IDExNCAtMTcgNDYgLTg0IDc2IC0xMjcgNTh6Ii8+CjxwYXRoIGQ9Ik02MDAgODg4IGMwIC00OSAxNiAtOTggNTAgLTE1MSA4NSAtMTM0IDMyNSAtMTM0IDQxMCAwIDUxIDgwIDY5IDE4MwozMSAxODMgLTEwIDAgLTUwIC0xNSAtODcgLTMyIC02MCAtMjkgLTc5IC0zMyAtMTQ5IC0zMyAtNzAgMCAtODkgNCAtMTQ5IDMzCi0zNyAxNyAtNzcgMzIgLTg3IDMyIC0xNSAwIC0xOSAtNyAtMTkgLTMyeiIvPgo8L2c+Cjwvc3ZnPgo=)](https://huggingface.co/ChainYo)
+[![LinkedIn](https://img.shields.io/badge/-%230077B5.svg?style=for-the-badge&logo=linkedin&logoColor=white)](https://www.linkedin.com/in/thomas-chaigneau-dev/)
+[![Discord](https://img.shields.io/badge/Chainyo%233610-%237289DA.svg?style=for-the-badge&logo=discord&logoColor=white)](https://discord.gg/)
+""")
 st.write("To add a new model, hit me up! ⬆️")
 
 with st.expander(label="❓ How does it work", expanded=True):
-  
+    st.markdown("""
+    **Translator** is a **simple tool** that allows you to **translate text** from one language to another.
+    **Translator** is powered by the [Transformers library](https://huggingface.co/transformers) and uses the 
+    [Helsinki-NLP](https://huggingface.co/Helsinki-NLP) models.
+    Choose the **source language**, the **target language** and add some **text to translate**.
+    **Translator** will translate the text and **save the output in a text file**. It cuts the sentences by following 
+    the punctuation marks.
+    The output file content will also be displayed in the browser to help you understand the translation and choose 
+    if you want to download it.
+    There is **no limit to the number of characters** that can be translated. 
+    The only limit is the time you are ready to wait! 🤗
+    *P.S. I have built this tool to help me start writing blog posts in different languages. I am a French native speaker
+    and I will use it to translate my potential future blog posts in English.*
+    *P.P.S. I am a **Junior ML Engineer** passionate about **machine learning** and **data science**. Reach out to me by 
+    clicking on the socials badges above.*
+    """)
 
-    lang1, lang2 = st.columns(2)
-    lang1.selectbox(
-    "Source Language", ["🇫🇷 French"], 
+lang1, lang2 = st.columns(2)
+lang1.selectbox(
+    "Source Language", ["🇬🇧 English", "🇫🇷 French", "🇩🇪 German", "🇪🇸 Spanish", "🇷🇺 Russian"], 
     key="input_lang", index=1,
 )
-    lang2.selectbox(
-    "Target Language", ["🇬🇧 English"], 
+lang2.selectbox(
+    "Target Language", ["🇬🇧 English", "🇫🇷 French", "🇩🇪 German", "🇪🇸 Spanish", "🇷🇺 Russian"], 
     key="output_lang", index=0,
 )
 
-    selected_model = MODELS[f"{st.session_state['input_lang']}->{st.session_state['output_lang']}"]
+selected_model = MODELS[f"{st.session_state['input_lang']}->{st.session_state['output_lang']}"]
 
 
 if selected_model[0] == None:
@@ -66,49 +91,9 @@ else:
 
         st.success("🗣️ Translated!")
         st.write(f"**Translation:** {' '.join(text_to_translate)}")
-  
-            
-            
-            
-            
-'''            
-                        
-            
-            import torch
-from transformers import BartTokenizer, BartForConditionalGeneration
-import gradio as gr
-from transformers import AutoTokenizer, AutoModelWithLMHead, TranslationPipeline
-from transformers import pipeline
-
-pipe= pipeline('text2text-generation', model="SEBIS/legal_t5_small_trans_fr_en")
-def generate_text(inp):
-    output=pipe(inp, forced_bos_token_id=pipe.tokenizer.get_lang_id('en'))
-    tln=output[0]
-    for item in tln:
-        result=tln[item]
-    return result
-#Gradio Interface
-
-model = BartForConditionalGeneration.from_pretrained("facebook/bart-large-cnn")
-tokenizer = BartTokenizer.from_pretrained("facebook/bart-large-cnn")
-
-def article_summarization(result):
-    input_ =  str(result) + ' </s>'
-# generate summary
-    input_ids = tokenizer.encode(result, return_tensors='pt')
-    summary_ids = model.generate(input_ids,
-            min_length=20,
-            max_length=12000)
-
-    summary_text = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
-    return(summary_text)
-
-
-#iface = gr.Interface(fn=article_summarization,title="Summarization in English",description="facebook/bart-large-cnn for summarization in English", inputs=(lines=50,['text']), outputs=["text"])
-
-iface = gr.Interface(fn=article_summarization,title="Summarization in English",description="facebook/bart-large-cnn for summarization in English", inputs=gr.inputs.Textbox(lines=50, placeholder="Enter newspaper article to be summarized"), outputs=["result"])
-
-iface.launch()
-
-
-'''
+        st.download_button(
+            label="Download translated text", 
+            data="\n".join(text_to_translate), 
+            file_name=f"{st.session_state['input_lang']}-{st.session_state['output_lang']}-{datetime.now().strftime('%Y-%m-%d-%H-%M-%S')}.txt",
+            mime="text/plain"
+        )