app.py

# AUTOGENERATED! DO NOT EDIT! File to edit: enro-app.ipynb.

# %% auto 0
__all__ = ['model_name', 'tokenizer', 'model', 'dataset', 'dialogs', 'encoded_key', 'decoded_bytes', 'firebase_creds',
           'get_translations', 'clean_sentence', 'get_random_sentence', 'save_option_to_repo', 'update_prompt']

# %% enro-app.ipynb 1
from transformers import MarianMTModel, MarianTokenizer
import gradio as gr

# %% enro-app.ipynb 2
model_name = "Helsinki-NLP/opus-mt-tc-big-en-ro"
tokenizer = MarianTokenizer.from_pretrained(model_name)
model = MarianMTModel.from_pretrained(model_name)

# %% enro-app.ipynb 3
import random

def get_translations(input_text):
    tokenized_text = tokenizer(input_text, return_tensors="pt")
# Generate multiple translations
# Set num_return_sequences to the number of translations you want
    translated = model.generate(**tokenized_text, num_return_sequences=4)
    translations = []
    for t in translated:
        translations.append(tokenizer.decode(t, skip_special_tokens=True))
    random_translations = random.sample(translations, 2)
    return random_translations[0], random_translations[1]

def get_top_translation(input_text):
    tokenized_text = tokenizer(input_text, return_tensors="pt")
# Generate multiple translations
# Set num_return_sequences to the number of translations you want
    translated = model.generate(**tokenized_text)
    translations = []
    translations.append(tokenizer.decode(translated, skip_special_tokens=True))
    return translations[0]

# %% enro-app.ipynb 5
from datasets import load_dataset
dataset = load_dataset("daily_dialog", trust_remote_code=True)

# %% enro-app.ipynb 6
import re

dialogs = dataset["train"]
# Function to clean extra spaces around punctuation marks
def clean_sentence(sentence):
    # Remove space before punctuation
    sentence = re.sub(r'\s+([?.!,"\'-])', r'\1', sentence)
    # Remove space after punctuation
    sentence = re.sub(r'([?.!,"\'-])\s+', r'\1 ', sentence)
    sentence = sentence.strip()
    return sentence

# Assuming dialogues is a list of lists, where each inner list contains sentences of a dialogue
# Example: dialogues = [["Hello, how are you?", "I'm fine, thank you!"], ["What's your name?", "My name is John."]]

# Function to randomly select one sentence from the dataset
def get_random_sentence():
    # Select a random dialogue
    random_dialogue = random.choice(dialogs['dialog'])
    # Select a random sentence from the chosen dialogue
    random_sentence = random.choice(random_dialogue)

    # Clean the sentence
    clean_random_sentence = clean_sentence(random_sentence)
    return clean_random_sentence



# %% enro-app.ipynb 7
import os
import firebase_admin
from firebase_admin import credentials
from firebase_admin import db
import json
import base64

encoded_key = os.getenv('FIREBASE_KEY')
decoded_bytes = base64.b64decode(encoded_key)
firebase_creds = json.loads(decoded_bytes.decode('utf-8'))
if not firebase_admin._apps:
    cred = credentials.Certificate(firebase_creds)
    firebase_admin.initialize_app(cred, {
        'databaseURL': 'https://ro-en-llm-default-rtdb.firebaseio.com/'
    })

# %% enro-app.ipynb 8
def save_option_to_repo(trans_prompt, translation1, translation2, button):
    ref = db.reference('dpo_feedback')
    # Push new data to the database
    if button == "Translation 1":
        ref.push({
            'prompt': trans_prompt,
            'chosen': translation1,
            'rejected': translation2
        })
    if button == "Translation 2":
        ref.push({
            'prompt': trans_prompt,
            'chosen': translation2,
            'rejected': translation1
        })



def update_prompt():
    return get_random_sentence() 

with gr.Blocks() as demo: 
    
    translations = []
    option_buttons = []

    with gr.Row():
        prompt = gr.components.Textbox(scale = 4)
        example_sentence = gr.Button("Get Random Sentence", scale = 1)
    
    with gr.Row():
        generate = gr.Button("Translate")

    with gr.Row(equal_height=True):
        translations.append(gr.components.Text(label=f"Translation 1"))
        translations.append(gr.components.Text(label=f"Translation 2"))
    
    with gr.Row():
        option_buttons.append(gr.Button(value="Translation 1"))
        option_buttons.append(gr.Button(value="Equal"))
        option_buttons.append(gr.Button(value="Translation 2"))

    generate.click(get_translations, inputs=prompt, outputs=translations)
    example_sentence.click(update_prompt, outputs=prompt)
    for i in range(0,3):
        option_buttons[i].click(save_option_to_repo, inputs=[prompt, translations[0], translations[1], option_buttons[i]])
    
    
demo.launch()