Update app.py

app.py

@@ -1,50 +1,25 @@
-from transformers import AutoModelForCausalLM, AutoTokenizer
-import gradio as gr
-import torch
-
-title = "🤖AI ChatBot"
-description = "A State-of-the-Art Large-scale Pretrained Response generation model (DialoGPT)"
-examples = [["How are you?"]]
-
-tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-large")
-model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-large")
-
-
-def predict(input_text, history=None):
-    if history is None:
-        history = []
-
-    # Tokenize the new input sentence
-    new_user_input_ids = tokenizer.encode(
-        input_text + tokenizer.eos_token, return_tensors="pt"
-    )
-
-    # Append the new user input tokens to the chat history
-    bot_input_ids = torch.cat([torch.LongTensor(history), new_user_input_ids], dim=-1)
-
-    # Generate a response using batch processing
-    generated_ids = model.generate(
-        bot_input_ids, max_length=4000, pad_token_id=tokenizer.eos_token_id
-    )
-
-    # Convert the generated response tokens to text
-    response = tokenizer.decode(generated_ids[0], skip_special_tokens=True)
-
-    # Split the responses into lines
-    response = response.split("\n")
-
-    # Convert to tuples of list
-    response = [(response[i], response[i + 1]) for i in range(0, len(response) - 1, 2)]
-
-    return response, generated_ids.tolist()
-
-
-gr.Interface(
-    fn=predict,
-    title=title,
-    description=description,
-    examples=examples,
-    inputs=["text", "state"],
-    outputs=["chatbot", "state"],
-    theme="finlaymacklon/boxy_violet",
-).launch()
+from transformers import MarianMTModel, MarianTokenizer
+
+# Load the model and tokenizer for English-to-French translation
+model_name = "Helsinki-NLP/opus-mt-en-fr"  # English to French translation model
+tokenizer = MarianTokenizer.from_pretrained(model_name)
+model = MarianMTModel.from_pretrained(model_name)
+
+def translate_text(input_text):
+    # Tokenize the input text
+    input_text = ">>en<< " + input_text  # Prefix the input text with the source language code (en for English)
+    inputs = tokenizer(input_text, return_tensors="pt")
+
+    # Perform translation
+    with torch.no_grad():
+        outputs = model.generate(**inputs)
+
+    # Decode the translated text
+    translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return translated_text
+
+# Example usage
+input_text = "Hello, how are you?"
+translated_text = translate_text(input_text)
+print("English:", input_text)
+print("French:", translated_text)