intial commit

.gitignore.txt

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+# Ignore Python cache files
+__pycache__/
+*.pyc
+*.pyo
+*.pyd
+
+# Ignore virtual environments and environment variables
+venv/
+.env
+*.env
+
+# Ignore package manager files
+poetry.lock
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Ignore Jupyter Notebook checkpoints (if using Colab or Jupyter)
+.ipynb_checkpoints/
+
+# Ignore Gradio cache and temporary files
+gradio/
+
+# Ignore Hugging Face transformers cache
+~/.cache/
+huggingface/
+transformers_cache/
+datasets_cache/
+
+# Ignore large model files
+*.pt
+*.pth
+*.bin
+*.h5
+*.onnx
+*.tflite
+models/
+checkpoints/
+
+# Ignore logs and temporary files
+*.log
+*.csv
+*.tsv
+*.sqlite
+*.db
+
+# Ignore VS Code settings (if using VS Code)
+.vscode/
+
+# Ignore system-specific files
+.DS_Store
+Thumbs.db

requirements.txt

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+torch
+transformers
+gradio

translation.py

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+# -*- coding: utf-8 -*-
+"""translation.ipynb
+
+Automatically generated by Colab.
+
+Original file is located at
+    https://colab.research.google.com/drive/1bKzjrfpxJqSrJQUuGR27-kRCSndSClBo
+"""
+
+
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+import gradio as gr
+
+device = "cuda" if torch.cuda.is_available() else "cpu"
+
+language_model_name = "Qwen/Qwen2-1.5B-Instruct"
+language_model = AutoModelForCausalLM.from_pretrained(
+    language_model_name,
+    torch_dtype="auto",
+    device_map="auto"
+)
+tokenizer = AutoTokenizer.from_pretrained(language_model_name)
+
+def process_input(input_text, action):
+    if action == "Translate to Japanese":
+        prompt = f"Please translate the following English text into Japanese: {input_text}"
+        lang = "ja"
+    elif action == "Translate to English":
+        prompt = f"Please translate the following Japanese text into English: {input_text}"
+        lang = "en"
+    else:
+        return "Invalid action. Please choose 'Translate to English' or 'Translate to Japanese'.", "error"
+
+    messages = [
+        {"role": "system", "content": "You are a helpful AI assistant for Language Translation."},
+        {"role": "user", "content": prompt}
+    ]
+    text = tokenizer.apply_chat_template(
+        messages,
+        tokenize=False,
+        add_generation_prompt=True
+    )
+    model_inputs = tokenizer([text], return_tensors="pt").to(device)
+
+    generated_ids = language_model.generate(
+        model_inputs.input_ids,
+        max_new_tokens=512
+    )
+    generated_ids = [
+        output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
+    ]
+
+    output_text = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
+    return output_text, lang
+
+def handle_interaction(input_text, action):
+    output_text, lang = process_input(input_text, action)
+    return output_text
+
+action_options = ["Translate to English", "Translate to Japanese"]
+
+iface = gr.Interface(
+    fn=handle_interaction,
+    inputs=[
+        gr.Textbox(label="input text"),
+        gr.Dropdown(action_options, label="select action")
+    ],
+    outputs=[
+        gr.Textbox(label="output text"),
+    ],
+    title="Translation App using AI",
+    description="Translate input text  based on the selected Language.",
+    theme= "gradio/soft"
+)
+
+if __name__ == "__main__":
+    iface.launch(share=True)
+