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app.py

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+import gradio as gr
+import os
+from translator import get_translation_pipeline, translate_cobol_to_csharp
+
+# ✅ Load the translation pipeline
+pipeline = get_translation_pipeline()
+
+# ✅ This function handles file upload and saving the output
+def translate_and_save(file_obj):
+    try:
+        if not file_obj:
+            return "❌ No file uploaded."
+
+        # ✅ Get path of uploaded file
+        file_path = file_obj.name
+
+        # ✅ Read the file content
+        with open(file_path, "r", encoding="utf-8") as f:
+            cobol_code = f.read()
+
+        # ✅ Extract base name
+        base_name = os.path.splitext(os.path.basename(file_path))[0]
+
+        # ✅ Translate COBOL to C#
+        csharp_code = translate_cobol_to_csharp(pipeline, cobol_code)
+
+        # ✅ Save the translated output
+        output_file = f"{base_name}.cs"
+        with open(output_file, "w", encoding="utf-8") as f:
+            f.write(csharp_code)
+
+        return f"✅ Translation complete. Saved as: {output_file}\n\n{csharp_code}"
+
+    except Exception as e:
+        return f"❌ ERROR: {str(e)}"
+
+# ✅ Create the Gradio interface
+gr.Interface(
+    fn=translate_and_save,
+    inputs=gr.File(label="Upload COBOL File (.cob)", file_types=[".cob"]),
+    outputs=gr.Textbox(label="C# Output", lines=25),
+    title="COBOL to C# (.NET) Translator",
+    description="Upload a COBOL file. This app will translate it and save a .cs file."
+).launch()

sample.cs

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+Translate this COBOL code to C# .

translator.py

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+from transformers import pipeline
+
+def get_translation_pipeline():
+    # Use a public model that doesn't require login
+    model_name = "Salesforce/codet5-base-multi-sum"
+    return pipeline("text2text-generation", model=model_name, tokenizer=model_name)
+
+def translate_cobol_to_csharp(pipe, cobol_code: str) -> str:
+    prompt = f"Translate this COBOL code to C#:\n\n{cobol_code}"
+    result = pipe(prompt, max_length=512, do_sample=False)[0]["generated_text"]
+    return result