Added app.py

app.py

@@ -0,0 +1,50 @@
+import torch
+import gradio as gr
+
+from transformers import pipeline
+
+pipe = pipeline(
+    "question-answering", 
+    model="deepset/roberta-base-squad2")
+
+# Function to read the content of a file object
+def read_file_content(file_obj):
+    """
+    Reads the content of a file object and returns it.
+    Parameters:
+    file_obj (file object): The file object to read from.
+    Returns:
+    str: The content of the file.
+    """
+    try:
+        with open(file_obj.name, 'r', encoding='utf-8') as file:
+            context = file.read()
+            return context
+    except Exception as e:
+        return f"An error occurred: {e}"
+
+# Function to get the answer to a question from a file
+def get_answer(file, question):
+    """
+    Answers a question based on the content of a file.
+    Parameters:
+    file (file object): The file object containing the context.
+    question (str): The question to answer.
+    Returns:
+    str: The answer to the question.
+    """
+    if not question or not file:
+        return "Please provide both a question and a file."
+    context = read_file_content(file)
+    answer = pipe(question=question, context=context)
+    return answer["answer"]
+
+# Create the Gradio interface
+demo = gr.Interface(fn=get_answer,
+                    inputs=[gr.File(label="File Upload"), gr.Textbox(label="Prompt Input", lines=1)],
+                    outputs=[gr.Textbox(label="Response", lines=1)],
+                    title="@caesar-2series: Rag Application",
+                    description="Retrieval Augmented Generation Questions-Answering Application")
+
+# Launch the Gradio interface
+demo.launch()