Update app.py

app.py

@@ -1,44 +1,40 @@
 import torch
 import gradio as gr
-import pdfplumber
+
+# Use a pipeline as a high-level helper
 from transformers import pipeline
 
-model_path = ("../Models/models--deepset--roberta-base-squad2/snapshots"
-              "/cbf50ba81465d4d8676b8bab348e31835147541b")
 
-question_answer = pipeline("question-answering", model="deepset/roberta-base-squad2")
+question_answer = pipeline("question-answering",
+                           model="deepset/roberta-base-squad2")
+
 
-def read_pdf_content(file_obj):
+def read_file_content(file_obj):
     """
-    Reads the content of a PDF file object and returns the extracted text.
+    Reads the content of a file object and returns it.
     Parameters:
     file_obj (file object): The file object to read from.
     Returns:
-    str: The extracted text from the PDF.
+    str: The content of the file.
     """
     try:
-        with pdfplumber.open(file_obj) as pdf:
-            text = ""
-            for page in pdf.pages:
-                text += page.extract_text()
-            return text
+        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}"
 
+
+
 def get_answer(file, question):
-    # Extract text from the uploaded PDF
-    context = read_pdf_content(file)
-    if context.startswith("An error occurred"):
-        return context
-    
-    # Get the answer from the model
+    context = read_file_content(file)
     answer = question_answer(question=question, context=context)
     return answer["answer"]
 
 demo = gr.Interface(fn=get_answer,
-                    inputs=[gr.File(label="Upload your PDF file"), gr.Textbox(label="Input your question", lines=1)],
-                    outputs=[gr.Textbox(label="Answer text", lines=1)],
+                    inputs=[gr.File(label="Upload your file"), gr.Textbox(label="Input your question",lines=1)],
+                    outputs=[gr.Textbox(label="Answer text",lines=1)],
                     title="@GenAILearniverse Project 5: Document Q & A",
-                    description="This application will be used to answer questions based on context provided from the uploaded PDF.")
+                    description="THIS APPLICATION WILL BE USED TO ANSER QUESTIONS BASED ON CONTEXT PROVIDED.")
 
-demo.launch()
+demo.launch()