Update app.py

app.py

@@ -86,9 +86,8 @@ app = FastAPI()
 
 # Initialize AI Models
 qa_model = pipeline("question-answering", model="distilbert-base-uncased-distilled-squad")
-
 image_captioning = pipeline("image-to-text", model="nlpconnect/vit-gpt2-image-captioning")
-reader = easyocr.Reader(['en', 'fr'])  # EasyOCR for image text extraction (English & French)
+reader = easyocr.Reader(['en', 'fr'])  # OCR for English & French
 
 # ---- TEXT EXTRACTION FUNCTIONS ----
 def extract_text_from_pdf(pdf_file):
@@ -157,9 +156,12 @@ def answer_question_from_doc(file, question):
     if not context.strip():
         return "No text found in the document."
 
-    # Generate answer using AI
-    answer = qa_model(question + " " + context, max_length=100)[0]["generated_text"]
-    return answer
+    # Generate answer using QA pipeline correctly
+    try:
+        result = qa_model({"question": question, "context": context})
+        return result["answer"]
+    except Exception as e:
+        return f"Error generating answer: {e}"
 
 def answer_question_from_image(image, question):
     """Process an image, extract text, and answer a question."""
@@ -167,13 +169,15 @@ def answer_question_from_image(image, question):
     if not img_text.strip():
         return "No readable text found in the image."
 
-    # Generate answer using AI
-    answer = qa_model(question + " " + img_text, max_length=50)[0]["generated_text"]
-    return answer
+    try:
+        result = qa_model({"question": question, "context": img_text})
+        return result["answer"]
+    except Exception as e:
+        return f"Error generating answer: {e}"
 
 # ---- GRADIO INTERFACES ----
 with gr.Blocks() as doc_interface:
-    gr.Markdown("## Document Question Answering")
+    gr.Markdown("## 📄 Document Question Answering")
     file_input = gr.File(label="Upload DOCX, PPTX, XLSX, or PDF")
     question_input = gr.Textbox(label="Ask a question")
     answer_output = gr.Textbox(label="Answer")
@@ -181,7 +185,7 @@ with gr.Blocks() as doc_interface:
     file_submit.click(answer_question_from_doc, inputs=[file_input, question_input], outputs=answer_output)
 
 with gr.Blocks() as img_interface:
-    gr.Markdown("## Image Question Answering")
+    gr.Markdown("## 🖼️ Image Question Answering")
     image_input = gr.Image(label="Upload an Image")
     img_question_input = gr.Textbox(label="Ask a question")
     img_answer_output = gr.Textbox(label="Answer")