Update app.py

app.py

@@ -8,11 +8,11 @@ from transformers import pipeline
 embedder = SentenceTransformer("all-MiniLM-L6-v2")
 qa_pipeline = pipeline("question-answering", model="distilbert-base-cased-distilled-squad")
 
-def extract_text(file_path):
-    if file_path.endswith(".pdf"):
-        return "\n".join([page.extract_text() or "" for page in PdfReader(file_path).pages])
-    elif file_path.endswith(".docx"):
-        return "\n".join([p.text for p in docx.Document(file_path).paragraphs])
+def extract_text(file):
+    if file.name.endswith(".pdf"):
+        return "\n".join([page.extract_text() or "" for page in PdfReader(file).pages])
+    elif file.name.endswith(".docx"):
+        return "\n".join([p.text for p in docx.Document(file).paragraphs])
     return ""
 
 def chunk_text(text, chunk_size=500):
@@ -28,11 +28,11 @@ def chunk_text(text, chunk_size=500):
         chunks.append(buffer.strip())
     return chunks
 
-def ask_question(file_path, question, history):
-    if not file_path:
+def ask_question(file, question, history):
+    if not file:
         return "Please upload a file.", history
 
-    text = extract_text(file_path)
+    text = extract_text(file)
     chunks = chunk_text(text)
     emb_chunks = embedder.encode(chunks, convert_to_tensor=True)
     emb_question = embedder.encode(question, convert_to_tensor=True)
@@ -46,26 +46,11 @@ def ask_question(file_path, question, history):
     return "", history
 
 with gr.Blocks() as demo:
-    gr.Markdown("## 📄 Document QA with Smart Retrieval")
-
-    # File upload styled like a dialogue box
-    with gr.Row():
-        with gr.Column():
-            gr.Markdown("### 🔽 Upload Your File")
-            file_input = gr.File(
-                label="Choose a PDF or Word file",
-                file_types=[".pdf", ".docx"],
-                type="filepath"   # ✅ Fixed for Hugging Face
-            )
-
-    chatbot = gr.Chatbot(label="💬 Chat with Document")
-    question = gr.Textbox(
-        label="Ask your question",
-        placeholder="Type your question here..."
-    )
+    gr.Markdown("##  Document QA with Smart Retrieval")
+    file_input = gr.File(label="Upload PDF or Word", file_types=[".pdf", ".docx"])
+    chatbot = gr.Chatbot()
+    question = gr.Textbox(label="Ask your question")
     state = gr.State([])
-
-    # Submit by pressing Enter
     question.submit(ask_question, [file_input, question, state], [question, chatbot])
 
 demo.launch()