updating app.py

app.py

@@ -4,49 +4,43 @@ from rag.pipeline import run_rag
 
 vectorstore = None
 
-def process_and_query(file, question):
+def load_document(file):
     global vectorstore
-    
-    status = ""
-    answer = ""
-    sources = ""
-    evaluation = ""
-    
-    # Processar PDF se fornecido
-    if file is not None:
-        try:
-            vectorstore = process_pdf(file.name)
-            status = "✓ Document processed successfully"
-        except Exception as e:
-            return f"❌ Error processing PDF: {str(e)}", "", "", ""
-    
-    # Responder pergunta
-    if question and question.strip():
-        if vectorstore is None:
-            answer = "⚠ Please upload a PDF first"
-        else:
-            try:
-                answer, sources, evaluation = run_rag(question, vectorstore)
-            except Exception as e:
-                answer = f"❌ Error: {str(e)}"
-    
-    return status, answer, sources, evaluation
-
-demo = gr.Interface(
-    fn=process_and_query,
-    inputs=[
-        gr.File(label="Upload PDF", file_types=[".pdf"]),
-        gr.Textbox(label="Question", placeholder="Ask about the document...")
-    ],
-    outputs=[
-        gr.Textbox(label="Status"),
-        gr.Textbox(label="Answer", lines=5),
-        gr.Textbox(label="Sources", lines=2),
-        gr.Textbox(label="Evaluation", lines=3)
-    ],
-    title="Tech Explainer — RAG with Automatic Evaluation",
-    description="Upload a PDF and ask questions about it",
-    theme=gr.themes.Soft()
-)
-
-demo.launch(share=False, server_name="0.0.0.0", server_port=7860)
+    if file is None:
+        return "Please upload a PDF file."
+    try:
+        vectorstore = process_pdf(file.name)
+        return "✓ Document processed successfully."
+    except Exception as e:
+        return f"❌ Error: {str(e)}"
+
+def ask(question):
+    if vectorstore is None:
+        return "⚠ Upload a document first", "", ""
+    if not question.strip():
+        return "⚠ Please enter a question", "", ""
+    try:
+        return run_rag(question, vectorstore)
+    except Exception as e:
+        return f"❌ Error: {str(e)}", "", ""
+
+with gr.Blocks() as demo:
+    gr.Markdown("# Tech Explainer — RAG with Automatic Evaluation")
+
+    file = gr.File(label="Upload PDF", file_types=[".pdf"])
+    load_btn = gr.Button("Process PDF")
+    status = gr.Textbox(label="Status")
+
+    gr.Markdown("---")
+
+    question = gr.Textbox(label="Question")
+    ask_btn = gr.Button("Ask")
+
+    answer = gr.Textbox(label="Answer", lines=5)
+    sources = gr.Textbox(label="Sources", lines=2)
+    evaluation = gr.Textbox(label="Evaluation", lines=3)
+
+    load_btn.click(load_document, inputs=file, outputs=status)
+    ask_btn.click(ask, inputs=question, outputs=[answer, sources, evaluation])
+
+demo.launch()

requirements.txt

@@ -1,4 +1,5 @@
-gradio==4.44.1
+gradio==4.44.0
+pydantic==2.9.2
 transformers
 sentence-transformers
 faiss-cpu