Update app.py

app.py

@@ -194,9 +194,37 @@ footer {
 }
 """
 
+import gradio as gr
+
+# Funções fictícias para os eventos
+def initialize_database(document, chunk_size, chunk_overlap):
+    # Lógica para inicializar o banco de dados vetorial
+    vector_db = "Banco de Dados Vetorial Inicializado"
+    collection_name = "Coleção 1"
+    db_progress = "Banco de Dados Inicializado"
+    return vector_db, collection_name, db_progress
+
+def initialize_LLM(llm_model, temperature, max_tokens, top_k, vector_db):
+    # Lógica para inicializar a cadeia LLM
+    qa_chain = "Cadeia de QA Inicializada"
+    llm_progress = "Cadeia LLM Inicializada"
+    return qa_chain, llm_progress
+
+def conversation(qa_chain, message, chatbot):
+    # Lógica de processamento de mensagem do chatbot
+    response = f"Resposta para: {message}"
+    doc_source1 = "Fonte 1"
+    source1_page = 1
+    doc_source2 = "Fonte 2"
+    source2_page = 2
+    doc_source3 = "Fonte 3"
+    source3_page = 3
+    chatbot.append((message, response))
+    return qa_chain, message, chatbot, doc_source1, source1_page, doc_source2, source2_page, doc_source3, source3_page
+
 # Interface Gradio
 def demo():
-    with gr.Blocks(theme=gr.themes.Default(primary_hue="blue", secondary_hue="gray"), css=custom_css) as demo:
+    with gr.Blocks(theme=gr.themes.Default(primary_hue="blue", secondary_hue="gray"), css=None) as demo:
         # Barra superior personalizada
         with gr.Row(visible=True, elem_id="top_bar"):
             gr.Image(value="https://huggingface.co/front/assets/huggingface_logo-noborder.svg", 
@@ -227,8 +255,6 @@ def demo():
             """
         )
 
-
-
         # Passo 1 - Upload do PDF
         with gr.Tab("Passo 1 - Carregar PDF"):
             with gr.Row():
@@ -255,7 +281,7 @@ def demo():
         # Passo 3 - Configuração da cadeia QA
         with gr.Tab("Passo 3 - Inicializar cadeia de QA"):
             with gr.Row():
-                llm_btn = gr.Radio(list_llm_simple, label="Modelos LLM", value=list_llm_simple[0], 
+                llm_btn = gr.Radio(["Model 1", "Model 2"], label="Modelos LLM", value="Model 1", 
                                  type="index", info="Escolha seu modelo LLM")
             with gr.Accordion("Opções avançadas - Modelo LLM", open=False):
                 with gr.Row():
@@ -295,13 +321,13 @@ def demo():
         process_btn.click(
             initialize_database,
             inputs=[document, slider_chunk_size, slider_chunk_overlap],
-            outputs=[vector_db, collection_name, db_progress]
+            outputs=[db_progress]
         )
 
         qa_init_btn.click(
             initialize_LLM,
-            inputs=[llm_btn, slider_temperature, slider_maxtokens, slider_topk, vector_db],
-            outputs=[qa_chain, llm_progress]
+            inputs=[llm_btn, slider_temperature, slider_maxtokens, slider_topk, db_progress],
+            outputs=[llm_progress]
         ).then(
             lambda: [None, "", 0, "", 0, "", 0],
             inputs=None,
@@ -334,4 +360,4 @@ def demo():
     demo.queue().launch(debug=True)
 
 if __name__ == "__main__":
-    demo()
+    demo()