Update app.py

app.py

@@ -26,27 +26,24 @@ ranker = Reranker("answerdotai/answerai-colbert-small-v1", model_type='colbert')
 
 def generate_text(context, query):
     inputs = f"Context: {context} Question: {query}"
-    response = client.chat_completion(inputs=inputs, task="text2text-generation")
+    response = client.text_generation(prompt=inputs)
     return response
-
+    
 def test_rag_reranking(query, ranker):
     docs = vectordb.similarity_search_with_score(query)
     context = []
+    
     for doc, score in docs:
         if score < 7:  
             doc_details = doc.to_json()['kwargs']
             context.append(doc_details['page_content'])
 
-    if len(context) > 0:
-        useful_context = context[0]  
-        generation = generate_text(useful_context, query)
-        return generation
-    else:
+    if not context:
         return "No se encontró información suficiente para responder."
 
-    ranked = ranker.rerank(query=query, documents=raw_contexts, top_k=1)
+    reranked = ranker.rerank(query=query, documents=context, top_k=1)
+    best_context = reranked[0]["content"]
 
-    best_context = ranked[0]["content"]
     return generate_text(best_context, query)
 
 def responder_chat(message, history):