Update rag.py

rag.py

@@ -85,6 +85,25 @@ class Rag:
                     chain_type="stuff",#map_reduce, refine, map_rerank
                     return_source_documents=True,
                 )
+        
+        # from langchain_together import Together
+        # self.qa = ConversationalRetrievalChain.from_llm(
+        #     llm=Together(model="mistralai/Mixtral-8x7B-Instruct-v0.1",  # 0125 #1106
+        #                    temperature=0,
+        #                    #top_k=20,
+        #                    together_api_key=os.environ['TOGETHER_KEY'],
+        #                    max_tokens=int(int(max_words) + (int(max_words) / 2))),
+        #     # número máximo de tokens para a resposta
+        #     memory=self.memory,
+        #     # retriever=vectorstore.as_retriever(search_type='similarity_score_threshold',
+        #     #                                    search_kwargs={'k':4, 'score_threshold':0.8}), #search_kwargs={'k': 3}
+        #     retriever=vectorstore.as_retriever(),
+        #     combine_docs_chain_kwargs={"prompt": self.prompt},
+        #     chain_type="stuff",  # map_reduce, refine, map_rerank
+        #     return_source_documents=True,
+        # )
+
+        
     def generate_text(self, subject):
         try:
             query = f"Elabore uma nova notícia sobre {subject}."