Update app.py

app.py

@@ -14,12 +14,11 @@ from langchain.llms import HuggingFaceHub, LlamaCpp
 from huggingface_hub import snapshot_download, hf_hub_download
 
 
-# from prompts import CONDENSE_QUESTION_PROMPT
+# If you want to use gguf model, uncomment 18-19 and 54-62 lines, comment-out 64-65. Otherwise provide GigaChat Credentials through HF secrets menu
+#repo_name = "IlyaGusev/saiga_mistral_7b_gguf"
+#model_name = "model-q4_K.gguf"
 
-repo_name = "IlyaGusev/saiga_mistral_7b_gguf"
-model_name = "model-q4_K.gguf"
-
-#snapshot_download(repo_id=repo_name, local_dir=".", allow_patterns=model_name)
+snapshot_download(repo_id=repo_name, local_dir=".", allow_patterns=model_name)
 
 
 def get_pdf_text(pdf_docs):
@@ -34,8 +33,8 @@ def get_pdf_text(pdf_docs):
 
 def get_text_chunks(text):
     text_splitter = CharacterTextSplitter(separator="\n",
-                                          chunk_size=1000,  # 1000
-                                          chunk_overlap=200,  # 200
+                                          chunk_size=1000,  
+                                          chunk_overlap=200,
                                           length_function=len
                                           )
     chunks = text_splitter.split_text(text)
@@ -44,10 +43,7 @@ def get_text_chunks(text):
 
 
 def get_vectorstore(text_chunks):
-    #embeddings = OpenAIEmbeddings()
-    #embeddings = HuggingFaceInstructEmbeddings(model_name="hkunlp/instructor-xl")
     embeddings = HuggingFaceEmbeddings(model_name="intfloat/multilingual-e5-large")
-    #embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/paraphrase-multilingual-mpnet-base-v2")
     vectorstore = FAISS.from_texts(texts=text_chunks, embedding=embeddings)
 
     return vectorstore
@@ -65,8 +61,6 @@ def get_conversation_chain(vectorstore, model_name):
     #                echo=True
     #               )
 
-    # llm = ChatOpenAI()
-
     llm = GigaChat(credentials=os.getenv("GIGACHAT_CREDENTIALS"),
                    verify_ssl_certs=False)
     
@@ -106,13 +100,6 @@ def handle_userinput(user_question):
             st.write(bot_template.replace(
                 "{{MSG}}", str(text.page_content)), unsafe_allow_html=True)
 
-            
-            
-    #for text in enumerate(st.session_state.retrieved_text):
-    #    st.write(text[1].page_content, '\n')
-
-    #print(response['source_documents'][0])
-
 # main code
 load_dotenv()