Update app.py

app.py

@@ -9,6 +9,7 @@ from langchain_community.vectorstores import FAISS
 from langchain_community.embeddings import HuggingFaceEmbeddings
 from langchain_community.llms import HuggingFacePipeline
 from transformers import BitsAndBytesConfig
+from langchain.embeddings.huggingface import HuggingFaceEmbeddings
 
 from langchain.prompts import PromptTemplate
 from langchain.schema.runnable import RunnablePassthrough
@@ -24,19 +25,11 @@ import transformers
 model_name='mistralai/Mistral-7B-Instruct-v0.1'
 from huggingface_hub import login
 login(token=st.secrets["HF_TOKEN"])
+llm = HuggingFaceEndpoint(
+    repo_id=repo_id, max_length=128, temperature=0.5, token=st.secrets["HF_TOKEN"]
+)
 
-# model loading.
-model = AutoModelForCausalLM.from_pretrained("TheBloke/Mistral-7B-Instruct-v0.1-GGUF",
-                                             model_file="mistral-7b-instruct-v0.1.Q5_K_M.gguf",
-                                             model_type="mistral",
-                                             max_new_tokens=1048,
-                                             temperature=0.01,
-                                             hf=True
-                                             )
-
-#initializes a tokenizer for the specified LLM model.
-tokenizer = AutoTokenizer.from_pretrained(model)
-dataset= load_dataset("mery22/testub/test-1.pdf")
+dataset= load_dataset("test-1.pdf")
 loader = PyPDFLoader(dataset)
 data = loader.load()
 text_splitter1 = CharacterTextSplitter(chunk_size=512, chunk_overlap=0,separator="\n\n")