new

app.py

@@ -10,9 +10,11 @@ import numpy as np
 from langchain.embeddings import HuggingFaceEmbeddings
 from langchain import HuggingFaceHub
 from typing import Any, Dict, List
-embeddings = HuggingFaceEmbeddings()
+from InstructorEmbedding import INSTRUCTOR
+from langchain.embeddings import HuggingFaceInstructEmbeddings
+instructor_embeddings = HuggingFaceInstructEmbeddings(model_name="hkunlp/instructor-xl")
 HUGGINGFACEHUB_API_TOKEN='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'
-new_vectorstore = FAISS.load_local("./faiss_docs_index", embeddings)
+new_vectorstore = FAISS.load_local("./faiss_docs_xl_index", embeddings)
 llm = HuggingFaceHub(repo_id="declare-lab/flan-alpaca-large", model_kwargs={"temperature": 0.1, "max_length": 512},huggingfacehub_api_token= "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")