Update app.py

app.py

@@ -24,7 +24,9 @@ import openai
 from langchain.llms import OpenAI
 
 from langchain.embeddings.openai import OpenAIEmbeddings
-#from langchain.embeddings.sentence_transformer import SentenceTransformerEmbeddings
+from langchain.embeddings import HuggingFaceBgeEmbeddings
+from langchain.embeddings import HuggingFaceInstructEmbeddings
+from langchain.embeddings import SentenceTransformerEmbeddings
 
 from langchain.document_loaders import SeleniumURLLoader, PyPDFLoader
 
@@ -61,10 +63,20 @@ def pretty_print_docs(docs):
 
 
 def getEmbeddingModel(embeddingId):
-    # if (embeddingId == 1):
-    #     embeddings = SentenceTransformerEmbeddings(model_name="all-MiniLM-L6-v2")
-    # else:
-    #     embeddings = OpenAIEmbeddings()
+    if (embeddingId == 1):
+        embeddings = SentenceTransformerEmbeddings(model_name="all-MiniLM-L6-v2")
+    elif (embeddingId == 2):
+        model_name = "hkunlp/instructor-large"
+        model_kwargs = {'device': 'cpu'}
+        encode_kwargs = {'normalize_embeddings': True}
+        embeddings = HuggingFaceInstructEmbeddings(model_name=model_name,model_kwargs=model_kwargs,encode_kwargs=encode_kwargs)
+    elif (embeddingId == 2):
+        model_name = "BAAI/bge-large-en-v1.5"
+        model_kwargs = {'device': 'cuda'}
+        encode_kwargs = {'normalize_embeddings': True} # set True to compute cosine similarity
+        model = HuggingFaceBgeEmbeddings(model_name=model_name,model_kwargs=model_kwargs,encode_kwargs=encode_kwargs)
+    else:
+        embeddings = OpenAIEmbeddings()
     return OpenAIEmbeddings()