Update app.py

app.py

@@ -8,20 +8,20 @@ from langchain.chains import LLMChain
 from langchain_core.output_parsers.string import StrOutputParser
 from langchain.chat_models import ChatOpenAI
 from langchain.embeddings.openai import OpenAIEmbeddings
-from langchain.embeddings import HuggingFaceBgeEmbeddings
+#from langchain.embeddings import HuggingFaceBgeEmbeddings
 
 from sentence_transformers import SentenceTransformer
 
 #embeddings = OpenAIEmbeddings()
-model_name = "BAAI/bge-large-en-v1.5"
-model_kwargs = {'device':'cuda'}
-encode_kwargs = {'normalize_embeddings':True}
-
-embedding_function = HuggingFaceBgeEmbeddings(
-    model_name = model_name,
-    model_kwargs = model_kwargs,
-    encode_kwargs = encode_kwargs
-)
+#model_name = "BAAI/bge-large-en-v1.5"
+#model_kwargs = {'device':'cuda'}
+#encode_kwargs = {'normalize_embeddings':True}
+
+#embedding_function = HuggingFaceBgeEmbeddings(
+#    model_name = model_name,
+#    model_kwargs = model_kwargs,
+#    encode_kwargs = encode_kwargs
+#)
 
 embedder = SentenceTransformer('all-mpnet-base-v2')
 
@@ -29,7 +29,7 @@ embedder = SentenceTransformer('all-mpnet-base-v2')
 #openai.api_key = os.getenv("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")
 
 # Load the FAISS index using LangChain's FAISS implementation
-db = FAISS.load_local("Faiss_index", embedding_function, allow_dangerous_deserialization=True)
+db = FAISS.load_local("Faiss_index", embedder, allow_dangerous_deserialization=True)
 parser = StrOutputParser()
 
 # Load your data (e.g., a DataFrame)