Update main.py

main.py

@@ -5,13 +5,13 @@ import openai
 import qdrant_client
 
 
-# from sentence_transformers import SentenceTransformer
+from sentence_transformers import SentenceTransformer
 #model = SentenceTransformer('paraphrase-multilingual-MiniLM-L12-v2') # good so far
-#model = SentenceTransformer('models/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2') # good so far
+model = SentenceTransformer('models/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2') # good so far
 
-from langchain.embeddings import HuggingFaceEmbeddings
+# from langchain.embeddings import HuggingFaceEmbeddings
 
-model = HuggingFaceEmbeddings(model_name='paraphrase-multilingual-MiniLM-L12-v2')
+# model = HuggingFaceEmbeddings(model_name='paraphrase-multilingual-MiniLM-L12-v2')
 
 import os
 os.environ['TRANSFORMERS_CACHE'] = '/blabla/cache/'
@@ -94,7 +94,7 @@ def chat():
 def perform_search_and_get_results(collection_name, query, limit=6):
     search_results = client.search(
         collection_name=collection_name,
-        query_vector=model.embed_query(query).tolist(),
+        query_vector=model.encode(query).tolist(),
         limit=limit
     )
     resultes = []
@@ -113,7 +113,7 @@ def perform_search_and_get_results_with_filter(collection_name, query,reference_
     search_results = client.search(
         collection_name=collection_name,
         query_filter=models.Filter(must=[models.FieldCondition(key="numero_article",match=models.MatchValue(value=reference_filter+"aymane",),)]),
-        query_vector=model.embed_query(query).tolist(),
+        query_vector=model.encode(query).tolist(),
         limit=1
     )
     resultes = []