Shipgit add .

app.py

@@ -56,10 +56,8 @@ rag_prompt = ChatPromptTemplate.from_template("""\
 vectorstore = VectorStore(
   collection_name="mg_alloy_collection_snowflake",
 )
-if not os.path.exists("data/collections/collection"):
-  documents = VectorStore.load_chunks_as_documents("data/contextual_chunks")
-  vectorstore.add_documents(documents)
-  
+documents = VectorStore.load_chunks_as_documents("data/contextual_chunks")
+vectorstore.add_documents(documents)
 retriever = vectorstore.as_retriever(k=5)
 
 # ------- Pydantic Models ------- #

vectorstore.py

@@ -31,17 +31,8 @@ SPARSE_EMBEDDINGS = FastEmbedSparse(model_name="Qdrant/BM25")
 class VectorStore:
     def __init__(self, collection_name="testCollection"):
         
-        # Initialize the Qdrant client
-        self.collection_name = collection_name
-        self.collections_path= "data/collections"
-        try:
-            lock_file = os.path.join(self.collections_path, ".lock")
-            if os.path.exists(lock_file):
-                os.remove(lock_file)
-        except:
-            pass
-                
-        self.client = QdrantClient(path=self.collections_path)
+
+        self.client = QdrantClient(":memory:")
         
         # create the collection if it doesn't exist
         if not self.client.collection_exists(collection_name):