fixv2

app.py

@@ -267,7 +267,6 @@ from langchain_core.runnables import RunnablePassthrough
 import chromadb
 chromadb.api.client.SharedSystemClient.clear_system_cache()
 os.environ['MISTRAL_API_KEY'] = 'XuyOObDE7trMbpAeI7OXYr3dnmoWy3L0'
-
 class VectorData():
     def __init__(self):
         embedding_model_name = 'l3cube-pune/punjabi-sentence-similarity-sbert'
@@ -278,32 +277,26 @@ class VectorData():
             model_kwargs=model_kwargs
         )
 
-        # Initialize ChromaDB client with proper settings
-        client_settings = chromadb.Settings(
-            chroma_db_impl="duckdb+parquet",
-            persist_directory="chroma_db",
-            anonymized_telemetry=False
-        )
+        # Initialize ChromaDB with new configuration
+        self.client = chromadb.PersistentClient(path="chroma_db")
         
-        # Create ChromaDB client
-        self.client = chromadb.Client(client_settings)
-        
-        # Create or get collection
-        self.collection = self.client.create_collection(
+        # Create or get collection with embeddings
+        self.collection = self.client.get_or_create_collection(
             name="my_collection",
-            get_or_create=True
+            metadata={"hnsw:space": "cosine"}
         )
 
-        # Initialize vectorstore with the client
+        # Initialize vectorstore
         self.vectorstore = Chroma(
             client=self.client,
             collection_name="my_collection",
-            embedding_function=self.embeddings,
-            persist_directory="chroma_db"
+            embedding_function=self.embeddings
         )
+        
         self.retriever = self.vectorstore.as_retriever()
         self.ingested_files = []
         
+        # Rest of your initialization code remains the same
         self.prompt = ChatPromptTemplate.from_messages(
             [
                 (