fix model

app/VectorStore/chroma-collections.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:6500348785bdf69480c86a933feaa0dd3328a9acffda71e251ca9928c6813627
-size 957
+oid sha256:ab6e5b0679e953f06abf1c6e74ddfc5ffafc233169ce2d6e08b99c1337c5e0cc
+size 1036

app/utils.py

@@ -52,8 +52,8 @@ def load_files():
             'Add to exsisting collection or create a new one',
             collections )
         if st.button('Delete Collection (⚠️ This is destructive and not reversible)'):
-            client.delete_collection(name=selected_collection)
-            retrieve_collections.clear()
+            client.delete_collection(name=selected_collection["name"])
+            #retrieve_collections.clear()
             collections = retrieve_collections()
 
         option = st.radio(
@@ -68,8 +68,9 @@ def load_files():
             if st.button('Upload'):
                 docs = load_from_file(uploaded_files)
                 sub_docs = load_and_split(docs, chunk_size=int(chunk_size))
-                create_and_add(selected_collection, sub_docs, None)
+                create_and_add(selected_collection["name"], sub_docs, selected_collection['model_name'], {"model_name": selected_collection['model_name']})
                 uploaded_files=None
+                st.write("Upload succesful")
         else:
             st.write('Urls of Source Documents (Comma separated):')
             urls = chunk_size = st.text_area('Urls:', '')
@@ -79,14 +80,16 @@ def load_files():
             if st.button('Upload'):
                 docs = load_from_web(urls)     
                 sub_docs = load_and_split(docs, chunk_size=int(chunk_size))
-                create_and_add(selected_collection, sub_docs, None)
+                create_and_add(selected_collection["name"], sub_docs, selected_collection['model_name'], {"model_name": selected_collection['model_name']})
                 uploaded_files=None
+                st.write("Upload succesful")
     else:
         collection = st.text_area('Name of your new collection:', '')
         model_name = st.text_area('Choose the embedding function:', "hkunlp/instructor-large")
         if st.button('Create'):
             if len(collection)>3:
                 ef = load_embedding(model_name)
-                client.create_collection(collection, embedding_function=ef) 
-                retrieve_collections.clear()
+                metadata= {"loaded_docs":[], "Subject":"Terms Example", "model_name": ef.model_name}
+                client.create_collection(collection, embedding_function=ef, metadata=metadata) 
+                # retrieve_collections.clear()
                 st.write("Collection " +collection+" succesfully created.")