use fine tuned model (1st model)

app.py

@@ -38,7 +38,7 @@ chainlit_state.qa_model_name = "gpt-4o-mini"
 chainlit_state.qa_model = ChatOpenAI(model=chainlit_state.qa_model_name, openai_api_key=openai_api_key)
 
 hf_username = "rchrdgwr"
-hf_repo_name = "finetuned-arctic-model-2"
+hf_repo_name = "finetuned-arctic-model"
 finetuned_model_name = f"{hf_username}/{hf_repo_name}"
 
 chainlit_state.embedding_model_name = finetuned_model_name
@@ -109,8 +109,12 @@ async def main(message):
     chunk_string = "Sources: "
     for doc in context_documents:
         document_title = doc.metadata.get("source", "Unknown Document") 
-        chunk_number = doc.metadata.get("chunk_number", "Unknown Chunk") 
-        chunk_string = chunk_string + " " + document_title + str(chunk_number)
+        chunk_number = doc.metadata.get("chunk_number", "Unknown Chunk")
+        if document_title == "":
+            doc_string = "BOR"
+        else:
+            doc_string = "RMF" 
+        chunk_string = chunk_string + " " + doc_string + "-" + str(chunk_number)
 
     await cl.Message(
         content=f"{chunk_string}",