minor fix

evaluations/evaluator.py

@@ -35,5 +35,5 @@ def langsmith_app(inputs):
     langsmith_app, # Your AI system
     data=dataset_name, # The data to predict and grade over
     evaluators=[evaluator], # The evaluators to score the results
-    experiment_prefix="metadata-chatbot-0.0.52", # A prefix for your experiment names to easily identify them
+    experiment_prefix="metadata-chatbot-0.0.53", # A prefix for your experiment names to easily identify them
 )

src/metadata_chatbot/agents/workflow.py

@@ -5,7 +5,7 @@
 from metadata_chatbot.agents.docdb_retriever import DocDBRetriever
 
 #from agentic_graph import datasource_router, query_retriever, filter_generation_chain, doc_grader, rag_chain, db_rag_chain
-from metadata_chatbot.agents.agentic_graph import datasource_router, query_retriever, query_grader, filter_generation_chain, doc_grader, rag_chain, db_rag_chain
+from metadata_chatbot.agents.agentic_graph import datasource_router, query_retriever, filter_generation_chain, doc_grader, rag_chain, db_rag_chain
 
 logging.basicConfig(filename='async_workflow.log', level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s', filemode="w")
 
@@ -213,6 +213,6 @@ def generate_vi(state):
 
 # query = "How was the tissue prepared for imaging, including fixation, delipidation, and refractive index matching procedures? in experiment: SmartSPIM_675388_2023-05-24_04-10-19_stitched_2023-05-28_18-07-46"
 
-# inputs = {"query" : query}
+# inputs = {"query": query}
 # answer = app.invoke(inputs)
 # print(answer['generation'])