diff --git a/main.py b/main.py index 13389f98f..920d7d90b 100644 --- a/main.py +++ b/main.py @@ -394,7 +394,8 @@ async def user_context_enrichment(session, user_id:str, query:str, generative_re query = translate_text(query, "sr", "en") logging.info("Translated query is %s", str(query)) - try: + if memory_type=='PublicMemory': + neo4j_graph_db = Neo4jGraphDB(url=config.graph_database_url, username=config.graph_database_username, password=config.graph_database_password) @@ -457,6 +458,7 @@ async def user_context_enrichment(session, user_id:str, query:str, generative_re observation=query, params=postgres_id[0], search_type="summary_filter_by_object_name") logging.info("Result is", str(results)) + search_context = "" for result in results['data']['Get'][namespace_id]: @@ -464,7 +466,8 @@ async def user_context_enrichment(session, user_id:str, query:str, generative_re source = result['source'] text = result['text'] search_context += f"Document source: {source}, Document text: {text} \n" - except: + + else: search_context = "No relevant documents found" context = f""" You are a memory system that uses cognitive architecture to enrich the @@ -706,7 +709,7 @@ async def main(): # await attach_user_to_memory(user_id=user_id, labels=['sr'], topic="PublicMemory") - return_ = await user_context_enrichment(user_id=user_id, query="hi how are you", session=session, memory_type="SemanticMemory", generative_response=False) + return_ = await user_context_enrichment(user_id=user_id, query="what should the size of a staircase in an apartment building be", session=session, memory_type="PublicMemory", generative_response=False) print(return_) # aa = await relevance_feedback("I need to understand how to build a staircase in an apartment building", "PublicMemory") # print(aa)