langchain-google-community

import os from langchain_google_community.chat_message_histories import BigQueryChatMessageHistory from langchain_core.messages import HumanMessage, AIMessage # Ensure you have GOOGLE_CLOUD_PROJECT, BIGQUERY_DATASET_NAME, BIGQUERY_TABLE_NAME set as environment variables # or pass them directly to the constructor. project_id = os.environ.get('GOOGLE_CLOUD_PROJECT', 'your-gcp-project-id') dataset_name = os.environ.get('BIGQUERY_DATASET_NAME', 'langchain_chat_history') table_name = os.environ.get('BIGQUERY_TABLE_NAME', 'chat_sessions') session_id = 'test_session_123' if not all([project_id, dataset_name, table_name]) or project_id == 'your-gcp-project-id': print("Warning: Skipping BigQuery history quickstart. Please set GOOGLE_CLOUD_PROJECT, BIGQUERY_DATASET_NAME, and BIGQUERY_TABLE_NAME environment variables.") print("Alternatively, replace 'your-gcp-project-id' with a valid project ID.") else: try: # Initialize BigQuery Chat Message History history = BigQueryChatMessageHistory( project_id=project_id, dataset_name=dataset_name, table_name=table_name, session_id=session_id ) # Add messages history.add_user_message("Hi there!") history.add_ai_message("Hello! How can I help you today?") history.add_message(HumanMessage(content="Tell me a joke.")) history.add_message(AIMessage(content="Why don't scientists trust atoms? Because they make up everything!")) # Retrieve messages messages = history.messages print(f"Retrieved {len(messages)} messages for session '{session_id}':") for msg in messages: print(f" {type(msg).__name__}: {msg.content}") # Clear messages (optional, for cleanup) # history.clear() # print("History cleared.") except Exception as e: print(f"Error running BigQuery history quickstart: {e}") print("Ensure you have authenticated with Google Cloud (e.g., `gcloud auth application-default login`) and BigQuery API is enabled in project: {project_id}.")