# The Cli Interface of MemoryScope ## Usage Before running, follow the [**Installation**](../../docs/installation.md#iii-install-from-pypi) guidelines in Readme, and start the Docker image first. MemoryScope can be launched in two different ways: ### 1. Using YAML Configuration File If you prefer to configure your settings via a YAML file, you can do so by providing the path to the configuration file as follows: ```bash memoryscope --config_path=memoryscope/core/config/demo_config.yaml ``` ### 2. Using Command Line Arguments Alternatively, you can specify all the parameters directly on the command line: ```bash # Chinese / Dashscope memoryscope --language="cn" \ --memory_chat_class="cli_memory_chat" \ --human_name="用户" \ --assistant_name="AI" \ --generation_backend="dashscope_generation" \ --generation_model="qwen-max" \ --embedding_backend="dashscope_embedding" \ --embedding_model="text-embedding-v2" \ --enable_ranker=True \ --rank_backend="dashscope_rank" \ --rank_model="gte-rerank" # English / OpenAI memoryscope --language="en" \ --memory_chat_class="cli_memory_chat" \ --human_name="user" \ --assistant_name="AI" \ --generation_backend="openai_generation" \ --generation_model="gpt-4o" \ --embedding_backend="openai_embedding" \ --embedding_model="text-embedding-3-small" \ --enable_ranker=False ``` Here are the available options that can be set through either method: - `--language`: The language used for the conversation. - `--memory_chat_class`: The class name for managing the chat history. - `--human_name`: The name of the human user. - `--assistant_name`: The name of the AI assistant. - `--generation_backend`: The backend used for generating responses. - `--generation_model`: The model used for generating responses. - `--embedding_backend`: The backend used for text embeddings. - `--embedding_model`: The model used for creating text embeddings. - `--enable_ranker`: A boolean indicating whether to use a dummy ranker (default is `False`). - `--rank_backend`: The backend used for ranking responses. - `--rank_model`: The model used for ranking responses. ### 3. View Memory You can open two command line windows following the method in the second step. In one command line window, you can have a conversation with the AI, while in the other, you can check the AI's long-term memory about the user. Use /help to open the command line help, and find the command /list_memory along with the corresponding auto-refresh instruction. ``` /list_memory refresh_time=5 ``` Then you can enjoy a pleasant conversation with the AI!