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Refactoring CLI to use config file, connect to Llama Index data sourc…
…es, and allow for multiple agents (#154) * Migrate to `memgpt run` and `memgpt configure` * Add Llama index data sources via `memgpt load` * Save config files for defaults and agents
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,148 @@ | ||
| import typer | ||
| import sys | ||
| import io | ||
| import logging | ||
| import asyncio | ||
| import os | ||
| from prettytable import PrettyTable | ||
| import questionary | ||
| import openai | ||
|
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||
| from llama_index import set_global_service_context | ||
| from llama_index import VectorStoreIndex, SimpleDirectoryReader, ServiceContext | ||
|
|
||
| import memgpt.interface # for printing to terminal | ||
| from memgpt.cli.cli_config import configure | ||
| import memgpt.agent as agent | ||
| import memgpt.system as system | ||
| import memgpt.presets as presets | ||
| import memgpt.constants as constants | ||
| import memgpt.personas.personas as personas | ||
| import memgpt.humans.humans as humans | ||
| import memgpt.utils as utils | ||
| from memgpt.utils import printd | ||
| from memgpt.persistence_manager import LocalStateManager | ||
| from memgpt.config import MemGPTConfig, AgentConfig | ||
| from memgpt.constants import MEMGPT_DIR | ||
| from memgpt.agent import AgentAsync | ||
| from memgpt.embeddings import embedding_model | ||
|
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||
|
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| def run( | ||
| persona: str = typer.Option(None, help="Specify persona"), | ||
| agent: str = typer.Option(None, help="Specify agent save file"), | ||
| human: str = typer.Option(None, help="Specify human"), | ||
| model: str = typer.Option(None, help="Specify the LLM model"), | ||
| preset: str = typer.Option(None, help="Specify preset"), | ||
| data_source: str = typer.Option(None, help="Specify data source to attach to agent"), | ||
| first: bool = typer.Option(False, "--first", help="Use --first to send the first message in the sequence"), | ||
| debug: bool = typer.Option(False, "--debug", help="Use --debug to enable debugging output"), | ||
| no_verify: bool = typer.Option(False, "--no_verify", help="Bypass message verification"), | ||
| yes: bool = typer.Option(False, "-y", help="Skip confirmation prompt and use defaults"), | ||
| ): | ||
| """Start chatting with an MemGPT agent | ||
| Example usage: `memgpt run --agent myagent --data-source mydata --persona mypersona --human myhuman --model gpt-3.5-turbo` | ||
| :param persona: Specify persona | ||
| :param agent: Specify agent name (will load existing state if the agent exists, or create a new one with that name) | ||
| :param human: Specify human | ||
| :param model: Specify the LLM model | ||
| :param data_source: Specify data source to attach to agent (if new agent is being created) | ||
| """ | ||
|
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||
| # setup logger | ||
| utils.DEBUG = debug | ||
| logging.getLogger().setLevel(logging.CRITICAL) | ||
| if debug: | ||
| logging.getLogger().setLevel(logging.DEBUG) | ||
|
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||
| if not MemGPTConfig.exists(): # if no config, run configure | ||
| if yes: | ||
| # use defaults | ||
| config = MemGPTConfig() | ||
| else: | ||
| # use input | ||
| configure() | ||
| config = MemGPTConfig.load() | ||
| else: # load config | ||
| config = MemGPTConfig.load() | ||
|
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| # override with command line arguments | ||
| if debug: | ||
| config.debug = debug | ||
| if no_verify: | ||
| config.no_verify = no_verify | ||
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||
| # determine agent to use, if not provided | ||
| if not yes and not agent: | ||
| agent_files = utils.list_agent_config_files() | ||
| agents = [AgentConfig.load(f).name for f in agent_files] | ||
|
|
||
| if len(agents) > 0: | ||
| select_agent = questionary.confirm("Would you like to select an existing agent?").ask() | ||
| if select_agent: | ||
| agent = questionary.select("Select agent:", choices=agents).ask() | ||
|
|
||
| # configure llama index | ||
| config = MemGPTConfig.load() | ||
| original_stdout = sys.stdout # unfortunate hack required to suppress confusing print statements from llama index | ||
| sys.stdout = io.StringIO() | ||
| embed_model = embedding_model(config) | ||
| service_context = ServiceContext.from_defaults(llm=None, embed_model=embed_model, chunk_size=config.embedding_chunk_size) | ||
| set_global_service_context(service_context) | ||
| sys.stdout = original_stdout | ||
|
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||
| # create agent config | ||
| if agent and AgentConfig.exists(agent): # use existing agent | ||
| typer.secho(f"Using existing agent {agent}", fg=typer.colors.GREEN) | ||
| agent_config = AgentConfig.load(agent) | ||
| printd("State path:", agent_config.save_state_dir()) | ||
| printd("Persistent manager path:", agent_config.save_persistence_manager_dir()) | ||
| printd("Index path:", agent_config.save_agent_index_dir()) | ||
| # persistence_manager = LocalStateManager(agent_config).load() # TODO: implement load | ||
| # TODO: load prior agent state | ||
| assert not any( | ||
| [persona, human, model] | ||
| ), f"Cannot override existing agent state with command line arguments: {persona}, {human}, {model}" | ||
|
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| # load existing agent | ||
| memgpt_agent = AgentAsync.load_agent(memgpt.interface, agent_config) | ||
| else: # create new agent | ||
| # create new agent config: override defaults with args if provided | ||
| typer.secho("Creating new agent...", fg=typer.colors.GREEN) | ||
| agent_config = AgentConfig( | ||
| name=agent if agent else None, | ||
| persona=persona if persona else config.default_persona, | ||
| human=human if human else config.default_human, | ||
| model=model if model else config.model, | ||
| preset=preset if preset else config.preset, | ||
| ) | ||
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| # attach data source to agent | ||
| agent_config.attach_data_source(data_source) | ||
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| # TODO: allow configrable state manager (only local is supported right now) | ||
| persistence_manager = LocalStateManager(agent_config) # TODO: insert dataset/pre-fill | ||
|
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| # save new agent config | ||
| agent_config.save() | ||
| typer.secho(f"Created new agent {agent_config.name}.", fg=typer.colors.GREEN) | ||
|
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| # create agent | ||
| memgpt_agent = presets.use_preset( | ||
| agent_config.preset, | ||
| agent_config, | ||
| agent_config.model, | ||
| agent_config.persona, | ||
| agent_config.human, | ||
| memgpt.interface, | ||
| persistence_manager, | ||
| ) | ||
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| # start event loop | ||
| from memgpt.main import run_agent_loop | ||
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| loop = asyncio.get_event_loop() | ||
| loop.run_until_complete(run_agent_loop(memgpt_agent, first, no_verify, config)) # TODO: add back no_verify |
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