mirror of
https://github.com/cpacker/MemGPT.git
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85faf5f474
Co-authored-by: Charles Packer <packercharles@gmail.com> Co-authored-by: Shubham Naik <shubham.naik10@gmail.com> Co-authored-by: Shubham Naik <shub@memgpt.ai>
91 lines
2.6 KiB
Python
91 lines
2.6 KiB
Python
import os
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import uuid
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from sqlalchemy import MetaData, Table, create_engine
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from letta import create_client
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from letta.config import LettaConfig
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from letta.data_types import AgentState, EmbeddingConfig, LLMConfig
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from letta.metadata import MetadataStore
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from letta.presets.presets import add_default_tools
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from letta.prompts import gpt_system
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# Replace this with your actual database connection URL
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config = LettaConfig.load()
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if config.recall_storage_type == "sqlite":
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DATABASE_URL = "sqlite:///" + os.path.join(config.recall_storage_path, "sqlite.db")
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else:
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DATABASE_URL = config.recall_storage_uri
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print(DATABASE_URL)
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engine = create_engine(DATABASE_URL)
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metadata = MetaData()
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# defaults
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system_prompt = gpt_system.get_system_text("memgpt_chat")
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# Reflect the existing table
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table = Table("agents", metadata, autoload_with=engine)
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# get all agent rows
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agent_states = []
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with engine.connect() as conn:
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agents = conn.execute(table.select()).fetchall()
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for agent in agents:
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id = uuid.UUID(agent[0])
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user_id = uuid.UUID(agent[1])
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name = agent[2]
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print(f"Migrating agent {name}")
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persona = agent[3]
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human = agent[4]
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system = agent[5]
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preset = agent[6]
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created_at = agent[7]
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llm_config = LLMConfig(**agent[8])
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embedding_config = EmbeddingConfig(**agent[9])
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state = agent[10]
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tools = agent[11]
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state["memory"] = {"human": {"value": human, "limit": 2000}, "persona": {"value": persona, "limit": 2000}}
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agent_state = AgentState(
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id=id,
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user_id=user_id,
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name=name,
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system=system,
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created_at=created_at,
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llm_config=llm_config,
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embedding_config=embedding_config,
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state=state,
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tools=tools,
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_metadata={"human": "migrated", "persona": "migrated"},
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)
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agent_states.append(agent_state)
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# remove agents table
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agents_model = Table("agents", metadata, autoload_with=engine)
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agents_model.drop(engine)
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# remove tool table
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tool_model = Table("toolmodel", metadata, autoload_with=engine)
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tool_model.drop(engine)
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# re-create tables and add default tools
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ms = MetadataStore(config)
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add_default_tools(None, ms)
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print("Tools", [tool.name for tool in ms.list_tools()])
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for agent in agent_states:
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ms.create_agent(agent)
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print(f"Agent {agent.name} migrated successfully!")
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# add another agent to create core memory tool
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client = create_client()
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dummy_agent = client.create_agent(name="dummy_agent")
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tools = client.list_tools()
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assert "core_memory_append" in [tool.name for tool in tools]
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print("Migration completed successfully!")
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