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from pathlib import Path
from personal_agent.agent import Agent
from personal_agent.database.database import Database
from personal_agent.identity import load_agent_identity, load_user_profile
from personal_agent.llm import LLM
from personal_agent.logging import configure_logging
from personal_agent.memory.store import LongTermMemoryStore
from personal_agent.tools import (
CalculatorTool,
FileSystemListTool,
FileSystemReadTool,
ToolRegistry,
WeatherTool,
)
configure_logging()
llm = LLM(
"http://localhost:8080/v1/chat/completions",
)
agent_identity = load_agent_identity("agent.toml")
user_profile = load_user_profile("user.toml")
tools = ToolRegistry()
# tools.register(HelloTool())
tools.register(CalculatorTool())
tools.register(WeatherTool())
tools.register(FileSystemListTool())
tools.register(FileSystemReadTool())
database = Database(Path("data/agent.db"))
database.migrate()
long_term_memory_store = LongTermMemoryStore(database)
agent = Agent(
llm,
agent_identity,
user_profile,
tools,
long_term_memory_store,
)
while True:
user_input = input("You: ")
if user_input.lower() in {"exit", "quit"}:
break
match user_input:
case "/end":
agent.end_task()
print("[task ended]")
continue
case "/task":
print(f"\n[memory: {agent.working_memory}]\n")
continue
case "/pause":
agent.pause_task()
print("[task paused]")
continue
case "/resume":
agent.resume_task()
print("[task resumed]")
continue
case "/complete":
agent.complete_task()
print("[task completed]")
continue
answer = agent.chat(user_input)
print(f"Agent: {answer}")
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