from knowlyrcore.env import AgentEnv
from knowlyrcore.timestep import TimeStep

class MyEnv(AgentEnv):
    domain = "my_domain"

    def reset(self, *, task=None, seed=None) -> TimeStep:
        return TimeStep(observation="ready")

    def step(self, action: dict) -> TimeStep:
        return TimeStep(observation="result", terminated=(action["tool"] == "submit"))

    @property
    def available_tools(self):
        return ["observe", "act", "submit"]

from knowlyrcore.registry import register, make, list_envs

register("my-project/my-env", MyEnv, domain="my_domain")

env = make("my-project/my-env")      # 按 ID 创建实例
envs = list_envs(domain="coding")    # 按领域查询

from knowlyrcore.wrappers import MaxStepsWrapper, RewardWrapper, RecorderWrapper

env = make("knowlyr/sandbox")
env = MaxStepsWrapper(env, max_steps=50)           # 限制步数
env = RewardWrapper(env, reward_fn=my_reward_fn)   # 注入 reward
env = RecorderWrapper(env, agent_name="my-agent")  # 录制轨迹

ts = env.reset(task=my_task)
while not ts.done:
    action = agent(ts.observation)
    ts = env.step(action)

trajectory = env.get_trajectory()   # RecorderWrapper 提供

from trajectoryhub import collect

trajs = collect(
    "knowlyr/sandbox",       # env ID 或 AgentEnv 实例
    agent=my_agent,          # (observation) -> action dict
    n_episodes=10,
    max_steps=30,
    agent_name="my-agent",
    model_name="gpt-4o",
)

from knowlyrcore import DomainProfile, ToolSpec, ToolCategory, OutcomeSpec

profile = DomainProfile(
    domain="my_domain",
    display_name="My Custom Domain",
    tools=[
        ToolSpec(name="observe", category=ToolCategory.READ, stateful_key="target"),
        ToolSpec(name="act", category=ToolCategory.WRITE, stateful_key="target"),
        ToolSpec(name="search", category=ToolCategory.SEARCH),
        ToolSpec(name="done", category=ToolCategory.SUBMIT),
    ],
    outcome_spec=OutcomeSpec(success_field="success", score_field="score"),
    default_rubric_weights={
        "goal_progress": 0.35,
        "tool_selection": 0.20,
        "param_correctness": 0.20,
        "info_utilization": 0.10,
        "non_redundancy": 0.15,
    },
)

from agentrecorder.adapters import BaseAdapter, register_adapter

class MyAgentAdapter(BaseAdapter):
    domain = "browser"

    def parse(self, log_path: str) -> Trajectory:
        ...  # 解析你的 Agent 日志

    def validate(self, log_path: str) -> bool:
        ...  # 验证日志格式

register_adapter("my-agent", MyAgentAdapter)