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b192407 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 | """
Base Agent Module - Defines the unified PromptAgent interface shared by all
agent implementations under testbed/da_agent/agent/.
All agents are constructed by run.py ONCE with the same keyword arguments
(model, max_tokens, top_p, temperature, max_memory_length, max_steps), then
set_env_and_task(env) is called per task before run(). This base class owns
that constructor and the cross-task state, so subclasses never re-declare the
parameter list. Per-task state belongs solely in set_env_and_task (no
duplication with __init__). Subclasses must implement set_env_and_task, run,
and get_trajectory.
"""
from da_agent.envs.da_agent import DA_Agent_Env
class BaseAgent:
"""Common constructor config and interface contract for all agents.
LLM/generation knobs that a given backend does not need are still accepted
(and stored) so every PromptAgent can be built with the same call site.
__init__ holds only cross-task state; per-task state is (re)initialized in
set_env_and_task, which runs before every run().
"""
def __init__(
self,
model,
max_tokens,
top_p,
temperature,
max_memory_length,
max_steps,
):
# LLM / generation config (some agents use only a subset).
self.model = model
self.max_tokens = max_tokens
self.top_p = top_p
self.temperature = temperature
self.max_memory_length = max_memory_length
self.max_steps = max_steps
# Cross-task runtime state (set_env_and_task overwrites per task).
self.env: DA_Agent_Env | None = None
self.instruction = ""
self.trajectory = []
self.work_dir = "/workspace"
def set_env_and_task(self, env: DA_Agent_Env):
raise NotImplementedError
def run(self):
raise NotImplementedError
def get_trajectory(self):
raise NotImplementedError |