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18feac5 | 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 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 | # # Copyright (c) Meta Platforms, Inc. and affiliates.
# # All rights reserved.
# #
# # This source code is licensed under the BSD-style license found in the
# # LICENSE file in the root directory of this source tree.
# """Tool Use Env Environment Client."""
# from typing import Dict
# from openenv.core import EnvClient
# from openenv.core.client_types import StepResult
# from openenv.core.env_server.types import State
# from .models import ToolUseAction, ToolUseObservation
# class ToolUseEnv(
# EnvClient[ToolUseAction, ToolUseObservation, State]
# ):
# """
# Client for the Tool Use Env Environment.
# This client maintains a persistent WebSocket connection to the environment server,
# enabling efficient multi-step interactions with lower latency.
# Each client instance has its own dedicated environment session on the server.
# Example:
# >>> # Connect to a running server
# >>> with ToolUseEnv(base_url="http://localhost:8000") as client:
# ... result = client.reset()
# ... print(result.observation.echoed_message)
# ...
# ... result = client.step(ToolUseAction(message="Hello!"))
# ... print(result.observation.echoed_message)
# Example with Docker:
# >>> # Automatically start container and connect
# >>> client = ToolUseEnv.from_docker_image("tool_use_env-env:latest")
# >>> try:
# ... result = client.reset()
# ... result = client.step(ToolUseAction(message="Test"))
# ... finally:
# ... client.close()
# """
# def _step_payload(self, action: ToolUseAction) -> Dict:
# """
# Convert ToolUseAction to JSON payload for step message.
# Args:
# action: ToolUseAction instance
# Returns:
# Dictionary representation suitable for JSON encoding
# """
# return {
# "message": action.message,
# }
# def _parse_result(self, payload: Dict) -> StepResult[ToolUseObservation]:
# """
# Parse server response into StepResult[ToolUseObservation].
# Args:
# payload: JSON response data from server
# Returns:
# StepResult with ToolUseObservation
# """
# obs_data = payload.get("observation", {})
# observation = ToolUseObservation(
# echoed_message=obs_data.get("echoed_message", ""),
# message_length=obs_data.get("message_length", 0),
# done=payload.get("done", False),
# reward=payload.get("reward"),
# metadata=obs_data.get("metadata", {}),
# )
# return StepResult(
# observation=observation,
# reward=payload.get("reward"),
# done=payload.get("done", False),
# )
# def _parse_state(self, payload: Dict) -> State:
# """
# Parse server response into State object.
# Args:
# payload: JSON response from state request
# Returns:
# State object with episode_id and step_count
# """
# return State(
# episode_id=payload.get("episode_id"),
# step_count=payload.get("step_count", 0),
# )
from openenv.core.env_client import EnvClient
from openenv.core.client_types import StepResult
from tool_use_env.models import ToolUseAction, ToolUseObservation, ToolUseState
class ToolUseEnv(EnvClient[ToolUseAction, ToolUseObservation, ToolUseState]):
def _step_payload(self, action: ToolUseAction) -> dict:
return {
"action_type": action.action_type,
"artifact_id": action.artifact_id,
"query": action.query,
"message": action.message,
"resolution_code": action.resolution_code,
}
def _parse_result(self, payload: dict) -> StepResult:
obs_data = payload.get("observation", {})
observation = ToolUseObservation(
done=payload.get("done", False),
reward=payload.get("reward"),
task_id=obs_data.get("task_id", ""),
difficulty=obs_data.get("difficulty", "easy"),
objective=obs_data.get("objective", ""),
customer_message=obs_data.get("customer_message", ""),
workspace_summary=obs_data.get("workspace_summary", ""),
available_actions=obs_data.get("available_actions", []),
available_resolution_codes=obs_data.get("available_resolution_codes", []),
collected_evidence=obs_data.get("collected_evidence", []),
last_tool_result=obs_data.get("last_tool_result"),
last_action_error=obs_data.get("last_action_error"),
remaining_steps=obs_data.get("remaining_steps", 0),
current_score=obs_data.get("current_score", 0.0),
metadata=obs_data.get("metadata", {}),
)
return StepResult(
observation=observation,
reward=payload.get("reward"),
done=payload.get("done", False),
)
def _parse_state(self, payload: dict) -> ToolUseState:
return ToolUseState(
episode_id=payload.get("episode_id"),
step_count=payload.get("step_count", 0),
task_id=payload.get("task_id", ""),
task_name=payload.get("task_name", ""),
difficulty=payload.get("difficulty", ""),
objective=payload.get("objective", ""),
cumulative_reward=payload.get("cumulative_reward", 0.0),
final_score=payload.get("final_score", 0.0),
drafted_reply=payload.get("drafted_reply"),
resolution_code=payload.get("resolution_code"),
expected_resolution_code=payload.get("expected_resolution_code", ""),
required_evidence=payload.get("required_evidence", []),
collected_evidence=payload.get("collected_evidence", []),
action_history=payload.get("action_history", []),
repeat_action_count=payload.get("repeat_action_count", 0),
last_action_error=payload.get("last_action_error"),
known_artifacts=payload.get("known_artifacts", {}),
known_policies=payload.get("known_policies", {}),
)
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