Spaces:
Sleeping
Sleeping
File size: 5,987 Bytes
1a1713a e965a47 1a1713a e965a47 c4a66be f6bd747 e965a47 6c6f994 e965a47 c41f6ba 7a6f18c 3fa3f1b 7a6f18c fd851a9 c41f6ba c7d40b5 e965a47 3fa3f1b e965a47 f6bd747 e965a47 f6bd747 65028b5 c4a66be 1a1713a 66cc86e c41f6ba 66cc86e | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 | """
FastAPI server using openenv.core base classes — required for validator.
"""
import random
from typing import Optional
from openenv.core.env_server.http_server import create_app
from openenv.core.env_server.interfaces import Environment
from openenv.core.env_server.types import State
try:
from sql_env.models import SQLAction, SQLObservation, SQLState
from sql_env.tasks import TASK_SETS
from sql_env.grader import grade, generate_feedback
except ImportError:
from models import SQLAction, SQLObservation, SQLState
from tasks import TASK_SETS
from grader import grade, generate_feedback
class SQLCorrectionEnvironment(Environment):
def __init__(self):
super().__init__()
self._difficulty = "easy"
self._current_task = None
self._step_count = 0
self._done = False
self._last_reward = 0.0
self._rewards_history = []
def reset(self, difficulty: str = "easy", task_id: str = None, **kwargs) -> SQLObservation:
actual_difficulty = task_id or difficulty or "easy"
self._difficulty = actual_difficulty
tasks = TASK_SETS.get(actual_difficulty, TASK_SETS["easy"])
self._current_task = random.choice(tasks)
self._step_count = 0
self._done = False
self._last_reward = 0.0
self._rewards_history = []
return SQLObservation(
task_id=self._current_task.task_id,
broken_query=self._current_task.broken_query,
schema_context=self._current_task.schema_context,
error_hint=self._current_task.error_hint,
step_number=0,
previous_attempt=None,
feedback=None,
reward=0.001,
done=False,
)
def step(self, action: SQLAction) -> SQLObservation:
if self._current_task is None:
self.reset()
self._step_count += 1
reward_obj = grade(action, self._current_task)
reward = reward_obj.value
self._last_reward = reward
self._rewards_history.append(reward)
done = (reward >= 0.95) or (self._step_count >= self._current_task.max_steps)
self._done = done
feedback = generate_feedback(action, self._current_task, reward_obj)
return SQLObservation(
task_id=self._current_task.task_id,
broken_query=self._current_task.broken_query,
schema_context=self._current_task.schema_context,
error_hint=self._current_task.error_hint,
step_number=self._step_count,
previous_attempt=action.corrected_query,
feedback=feedback,
reward=reward,
done=done,
)
def state(self) -> SQLState:
if self._current_task is None:
return SQLState(
task_id="none",
difficulty="none",
step_count=0,
max_steps=0,
done=False,
last_reward=0.0,
rewards_history=[],
)
return SQLState(
task_id=self._current_task.task_id,
difficulty=self._difficulty,
step_count=self._step_count,
max_steps=self._current_task.max_steps,
done=self._done,
last_reward=self._last_reward,
rewards_history=self._rewards_history,
)
def step(self, action: SQLAction) -> SQLObservation:
# Auto-reset if no task loaded (create_app may use fresh instances)
if self._current_task is None:
self.reset()
self._step_count += 1
reward_obj = grade(action, self._current_task)
reward = reward_obj.value
self._last_reward = reward
self._rewards_history.append(reward)
done = (reward >= 0.95) or (self._step_count >= self._current_task.max_steps)
self._done = done
feedback = generate_feedback(action, self._current_task, reward_obj)
return SQLObservation(
task_id=self._current_task.task_id,
broken_query=self._current_task.broken_query,
schema_context=self._current_task.schema_context,
error_hint=self._current_task.error_hint,
step_number=self._step_count,
previous_attempt=action.corrected_query,
feedback=feedback,
reward=reward,
done=done,
)
@property
def state(self) -> SQLState:
if self._current_task is None:
return SQLState(
task_id="none",
difficulty="none",
step_count=0,
max_steps=0,
done=False,
last_reward=0.001,
rewards_history=[],
)
return SQLState(
task_id=self._current_task.task_id,
difficulty=self._difficulty,
step_count=self._step_count,
max_steps=self._current_task.max_steps,
done=self._done,
last_reward=self._last_reward,
rewards_history=self._rewards_history,
)
app = create_app(
SQLCorrectionEnvironment,
SQLAction,
SQLObservation,
env_name="sql-correction-env",
max_concurrent_envs=1,
)
def main():
import uvicorn
uvicorn.run(app, host="0.0.0.0", port=7860)
if __name__ == "__main__":
main()
from fastapi import Request
@app.get("/tasks")
async def list_tasks():
return {
"tasks": [
{"id": "easy", "difficulty": "easy", "description": "Fix a single syntax error.", "steps": 5, "ideal_action": "correct_sql", "has_grader": True, "grader": "sql_env.grader.grade"},
{"id": "medium", "difficulty": "medium", "description": "Fix multiple errors.", "steps": 5, "ideal_action": "correct_sql", "has_grader": True, "grader": "sql_env.grader.grade"},
{"id": "hard", "difficulty": "hard", "description": "Fix complex multi-join queries.", "steps": 4, "ideal_action": "correct_sql", "has_grader": True, "grader": "sql_env.grader.grade"},
]
}
|