diff --git a/rdagent/scenarios/data_science/proposal/exp_gen/parallel.py b/rdagent/scenarios/data_science/proposal/exp_gen/parallel.py
deleted file mode 100644
index fe3aab58..00000000
--- a/rdagent/scenarios/data_science/proposal/exp_gen/parallel.py
+++ /dev/null
@@ -1,101 +0,0 @@
-from __future__ import annotations
-
-import asyncio
-from datetime import timedelta
-from typing import TYPE_CHECKING
-
-from rdagent.app.data_science.conf import DS_RD_SETTING
-from rdagent.core.conf import RD_AGENT_SETTINGS
-from rdagent.core.proposal import ExperimentPlan, ExpGen
-from rdagent.log import rdagent_logger as logger
-from rdagent.log.timer import RD_Agent_TIMER_wrapper, RDAgentTimer
-from rdagent.scenarios.data_science.loop import DataScienceRDLoop
-from rdagent.scenarios.data_science.proposal.exp_gen.merge import ExpGen2Hypothesis
-from rdagent.scenarios.data_science.proposal.exp_gen.trace_scheduler import (
-    RoundRobinScheduler,
-    TraceScheduler,
-)
-
-if TYPE_CHECKING:
-    from rdagent.scenarios.data_science.experiment.experiment import DSExperiment
-    from rdagent.scenarios.data_science.proposal.exp_gen.base import DSTrace, Experiment
-    from rdagent.utils.workflow.loop import LoopBase
-
-
-class ParallelMultiTraceExpGen(ExpGen):
-    """
-    An experiment generation strategy that enables parallel multi-trace exploration.
-
-    This generator is designed to work with the "Attribute Injection" model.
-    It uses a TraceScheduler to determine which parent node to expand, and
-    injects this parent context into the experiment object itself.
-    """
-
-    def __init__(self, *args, **kwargs):
-        super().__init__(*args, **kwargs)
-        # The underlying generator for creating a single experiment
-        self.exp_gen = DataScienceRDLoop.default_exp_gen(self.scen)
-        self.merge_exp_gen = ExpGen2Hypothesis(self.scen)
-        self.trace_scheduler: TraceScheduler = RoundRobinScheduler(DS_RD_SETTING.max_trace_num)
-
-    def gen(
-        self,
-        trace: "DSTrace",
-        plan: "ExperimentPlan" | None = None,
-    ) -> "Experiment":
-        raise NotImplementedError(
-            "ParallelMultiTraceExpGen is designed for async usage, please call async_gen instead."
-        )
-
-    async def async_gen(self, trace: DSTrace, loop: LoopBase) -> DSExperiment:
-        """
-        Waits for a free execution slot, selects a parent trace using the
-        scheduler, generates a new experiment, and injects the parent context
-        into it before returning.
-        """
-        timer: RDAgentTimer = RD_Agent_TIMER_wrapper.timer
-        logger.info(f"Remain time: {timer.remain_time()}")
-        local_selection: tuple[int, ...] = None
-
-        while True:
-
-            if timer.remain_time() >= timedelta(hours=DS_RD_SETTING.merge_hours):
-
-                if loop.get_unfinished_loop_cnt(loop.loop_idx) < RD_AGENT_SETTINGS.get_max_parallel():
-                    local_selection = await self.trace_scheduler.next(trace)
-
-                    # set the local selection as the global current selection for the trace
-                    trace.set_current_selection(local_selection)
-                    # step 2: generate the experiment with the local selection
-                    exp = self.exp_gen.gen(trace)
-
-                    # Inject the local selection to the experiment object
-                    exp.set_local_selection(local_selection)
-
-                    return exp
-
-            else:
-                # enter the merging stage
-                # make sure the all loops are finished
-                if loop.get_unfinished_loop_cnt(loop.loop_idx) < RD_AGENT_SETTINGS.get_max_parallel():
-                    # disable reset in merging stage
-                    DS_RD_SETTING.coding_fail_reanalyze_threshold = 100000
-                    DS_RD_SETTING.consecutive_errors = 100000
-
-                    leaves: list[int] = trace.get_leaves()
-                    if len(leaves) < 2:
-                        trace.set_current_selection(selection=(-1,))
-                        return self.exp_gen.gen(trace)
-                    else:
-                        local_selection = (leaves[0],)
-                        if trace.sota_exp_to_submit is not None:
-                            for i in range(1, len(leaves)):
-                                if trace.is_parent(trace.exp2idx(trace.sota_exp_to_submit), leaves[i]):
-                                    local_selection = (leaves[i],)
-                                    break
-                        trace.set_current_selection(local_selection)
-                        exp = self.merge_exp_gen.gen(trace)
-                        exp.set_local_selection(local_selection)
-                        return exp
-
-            await asyncio.sleep(1)
diff --git a/rdagent/scenarios/data_science/proposal/exp_gen/select/prompts.yaml b/rdagent/scenarios/data_science/proposal/exp_gen/select/prompts.yaml
index c4e4a728..240ba779 100644
--- a/rdagent/scenarios/data_science/proposal/exp_gen/select/prompts.yaml
+++ b/rdagent/scenarios/data_science/proposal/exp_gen/select/prompts.yaml
@@ -74,7 +74,7 @@ auto_sota_selector:
         "explanation": "No SOTA experiments and feedbacks"
       }
 
-user: |-
+  user: |-
     # SOTA Experiments and Feedback
     {{ historical_sota_exp_with_desc_and_scores }}