feat: base data science scenario UI (#525)

* base data science ui

* fix bug

* fix mle grade

* not cache when mle prepare

* fix

* fix grade sample

* fix a small bug

* fix

* cache mle score

* fix

* add gen_mle_score script

* update for mle score

* simple debug show

* small change

* summary folder

* add evo loop tag

* add loop id

* add comment

* fix CI

* add enable_cache for docker conf

* CI

* use setting data path

* fix ui bug

---------

Co-authored-by: yuanteli <1957922024@qq.com>

rdagent/app/data_science/loop.py

@@ -60,7 +60,7 @@ class DataScienceRDLoop(RDLoop):
 
     def direct_exp_gen(self, prev_out: dict[str, Any]):
         exp = self.exp_gen.gen(self.trace)
-        logger.log_object(exp, tag="direct_exp_gen")
+        logger.log_object(exp)
 
         # FIXME: this is for LLM debug webapp, remove this when the debugging is done.
         logger.log_object(exp, tag="debug_exp_gen")
@@ -83,14 +83,14 @@ class DataScienceRDLoop(RDLoop):
             else:
                 raise NotImplementedError(f"Unsupported component in DataScienceRDLoop: {exp.hypothesis.component}")
             exp.sub_tasks = []
-        logger.log_object(exp, tag="coding")
+        logger.log_object(exp)
         return exp
 
     def running(self, prev_out: dict[str, Any]):
         exp: DSExperiment = prev_out["coding"]
         if exp.next_component_required() is None:
             new_exp = self.runner.develop(exp)
-            logger.log_object(new_exp, tag="running")
+            logger.log_object(new_exp)
             return new_exp
         else:
             return exp
@@ -104,7 +104,7 @@ class DataScienceRDLoop(RDLoop):
                 reason=f"{exp.hypothesis.component} is completed.",
                 decision=True,
             )
-        logger.log_object(feedback, tag="feedback")
+        logger.log_object(feedback)
         return feedback
 
     def record(self, prev_out: dict[str, Any]):