refine core to store experiment results and hypothesis feedback (#55)

* Update proposal.py

Completed The HypothesisFeedback Class.

* refine the core code

---------

Co-authored-by: xuyang1 <xuyang1@microsoft.com>

rdagent/app/qlib_rd_loop/conf.py

@@ -4,12 +4,22 @@ from pydantic_settings import BaseSettings
 class PropSetting(BaseSettings):
     """"""
 
-    scen: str = "rdagent.scenarios.qlib.experiment.factor_experiment.QlibFactorScenario"
-    hypothesis_gen: str = "rdagent.scenarios.qlib.factor_proposal.QlibFactorHypothesisGen"
-    hypothesis2experiment: str = "rdagent.scenarios.qlib.factor_proposal.QlibFactorHypothesis2Experiment"
+    qlib_factor_scen: str = "rdagent.scenarios.qlib.experiment.factor_experiment.QlibFactorScenario"
+    qlib_factor_hypothesis_gen: str = "rdagent.scenarios.qlib.factor_proposal.QlibFactorHypothesisGen"
+    qlib_factor_hypothesis2experiment: str = "rdagent.scenarios.qlib.factor_proposal.QlibFactorHypothesis2Experiment"
     qlib_factor_coder: str = "rdagent.scenarios.qlib.factor_task_implementation.QlibFactorCoSTEER"
     qlib_factor_runner: str = "rdagent.scenarios.qlib.task_generator.data.QlibFactorRunner"
-    qlib_factor_summarizer: str = "rdagent.scenarios.qlib.task_generator.feedback.QlibFactorExperiment2Feedback"
+    qlib_factor_summarizer: str = (
+        "rdagent.scenarios.qlib.task_generator.feedback.QlibFactorHypothesisExperiment2Feedback"
+    )
+
+    # TODO: model part is not finished yet
+    qlib_model_scen: str = ""
+    qlib_model_hypothesis_gen: str = ""
+    qlib_model_hypothesis2experiment: str = ""
+    qlib_model_coder: str = ""
+    qlib_model_runner: str = ""
+    qlib_model_summarizer: str = ""
 
     evolving_n: int = 10
 

rdagent/app/qlib_rd_loop/factor.py

@@ -6,37 +6,34 @@ from dotenv import load_dotenv
 
 load_dotenv(override=True)
 
-# import_from
 from rdagent.app.qlib_rd_loop.conf import PROP_SETTING
 from rdagent.core.proposal import (
-    Experiment2Feedback,
     Hypothesis2Experiment,
+    HypothesisExperiment2Feedback,
     HypothesisGen,
-    HypothesisSet,
     Trace,
 )
 from rdagent.core.task_generator import TaskGenerator
 from rdagent.core.utils import import_class
 
-scen = import_class(PROP_SETTING.scen)()
+scen = import_class(PROP_SETTING.qlib_factor_scen)()
 
-hypothesis_gen: HypothesisGen = import_class(PROP_SETTING.hypothesis_gen)(scen)
+hypothesis_gen: HypothesisGen = import_class(PROP_SETTING.qlib_factor_hypothesis_gen)(scen)
 
-hypothesis2experiment: Hypothesis2Experiment = import_class(PROP_SETTING.hypothesis2experiment)()
+hypothesis2experiment: Hypothesis2Experiment = import_class(PROP_SETTING.qlib_factor_hypothesis2experiment)()
 
 qlib_factor_coder: TaskGenerator = import_class(PROP_SETTING.qlib_factor_coder)(scen)
 qlib_factor_runner: TaskGenerator = import_class(PROP_SETTING.qlib_factor_runner)(scen)
 
-qlib_factor_summarizer: Experiment2Feedback = import_class(PROP_SETTING.qlib_factor_summarizer)()
+qlib_factor_summarizer: HypothesisExperiment2Feedback = import_class(PROP_SETTING.qlib_factor_summarizer)()
 
 
 trace = Trace(scen=scen)
-hs = HypothesisSet(trace=trace)
 for _ in range(PROP_SETTING.evolving_n):
     hypothesis = hypothesis_gen.gen(trace)
-    exp = hypothesis2experiment.convert(hs)
+    exp = hypothesis2experiment.convert(hypothesis, trace)
     exp = qlib_factor_coder.generate(exp)
     exp = qlib_factor_runner.generate(exp)
-    feedback = qlib_factor_summarizer.summarize(exp)
+    feedback = qlib_factor_summarizer.generateFeedback(exp, hypothesis, trace)
 
     trace.hist.append((hypothesis, exp, feedback))

rdagent/app/qlib_rd_loop/model.py

@@ -4,39 +4,33 @@ TODO: move the following code to a new class: Model_RD_Agent
 """
 
 # import_from
-from rdagent.app.model_proposal.conf import MODEL_PROP_SETTING
 
+from rdagent.app.qlib_rd_loop.conf import PROP_SETTING
 from rdagent.core.proposal import (
-    Experiment2Feedback,
     Hypothesis2Experiment,
-    HypothesisSet,
+    HypothesisExperiment2Feedback,
     Trace,
 )
 from rdagent.core.task_generator import TaskGenerator
+from rdagent.core.utils import import_class
 
-# load_from_cls_uri
+scen = import_class(PROP_SETTING.qlib_model_scen)()
 
+hypothesis_gen = import_class(PROP_SETTING.qlib_model_hypothesis_gen)(scen)
 
-scen = load_from_cls_uri(MODEL_PROP_SETTING.scen)()
+hypothesis2experiment: Hypothesis2Experiment = import_class(PROP_SETTING.qlib_model_hypothesis2experiment)()
 
-hypothesis_gen = load_from_cls_uri(MODEL_PROP_SETTING.hypothesis_gen)(scen)
+qlib_model_coder: TaskGenerator = import_class(PROP_SETTING.qlib_model_coder)(scen)
+qlib_model_runner: TaskGenerator = import_class(PROP_SETTING.qlib_model_runner)(scen)
 
-hypothesis2task: Hypothesis2Experiment = load_from_cls_uri(MODEL_PROP_SETTING.hypothesis2task)()
+qlib_model_summarizer: HypothesisExperiment2Feedback = import_class(PROP_SETTING.qlib_model_hypothesis2experiment)(scen)
 
-task_gen: TaskGenerator = load_from_cls_uri(MODEL_PROP_SETTING.task_gen)(scen)  # for implementation
-
-imp2feedback: Experiment2Feedback = load_from_cls_uri(MODEL_PROP_SETTING.imp2feedback)(scen)  # for implementation
-
-
-iter_n = MODEL_PROP_SETTING.iter_n
-
-trace = Trace()
-
-hypothesis_set = HypothesisSet()
-for _ in range(iter_n):
+trace = Trace(scen=scen)
+for _ in range(PROP_SETTING.evolving_n):
     hypothesis = hypothesis_gen.gen(trace)
-    task = hypothesis2task.convert(hypothesis)
-    imp = task_gen.gen(task)
-    imp.execute()
-    feedback = imp2feedback.summarize(imp)
-    trace.hist.append((hypothesis, feedback))
+    exp = hypothesis2experiment.convert(hypothesis, trace)
+    exp = qlib_model_coder.generate(exp)
+    exp = qlib_model_runner.generate(exp)
+    feedback = qlib_model_summarizer.generateFeedback(exp, hypothesis, trace)
+
+    trace.hist.append((hypothesis, exp, feedback))