Checking general demo (#126)

* Init todo

* Evaluation & dataset

* Generate new data

* dataset generation

* add the result

* Analysis

* Factor update

* Updates

* Reformat analysis.py

* CI fix

* Further Optimised Model Workflow by Incorporating Feedbacks on Exp Task Card

* Rebasing To build the extraction & implementation demo

* Revised for clean code

* Revised further to show "Knowledge"

* Revised to make model_research_copilot better

* Further Optimised Model Workflow by Incorporating Feedbacks on Exp Task Card

* Rebasing To build the extraction & implementation demo

* Revised for clean code

* Revised further to show "Knowledge"

* Revised to make model_research_copilot better

---------

Co-authored-by: Young <afe.young@gmail.com>
Co-authored-by: Taozhi Wang <taozhi.mark.wang@gmail.com>
Co-authored-by: you-n-g <you-n-g@users.noreply.github.com>
Co-authored-by: cyncyw <47289405+taozhiwang@users.noreply.github.com>

rdagent/app/quant_factor_benchmark/eval.py

@@ -15,6 +15,12 @@ from rdagent.scenarios.qlib.factor_experiment_loader.json_loader import (
     FactorTestCaseLoaderFromJsonFile,
 )
 
+from rdagent.core.utils import import_class
+from rdagent.core.scenario import Scenario
+from rdagent.scenarios.qlib.experiment.factor_experiment import QlibFactorScenario
+
+from pprint import pprint
+
 # 1.read the settings
 bs = BenchmarkSettings()
 
@@ -25,7 +31,6 @@ test_cases = FactorTestCaseLoaderFromJsonFile().load(bs.bench_data_path)
 
 scen: Scenario = import_class(PROP_SETTING.factor_scen)()
 generate_method = import_class(bs.bench_method_cls)(scen=scen)
-
 # 4.declare the eval method and pass the arguments.
 eval_method = FactorImplementEval(
     method=generate_method,