first version of model runner and model feedback (#70)

* Implemented model.py

- Need to run within the RDAgent folder (relevant path)
- Each time copy a template & insert code & run qlib & store result back to experiment

* Create model.py

* Create conf.yaml

This is the sample conf.yaml to be copied each time.

This has gone several times of iteration and is now working for both tabular and Time-Series data.

* Create read_exp.py

This is to read the results within Qlib

* Create ReadMe.md

* Update model.py

* Create test_model.py

A testing file that separates model code generation and running&feedback section.

* move the template folder

* help xisen finish the model runner

* help xisen fix improve model feedback generation

* delete debug file

* rename readme.md

---------

Co-authored-by: Xisen Wang <118058822+Xisen-Wang@users.noreply.github.com>

rdagent/core/experiment.py

@@ -124,16 +124,16 @@ class Experiment(ABC, Generic[ASpecificTask, ASpecificImp]):
     The experiment is a sequence of tasks and the implementations of the tasks after generated by the TaskGenerator.
     """
 
-    result_ws: Optional[FBImplementation]
-
     def __init__(self, sub_tasks: Sequence[ASpecificTask]) -> None:
         self.sub_tasks = sub_tasks
         self.sub_implementations: Sequence[ASpecificImp] = [None for _ in self.sub_tasks]
         self.based_experiments: Sequence[Experiment] = []
         self.result: object = None  # The result of the experiment, can be different types in different scenarios.
-        self.result_ws = None
+        self.exp_ws: ASpecificImp = None
 
 
+ASpecificExp = TypeVar("ASpecificExp", bound=Experiment)
+
 TaskOrExperiment = TypeVar("TaskOrExperiment", Task, Experiment)