feat: add RD-Agent-Quant scenario (#838)

* fix model input shape bug and costeer_model bug

* fix a bug

* fix a bug in docker result extraction

* a system-level optimization

* add a filter of stdout

* update

* add stdout to model

* model training_hyperparameters update

* quant scenario

* update some quant settings

* llm choose action

* Thompson Sampling Bandit for action choosing

* refine both scens

* add trace messages for quant scen

* fix some bugs

* fix some bugs

* update

* update

* update

* fix

* fix

* fix

* update for merge

* fix ci

* fix some bugs

* fix ci

* fix ci

* fix ci

* fix ci

* refactor

* default qlib4rdagent local env downloading

* fix ci

* fix ci

* fix a bug

* fix ci

* fix: align all prompts on template (#908)

* use template to render all prompts

* fix CI

---------

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

* add fin_quant in cli

* fix a bug

* fix ci

* fix some bugs

* refactor

* remove the columns in hypothesis if no value generated in this column

* fix a bug

* fix ci

* fix conda env

* add qlib gitignore

* remove existed qlib folder & install torch in qlib conda

* fix workspace ui in feedback

* align model config in coder and runner in docker or conda

* fix CI

* fix CI

---------

Co-authored-by: Xu Yang <peteryang@vip.qq.com>
Co-authored-by: Xu Yang <xuyang1@microsoft.com>

rdagent/components/coder/model_coder/one_shot/__init__.py

@@ -1,12 +1,10 @@
 import re
 from pathlib import Path
 
-from jinja2 import Environment, StrictUndefined
-
 from rdagent.components.coder.model_coder.model import ModelExperiment, ModelFBWorkspace
 from rdagent.core.developer import Developer
-from rdagent.core.prompts import Prompts
 from rdagent.oai.llm_utils import APIBackend
+from rdagent.utils.agent.tpl import T
 
 DIRNAME = Path(__file__).absolute().resolve().parent
 
@@ -17,18 +15,14 @@ class ModelCodeWriter(Developer[ModelExperiment]):
         for t in exp.sub_tasks:
             mti = ModelFBWorkspace(t)
             mti.prepare()
-            pr = Prompts(file_path=DIRNAME / "prompt.yaml")
 
-            user_prompt_tpl = Environment(undefined=StrictUndefined).from_string(pr["code_implement_user"])
-            sys_prompt_tpl = Environment(undefined=StrictUndefined).from_string(pr["code_implement_sys"])
-
-            user_prompt = user_prompt_tpl.render(
+            user_prompt = T(".prompts:code_implement_user").r(
                 name=t.name,
                 description=t.description,
                 formulation=t.formulation,
                 variables=t.variables,
             )
-            system_prompt = sys_prompt_tpl.render()
+            system_prompt = T(".prompts:code_implement_sys").r()
 
             resp = APIBackend().build_messages_and_create_chat_completion(user_prompt, system_prompt)