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/task_loader.py

@@ -2,19 +2,16 @@ from __future__ import annotations
 
 import json
 import re
-from pathlib import Path
 
-from rdagent.components.coder.model_coder.model import ModelExperiment, ModelTask
+from rdagent.components.coder.model_coder.model import ModelTask
 from rdagent.components.document_reader.document_reader import (
     load_and_process_pdfs_by_langchain,
 )
 from rdagent.components.loader.task_loader import ModelTaskLoader
-from rdagent.core.prompts import Prompts
 from rdagent.log import rdagent_logger as logger
 from rdagent.oai.llm_utils import APIBackend
 from rdagent.scenarios.qlib.experiment.model_experiment import QlibModelExperiment
-
-document_process_prompts = Prompts(file_path=Path(__file__).parent / "prompts.yaml")
+from rdagent.utils.agent.tpl import T
 
 
 def extract_model_from_doc(doc_content: str) -> dict:
@@ -32,7 +29,7 @@ def extract_model_from_doc(doc_content: str) -> dict:
         {model_name: dict{description, formulation, variables}}
     """
     session = APIBackend().build_chat_session(
-        session_system_prompt=document_process_prompts["extract_model_formulation_system"],
+        session_system_prompt=T(".prompts:extract_model_formulation_system").r(),
     )
     current_user_prompt = doc_content