mirror of
https://github.com/NicolasBohn/NexQuant.git
synced 2026-08-04 18:57:44 +00:00
Xu Yang
e0a24fb46f
* ignore result csv file * fix app scripts * rename taskgenerator to developer and generate to develop * fix a config bug in coder * fix a small bug in factor coder evaluators * remove a single logger in factor coder evaluators * fix a small bug in model coder main.py * rename Implementation to Workspace * move the prepare the inject_code into FBWorkspace to align all the behavior * fix a small bug in model feedback * remove debug lines for multi processing and simplify evaluators multi proc * add a copy function to workspace to freeze the workspace && add config prefix to speed up debugging * make hypothesisgen a abc class * use Qlib***Experiment * fix a small bug * rename Imp to Ws * rename sub_implementations to sub_workspace_list * fix a bug in feedback not presented as content in prompts * move proposal pys to proposal folder * reformat the folder * align factor and model qlib workspace and use template to handle the workspace * add a filter to evoagent to filter out false evo * align multi_proc_n into RDAGENT seeting * handle when runner gets empty experiment * fix logger merge remaining problems * fix black and isort automatically
84 lines
3.2 KiB
Python
84 lines
3.2 KiB
Python
import json
|
|
from pathlib import Path
|
|
from typing import List, Tuple
|
|
|
|
from jinja2 import Environment, StrictUndefined
|
|
|
|
from rdagent.components.coder.factor_coder.factor import FactorExperiment, FactorTask
|
|
from rdagent.components.proposal.factor_proposal import (
|
|
FactorHypothesis,
|
|
FactorHypothesis2Experiment,
|
|
FactorHypothesisGen,
|
|
)
|
|
from rdagent.core.prompts import Prompts
|
|
from rdagent.core.proposal import Hypothesis, Scenario, Trace
|
|
from rdagent.scenarios.qlib.experiment.factor_experiment import QlibFactorExperiment
|
|
|
|
prompt_dict = Prompts(file_path=Path(__file__).parent.parent / "prompts.yaml")
|
|
|
|
QlibFactorHypothesis = FactorHypothesis
|
|
|
|
|
|
class QlibFactorHypothesisGen(FactorHypothesisGen):
|
|
def __init__(self, scen: Scenario) -> Tuple[dict, bool]:
|
|
super().__init__(scen)
|
|
|
|
def prepare_context(self, trace: Trace) -> Tuple[dict, bool]:
|
|
hypothesis_feedback = (
|
|
Environment(undefined=StrictUndefined)
|
|
.from_string(prompt_dict["hypothesis_and_feedback"])
|
|
.render(trace=trace)
|
|
)
|
|
context_dict = {
|
|
"hypothesis_and_feedback": hypothesis_feedback,
|
|
"RAG": ...,
|
|
"hypothesis_output_format": prompt_dict["hypothesis_output_format"],
|
|
}
|
|
return context_dict, True
|
|
|
|
def convert_response(self, response: str) -> FactorHypothesis:
|
|
response_dict = json.loads(response)
|
|
hypothesis = QlibFactorHypothesis(hypothesis=response_dict["hypothesis"], reason=response_dict["reason"])
|
|
return hypothesis
|
|
|
|
|
|
class QlibFactorHypothesis2Experiment(FactorHypothesis2Experiment):
|
|
def prepare_context(self, hypothesis: Hypothesis, trace: Trace) -> Tuple[dict | bool]:
|
|
scenario = trace.scen.get_scenario_all_desc()
|
|
experiment_output_format = prompt_dict["factor_experiment_output_format"]
|
|
|
|
hypothesis_and_feedback = (
|
|
Environment(undefined=StrictUndefined)
|
|
.from_string(prompt_dict["hypothesis_and_feedback"])
|
|
.render(trace=trace)
|
|
)
|
|
|
|
experiment_list: List[FactorExperiment] = [t[1] for t in trace.hist]
|
|
|
|
factor_list = []
|
|
for experiment in experiment_list:
|
|
factor_list.extend(experiment.sub_tasks)
|
|
|
|
return {
|
|
"target_hypothesis": str(hypothesis),
|
|
"scenario": scenario,
|
|
"hypothesis_and_feedback": hypothesis_and_feedback,
|
|
"experiment_output_format": experiment_output_format,
|
|
"target_list": factor_list,
|
|
"RAG": ...,
|
|
}, True
|
|
|
|
def convert_response(self, response: str, trace: Trace) -> FactorExperiment:
|
|
response_dict = json.loads(response)
|
|
tasks = []
|
|
for factor_name in response_dict:
|
|
description = response_dict[factor_name]["description"]
|
|
formulation = response_dict[factor_name]["formulation"]
|
|
variables = response_dict[factor_name]["variables"]
|
|
tasks.append(FactorTask(factor_name, description, formulation, variables))
|
|
exp = QlibFactorExperiment(tasks)
|
|
exp.based_experiments = [t[1] for t in trace.hist if t[2]]
|
|
if len(exp.based_experiments) == 0:
|
|
exp.based_experiments.append(QlibFactorExperiment(sub_tasks=[]))
|
|
return exp
|