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model proposal first version (#61)

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* init code

* first version of model proposal
This commit is contained in:
Xu Yang
2024-07-11 10:50:34 +08:00
committed by GitHub
parent 720994c8e0
commit b1ddba388a
14 changed files with 248 additions and 50 deletions
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rdagent/components/coder/model_coder/model.py
-6
View File
@@ -15,12 +15,6 @@ from rdagent.utils import get_module_by_module_path
class ModelTask(Task):
# TODO: it should change when the Task changes.
name: str
description: str
formulation: str
variables: Dict[str, str] # map the variable name to the variable description
def __init__(
self, name: str, description: str, formulation: str, variables: Dict[str, str], model_type: Optional[str] = None
) -> None:
rdagent/components/proposal/factor_proposal.py
+9 -7
View File
@@ -37,16 +37,18 @@ class FactorHypothesisGen(HypothesisGen):
system_prompt = (
Environment(undefined=StrictUndefined)
.from_string(prompt_dict["factor_hypothesis_gen"]["system_prompt"])
.from_string(prompt_dict["hypothesis_gen"]["system_prompt"])
.render(
targets="factors",
scenario=self.scen.get_scenario_all_desc(),
hypothesis_output_format=context_dict["hypothesis_output_format"],
)
)
user_prompt = (
Environment(undefined=StrictUndefined)
.from_string(prompt_dict["factor_hypothesis_gen"]["user_prompt"])
.from_string(prompt_dict["hypothesis_gen"]["user_prompt"])
.render(
targets="factors",
hypothesis_and_feedback=context_dict["hypothesis_and_feedback"],
RAG=context_dict["RAG"],
)
@@ -60,8 +62,6 @@ class FactorHypothesisGen(HypothesisGen):
class FactorHypothesis2Experiment(Hypothesis2Experiment[FactorExperiment]):
def __init__(self) -> None:
super().__init__()
@abstractmethod
def prepare_context(self, hypothesis: Hypothesis, trace: Trace) -> Tuple[dict, bool]: ...
@@ -73,19 +73,21 @@ class FactorHypothesis2Experiment(Hypothesis2Experiment[FactorExperiment]):
context, json_flag = self.prepare_context(hypothesis, trace)
system_prompt = (
Environment(undefined=StrictUndefined)
.from_string(prompt_dict["factor_hypothesis2experiment"]["system_prompt"])
.from_string(prompt_dict["hypothesis2experiment"]["system_prompt"])
.render(
targets="factors",
scenario=trace.scen.get_scenario_all_desc(),
experiment_output_format=context["experiment_output_format"],
)
)
user_prompt = (
Environment(undefined=StrictUndefined)
.from_string(prompt_dict["factor_hypothesis2experiment"]["user_prompt"])
.from_string(prompt_dict["hypothesis2experiment"]["user_prompt"])
.render(
targets="factors",
target_hypothesis=context["target_hypothesis"],
hypothesis_and_feedback=context["hypothesis_and_feedback"],
factor_list=context["factor_list"],
target_list=context["target_list"],
RAG=context["RAG"],
)
)
rdagent/components/proposal/model_proposal.py
+96
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@@ -0,0 +1,96 @@
from abc import abstractmethod
from pathlib import Path
from typing import Tuple
from jinja2 import Environment, StrictUndefined
from rdagent.components.coder.model_coder.model import ModelExperiment
from rdagent.core.prompts import Prompts
from rdagent.core.proposal import (
Hypothesis,
Hypothesis2Experiment,
HypothesisGen,
Scenario,
Trace,
)
from rdagent.oai.llm_utils import APIBackend
prompt_dict = Prompts(file_path=Path(__file__).parent / "prompts.yaml")
ModelHypothesis = Hypothesis
class ModelHypothesisGen(HypothesisGen):
# The following methods are scenario related so they should be implemented in the subclass
@abstractmethod
def prepare_context(self, trace: Trace) -> Tuple[dict, bool]: ...
@abstractmethod
def convert_response(self, response: str) -> ModelHypothesis: ...
def gen(self, trace: Trace) -> ModelHypothesis:
context_dict, json_flag = self.prepare_context(trace)
system_prompt = (
Environment(undefined=StrictUndefined)
.from_string(prompt_dict["hypothesis_gen"]["system_prompt"])
.render(
targets="factors",
scenario=self.scen.get_scenario_all_desc(),
hypothesis_output_format=context_dict["hypothesis_output_format"],
)
)
user_prompt = (
Environment(undefined=StrictUndefined)
.from_string(prompt_dict["hypothesis_gen"]["user_prompt"])
.render(
targets="factors",
hypothesis_and_feedback=context_dict["hypothesis_and_feedback"],
RAG=context_dict["RAG"],
)
)
resp = APIBackend().build_messages_and_create_chat_completion(user_prompt, system_prompt, json_mode=json_flag)
hypothesis = self.convert_response(resp)
return hypothesis
class ModelHypothesis2Experiment(Hypothesis2Experiment[ModelExperiment]):
def __init__(self) -> None:
super().__init__()
@abstractmethod
def prepare_context(self, hypothesis: Hypothesis, trace: Trace) -> Tuple[dict, bool]: ...
@abstractmethod
def convert_response(self, response: str, trace: Trace) -> ModelExperiment: ...
def convert(self, hypothesis: Hypothesis, trace: Trace) -> ModelExperiment:
context, json_flag = self.prepare_context(hypothesis, trace)
system_prompt = (
Environment(undefined=StrictUndefined)
.from_string(prompt_dict["hypothesis2experiment"]["system_prompt"])
.render(
targets="factors",
scenario=trace.scen.get_scenario_all_desc(),
experiment_output_format=context["experiment_output_format"],
)
)
user_prompt = (
Environment(undefined=StrictUndefined)
.from_string(prompt_dict["hypothesis2experiment"]["user_prompt"])
.render(
targets="factors",
target_hypothesis=context["target_hypothesis"],
hypothesis_and_feedback=context["hypothesis_and_feedback"],
target_list=context["target_list"],
RAG=context["RAG"],
)
)
resp = APIBackend().build_messages_and_create_chat_completion(user_prompt, system_prompt, json_mode=json_flag)
return self.convert_response(resp, trace)
rdagent/components/proposal/prompts.yaml
+17 -17
View File
@@ -1,41 +1,41 @@
factor_hypothesis_gen:
hypothesis_gen:
system_prompt: |-
The user is trying to generate new hypothesis on the factors in data-driven research and development.
The factors are used in a certain scenario, the scenario is as follows:
The user is trying to generate new hypothesis on the {{targets}} in data-driven research and development.
The {{targets}} are used in a certain scenario, the scenario is as follows:
{{ scenario }}
The user has made several hypothesis on this scenario and did several evaluation on them. The user will provide this information to you.
To help you generate new hypothesis, the user has prepared some additional information for you. You should use this information to help generate new factors.
To help you generate new hypothesis, the user has prepared some additional information for you. You should use this information to help generate new {{targets}}.
Please generate the output following the format below:
{{ hypothesis_output_format }}
user_prompt: |-
The user has made several hypothesis on this scenario and did several evaluation on them.
The former hypothesis and the corresponding feedbacks are as follows:
{{ hypothesis_and_feedback }}
To help you generate new factors, we have prepared the following information for you:
To help you generate new {{targets}}, we have prepared the following information for you:
{{ RAG }}
Please generate the new hypothesis based on the information above.
factor_hypothesis2experiment:
hypothesis2experiment:
system_prompt: |-
The user is trying to generate new factors based on the hypothesis generated in the previous step.
The factors are used in certain scenario, the scenario is as follows:
The user is trying to generate new {{targets}} based on the hypothesis generated in the previous step.
The {{targets}} are used in certain scenario, the scenario is as follows:
{{ scenario }}
The user will use the factors generated to do some experiments. The user will provide this information to you:
1. The target hypothesis you are targeting to generate factors for.
The user will use the {{targets}} generated to do some experiments. The user will provide this information to you:
1. The target hypothesis you are targeting to generate {{targets}} for.
2. The hypothesis generated in the previous steps and their corresponding feedbacks.
3. Former proposed factors on similar hypothesis.
4. Some additional information to help you generate new factors.
3. Former proposed {{targets}} on similar hypothesis.
4. Some additional information to help you generate new {{targets}}.
Please generate the output following the format below:
{{ experiment_output_format }}
user_prompt: |-
The user has made several hypothesis on this scenario and did several evaluation on them.
The target hypothesis you are targeting to generate factors for is as follows:
The target hypothesis you are targeting to generate {{targets}} for is as follows:
{{ target_hypothesis }}
The former hypothesis and the corresponding feedbacks are as follows:
{{ hypothesis_and_feedback }}
The former proposed factors on similar hypothesis are as follows:
{{ factor_list }}
To help you generate new factors, we have prepared the following information for you:
The former proposed {{targets}} on similar hypothesis are as follows:
{{ target_list }}
To help you generate new {{targets}}, we have prepared the following information for you:
{{ RAG }}
Please generate the new factors based on the information above.
Please generate the new {{targets}} based on the information above.