apunkt/MetaGPT
1
0
Fork 0
mirror of https://github.com/FoundationAgents/MetaGPT.git synced 2026-06-20 15:38:09 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions

Final version

Browse source
This commit is contained in:
didi 2024-10-24 20:04:56 +08:00
parent 39ae68225b
commit 072839af7f
9 changed files with 21 additions and 28 deletions
Download patch file Download diff file Expand all files Collapse all files

5
examples/aflow/experiments/optimize_drop.py
View file

@ -5,7 +5,6 @@
from metagpt.configs.models_config import ModelsConfig
from metagpt.ext.aflow.data.download_data import download
from metagpt.ext.aflow.scripts.optimizer import DatasetType, Optimizer, QuestionType
# DatasetType, QuestionType, and OptimizerType definitions
@ -24,7 +23,7 @@ optimized_path: str = "metagpt/ext/aflow/scripts/optimized" # Optimized Result
initial_round: int = 1 # Corrected the case from Initial_round to initial_round
max_rounds: int = 20 # The max iteration of AFLOW.
check_convergence: bool = True # Whether Early Stop
validation_rounds: int = 5 # The validation rounds of AFLOW.
validation_rounds: int = 5 # The validation rounds of AFLOW.
# Config llm model, you can modify `config/config2.yaml` to use more llms.
mini_llm_config = ModelsConfig.default().get("gpt-4o-mini")
@ -33,7 +32,7 @@ claude_llm_config = ModelsConfig.default().get("claude-3-5-sonnet-20240620")
# Config operators.
operators = [
"Custom", # It's basic unit of a fixed node. optimizer can modify its prompt to get vairous nodes.
"AnswerGenerate", # It's for qa
"AnswerGenerate", # It's for qa
# "CustomCodeGenerate", # It's for code
"ScEnsemble", # It's for code, math and qa
# "Test", # It's for code

3
examples/aflow/experiments/optimize_gsm8k.py
View file

@ -5,7 +5,6 @@
from metagpt.configs.models_config import ModelsConfig
from metagpt.ext.aflow.data.download_data import download
from metagpt.ext.aflow.scripts.optimizer import DatasetType, Optimizer, QuestionType
# DatasetType, QuestionType, and OptimizerType definitions
@ -24,7 +23,7 @@ optimized_path: str = "metagpt/ext/aflow/scripts/optimized" # Optimized Result
initial_round: int = 1 # Corrected the case from Initial_round to initial_round
max_rounds: int = 20 # The max iteration of AFLOW.
check_convergence: bool = True # Whether Early Stop
validation_rounds: int = 5 # The validation rounds of AFLOW.
validation_rounds: int = 5 # The validation rounds of AFLOW.
# Config llm model, you can modify `config/config2.yaml` to use more llms.
mini_llm_config = ModelsConfig.default().get("gpt-4o-mini")

5
examples/aflow/experiments/optimize_hotpotqa.py
View file

@ -5,7 +5,6 @@
from metagpt.configs.models_config import ModelsConfig
from metagpt.ext.aflow.data.download_data import download
from metagpt.ext.aflow.scripts.optimizer import DatasetType, Optimizer, QuestionType
# DatasetType, QuestionType, and OptimizerType definitions
@ -24,7 +23,7 @@ optimized_path: str = "metagpt/ext/aflow/scripts/optimized" # Optimized Result
initial_round: int = 1 # Corrected the case from Initial_round to initial_round
max_rounds: int = 20 # The max iteration of AFLOW.
check_convergence: bool = True # Whether Early Stop
validation_rounds: int = 5 # The validation rounds of AFLOW.
validation_rounds: int = 5 # The validation rounds of AFLOW.
# Config llm model, you can modify `config/config2.yaml` to use more llms.
mini_llm_config = ModelsConfig.default().get("gpt-4o-mini")
@ -33,7 +32,7 @@ claude_llm_config = ModelsConfig.default().get("claude-3-5-sonnet-20240620")
# Config operators.
operators = [
"Custom", # It's basic unit of a fixed node. optimizer can modify its prompt to get vairous nodes.
"AnswerGenerate", # It's for qa
"AnswerGenerate", # It's for qa
# "CustomCodeGenerate", # It's for code
"ScEnsemble", # It's for code, math and qa
# "Test", # It's for code

7
examples/aflow/experiments/optimize_humaneval.py
View file

@ -5,7 +5,6 @@
from metagpt.configs.models_config import ModelsConfig
from metagpt.ext.aflow.data.download_data import download
from metagpt.ext.aflow.scripts.optimizer import DatasetType, Optimizer, QuestionType
# DatasetType, QuestionType, and OptimizerType definitions
@ -24,7 +23,7 @@ optimized_path: str = "metagpt/ext/aflow/scripts/optimized" # Optimized Result
initial_round: int = 1 # Corrected the case from Initial_round to initial_round
max_rounds: int = 20 # The max iteration of AFLOW.
check_convergence: bool = True # Whether Early Stop
validation_rounds: int = 5 # The validation rounds of AFLOW.
validation_rounds: int = 5 # The validation rounds of AFLOW.
# Config llm model, you can modify `config/config2.yaml` to use more llms.
mini_llm_config = ModelsConfig.default().get("gpt-4o-mini")
@ -34,9 +33,9 @@ claude_llm_config = ModelsConfig.default().get("claude-3-5-sonnet-20240620")
operators = [
"Custom", # It's basic unit of a fixed node. optimizer can modify its prompt to get vairous nodes.
# "AnswerGenerate", # It's for qa
"CustomCodeGenerate", # It's for code
"CustomCodeGenerate", # It's for code
"ScEnsemble", # It's for code, math and qa
"Test", # It's for code
"Test", # It's for code
# "Programmer", # It's for math
]

3
examples/aflow/experiments/optimize_math.py
View file

@ -5,7 +5,6 @@
from metagpt.configs.models_config import ModelsConfig
from metagpt.ext.aflow.data.download_data import download
from metagpt.ext.aflow.scripts.optimizer import DatasetType, Optimizer, QuestionType
# DatasetType, QuestionType, and OptimizerType definitions
@ -24,7 +23,7 @@ optimized_path: str = "metagpt/ext/aflow/scripts/optimized" # Optimized Result
initial_round: int = 1 # Corrected the case from Initial_round to initial_round
max_rounds: int = 20 # The max iteration of AFLOW.
check_convergence: bool = True # Whether Early Stop
validation_rounds: int = 5 # The validation rounds of AFLOW.
validation_rounds: int = 5 # The validation rounds of AFLOW.
# Config llm model, you can modify `config/config2.yaml` to use more llms.
mini_llm_config = ModelsConfig.default().get("gpt-4o-mini")

7
examples/aflow/experiments/optimize_mbpp.py
View file

@ -5,7 +5,6 @@
from metagpt.configs.models_config import ModelsConfig
from metagpt.ext.aflow.data.download_data import download
from metagpt.ext.aflow.scripts.optimizer import DatasetType, Optimizer, QuestionType
# DatasetType, QuestionType, and OptimizerType definitions
@ -24,7 +23,7 @@ optimized_path: str = "metagpt/ext/aflow/scripts/optimized" # Optimized Result
initial_round: int = 1 # Corrected the case from Initial_round to initial_round
max_rounds: int = 20 # The max iteration of AFLOW.
check_convergence: bool = True # Whether Early Stop
validation_rounds: int = 5 # The validation rounds of AFLOW.
validation_rounds: int = 5 # The validation rounds of AFLOW.
# Config llm model, you can modify `config/config2.yaml` to use more llms.
mini_llm_config = ModelsConfig.default().get("gpt-4o-mini")
@ -34,9 +33,9 @@ claude_llm_config = ModelsConfig.default().get("claude-3-5-sonnet-20240620")
operators = [
"Custom", # It's basic unit of a fixed node. optimizer can modify its prompt to get vairous nodes.
# "AnswerGenerate", # It's for qa
"CustomCodeGenerate", # It's for code
"CustomCodeGenerate", # It's for code
"ScEnsemble", # It's for code, math and qa
"Test", # It's for code
"Test", # It's for code
# "Programmer", # It's for math
]

2
examples/aflow/optimize.py
View file

@ -24,7 +24,7 @@ optimized_path: str = "metagpt/ext/aflow/scripts/optimized" # Optimized Result
initial_round: int = 1 # Corrected the case from Initial_round to initial_round
max_rounds: int = 20 # The max iteration of AFLOW.
check_convergence: bool = True # Whether Early Stop
validation_rounds: int = 5 # The validation rounds of AFLOW.
validation_rounds: int = 5 # The validation rounds of AFLOW.
# Config llm model, you can modify `config/config2.yaml` to use more llms.
mini_llm_config = ModelsConfig.default().get("gpt-4o-mini")