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change register arg name, integrate image2web tool

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This commit is contained in:
yzlin 2024-01-18 20:34:32 +08:00
parent 9dc421b122
commit 1cabf2c503
15 changed files with 100 additions and 103 deletions
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4
metagpt/tools/__init__.py
View file

@ -11,9 +11,7 @@ from metagpt.tools import tool_types # this registers all tool types
from metagpt.tools import libs # this registers all tools
from metagpt.tools.tool_registry import TOOL_REGISTRY
_ = tool_types # Avoid pre-commit error
_ = libs # Avoid pre-commit error
_ = TOOL_REGISTRY # Avoid pre-commit error
_, _, _ = tool_types, libs, TOOL_REGISTRY # Avoid pre-commit error
class SearchEngineType(Enum):

5
metagpt/tools/libs/__init__.py
View file

@ -7,7 +7,8 @@
from metagpt.tools.libs import (
data_preprocess,
feature_engineering,
sd_engine,
gpt_v_generator,
)
_ = data_preprocess # Avoid pre-commit error
_ = feature_engineering # Avoid pre-commit error
_, _, _, _ = data_preprocess, feature_engineering, sd_engine, gpt_v_generator # Avoid pre-commit error

18
metagpt/tools/libs/data_preprocess.py
View file

@ -31,7 +31,7 @@ class MLProcess(object):
return self.transform(df)
@register_tool(tool_type_name=TOOL_TYPE)
@register_tool(tool_type=TOOL_TYPE)
class FillMissingValue(MLProcess):
def __init__(
self,
@ -58,7 +58,7 @@ class FillMissingValue(MLProcess):
return new_df
@register_tool(tool_type_name=TOOL_TYPE)
@register_tool(tool_type=TOOL_TYPE)
class MinMaxScale(MLProcess):
def __init__(
self,
@ -77,7 +77,7 @@ class MinMaxScale(MLProcess):
return new_df
@register_tool(tool_type_name=TOOL_TYPE)
@register_tool(tool_type=TOOL_TYPE)
class StandardScale(MLProcess):
def __init__(
self,
@ -96,7 +96,7 @@ class StandardScale(MLProcess):
return new_df
@register_tool(tool_type_name=TOOL_TYPE)
@register_tool(tool_type=TOOL_TYPE)
class MaxAbsScale(MLProcess):
def __init__(
self,
@ -115,7 +115,7 @@ class MaxAbsScale(MLProcess):
return new_df
@register_tool(tool_type_name=TOOL_TYPE)
@register_tool(tool_type=TOOL_TYPE)
class RobustScale(MLProcess):
def __init__(
self,
@ -134,7 +134,7 @@ class RobustScale(MLProcess):
return new_df
@register_tool(tool_type_name=TOOL_TYPE)
@register_tool(tool_type=TOOL_TYPE)
class OrdinalEncode(MLProcess):
def __init__(
self,
@ -153,7 +153,7 @@ class OrdinalEncode(MLProcess):
return new_df
@register_tool(tool_type_name=TOOL_TYPE)
@register_tool(tool_type=TOOL_TYPE)
class OneHotEncode(MLProcess):
def __init__(
self,
@ -175,7 +175,7 @@ class OneHotEncode(MLProcess):
return new_df
@register_tool(tool_type_name=TOOL_TYPE)
@register_tool(tool_type=TOOL_TYPE)
class LabelEncode(MLProcess):
def __init__(
self,
@ -204,7 +204,7 @@ class LabelEncode(MLProcess):
return new_df
@register_tool(tool_type_name=TOOL_TYPE)
@register_tool(tool_type=TOOL_TYPE)
def get_column_info(df: pd.DataFrame) -> dict:
column_info = {
"Category": [],

20
metagpt/tools/libs/feature_engineering.py
View file

@ -22,7 +22,7 @@ from metagpt.tools.tool_registry import register_tool
TOOL_TYPE = ToolTypeEnum.FEATURE_ENGINEERING.value
@register_tool(tool_type_name=TOOL_TYPE)
@register_tool(tool_type=TOOL_TYPE)
class PolynomialExpansion(MLProcess):
def __init__(self, cols: list, degree: int = 2, label_col: str = None):
self.cols = cols
@ -53,7 +53,7 @@ class PolynomialExpansion(MLProcess):
return new_df
@register_tool(tool_type_name=TOOL_TYPE)
@register_tool(tool_type=TOOL_TYPE)
class CatCount(MLProcess):
def __init__(self, col: str):
self.col = col
@ -68,7 +68,7 @@ class CatCount(MLProcess):
return new_df
@register_tool(tool_type_name=TOOL_TYPE)
@register_tool(tool_type=TOOL_TYPE)
class TargetMeanEncoder(MLProcess):
def __init__(self, col: str, label: str):
self.col = col
@ -84,7 +84,7 @@ class TargetMeanEncoder(MLProcess):
return new_df
@register_tool(tool_type_name=TOOL_TYPE)
@register_tool(tool_type=TOOL_TYPE)
class KFoldTargetMeanEncoder(MLProcess):
def __init__(self, col: str, label: str, n_splits: int = 5, random_state: int = 2021):
self.col = col
@ -111,7 +111,7 @@ class KFoldTargetMeanEncoder(MLProcess):
return new_df
@register_tool(tool_type_name=TOOL_TYPE)
@register_tool(tool_type=TOOL_TYPE)
class CatCross(MLProcess):
def __init__(self, cols: list, max_cat_num: int = 100):
self.cols = cols
@ -147,7 +147,7 @@ class CatCross(MLProcess):
return new_df
@register_tool(tool_type_name=TOOL_TYPE)
@register_tool(tool_type=TOOL_TYPE)
class GroupStat(MLProcess):
def __init__(self, group_col: str, agg_col: str, agg_funcs: list):
self.group_col = group_col
@ -167,7 +167,7 @@ class GroupStat(MLProcess):
return new_df
@register_tool(tool_type_name=TOOL_TYPE)
@register_tool(tool_type=TOOL_TYPE)
class SplitBins(MLProcess):
def __init__(self, cols: list, strategy: str = "quantile"):
self.cols = cols
@ -184,7 +184,7 @@ class SplitBins(MLProcess):
return new_df
@register_tool(tool_type_name=TOOL_TYPE)
@register_tool(tool_type=TOOL_TYPE)
class ExtractTimeComps(MLProcess):
def __init__(self, time_col: str, time_comps: list):
self.time_col = time_col
@ -213,7 +213,7 @@ class ExtractTimeComps(MLProcess):
return new_df
@register_tool(tool_type_name=TOOL_TYPE)
@register_tool(tool_type=TOOL_TYPE)
class GeneralSelection(MLProcess):
def __init__(self, label_col: str):
self.label_col = label_col
@ -284,7 +284,7 @@ class TreeBasedSelection(MLProcess):
return new_df
@register_tool(tool_type_name=TOOL_TYPE)
@register_tool(tool_type=TOOL_TYPE)
class VarianceBasedSelection(MLProcess):
def __init__(self, label_col: str, threshold: float = 0):
self.label_col = label_col

34
metagpt/tools/functions/libs/vision.py → metagpt/tools/libs/gpt_v_generator.py
View file

@ -5,18 +5,13 @@
@Author : mannaandpoem
@File : vision.py
"""
import base64
from pathlib import Path
import requests
import base64
from metagpt.config import CONFIG
OPENAI_API_BASE = CONFIG.OPENAI_BASE_URL
API_KEY = CONFIG.OPENAI_API_KEY
MODEL = CONFIG.OPENAI_VISION_MODEL
MAX_TOKENS = CONFIG.VISION_MAX_TOKENS
from metagpt.tools.tool_data_type import ToolTypeEnum
from metagpt.tools.tool_registry import register_tool
ANALYZE_LAYOUT_PROMPT = """You are now a UI/UX, please generate layout information for this image:
@ -33,8 +28,15 @@ As the design pays tribute to large companies, sometimes it is normal for some c
Now, please generate the corresponding webpage code including HTML, CSS and JavaScript:"""
class Vision:
@register_tool(tool_type=ToolTypeEnum.IMAGE2WEBPAGE.value)
class GPTvGenerator:
def __init__(self):
from metagpt.config import CONFIG
OPENAI_API_BASE = CONFIG.OPENAI_BASE_URL
API_KEY = CONFIG.OPENAI_API_KEY
MODEL = CONFIG.OPENAI_VISION_MODEL
MAX_TOKENS = CONFIG.VISION_MAX_TOKENS
self.api_key = API_KEY
self.api_base = OPENAI_API_BASE
self.model = MODEL
@ -51,10 +53,7 @@ class Vision:
def get_result(self, image_path, prompt):
base64_image = self.encode_image(image_path)
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {self.api_key}"
}
headers = {"Content-Type": "application/json", "Authorization": f"Bearer {self.api_key}"}
payload = {
"model": self.model,
"messages": [
@ -62,11 +61,8 @@ class Vision:
"role": "user",
"content": [
{"type": "text", "text": prompt},
{
"type": "image_url",
"image_url": {"url": f"data:image/jpeg;base64,{base64_image}"}
}
]
{"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{base64_image}"}},
],
}
],
"max_tokens": self.max_tokens,
@ -81,7 +77,7 @@ class Vision:
@staticmethod
def encode_image(image_path):
with open(image_path, "rb") as image_file:
return base64.b64encode(image_file.read()).decode('utf-8')
return base64.b64encode(image_file.read()).decode("utf-8")
@staticmethod
def save_webpages(image_path, webpages) -> Path:

5
metagpt/tools/libs/sd_engine.py
View file

@ -13,7 +13,6 @@ import requests
from aiohttp import ClientSession
from PIL import Image, PngImagePlugin
from metagpt.config import CONFIG
from metagpt.const import SD_OUTPUT_FILE_REPO
from metagpt.logs import logger
from metagpt.tools.tool_data_type import ToolTypeEnum
@ -53,9 +52,11 @@ payload = {
default_negative_prompt = "(easynegative:0.8),black, dark,Low resolution"
@register_tool(tool_type_name=ToolTypeEnum.STABLE_DIFFUSION.value)
@register_tool(tool_type=ToolTypeEnum.STABLE_DIFFUSION.value)
class SDEngine:
def __init__(self, sd_url=""):
from metagpt.config import CONFIG
# Initialize the SDEngine with configuration
self.sd_url = sd_url if sd_url else CONFIG.get("SD_URL")
self.sd_t2i_url = f"{self.sd_url}{CONFIG.get('SD_T2I_API')}"

2
metagpt/tools/functions/schemas/vision.yml → metagpt/tools/schemas/image2webpage/GPTvGenerator.yml
View file

@ -1,4 +1,4 @@
Vision:
GPTvGenerator:
type: class
description: "Class for generating web pages at once."
methods:

1
metagpt/tools/tool_data_type.py
View file

@ -10,6 +10,7 @@ class ToolTypeEnum(Enum):
MODEL_TRAIN = "model_train"
MODEL_EVALUATE = "model_evaluate"
STABLE_DIFFUSION = "stable_diffusion"
IMAGE2WEBPAGE = "image2webpage"
OTHER = "other"
def __missing__(self, key):

12
metagpt/tools/tool_registry.py
View file

@ -21,7 +21,7 @@ class ToolRegistry:
def __init__(self):
self.tools = {}
self.tool_types = {}
self.tools_by_types = defaultdict(dict) # two-layer k-v, {tool_type_name: {tool_name: {...}, ...}, ...}
self.tools_by_types = defaultdict(dict) # two-layer k-v, {tool_type: {tool_name: {...}, ...}, ...}
def register_tool_type(self, tool_type: ToolType):
self.tool_types[tool_type.name] = tool_type
@ -33,13 +33,13 @@ class ToolRegistry:
tool_path,
schema_path=None,
tool_code="",
tool_type_name="other",
tool_type="other",
make_schema_if_not_exists=False,
):
if self.has_tool(tool_name):
return
schema_path = schema_path or TOOL_SCHEMA_PATH / tool_type_name / f"{tool_name}.yml"
schema_path = schema_path or TOOL_SCHEMA_PATH / tool_type / f"{tool_name}.yml"
if not os.path.exists(schema_path):
if make_schema_if_not_exists:
@ -62,7 +62,7 @@ class ToolRegistry:
# )
tool = Tool(name=tool_name, path=tool_path, schemas=schemas, code=tool_code)
self.tools[tool_name] = tool
self.tools_by_types[tool_type_name][tool_name] = tool
self.tools_by_types[tool_type][tool_name] = tool
logger.info(f"{tool_name} registered")
def has_tool(self, key):
@ -94,7 +94,7 @@ def register_tool_type(cls):
return cls
def register_tool(tool_name="", tool_type_name="other", schema_path=None):
def register_tool(tool_name="", tool_type="other", schema_path=None):
"""register a tool to registry"""
def decorator(cls, tool_name=tool_name):
@ -111,7 +111,7 @@ def register_tool(tool_name="", tool_type_name="other", schema_path=None):
tool_path=file_path,
schema_path=schema_path,
tool_code=source_code,
tool_type_name=tool_type_name,
tool_type=tool_type,
)
return cls

8
metagpt/tools/tool_types.py
View file

@ -1,6 +1,7 @@
from metagpt.prompts.tool_types import (
DATA_PREPROCESS_PROMPT,
FEATURE_ENGINEERING_PROMPT,
IMAGE2WEBPAGE_PROMPT,
MODEL_EVALUATE_PROMPT,
MODEL_TRAIN_PROMPT,
)
@ -48,6 +49,13 @@ class StableDiffusion(ToolType):
desc: str = "Related to text2image, image2image using stable diffusion model."
@register_tool_type
class Image2Webpage(ToolType):
name: str = ToolTypeEnum.IMAGE2WEBPAGE.value
desc: str = "For converting image into webpage code."
usage_prompt: str = IMAGE2WEBPAGE_PROMPT
@register_tool_type
class Other(ToolType):
name: str = ToolTypeEnum.OTHER.value