Merge branch 'main' into feature/json_write_prd

tests/metagpt/actions/test_clone_function.py

@@ -0,0 +1,54 @@
+import pytest
+
+from metagpt.actions.clone_function import CloneFunction, run_function_code
+
+
+source_code = """
+import pandas as pd
+import ta
+
+def user_indicator():
+    # 读取股票数据
+    stock_data = pd.read_csv('./tests/data/baba_stock.csv')
+    stock_data.head()
+    # 计算简单移动平均线
+    stock_data['SMA'] = ta.trend.sma_indicator(stock_data['Close'], window=6)
+    stock_data[['Date', 'Close', 'SMA']].head()
+    # 计算布林带
+    stock_data['bb_upper'], stock_data['bb_middle'], stock_data['bb_lower'] = ta.volatility.bollinger_hband_indicator(stock_data['Close'], window=20), ta.volatility.bollinger_mavg(stock_data['Close'], window=20), ta.volatility.bollinger_lband_indicator(stock_data['Close'], window=20)
+    stock_data[['Date', 'Close', 'bb_upper', 'bb_middle', 'bb_lower']].head()
+"""
+
+template_code = """
+def stock_indicator(stock_path: str, indicators=['Simple Moving Average', 'BollingerBands', 'MACD]) -> pd.DataFrame:
+    import pandas as pd
+    # here is your code.
+"""
+
+
+def get_expected_res():
+    import pandas as pd
+    import ta
+
+    # 读取股票数据
+    stock_data = pd.read_csv('./tests/data/baba_stock.csv')
+    stock_data.head()
+    # 计算简单移动平均线
+    stock_data['SMA'] = ta.trend.sma_indicator(stock_data['Close'], window=6)
+    stock_data[['Date', 'Close', 'SMA']].head()
+    # 计算布林带
+    stock_data['bb_upper'], stock_data['bb_middle'], stock_data['bb_lower'] = ta.volatility.bollinger_hband_indicator(stock_data['Close'], window=20), ta.volatility.bollinger_mavg(stock_data['Close'], window=20), ta.volatility.bollinger_lband_indicator(stock_data['Close'], window=20)
+    stock_data[['Date', 'Close', 'bb_upper', 'bb_middle', 'bb_lower']].head()
+    return stock_data
+
+
+@pytest.mark.asyncio
+async def test_clone_function():
+    clone = CloneFunction()
+    code = await clone.run(template_code, source_code)
+    assert 'def ' in code
+    stock_path = './tests/data/baba_stock.csv'
+    df, msg = run_function_code(code, 'stock_indicator', stock_path)
+    assert not msg
+    expected_df = get_expected_res()
+    assert df.equals(expected_df)

tests/metagpt/planner/__init__.py

@@ -0,0 +1,7 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+"""
+@Time    : 2023/9/16 20:03
+@Author  : femto Zheng
+@File    : __init__.py
+"""

tests/metagpt/planner/test_action_planner.py

@@ -0,0 +1,29 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+"""
+@Time    : 2023/9/16 20:03
+@Author  : femto Zheng
+@File    : test_basic_planner.py
+"""
+import pytest
+from semantic_kernel.core_skills import FileIOSkill, MathSkill, TextSkill, TimeSkill
+from semantic_kernel.planning.action_planner.action_planner import ActionPlanner
+
+from metagpt.actions import BossRequirement
+from metagpt.roles.sk_agent import SkAgent
+from metagpt.schema import Message
+
+
+@pytest.mark.asyncio
+async def test_action_planner():
+    role = SkAgent(planner_cls=ActionPlanner)
+    # let's give the agent 4 skills
+    role.import_skill(MathSkill(), "math")
+    role.import_skill(FileIOSkill(), "fileIO")
+    role.import_skill(TimeSkill(), "time")
+    role.import_skill(TextSkill(), "text")
+    task = "What is the sum of 110 and 990?"
+    role.recv(Message(content=task, cause_by=BossRequirement))
+
+    await role._think()  # it will choose mathskill.Add
+    assert "1100" == (await role._act()).content

tests/metagpt/planner/test_basic_planner.py

@@ -0,0 +1,34 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+"""
+@Time    : 2023/9/16 20:03
+@Author  : femto Zheng
+@File    : test_basic_planner.py
+"""
+import pytest
+from semantic_kernel.core_skills import TextSkill
+
+from metagpt.actions import BossRequirement
+from metagpt.const import SKILL_DIRECTORY
+from metagpt.roles.sk_agent import SkAgent
+from metagpt.schema import Message
+
+
+@pytest.mark.asyncio
+async def test_basic_planner():
+    task = """
+        Tomorrow is Valentine's day. I need to come up with a few date ideas. She speaks French so write it in French.
+        Convert the text to uppercase"""
+    role = SkAgent()
+
+    # let's give the agent some skills
+    role.import_semantic_skill_from_directory(SKILL_DIRECTORY, "SummarizeSkill")
+    role.import_semantic_skill_from_directory(SKILL_DIRECTORY, "WriterSkill")
+    role.import_skill(TextSkill(), "TextSkill")
+    # using BasicPlanner
+    role.recv(Message(content=task, cause_by=BossRequirement))
+    await role._think()
+    # assuming sk_agent will think he needs WriterSkill.Brainstorm and WriterSkill.Translate
+    assert "WriterSkill.Brainstorm" in role.plan.generated_plan.result
+    assert "WriterSkill.Translate" in role.plan.generated_plan.result
+    # assert "SALUT" in (await role._act()).content #content will be some French

tests/metagpt/tools/test_code_interpreter.py

@@ -0,0 +1,42 @@
+import pytest
+import pandas as pd
+from pathlib import Path
+
+from tests.data import sales_desc, store_desc
+from metagpt.tools.code_interpreter import OpenCodeInterpreter, OpenInterpreterDecorator
+from metagpt.actions import Action
+from metagpt.logs import logger
+
+
+logger.add('./tests/data/test_ci.log')
+stock = "./tests/data/baba_stock.csv"
+
+
+# TODO: 需要一种表格数据格式，能够支持schame管理的，标注字段类型和字段含义。
+class CreateStockIndicators(Action):
+    @OpenInterpreterDecorator(save_code=True, code_file_path="./tests/data/stock_indicators.py")
+    async def run(self, stock_path: str, indicators=['Simple Moving Average', 'BollingerBands']) -> pd.DataFrame:
+        """对stock_path中的股票数据, 使用pandas和ta计算indicators中的技术指标, 返回带有技术指标的股票数据，不需要去除空值, 不需要安装任何包；
+            指标生成对应的三列: SMA, BB_upper, BB_lower
+        """
+        ...
+
+
+@pytest.mark.asyncio
+async def test_actions():
+    # 计算指标
+    indicators = ['Simple Moving Average', 'BollingerBands']
+    stocker = CreateStockIndicators()
+    df, msg = await stocker.run(stock, indicators=indicators)
+    assert isinstance(df, pd.DataFrame)
+    assert 'Close' in df.columns
+    assert 'Date' in df.columns
+    # 将df保存为文件，将文件路径传入到下一个action
+    df_path = './tests/data/stock_indicators.csv'
+    df.to_csv(df_path)
+    assert Path(df_path).is_file()
+    # 可视化指标结果
+    figure_path = './tests/data/figure_ci.png'
+    ci_ploter = OpenCodeInterpreter()
+    ci_ploter.chat(f"使用seaborn对{df_path}中与股票布林带有关的数据列的Date, Close, SMA, BB_upper（布林带上界）, BB_lower（布林带下界）进行可视化, 可视化图片保存在{figure_path}中。不需要任何指标计算，把Date列转换为日期类型。要求图片优美，BB_upper, BB_lower之间使用合适的颜色填充。")
+    assert Path(figure_path).is_file()

tests/metagpt/utils/test_file.py

@@ -7,7 +7,6 @@
 """
 from pathlib import Path
 
-import aiofiles
 import pytest
 
 from metagpt.utils.file import File
@@ -18,10 +17,10 @@ from metagpt.utils.file import File
     ("root_path", "filename", "content"),
     [(Path("/code/MetaGPT/data/tutorial_docx/2023-09-07_17-05-20"), "test.md", "Hello World!")]
 )
-async def test_write_file(root_path: Path, filename: str, content: bytes):
+async def test_write_and_read_file(root_path: Path, filename: str, content: bytes):
     full_file_name = await File.write(root_path=root_path, filename=filename, content=content.encode('utf-8'))
     assert isinstance(full_file_name, Path)
     assert root_path / filename == full_file_name
-    async with aiofiles.open(full_file_name, mode="r") as reader:
-        body = await reader.read()
-        assert body == content
+    file_data = await File.read(full_file_name)
+    assert file_data.decode("utf-8") == content
+

tests/metagpt/utils/test_output_parser.py

@@ -5,7 +5,7 @@
 @Author  : chengmaoyu
 @File    : test_output_parser.py
 """
-from typing import List, Tuple
+from typing import List, Tuple, Union
 
 import pytest
 
@@ -64,6 +64,59 @@ def test_parse_data():
     assert OutputParser.parse_data(test_data) == expected_result
 
 
+@pytest.mark.parametrize(
+    ("text", "data_type", "parsed_data", "expected_exception"),
+    [
+        (
+            """xxx [1, 2, ["a", "b", [3, 4]], {"x": 5, "y": [6, 7]}] xxx""",
+            list,
+            [1, 2, ["a", "b", [3, 4]], {"x": 5, "y": [6, 7]}],
+            None,
+        ),
+        (
+            """xxx ["1", "2", "3"] xxx \n xxx \t xx""",
+            list,
+            ["1", "2", "3"],
+            None,
+        ),
+        (
+            """{"title": "a", "directory": {"sub_dir1": ["title1, title2"]}, "sub_dir2": [1, 2]}""",
+            dict,
+            {"title": "a", "directory": {"sub_dir1": ["title1, title2"]}, "sub_dir2": [1, 2]},
+            None,
+        ),
+        (
+            """xxx {"title": "x", \n  \t "directory": ["x", \n "y"]} xxx \n xxx \t xx""",
+            dict,
+            {"title": "x", "directory": ["x", "y"]},
+            None,
+        ),
+        (
+            """xxx xx""",
+            list,
+            None,
+            Exception,
+        ),
+        (
+            """xxx [1, 2, []xx""",
+            list,
+            None,
+            Exception,
+        ),
+    ]
+)
+def test_extract_struct(text: str, data_type: Union[type(list), type(dict)], parsed_data: Union[list, dict], expected_exception):
+    def case():
+        resp = OutputParser.extract_struct(text, data_type)
+        assert resp == parsed_data
+
+    if expected_exception:
+        with pytest.raises(expected_exception):
+            case()
+    else:
+        case()
+
+
 if __name__ == '__main__':
     t_text = '''
 ## Required Python third-party packages