Merge branch 'main' into code_interpreter

examples/di/arxiv_reader.py

@@ -0,0 +1,21 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+from metagpt.roles.di.data_interpreter import DataInterpreter
+
+
+async def main():
+    template = "https://arxiv.org/list/{tag}/pastweek?skip=0&show=300"
+    tags = ["cs.ai", "cs.cl", "cs.lg", "cs.se"]
+    urls = [template.format(tag=tag) for tag in tags]
+    prompt = f"""This is a collection of arxiv urls: '{urls}' .
+Record each article, remove duplicates by title (they may have multiple tags), filter out papers related to 
+large language model / agent / llm, print top 100 and visualize the word count of the titles"""
+    di = DataInterpreter(react_mode="react", tools=["scrape_web_playwright"])
+
+    await di.run(prompt)
+
+
+if __name__ == "__main__":
+    import asyncio
+
+    asyncio.run(main())

examples/di/custom_tool.py

@@ -0,0 +1,36 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+"""
+@Time    : 2024/3/22 10:54
+@Author  : alexanderwu
+@File    : custom_tool.py
+"""
+
+from metagpt.roles.di.data_interpreter import DataInterpreter
+from metagpt.tools.tool_registry import register_tool
+
+
+@register_tool()
+def magic_function(arg1: str, arg2: int) -> dict:
+    """
+    The magic function that does something.
+
+    Args:
+        arg1 (str): ...
+        arg2 (int): ...
+
+    Returns:
+        dict: ...
+    """
+    return {"arg1": arg1 * 3, "arg2": arg2 * 5}
+
+
+async def main():
+    di = DataInterpreter(tools=["magic_function"])
+    await di.run("Just call the magic function with arg1 'A' and arg2 2. Tell me the result.")
+
+
+if __name__ == "__main__":
+    import asyncio
+
+    asyncio.run(main())

examples/di/data_visualization.py

@@ -1,14 +1,17 @@
 import asyncio
 
+from metagpt.logs import logger
 from metagpt.roles.di.data_interpreter import DataInterpreter
+from metagpt.utils.recovery_util import save_history
 
 
 async def main(requirement: str = ""):
     di = DataInterpreter()
-    await di.run(requirement)
+    rsp = await di.run(requirement)
+    logger.info(rsp)
+    save_history(role=di)
 
 
 if __name__ == "__main__":
     requirement = "Run data analysis on sklearn Iris dataset, include a plot"
-
     asyncio.run(main(requirement))