update: The teminal tool adds Conda environment support for daemon mode running

examples/di/run_flask.py

@@ -0,0 +1,20 @@
+import asyncio
+
+from metagpt.roles.di.data_interpreter import DataInterpreter
+
+
+USE_GOT_REPO_REQ = """
+Write a service using Flask, create a conda environment and run it, and call the service's interface for validation.
+Notice: Don't write all codes in one response, each time, just write code for one step.
+"""
+# If you have created a conda environment, you can say:
+# I have created the conda environment '{env_name}', please use this environment to execute.
+
+
+async def main():
+    di = DataInterpreter(tools=["Terminal", "FileManager"])
+    await di.run(USE_GOT_REPO_REQ)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

examples/di/use_github_repo.py

@@ -5,7 +5,8 @@ from metagpt.roles.di.data_interpreter import DataInterpreter
 USE_GOT_REPO_REQ = """
 This is a link to the GOT github repo: https://github.com/spcl/graph-of-thoughts.git.
 Clone it, read the README to understand the usage, install it, and finally run the quick start example.
-**Note the config for LLM is at `config/config_got.json`, use this path directly.** Don't write all codes in one response, each time, just write code for one step.
+**Note the config for LLM is at `config/config_got.json`, it's outside the repo path, before using it, you need to copy it into graph-of-thoughts.
+** Don't write all codes in one response, each time, just write code for one step.
 """