microsoft · sonichi · Sep 28, 2023 · Sep 28, 2023 · Sep 28, 2023 · Sep 28, 2023
diff --git a/.gitignore b/.gitignore
@@ -159,3 +159,8 @@ output/
 
 # local config files
 *.config.local
+OAI_CONFIG_LIST
+key_openai.txt
+key_aoai.txt
+base_aoai.txt
+wolfram.txt
diff --git a/OAI_CONFIG_LIST_sample b/OAI_CONFIG_LIST_sample
@@ -0,0 +1,21 @@
+// Please modify the content, remove this comment and rename this file to OAI_CONFIG_LIST to run the sample code.
+[
+    {
+        "model": "gpt-4",
+        "api_key": "<your OpenAI API key here>"
+    },
+    {
+        "model": "gpt-4",
+        "api_key": "<your Azure OpenAI API key here>",
+        "api_base": "<your Azure OpenAI API base here>",
+        "api_type": "azure",
+        "api_version": "2023-07-01-preview"
+    },
+    {
+        "model": "gpt-3.5-turbo",
+        "api_key": "<your Azure OpenAI API key here>",
+        "api_base": "<your Azure OpenAI API base here>",
+        "api_type": "azure",
+        "api_version": "2023-07-01-preview"
+    }
+]
diff --git a/README.md b/README.md
@@ -60,15 +60,24 @@ For LLM inference configurations, check the [FAQ](https://microsoft.github.io/au
 ## Quickstart
 
 * Autogen enables the next-gen LLM applications with a generic multi-agent conversation framework. It offers customizable and conversable agents which integrate LLMs, tools and human.
-By automating chat among multiple capable agents, one can easily make them collectively perform tasks autonomously or with human feedback, including tasks that require using tools via code. For example,
+By automating chat among multiple capable agents, one can easily make them collectively perform tasks autonomously or with human feedback, including tasks that require using tools via code. For [example](https://github.com/microsoft/autogen/blob/main/test/twoagent.py),
 ```python
-from autogen import AssistantAgent, UserProxyAgent
-assistant = AssistantAgent("assistant")
-user_proxy = UserProxyAgent("user_proxy")
-user_proxy.initiate_chat(assistant, message="Plot a chart of META and TESLA stock price change YTD.")
+from autogen import AssistantAgent, UserProxyAgent, config_list_from_json
+# Load LLM inference endpoints from an env variable or a file
+# See https://microsoft.github.io/autogen/docs/FAQ#set-your-api-endpoints
+# and OAI_CONFIG_LIST_sample.json
+config_list = config_list_from_json(env_or_file="OAI_CONFIG_LIST")
+assistant = AssistantAgent("assistant", llm_config={"config_list": config_list})
+user_proxy = UserProxyAgent("user_proxy", code_execution_config={"work_dir": "coding"})
+user_proxy.initiate_chat(assistant, message="Plot a chart of NVDA and TESLA stock price change YTD.")
 # This initiates an automated chat between the two agents to solve the task
 ```
 
+This example can be run with
+```python
+python test/twoagent.py
+```
+After the repo is cloned.
 The figure below shows an example conversation flow with AutoGen.
 ![Agent Chat Example](https://github.com/microsoft/autogen/blob/main/website/static/img/chat_example.png)
 

diff --git a/autogen/agentchat/assistant_agent.py b/autogen/agentchat/assistant_agent.py
@@ -16,7 +16,7 @@ class AssistantAgent(ConversableAgent):
     DEFAULT_SYSTEM_MESSAGE = """You are a helpful AI assistant.
 Solve tasks using your coding and language skills.
 In the following cases, suggest python code (in a python coding block) or shell script (in a sh coding block) for the user to execute.
-    1. When you need to collect info, use the code to output the info you need, for example, browse or search the web, download/read a file, print the content of a webpage or a file, get the current date/time. After sufficient info is printed and the task is ready to be solved based on your language skill, you can solve the task by yourself.
+    1. When you need to collect info, use the code to output the info you need, for example, browse or search the web, download/read a file, print the content of a webpage or a file, get the current date/time, check the operating system. After sufficient info is printed and the task is ready to be solved based on your language skill, you can solve the task by yourself.
     2. When you need to perform some task with code, use the code to perform the task and output the result. Finish the task smartly.
 Solve the task step by step if you need to. If a plan is not provided, explain your plan first. Be clear which step uses code, and which step uses your language skill.
 When using code, you must indicate the script type in the code block. The user cannot provide any other feedback or perform any other action beyond executing the code you suggest. The user can't modify your code. So do not suggest incomplete code which requires users to modify. Don't use a code block if it's not intended to be executed by the user.

diff --git a/autogen/code_utils.py b/autogen/code_utils.py
@@ -23,6 +23,8 @@
 UNKNOWN = "unknown"
 TIMEOUT_MSG = "Timeout"
 DEFAULT_TIMEOUT = 600
+WIN32 = sys.platform == "win32"
+PATH_SEPARATOR = WIN32 and "\\" or "/"
 
 
 def infer_lang(code):
@@ -193,10 +195,12 @@ def timeout_handler(signum, frame):
 
 
 def _cmd(lang):
-    if lang.startswith("python") or lang in ["bash", "sh"]:
+    if lang.startswith("python") or lang in ["bash", "sh", "powershell"]:
         return lang
-    if lang == "shell":
+    if lang in ["shell"]:
         return "sh"
+    if lang in ["ps1"]:
+        return "powershell"
     raise NotImplementedError(f"{lang} not recognized in code execution")
 
 
@@ -242,6 +246,8 @@ def execute_code(
     assert code is not None or filename is not None, "Either code or filename must be provided."
     timeout = timeout or DEFAULT_TIMEOUT
     original_filename = filename
+    if WIN32 and lang in ["sh", "shell"]:
+        lang = "ps1"
     if filename is None:
         code_hash = md5(code.encode()).hexdigest()
         # create a file with a automatically generated name
@@ -258,13 +264,17 @@ def execute_code(
     in_docker_container = os.path.exists("/.dockerenv")
     if not use_docker or in_docker_container:
         # already running in a docker container
-        cmd = [sys.executable if lang.startswith("python") else _cmd(lang), filename]
-        if sys.platform == "win32":
+        cmd = [
+            sys.executable if lang.startswith("python") else _cmd(lang),
+            f".\\{filename}" if WIN32 else filename,
+        ]
+        if WIN32:
             logging.warning("SIGALRM is not supported on Windows. No timeout will be enforced.")
             result = subprocess.run(
                 cmd,
                 cwd=work_dir,
                 capture_output=True,
+                text=True,
             )
         else:
             signal.signal(signal.SIGALRM, timeout_handler)
@@ -290,7 +300,7 @@ def execute_code(
                 abs_path = str(pathlib.Path(filepath).absolute())
                 logs = logs.replace(str(abs_path), "").replace(filename, "")
             else:
-                abs_path = str(pathlib.Path(work_dir).absolute()) + "/"
+                abs_path = str(pathlib.Path(work_dir).absolute()) + PATH_SEPARATOR
                 logs = logs.replace(str(abs_path), "")
         else:
             logs = result.stdout

diff --git a/autogen/version.py b/autogen/version.py
@@ -1 +1 @@
-__version__ = "0.1.2"
+__version__ = "0.1.3"
diff --git a/notebook/agentchat_MathChat.ipynb b/notebook/agentchat_MathChat.ipynb
@@ -5,7 +5,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<a href=\"https://colab.research.google.com/github/microsoft/FLAML/blob/main/notebook/agentchat_MathChat.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+    "<a href=\"https://colab.research.google.com/github/microsoft/autogen/blob/main/notebook/agentchat_MathChat.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
    ]
   },
   {
@@ -43,7 +43,7 @@
    "source": [
     "## Set your API Endpoint\n",
     "\n",
-    "The [`config_list_from_json`](https://microsoft.github.io/FLAML/docs/reference/autogen/oai/openai_utils#config_list_from_json) function loads a list of configurations from an environment variable or a json file.\n"
+    "The [`config_list_from_json`](https://microsoft.github.io/autogen/docs/reference/oai/openai_utils#config_list_from_json) function loads a list of configurations from an environment variable or a json file.\n"
    ]
   },
   {

diff --git a/notebook/agentchat_RetrieveChat.ipynb b/notebook/agentchat_RetrieveChat.ipynb
@@ -62,7 +62,7 @@
    "source": [
     "## Set your API Endpoint\n",
     "\n",
-    "The [`config_list_from_json`](https://microsoft.github.io/FLAML/docs/reference/autogen/oai/openai_utils#config_list_from_json) function loads a list of configurations from an environment variable or a json file.\n"
+    "The [`config_list_from_json`](https://microsoft.github.io/autogen/docs/reference/oai/openai_utils#config_list_from_json) function loads a list of configurations from an environment variable or a json file.\n"
    ]
   },
   {
@@ -3684,6 +3684,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [

diff --git a/notebook/agentchat_auto_feedback_from_code_execution.ipynb b/notebook/agentchat_auto_feedback_from_code_execution.ipynb
@@ -55,7 +55,7 @@
    "source": [
     "## Set your API Endpoint\n",
     "\n",
-    "The [`config_list_from_json`](https://microsoft.github.io/FLAML/docs/reference/autogen/oai/openai_utils#config_list_from_json) function loads a list of configurations from an environment variable or a json file.\n"
+    "The [`config_list_from_json`](https://microsoft.github.io/autogen/docs/reference/oai/openai_utils#config_list_from_json) function loads a list of configurations from an environment variable or a json file.\n"
    ]
   },
   {

diff --git a/notebook/agentchat_chess.ipynb b/notebook/agentchat_chess.ipynb
@@ -56,7 +56,7 @@
    "source": [
     "## Set your API Endpoint\n",
     "\n",
-    "The [`config_list_from_json`](https://microsoft.github.io/FLAML/docs/reference/autogen/oai/openai_utils#config_list_from_json) function loads a list of configurations from an environment variable or a json file."
+    "The [`config_list_from_json`](https://microsoft.github.io/autogen/docs/reference/oai/openai_utils#config_list_from_json) function loads a list of configurations from an environment variable or a json file."
    ]
   },
   {

diff --git a/notebook/agentchat_function_call.ipynb b/notebook/agentchat_function_call.ipynb
@@ -47,7 +47,7 @@
    "source": [
     "## Set your API Endpoint\n",
     "\n",
-    "The [`config_list_from_models`](https://microsoft.github.io/FLAML/docs/reference/autogen/oai/openai_utils#config_list_from_models) function tries to create a list of configurations using Azure OpenAI endpoints and OpenAI endpoints for the provided list of models. It assumes the api keys and api bases are stored in the corresponding environment variables or local txt files:\n",
+    "The [`config_list_from_models`](https://microsoft.github.io/autogen/docs/reference/oai/openai_utils#config_list_from_models) function tries to create a list of configurations using Azure OpenAI endpoints and OpenAI endpoints for the provided list of models. It assumes the api keys and api bases are stored in the corresponding environment variables or local txt files:\n",
     "\n",
     "- OpenAI API key: os.environ[\"OPENAI_API_KEY\"] or `openai_api_key_file=\"key_openai.txt\"`.\n",
     "- Azure OpenAI API key: os.environ[\"AZURE_OPENAI_API_KEY\"] or `aoai_api_key_file=\"key_aoai.txt\"`. Multiple keys can be stored, one per line.\n",

diff --git a/notebook/agentchat_groupchat.ipynb b/notebook/agentchat_groupchat.ipynb
@@ -45,7 +45,7 @@
    "source": [
     "## Set your API Endpoint\n",
     "\n",
-    "The [`config_list_from_json`](https://microsoft.github.io/FLAML/docs/reference/autogen/oai/openai_utils#config_list_from_json) function loads a list of configurations from an environment variable or a json file."
+    "The [`config_list_from_json`](https://microsoft.github.io/autogen/docs/reference/oai/openai_utils#config_list_from_json) function loads a list of configurations from an environment variable or a json file."
    ]
   },
   {

diff --git a/notebook/agentchat_groupchat_vis.ipynb b/notebook/agentchat_groupchat_vis.ipynb
@@ -43,7 +43,7 @@
    "source": [
     "## Set your API Endpoint\n",
     "\n",
-    "The [`config_list_from_json`](https://microsoft.github.io/FLAML/docs/reference/autogen/oai/openai_utils#config_list_from_json) function loads a list of configurations from an environment variable or a json file."
+    "The [`config_list_from_json`](https://microsoft.github.io/autogen/docs/reference/oai/openai_utils#config_list_from_json) function loads a list of configurations from an environment variable or a json file."
    ]
   },
   {
@@ -1029,7 +1029,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.17"
+   "version": "3.10.12"
   },
   "orig_nbformat": 4
  },

diff --git a/notebook/agentchat_teaching.ipynb b/notebook/agentchat_teaching.ipynb
@@ -81,7 +81,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from flaml import autogen\n",
+    "import autogen\n",
     "\n",
     "llm_config={\n",
     "    \"request_timeout\": 600,\n",
@@ -95,6 +95,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -104,6 +105,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -138,6 +140,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -697,6 +700,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -825,6 +829,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [

diff --git a/notebook/oai_chatgpt_gpt4.ipynb b/notebook/oai_chatgpt_gpt4.ipynb
@@ -88,7 +88,7 @@
    "source": [
     "### Set your API Endpoint\n",
     "\n",
-    "The [`config_list_openai_aoai`](https://microsoft.github.io/FLAML/docs/reference/autogen/oai/openai_utils#config_list_openai_aoai) function tries to create a list of  Azure OpenAI endpoints and OpenAI endpoints. It assumes the api keys and api bases are stored in the corresponding environment variables or local txt files:\n",
+    "The [`config_list_openai_aoai`](https://microsoft.github.io/autogen/docs/reference/oai/openai_utils#config_list_openai_aoai) function tries to create a list of  Azure OpenAI endpoints and OpenAI endpoints. It assumes the api keys and api bases are stored in the corresponding environment variables or local txt files:\n",
     "\n",
     "- OpenAI API key: os.environ[\"OPENAI_API_KEY\"] or `openai_api_key_file=\"key_openai.txt\"`.\n",
     "- Azure OpenAI API key: os.environ[\"AZURE_OPENAI_API_KEY\"] or `aoai_api_key_file=\"key_aoai.txt\"`. Multiple keys can be stored, one per line.\n",

diff --git a/notebook/oai_completion.ipynb b/notebook/oai_completion.ipynb
@@ -59,11 +59,11 @@
    "source": [
     "## Set your API Endpoint\n",
     "\n",
-    "* The [`config_list_openai_aoai`](https://microsoft.github.io/FLAML/docs/reference/autogen/oai/openai_utils#config_list_openai_aoai) function tries to create a list of configurations using Azure OpenAI endpoints and OpenAI endpoints. It assumes the api keys and api bases are stored in the corresponding environment variables or local txt files:\n",
+    "* The [`config_list_openai_aoai`](https://microsoft.github.io/autogen/docs/reference/oai/openai_utils#config_list_openai_aoai) function tries to create a list of configurations using Azure OpenAI endpoints and OpenAI endpoints. It assumes the api keys and api bases are stored in the corresponding environment variables or local txt files:\n",
     "  - OpenAI API key: os.environ[\"OPENAI_API_KEY\"] or `openai_api_key_file=\"key_openai.txt\"`.\n",
     "  - Azure OpenAI API key: os.environ[\"AZURE_OPENAI_API_KEY\"] or `aoai_api_key_file=\"key_aoai.txt\"`. Multiple keys can be stored, one per line.\n",
     "  - Azure OpenAI API base: os.environ[\"AZURE_OPENAI_API_BASE\"] or `aoai_api_base_file=\"base_aoai.txt\"`. Multiple bases can be stored, one per line.\n",
-    "* The [`config_list_from_json`](https://microsoft.github.io/FLAML/docs/reference/autogen/oai/openai_utils#config_list_from_json) function loads a list of configurations from an environment variable or a json file. It first looks for environment variable `env_or_file` which needs to be a valid json string. If that variable is not found, it then looks for a json file with the same name. It filters the configs by filter_dict.\n",
+    "* The [`config_list_from_json`](https://microsoft.github.io/autogen/docs/reference/oai/openai_utils#config_list_from_json) function loads a list of configurations from an environment variable or a json file. It first looks for environment variable `env_or_file` which needs to be a valid json string. If that variable is not found, it then looks for a json file with the same name. It filters the configs by filter_dict.\n",
     "\n",
     "It's OK to have only the OpenAI API key, or only the Azure OpenAI API key + base. If you open this notebook in colab, you can upload your files by clicking the file icon on the left panel and then choose \"upload file\" icon.\n"
    ]

diff --git a/test/test_code.py b/test/test_code.py
@@ -9,6 +9,8 @@
     infer_lang,
     improve_code,
     improve_function,
+    PATH_SEPARATOR,
+    WIN32,
 )
 
 KEY_LOC = "notebook"
@@ -214,36 +216,56 @@ def scrape(url):
 
 
 @pytest.mark.skipif(
-    sys.platform in ["darwin", "win32"],
-    reason="do not run on MacOS or windows",
+    sys.platform in ["darwin"],
+    reason="do not run on MacOS",
 )
-def test_execute_code():
+def test_execute_code(use_docker=None):
     try:
         import docker
     except ImportError as exc:
         print(exc)
         docker = None
-    exit_code, msg, image = execute_code("print('hello world')", filename="tmp/codetest.py")
+    if use_docker is None:
+        use_docker = docker is not None
+    exit_code, msg, image = execute_code("print('hello world')", filename="tmp/codetest.py", use_docker=use_docker)
     assert exit_code == 0 and msg == "hello world\n", msg
     # read a file
-    print(execute_code("with open('tmp/codetest.py', 'r') as f: a=f.read()"))
+    print(execute_code("with open('tmp/codetest.py', 'r') as f: a=f.read()", use_docker=use_docker))
     # create a file
     exit_code, msg, image = execute_code(
-        "with open('tmp/codetest.py', 'w') as f: f.write('b=1')", work_dir=f"{here}/my_tmp", filename="tmp2/codetest.py"
+        "with open('tmp/codetest.py', 'w') as f: f.write('b=1')",
+        work_dir=f"{here}/my_tmp",
+        filename="tmp2/codetest.py",
+        use_docker=use_docker,
+    )
+    assert exit_code and (
+        'File "tmp2/codetest.py"'.replace("/", PATH_SEPARATOR) in msg
+        or 'File ".\\tmp2/codetest.py' in msg  # py3.8 + win32
+    ), msg
+    print(
+        execute_code(
+            "with open('tmp/codetest.py', 'w') as f: f.write('b=1')", work_dir=f"{here}/my_tmp", use_docker=use_docker
+        )
     )
-    assert exit_code and 'File "tmp2/codetest.py"' in msg, msg
-    print(execute_code("with open('tmp/codetest.py', 'w') as f: f.write('b=1')", work_dir=f"{here}/my_tmp"))
     # execute code in a file
-    print(execute_code(filename="tmp/codetest.py"))
-    print(execute_code("python tmp/codetest.py", lang="sh"))
+    print(execute_code(filename="tmp/codetest.py", use_docker=use_docker))
+    print(execute_code("python tmp/codetest.py", lang="sh", use_docker=use_docker))
     # execute code for assertion error
-    exit_code, msg, image = execute_code("assert 1==2")
+    exit_code, msg, image = execute_code("assert 1==2", use_docker=use_docker)
     assert exit_code, msg
-    assert 'File ""' in msg
+    assert 'File ""' in msg or 'File ".\\"' in msg  # py3.8 + win32
     # execute code which takes a long time
-    exit_code, error, image = execute_code("import time; time.sleep(2)", timeout=1)
-    assert exit_code and error == "Timeout"
-    assert isinstance(image, str) or docker is None or os.path.exists("/.dockerenv")
+    exit_code, error, image = execute_code("import time; time.sleep(2)", timeout=1, use_docker=use_docker)
+    assert exit_code and error == "Timeout" or WIN32
+    assert isinstance(image, str) or docker is None or os.path.exists("/.dockerenv") or use_docker is False
+
+
+@pytest.mark.skipif(
+    sys.platform in ["darwin"],
+    reason="do not run on MacOS",
+)
+def test_execute_code_nodocker():
+    test_execute_code(use_docker=False)
 
 
 def test_execute_code_no_docker():

diff --git a/test/twoagent.py b/test/twoagent.py
@@ -0,0 +1,9 @@
+from autogen import AssistantAgent, UserProxyAgent, config_list_from_json
+
+# Load LLM inference endpoints from an env variable or a file
+# See https://microsoft.github.io/autogen/docs/FAQ#set-your-api-endpoints
+# and OAI_CONFIG_LIST_sample.json
+config_list = config_list_from_json(env_or_file="OAI_CONFIG_LIST")
+assistant = AssistantAgent("assistant", llm_config={"config_list": config_list})
+user_proxy = UserProxyAgent("user_proxy", code_execution_config={"work_dir": "coding"})
+user_proxy.initiate_chat(assistant, message="Plot a chart of NVDA and TESLA stock price change YTD.")