Feat:

- Add pytest for load_config_from_json for yaml format
- Add docs for website
- Add pyyaml to setup.py

setup.py

@@ -25,6 +25,7 @@
     # Disallowing 2.6.0 can be removed when this is fixed https://github.com/pydantic/pydantic/issues/8705
     "pydantic>=1.10,<3,!=2.6.0",  # could be both V1 and V2
     "docker",
+    "pyyaml",
 ]
 
 jupyter_executor = [

test/oai/test_utils.py

@@ -8,6 +8,7 @@
 from unittest.mock import patch
 
 import pytest
+import yaml
 from conftest import MOCK_OPEN_AI_API_KEY
 
 import autogen  # noqa: E402
@@ -65,30 +66,49 @@
 ]
 """
 
+YAML_SAMPLE = """
+- model: gpt-3.5-turbo
+  api_type: openai
+- model: gpt-4
+  api_type: openai
+- model: gpt-35-turbo-v0301
+  tags:
+    - gpt-3.5-turbo
+    - gpt35_turbo
+  api_key: "111113fc7e8a46419bfac511bb301111"
+  base_url: "https://1111.openai.azure.com"
+  api_type: azure
+  api_version: "2024-02-15-preview"
+- model: gpt
+  api_key: not-needed
+  base_url: "http://localhost:1234/v1"
+"""
+
 
 @pytest.fixture
 def mock_os_environ():
     with mock.patch.dict(os.environ, ENV_VARS):
         yield
 
 
-def test_config_list_from_json():
+@pytest.mark.parametrize("config_example", [JSON_SAMPLE, YAML_SAMPLE], ids=["from_json", "from_yaml"])
+def test_config_list_from_json(config_example):
     with tempfile.NamedTemporaryFile(mode="w+", delete=False) as tmp_file:
-        json_data = json.loads(JSON_SAMPLE)
-        tmp_file.write(JSON_SAMPLE)
+        config_data = yaml.safe_load(config_example)
+        tmp_file.write(config_example)
         tmp_file.flush()
         config_list = autogen.config_list_from_json(tmp_file.name)
 
-        assert len(config_list) == len(json_data)
+        assert len(config_list) == len(config_data)
         i = 0
         for config in config_list:
             assert isinstance(config, dict)
             for key in config:
-                assert key in json_data[i]
-                assert config[key] == json_data[i][key]
+                assert key in config_data[i]
+                assert config[key] == config_data[i][key]
             i += 1
 
-        os.environ["config_list_test"] = JSON_SAMPLE
+        os.environ["config_list_test"] = config_example
         config_list_2 = autogen.config_list_from_json("config_list_test")
         assert config_list == config_list_2
 

website/docs/topics/llm_configuration.ipynb

@@ -116,6 +116,57 @@
     "</Tabs>\n",
     "````\n",
     "\n",
+    "There is another way to specify the `config_list` using a YAML file. This is useful when you have multiple models and want to keep the configuration separate from the code. The YAML file should be formatted as follows:\n",
+    "\n",
+    "````{=mdx}\n",
+    "import Tabs from '@theme/Tabs';\n",
+    "import TabItem from '@theme/TabItem';\n",
+    "\n",
+    "<Tabs>\n",
+    "  <TabItem value=\"openai\" label=\"OpenAI\" default>\n",
+    "    - `model` (str, required): The identifier of the model to be used, such as 'gpt-4', 'gpt-3.5-turbo'.\n",
+    "    - `api_key` (str, optional): The API key required for authenticating requests to the model's API endpoint.\n",
+    "    - `base_url` (str, optional): The base URL of the API endpoint. This is the root address where API calls are directed.\n",
+    "    - `tags` (List[str], optional): Tags which can be used for filtering.\n",
+    "\n",
+    "    Example:\n",
+    "    ```yaml\n",
+    "    - model: gpt-4\n",
+    "      api_key: <your OpenAI API key here>\n",
+    "    ```\n",
+    "  </TabItem>\n",
+    "  <TabItem value=\"azureopenai\" label=\"Azure OpenAI\">\n",
+    "    - `model` (str, required): The deployment to be used. The model corresponds to the deployment name on Azure OpenAI.\n",
+    "    - `api_key` (str, optional): The API key required for authenticating requests to the model's API endpoint.\n",
+    "    - `api_type`: `azure`\n",
+    "    - `base_url` (str, optional): The base URL of the API endpoint. This is the root address where API calls are directed.\n",
+    "    - `api_version` (str, optional): The version of the Azure API you wish to use.\n",
+    "    - `tags` (List[str], optional): Tags which can be used for filtering.\n",
+    "\n",
+    "    Example:\n",
+    "    ```yaml\n",
+    "    - model: my-gpt-4-deployment\n",
+    "      api_type: azure\n",
+    "      api_key: <your Azure OpenAI API key here>\n",
+    "      base_url: https://ENDPOINT.openai.azure.com/\n",
+    "      api_version: 2024-02-15-preview\n",
+    "    ```\n",
+    "  </TabItem>\n",
+    "  <TabItem value=\"other\" label=\"Other OpenAI compatible\">\n",
+    "    - `model` (str, required): The identifier of the model to be used, such as 'llama-7B'.\n",
+    "    - `api_key` (str, optional): The API key required for authenticating requests to the model's API endpoint.\n",
+    "    - `base_url` (str, optional): The base URL of the API endpoint. This is the root address where API calls are directed.\n",
+    "    - `tags` (List[str], optional): Tags which can be used for filtering.\n",
+    "\n",
+    "    Example:\n",
+    "    ```yaml\n",
+    "    - model: llama-7B\n",
+    "      base_url: http://localhost:1234\n",
+    "    ```\n",
+    "  </TabItem>\n",
+    "</Tabs>\n",
+    "````\n",
+    "\n",
     "---\n",
     "\n",
     "````{=mdx}\n",
@@ -126,9 +177,16 @@
     "\n",
     "### `OAI_CONFIG_LIST` pattern\n",
     "\n",
-    "A common, useful pattern used is to define this `config_list` is via JSON (specified as a file or an environment variable set to a JSON-formatted string) and then use the [`config_list_from_json`](/docs/reference/oai/openai_utils#config_list_from_json) helper function to load it:"
+    "A common, useful pattern used is to define this `config_list` is via JSON/YAML (specified as a file or an environment variable set to a JSON-formatted string) and then use the [`config_list_from_json`](/docs/reference/oai/openai_utils#config_list_from_json) helper function to load it:"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
   {
    "cell_type": "code",
    "execution_count": null,