Replace create_completion_client_from_env with component config (#4928)

* Replace create_completion_client_from_env with component config

* json load

python/packages/agbench/benchmarks/AssistantBench/Templates/MagenticOne/scenario.py

@@ -1,4 +1,5 @@
 import asyncio
+import json
 import logging
 import os
 import re
@@ -10,7 +11,7 @@ from typing import List
 
 from autogen_core import AgentId, AgentProxy, TopicId
 from autogen_core import SingleThreadedAgentRuntime
-from autogen_core.logging import EVENT_LOGGER_NAME
+from autogen_core import EVENT_LOGGER_NAME
 from autogen_core.models import (
     ChatCompletionClient,
     UserMessage,
@@ -26,7 +27,7 @@ from autogen_magentic_one.agents.orchestrator import LedgerOrchestrator
 from autogen_magentic_one.messages import BroadcastMessage
 from autogen_magentic_one.agents.multimodal_web_surfer import MultimodalWebSurfer
 from autogen_magentic_one.agents.file_surfer import FileSurfer
-from autogen_magentic_one.utils import LogHandler, message_content_to_str, create_completion_client_from_env
+from autogen_magentic_one.utils import LogHandler, message_content_to_str
 
 encoding = None
 def count_token(value: str) -> int:
@@ -123,10 +124,8 @@ async def main() -> None:
     runtime = SingleThreadedAgentRuntime()
 
     # Create the AzureOpenAI client from the environment file
-    client = create_completion_client_from_env()
-
-
-    mlm_client = create_completion_client_from_env()
+    client = ChatCompletionClient.load_component(json.loads(os.environ["CHAT_COMPLETION_CLIENT_CONFIG"]))
+    mlm_client = ChatCompletionClient.load_component(json.loads(os.environ["MLM_CHAT_COMPLETION_CLIENT_CONFIG"]))
 
 
     # Register agents.

python/packages/agbench/benchmarks/GAIA/Templates/MagenticOne/scenario.py

@@ -1,4 +1,5 @@
 import asyncio
+import json
 import logging
 import os
 import re
@@ -27,7 +28,7 @@ from autogen_magentic_one.agents.orchestrator import LedgerOrchestrator
 from autogen_magentic_one.messages import BroadcastMessage
 from autogen_magentic_one.agents.multimodal_web_surfer import MultimodalWebSurfer
 from autogen_magentic_one.agents.file_surfer import FileSurfer
-from autogen_magentic_one.utils import LogHandler, message_content_to_str, create_completion_client_from_env
+from autogen_magentic_one.utils import LogHandler, message_content_to_str
 
 encoding = None
 def count_token(value: str) -> int:
@@ -124,11 +125,10 @@ async def main() -> None:
     runtime = SingleThreadedAgentRuntime()
 
     # Create the AzureOpenAI client, with AAD auth, from environment
-    client = create_completion_client_from_env()
+    client = ChatCompletionClient.load_component(json.loads(os.environ["CHAT_COMPLETION_CLIENT_CONFIG"]))
+    mlm_client = ChatCompletionClient.load_component(json.loads(os.environ["MLM_CHAT_COMPLETION_CLIENT_CONFIG"]))
 
 
-    mlm_client = create_completion_client_from_env()
-
     # Register agents.
     await runtime.register(
         "Assistant",

python/packages/agbench/benchmarks/HumanEval/Templates/MagenticOne/scenario.py

@@ -13,7 +13,6 @@ from autogen_core.models import (
 from autogen_magentic_one.agents.coder import Coder, Executor
 from autogen_magentic_one.agents.orchestrator import RoundRobinOrchestrator
 from autogen_magentic_one.messages import BroadcastMessage, OrchestrationEvent
-from autogen_magentic_one.utils import create_completion_client_from_env
 
 
 async def main() -> None:
@@ -21,7 +20,8 @@ async def main() -> None:
     runtime = SingleThreadedAgentRuntime()
 
     # Create the AzureOpenAI client
-    client = create_completion_client_from_env()
+    client = ChatCompletionClient.load_component(json.loads(os.environ["CHAT_COMPLETION_CLIENT_CONFIG"]))
+
 
     # Register agents.
     await runtime.register(

python/packages/agbench/benchmarks/WebArena/Templates/MagenticOne/scenario.py

@@ -24,7 +24,7 @@ from autogen_magentic_one.agents.orchestrator import RoundRobinOrchestrator, Led
 from autogen_magentic_one.messages import BroadcastMessage, OrchestrationEvent, RequestReplyMessage, ResetMessage, DeactivateMessage
 from autogen_magentic_one.agents.multimodal_web_surfer import MultimodalWebSurfer
 from autogen_magentic_one.agents.file_surfer import FileSurfer
-from autogen_magentic_one.utils import LogHandler, message_content_to_str, create_completion_client_from_env
+from autogen_magentic_one.utils import LogHandler, message_content_to_str
 
 
 import evaluation_harness
@@ -120,7 +120,8 @@ async def main() -> None:
     runtime = SingleThreadedAgentRuntime()
 
     # Create the AzureOpenAI client, with AAD auth
-    client = create_completion_client_from_env()
+    client = ChatCompletionClient.load_component(json.loads(os.environ["CHAT_COMPLETION_CLIENT_CONFIG"]))
+
     # Login assistant
     await runtime.register(
         "LoginAssistant",

python/packages/autogen-magentic-one/README.md

@@ -119,28 +119,39 @@ playwright install --with-deps chromium
 
 ## Environment Configuration for Chat Completion Client
 
-This guide outlines how to configure your environment to use the `create_completion_client_from_env` function, which reads environment variables to return an appropriate `ChatCompletionClient`.
+This guide outlines how to structure the config to load a ChatCompletionClient for Magentic-One.
+
+```python
+from autogen_core.models import ChatCompletionClient
+
+config = {}
+client = ChatCompletionClient.load_component(config)
+```
 
 Currently, Magentic-One only supports OpenAI's GPT-4o as the underlying LLM.
 
 ### Azure OpenAI service
 
-To configure for Azure OpenAI service, set the following environment variables:
-
-- `CHAT_COMPLETION_PROVIDER='azure'`
-- `CHAT_COMPLETION_KWARGS_JSON` with the following JSON structure:
+To configure for Azure OpenAI service, use the following config:
 
 ```json
 {
-  "api_version": "2024-02-15-preview",
-  "azure_endpoint": "REPLACE_WITH_YOUR_ENDPOINT",
-  "model_capabilities": {
-    "function_calling": true,
-    "json_output": true,
-    "vision": true
-  },
-  "azure_ad_token_provider": "DEFAULT",
-  "model": "gpt-4o-2024-05-13"
+    "provider": "AzureOpenAIChatCompletionClient",
+    "config": {
+        "model": "gpt-4o-2024-05-13",
+        "azure_endpoint": "https://{your-custom-endpoint}.openai.azure.com/",
+        "azure_deployment": "{your-azure-deployment}",
+        "api_version": "2024-06-01",
+        "azure_ad_token_provider": {
+            "provider": "autogen_ext.models.openai.AzureTokenProvider",
+            "config": {
+                "provider_kind": "DefaultAzureCredential",
+                "scopes": [
+                    "https://cognitiveservices.azure.com/.default"
+                ]
+            }
+        }
+    }
 }
 ```
 
@@ -150,19 +161,34 @@ Log in to Azure using `az login`, and then run the examples. The account used mu
 
 Note that even if you are the owner of the subscription, you still need to grant the necessary Azure Cognitive Services OpenAI permissions to call the API.
 
+Or, to use an API key:
+```json
+{
+    "provider": "AzureOpenAIChatCompletionClient",
+    "config": {
+        "model": "gpt-4o-2024-05-13",
+        "azure_endpoint": "https://{your-custom-endpoint}.openai.azure.com/",
+        "azure_deployment": "{your-azure-deployment}",
+        "api_version": "2024-06-01",
+        "api_key": "REPLACE_WITH_YOUR_API_KEY"
+    }
+}
+```
+
 ### With OpenAI
 
-To configure for OpenAI, set the following environment variables:
-
-- `CHAT_COMPLETION_PROVIDER='openai'`
-- `CHAT_COMPLETION_KWARGS_JSON` with the following JSON structure:
+To configure for OpenAI, use the following config:
 
 ```json
 {
-  "api_key": "REPLACE_WITH_YOUR_API",
-  "model": "gpt-4o-2024-05-13"
+  "provider": "OpenAIChatCompletionClient",
+  "config": {
+      "model": "gpt-4o-2024-05-13",
+      "api_key": "REPLACE_WITH_YOUR_API_KEY"
+  }
 }
 ```
+
 Feel free to replace the model with newer versions of gpt-4o if needed.
 
 ### Other Keys (Optional)

python/packages/autogen-magentic-one/examples/example.py

@@ -2,11 +2,13 @@
 
 import argparse
 import asyncio
+import json
 import logging
 import os
 
 from autogen_core import EVENT_LOGGER_NAME, AgentId, AgentProxy, SingleThreadedAgentRuntime
 from autogen_core.code_executor import CodeBlock
+from autogen_core.models._model_client import ChatCompletionClient
 from autogen_ext.code_executors.docker import DockerCommandLineCodeExecutor
 from autogen_magentic_one.agents.coder import Coder, Executor
 from autogen_magentic_one.agents.file_surfer import FileSurfer
@@ -14,7 +16,7 @@ from autogen_magentic_one.agents.multimodal_web_surfer import MultimodalWebSurfe
 from autogen_magentic_one.agents.orchestrator import LedgerOrchestrator
 from autogen_magentic_one.agents.user_proxy import UserProxy
 from autogen_magentic_one.messages import RequestReplyMessage
-from autogen_magentic_one.utils import LogHandler, create_completion_client_from_env
+from autogen_magentic_one.utils import LogHandler
 
 # NOTE: Don't forget to 'playwright install --with-deps chromium'
 
@@ -32,7 +34,8 @@ async def main(logs_dir: str, hil_mode: bool, save_screenshots: bool) -> None:
     runtime = SingleThreadedAgentRuntime()
 
     # Create an appropriate client
-    client = create_completion_client_from_env(model="gpt-4o")
+    client = ChatCompletionClient.load_component(json.loads(os.environ["CHAT_COMPLETION_CLIENT_CONFIG"]))
+    assert client.model_info["family"] == "gpt-4o", "This example requires the gpt-4o model"
 
     async with DockerCommandLineCodeExecutor(work_dir=logs_dir) as code_executor:
         # Register agents.

python/packages/autogen-magentic-one/examples/example_coder.py

@@ -5,16 +5,19 @@ round-robin orchestrator agent. The code snippets are executed inside a docker c
 """
 
 import asyncio
+import json
 import logging
+import os
 
 from autogen_core import EVENT_LOGGER_NAME, AgentId, AgentProxy, SingleThreadedAgentRuntime
 from autogen_core.code_executor import CodeBlock
+from autogen_core.models._model_client import ChatCompletionClient
 from autogen_ext.code_executors.docker import DockerCommandLineCodeExecutor
 from autogen_magentic_one.agents.coder import Coder, Executor
 from autogen_magentic_one.agents.orchestrator import RoundRobinOrchestrator
 from autogen_magentic_one.agents.user_proxy import UserProxy
 from autogen_magentic_one.messages import RequestReplyMessage
-from autogen_magentic_one.utils import LogHandler, create_completion_client_from_env
+from autogen_magentic_one.utils import LogHandler
 
 
 async def confirm_code(code: CodeBlock) -> bool:
@@ -29,9 +32,10 @@ async def main() -> None:
     # Create the runtime.
     runtime = SingleThreadedAgentRuntime()
 
+    model_client = ChatCompletionClient.load_component(json.loads(os.environ["CHAT_COMPLETION_CLIENT_CONFIG"]))
     async with DockerCommandLineCodeExecutor() as code_executor:
         # Register agents.
-        await Coder.register(runtime, "Coder", lambda: Coder(model_client=create_completion_client_from_env()))
+        await Coder.register(runtime, "Coder", lambda: Coder(model_client=model_client))
         coder = AgentProxy(AgentId("Coder", "default"), runtime)
 
         await Executor.register(

python/packages/autogen-magentic-one/examples/example_file_surfer.py

@@ -3,14 +3,17 @@ to navigate the file system. The human user and the file surfer agent takes turn
 to write input or perform actions, orchestrated by an round-robin orchestrator agent."""
 
 import asyncio
+import json
 import logging
+import os
 
 from autogen_core import EVENT_LOGGER_NAME, AgentId, AgentProxy, SingleThreadedAgentRuntime
+from autogen_core.models._model_client import ChatCompletionClient
 from autogen_magentic_one.agents.file_surfer import FileSurfer
 from autogen_magentic_one.agents.orchestrator import RoundRobinOrchestrator
 from autogen_magentic_one.agents.user_proxy import UserProxy
 from autogen_magentic_one.messages import RequestReplyMessage
-from autogen_magentic_one.utils import LogHandler, create_completion_client_from_env
+from autogen_magentic_one.utils import LogHandler
 
 
 async def main() -> None:
@@ -18,7 +21,7 @@ async def main() -> None:
     runtime = SingleThreadedAgentRuntime()
 
     # Get an appropriate client
-    client = create_completion_client_from_env()
+    client = ChatCompletionClient.load_component(json.loads(os.environ["CHAT_COMPLETION_CLIENT_CONFIG"]))
 
     # Register agents.
     await FileSurfer.register(runtime, "file_surfer", lambda: FileSurfer(model_client=client))

python/packages/autogen-magentic-one/examples/example_userproxy.py

@@ -5,16 +5,19 @@ round-robin orchestrator agent.
 The code snippets are not executed in this example."""
 
 import asyncio
+import json
 import logging
+import os
 
 from autogen_core import EVENT_LOGGER_NAME, AgentId, AgentProxy, SingleThreadedAgentRuntime
 
 # from typing import Any, Dict, List, Tuple, Union
+from autogen_core.models._model_client import ChatCompletionClient
 from autogen_magentic_one.agents.coder import Coder
 from autogen_magentic_one.agents.orchestrator import RoundRobinOrchestrator
 from autogen_magentic_one.agents.user_proxy import UserProxy
 from autogen_magentic_one.messages import RequestReplyMessage
-from autogen_magentic_one.utils import LogHandler, create_completion_client_from_env
+from autogen_magentic_one.utils import LogHandler
 
 
 async def main() -> None:
@@ -22,7 +25,7 @@ async def main() -> None:
     runtime = SingleThreadedAgentRuntime()
 
     # Get an appropriate client
-    client = create_completion_client_from_env()
+    client = ChatCompletionClient.load_component(json.loads(os.environ["CHAT_COMPLETION_CLIENT_CONFIG"]))
 
     # Register agents.
     await Coder.register(runtime, "Coder", lambda: Coder(model_client=client))

python/packages/autogen-magentic-one/examples/example_websurfer.py

@@ -4,15 +4,17 @@ The human user and the web surfer agent takes turn to write input or perform act
 orchestrated by an round-robin orchestrator agent."""
 
 import asyncio
+import json
 import logging
 import os
 
 from autogen_core import EVENT_LOGGER_NAME, AgentId, AgentProxy, SingleThreadedAgentRuntime
+from autogen_core.models import ChatCompletionClient
 from autogen_magentic_one.agents.multimodal_web_surfer import MultimodalWebSurfer
 from autogen_magentic_one.agents.orchestrator import RoundRobinOrchestrator
 from autogen_magentic_one.agents.user_proxy import UserProxy
 from autogen_magentic_one.messages import RequestReplyMessage
-from autogen_magentic_one.utils import LogHandler, create_completion_client_from_env
+from autogen_magentic_one.utils import LogHandler
 
 # NOTE: Don't forget to 'playwright install --with-deps chromium'
 
@@ -22,7 +24,8 @@ async def main() -> None:
     runtime = SingleThreadedAgentRuntime()
 
     # Create an appropriate client
-    client = create_completion_client_from_env(model="gpt-4o")
+    client = ChatCompletionClient.load_component(json.loads(os.environ["CHAT_COMPLETION_CLIENT_CONFIG"]))
+    assert client.model_info["family"] == "gpt-4o", "This example requires the gpt-4o model"
 
     # Register agents.
     await MultimodalWebSurfer.register(runtime, "WebSurfer", MultimodalWebSurfer)

python/packages/autogen-magentic-one/interface/magentic_one_helper.py

@@ -10,6 +10,7 @@ from autogen_core import SingleThreadedAgentRuntime
 from autogen_core import EVENT_LOGGER_NAME
 from autogen_core import AgentId, AgentProxy
 from autogen_core import DefaultTopicId
+from autogen_core.models._model_client import ChatCompletionClient
 from autogen_ext.code_executors.local import LocalCommandLineCodeExecutor
 from autogen_ext.code_executors.docker import DockerCommandLineCodeExecutor
 from autogen_core.code_executor import CodeBlock
@@ -19,7 +20,7 @@ from autogen_magentic_one.agents.multimodal_web_surfer import MultimodalWebSurfe
 from autogen_magentic_one.agents.orchestrator import LedgerOrchestrator
 from autogen_magentic_one.agents.user_proxy import UserProxy
 from autogen_magentic_one.messages import BroadcastMessage
-from autogen_magentic_one.utils import LogHandler, create_completion_client_from_env
+from autogen_magentic_one.utils import LogHandler
 from autogen_core.models import UserMessage
 from threading import Lock
 
@@ -60,7 +61,9 @@ class MagenticOneHelper:
         logger.handlers = [self.log_handler]
 
         # Create client
-        client = create_completion_client_from_env(model="gpt-4o")
+        client = ChatCompletionClient.load_component(json.loads(os.environ["CHAT_COMPLETION_CLIENT_CONFIG"]))
+        assert client.model_info["family"] == "gpt-4o", "This example requires the gpt-4o model"
+
 
         # Set up code executor
         self.code_executor = DockerCommandLineCodeExecutor(work_dir=self.logs_dir)

python/packages/autogen-magentic-one/src/autogen_magentic_one/utils.py

@@ -1,17 +1,11 @@
 import json
 import logging
-import os
 from dataclasses import asdict
 from datetime import datetime
 from typing import Any, Dict, List, Literal
 
 from autogen_core import Image
 from autogen_core.logging import LLMCallEvent
-from autogen_core.models import (
-    ChatCompletionClient,
-    ModelCapabilities,  # type: ignore
-)
-from autogen_ext.models.openai import AzureOpenAIChatCompletionClient, OpenAIChatCompletionClient
 
 from .messages import (
     AgentEvent,
@@ -23,62 +17,6 @@ from .messages import (
     WebSurferEvent,
 )
 
-ENVIRON_KEY_CHAT_COMPLETION_PROVIDER = "CHAT_COMPLETION_PROVIDER"
-ENVIRON_KEY_CHAT_COMPLETION_KWARGS_JSON = "CHAT_COMPLETION_KWARGS_JSON"
-
-# The singleton _default_azure_ad_token_provider, which will be created if needed
-_default_azure_ad_token_provider = None
-
-
-# Create a model client based on information provided in environment variables.
-def create_completion_client_from_env(env: Dict[str, str] | None = None, **kwargs: Any) -> ChatCompletionClient:
-    global _default_azure_ad_token_provider
-
-    """
-    Create a model client based on information provided in environment variables.
-        env (Optional):     When provied, read from this dictionary rather than os.environ
-        kwargs**:           ChatClient arguments to override (e.g., model)
-
-    NOTE: If 'azure_ad_token_provider' is included, and euquals the string 'DEFAULT' then replace it with
-          azure.identity.get_bearer_token_provider(DefaultAzureCredential(), "https://cognitiveservices.azure.com/.default")
-    """
-
-    # If a dictionary was not provided, load it from the environment
-    if env is None:
-        env = dict()
-        env.update(os.environ)
-
-    # Load the kwargs, and override with provided kwargs
-    _kwargs = json.loads(env.get(ENVIRON_KEY_CHAT_COMPLETION_KWARGS_JSON, "{}"))
-    _kwargs.update(kwargs)
-
-    # If model capabilities were provided, deserialize them as well
-    if "model_capabilities" in _kwargs:
-        _kwargs["model_capabilities"] = ModelCapabilities(  # type: ignore
-            vision=_kwargs["model_capabilities"].get("vision"),
-            function_calling=_kwargs["model_capabilities"].get("function_calling"),
-            json_output=_kwargs["model_capabilities"].get("json_output"),
-        )
-
-    # Figure out what provider we are using. Default to OpenAI
-    _provider = env.get(ENVIRON_KEY_CHAT_COMPLETION_PROVIDER, "openai").lower().strip()
-
-    # Instantiate the correct client
-    if _provider == "openai":
-        return OpenAIChatCompletionClient(**_kwargs)  # type: ignore
-    elif _provider == "azure":
-        if _kwargs.get("azure_ad_token_provider", "").lower() == "default":
-            if _default_azure_ad_token_provider is None:
-                from azure.identity import DefaultAzureCredential, get_bearer_token_provider
-
-                _default_azure_ad_token_provider = get_bearer_token_provider(
-                    DefaultAzureCredential(), "https://cognitiveservices.azure.com/.default"
-                )
-            _kwargs["azure_ad_token_provider"] = _default_azure_ad_token_provider
-        return AzureOpenAIChatCompletionClient(**_kwargs)  # type: ignore
-    else:
-        raise ValueError(f"Unknown OAI provider '{_provider}'")
-
 
 # Convert UserContent to a string
 def message_content_to_str(

python/packages/autogen-magentic-one/tests/headless_web_surfer/test_web_surfer.py

@@ -1,6 +1,7 @@
 #!/usr/bin/env python3 -m pytest
 
 import asyncio
+import json
 import os
 import re
 from json import dumps
@@ -12,6 +13,7 @@ from autogen_core import AgentId, AgentProxy, FunctionCall, SingleThreadedAgentR
 from autogen_core.models import (
     UserMessage,
 )
+from autogen_core.models._model_client import ChatCompletionClient
 from autogen_core.tools._base import ToolSchema
 from autogen_magentic_one.agents.multimodal_web_surfer import MultimodalWebSurfer
 from autogen_magentic_one.agents.multimodal_web_surfer.tool_definitions import (
@@ -25,11 +27,6 @@ from autogen_magentic_one.agents.multimodal_web_surfer.tool_definitions import (
 from autogen_magentic_one.agents.orchestrator import RoundRobinOrchestrator
 from autogen_magentic_one.agents.user_proxy import UserProxy
 from autogen_magentic_one.messages import BroadcastMessage
-from autogen_magentic_one.utils import (
-    ENVIRON_KEY_CHAT_COMPLETION_KWARGS_JSON,
-    ENVIRON_KEY_CHAT_COMPLETION_PROVIDER,
-    create_completion_client_from_env,
-)
 from conftest import MOCK_CHAT_COMPLETION_KWARGS, reason
 from openai import AuthenticationError
 
@@ -57,7 +54,7 @@ skip_all = False
 # Search currently does not require an API key
 skip_bing = False
 
-if os.getenv(ENVIRON_KEY_CHAT_COMPLETION_KWARGS_JSON):
+if os.getenv("CHAT_COMPLETION_CLIENT_CONFIG"):
     skip_openai = False
 else:
     skip_openai = True
@@ -99,14 +96,10 @@ async def make_browser_request(browser: MultimodalWebSurfer, tool: ToolSchema, a
 @pytest.mark.skip(reason="Need to fix this test to use a local website instead of a public one.")
 @pytest.mark.asyncio
 async def test_web_surfer() -> None:
-    env = {
-        ENVIRON_KEY_CHAT_COMPLETION_PROVIDER: "openai",
-        ENVIRON_KEY_CHAT_COMPLETION_KWARGS_JSON: MOCK_CHAT_COMPLETION_KWARGS,
-    }
-
     runtime = SingleThreadedAgentRuntime()
     # Create an appropriate client
-    client = create_completion_client_from_env(env)
+    config = {"provider": "OpenAIChatCompletionClient", "config": json.loads(MOCK_CHAT_COMPLETION_KWARGS)}
+    client = ChatCompletionClient.load_component(config)
 
     # Register agents.
 
@@ -183,7 +176,7 @@ async def test_web_surfer_oai() -> None:
     runtime = SingleThreadedAgentRuntime()
 
     # Create an appropriate client
-    client = create_completion_client_from_env()
+    client = ChatCompletionClient.load_component(json.loads(os.environ["CHAT_COMPLETION_CLIENT_CONFIG"]))
 
     # Register agents.
     await MultimodalWebSurfer.register(
@@ -247,14 +240,10 @@ async def test_web_surfer_oai() -> None:
 )
 @pytest.mark.asyncio
 async def test_web_surfer_bing() -> None:
-    env = {
-        ENVIRON_KEY_CHAT_COMPLETION_PROVIDER: "openai",
-        ENVIRON_KEY_CHAT_COMPLETION_KWARGS_JSON: MOCK_CHAT_COMPLETION_KWARGS,
-    }
-
     runtime = SingleThreadedAgentRuntime()
     # Create an appropriate client
-    client = create_completion_client_from_env(env)
+    config = {"provider": "OpenAIChatCompletionClient", "config": json.loads(MOCK_CHAT_COMPLETION_KWARGS)}
+    client = ChatCompletionClient.load_component(config)
 
     # Register agents.
     await MultimodalWebSurfer.register(