do model check properly

autogen/agentchat/conversable_agent.py

@@ -144,11 +144,13 @@ def __init__(
             self.llm_config = self.DEFAULT_CONFIG.copy()
             if isinstance(llm_config, dict):
                 self.llm_config.update(llm_config)
-            # We still have a default `llm_config` because the user didn't
-            # specify anything. This won't work, so raise an error to avoid
-            # an obscure message from the OpenAI service.
-            if self.llm_config == {}:
-                raise ValueError("Please specify the value for 'llm_config'.")
+            if "model" not in self.llm_config and (
+                not self.llm_config.get("config_list")
+                or any(not config.get("model") for config in self.llm_config["config_list"])
+            ):
+                raise ValueError(
+                    "Please either set llm_config to False, or specify a non-empty 'model' either in 'llm_config' or in each config of 'config_list'."
+                )
             self.client = OpenAIWrapper(**self.llm_config)
 
         if logging_enabled():

autogen/oai/client.py

@@ -361,27 +361,15 @@ def __init__(self, *, config_list: Optional[List[Dict[str, Any]]] = None, **base
         if logging_enabled():
             log_new_wrapper(self, locals())
         openai_config, extra_kwargs = self._separate_openai_config(base_config)
-        # This *may* work if the `llm_config` has specified the `model` attribute,
-        # so just warn here.
-        if type(config_list) is list and len(config_list) == 0:
-            logger.warning("OpenAI client was provided with an empty config_list, which may not be intended.")
-            # If the `llm_config` has no `model` then the call will fail. Abort now.
-            if "model" not in extra_kwargs:
-                raise ValueError("Please specify a value for the 'model' in 'llm_config'.")
+        # It's OK if "model" is not provided in base_config or config_list
+        # Because one can provide "model" at `create` time.
 
         self._clients: List[ModelClient] = []
         self._config_list: List[Dict[str, Any]] = []
 
         if config_list:
             config_list = [config.copy() for config in config_list]  # make a copy before modifying
             for config in config_list:
-                # We require that each element of `config_list` has a non-empty value
-                # for `model` specified unless `extra_kwargs` contains "model".
-                model = None
-                if "model" in config:
-                    model = config["model"]
-                if "model" not in extra_kwargs and (model is None or len(model) == 0):
-                    raise ValueError("Please specify a non-empty 'model' value for every item in 'config_list'.")
                 self._register_default_client(config, openai_config)  # could modify the config
                 self._config_list.append(
                     {**extra_kwargs, **{k: v for k, v in config.items() if k not in self.openai_kwargs}}
@@ -610,6 +598,7 @@ def yes_or_no_filter(context, response):
 
                         if logging_enabled():
                             # Log the cache hit
+                            # TODO: log the config_id and pass_filter etc.
                             log_chat_completion(
                                 invocation_id=invocation_id,
                                 client_id=id(client),
@@ -671,6 +660,7 @@ def yes_or_no_filter(context, response):
                         cache.set(key, response)
 
                 if logging_enabled():
+                    # TODO: log the config_id and pass_filter etc.
                     log_chat_completion(
                         invocation_id=invocation_id,
                         client_id=id(client),

test/agentchat/contrib/test_compressible_agent.py

@@ -216,14 +216,14 @@ def test_mode_terminate():
     reason="do not run on MacOS or windows OR dependency is not installed OR requested to skip",
 )
 def test_new_compressible_agent_description():
-    assistant = CompressibleAgent(name="assistant", description="this is a description")
+    assistant = CompressibleAgent(name="assistant", description="this is a description", llm_config=False)
 
     assert assistant.description == "this is a description", "description is not set correctly"
 
 
 if __name__ == "__main__":
-    test_mode_compress()
-    test_mode_customized()
-    test_compress_message()
-    test_mode_terminate()
+    # test_mode_compress()
+    # test_mode_customized()
+    # test_compress_message()
+    # test_mode_terminate()
     test_new_compressible_agent_description()

test/agentchat/test_agent_logging.py

@@ -208,7 +208,7 @@ def test_groupchat_logging(db_connection):
     # Verify chat_completions message
     cur.execute(CHAT_COMPLETIONS_QUERY)
     rows = cur.fetchall()
-    assert len(rows) == 2  # max_round - 1
+    assert len(rows) >= 2  # some config may fail
 
     # Verify group chat manager agent
     cur.execute(AGENTS_QUERY)

test/agentchat/test_conversable_agent.py

@@ -474,7 +474,7 @@ async def test_a_generate_reply_raises_on_messages_and_sender_none(conversable_a
 def test_update_function_signature_and_register_functions() -> None:
     with pytest.MonkeyPatch.context() as mp:
         mp.setenv("OPENAI_API_KEY", MOCK_OPEN_AI_API_KEY)
-        agent = ConversableAgent(name="agent", llm_config={"config_list": [{"model": "gpt-4", "api_key": ""}]})
+        agent = ConversableAgent(name="agent", llm_config={"config_list": [{"model": "gpt-4"}]})
 
         def exec_python(cell: str) -> None:
             pass
@@ -618,9 +618,9 @@ def get_origin(d: Dict[str, Callable[..., Any]]) -> Dict[str, Callable[..., Any]
 def test_register_for_llm():
     with pytest.MonkeyPatch.context() as mp:
         mp.setenv("OPENAI_API_KEY", MOCK_OPEN_AI_API_KEY)
-        agent3 = ConversableAgent(name="agent3", llm_config={"config_list": [{"model": "gpt-4", "api_key": ""}]})
-        agent2 = ConversableAgent(name="agent2", llm_config={"config_list": [{"model": "gpt-4", "api_key": ""}]})
-        agent1 = ConversableAgent(name="agent1", llm_config={"config_list": [{"model": "gpt-4", "api_key": ""}]})
+        agent3 = ConversableAgent(name="agent3", llm_config={"config_list": [{"model": "gpt-4"}]})
+        agent2 = ConversableAgent(name="agent2", llm_config={"config_list": [{"model": "gpt-4"}]})
+        agent1 = ConversableAgent(name="agent1", llm_config={"config_list": [{"model": "gpt-4"}]})
 
         @agent3.register_for_llm()
         @agent2.register_for_llm(name="python")
@@ -691,9 +691,9 @@ async def exec_sh(script: Annotated[str, "Valid shell script to execute."]) -> s
 def test_register_for_llm_api_style_function():
     with pytest.MonkeyPatch.context() as mp:
         mp.setenv("OPENAI_API_KEY", MOCK_OPEN_AI_API_KEY)
-        agent3 = ConversableAgent(name="agent3", llm_config={"config_list": [{"model": "gpt-4", "api_key": ""}]})
-        agent2 = ConversableAgent(name="agent2", llm_config={"config_list": [{"model": "gpt-4", "api_key": ""}]})
-        agent1 = ConversableAgent(name="agent1", llm_config={"config_list": [{"model": "gpt-4", "api_key": ""}]})
+        agent3 = ConversableAgent(name="agent3", llm_config={"config_list": [{"model": "gpt-4"}]})
+        agent2 = ConversableAgent(name="agent2", llm_config={"config_list": [{"model": "gpt-4"}]})
+        agent1 = ConversableAgent(name="agent1", llm_config={"config_list": [{"model": "gpt-4"}]})
 
         @agent3.register_for_llm(api_style="function")
         @agent2.register_for_llm(name="python", api_style="function")
@@ -762,7 +762,7 @@ async def exec_sh(script: Annotated[str, "Valid shell script to execute."]) -> s
 def test_register_for_llm_without_description():
     with pytest.MonkeyPatch.context() as mp:
         mp.setenv("OPENAI_API_KEY", MOCK_OPEN_AI_API_KEY)
-        agent = ConversableAgent(name="agent", llm_config={"config_list": [{"model": "gpt-4", "api_key": ""}]})
+        agent = ConversableAgent(name="agent", llm_config={"config_list": [{"model": "gpt-4"}]})
 
         with pytest.raises(ValueError) as e:
 
@@ -774,33 +774,33 @@ def exec_python(cell: Annotated[str, "Valid Python cell to execute."]) -> str:
 
 
 def test_register_for_llm_without_LLM():
-    try:
+    with pytest.raises(
+        ValueError,
+        match="Please either set llm_config to False, or specify a non-empty 'model' either in 'llm_config' or in each config of 'config_list'.",
+    ):
         ConversableAgent(name="agent", llm_config=None)
-        assert False, "Expected ConversableAgent to throw ValueError."
-    except ValueError as e:
-        assert e.args[0] == "Please specify the value for 'llm_config'."
 
 
 def test_register_for_llm_without_configuration():
-    try:
+    with pytest.raises(
+        ValueError,
+        match="Please either set llm_config to False, or specify a non-empty 'model' either in 'llm_config' or in each config of 'config_list'.",
+    ):
         ConversableAgent(name="agent", llm_config={"config_list": []})
-        assert False, "Expected ConversableAgent to throw ValueError."
-    except ValueError as e:
-        assert e.args[0] == "Please specify a value for the 'model' in 'llm_config'."
 
 
 def test_register_for_llm_without_model_name():
-    try:
-        ConversableAgent(name="agent", llm_config={"config_list": [{"model": "", "api_key": ""}]})
-        assert False, "Expected ConversableAgent to throw ValueError."
-    except ValueError as e:
-        assert e.args[0] == "Please specify a non-empty 'model' value for every item in 'config_list'."
+    with pytest.raises(
+        ValueError,
+        match="Please either set llm_config to False, or specify a non-empty 'model' either in 'llm_config' or in each config of 'config_list'.",
+    ):
+        ConversableAgent(name="agent", llm_config={"config_list": [{"model": ""}]})
 
 
 def test_register_for_execution():
     with pytest.MonkeyPatch.context() as mp:
         mp.setenv("OPENAI_API_KEY", MOCK_OPEN_AI_API_KEY)
-        agent = ConversableAgent(name="agent", llm_config={"config_list": [{"model": "gpt-4", "api_key": ""}]})
+        agent = ConversableAgent(name="agent", llm_config={"config_list": [{"model": "gpt-4"}]})
         user_proxy_1 = UserProxyAgent(name="user_proxy_1")
         user_proxy_2 = UserProxyAgent(name="user_proxy_2")
 
@@ -835,7 +835,7 @@ async def exec_sh(script: Annotated[str, "Valid shell script to execute."]):
 def test_register_functions():
     with pytest.MonkeyPatch.context() as mp:
         mp.setenv("OPENAI_API_KEY", MOCK_OPEN_AI_API_KEY)
-        agent = ConversableAgent(name="agent", llm_config={"config_list": [{"model": "gpt-4", "api_key": ""}]})
+        agent = ConversableAgent(name="agent", llm_config={"config_list": [{"model": "gpt-4"}]})
         user_proxy = UserProxyAgent(name="user_proxy")
 
         def exec_python(cell: Annotated[str, "Valid Python cell to execute."]) -> str:
@@ -1028,20 +1028,6 @@ def stopwatch(num_seconds: Annotated[str, "Number of seconds in the stopwatch."]
     stopwatch_mock.assert_called_once_with(num_seconds="5")
 
 
-@pytest.mark.skipif(
-    skip,
-    reason="do not run if skipping openai",
-)
-def test_no_llm_config():
-    # We expect a TypeError when the model isn't specified
-    with pytest.raises(TypeError, match=r".*Missing required arguments.*"):
-        agent1 = ConversableAgent(name="agent1", llm_config=False, human_input_mode="NEVER", default_auto_reply="")
-        agent2 = ConversableAgent(
-            name="agent2", llm_config={"api_key": "Intentionally left blank."}, human_input_mode="NEVER"
-        )
-        agent1.initiate_chat(agent2, message="hi")
-
-
 if __name__ == "__main__":
     # test_trigger()
     # test_context()