[api] Specify model in ChatModelSetup (Java + Python)

integrations/chat-models/ollama/src/main/java/org/apache/flink/agents/integrations/chatmodels/ollama/OllamaChatModelSetup.java

@@ -53,13 +53,11 @@
  */
 public class OllamaChatModelSetup extends BaseChatModelSetup {
 
-    private final String model;
     private final Object think;
     private final boolean extractReasoning;
 
     public OllamaChatModelSetup(ResourceDescriptor descriptor, ResourceContext resourceContext) {
         super(descriptor, resourceContext);
-        this.model = descriptor.getArgument("model");
         this.think = descriptor.getArgument("think", true);
         this.extractReasoning = descriptor.getArgument("extract_reasoning", true);
     }

integrations/chat-models/ollama/src/test/java/org/apache/flink/agents/integrations/chatmodels/ollama/OllamaChatModelSetupTest.java

@@ -0,0 +1,55 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.flink.agents.integrations.chatmodels.ollama;
+
+import org.apache.flink.agents.api.resource.ResourceContext;
+import org.apache.flink.agents.api.resource.ResourceDescriptor;
+import org.junit.jupiter.api.Test;
+
+import static org.assertj.core.api.Assertions.assertThat;
+
+/** Tests for {@link OllamaChatModelSetup}. */
+class OllamaChatModelSetupTest {
+
+    private static final ResourceContext NOOP = ResourceContext.fromGetResource((a, b) -> null);
+
+    @Test
+    void getModel_returnsValueFromDescriptor() {
+        ResourceDescriptor desc =
+                ResourceDescriptor.Builder.newBuilder(OllamaChatModelSetup.class.getName())
+                        .addInitialArgument("connection", "dummy-connection")
+                        .addInitialArgument("model", "qwen3:4b")
+                        .build();
+        OllamaChatModelSetup setup = new OllamaChatModelSetup(desc, NOOP);
+
+        assertThat(setup.getModel()).isEqualTo("qwen3:4b");
+    }
+
+    @Test
+    void getParameters_includesModelFromDescriptor() {
+        ResourceDescriptor desc =
+                ResourceDescriptor.Builder.newBuilder(OllamaChatModelSetup.class.getName())
+                        .addInitialArgument("connection", "dummy-connection")
+                        .addInitialArgument("model", "qwen3:4b")
+                        .build();
+        OllamaChatModelSetup setup = new OllamaChatModelSetup(desc, NOOP);
+
+        assertThat(setup.getParameters()).containsEntry("model", "qwen3:4b");
+    }
+}

plan/src/test/java/org/apache/flink/agents/plan/compatibility/CreateJavaAgentPlanFromJson.java

@@ -144,6 +144,8 @@ public static void main(String[] args) throws IOException {
         kwargs.put("name", "chat_model");
         kwargs.put("prompt", "prompt");
         kwargs.put("tools", List.of("add"));
+        kwargs.put("connection", "mock_connection");
+        kwargs.put("model", "mock-model");
         ResourceDescriptor chatModelDescriptor =
                 new ResourceDescriptor(
                         "flink_agents.plan.tests.compatibility.python_agent_plan_compatibility_test_agent",

python/flink_agents/api/agents/react_agent.py

@@ -91,6 +91,7 @@ class OutputData(BaseModel):
                 chat_model=ResourceDescriptor(
                     clazz=OllamaChatModelSetup,
                     connection="ollama_server",
+                    model="qwen3:8b",
                     tools=["notify_shipping_manager"],
                 ),
                 prompt=prompt,

python/flink_agents/api/chat_models/chat_model.py

@@ -131,6 +131,8 @@ class BaseChatModelSetup(Resource):
     """Base abstract class for chat model setup.
 
     Responsible for managing chat configurations, such as:
+    - Connection to chat model service (connection)
+    - Model name (model)
     - Prompt templates (prompt)
     - Available tools (tools)
     - Generation parameters (temperature, max_tokens, etc.)
@@ -143,6 +145,7 @@ class BaseChatModelSetup(Resource):
     """
 
     connection: str = Field(description="The referenced connection name.")
+    model: str = Field(description="Name of the chat model to use.")
     _resolved_connection: BaseChatModelConnection | None = PrivateAttr(default=None)
     prompt: Prompt | str | None = None
     tools: List[str] | List[Tool] = Field(default_factory=list)

python/flink_agents/api/chat_models/tests/test_chat_model_base.py

@@ -0,0 +1,47 @@
+################################################################################
+#  Licensed to the Apache Software Foundation (ASF) under one
+#  or more contributor license agreements.  See the NOTICE file
+#  distributed with this work for additional information
+#  regarding copyright ownership.  The ASF licenses this file
+#  to you under the Apache License, Version 2.0 (the
+#  "License"); you may not use this file except in compliance
+#  with the License.  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+# limitations under the License.
+#################################################################################
+from typing import Any, Dict
+
+import pytest
+from pydantic import ValidationError
+
+from flink_agents.api.chat_models.chat_model import BaseChatModelSetup
+
+
+class _MinimalChatModelSetup(BaseChatModelSetup):
+    """Minimal subclass that omits the `model` field declaration.
+
+    Used to assert the `model` field is inherited from `BaseChatModelSetup`.
+    """
+
+    @property
+    def model_kwargs(self) -> Dict[str, Any]:
+        """Return chat model settings derived from the inherited `model` field."""
+        return {"model": self.model}
+
+
+def test_inherits_model_field_from_base() -> None:
+    """A subclass that omits `model` still exposes it via inheritance."""
+    setup = _MinimalChatModelSetup(connection="c", model="m1")
+    assert setup.model == "m1"
+
+
+def test_missing_model_raises_validation_error() -> None:
+    """Constructing without `model` must raise a Pydantic ValidationError."""
+    with pytest.raises(ValidationError):
+        _MinimalChatModelSetup(connection="c")

python/flink_agents/api/chat_models/tests/test_token_metrics.py

@@ -100,7 +100,7 @@ class TestBaseChatModelTokenMetrics:
 
     def test_record_token_metrics_with_metric_group(self) -> None:
         """Test token metrics are recorded when metric group is set."""
-        chat_model = TestChatModelSetup(connection="mock")
+        chat_model = TestChatModelSetup(connection="mock", model="mock-model")
         mock_metric_group = _MockMetricGroup()
 
         # Set the metric group
@@ -116,7 +116,7 @@ def test_record_token_metrics_with_metric_group(self) -> None:
 
     def test_record_token_metrics_without_metric_group(self) -> None:
         """Test token metrics are not recorded when metric group is null."""
-        chat_model = TestChatModelSetup(connection="mock")
+        chat_model = TestChatModelSetup(connection="mock", model="mock-model")
 
         # Do not set metric group (should be None by default)
         # Record token metrics - should not throw
@@ -125,7 +125,7 @@ def test_record_token_metrics_without_metric_group(self) -> None:
 
     def test_token_metrics_hierarchy(self) -> None:
         """Test token metrics hierarchy: actionMetricGroup -> modelName -> counters."""
-        chat_model = TestChatModelSetup(connection="mock")
+        chat_model = TestChatModelSetup(connection="mock", model="mock-model")
         mock_metric_group = _MockMetricGroup()
 
         # Set the metric group
@@ -148,7 +148,7 @@ def test_token_metrics_hierarchy(self) -> None:
 
     def test_token_metrics_accumulation(self) -> None:
         """Test that token metrics accumulate across multiple calls."""
-        chat_model = TestChatModelSetup(connection="mock")
+        chat_model = TestChatModelSetup(connection="mock", model="mock-model")
         mock_metric_group = _MockMetricGroup()
 
         # Set the metric group
@@ -165,12 +165,12 @@ def test_token_metrics_accumulation(self) -> None:
 
     def test_resource_type(self) -> None:
         """Test resource type is CHAT_MODEL_CONNECTION."""
-        chat_model = TestChatModelSetup(connection="mock")
+        chat_model = TestChatModelSetup(connection="mock", model="mock-model")
         assert chat_model.resource_type() == ResourceType.CHAT_MODEL
 
     def test_bound_metric_group_property(self) -> None:
         """Test bound_metric_group property."""
-        chat_model = TestChatModelSetup(connection="mock")
+        chat_model = TestChatModelSetup(connection="mock", model="mock-model")
 
         # Initially should be None
         assert chat_model.metric_group is None

python/flink_agents/e2e_tests/e2e_tests_integration/built_in_action_async_execution_test.py

@@ -72,6 +72,7 @@ def slow_chat_model() -> ResourceDescriptor:
         return ResourceDescriptor(
             clazz=f"{SlowMockChatModel.__module__}.{SlowMockChatModel.__name__}",
             connection="placement",
+            model="slow-mock-model",
             tools=["add"],
         )
 

python/flink_agents/integrations/chat_models/anthropic/anthropic_chat_model.py

@@ -246,23 +246,19 @@ class AnthropicChatModelSetup(BaseChatModelSetup):
     ----------
     connection : str
         Name of the referenced connection. (Inherited from BaseChatModelSetup)
+    model : str
+        Specifies the Anthropic model to use. Defaults to claude-sonnet-4-20250514
+        when omitted via ``__init__``. (Inherited from BaseChatModelSetup)
     prompt : Optional[Union[Prompt, str]
         Prompt template or string for the model. (Inherited from BaseChatModelSetup)
     tools : Optional[List[str]]
         List of available tools to use in the chat. (Inherited from BaseChatModelSetup)
-    model : str
-        Specifies the Anthropic model to use. Defaults to claude-sonnet-4-20250514.
     max_tokens: int
         The maximum number of tokens to generate before stopping. Defaults to 1024.
     temperature : float
         Amount of randomness injected into the response.
     """
 
-    model: str = Field(
-        default=DEFAULT_ANTHROPIC_MODEL,
-        description="Specifies the Anthropic model to use. Defaults to "
-        "claude-sonnet-4-20250514.",
-    )
     max_tokens: int = Field(
         default=DEFAULT_MAX_TOKENS,
         description="The maximum number of tokens to generate before stopping. Defaults to 1024.",

python/flink_agents/integrations/chat_models/anthropic/tests/test_anthropic_chat_model.py

@@ -24,6 +24,7 @@
 from flink_agents.api.resource import Resource, ResourceType
 from flink_agents.api.resource_context import ResourceContext
 from flink_agents.integrations.chat_models.anthropic.anthropic_chat_model import (
+    DEFAULT_ANTHROPIC_MODEL,
     AnthropicChatModelConnection,
     AnthropicChatModelSetup,
 )
@@ -103,3 +104,16 @@ def get_resource(name: str, type: ResourceType) -> Resource:
     tool_call = tool_calls[0]
     assert add(**tool_call["function"]["arguments"]) == 2
     assert tool_call.get("original_id") is not None
+
+
+def test_model_field_roundtrip() -> None:
+    """Verify `model` is preserved through pydantic dump/validate round-trip."""
+    setup = AnthropicChatModelSetup(connection="conn", model="test-model")
+    restored = AnthropicChatModelSetup.model_validate(setup.model_dump())
+    assert restored.model == "test-model"
+
+
+def test_default_model_when_omitted() -> None:
+    """Verify per-integration default applies when `model` is omitted from __init__."""
+    setup = AnthropicChatModelSetup(connection="conn")
+    assert setup.model == DEFAULT_ANTHROPIC_MODEL

python/flink_agents/integrations/chat_models/azure/azure_openai_chat_model.py

@@ -167,12 +167,12 @@ class AzureOpenAIChatModelSetup(BaseChatModelSetup):
     ----------
     connection : str
         Name of the referenced connection. (Inherited from BaseChatModelSetup)
+    model : str
+        Name of OpenAI model deployment on Azure. (Inherited from BaseChatModelSetup)
     prompt : Optional[Union[Prompt, str]
         Prompt template or string for the model. (Inherited from BaseChatModelSetup)
     tools : Optional[List[str]]
         List of available tools to use in the chat. (Inherited from BaseChatModelSetup)
-    model : str
-        Name of OpenAI model deployment on Azure.
     model_of_azure_deployment : Optional[str]
         The underlying model name of the Azure deployment (e.g., 'gpt-4').
         Used for token counting and cost calculation.
@@ -193,9 +193,6 @@ class AzureOpenAIChatModelSetup(BaseChatModelSetup):
         Additional kwargs for the Azure OpenAI API.
     """
 
-    model: str = Field(
-        description="Name of OpenAI model deployment on Azure.",
-    )
     model_of_azure_deployment: str | None = Field(
         default=None,
         description="The underlying model name of the Azure deployment (e.g., 'gpt-4', "

python/flink_agents/integrations/chat_models/azure/tests/test_azure_openai_chat_model.py

@@ -119,3 +119,10 @@ def get_resource(name: str, type: ResourceType) -> Resource:
     assert len(tool_calls) == 1
     tool_call = tool_calls[0]
     assert add(**tool_call["function"]["arguments"]) == 1065
+
+
+def test_model_field_roundtrip() -> None:
+    """Verify `model` is preserved through pydantic dump/validate round-trip."""
+    setup = AzureOpenAIChatModelSetup(connection="conn", model="test-deployment")
+    restored = AzureOpenAIChatModelSetup.model_validate(setup.model_dump())
+    assert restored.model == "test-deployment"

python/flink_agents/integrations/chat_models/ollama_chat_model.py

@@ -176,12 +176,12 @@ class OllamaChatModelSetup(BaseChatModelSetup):
     ----------
     connection : str
         Name of the referenced connection. (Inherited from BaseChatModelSetup)
+    model : str
+        Model name to use. (Inherited from BaseChatModelSetup)
     prompt : Optional[Union[Prompt, str]
         Prompt template or string for the model. (Inherited from BaseChatModelSetup)
     tools : Optional[List[str]]
         List of available tools to use in the chat. (Inherited from BaseChatModelSetup)
-    model : str
-        Model name to use.
     temperature : float
         The temperature to use for sampling.
     num_ctx : int
@@ -196,8 +196,6 @@ class OllamaChatModelSetup(BaseChatModelSetup):
         stores it in additional_kwargs.
     """
 
-    model: str = Field(description="Model name to use.")
-
     temperature: float = Field(
         default=0.75,
         description="The temperature to use for sampling.",

python/flink_agents/integrations/chat_models/openai/openai_chat_model.py

@@ -203,12 +203,13 @@ class OpenAIChatModelSetup(BaseChatModelSetup):
     ----------
     connection : str
         Name of the referenced connection. (Inherited from BaseChatModelSetup)
+    model : str
+        The OpenAI model to use. Defaults to ``DEFAULT_OPENAI_MODEL`` when omitted via
+        ``__init__``. (Inherited from BaseChatModelSetup)
     prompt : Optional[Union[Prompt, str]
         Prompt template or string for the model. (Inherited from BaseChatModelSetup)
     tools : Optional[List[str]]
         List of available tools to use in the chat. (Inherited from BaseChatModelSetup)
-    model : str
-        The OpenAI model to use.
     temperature : float
         The temperature to use during generation.
     max_tokens : Optional[int]
@@ -225,9 +226,6 @@ class OpenAIChatModelSetup(BaseChatModelSetup):
         The effort to use for reasoning models.
     """
 
-    model: str = Field(
-        default=DEFAULT_OPENAI_MODEL, description="The OpenAI model to use."
-    )
     temperature: float = Field(
         default=DEFAULT_TEMPERATURE,
         description="The temperature to use during generation.",

python/flink_agents/integrations/chat_models/openai/tests/test_openai_chat_model.py

@@ -24,6 +24,7 @@
 from flink_agents.api.resource import Resource, ResourceType
 from flink_agents.api.resource_context import ResourceContext
 from flink_agents.integrations.chat_models.openai.openai_chat_model import (
+    DEFAULT_OPENAI_MODEL,
     OpenAIChatModelConnection,
     OpenAIChatModelSetup,
 )
@@ -104,3 +105,16 @@ def get_resource(name: str, type: ResourceType) -> Resource:
     assert len(tool_calls) == 1
     tool_call = tool_calls[0]
     assert add(**tool_call["function"]["arguments"]) == 1065
+
+
+def test_model_field_roundtrip() -> None:
+    """Verify `model` is preserved through pydantic dump/validate round-trip."""
+    setup = OpenAIChatModelSetup(connection="conn", model="test-model")
+    restored = OpenAIChatModelSetup.model_validate(setup.model_dump())
+    assert restored.model == "test-model"
+
+
+def test_default_model_when_omitted() -> None:
+    """Verify per-integration default applies when `model` is omitted from __init__."""
+    setup = OpenAIChatModelSetup(connection="conn")
+    assert setup.model == DEFAULT_OPENAI_MODEL

python/flink_agents/integrations/chat_models/tests/test_ollama_chat_model.py

@@ -133,6 +133,13 @@ def get_resource(name: str, type: ResourceType) -> Resource:
     assert add(**tool_call["function"]["arguments"]) == 3
 
 
+def test_model_field_roundtrip() -> None:
+    """Verify `model` is preserved through pydantic dump/validate round-trip."""
+    setup = OllamaChatModelSetup(connection="conn", model="test-model")
+    restored = OllamaChatModelSetup.model_validate(setup.model_dump())
+    assert restored.model == "test-model"
+
+
 def test_extract_think_tags() -> None:
     """Test the static method that extracts content from <think></think> tags."""
     # Test with a think tag at the beginning (most common case)