Updated tests.

aana/core/models/sampling.py

@@ -22,8 +22,8 @@ class SamplingParams(BaseModel):
         kwargs (dict): Extra keyword arguments to pass as sampling parameters.
     """
 
-    temperature: float | None = Field(
-        default=None,
+    temperature: float = Field(
+        default=1.0,
         ge=0.0,
         description=(
             "Float that controls the randomness of the sampling. "
@@ -32,8 +32,8 @@ class SamplingParams(BaseModel):
             "Zero means greedy sampling."
         ),
     )
-    top_p: float | None = Field(
-        default=None,
+    top_p: float = Field(
+        default=1.0,
         gt=0.0,
         le=1.0,
         description=(
@@ -51,8 +51,8 @@ class SamplingParams(BaseModel):
     max_tokens: int | None = Field(
         default=None, ge=1, description="The maximum number of tokens to generate."
     )
-    repetition_penalty: float | None = Field(
-        default=None,
+    repetition_penalty: float = Field(
+        default=1.0,
         description=(
             "Float that penalizes new tokens based on whether they appear in the "
             "prompt and the generated text so far. Values > 1 encourage the model "

aana/deployments/hf_text_generation_deployment.py

@@ -132,6 +132,7 @@ async def generate_stream(
                     temperature=sampling_params.temperature,
                     num_return_sequences=1,
                     eos_token_id=self.tokenizer.eos_token_id,
+                    repetition_penalty=sampling_params.repetition_penalty,
                     **sampling_params.kwargs,
                 )
                 if sampling_params.temperature == 0:

aana/deployments/vllm_deployment.py

@@ -148,7 +148,7 @@ async def generate_stream(
         try:
             # convert SamplingParams to VLLMSamplingParams
             sampling_params_vllm = VLLMSamplingParams(
-                **sampling_params.model_dump(exclude_unset=True),
+                **sampling_params.model_dump(exclude_unset=True, exclude=["kwargs"]),
                 **sampling_params.kwargs,
             )
             # start the request

aana/tests/deployments/test_idefics2_deployment.py

@@ -6,6 +6,7 @@
 from aana.core.models.chat import ChatMessage
 from aana.core.models.image import Image
 from aana.core.models.image_chat import ImageChatDialog
+from aana.core.models.sampling import SamplingParams
 from aana.core.models.types import Dtype
 from aana.deployments.aana_deployment_handle import AanaDeploymentHandle
 from aana.deployments.idefics_2_deployment import Idefics2Config, Idefics2Deployment
@@ -21,6 +22,9 @@
             user_config=Idefics2Config(
                 model="HuggingFaceM4/idefics2-8b",
                 dtype=Dtype.FLOAT16,
+                default_sampling_params=SamplingParams(
+                    temperature=0.0, kwargs={"diversity_penalty": 0.0}
+                ),
             ).model_dump(mode="json"),
         ),
     )

aana/tests/deployments/test_text_generation_deployment.py

@@ -28,6 +28,9 @@
                     model_kwargs={
                         "trust_remote_code": True,
                     },
+                    default_sampling_params=SamplingParams(
+                        temperature=0.0, kwargs={"diversity_penalty": 0.0}
+                    ),
                 ).model_dump(mode="json"),
             ),
         ),
@@ -46,7 +49,11 @@
                     gpu_memory_reserved=10000,
                     enforce_eager=True,
                     default_sampling_params=SamplingParams(
-                        temperature=0.0, top_p=1.0, top_k=-1, max_tokens=1024
+                        temperature=0.0,
+                        top_p=1.0,
+                        top_k=-1,
+                        max_tokens=1024,
+                        kwargs={"frequency_penalty": 0.0},
                     ),
                     engine_args={
                         "trust_remote_code": True,

aana/tests/units/test_sampling_params.py

@@ -15,13 +15,13 @@ def test_valid_sampling_params():
     assert params.max_tokens == 50
     assert params.repetition_penalty == 1.5
 
-    # Test valid params with default values (None)
+    # Test valid params with default values
     params = SamplingParams()
-    assert params.temperature is None
-    assert params.top_p is None
+    assert params.temperature == 1.0
+    assert params.top_p == 1.0
     assert params.top_k is None
     assert params.max_tokens is None
-    assert params.repetition_penalty is None
+    assert params.repetition_penalty == 1.0
 
 
 def test_invalid_temperature():
@@ -59,7 +59,7 @@ def test_kwargs():
     )
     assert params.kwargs == {"presence_penalty": 2.0, "frequency_penalty": 1.0}
     assert params.temperature == 0.5
-    assert params.top_p is None
+    assert params.top_p == 1.0
     assert params.top_k is None
     assert params.max_tokens is None
-    assert params.repetition_penalty is None
+    assert params.repetition_penalty == 1.0