Model provider updates

integration/test_client.py

@@ -271,7 +271,7 @@ def test_create_export_and_recreate(client: weaviate.WeaviateClient, request: Su
     assert export.generative_config is not None
     assert export.generative_config.generative == GenerativeSearches.COHERE
     assert export.generative_config.model["model"] == "command-r-plus"
-    assert export.generative_config.model["kProperty"] == 10
+    assert export.generative_config.model["k"] == 10
 
     client.collections.delete([name1, name2])
     assert not client.collections.exists(name1)

test/collection/test_config.py

@@ -844,11 +844,11 @@ def test_config_with_vectorizer_and_properties(
         {
             "generative-openai": {
                 "model": "gpt-4",
-                "frequencyPenaltyProperty": 0.5,
-                "maxTokensProperty": 100,
-                "presencePenaltyProperty": 0.5,
-                "temperatureProperty": 0.5,
-                "topPProperty": 0.5,
+                "frequencyPenalty": 0.5,
+                "maxTokens": 100,
+                "presencePenalty": 0.5,
+                "temperature": 0.5,
+                "topP": 0.5,
                 "baseURL": "https://api.openai.com/",
                 "reasoningEffort": "high",
                 "verbosity": "verbose",
@@ -861,19 +861,17 @@ def test_config_with_vectorizer_and_properties(
             model="model",
             k=10,
             max_tokens=100,
-            return_likelihoods="ALL",
             stop_sequences=["stop"],
             temperature=0.5,
             base_url="https://api.cohere.ai",
         ),
         {
             "generative-cohere": {
                 "model": "model",
-                "kProperty": 10,
-                "maxTokensProperty": 100,
-                "returnLikelihoodsProperty": "ALL",
-                "stopSequencesProperty": ["stop"],
-                "temperatureProperty": 0.5,
+                "k": 10,
+                "maxTokens": 100,
+                "stopSequences": ["stop"],
+                "temperature": 0.5,
                 "baseURL": "https://api.cohere.ai/",
             }
         },
@@ -939,12 +937,26 @@ def test_config_with_vectorizer_and_properties(
         },
     ),
     (
-        Configure.Generative.aws(model="cohere.command-light-text-v14", region="us-east-1"),
+        Configure.Generative.aws(
+            model="cohere.command-light-text-v14",
+            region="us-east-1",
+            service="bedrock",
+            endpoint="custom-endpoint",
+            max_tokens=100,
+            temperature=0.5,
+            target_model="target-model",
+            target_variant="target-variant",
+        ),
         {
             "generative-aws": {
                 "model": "cohere.command-light-text-v14",
                 "region": "us-east-1",
                 "service": "bedrock",
+                "endpoint": "custom-endpoint",
+                "maxTokens": 100,
+                "temperature": 0.5,
+                "targetModel": "target-model",
+                "targetVariant": "target-variant",
             }
         },
     ),
@@ -970,13 +982,13 @@ def test_config_with_vectorizer_and_properties(
         ),
         {
             "generative-openai": {
-                "deploymentId": "id",
                 "resourceName": "name",
-                "frequencyPenaltyProperty": 0.5,
-                "maxTokensProperty": 100,
-                "presencePenaltyProperty": 0.5,
-                "temperatureProperty": 0.5,
-                "topPProperty": 0.5,
+                "deploymentId": "id",
+                "frequencyPenalty": 0.5,
+                "maxTokens": 100,
+                "presencePenalty": 0.5,
+                "temperature": 0.5,
+                "topP": 0.5,
                 "baseURL": "https://api.openai.com/",
             }
         },

weaviate/collections/classes/config.py

@@ -391,6 +391,7 @@ class _GenerativeXai(_GenerativeProvider):
     model: Optional[str]
     maxTokens: Optional[int]
     baseURL: Optional[str]
+    topP: Optional[float]
 
 
 class _GenerativeFriendliai(_GenerativeProvider):
@@ -416,11 +417,11 @@ class _GenerativeOpenAIConfigBase(_GenerativeProvider):
         default=GenerativeSearches.OPENAI, frozen=True, exclude=True
     )
     baseURL: Optional[AnyHttpUrl]
-    frequencyPenaltyProperty: Optional[float]
-    presencePenaltyProperty: Optional[float]
-    maxTokensProperty: Optional[int]
-    temperatureProperty: Optional[float]
-    topPProperty: Optional[float]
+    frequencyPenalty: Optional[float]
+    presencePenalty: Optional[float]
+    maxTokens: Optional[int]
+    temperature: Optional[float]
+    topP: Optional[float]
 
     def _to_dict(self) -> Dict[str, Any]:
         ret_dict = super()._to_dict()
@@ -445,12 +446,12 @@ class _GenerativeCohereConfig(_GenerativeProvider):
         default=GenerativeSearches.COHERE, frozen=True, exclude=True
     )
     baseURL: Optional[AnyHttpUrl]
-    kProperty: Optional[int]
+    k: Optional[int]
     model: Optional[str]
-    maxTokensProperty: Optional[int]
-    returnLikelihoodsProperty: Optional[str]
-    stopSequencesProperty: Optional[List[str]]
-    temperatureProperty: Optional[float]
+    maxTokens: Optional[int]
+    # returnLikelihoods: Optional[str]  # Not implemented server-side
+    stopSequences: Optional[List[str]]
+    temperature: Optional[float]
 
     def _to_dict(self) -> Dict[str, Any]:
         ret_dict = super()._to_dict()
@@ -481,6 +482,9 @@ class _GenerativeAWSConfig(_GenerativeProvider):
     model: Optional[str]
     endpoint: Optional[str]
     maxTokens: Optional[int]
+    temperature: Optional[float]
+    targetModel: Optional[str]
+    targetVariant: Optional[str]
 
 
 class _GenerativeAnthropicConfig(_GenerativeProvider):
@@ -691,6 +695,7 @@ def xai(
         model: Optional[str] = None,
         temperature: Optional[float] = None,
         max_tokens: Optional[int] = None,
+        top_p: Optional[float] = None,
     ) -> _GenerativeProvider:
         """Create a `_GenerativeXai` object for use when performing AI generation using the `generative-xai` module.
 
@@ -699,9 +704,10 @@ def xai(
             model: The model to use. Defaults to `None`, which uses the server-defined default
             temperature: The temperature to use. Defaults to `None`, which uses the server-defined default
             max_tokens: The maximum number of tokens to generate. Defaults to `None`, which uses the server-defined default
+            top_p: The top P value to use. Defaults to `None`, which uses the server-defined default
         """
         return _GenerativeXai(
-            model=model, temperature=temperature, maxTokens=max_tokens, baseURL=base_url
+            model=model, temperature=temperature, maxTokens=max_tokens, topP=top_p, baseURL=base_url
         )
 
     @staticmethod
@@ -750,12 +756,12 @@ def openai(
         """
         return _GenerativeOpenAIConfig(
             baseURL=base_url,
-            frequencyPenaltyProperty=frequency_penalty,
-            maxTokensProperty=max_tokens,
+            frequencyPenalty=frequency_penalty,
+            maxTokens=max_tokens,
             model=model,
-            presencePenaltyProperty=presence_penalty,
-            temperatureProperty=temperature,
-            topPProperty=top_p,
+            presencePenalty=presence_penalty,
+            temperature=temperature,
+            topP=top_p,
             verbosity=verbosity,
             reasoningEffort=reasoning_effort,
         )
@@ -789,12 +795,12 @@ def azure_openai(
         return _GenerativeAzureOpenAIConfig(
             baseURL=base_url,
             deploymentId=deployment_id,
-            frequencyPenaltyProperty=frequency_penalty,
-            maxTokensProperty=max_tokens,
-            presencePenaltyProperty=presence_penalty,
+            frequencyPenalty=frequency_penalty,
+            maxTokens=max_tokens,
+            presencePenalty=presence_penalty,
             resourceName=resource_name,
-            temperatureProperty=temperature,
-            topPProperty=top_p,
+            temperature=temperature,
+            topP=top_p,
         )
 
     @staticmethod
@@ -816,19 +822,18 @@ def cohere(
             model: The model to use. Defaults to `None`, which uses the server-defined default
             k: The number of sequences to generate. Defaults to `None`, which uses the server-defined default
             max_tokens: The maximum number of tokens to generate. Defaults to `None`, which uses the server-defined default
-            return_likelihoods: Whether to return the likelihoods. Defaults to `None`, which uses the server-defined default
+            return_likelihoods: (Deprecated) The return likelihoods setting to use. No longer has any effect.
             stop_sequences: The stop sequences to use. Defaults to `None`, which uses the server-defined default
             temperature: The temperature to use. Defaults to `None`, which uses the server-defined default
             base_url: The base URL where the API request should go. Defaults to `None`, which uses the server-defined default
         """
         return _GenerativeCohereConfig(
             baseURL=base_url,
-            kProperty=k,
-            maxTokensProperty=max_tokens,
+            k=k,
+            maxTokens=max_tokens,
             model=model,
-            returnLikelihoodsProperty=return_likelihoods,
-            stopSequencesProperty=stop_sequences,
-            temperatureProperty=temperature,
+            stopSequences=stop_sequences,
+            temperature=temperature,
         )
 
     @staticmethod
@@ -916,6 +921,9 @@ def aws(
         endpoint: Optional[str] = None,
         service: Union[AWSService, str] = "bedrock",
         max_tokens: Optional[int] = None,
+        target_model: Optional[str] = None,
+        target_variant: Optional[str] = None,
+        temperature: Optional[float] = None,
     ) -> _GenerativeProvider:
         """Create a `_GenerativeAWSConfig` object for use when performing AI generation using the `generative-aws` module.
 
@@ -928,9 +936,19 @@ def aws(
             region: The AWS region to run the model from, REQUIRED.
             endpoint: The model to use, REQUIRED for service "sagemaker".
             service: The AWS service to use, options are "bedrock" and "sagemaker".
+            target_model: The target model to use. Defaults to `None`, which uses the server-defined default
+            target_variant: The target variant to use. Defaults to `None`, which uses the server-defined default
+            temperature: The temperature to use. Defaults to `None`, which uses the server-defined default
         """
         return _GenerativeAWSConfig(
-            model=model, region=region, service=service, endpoint=endpoint, maxTokens=max_tokens
+            model=model,
+            region=region,
+            service=service,
+            endpoint=endpoint,
+            maxTokens=max_tokens,
+            temperature=temperature,
+            targetModel=target_model,
+            targetVariant=target_variant,
         )
 
     @staticmethod