Add generative Anthropic module integration (#1149)

* Add anthropic generative config and test

* Fix expected response field names

---------

Co-authored-by: Tommy Smith <tommy@weaviate.io>

test/collection/test_config.py

@@ -752,6 +752,26 @@ def test_config_with_vectorizer_and_properties(
             }
         },
     ),
+    (
+        Configure.Generative.anthropic(
+            model="model",
+            max_tokens=100,
+            stop_sequences=["stop"],
+            temperature=0.5,
+            top_k=10,
+            top_p=0.5,
+        ),
+        {
+            "generative-anthropic": {
+                "model": "model",
+                "maxTokens": 100,
+                "stopSequences": ["stop"],
+                "temperature": 0.5,
+                "topK": 10,
+                "topP": 0.5,
+            }
+        },
+    ),
 ]
 
 

weaviate/collections/classes/config.py

@@ -29,26 +29,23 @@
     _NamedVectors,
     _NamedVectorsUpdate,
 )
+from weaviate.collections.classes.config_vector_index import VectorIndexType as VectorIndexTypeAlias
 from weaviate.collections.classes.config_vector_index import (
     _QuantizerConfigCreate,
     _VectorIndexConfigCreate,
+    _VectorIndexConfigDynamicCreate,
     _VectorIndexConfigDynamicUpdate,
-    _VectorIndexConfigHNSWCreate,
     _VectorIndexConfigFlatCreate,
-    _VectorIndexConfigHNSWUpdate,
     _VectorIndexConfigFlatUpdate,
-    _VectorIndexConfigDynamicCreate,
+    _VectorIndexConfigHNSWCreate,
+    _VectorIndexConfigHNSWUpdate,
     _VectorIndexConfigSkipCreate,
     _VectorIndexConfigUpdate,
-    VectorIndexType as VectorIndexTypeAlias,
-)
-from weaviate.collections.classes.config_vectorizers import (
-    _Vectorizer,
-    _VectorizerConfigCreate,
-    CohereModel,
-    Vectorizers as VectorizersAlias,
-    VectorDistances as VectorDistancesAlias,
 )
+from weaviate.collections.classes.config_vectorizers import CohereModel
+from weaviate.collections.classes.config_vectorizers import VectorDistances as VectorDistancesAlias
+from weaviate.collections.classes.config_vectorizers import Vectorizers as VectorizersAlias
+from weaviate.collections.classes.config_vectorizers import _Vectorizer, _VectorizerConfigCreate
 from weaviate.exceptions import WeaviateInvalidInputError
 from weaviate.util import _capitalize_first_letter
 from weaviate.warnings import _Warnings
@@ -161,9 +158,12 @@ class GenerativeSearches(str, Enum):
             Weaviate module backed by PaLM generative models.
         `AWS`
             Weaviate module backed by AWS Bedrock generative models.
+        `ANTHROPIC`
+            Weaviate module backed by Anthropic generative models.
     """
 
     AWS = "generative-aws"
+    ANTHROPIC = "generative-anthropic"
     ANYSCALE = "generative-anyscale"
     COHERE = "generative-cohere"
     MISTRAL = "generative-mistral"
@@ -494,6 +494,18 @@ class _GenerativeAWSConfig(_GenerativeConfigCreate):
     endpoint: Optional[str]
 
 
+class _GenerativeAnthropicConfig(_GenerativeConfigCreate):
+    generative: GenerativeSearches = Field(
+        default=GenerativeSearches.ANTHROPIC, frozen=True, exclude=True
+    )
+    model: Optional[str]
+    maxTokens: Optional[int]
+    stopSequences: Optional[List[str]]
+    temperature: Optional[float]
+    topK: Optional[int]
+    topP: Optional[float]
+
+
 class _RerankerConfigCreate(_ConfigCreateModel):
     reranker: Rerankers
 
@@ -767,6 +779,41 @@ def aws(
             endpoint=endpoint,
         )
 
+    @staticmethod
+    def anthropic(
+        model: Optional[str] = None,
+        max_tokens: Optional[int] = None,
+        stop_sequences: Optional[List[str]] = None,
+        temperature: Optional[float] = None,
+        top_k: Optional[int] = None,
+        top_p: Optional[float] = None,
+    ) -> _GenerativeConfigCreate:
+        """
+        Create a `_GenerativeAnthropicConfig` object for use when performing AI generation using the `generative-anthropic` module.
+
+        Arguments:
+            `model`
+                The model 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
+            `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
+            `top_k`
+                The top K to use. Defaults to `None`, which uses the server-defined default
+            `top_p`
+                The top P to use. Defaults to `None`, which uses the server-defined default
+        """
+        return _GenerativeAnthropicConfig(
+            model=model,
+            maxTokens=max_tokens,
+            stopSequences=stop_sequences,
+            temperature=temperature,
+            topK=top_k,
+            topP=top_p,
+        )
+
 
 class _Reranker:
     """Use this factory class to create the correct object for the `reranker_config` argument in the `collections.create()` method.