first commit

configs/vector_stores/s3_vectors.py

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+from typing import Any, Dict, Optional
+
+from pydantic import BaseModel, ConfigDict, Field, model_validator
+
+
+class S3VectorsConfig(BaseModel):
+    vector_bucket_name: str = Field(description="Name of the S3 Vector bucket")
+    collection_name: str = Field("mem0", description="Name of the vector index")
+    embedding_model_dims: int = Field(1536, description="Dimension of the embedding vector")
+    distance_metric: str = Field(
+        "cosine",
+        description="Distance metric for similarity search. Options: 'cosine', 'euclidean'",
+    )
+    region_name: Optional[str] = Field(None, description="AWS region for the S3 Vectors client")
+
+    @model_validator(mode="before")
+    @classmethod
+    def validate_extra_fields(cls, values: Dict[str, Any]) -> Dict[str, Any]:
+        allowed_fields = set(cls.model_fields.keys())
+        input_fields = set(values.keys())
+        extra_fields = input_fields - allowed_fields
+        if extra_fields:
+            raise ValueError(
+                f"Extra fields not allowed: {', '.join(extra_fields)}. Please input only the following fields: {', '.join(allowed_fields)}"
+            )
+        return values
+
+    model_config = ConfigDict(arbitrary_types_allowed=True)