first commit

configs/vector_stores/azure_ai_search.py

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+from typing import Any, Dict, Optional
+
+from pydantic import BaseModel, ConfigDict, Field, model_validator
+
+
+class AzureAISearchConfig(BaseModel):
+    collection_name: str = Field("mem0", description="Name of the collection")
+    service_name: str = Field(None, description="Azure AI Search service name")
+    api_key: str = Field(None, description="API key for the Azure AI Search service")
+    embedding_model_dims: int = Field(1536, description="Dimension of the embedding vector")
+    compression_type: Optional[str] = Field(
+        None, description="Type of vector compression to use. Options: 'scalar', 'binary', or None"
+    )
+    use_float16: bool = Field(
+        False,
+        description="Whether to store vectors in half precision (Edm.Half) instead of full precision (Edm.Single)",
+    )
+    hybrid_search: bool = Field(
+        False, description="Whether to use hybrid search. If True, vector_filter_mode must be 'preFilter'"
+    )
+    vector_filter_mode: Optional[str] = Field(
+        "preFilter", description="Mode for vector filtering. Options: 'preFilter', 'postFilter'"
+    )
+
+    @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
+
+        # Check for use_compression to provide a helpful error
+        if "use_compression" in extra_fields:
+            raise ValueError(
+                "The parameter 'use_compression' is no longer supported. "
+                "Please use 'compression_type=\"scalar\"' instead of 'use_compression=True' "
+                "or 'compression_type=None' instead of 'use_compression=False'."
+            )
+
+        if extra_fields:
+            raise ValueError(
+                f"Extra fields not allowed: {', '.join(extra_fields)}. "
+                f"Please input only the following fields: {', '.join(allowed_fields)}"
+            )
+
+        # Validate compression_type values
+        if "compression_type" in values and values["compression_type"] is not None:
+            valid_types = ["scalar", "binary"]
+            if values["compression_type"].lower() not in valid_types:
+                raise ValueError(
+                    f"Invalid compression_type: {values['compression_type']}. "
+                    f"Must be one of: {', '.join(valid_types)}, or None"
+                )
+
+        return values
+
+    model_config = ConfigDict(arbitrary_types_allowed=True)