57 lines
2.6 KiB
Python
57 lines
2.6 KiB
Python
import os
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from typing import Any, Dict, Optional
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from pydantic import BaseModel, Field, model_validator
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class PineconeConfig(BaseModel):
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"""Configuration for Pinecone vector database."""
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collection_name: str = Field("mem0", description="Name of the index/collection")
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embedding_model_dims: int = Field(1536, description="Dimensions of the embedding model")
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client: Optional[Any] = Field(None, description="Existing Pinecone client instance")
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api_key: Optional[str] = Field(None, description="API key for Pinecone")
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environment: Optional[str] = Field(None, description="Pinecone environment")
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serverless_config: Optional[Dict[str, Any]] = Field(None, description="Configuration for serverless deployment")
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pod_config: Optional[Dict[str, Any]] = Field(None, description="Configuration for pod-based deployment")
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hybrid_search: bool = Field(False, description="Whether to enable hybrid search")
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metric: str = Field("cosine", description="Distance metric for vector similarity")
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batch_size: int = Field(100, description="Batch size for operations")
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extra_params: Optional[Dict[str, Any]] = Field(None, description="Additional parameters for Pinecone client")
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@model_validator(mode="before")
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@classmethod
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def check_api_key_or_client(cls, values: Dict[str, Any]) -> Dict[str, Any]:
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api_key, client = values.get("api_key"), values.get("client")
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if not api_key and not client and "PINECONE_API_KEY" not in os.environ:
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raise ValueError(
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"Either 'api_key' or 'client' must be provided, or PINECONE_API_KEY environment variable must be set."
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)
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return values
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@model_validator(mode="before")
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@classmethod
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def check_pod_or_serverless(cls, values: Dict[str, Any]) -> Dict[str, Any]:
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pod_config, serverless_config = values.get("pod_config"), values.get("serverless_config")
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if pod_config and serverless_config:
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raise ValueError(
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"Both 'pod_config' and 'serverless_config' cannot be specified. Choose one deployment option."
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)
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return values
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@model_validator(mode="before")
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@classmethod
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def validate_extra_fields(cls, values: Dict[str, Any]) -> Dict[str, Any]:
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allowed_fields = set(cls.model_fields.keys())
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input_fields = set(values.keys())
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extra_fields = input_fields - allowed_fields
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if extra_fields:
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raise ValueError(
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f"Extra fields not allowed: {', '.join(extra_fields)}. Please input only the following fields: {', '.join(allowed_fields)}"
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)
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return values
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model_config = {
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"arbitrary_types_allowed": True,
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}
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