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58
configs/vector_stores/chroma.py
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58
configs/vector_stores/chroma.py
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from typing import Any, ClassVar, Dict, Optional
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from pydantic import BaseModel, ConfigDict, Field, model_validator
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class ChromaDbConfig(BaseModel):
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try:
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from chromadb.api.client import Client
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except ImportError:
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raise ImportError("The 'chromadb' library is required. Please install it using 'pip install chromadb'.")
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Client: ClassVar[type] = Client
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collection_name: str = Field("mem0", description="Default name for the collection/database")
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client: Optional[Client] = Field(None, description="Existing ChromaDB client instance")
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path: Optional[str] = Field(None, description="Path to the database directory")
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host: Optional[str] = Field(None, description="Database connection remote host")
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port: Optional[int] = Field(None, description="Database connection remote port")
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# ChromaDB Cloud configuration
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api_key: Optional[str] = Field(None, description="ChromaDB Cloud API key")
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tenant: Optional[str] = Field(None, description="ChromaDB Cloud tenant ID")
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@model_validator(mode="before")
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def check_connection_config(cls, values):
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host, port, path = values.get("host"), values.get("port"), values.get("path")
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api_key, tenant = values.get("api_key"), values.get("tenant")
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# Check if cloud configuration is provided
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cloud_config = bool(api_key and tenant)
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# If cloud configuration is provided, remove any default path that might have been added
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if cloud_config and path == "/tmp/chroma":
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values.pop("path", None)
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return values
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# Check if local/server configuration is provided (excluding default tmp path for cloud config)
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local_config = bool(path and path != "/tmp/chroma") or bool(host and port)
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if not cloud_config and not local_config:
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raise ValueError("Either ChromaDB Cloud configuration (api_key, tenant) or local configuration (path or host/port) must be provided.")
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if cloud_config and local_config:
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raise ValueError("Cannot specify both cloud configuration and local configuration. Choose one.")
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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 = ConfigDict(arbitrary_types_allowed=True)
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