769d6b5080
Add possibility to create a new Vector memory and store text data points using openai embeddings.
32 lines
1.1 KiB
Python
32 lines
1.1 KiB
Python
from enum import Enum
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from qdrant_client.models import Distance, VectorParams
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from cognitive_architecture.modules.memory.vector import create_vector_memory
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from cognitive_architecture.modules.users.memory import is_existing_memory, register_memory_for_user
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from cognitive_architecture.infrastructure.databases.vector.qdrant.adapter import CollectionConfig
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class MemoryType(Enum):
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GRAPH = "GRAPH"
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VECTOR = "VECTOR"
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RELATIONAL = "RELATIONAL"
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class MemoryException(Exception):
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message: str
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def __init__(self, message: str):
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self.message = message
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async def create_memory(user_id: str, memory_name: str, memory_type: MemoryType):
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if await is_existing_memory(memory_name):
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raise MemoryException(f'Memory with the name "{memory_name}" already exists. Memory names must be unique.')
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match memory_type:
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case MemoryType.VECTOR:
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await create_vector_memory(memory_name, CollectionConfig(
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vector_config = VectorParams(
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size = 1536,
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distance = Distance.DOT,
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)
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))
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await register_memory_for_user(user_id, memory_name)
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