chroma / chromadb /ingest /__init__.py
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feat: chroma initial deploy
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from abc import abstractmethod
from typing import Callable, Optional, Sequence
from chromadb.types import (
SubmitEmbeddingRecord,
EmbeddingRecord,
SeqId,
Vector,
ScalarEncoding,
)
from chromadb.config import Component
from uuid import UUID
import array
def encode_vector(vector: Vector, encoding: ScalarEncoding) -> bytes:
"""Encode a vector into a byte array."""
if encoding == ScalarEncoding.FLOAT32:
return array.array("f", vector).tobytes()
elif encoding == ScalarEncoding.INT32:
return array.array("i", vector).tobytes()
else:
raise ValueError(f"Unsupported encoding: {encoding.value}")
def decode_vector(vector: bytes, encoding: ScalarEncoding) -> Vector:
"""Decode a byte array into a vector"""
if encoding == ScalarEncoding.FLOAT32:
return array.array("f", vector).tolist()
elif encoding == ScalarEncoding.INT32:
return array.array("i", vector).tolist()
else:
raise ValueError(f"Unsupported encoding: {encoding.value}")
class Producer(Component):
"""Interface for writing embeddings to an ingest stream"""
@abstractmethod
def create_topic(self, topic_name: str) -> None:
pass
@abstractmethod
def delete_topic(self, topic_name: str) -> None:
pass
@abstractmethod
def submit_embedding(
self, topic_name: str, embedding: SubmitEmbeddingRecord
) -> SeqId:
"""Add an embedding record to the given topic. Returns the SeqID of the record."""
pass
@abstractmethod
def submit_embeddings(
self, topic_name: str, embeddings: Sequence[SubmitEmbeddingRecord]
) -> Sequence[SeqId]:
"""Add a batch of embedding records to the given topic. Returns the SeqIDs of
the records. The returned SeqIDs will be in the same order as the given
SubmitEmbeddingRecords. However, it is not guaranteed that the SeqIDs will be
processed in the same order as the given SubmitEmbeddingRecords. If the number
of records exceeds the maximum batch size, an exception will be thrown."""
pass
@property
@abstractmethod
def max_batch_size(self) -> int:
"""Return the maximum number of records that can be submitted in a single call
to submit_embeddings."""
pass
ConsumerCallbackFn = Callable[[Sequence[EmbeddingRecord]], None]
class Consumer(Component):
"""Interface for reading embeddings off an ingest stream"""
@abstractmethod
def subscribe(
self,
topic_name: str,
consume_fn: ConsumerCallbackFn,
start: Optional[SeqId] = None,
end: Optional[SeqId] = None,
id: Optional[UUID] = None,
) -> UUID:
"""Register a function that will be called to recieve embeddings for a given
topic. The given function may be called any number of times, with any number of
records, and may be called concurrently.
Only records between start (exclusive) and end (inclusive) SeqIDs will be
returned. If start is None, the first record returned will be the next record
generated, not including those generated before creating the subscription. If
end is None, the consumer will consume indefinitely, otherwise it will
automatically be unsubscribed when the end SeqID is reached.
If the function throws an exception, the function may be called again with the
same or different records.
Takes an optional UUID as a unique subscription ID. If no ID is provided, a new
ID will be generated and returned."""
pass
@abstractmethod
def unsubscribe(self, subscription_id: UUID) -> None:
"""Unregister a subscription. The consume function will no longer be invoked,
and resources associated with the subscription will be released."""
pass
@abstractmethod
def min_seqid(self) -> SeqId:
"""Return the minimum possible SeqID in this implementation."""
pass
@abstractmethod
def max_seqid(self) -> SeqId:
"""Return the maximum possible SeqID in this implementation."""
pass
class CollectionAssignmentPolicy(Component):
"""Interface for assigning collections to topics"""
@abstractmethod
def assign_collection(self, collection_id: UUID) -> str:
"""Return the topic that should be used for the given collection"""
pass
@abstractmethod
def get_topics(self) -> Sequence[str]:
"""Return the list of topics that this policy is currently using"""
pass