Spaces:
Runtime error
Runtime error
File size: 9,193 Bytes
4a51346 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 |
from chromadb.db.base import SqlDB, ParameterValue, get_sql
from chromadb.ingest import (
Producer,
Consumer,
encode_vector,
decode_vector,
ConsumerCallbackFn,
)
from chromadb.types import (
SubmitEmbeddingRecord,
EmbeddingRecord,
SeqId,
ScalarEncoding,
Operation,
)
from chromadb.config import System
from overrides import override
from collections import defaultdict
from typing import Tuple, Optional, Dict, Set, cast
from uuid import UUID
from pypika import Table, functions
import uuid
import json
import logging
logger = logging.getLogger(__name__)
_operation_codes = {
Operation.ADD: 0,
Operation.UPDATE: 1,
Operation.UPSERT: 2,
Operation.DELETE: 3,
}
_operation_codes_inv = {v: k for k, v in _operation_codes.items()}
class SqlEmbeddingsQueue(SqlDB, Producer, Consumer):
"""A SQL database that stores embeddings, allowing a traditional RDBMS to be used as
the primary ingest queue and satisfying the top level Producer/Consumer interfaces.
Note that this class is only suitable for use cases where the producer and consumer
are in the same process.
This is because notifiaction of new embeddings happens solely in-process: this
implementation does not actively listen to the the database for new records added by
other processes.
"""
class Subscription:
id: UUID
topic_name: str
start: int
end: int
callback: ConsumerCallbackFn
def __init__(
self,
id: UUID,
topic_name: str,
start: int,
end: int,
callback: ConsumerCallbackFn,
):
self.id = id
self.topic_name = topic_name
self.start = start
self.end = end
self.callback = callback
_subscriptions: Dict[str, Set[Subscription]]
def __init__(self, system: System):
self._subscriptions = defaultdict(set)
super().__init__(system)
@override
def reset(self) -> None:
super().reset()
self._subscriptions = defaultdict(set)
@override
def create_topic(self, topic_name: str) -> None:
# Topic creation is implicit for this impl
pass
@override
def delete_topic(self, topic_name: str) -> None:
t = Table("embeddings_queue")
q = (
self.querybuilder()
.from_(t)
.where(t.topic == ParameterValue(topic_name))
.delete()
)
with self.tx() as cur:
sql, params = get_sql(q, self.parameter_format())
cur.execute(sql, params)
@override
def submit_embedding(
self, topic_name: str, embedding: SubmitEmbeddingRecord
) -> SeqId:
if not self._running:
raise RuntimeError("Component not running")
if embedding["embedding"]:
encoding_type = cast(ScalarEncoding, embedding["encoding"])
encoding = encoding_type.value
embedding_bytes = encode_vector(embedding["embedding"], encoding_type)
else:
embedding_bytes = None
encoding = None
metadata = json.dumps(embedding["metadata"]) if embedding["metadata"] else None
t = Table("embeddings_queue")
insert = (
self.querybuilder()
.into(t)
.columns(t.operation, t.topic, t.id, t.vector, t.encoding, t.metadata)
.insert(
ParameterValue(_operation_codes[embedding["operation"]]),
ParameterValue(topic_name),
ParameterValue(embedding["id"]),
ParameterValue(embedding_bytes),
ParameterValue(encoding),
ParameterValue(metadata),
)
)
with self.tx() as cur:
sql, params = get_sql(insert, self.parameter_format())
sql = f"{sql} RETURNING seq_id" # Pypika doesn't support RETURNING
seq_id = int(cur.execute(sql, params).fetchone()[0])
embedding_record = EmbeddingRecord(
id=embedding["id"],
seq_id=seq_id,
embedding=embedding["embedding"],
encoding=embedding["encoding"],
metadata=embedding["metadata"],
operation=embedding["operation"],
)
self._notify_all(topic_name, embedding_record)
return seq_id
@override
def subscribe(
self,
topic_name: str,
consume_fn: ConsumerCallbackFn,
start: Optional[SeqId] = None,
end: Optional[SeqId] = None,
id: Optional[UUID] = None,
) -> UUID:
if not self._running:
raise RuntimeError("Component not running")
subscription_id = id or uuid.uuid4()
start, end = self._validate_range(start, end)
subscription = self.Subscription(
subscription_id, topic_name, start, end, consume_fn
)
# Backfill first, so if it errors we do not add the subscription
self._backfill(subscription)
self._subscriptions[topic_name].add(subscription)
return subscription_id
@override
def unsubscribe(self, subscription_id: UUID) -> None:
for topic_name, subscriptions in self._subscriptions.items():
for subscription in subscriptions:
if subscription.id == subscription_id:
subscriptions.remove(subscription)
if len(subscriptions) == 0:
del self._subscriptions[topic_name]
return
@override
def min_seqid(self) -> SeqId:
return -1
@override
def max_seqid(self) -> SeqId:
return 2**63 - 1
def _backfill(self, subscription: Subscription) -> None:
"""Backfill the given subscription with any currently matching records in the
DB"""
t = Table("embeddings_queue")
q = (
self.querybuilder()
.from_(t)
.where(t.topic == ParameterValue(subscription.topic_name))
.where(t.seq_id > ParameterValue(subscription.start))
.where(t.seq_id <= ParameterValue(subscription.end))
.select(t.seq_id, t.operation, t.id, t.vector, t.encoding, t.metadata)
.orderby(t.seq_id)
)
with self.tx() as cur:
sql, params = get_sql(q, self.parameter_format())
cur.execute(sql, params)
rows = cur.fetchall()
for row in rows:
if row[3]:
encoding = ScalarEncoding(row[4])
vector = decode_vector(row[3], encoding)
else:
encoding = None
vector = None
self._notify_one(
subscription,
EmbeddingRecord(
seq_id=row[0],
operation=_operation_codes_inv[row[1]],
id=row[2],
embedding=vector,
encoding=encoding,
metadata=json.loads(row[5]) if row[5] else None,
),
)
def _validate_range(
self, start: Optional[SeqId], end: Optional[SeqId]
) -> Tuple[int, int]:
"""Validate and normalize the start and end SeqIDs for a subscription using this
impl."""
start = start or self._next_seq_id()
end = end or self.max_seqid()
if not isinstance(start, int) or not isinstance(end, int):
raise ValueError("SeqIDs must be integers for sql-based EmbeddingsDB")
if start >= end:
raise ValueError(f"Invalid SeqID range: {start} to {end}")
return start, end
def _next_seq_id(self) -> int:
"""Get the next SeqID for this database."""
t = Table("embeddings_queue")
q = self.querybuilder().from_(t).select(functions.Max(t.seq_id))
with self.tx() as cur:
cur.execute(q.get_sql())
return int(cur.fetchone()[0]) + 1
def _notify_all(self, topic: str, embedding: EmbeddingRecord) -> None:
"""Send a notification to each subscriber of the given topic."""
if self._running:
for sub in self._subscriptions[topic]:
self._notify_one(sub, embedding)
def _notify_one(self, sub: Subscription, embedding: EmbeddingRecord) -> None:
"""Send a notification to a single subscriber."""
if embedding["seq_id"] > sub.end:
self.unsubscribe(sub.id)
return
if embedding["seq_id"] <= sub.start:
return
# Log errors instead of throwing them to preserve async semantics
# for consistency between local and distributed configurations
try:
sub.callback([embedding])
except BaseException as e:
id = embedding.get("id", embedding.get("delete_id"))
logger.error(
f"Exception occurred invoking consumer for subscription {sub.id}"
+ f"to topic {sub.topic_name} for embedding id {id} ",
e,
)
|