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2e818da | 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 | """Chroma-backed project-specific research memory."""
from __future__ import annotations
import hashlib
import json
from datetime import datetime, timezone
from typing import Any, Sequence
from pydantic import BaseModel, Field
from app.observability.operation import observe_operation
from app.rag.chromadb_client import ChromaDBClient
from app.rag.models import MemoryContextItem
PROJECT_MEMORY_COLLECTION = "project_memory"
class ProjectMemoryRecord(BaseModel):
memory_id: str
project_id: str
kind: str
statement: str
evidence_ids: list[str] = Field(default_factory=list)
interaction_ids: list[str] = Field(default_factory=list)
attribution: str
confidence: float = Field(default=1.0, ge=0.0, le=1.0)
novelty_key: str = ""
status: str = "active"
contradicts: list[str] = Field(default_factory=list)
supersedes: list[str] = Field(default_factory=list)
observed_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
metadata: dict[str, Any] = Field(default_factory=dict)
def make_project_memory_id(project_id: str, kind: str, novelty_key: str, statement: str) -> str:
normalized = " ".join((novelty_key or statement).casefold().split())
digest = hashlib.sha256(f"{project_id}\0{kind}\0{normalized}".encode("utf-8")).hexdigest()
return f"pm_{digest}"
class ProjectMemoryStore:
"""Project-only personalization and research state backed by Chroma."""
def __init__(self, db: ChromaDBClient | None = None) -> None:
self.db = db or ChromaDBClient()
def upsert(self, records: ProjectMemoryRecord | Sequence[ProjectMemoryRecord]) -> int:
items = [records] if isinstance(records, ProjectMemoryRecord) else list(records)
if not items:
return 0
for record in items:
if not record.project_id:
raise ValueError("project memory requires project_id")
for start in range(0, len(items), 128):
batch = items[start : start + 128]
self.db.upsert(
PROJECT_MEMORY_COLLECTION,
documents=[_document(record) for record in batch],
metadatas=[_metadata(record) for record in batch],
ids=[record.memory_id for record in batch],
)
return len(items)
def search(
self,
project_id: str,
query: str,
limit: int = 8,
*,
kinds: Sequence[str] | None = None,
consumer: str | None = None,
) -> list[MemoryContextItem]:
if not project_id or not query.strip():
return []
clauses: list[dict[str, Any]] = [{"project_id": project_id}, {"status": "active"}]
if kinds:
clauses.append({"kind": {"$in": list(kinds)}})
with observe_operation(
"embedding.query",
subsystem="embedding",
consumer=consumer,
attributes={"collection_role": "project_memory"},
) as op:
embedding = self.db.embedder.embed([query])[0]
op.add_count("query_chars", len(query))
rows = self.db.query_raw(
PROJECT_MEMORY_COLLECTION,
embedding,
n_results=limit,
where={"$and": clauses},
consumer=consumer,
raise_on_failure=True,
)
return [_memory_hit(project_id, row) for row in rows]
def delete_project(self, project_id: str) -> None:
if project_id:
self.db.delete_where(PROJECT_MEMORY_COLLECTION, {"project_id": project_id})
def count_project(self, project_id: str) -> int:
return self.db.count_where(PROJECT_MEMORY_COLLECTION, {"project_id": project_id}) if project_id else 0
def list_project(self, project_id: str) -> list[MemoryContextItem]:
if not project_id:
return []
result = self.db.get_where(
PROJECT_MEMORY_COLLECTION,
{"$and": [{"project_id": project_id}, {"status": "active"}]},
include=["documents", "metadatas"],
)
ids = result.get("ids") or []
documents = result.get("documents") or []
metadatas = result.get("metadatas") or []
return [
_memory_hit(
project_id,
{
"id": memory_id,
"text": documents[index] if index < len(documents) else "",
"metadata": metadatas[index] if index < len(metadatas) else {},
"distance": None,
},
)
for index, memory_id in enumerate(ids)
]
def delete_document(self, project_id: str, document_id: str) -> None:
if project_id and document_id:
self.db.delete_where(
PROJECT_MEMORY_COLLECTION,
{"$and": [{"project_id": project_id}, {"document_id": document_id}]},
)
def delete_annotation_document(self, project_id: str, document_id: str) -> None:
if project_id and document_id:
self.db.delete_where(
PROJECT_MEMORY_COLLECTION,
{
"$and": [
{"project_id": project_id},
{"document_id": document_id},
{"kind": "annotation_note"},
]
},
)
def delete_by_evidence_ids(self, project_id: str, evidence_ids: Sequence[str]) -> int:
"""Remove memories grounded in evidence that is about to disappear."""
targets = set(evidence_ids)
if not project_id or not targets:
return 0
result = self.db.get_where(
PROJECT_MEMORY_COLLECTION,
{"project_id": project_id},
include=["metadatas"],
)
ids = result.get("ids") or []
metadatas = result.get("metadatas") or []
stale = [
str(memory_id)
for memory_id, metadata in zip(ids, metadatas)
if targets.intersection(_loads_list((metadata or {}).get("evidence_ids_json")))
]
if stale:
self.db.delete_ids(PROJECT_MEMORY_COLLECTION, stale)
return len(stale)
def _document(record: ProjectMemoryRecord) -> str:
return (
f"Project memory type: {record.kind}\n"
f"Attribution: {record.attribution}\n"
f"Statement: {record.statement}"
)
def _metadata(record: ProjectMemoryRecord) -> dict[str, Any]:
return {
"project_id": record.project_id,
"kind": record.kind,
"attribution": record.attribution,
"confidence": float(record.confidence),
"novelty_key": record.novelty_key,
"status": record.status,
"observed_at": record.observed_at.isoformat(),
"evidence_ids_json": json.dumps(record.evidence_ids, separators=(",", ":")),
"interaction_ids_json": json.dumps(record.interaction_ids, separators=(",", ":")),
"contradicts_json": json.dumps(record.contradicts, separators=(",", ":")),
"supersedes_json": json.dumps(record.supersedes, separators=(",", ":")),
"document_id": str(record.metadata.get("document_id") or ""),
"metadata_json": json.dumps(record.metadata, ensure_ascii=False, separators=(",", ":")),
}
def _memory_hit(project_id: str, row: dict[str, Any]) -> MemoryContextItem:
metadata = dict(row.get("metadata") or {})
document = str(row.get("text") or "")
marker = "Statement: "
statement = document.split(marker, 1)[1].strip() if marker in document else document.strip()
return MemoryContextItem(
memory_id=str(row["id"]),
source="project_memory",
statement=statement,
project_id=project_id,
kind=str(metadata.get("kind") or "project_observation"),
score=_distance_score(row.get("distance")),
evidence_ids=_loads_list(metadata.get("evidence_ids_json")),
observed_at=metadata.get("observed_at") or None,
metadata={
"attribution": metadata.get("attribution"),
"confidence": metadata.get("confidence"),
"novelty_key": metadata.get("novelty_key"),
"contradicts": _loads_list(metadata.get("contradicts_json")),
"supersedes": _loads_list(metadata.get("supersedes_json")),
"record": _loads_dict(metadata.get("metadata_json")),
},
)
def _distance_score(distance: Any) -> float:
if distance is None:
return 0.0
return 1.0 / (1.0 + max(0.0, float(distance)))
def _loads_list(value: Any) -> list[str]:
if not value:
return []
try:
parsed = json.loads(str(value))
return [str(item) for item in parsed] if isinstance(parsed, list) else []
except (TypeError, ValueError, json.JSONDecodeError):
return []
def _loads_dict(value: Any) -> dict[str, Any]:
if not value:
return {}
try:
parsed = json.loads(str(value))
return dict(parsed) if isinstance(parsed, dict) else {}
except (TypeError, ValueError, json.JSONDecodeError):
return {}
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