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Add memory observability system (Phase 1)

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Implements comprehensive memory tracking for all in-memory components:

- Add MemoryTracker singleton with ComponentStats, ProcessStats, MemoryReport
- Add get_memory_stats() to CompressionStore, BatchContextStore,
  GraphStore, HNSWVectorIndex
- Add /debug/memory API endpoint for runtime monitoring

Components tracked:
- compression_store: CCR compressed tool outputs
- batch_context_store: Batch API request contexts
- graph_store: Knowledge graph entities and relationships
- vector_index: HNSW vector embeddings
- semantic_cache: Response cache
- request_logger: Request metadata

Includes 47 tests (unit + integration) with real API calls.
This commit is contained in:
chopratejas 2026-02-01 19:49:53 -08:00
parent 5e2186c42a
commit e16691dd38
9 changed files with 2243 additions and 4 deletions
Download patch file Download diff file Expand all files Collapse all files

34
headroom/cache/compression_store.py vendored
View file

@ -46,6 +46,7 @@ from typing import TYPE_CHECKING, Any
from ..relevance.bm25 import BM25Scorer
if TYPE_CHECKING:
from ..memory.tracker import ComponentStats
from .backends import CompressionStoreBackend
logger = logging.getLogger(__name__)
@ -505,6 +506,39 @@ class CompressionStore:
"backend": backend_stats,
}
def get_memory_stats(self) -> ComponentStats:
"""Get memory statistics for the MemoryTracker.
Returns:
ComponentStats with current memory usage.
"""
from ..memory.tracker import ComponentStats
with self._lock:
# Get backend stats which include bytes_used
backend_stats = self._backend.get_stats()
bytes_used = backend_stats.get("bytes_used", 0)
# Add retrieval events memory
import sys
bytes_used += sys.getsizeof(self._retrieval_events)
for event in self._retrieval_events:
bytes_used += sys.getsizeof(event)
# Add eviction heap memory
bytes_used += sys.getsizeof(self._eviction_heap)
return ComponentStats(
name="compression_store",
entry_count=self._backend.count(),
size_bytes=bytes_used,
budget_bytes=None, # No budget set yet
hits=sum(1 for _, e in self._backend.items() if e.retrieval_count > 0),
misses=0, # CompressionStore doesn't track misses directly
evictions=0, # Would need to track this separately
)
def get_retrieval_events(
self,
limit: int = 100,

50
headroom/ccr/batch_store.py
View file

@ -15,7 +15,10 @@ import asyncio
import logging
import time
from dataclasses import dataclass, field
from typing import Any
from typing import TYPE_CHECKING, Any
if TYPE_CHECKING:
from ..memory.tracker import ComponentStats
logger = logging.getLogger(__name__)
@ -234,6 +237,51 @@ class BatchContextStore:
counts[ctx.provider] = counts.get(ctx.provider, 0) + 1
return counts
def get_memory_stats(self) -> ComponentStats:
"""Get memory statistics for the MemoryTracker.
Returns:
ComponentStats with current memory usage.
"""
import sys
from ..memory.tracker import ComponentStats
# Calculate size
size_bytes = sys.getsizeof(self._contexts)
for batch_id, ctx in self._contexts.items():
size_bytes += len(batch_id)
size_bytes += sys.getsizeof(ctx)
# Add request contexts
for req_id, req in ctx.requests.items():
size_bytes += len(req_id)
size_bytes += sys.getsizeof(req)
# Messages can be large
size_bytes += sys.getsizeof(req.messages)
for msg in req.messages:
size_bytes += sys.getsizeof(msg)
for _k, v in msg.items():
if isinstance(v, str):
size_bytes += len(v)
elif isinstance(v, list):
size_bytes += sys.getsizeof(v)
# Tools
if req.tools:
size_bytes += sys.getsizeof(req.tools)
return ComponentStats(
name="batch_context_store",
entry_count=len(self._contexts),
size_bytes=size_bytes,
budget_bytes=None,
hits=0,
misses=0,
evictions=0,
)
# Global store instance
_batch_context_store: BatchContextStore | None = None

62
headroom/memory/adapters/graph.py
View file

@ -13,7 +13,7 @@ from typing import TYPE_CHECKING
from .graph_models import Entity, Relationship, RelationshipDirection, Subgraph
if TYPE_CHECKING:
pass
from ..tracker import ComponentStats
class InMemoryGraphStore:
@ -572,3 +572,63 @@ class InMemoryGraphStore:
"source_index_size": len(self._relationships_by_source),
"target_index_size": len(self._relationships_by_target),
}
def get_memory_stats(self) -> ComponentStats:
"""Get memory statistics for the MemoryTracker.
Returns:
ComponentStats with current memory usage.
"""
import sys
from ..tracker import ComponentStats
with self._lock:
# Calculate size of all data structures
size_bytes = 0
# Entities
size_bytes += sys.getsizeof(self._entities)
for entity_id, entity in self._entities.items():
size_bytes += len(entity_id)
size_bytes += sys.getsizeof(entity)
size_bytes += len(entity.id) + len(entity.user_id) + len(entity.name)
size_bytes += len(entity.entity_type)
if entity.properties:
size_bytes += sys.getsizeof(entity.properties)
# Relationships
size_bytes += sys.getsizeof(self._relationships)
for rel_id, rel in self._relationships.items():
size_bytes += len(rel_id)
size_bytes += sys.getsizeof(rel)
size_bytes += len(rel.id) + len(rel.source_id) + len(rel.target_id)
size_bytes += len(rel.relation_type)
if rel.properties:
size_bytes += sys.getsizeof(rel.properties)
# Indexes
size_bytes += sys.getsizeof(self._entities_by_user)
for user_id, entity_ids in self._entities_by_user.items():
size_bytes += len(user_id)
size_bytes += sys.getsizeof(entity_ids)
size_bytes += sys.getsizeof(self._entities_by_name)
for user_id, name_map in self._entities_by_name.items():
size_bytes += len(user_id)
size_bytes += sys.getsizeof(name_map)
size_bytes += sys.getsizeof(self._relationships_by_source)
size_bytes += sys.getsizeof(self._relationships_by_target)
entry_count = len(self._entities) + len(self._relationships)
return ComponentStats(
name="graph_store",
entry_count=entry_count,
size_bytes=size_bytes,
budget_bytes=None,
hits=0,
misses=0,
evictions=0,
)

60
headroom/memory/adapters/hnsw.py
View file

@ -91,7 +91,7 @@ def _check_hnswlib_available() -> bool:
if TYPE_CHECKING:
pass
from ..tracker import ComponentStats
@dataclass
@ -854,6 +854,64 @@ class HNSWVectorIndex:
),
}
def get_memory_stats(self) -> ComponentStats:
"""Get memory statistics for the MemoryTracker.
Returns:
ComponentStats with current memory usage.
"""
import sys
from ..tracker import ComponentStats
with self._lock:
size_bytes = 0
# ID mappings
size_bytes += sys.getsizeof(self._memory_to_hnsw)
for mem_id, hnsw_id in self._memory_to_hnsw.items():
size_bytes += len(mem_id) + sys.getsizeof(hnsw_id)
size_bytes += sys.getsizeof(self._hnsw_to_memory)
for hnsw_id, mem_id in self._hnsw_to_memory.items():
size_bytes += sys.getsizeof(hnsw_id) + len(mem_id)
# Metadata storage
size_bytes += sys.getsizeof(self._metadata)
for mem_id, meta in self._metadata.items():
size_bytes += len(mem_id)
size_bytes += sys.getsizeof(meta)
# Estimate metadata fields
if meta.content:
size_bytes += len(meta.content)
if meta.entity_refs:
size_bytes += sys.getsizeof(meta.entity_refs)
if meta.metadata:
size_bytes += sys.getsizeof(meta.metadata)
# Embeddings storage (numpy arrays)
size_bytes += sys.getsizeof(self._embeddings)
for mem_id, embedding in self._embeddings.items():
size_bytes += len(mem_id)
# numpy array size: dtype size * number of elements
size_bytes += embedding.nbytes
# HNSW index size estimate
# The actual index is in hnswlib C++ memory, so we estimate:
# Each element uses approximately: dimension * 4 bytes (float32) + M * 8 bytes (neighbors)
index_size_estimate = len(self._memory_to_hnsw) * (self._dimension * 4 + self._m * 8)
size_bytes += index_size_estimate
return ComponentStats(
name="vector_index",
entry_count=len(self._memory_to_hnsw),
size_bytes=size_bytes,
budget_bytes=None,
hits=0,
misses=0,
evictions=0,
)
def set_ef_search(self, ef_search: int) -> None:
"""Update the ef_search parameter for query time.

388
headroom/memory/tracker.py Normal file
View file

@ -0,0 +1,388 @@
"""Memory tracking infrastructure for headroom.
This module provides centralized memory tracking across all components,
enabling observability into memory usage patterns and budget enforcement.
"""
from __future__ import annotations
import sys
import threading
import time
from collections.abc import Callable
from dataclasses import dataclass, field
from typing import Any
# Try to import psutil for process memory tracking
try:
import psutil
PSUTIL_AVAILABLE = True
except ImportError:
PSUTIL_AVAILABLE = False
@dataclass
class ComponentStats:
"""Statistics for a single memory component."""
name: str
entry_count: int
size_bytes: int
budget_bytes: int | None = None
hits: int = 0
misses: int = 0
evictions: int = 0
last_updated: float = field(default_factory=time.time)
@property
def size_mb(self) -> float:
"""Size in megabytes."""
return self.size_bytes / (1024 * 1024)
@property
def budget_mb(self) -> float | None:
"""Budget in megabytes."""
return self.budget_bytes / (1024 * 1024) if self.budget_bytes else None
@property
def budget_used_percent(self) -> float | None:
"""Percentage of budget used."""
if self.budget_bytes and self.budget_bytes > 0:
return (self.size_bytes / self.budget_bytes) * 100
return None
@property
def hit_rate(self) -> float | None:
"""Cache hit rate as percentage."""
total = self.hits + self.misses
if total > 0:
return (self.hits / total) * 100
return None
def to_dict(self) -> dict[str, Any]:
"""Convert to dictionary for JSON serialization."""
return {
"name": self.name,
"entry_count": self.entry_count,
"size_bytes": self.size_bytes,
"size_mb": round(self.size_mb, 2),
"budget_bytes": self.budget_bytes,
"budget_mb": round(self.budget_mb, 2) if self.budget_mb else None,
"budget_used_percent": round(self.budget_used_percent, 2)
if self.budget_used_percent
else None,
"hits": self.hits,
"misses": self.misses,
"evictions": self.evictions,
"hit_rate": round(self.hit_rate, 2) if self.hit_rate else None,
"last_updated": self.last_updated,
}
@dataclass
class ProcessStats:
"""Process-level memory statistics."""
rss_bytes: int
vms_bytes: int
percent: float
available_bytes: int
total_bytes: int
@property
def rss_mb(self) -> float:
"""Resident set size in MB."""
return self.rss_bytes / (1024 * 1024)
@property
def vms_mb(self) -> float:
"""Virtual memory size in MB."""
return self.vms_bytes / (1024 * 1024)
@property
def available_mb(self) -> float:
"""Available system memory in MB."""
return self.available_bytes / (1024 * 1024)
@property
def total_mb(self) -> float:
"""Total system memory in MB."""
return self.total_bytes / (1024 * 1024)
def to_dict(self) -> dict[str, Any]:
"""Convert to dictionary for JSON serialization."""
return {
"rss_bytes": self.rss_bytes,
"rss_mb": round(self.rss_mb, 2),
"vms_bytes": self.vms_bytes,
"vms_mb": round(self.vms_mb, 2),
"percent": round(self.percent, 2),
"available_mb": round(self.available_mb, 2),
"total_mb": round(self.total_mb, 2),
}
@dataclass
class MemoryReport:
"""Complete memory report including process and component stats."""
process: ProcessStats
components: dict[str, ComponentStats]
total_tracked_bytes: int
target_budget_bytes: int | None
timestamp: float = field(default_factory=time.time)
@property
def total_tracked_mb(self) -> float:
"""Total tracked memory in MB."""
return self.total_tracked_bytes / (1024 * 1024)
@property
def target_budget_mb(self) -> float | None:
"""Target budget in MB."""
return self.target_budget_bytes / (1024 * 1024) if self.target_budget_bytes else None
@property
def is_over_budget(self) -> bool:
"""Check if tracked memory exceeds target budget."""
if self.target_budget_bytes:
return self.total_tracked_bytes > self.target_budget_bytes
return False
def to_dict(self) -> dict[str, Any]:
"""Convert to dictionary for JSON serialization."""
return {
"process": self.process.to_dict(),
"components": {name: stats.to_dict() for name, stats in self.components.items()},
"total_tracked_bytes": self.total_tracked_bytes,
"total_tracked_mb": round(self.total_tracked_mb, 2),
"target_budget_bytes": self.target_budget_bytes,
"target_budget_mb": round(self.target_budget_mb, 2) if self.target_budget_mb else None,
"is_over_budget": self.is_over_budget,
"timestamp": self.timestamp,
}
class MemoryTracker:
"""Singleton that tracks memory usage across all components.
Usage:
# Register a component
tracker = MemoryTracker.get()
tracker.register("my_store", my_store.get_memory_stats)
# Get all stats
report = tracker.get_report()
# Get specific component
stats = tracker.get_component_stats("my_store")
"""
_instance: MemoryTracker | None = None
_lock: threading.Lock = threading.Lock()
def __init__(self, target_budget_mb: float | None = None):
"""Initialize the tracker.
Args:
target_budget_mb: Target memory budget in MB for all tracked components.
"""
self._components: dict[str, Callable[[], ComponentStats]] = {}
self._target_budget_bytes: int | None = (
int(target_budget_mb * 1024 * 1024) if target_budget_mb else None
)
self._component_lock = threading.Lock()
@classmethod
def get(cls, target_budget_mb: float | None = None) -> MemoryTracker:
"""Get or create the singleton instance.
Args:
target_budget_mb: Target memory budget (only used on first call).
Returns:
The singleton MemoryTracker instance.
"""
if cls._instance is None:
with cls._lock:
if cls._instance is None:
cls._instance = cls(target_budget_mb=target_budget_mb)
return cls._instance
@classmethod
def reset(cls) -> None:
"""Reset the singleton instance. Useful for testing."""
with cls._lock:
cls._instance = None
def set_target_budget(self, budget_mb: float) -> None:
"""Set the target memory budget.
Args:
budget_mb: Target budget in megabytes.
"""
self._target_budget_bytes = int(budget_mb * 1024 * 1024)
def register(self, name: str, stats_fn: Callable[[], ComponentStats]) -> None:
"""Register a component's stats function.
Args:
name: Unique name for the component.
stats_fn: Function that returns ComponentStats for this component.
"""
with self._component_lock:
self._components[name] = stats_fn
def unregister(self, name: str) -> bool:
"""Unregister a component.
Args:
name: Name of the component to unregister.
Returns:
True if component was unregistered, False if not found.
"""
with self._component_lock:
if name in self._components:
del self._components[name]
return True
return False
def get_component_stats(self, name: str) -> ComponentStats | None:
"""Get stats for a specific component.
Args:
name: Name of the component.
Returns:
ComponentStats or None if component not found.
"""
with self._component_lock:
if name in self._components:
try:
return self._components[name]()
except Exception:
return None
return None
def get_all_component_stats(self) -> dict[str, ComponentStats]:
"""Get stats for all registered components.
Returns:
Dictionary mapping component names to their stats.
"""
stats: dict[str, ComponentStats] = {}
with self._component_lock:
for name, fn in self._components.items():
try:
stats[name] = fn()
except Exception:
# Skip components that fail to report stats
pass
return stats
def get_process_stats(self) -> ProcessStats:
"""Get process-level memory statistics.
Returns:
ProcessStats with current memory usage.
"""
if PSUTIL_AVAILABLE:
process = psutil.Process()
mem_info = process.memory_info()
sys_mem = psutil.virtual_memory()
return ProcessStats(
rss_bytes=mem_info.rss,
vms_bytes=mem_info.vms,
percent=process.memory_percent(),
available_bytes=sys_mem.available,
total_bytes=sys_mem.total,
)
else:
# Fallback when psutil not available
return ProcessStats(
rss_bytes=0,
vms_bytes=0,
percent=0.0,
available_bytes=0,
total_bytes=0,
)
def get_total_tracked_bytes(self) -> int:
"""Get total memory used by all tracked components.
Returns:
Total bytes used by tracked components.
"""
stats = self.get_all_component_stats()
return sum(s.size_bytes for s in stats.values())
def get_report(self) -> MemoryReport:
"""Get a complete memory report.
Returns:
MemoryReport with process and component statistics.
"""
process_stats = self.get_process_stats()
component_stats = self.get_all_component_stats()
total_tracked = sum(s.size_bytes for s in component_stats.values())
return MemoryReport(
process=process_stats,
components=component_stats,
total_tracked_bytes=total_tracked,
target_budget_bytes=self._target_budget_bytes,
)
@property
def registered_components(self) -> list[str]:
"""Get list of registered component names."""
with self._component_lock:
return list(self._components.keys())
@property
def target_budget_mb(self) -> float | None:
"""Get target budget in MB."""
return self._target_budget_bytes / (1024 * 1024) if self._target_budget_bytes else None
def estimate_object_size(obj: Any, seen: set | None = None) -> int:
"""Estimate the memory size of a Python object recursively.
This provides a rough estimate by traversing the object graph.
For more accurate measurements, use tracemalloc or memory_profiler.
Args:
obj: Object to measure.
seen: Set of already-seen object ids (for cycle detection).
Returns:
Estimated size in bytes.
"""
if seen is None:
seen = set()
obj_id = id(obj)
if obj_id in seen:
return 0
seen.add(obj_id)
size = sys.getsizeof(obj)
if isinstance(obj, dict):
size += sum(
estimate_object_size(k, seen) + estimate_object_size(v, seen) for k, v in obj.items()
)
elif isinstance(obj, (list, tuple, set, frozenset)):
size += sum(estimate_object_size(item, seen) for item in obj)
elif hasattr(obj, "__dict__"):
size += estimate_object_size(obj.__dict__, seen)
elif hasattr(obj, "__slots__"):
size += sum(
estimate_object_size(getattr(obj, slot, None), seen)
for slot in obj.__slots__
if hasattr(obj, slot)
)
return size

136
headroom/proxy/server.py
View file

@ -36,7 +36,10 @@ from collections import OrderedDict, defaultdict, deque
from dataclasses import asdict, dataclass
from datetime import datetime, timedelta
from pathlib import Path
from typing import Any, Literal
from typing import TYPE_CHECKING, Any, Literal
if TYPE_CHECKING:
from ..memory.tracker import ComponentStats, MemoryTracker
import httpx
@ -402,6 +405,37 @@ class SemanticCache:
async with self._lock:
self._cache.clear()
def get_memory_stats(self) -> ComponentStats:
"""Get memory statistics for the MemoryTracker.
Returns:
ComponentStats with current memory usage.
"""
from ..memory.tracker import ComponentStats
# Calculate size - this is sync but we access _cache directly
# Note: This is a rough estimate, not perfectly accurate under async load
size_bytes = sys.getsizeof(self._cache)
total_hits = 0
for entry in self._cache.values():
size_bytes += sys.getsizeof(entry)
size_bytes += len(entry.response_body)
size_bytes += sys.getsizeof(entry.response_headers)
for k, v in entry.response_headers.items():
size_bytes += len(k) + len(v)
total_hits += entry.hit_count
return ComponentStats(
name="semantic_cache",
entry_count=len(self._cache),
size_bytes=size_bytes,
budget_bytes=None,
hits=total_hits,
misses=0, # Would need to track this separately
evictions=0, # Would need to track this separately
)
# =============================================================================
# Rate Limiting
@ -865,6 +899,44 @@ class RequestLogger:
"log_file": str(self.log_file) if self.log_file else None,
}
def get_memory_stats(self) -> ComponentStats:
"""Get memory statistics for the MemoryTracker.
Returns:
ComponentStats with current memory usage.
"""
from ..memory.tracker import ComponentStats
# Calculate size
size_bytes = sys.getsizeof(self._logs)
for log_entry in self._logs:
size_bytes += sys.getsizeof(log_entry)
# Add string fields
if log_entry.request_id:
size_bytes += len(log_entry.request_id)
if log_entry.provider:
size_bytes += len(log_entry.provider)
if log_entry.model:
size_bytes += len(log_entry.model)
if log_entry.error:
size_bytes += len(log_entry.error)
# Messages and response can be large
if log_entry.request_messages:
size_bytes += sys.getsizeof(log_entry.request_messages)
if log_entry.response_content:
size_bytes += len(log_entry.response_content)
return ComponentStats(
name="request_logger",
entry_count=len(self._logs),
size_bytes=size_bytes,
budget_bytes=None,
hits=0,
misses=0,
evictions=0,
)
# =============================================================================
# Main Proxy
@ -5333,6 +5405,44 @@ async def _log_toin_stats_periodically(interval_seconds: int = 300) -> None:
logger.debug("Failed to log TOIN stats: %s", e)
def _register_memory_components(proxy: HeadroomProxy, tracker: MemoryTracker) -> None:
"""Register all memory-tracked components with the tracker.
This function is idempotent - it checks if components are already registered.
Args:
proxy: The HeadroomProxy instance.
tracker: The MemoryTracker instance.
"""
# Register compression store (global singleton)
if "compression_store" not in tracker.registered_components:
store = get_compression_store()
tracker.register("compression_store", store.get_memory_stats)
# Register semantic cache (instance on proxy)
if proxy.cache and "semantic_cache" not in tracker.registered_components:
tracker.register("semantic_cache", proxy.cache.get_memory_stats)
# Register request logger (instance on proxy)
if proxy.logger and "request_logger" not in tracker.registered_components:
tracker.register("request_logger", proxy.logger.get_memory_stats)
# Register batch context store (global singleton)
if "batch_context_store" not in tracker.registered_components:
try:
from ..ccr.batch_store import get_batch_context_store
batch_store = get_batch_context_store()
if hasattr(batch_store, "get_memory_stats"):
tracker.register("batch_context_store", batch_store.get_memory_stats)
except ImportError:
pass
# Note: graph_store and vector_index are created per-user within the
# LocalMemoryBackend, not as global singletons. They would need to be
# registered when the memory system is initialized with specific backends.
def create_app(config: ProxyConfig | None = None) -> FastAPI:
"""Create FastAPI application."""
if not FASTAPI_AVAILABLE:
@ -5508,6 +5618,30 @@ def create_app(config: ProxyConfig | None = None) -> FastAPI:
media_type="text/plain; version=0.0.4",
)
# Debug endpoints
@app.get("/debug/memory")
async def debug_memory():
"""Get detailed memory usage statistics.
Returns memory usage for all tracked components including:
- Process-level memory (RSS, VMS, percent)
- Per-component memory usage and budgets
- Cache hit/miss statistics
- Total tracked vs target budget
This endpoint is useful for debugging memory issues and
monitoring memory budgets.
"""
from ..memory.tracker import MemoryTracker
tracker = MemoryTracker.get()
# Register components if not already registered
_register_memory_components(proxy, tracker)
report = tracker.get_report()
return report.to_dict()
@app.post("/cache/clear")
async def clear_cache():
"""Clear the response cache."""

399
tests/test_memory_tracker.py Normal file
View file

@ -0,0 +1,399 @@
"""Tests for memory tracking functionality.
These tests verify that the MemoryTracker correctly tracks memory usage
across all components without mocks or simulations.
"""
from __future__ import annotations
import sys
import pytest
from headroom.memory.tracker import (
ComponentStats,
MemoryReport,
MemoryTracker,
ProcessStats,
estimate_object_size,
)
class TestComponentStats:
"""Tests for ComponentStats dataclass."""
def test_basic_properties(self):
"""Test basic property calculations."""
stats = ComponentStats(
name="test_store",
entry_count=100,
size_bytes=1024 * 1024, # 1 MB
budget_bytes=2 * 1024 * 1024, # 2 MB
hits=80,
misses=20,
evictions=5,
)
assert stats.name == "test_store"
assert stats.entry_count == 100
assert stats.size_mb == 1.0
assert stats.budget_mb == 2.0
assert stats.budget_used_percent == 50.0
assert stats.hit_rate == 80.0
def test_no_budget(self):
"""Test when no budget is set."""
stats = ComponentStats(
name="test_store",
entry_count=100,
size_bytes=1024 * 1024,
budget_bytes=None,
)
assert stats.budget_mb is None
assert stats.budget_used_percent is None
def test_no_hits_misses(self):
"""Test when no hits or misses recorded."""
stats = ComponentStats(
name="test_store",
entry_count=100,
size_bytes=1024,
hits=0,
misses=0,
)
assert stats.hit_rate is None
def test_to_dict(self):
"""Test serialization to dictionary."""
stats = ComponentStats(
name="test_store",
entry_count=100,
size_bytes=1024 * 1024,
budget_bytes=2 * 1024 * 1024,
hits=80,
misses=20,
evictions=5,
)
d = stats.to_dict()
assert d["name"] == "test_store"
assert d["entry_count"] == 100
assert d["size_bytes"] == 1024 * 1024
assert d["size_mb"] == 1.0
assert d["budget_mb"] == 2.0
assert d["budget_used_percent"] == 50.0
assert d["hit_rate"] == 80.0
class TestProcessStats:
"""Tests for ProcessStats dataclass."""
def test_basic_properties(self):
"""Test basic property calculations."""
stats = ProcessStats(
rss_bytes=500 * 1024 * 1024, # 500 MB
vms_bytes=1024 * 1024 * 1024, # 1 GB
percent=5.0,
available_bytes=8 * 1024 * 1024 * 1024, # 8 GB
total_bytes=16 * 1024 * 1024 * 1024, # 16 GB
)
assert stats.rss_mb == 500.0
assert stats.vms_mb == 1024.0
assert stats.percent == 5.0
assert stats.available_mb == 8192.0
assert stats.total_mb == 16384.0
def test_to_dict(self):
"""Test serialization to dictionary."""
stats = ProcessStats(
rss_bytes=500 * 1024 * 1024,
vms_bytes=1024 * 1024 * 1024,
percent=5.0,
available_bytes=8 * 1024 * 1024 * 1024,
total_bytes=16 * 1024 * 1024 * 1024,
)
d = stats.to_dict()
assert d["rss_mb"] == 500.0
assert d["vms_mb"] == 1024.0
assert d["percent"] == 5.0
class TestMemoryTracker:
"""Tests for MemoryTracker singleton."""
@pytest.fixture(autouse=True)
def reset_tracker(self):
"""Reset the tracker singleton before each test."""
MemoryTracker.reset()
yield
MemoryTracker.reset()
def test_singleton_pattern(self):
"""Test that MemoryTracker is a singleton."""
tracker1 = MemoryTracker.get()
tracker2 = MemoryTracker.get()
assert tracker1 is tracker2
def test_reset(self):
"""Test singleton reset."""
tracker1 = MemoryTracker.get()
MemoryTracker.reset()
tracker2 = MemoryTracker.get()
assert tracker1 is not tracker2
def test_register_component(self):
"""Test registering a component."""
tracker = MemoryTracker.get()
def get_stats() -> ComponentStats:
return ComponentStats(
name="test_component",
entry_count=10,
size_bytes=1024,
)
tracker.register("test_component", get_stats)
assert "test_component" in tracker.registered_components
def test_unregister_component(self):
"""Test unregistering a component."""
tracker = MemoryTracker.get()
def get_stats() -> ComponentStats:
return ComponentStats(
name="test_component",
entry_count=10,
size_bytes=1024,
)
tracker.register("test_component", get_stats)
assert "test_component" in tracker.registered_components
result = tracker.unregister("test_component")
assert result is True
assert "test_component" not in tracker.registered_components
# Unregistering non-existent component returns False
result = tracker.unregister("non_existent")
assert result is False
def test_get_component_stats(self):
"""Test getting stats for a specific component."""
tracker = MemoryTracker.get()
def get_stats() -> ComponentStats:
return ComponentStats(
name="test_component",
entry_count=42,
size_bytes=2048,
)
tracker.register("test_component", get_stats)
stats = tracker.get_component_stats("test_component")
assert stats is not None
assert stats.name == "test_component"
assert stats.entry_count == 42
assert stats.size_bytes == 2048
def test_get_component_stats_not_found(self):
"""Test getting stats for non-existent component."""
tracker = MemoryTracker.get()
stats = tracker.get_component_stats("non_existent")
assert stats is None
def test_get_all_component_stats(self):
"""Test getting stats for all components."""
tracker = MemoryTracker.get()
def get_stats_a() -> ComponentStats:
return ComponentStats(name="component_a", entry_count=10, size_bytes=1024)
def get_stats_b() -> ComponentStats:
return ComponentStats(name="component_b", entry_count=20, size_bytes=2048)
tracker.register("component_a", get_stats_a)
tracker.register("component_b", get_stats_b)
all_stats = tracker.get_all_component_stats()
assert len(all_stats) == 2
assert "component_a" in all_stats
assert "component_b" in all_stats
assert all_stats["component_a"].entry_count == 10
assert all_stats["component_b"].entry_count == 20
def test_get_process_stats(self):
"""Test getting process-level stats."""
tracker = MemoryTracker.get()
stats = tracker.get_process_stats()
# Should return ProcessStats (may be zero if psutil not available)
assert isinstance(stats, ProcessStats)
assert stats.rss_bytes >= 0
assert stats.vms_bytes >= 0
def test_get_total_tracked_bytes(self):
"""Test getting total tracked bytes."""
tracker = MemoryTracker.get()
def get_stats_a() -> ComponentStats:
return ComponentStats(name="a", entry_count=10, size_bytes=1000)
def get_stats_b() -> ComponentStats:
return ComponentStats(name="b", entry_count=20, size_bytes=2000)
tracker.register("a", get_stats_a)
tracker.register("b", get_stats_b)
total = tracker.get_total_tracked_bytes()
assert total == 3000
def test_get_report(self):
"""Test getting full memory report."""
tracker = MemoryTracker.get(target_budget_mb=100.0)
def get_stats() -> ComponentStats:
return ComponentStats(name="test", entry_count=10, size_bytes=50 * 1024 * 1024)
tracker.register("test", get_stats)
report = tracker.get_report()
assert isinstance(report, MemoryReport)
assert isinstance(report.process, ProcessStats)
assert "test" in report.components
assert report.total_tracked_bytes == 50 * 1024 * 1024
assert report.target_budget_bytes == 100 * 1024 * 1024
assert report.is_over_budget is False
def test_is_over_budget(self):
"""Test budget checking."""
tracker = MemoryTracker.get(target_budget_mb=10.0) # 10 MB budget
def get_stats() -> ComponentStats:
return ComponentStats(
name="large", entry_count=10, size_bytes=20 * 1024 * 1024
) # 20 MB
tracker.register("large", get_stats)
report = tracker.get_report()
assert report.is_over_budget is True
def test_set_target_budget(self):
"""Test setting target budget after creation."""
tracker = MemoryTracker.get()
assert tracker.target_budget_mb is None
tracker.set_target_budget(500.0)
assert tracker.target_budget_mb == 500.0
class TestEstimateObjectSize:
"""Tests for the estimate_object_size utility function."""
def test_simple_types(self):
"""Test size estimation for simple types."""
# Integer
int_size = estimate_object_size(42)
assert int_size == sys.getsizeof(42)
# String
s = "hello world"
str_size = estimate_object_size(s)
assert str_size == sys.getsizeof(s)
def test_dict(self):
"""Test size estimation for dictionaries."""
d = {"a": 1, "b": 2, "c": 3}
size = estimate_object_size(d)
# Size should be at least the base dict size
assert size >= sys.getsizeof(d)
# Size should include keys and values
assert size > sys.getsizeof({})
def test_list(self):
"""Test size estimation for lists."""
lst = [1, 2, 3, "hello", "world"]
size = estimate_object_size(lst)
assert size >= sys.getsizeof(lst)
assert size > sys.getsizeof([])
def test_nested_structure(self):
"""Test size estimation for nested structures."""
nested = {
"items": [{"id": 1, "name": "first"}, {"id": 2, "name": "second"}],
"metadata": {"count": 2, "tags": ["a", "b", "c"]},
}
size = estimate_object_size(nested)
# Should be larger than just the outer dict
assert size > sys.getsizeof(nested)
def test_circular_reference(self):
"""Test that circular references don't cause infinite loop."""
d: dict = {"a": 1}
d["self"] = d # Circular reference
# Should not hang or crash
size = estimate_object_size(d)
assert size > 0
class TestMemoryReportSerialization:
"""Tests for MemoryReport serialization."""
def test_to_dict(self):
"""Test that MemoryReport serializes correctly."""
process = ProcessStats(
rss_bytes=100 * 1024 * 1024,
vms_bytes=200 * 1024 * 1024,
percent=1.0,
available_bytes=8 * 1024 * 1024 * 1024,
total_bytes=16 * 1024 * 1024 * 1024,
)
components = {
"store_a": ComponentStats(name="store_a", entry_count=100, size_bytes=10 * 1024 * 1024),
"store_b": ComponentStats(name="store_b", entry_count=200, size_bytes=20 * 1024 * 1024),
}
report = MemoryReport(
process=process,
components=components,
total_tracked_bytes=30 * 1024 * 1024,
target_budget_bytes=50 * 1024 * 1024,
)
d = report.to_dict()
assert "process" in d
assert "components" in d
assert "total_tracked_mb" in d
assert "target_budget_mb" in d
assert "is_over_budget" in d
assert d["process"]["rss_mb"] == 100.0
assert d["total_tracked_mb"] == 30.0
assert d["target_budget_mb"] == 50.0
assert d["is_over_budget"] is False

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"""Integration tests for memory tracking with real stores.
These tests verify that memory tracking works correctly with actual
store implementations - no mocks, no simulations.
"""
from __future__ import annotations
import pytest
from headroom.memory.tracker import MemoryTracker
class TestCompressionStoreMemoryTracking:
"""Tests for CompressionStore memory tracking integration."""
@pytest.fixture(autouse=True)
def reset_tracker(self):
"""Reset the tracker singleton before each test."""
MemoryTracker.reset()
yield
MemoryTracker.reset()
def test_compression_store_reports_memory_stats(self):
"""Test that CompressionStore correctly reports memory stats."""
from headroom.cache.compression_store import CompressionStore
store = CompressionStore(max_entries=100)
# Add some data - store(original, compressed, ...)
store.store("original content 1" * 100, "compressed1")
store.store("original content 2" * 100, "compressed2")
stats = store.get_memory_stats()
assert stats.name == "compression_store"
assert stats.entry_count == 2
assert stats.size_bytes > 0
# budget_bytes is None since CompressionStore uses entry count limit not byte limit
def test_compression_store_tracks_hits(self):
"""Test that CompressionStore tracks cache hits."""
from headroom.cache.compression_store import CompressionStore
store = CompressionStore(max_entries=100)
# Store and retrieve (hit)
hash_key = store.store("original content", "compressed")
store.retrieve(hash_key) # Hit - increments retrieval_count
store.retrieve(hash_key) # Another retrieval
store.retrieve("nonexistent_hash") # Miss (not tracked)
stats = store.get_memory_stats()
# Hits counts entries with retrieval_count > 0, not total retrievals
assert stats.hits == 1 # 1 entry has been retrieved
# CompressionStore doesn't track misses
assert stats.misses == 0
def test_compression_store_registers_with_tracker(self):
"""Test that CompressionStore can register with MemoryTracker."""
from headroom.cache.compression_store import CompressionStore
tracker = MemoryTracker.get()
store = CompressionStore(max_entries=100)
# Register the store
tracker.register("compression_store", store.get_memory_stats)
# Verify it's registered
assert "compression_store" in tracker.registered_components
# Get stats through tracker
stats = tracker.get_component_stats("compression_store")
assert stats is not None
assert stats.name == "compression_store"
class TestBatchContextStoreMemoryTracking:
"""Tests for BatchContextStore memory tracking integration."""
@pytest.fixture(autouse=True)
def reset_tracker(self):
"""Reset the tracker singleton before each test."""
MemoryTracker.reset()
yield
MemoryTracker.reset()
def test_batch_context_store_reports_memory_stats(self):
"""Test that BatchContextStore correctly reports memory stats."""
from headroom.ccr.batch_store import (
BatchContext,
BatchContextStore,
BatchRequestContext,
)
store = BatchContextStore(ttl=3600, max_contexts=100)
# Add some batch contexts
ctx1 = BatchContext(batch_id="batch_1", provider="anthropic")
ctx1.add_request(
BatchRequestContext(
custom_id="req_1",
messages=[{"role": "user", "content": "Hello world"}],
model="claude-3-opus",
)
)
ctx2 = BatchContext(batch_id="batch_2", provider="openai")
ctx2.add_request(
BatchRequestContext(
custom_id="req_2",
messages=[{"role": "user", "content": "Test message"}],
model="gpt-4",
)
)
# Store them (sync for testing - accessing internal dict)
store._contexts["batch_1"] = ctx1
store._contexts["batch_2"] = ctx2
stats = store.get_memory_stats()
assert stats.name == "batch_context_store"
assert stats.entry_count == 2
assert stats.size_bytes > 0
def test_batch_context_store_registers_with_tracker(self):
"""Test that BatchContextStore can register with MemoryTracker."""
from headroom.ccr.batch_store import BatchContextStore
tracker = MemoryTracker.get()
store = BatchContextStore()
# Register the store
tracker.register("batch_context_store", store.get_memory_stats)
# Verify it's registered
assert "batch_context_store" in tracker.registered_components
class TestGraphStoreMemoryTracking:
"""Tests for InMemoryGraphStore memory tracking integration."""
@pytest.fixture(autouse=True)
def reset_tracker(self):
"""Reset the tracker singleton before each test."""
MemoryTracker.reset()
yield
MemoryTracker.reset()
@pytest.mark.asyncio
async def test_graph_store_reports_memory_stats(self):
"""Test that InMemoryGraphStore correctly reports memory stats."""
from headroom.memory.adapters.graph import InMemoryGraphStore
from headroom.memory.adapters.graph_models import Entity, Relationship
store = InMemoryGraphStore()
# Add some entities using the correct API
entity1 = Entity(id="node1", user_id="test", name="Test Entity 1", entity_type="entity")
entity2 = Entity(id="node2", user_id="test", name="Test Entity 2", entity_type="entity")
entity3 = Entity(id="node3", user_id="test", name="Test Concept", entity_type="concept")
await store.add_entity(entity1)
await store.add_entity(entity2)
await store.add_entity(entity3)
# Add a relationship
rel = Relationship(
source_id="node1",
target_id="node2",
relation_type="related_to",
user_id="test",
)
await store.add_relationship(rel)
stats = store.get_memory_stats()
assert stats.name == "graph_store"
assert stats.entry_count == 4 # 3 entities + 1 relationship
assert stats.size_bytes > 0
@pytest.mark.asyncio
async def test_graph_store_size_grows_with_data(self):
"""Test that reported size grows as data is added."""
from headroom.memory.adapters.graph import InMemoryGraphStore
from headroom.memory.adapters.graph_models import Entity
store = InMemoryGraphStore()
# Get initial size
initial_stats = store.get_memory_stats()
initial_size = initial_stats.size_bytes
# Add data
for i in range(100):
entity = Entity(
id=f"node_{i}",
user_id="test",
name=f"Entity {i}",
entity_type="entity",
properties={"data": "x" * 100},
)
await store.add_entity(entity)
# Get new size
final_stats = store.get_memory_stats()
assert final_stats.size_bytes > initial_size
assert final_stats.entry_count == 100
class TestHNSWVectorIndexMemoryTracking:
"""Tests for HNSWVectorIndex memory tracking integration."""
@pytest.fixture(autouse=True)
def reset_tracker(self):
"""Reset the tracker singleton before each test."""
MemoryTracker.reset()
yield
MemoryTracker.reset()
@pytest.mark.asyncio
async def test_hnsw_index_reports_memory_stats(self):
"""Test that HNSWVectorIndex correctly reports memory stats."""
from headroom.memory.adapters.hnsw import HNSWVectorIndex
from headroom.memory.models import Memory
index = HNSWVectorIndex(dimension=128)
# Add some vectors using Memory objects
import numpy as np
for i in range(10):
embedding = np.random.rand(128).astype(np.float32).tolist()
memory = Memory(
id=f"mem_{i}",
content=f"Test memory {i}",
user_id="test_user",
embedding=embedding,
)
await index.index(memory)
stats = index.get_memory_stats()
assert stats.name == "vector_index"
assert stats.entry_count == 10
assert stats.size_bytes > 0
@pytest.mark.asyncio
async def test_hnsw_index_size_grows_with_vectors(self):
"""Test that reported size grows as vectors are added."""
from headroom.memory.adapters.hnsw import HNSWVectorIndex
from headroom.memory.models import Memory
index = HNSWVectorIndex(dimension=256)
# Get initial size
initial_stats = index.get_memory_stats()
initial_size = initial_stats.size_bytes
# Add vectors
import numpy as np
for i in range(100):
embedding = np.random.rand(256).astype(np.float32).tolist()
memory = Memory(
id=f"mem_{i}",
content=f"Test memory {i}",
user_id="test_user",
embedding=embedding,
)
await index.index(memory)
# Get new size
final_stats = index.get_memory_stats()
assert final_stats.size_bytes > initial_size
assert final_stats.entry_count == 100
class TestTrackerIntegrationWithMultipleStores:
"""Tests for MemoryTracker with multiple real stores."""
@pytest.fixture(autouse=True)
def reset_tracker(self):
"""Reset the tracker singleton before each test."""
MemoryTracker.reset()
yield
MemoryTracker.reset()
@pytest.mark.asyncio
async def test_tracker_aggregates_multiple_stores(self):
"""Test that tracker correctly aggregates stats from multiple stores."""
from headroom.cache.compression_store import CompressionStore
from headroom.ccr.batch_store import BatchContextStore
from headroom.memory.adapters.graph import InMemoryGraphStore
from headroom.memory.adapters.graph_models import Entity
tracker = MemoryTracker.get()
# Create stores
compression_store = CompressionStore(max_entries=100)
batch_store = BatchContextStore()
graph_store = InMemoryGraphStore()
# Add some data
compression_store.store("original content" * 50, "compressed")
entity = Entity(id="node1", user_id="test", name="Test", entity_type="entity")
await graph_store.add_entity(entity)
# Register all stores
tracker.register("compression_store", compression_store.get_memory_stats)
tracker.register("batch_context_store", batch_store.get_memory_stats)
tracker.register("graph_store", graph_store.get_memory_stats)
# Get total
total = tracker.get_total_tracked_bytes()
# Should be sum of all stores
cs_stats = compression_store.get_memory_stats()
bs_stats = batch_store.get_memory_stats()
gs_stats = graph_store.get_memory_stats()
expected_total = cs_stats.size_bytes + bs_stats.size_bytes + gs_stats.size_bytes
assert total == expected_total
@pytest.mark.asyncio
async def test_full_memory_report(self):
"""Test generating a full memory report with real stores."""
from headroom.cache.compression_store import CompressionStore
from headroom.memory.adapters.graph import InMemoryGraphStore
from headroom.memory.adapters.graph_models import Entity
tracker = MemoryTracker.get(target_budget_mb=100.0)
# Create and register stores
compression_store = CompressionStore(max_entries=1000)
graph_store = InMemoryGraphStore()
# Add data
for i in range(10):
compression_store.store(f"original content {i}" * 100, f"compressed_{i}")
entity = Entity(
id=f"node_{i}",
user_id="test",
name=f"Entity {i}",
entity_type="entity",
)
await graph_store.add_entity(entity)
tracker.register("compression_store", compression_store.get_memory_stats)
tracker.register("graph_store", graph_store.get_memory_stats)
# Get full report
report = tracker.get_report()
# Verify report structure
assert report.process is not None
assert report.process.rss_bytes >= 0
assert len(report.components) == 2
assert "compression_store" in report.components
assert "graph_store" in report.components
assert report.total_tracked_bytes > 0
assert report.target_budget_bytes == 100 * 1024 * 1024
# Verify serialization
d = report.to_dict()
assert "process" in d
assert "components" in d
assert "total_tracked_mb" in d
class TestMemoryBudgetEnforcement:
"""Tests for memory budget checking."""
@pytest.fixture(autouse=True)
def reset_tracker(self):
"""Reset the tracker singleton before each test."""
MemoryTracker.reset()
yield
MemoryTracker.reset()
def test_under_budget(self):
"""Test that under-budget is correctly detected."""
from headroom.cache.compression_store import CompressionStore
tracker = MemoryTracker.get(target_budget_mb=100.0) # 100 MB budget
store = CompressionStore(max_entries=10) # Small store
store.store("original", "compressed")
tracker.register("compression_store", store.get_memory_stats)
report = tracker.get_report()
# Small store should be under budget
assert report.is_over_budget is False
def test_over_budget_detection(self):
"""Test that over-budget is correctly detected."""
tracker = MemoryTracker.get(target_budget_mb=0.001) # Very small budget (1 KB)
# Create a component that reports large size
from headroom.memory.tracker import ComponentStats
def large_component_stats() -> ComponentStats:
return ComponentStats(
name="large_component",
entry_count=1000,
size_bytes=10 * 1024 * 1024, # 10 MB
)
tracker.register("large_component", large_component_stats)
report = tracker.get_report()
# Should be over budget
assert report.is_over_budget is True
class TestProcessStatsCollection:
"""Tests for process-level memory stats."""
@pytest.fixture(autouse=True)
def reset_tracker(self):
"""Reset the tracker singleton before each test."""
MemoryTracker.reset()
yield
MemoryTracker.reset()
def test_process_stats_collected(self):
"""Test that process stats are collected from the real process."""
tracker = MemoryTracker.get()
stats = tracker.get_process_stats()
# Should have real values from the current process
assert stats.rss_bytes > 0 # Process must use some memory
assert stats.vms_bytes > 0
assert stats.percent >= 0 # Could be 0 on some systems
def test_process_stats_in_report(self):
"""Test that process stats are included in report."""
tracker = MemoryTracker.get()
report = tracker.get_report()
assert report.process.rss_bytes > 0
assert report.process.rss_mb > 0

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"""Comprehensive integration tests for memory tracking with real components.
These tests exercise the full system including:
- Memory system (GraphStore, HNSWVectorIndex)
- CCR (Compress-Cache-Retrieve)
- Compression store
- Real API calls through the proxy
Tests track memory usage throughout to verify our tracking is accurate.
Requirements:
- ANTHROPIC_API_KEY in .env
- Run with: uv run pytest tests/test_memory_usage_integration.py -v -s
"""
from __future__ import annotations
import os
import pytest
# Load .env file
from dotenv import load_dotenv
load_dotenv()
def get_process_memory_mb() -> float:
"""Get current process memory in MB."""
import psutil
return psutil.Process(os.getpid()).memory_info().rss / 1024 / 1024
def get_tracked_memory() -> dict:
"""Get memory stats from the tracker."""
from headroom.memory.tracker import MemoryTracker
tracker = MemoryTracker.get()
report = tracker.get_report()
return report.to_dict()
class TestMemorySystemIntegration:
"""Tests for the memory system (GraphStore + HNSWVectorIndex)."""
@pytest.fixture(autouse=True)
def reset_tracker(self):
"""Reset the tracker singleton before each test."""
from headroom.memory.tracker import MemoryTracker
MemoryTracker.reset()
yield
MemoryTracker.reset()
@pytest.mark.asyncio
async def test_graph_store_memory_growth(self):
"""Test that graph store memory is tracked as entities are added."""
from headroom.memory.adapters.graph import InMemoryGraphStore
from headroom.memory.adapters.graph_models import Entity, Relationship
from headroom.memory.tracker import MemoryTracker
tracker = MemoryTracker.get()
store = InMemoryGraphStore()
tracker.register("graph_store", store.get_memory_stats)
print("\n=== Graph Store Memory Growth Test ===")
# Track memory at each stage
memory_snapshots = []
# Initial state
stats = store.get_memory_stats()
memory_snapshots.append(("initial", stats.entry_count, stats.size_bytes))
print(f"Initial: {stats.entry_count} entries, {stats.size_bytes} bytes")
# Add 100 entities
for i in range(100):
entity = Entity(
id=f"entity_{i}",
user_id="test_user",
name=f"Test Entity {i}",
entity_type="concept",
description=f"This is a detailed description for entity {i} " * 10,
properties={"index": i, "data": "x" * 200},
)
await store.add_entity(entity)
stats = store.get_memory_stats()
memory_snapshots.append(("100 entities", stats.entry_count, stats.size_bytes))
print(f"After 100 entities: {stats.entry_count} entries, {stats.size_bytes} bytes")
# Add 200 relationships
for i in range(200):
rel = Relationship(
id=f"rel_{i}",
user_id="test_user",
source_id=f"entity_{i % 100}",
target_id=f"entity_{(i + 1) % 100}",
relation_type="related_to",
properties={"weight": 0.5, "metadata": "y" * 100},
)
await store.add_relationship(rel)
stats = store.get_memory_stats()
memory_snapshots.append(("+ 200 relationships", stats.entry_count, stats.size_bytes))
print(f"After 200 relationships: {stats.entry_count} entries, {stats.size_bytes} bytes")
# Verify memory grew
assert memory_snapshots[1][2] > memory_snapshots[0][2], (
"Memory should grow after adding entities"
)
assert memory_snapshots[2][2] > memory_snapshots[1][2], (
"Memory should grow after adding relationships"
)
# Verify tracker reports correctly
report = tracker.get_report()
assert "graph_store" in report.components
assert (
report.components["graph_store"].entry_count == 300
) # 100 entities + 200 relationships
print(f"\nTotal tracked memory: {report.total_tracked_mb:.4f} MB")
print(f"Process RSS: {report.process.rss_mb:.1f} MB")
@pytest.mark.asyncio
async def test_hnsw_vector_index_memory_growth(self):
"""Test that HNSW vector index memory is tracked as vectors are added."""
from headroom.memory.adapters.hnsw import HNSWVectorIndex
from headroom.memory.models import Memory
from headroom.memory.tracker import MemoryTracker
tracker = MemoryTracker.get()
# Use 384 dimensions (common for MiniLM embeddings)
index = HNSWVectorIndex(dimension=384)
tracker.register("vector_index", index.get_memory_stats)
print("\n=== HNSW Vector Index Memory Growth Test ===")
import numpy as np
# Track memory at each stage
memory_snapshots = []
# Initial state
stats = index.get_memory_stats()
memory_snapshots.append(("initial", stats.entry_count, stats.size_bytes))
print(f"Initial: {stats.entry_count} entries, {stats.size_bytes} bytes")
# Add 100 vectors
for i in range(100):
embedding = np.random.rand(384).astype(np.float32).tolist()
memory = Memory(
id=f"mem_{i}",
content=f"This is memory content {i} with some additional text " * 5,
user_id="test_user",
embedding=embedding,
importance=0.5 + (i % 10) / 20,
)
await index.index(memory)
stats = index.get_memory_stats()
memory_snapshots.append(("100 vectors", stats.entry_count, stats.size_bytes))
print(f"After 100 vectors: {stats.entry_count} entries, {stats.size_bytes} bytes")
# Add 400 more vectors
for i in range(100, 500):
embedding = np.random.rand(384).astype(np.float32).tolist()
memory = Memory(
id=f"mem_{i}",
content=f"This is memory content {i} with some additional text " * 5,
user_id="test_user",
embedding=embedding,
)
await index.index(memory)
stats = index.get_memory_stats()
memory_snapshots.append(("500 vectors", stats.entry_count, stats.size_bytes))
print(f"After 500 vectors: {stats.entry_count} entries, {stats.size_bytes} bytes")
# Verify memory grew
assert memory_snapshots[1][2] > memory_snapshots[0][2], (
"Memory should grow after adding vectors"
)
assert memory_snapshots[2][2] > memory_snapshots[1][2], (
"Memory should grow with more vectors"
)
# Verify tracker reports correctly
report = tracker.get_report()
assert "vector_index" in report.components
assert report.components["vector_index"].entry_count == 500
print(f"\nTotal tracked memory: {report.total_tracked_mb:.4f} MB")
print(f"Process RSS: {report.process.rss_mb:.1f} MB")
class TestCCRIntegration:
"""Tests for CCR (Compress-Cache-Retrieve) memory tracking."""
@pytest.fixture(autouse=True)
def reset_stores(self):
"""Reset stores before each test."""
from headroom.ccr.batch_store import reset_batch_context_store
from headroom.memory.tracker import MemoryTracker
MemoryTracker.reset()
reset_batch_context_store()
yield
MemoryTracker.reset()
reset_batch_context_store()
def test_compression_store_memory_growth(self):
"""Test that compression store memory is tracked correctly."""
from headroom.cache.compression_store import CompressionStore
from headroom.memory.tracker import MemoryTracker
tracker = MemoryTracker.get()
store = CompressionStore(max_entries=1000, default_ttl=3600)
tracker.register("compression_store", store.get_memory_stats)
print("\n=== Compression Store Memory Growth Test ===")
memory_snapshots = []
# Initial state
stats = store.get_memory_stats()
memory_snapshots.append(("initial", stats.entry_count, stats.size_bytes))
print(f"Initial: {stats.entry_count} entries, {stats.size_bytes} bytes")
# Add compressed content (simulating tool outputs)
for i in range(50):
original = f"Original tool output {i}: " + "data " * 500
compressed = f"Compressed {i}: " + "data " * 50
store.store(
original=original,
compressed=compressed,
original_tokens=len(original.split()),
compressed_tokens=len(compressed.split()),
tool_name=f"tool_{i % 5}",
)
stats = store.get_memory_stats()
memory_snapshots.append(("50 entries", stats.entry_count, stats.size_bytes))
print(f"After 50 entries: {stats.entry_count} entries, {stats.size_bytes} bytes")
# Add more with larger content
for i in range(50, 150):
original = f"Large tool output {i}: " + "data " * 2000
compressed = f"Compressed {i}: " + "data " * 200
store.store(
original=original,
compressed=compressed,
original_tokens=len(original.split()),
compressed_tokens=len(compressed.split()),
tool_name=f"tool_{i % 5}",
)
stats = store.get_memory_stats()
memory_snapshots.append(("150 entries", stats.entry_count, stats.size_bytes))
print(f"After 150 entries: {stats.entry_count} entries, {stats.size_bytes} bytes")
# Verify memory grew
assert memory_snapshots[1][2] > memory_snapshots[0][2]
assert memory_snapshots[2][2] > memory_snapshots[1][2]
# Test retrieval (should register hits)
# Get a key from the first entry
first_key = store.store("test original", "test compressed")
store.retrieve(first_key)
store.retrieve(first_key)
store.retrieve("nonexistent")
stats = store.get_memory_stats()
print(f"\nAfter retrievals - Hits: {stats.hits}, Misses: {stats.misses}")
report = tracker.get_report()
print(f"Total tracked memory: {report.total_tracked_mb:.4f} MB")
def test_batch_context_store_memory_growth(self):
"""Test that batch context store memory is tracked correctly."""
from headroom.ccr.batch_store import (
BatchContext,
BatchContextStore,
BatchRequestContext,
)
from headroom.memory.tracker import MemoryTracker
tracker = MemoryTracker.get()
store = BatchContextStore(ttl=3600, max_contexts=1000)
tracker.register("batch_context_store", store.get_memory_stats)
print("\n=== Batch Context Store Memory Growth Test ===")
memory_snapshots = []
# Initial state
stats = store.get_memory_stats()
memory_snapshots.append(("initial", stats.entry_count, stats.size_bytes))
print(f"Initial: {stats.entry_count} entries, {stats.size_bytes} bytes")
# Add batch contexts (simulating batch API submissions)
for batch_num in range(20):
ctx = BatchContext(
batch_id=f"batch_{batch_num}",
provider="anthropic",
)
# Each batch has multiple requests
for req_num in range(10):
ctx.add_request(
BatchRequestContext(
custom_id=f"req_{batch_num}_{req_num}",
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": f"Request {req_num}: " + "context " * 100},
],
model="claude-sonnet-4-20250514",
tools=[
{
"name": "search",
"description": "Search the web",
"input_schema": {"type": "object", "properties": {}},
}
],
)
)
# Store directly (bypassing async for testing)
store._contexts[ctx.batch_id] = ctx
stats = store.get_memory_stats()
memory_snapshots.append(("20 batches", stats.entry_count, stats.size_bytes))
print(
f"After 20 batches (200 requests): {stats.entry_count} entries, {stats.size_bytes} bytes"
)
# Verify memory grew
assert memory_snapshots[1][2] > memory_snapshots[0][2]
report = tracker.get_report()
print(f"Total tracked memory: {report.total_tracked_mb:.4f} MB")
@pytest.mark.skipif(
not os.environ.get("ANTHROPIC_API_KEY"),
reason="ANTHROPIC_API_KEY not set in environment",
)
class TestProxyMemoryIntegration:
"""Tests that exercise the proxy with real API calls and track memory."""
@pytest.fixture
def api_key(self):
"""Get API key from environment."""
return os.environ.get("ANTHROPIC_API_KEY")
@pytest.fixture(autouse=True)
def reset_tracker(self):
"""Reset the tracker singleton before each test."""
from headroom.memory.tracker import MemoryTracker
MemoryTracker.reset()
yield
MemoryTracker.reset()
def test_real_api_calls_memory_tracking(self, api_key):
"""Test memory tracking with real API calls."""
import httpx
from headroom.memory.tracker import MemoryTracker
tracker = MemoryTracker.get()
print("\n=== Real API Calls Memory Tracking Test ===")
# Note: This test requires a running proxy
# We'll test the components directly instead
# Create and register stores
from headroom.cache.compression_store import CompressionStore
from headroom.ccr.batch_store import BatchContextStore
compression_store = CompressionStore(max_entries=100)
batch_store = BatchContextStore()
tracker.register("compression_store", compression_store.get_memory_stats)
tracker.register("batch_context_store", batch_store.get_memory_stats)
initial_report = tracker.get_report()
print(f"Initial tracked: {initial_report.total_tracked_mb:.4f} MB")
print(f"Initial RSS: {initial_report.process.rss_mb:.1f} MB")
# Make real API call using httpx directly
headers = {
"x-api-key": api_key,
"anthropic-version": "2023-06-01",
"content-type": "application/json",
}
messages_list = [
[{"role": "user", "content": f"Say 'test {i}' and nothing else."}] for i in range(3)
]
with httpx.Client(timeout=60.0) as client:
for i, messages in enumerate(messages_list):
response = client.post(
"https://api.anthropic.com/v1/messages",
headers=headers,
json={
"model": "claude-sonnet-4-20250514",
"max_tokens": 50,
"messages": messages,
},
)
assert response.status_code == 200, f"API call failed: {response.text}"
# Simulate storing compressed response (as CCR would)
response_text = response.text
compression_store.store(
original=response_text,
compressed=response_text[:100], # Simulated compression
tool_name="api_response",
)
report = tracker.get_report()
print(
f"After request {i + 1}: tracked={report.total_tracked_mb:.4f} MB, RSS={report.process.rss_mb:.1f} MB"
)
final_report = tracker.get_report()
print(f"\nFinal tracked: {final_report.total_tracked_mb:.4f} MB")
print(f"Final RSS: {final_report.process.rss_mb:.1f} MB")
# Verify stores have entries
assert final_report.components["compression_store"].entry_count == 3
class TestCombinedMemoryTracking:
"""Tests that combine multiple components and track total memory."""
@pytest.fixture(autouse=True)
def reset_all(self):
"""Reset all stores."""
from headroom.ccr.batch_store import reset_batch_context_store
from headroom.memory.tracker import MemoryTracker
MemoryTracker.reset()
reset_batch_context_store()
yield
MemoryTracker.reset()
reset_batch_context_store()
@pytest.mark.asyncio
async def test_all_components_memory_tracking(self):
"""Test memory tracking with all components active."""
import numpy as np
from headroom.cache.compression_store import CompressionStore
from headroom.ccr.batch_store import BatchContext, BatchContextStore, BatchRequestContext
from headroom.memory.adapters.graph import InMemoryGraphStore
from headroom.memory.adapters.graph_models import Entity, Relationship
from headroom.memory.adapters.hnsw import HNSWVectorIndex
from headroom.memory.models import Memory
from headroom.memory.tracker import MemoryTracker
tracker = MemoryTracker.get(target_budget_mb=50.0) # Set a 50MB budget
print("\n=== Combined Memory Tracking Test ===")
# Create all components
compression_store = CompressionStore(max_entries=500)
batch_store = BatchContextStore(max_contexts=100)
graph_store = InMemoryGraphStore()
vector_index = HNSWVectorIndex(dimension=384)
# Register all with tracker
tracker.register("compression_store", compression_store.get_memory_stats)
tracker.register("batch_context_store", batch_store.get_memory_stats)
tracker.register("graph_store", graph_store.get_memory_stats)
tracker.register("vector_index", vector_index.get_memory_stats)
# Initial state
report = tracker.get_report()
print("\nInitial state:")
print(f" Total tracked: {report.total_tracked_mb:.4f} MB")
print(f" Budget: {report.target_budget_mb:.1f} MB")
print(f" Over budget: {report.is_over_budget}")
# Add data to all components
print("\nAdding data to components...")
# 1. Compression store - 100 entries (unique content for each)
for i in range(100):
compression_store.store(
original=f"unique content {i}: " + "x" * 1000,
compressed=f"compressed {i}: " + "x" * 100,
tool_name=f"tool_{i}",
)
# 2. Batch store - 10 batches with 5 requests each
for b in range(10):
ctx = BatchContext(batch_id=f"batch_{b}", provider="anthropic")
for r in range(5):
ctx.add_request(
BatchRequestContext(
custom_id=f"req_{b}_{r}",
messages=[{"role": "user", "content": "test " * 50}],
model="claude-sonnet-4-20250514",
)
)
batch_store._contexts[ctx.batch_id] = ctx
# 3. Graph store - 50 entities, 100 relationships
for i in range(50):
entity = Entity(
id=f"entity_{i}",
user_id="test",
name=f"Entity {i}",
entity_type="concept",
properties={"data": "y" * 200},
)
await graph_store.add_entity(entity)
for i in range(100):
rel = Relationship(
id=f"rel_{i}",
user_id="test",
source_id=f"entity_{i % 50}",
target_id=f"entity_{(i + 1) % 50}",
relation_type="related",
)
await graph_store.add_relationship(rel)
# 4. Vector index - 200 vectors
for i in range(200):
embedding = np.random.rand(384).astype(np.float32).tolist()
memory = Memory(
id=f"mem_{i}",
content=f"Memory {i}",
user_id="test",
embedding=embedding,
)
await vector_index.index(memory)
# Final state
report = tracker.get_report()
print("\nAfter adding data:")
print(" Components:")
for name, comp in report.components.items():
print(f" {name}: {comp.entry_count} entries, {comp.size_bytes / 1024:.2f} KB")
print(f" Total tracked: {report.total_tracked_mb:.4f} MB")
print(f" Process RSS: {report.process.rss_mb:.1f} MB")
print(f" Over budget: {report.is_over_budget}")
# Verify all components are tracked
assert len(report.components) == 4
assert report.components["compression_store"].entry_count == 100
assert report.components["batch_context_store"].entry_count == 10
assert report.components["graph_store"].entry_count == 150 # 50 + 100
assert report.components["vector_index"].entry_count == 200
# Verify total is sum of components
total_from_components = sum(c.size_bytes for c in report.components.values())
assert report.total_tracked_bytes == total_from_components
@pytest.mark.asyncio
async def test_memory_budget_enforcement(self):
"""Test that budget enforcement works correctly."""
import numpy as np
from headroom.memory.adapters.hnsw import HNSWVectorIndex
from headroom.memory.models import Memory
from headroom.memory.tracker import MemoryTracker
# Set a very small budget (1 MB)
tracker = MemoryTracker.get(target_budget_mb=1.0)
vector_index = HNSWVectorIndex(dimension=384)
tracker.register("vector_index", vector_index.get_memory_stats)
print("\n=== Budget Enforcement Test ===")
# Add vectors until we exceed budget
for i in range(1000):
embedding = np.random.rand(384).astype(np.float32).tolist()
memory = Memory(
id=f"mem_{i}",
content=f"Memory {i} with extra content " * 10,
user_id="test",
embedding=embedding,
)
await vector_index.index(memory)
if i % 100 == 0:
report = tracker.get_report()
print(
f"After {i} vectors: {report.total_tracked_mb:.4f} MB, over_budget={report.is_over_budget}"
)
if report.is_over_budget:
print(f" Budget exceeded at {i} vectors!")
break
report = tracker.get_report()
print(
f"\nFinal: {report.total_tracked_mb:.4f} MB (budget: {report.target_budget_mb:.1f} MB)"
)
# With 1MB budget and 384-dim vectors, we should exceed budget
# Each vector is ~1.5KB (384 floats * 4 bytes + metadata)
# 1000 vectors = ~1.5MB, so we should exceed 1MB budget
class TestMemoryReportEndpoint:
"""Test the /debug/memory endpoint format."""
@pytest.fixture(autouse=True)
def reset_tracker(self):
"""Reset the tracker singleton before each test."""
from headroom.memory.tracker import MemoryTracker
MemoryTracker.reset()
yield
MemoryTracker.reset()
def test_memory_report_serialization(self):
"""Test that memory report serializes correctly for API response."""
from headroom.cache.compression_store import CompressionStore
from headroom.memory.tracker import MemoryTracker
tracker = MemoryTracker.get(target_budget_mb=100.0)
store = CompressionStore(max_entries=10)
store.store("original", "compressed")
tracker.register("compression_store", store.get_memory_stats)
report = tracker.get_report()
data = report.to_dict()
# Verify structure matches what API returns
assert "process" in data
assert "rss_mb" in data["process"]
assert "vms_mb" in data["process"]
assert "percent" in data["process"]
assert "components" in data
assert "compression_store" in data["components"]
comp = data["components"]["compression_store"]
assert "name" in comp
assert "entry_count" in comp
assert "size_bytes" in comp
assert "size_mb" in comp
assert "hits" in comp
assert "misses" in comp
assert "total_tracked_mb" in data
assert "target_budget_mb" in data
assert "is_over_budget" in data
assert "timestamp" in data
print("\n=== Memory Report Format ===")
import json
print(json.dumps(data, indent=2))
if __name__ == "__main__":
pytest.main([__file__, "-v", "-s"])