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fix: list/set sampling optimization bug in _recursive_datetime_check #2

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fix: list/set sampling optimization bug in _recursive_datetime_check #2

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1f581ac
docs: update screenshot and live demo links in README (#114)
cyfyifanchen Mar 5, 2026
1900be4
docs: update README with OpenClaw plugin release and image link (#116)
cyfyifanchen Mar 6, 2026
c2fdcb5
docs: update README with link to agent_memory branch (#117)
cyfyifanchen Mar 6, 2026
b75642f
fix: list/set sampling optimization bug in _recursive_datetime_check
Mar 6, 2026
7cea8c9
fix: search all requested memory_types instead of only first one
Mar 7, 2026
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10 changes: 5 additions & 5 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -96,11 +96,11 @@ Welcome to EverMemOS! Join our community to help improve the project and collabo

## Usecases

![Image](https://github.com/user-attachments/assets/0c3eb2c5-3a15-4d09-8dee-c38f96422168)
[![Image](https://github.com/user-attachments/assets/60713404-2e94-4cab-9e5f-15b36291dc6f)](https://github.com/EverMind-AI/EverMemOS/tree/agent_memory)

**OpenClaw Long-Term Memory Plugin(coming this week)**
**OpenClaw Long-Term Memory Plugin**

Claw is putting the pieces of his memory together. Imagine a 24/7 agent with continuous learning memory that you can carry with you wherever you go next.
Claw is putting the pieces of his memory together. Imagine a 24/7 agent with continuous learning memory that you can carry with you wherever you go next. Check out the [agent_memory](https://github.com/EverMind-AI/EverMemOS/tree/agent_memory) branch for more details.


![divider][divider-light]
Expand All @@ -121,12 +121,12 @@ See the [Live2D Character with Memory Example](https://github.com/TEN-framework/

<br>

![Image](https://github.com/user-attachments/assets/0d306b4c-bcd7-4e9e-a244-22fa3cb7b727)
[![Image](https://github.com/user-attachments/assets/0d306b4c-bcd7-4e9e-a244-22fa3cb7b727)](https://screenshot-analysis-vercel.vercel.app/)

**Computer-Use with Memory**

Use computer-use to launch screenshot to do analysis all in your memory.
See the [live demo]() for more details.
See the [live demo](https://screenshot-analysis-vercel.vercel.app/) for more details.


![divider][divider-light]
Expand Down
232 changes: 134 additions & 98 deletions src/agentic_layer/memory_manager.py
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Original file line number Diff line number Diff line change
Expand Up @@ -94,6 +94,13 @@
MemoryType.EPISODIC_MEMORY: EpisodicMemoryEsRepository,
}

# Milvus repository mapping - same types as ES but for vector search
MILVUS_REPO_MAP = {
MemoryType.FORESIGHT: ForesightMilvusRepository,
MemoryType.EVENT_LOG: EventLogMilvusRepository,
MemoryType.EPISODIC_MEMORY: EpisodicMemoryMilvusRepository,
}


@dataclass
class EventLogCandidate:
Expand Down Expand Up @@ -337,8 +344,10 @@ async def get_keyword_search_results(
retrieve_mem_request: 'RetrieveMemRequest',
retrieve_method: str = RetrieveMethod.KEYWORD.value,
) -> List[Dict[str, Any]]:
"""Keyword search with stage-level metrics"""
"""Keyword search with stage-level metrics - searches all supported memory types"""
stage_start = time.perf_counter()

# Get all memory types for metrics recording (use first one as representative)
memory_type = (
retrieve_mem_request.memory_types[0].value
if retrieve_mem_request.memory_types
Expand Down Expand Up @@ -375,32 +384,45 @@ async def get_keyword_search_results(
if end_time is not None:
date_range["lte"] = end_time

mem_type = memory_types[0]

repo_class = ES_REPO_MAP.get(mem_type)
if not repo_class:
logger.warning(f"Unsupported memory_type: {mem_type}")
# Filter to only supported memory types (exclude profile, etc. that aren't in ES)
supported_types = [mt for mt in memory_types if mt in ES_REPO_MAP]

if not supported_types:
logger.warning(f"No supported memory_types for keyword search. Requested: {[mt.value for mt in memory_types]}")
return []

es_repo = get_bean_by_type(repo_class)
logger.debug(f"Using {repo_class.__name__} for {mem_type}")

results = await es_repo.multi_search(
query=query_words,
user_id=user_id,
group_id=group_id,
size=top_k,
from_=0,
date_range=date_range,
)
# Search each supported memory type and collect all results
all_results = []
for mem_type in supported_types:
repo_class = ES_REPO_MAP.get(mem_type)
if not repo_class:
logger.info(f"Skipping unsupported memory_type in keyword search: {mem_type}")
continue

es_repo = get_bean_by_type(repo_class)
logger.debug(f"Using {repo_class.__name__} for {mem_type}")

try:
results = await es_repo.multi_search(
query=query_words,
user_id=user_id,
group_id=group_id,
size=top_k,
from_=0,
date_range=date_range,
)

# Mark memory_type, search_source, and unified score
if results:
for r in results:
r['memory_type'] = mem_type.value
r['_search_source'] = RetrieveMethod.KEYWORD.value
r['id'] = r.get('_id', '') # Unify ES '_id' to 'id'
r['score'] = r.get('_score', 0.0) # Unified score field
# Mark memory_type, search_source, and unified score
if results:
for r in results:
r['memory_type'] = mem_type.value
r['_search_source'] = RetrieveMethod.KEYWORD.value
r['id'] = r.get('_id', '') # Unify ES '_id' to 'id'
r['score'] = r.get('_score', 0.0) # Unified score field
all_results.extend(results)
except Exception as e:
logger.warning(f"Keyword search failed for {mem_type}: {e}")
continue

# Record stage metrics
record_retrieve_stage(
Expand All @@ -410,7 +432,7 @@ async def get_keyword_search_results(
duration_seconds=time.perf_counter() - stage_start,
)

return results or []
return all_results
except Exception as e:
record_retrieve_stage(
retrieve_method=retrieve_method,
Expand Down Expand Up @@ -472,7 +494,7 @@ async def get_vector_search_results(
retrieve_mem_request: 'RetrieveMemRequest',
retrieve_method: str = RetrieveMethod.VECTOR.value,
) -> List[Dict[str, Any]]:
"""Vector search with stage-level metrics (embedding + milvus_search)"""
"""Vector search with stage-level metrics - searches all supported memory types"""
memory_type = (
retrieve_mem_request.memory_types[0].value
if retrieve_mem_request.memory_types
Expand All @@ -497,7 +519,7 @@ async def get_vector_search_results(
top_k = retrieve_mem_request.top_k
start_time = retrieve_mem_request.start_time
end_time = retrieve_mem_request.end_time
mem_type = retrieve_mem_request.memory_types[0]
memory_types = retrieve_mem_request.memory_types

logger.debug(
f"retrieve_mem_vector called with query: {query}, user_id: {user_id}, group_id: {group_id}, top_k: {top_k}"
Expand All @@ -521,87 +543,101 @@ async def get_vector_search_results(
f"Query text vectorization completed, vector dimension: {len(query_vector_list)}"
)

# Select Milvus repository based on memory type
match mem_type:
case MemoryType.FORESIGHT:
milvus_repo = get_bean_by_type(ForesightMilvusRepository)
case MemoryType.EVENT_LOG:
milvus_repo = get_bean_by_type(EventLogMilvusRepository)
case MemoryType.EPISODIC_MEMORY:
milvus_repo = get_bean_by_type(EpisodicMemoryMilvusRepository)
case _:
raise ValueError(f"Unsupported memory type: {mem_type}")
# Filter to only supported memory types (exclude profile, etc. that aren't in Milvus)
supported_types = [mt for mt in memory_types if mt in MILVUS_REPO_MAP]

if not supported_types:
logger.warning(f"No supported memory_types for vector search. Requested: {[mt.value for mt in memory_types]}")
return []

# Handle time range filter conditions
start_time_dt = None
end_time_dt = None
current_time_dt = None
# Search each supported memory type and collect all results
all_results = []
for mem_type in supported_types:
# Select Milvus repository based on memory type
milvus_repo_class = MILVUS_REPO_MAP.get(mem_type)
if not milvus_repo_class:
logger.info(f"Skipping unsupported memory_type in vector search: {mem_type}")
continue

milvus_repo = get_bean_by_type(milvus_repo_class)

# Handle time range filter conditions
start_time_dt = None
end_time_dt = None
current_time_dt = None

if start_time is not None:
start_time_dt = (
from_iso_format(start_time)
if isinstance(start_time, str)
else start_time
)

if start_time is not None:
start_time_dt = (
from_iso_format(start_time)
if isinstance(start_time, str)
else start_time
)
if end_time is not None:
if isinstance(end_time, str):
end_time_dt = from_iso_format(end_time)
# If date only format, set to end of day
if len(end_time) == 10:
end_time_dt = end_time_dt.replace(hour=23, minute=59, second=59)
else:
end_time_dt = end_time

# Handle foresight time range (only valid for foresight)
if mem_type == MemoryType.FORESIGHT:
if retrieve_mem_request.start_time:
start_time_dt = from_iso_format(retrieve_mem_request.start_time)
if retrieve_mem_request.end_time:
end_time_dt = from_iso_format(retrieve_mem_request.end_time)
if retrieve_mem_request.current_time:
current_time_dt = from_iso_format(retrieve_mem_request.current_time)

# Call Milvus vector search (pass different parameters based on memory type)
milvus_start = time.perf_counter()
try:
if mem_type == MemoryType.FORESIGHT:
# Foresight: supports time range and validity filtering, supports radius parameter
search_results = await milvus_repo.vector_search(
query_vector=query_vector_list,
user_id=user_id,
group_id=group_id,
start_time=start_time_dt,
end_time=end_time_dt,
current_time=current_time_dt,
limit=top_k,
score_threshold=0.0,
radius=retrieve_mem_request.radius,
)
else:
# Episodic memory and event log: use timestamp filtering, supports radius parameter
search_results = await milvus_repo.vector_search(
query_vector=query_vector_list,
user_id=user_id,
group_id=group_id,
start_time=start_time_dt,
end_time=end_time_dt,
limit=top_k,
score_threshold=0.0,
radius=retrieve_mem_request.radius,
)

# Mark memory_type and search_source
if search_results:
for r in search_results:
r['memory_type'] = mem_type.value
r['_search_source'] = RetrieveMethod.VECTOR.value
all_results.extend(search_results)
except Exception as e:
logger.warning(f"Vector search failed for {mem_type}: {e}")
continue

if end_time is not None:
if isinstance(end_time, str):
end_time_dt = from_iso_format(end_time)
# If date only format, set to end of day
if len(end_time) == 10:
end_time_dt = end_time_dt.replace(hour=23, minute=59, second=59)
else:
end_time_dt = end_time

# Handle foresight time range (only valid for foresight)
if mem_type == MemoryType.FORESIGHT:
if retrieve_mem_request.start_time:
start_time_dt = from_iso_format(retrieve_mem_request.start_time)
if retrieve_mem_request.end_time:
end_time_dt = from_iso_format(retrieve_mem_request.end_time)
if retrieve_mem_request.current_time:
current_time_dt = from_iso_format(retrieve_mem_request.current_time)

# Call Milvus vector search (pass different parameters based on memory type)
milvus_start = time.perf_counter()
if mem_type == MemoryType.FORESIGHT:
# Foresight: supports time range and validity filtering, supports radius parameter
search_results = await milvus_repo.vector_search(
query_vector=query_vector_list,
user_id=user_id,
group_id=group_id,
start_time=start_time_dt,
end_time=end_time_dt,
current_time=current_time_dt,
limit=top_k,
score_threshold=0.0,
radius=retrieve_mem_request.radius,
)
else:
# Episodic memory and event log: use timestamp filtering, supports radius parameter
search_results = await milvus_repo.vector_search(
query_vector=query_vector_list,
user_id=user_id,
group_id=group_id,
start_time=start_time_dt,
end_time=end_time_dt,
limit=top_k,
score_threshold=0.0,
radius=retrieve_mem_request.radius,
)
record_retrieve_stage(
retrieve_method=retrieve_method,
stage='milvus_search',
memory_type=memory_type,
duration_seconds=time.perf_counter() - milvus_start,
)

for r in search_results:
r['memory_type'] = mem_type.value
r['_search_source'] = RetrieveMethod.VECTOR.value
# Milvus already uses 'score', no need to rename

return search_results
return all_results
except Exception as e:
record_retrieve_stage(
retrieve_method=retrieve_method,
Expand Down
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