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[Misc] Lint code and fix code smells (#1871)

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This commit is contained in:
Deshraj Yadav
2024-09-16 17:39:54 -07:00
committed by GitHub
parent 0a78cb9f7a
commit 55c54beeab
57 changed files with 1178 additions and 1357 deletions
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157
mem0/memory/graph_memory.py
View File

@@ -3,30 +3,28 @@ import logging
from langchain_community.graphs import Neo4jGraph
from rank_bm25 import BM25Okapi
from mem0.graphs.tools import (
ADD_MEMORY_TOOL_GRAPH,
ADD_MESSAGE_TOOL,
NOOP_TOOL,
SEARCH_TOOL,
UPDATE_MEMORY_TOOL_GRAPH,
UPDATE_MEMORY_STRUCT_TOOL_GRAPH,
ADD_MEMORY_STRUCT_TOOL_GRAPH,
NOOP_STRUCT_TOOL,
ADD_MESSAGE_STRUCT_TOOL,
SEARCH_STRUCT_TOOL
)
from mem0.graphs.utils import EXTRACT_ENTITIES_PROMPT, get_update_memory_messages
from mem0.graphs.tools import (ADD_MEMORY_STRUCT_TOOL_GRAPH,
ADD_MEMORY_TOOL_GRAPH, ADD_MESSAGE_STRUCT_TOOL,
ADD_MESSAGE_TOOL, NOOP_STRUCT_TOOL, NOOP_TOOL,
SEARCH_STRUCT_TOOL, SEARCH_TOOL,
UPDATE_MEMORY_STRUCT_TOOL_GRAPH,
UPDATE_MEMORY_TOOL_GRAPH)
from mem0.graphs.utils import (EXTRACT_ENTITIES_PROMPT,
get_update_memory_messages)
from mem0.utils.factory import EmbedderFactory, LlmFactory
logger = logging.getLogger(__name__)
class MemoryGraph:
def __init__(self, config):
self.config = config
self.graph = Neo4jGraph(self.config.graph_store.config.url, self.config.graph_store.config.username, self.config.graph_store.config.password)
self.embedding_model = EmbedderFactory.create(
self.config.embedder.provider, self.config.embedder.config
self.graph = Neo4jGraph(
self.config.graph_store.config.url,
self.config.graph_store.config.username,
self.config.graph_store.config.password,
)
self.embedding_model = EmbedderFactory.create(self.config.embedder.provider, self.config.embedder.config)
self.llm_provider = "openai_structured"
if self.config.llm.provider:
@@ -51,15 +49,23 @@ class MemoryGraph:
search_output = self._search(data, filters)
if self.config.graph_store.custom_prompt:
messages=[
{"role": "system", "content": EXTRACT_ENTITIES_PROMPT.replace("USER_ID", self.user_id).replace("CUSTOM_PROMPT", f"4. {self.config.graph_store.custom_prompt}")},
messages = [
{
"role": "system",
"content": EXTRACT_ENTITIES_PROMPT.replace("USER_ID", self.user_id).replace(
"CUSTOM_PROMPT", f"4. {self.config.graph_store.custom_prompt}"
),
},
{"role": "user", "content": data},
]
else:
messages=[
{"role": "system", "content": EXTRACT_ENTITIES_PROMPT.replace("USER_ID", self.user_id)},
messages = [
{
"role": "system",
"content": EXTRACT_ENTITIES_PROMPT.replace("USER_ID", self.user_id),
},
{"role": "user", "content": data},
]
]
_tools = [ADD_MESSAGE_TOOL]
if self.llm_provider in ["azure_openai_structured", "openai_structured"]:
@@ -67,11 +73,11 @@ class MemoryGraph:
extracted_entities = self.llm.generate_response(
messages=messages,
tools = _tools,
tools=_tools,
)
if extracted_entities['tool_calls']:
extracted_entities = extracted_entities['tool_calls'][0]['arguments']['entities']
if extracted_entities["tool_calls"]:
extracted_entities = extracted_entities["tool_calls"][0]["arguments"]["entities"]
else:
extracted_entities = []
@@ -79,9 +85,13 @@ class MemoryGraph:
update_memory_prompt = get_update_memory_messages(search_output, extracted_entities)
_tools=[UPDATE_MEMORY_TOOL_GRAPH, ADD_MEMORY_TOOL_GRAPH, NOOP_TOOL]
if self.llm_provider in ["azure_openai_structured","openai_structured"]:
_tools = [UPDATE_MEMORY_STRUCT_TOOL_GRAPH, ADD_MEMORY_STRUCT_TOOL_GRAPH, NOOP_STRUCT_TOOL]
_tools = [UPDATE_MEMORY_TOOL_GRAPH, ADD_MEMORY_TOOL_GRAPH, NOOP_TOOL]
if self.llm_provider in ["azure_openai_structured", "openai_structured"]:
_tools = [
UPDATE_MEMORY_STRUCT_TOOL_GRAPH,
ADD_MEMORY_STRUCT_TOOL_GRAPH,
NOOP_STRUCT_TOOL,
]
memory_updates = self.llm.generate_response(
messages=update_memory_prompt,
@@ -90,28 +100,29 @@ class MemoryGraph:
to_be_added = []
for item in memory_updates['tool_calls']:
if item['name'] == "add_graph_memory":
to_be_added.append(item['arguments'])
elif item['name'] == "update_graph_memory":
self._update_relationship(item['arguments']['source'], item['arguments']['destination'], item['arguments']['relationship'], filters)
elif item['name'] == "noop":
for item in memory_updates["tool_calls"]:
if item["name"] == "add_graph_memory":
to_be_added.append(item["arguments"])
elif item["name"] == "update_graph_memory":
self._update_relationship(
item["arguments"]["source"],
item["arguments"]["destination"],
item["arguments"]["relationship"],
filters,
)
elif item["name"] == "noop":
continue
returned_entities = []
for item in to_be_added:
source = item['source'].lower().replace(" ", "_")
source_type = item['source_type'].lower().replace(" ", "_")
relation = item['relationship'].lower().replace(" ", "_")
destination = item['destination'].lower().replace(" ", "_")
destination_type = item['destination_type'].lower().replace(" ", "_")
source = item["source"].lower().replace(" ", "_")
source_type = item["source_type"].lower().replace(" ", "_")
relation = item["relationship"].lower().replace(" ", "_")
destination = item["destination"].lower().replace(" ", "_")
destination_type = item["destination_type"].lower().replace(" ", "_")
returned_entities.append({
"source" : source,
"relationship" : relation,
"target" : destination
})
returned_entities.append({"source": source, "relationship": relation, "target": destination})
# Create embeddings
source_embedding = self.embedding_model.embed(source)
@@ -135,7 +146,7 @@ class MemoryGraph:
"dest_name": destination,
"source_embedding": source_embedding,
"dest_embedding": dest_embedding,
"user_id": filters["user_id"]
"user_id": filters["user_id"],
}
_ = self.graph.query(cypher, params=params)
@@ -150,19 +161,22 @@ class MemoryGraph:
_tools = [SEARCH_STRUCT_TOOL]
search_results = self.llm.generate_response(
messages=[
{"role": "system", "content": f"You are a smart assistant who understands the entities, their types, and relations in a given text. If user message contains self reference such as 'I', 'me', 'my' etc. then use {filters['user_id']} as the source node. Extract the entities."},
{
"role": "system",
"content": f"You are a smart assistant who understands the entities, their types, and relations in a given text. If user message contains self reference such as 'I', 'me', 'my' etc. then use {filters['user_id']} as the source node. Extract the entities.",
},
{"role": "user", "content": query},
],
tools = _tools
tools=_tools,
)
node_list = []
relation_list = []
for item in search_results['tool_calls']:
if item['name'] == "search":
for item in search_results["tool_calls"]:
if item["name"] == "search":
try:
node_list.extend(item['arguments']['nodes'])
node_list.extend(item["arguments"]["nodes"])
except Exception as e:
logger.error(f"Error in search tool: {e}")
@@ -201,13 +215,16 @@ class MemoryGraph:
RETURN m.name AS source, elementId(m) AS source_id, type(r) AS relation, elementId(r) AS relation_id, n.name AS destination, elementId(n) AS destination_id, similarity
ORDER BY similarity DESC
"""
params = {"n_embedding": n_embedding, "threshold": self.threshold, "user_id": filters["user_id"]}
params = {
"n_embedding": n_embedding,
"threshold": self.threshold,
"user_id": filters["user_id"],
}
ans = self.graph.query(cypher_query, params=params)
result_relations.extend(ans)
return result_relations
def search(self, query, filters):
"""
Search for memories and related graph data.
@@ -235,17 +252,12 @@ class MemoryGraph:
search_results = []
for item in reranked_results:
search_results.append({
"source": item[0],
"relationship": item[1],
"target": item[2]
})
search_results.append({"source": item[0], "relationship": item[1], "target": item[2]})
logger.info(f"Returned {len(search_results)} search results")
return search_results
def delete_all(self, filters):
cypher = """
MATCH (n {user_id: $user_id})
@@ -254,7 +266,6 @@ class MemoryGraph:
params = {"user_id": filters["user_id"]}
self.graph.query(cypher, params=params)
def get_all(self, filters):
"""
Retrieves all nodes and relationships from the graph database based on optional filtering criteria.
@@ -276,17 +287,18 @@ class MemoryGraph:
final_results = []
for result in results:
final_results.append({
"source": result['source'],
"relationship": result['relationship'],
"target": result['target']
})
final_results.append(
{
"source": result["source"],
"relationship": result["relationship"],
"target": result["target"],
}
)
logger.info(f"Retrieved {len(final_results)} relationships")
return final_results
def _update_relationship(self, source, target, relationship, filters):
"""
Update or create a relationship between two nodes in the graph.
@@ -309,14 +321,20 @@ class MemoryGraph:
MERGE (n1 {name: $source, user_id: $user_id})
MERGE (n2 {name: $target, user_id: $user_id})
"""
self.graph.query(check_and_create_query, params={"source": source, "target": target, "user_id": filters["user_id"]})
self.graph.query(
check_and_create_query,
params={"source": source, "target": target, "user_id": filters["user_id"]},
)
# Delete any existing relationship between the nodes
delete_query = """
MATCH (n1 {name: $source, user_id: $user_id})-[r]->(n2 {name: $target, user_id: $user_id})
DELETE r
"""
self.graph.query(delete_query, params={"source": source, "target": target, "user_id": filters["user_id"]})
self.graph.query(
delete_query,
params={"source": source, "target": target, "user_id": filters["user_id"]},
)
# Create the new relationship
create_query = f"""
@@ -324,7 +342,10 @@ class MemoryGraph:
CREATE (n1)-[r:{relationship}]->(n2)
RETURN n1, r, n2
"""
result = self.graph.query(create_query, params={"source": source, "target": target, "user_id": filters["user_id"]})
result = self.graph.query(
create_query,
params={"source": source, "target": target, "user_id": filters["user_id"]},
)
if not result:
raise Exception(f"Failed to update or create relationship between {source} and {target}")

178
mem0/memory/main.py
View File

@@ -10,14 +10,14 @@ from typing import Any, Dict
import pytz
from pydantic import ValidationError
from mem0.configs.base import MemoryConfig, MemoryItem
from mem0.configs.prompts import get_update_memory_messages
from mem0.memory.base import MemoryBase
from mem0.memory.setup import setup_config
from mem0.memory.storage import SQLiteManager
from mem0.memory.telemetry import capture_event
from mem0.memory.utils import get_fact_retrieval_messages, parse_messages
from mem0.utils.factory import LlmFactory, EmbedderFactory, VectorStoreFactory
from mem0.configs.base import MemoryItem, MemoryConfig
from mem0.utils.factory import EmbedderFactory, LlmFactory, VectorStoreFactory
# Setup user config
setup_config()
@@ -30,9 +30,7 @@ class Memory(MemoryBase):
self.config = config
self.custom_prompt = self.config.custom_prompt
self.embedding_model = EmbedderFactory.create(
self.config.embedder.provider, self.config.embedder.config
)
self.embedding_model = EmbedderFactory.create(self.config.embedder.provider, self.config.embedder.config)
self.vector_store = VectorStoreFactory.create(
self.config.vector_store.provider, self.config.vector_store.config
)
@@ -45,12 +43,12 @@ class Memory(MemoryBase):
if self.version == "v1.1" and self.config.graph_store.config:
from mem0.memory.graph_memory import MemoryGraph
self.graph = MemoryGraph(self.config)
self.enable_graph = True
capture_event("mem0.init", self)
@classmethod
def from_config(cls, config_dict: Dict[str, Any]):
try:
@@ -60,7 +58,6 @@ class Memory(MemoryBase):
raise
return cls(config)
def add(
self,
messages,
@@ -98,9 +95,7 @@ class Memory(MemoryBase):
filters["run_id"] = metadata["run_id"] = run_id
if not any(key in filters for key in ("user_id", "agent_id", "run_id")):
raise ValueError(
"One of the filters: user_id, agent_id or run_id is required!"
)
raise ValueError("One of the filters: user_id, agent_id or run_id is required!")
if isinstance(messages, str):
messages = [{"role": "user", "content": messages}]
@@ -116,8 +111,8 @@ class Memory(MemoryBase):
if self.version == "v1.1":
return {
"results" : vector_store_result,
"relations" : graph_result,
"results": vector_store_result,
"relations": graph_result,
}
else:
warnings.warn(
@@ -125,29 +120,29 @@ class Memory(MemoryBase):
"To use the latest format, set `api_version='v1.1'`. "
"The current format will be removed in mem0ai 1.1.0 and later versions.",
category=DeprecationWarning,
stacklevel=2
stacklevel=2,
)
return {"message": "ok"}
def _add_to_vector_store(self, messages, metadata, filters):
parsed_messages = parse_messages(messages)
if self.custom_prompt:
system_prompt=self.custom_prompt
user_prompt=f"Input: {parsed_messages}"
system_prompt = self.custom_prompt
user_prompt = f"Input: {parsed_messages}"
else:
system_prompt, user_prompt = get_fact_retrieval_messages(parsed_messages)
response = self.llm.generate_response(
messages=[{"role": "system", "content": system_prompt}, {"role": "user", "content": user_prompt}],
messages=[
{"role": "system", "content": system_prompt},
{"role": "user", "content": user_prompt},
],
response_format={"type": "json_object"},
)
try:
new_retrieved_facts = json.loads(response)[
"facts"
]
new_retrieved_facts = json.loads(response)["facts"]
except Exception as e:
logging.error(f"Error in new_retrieved_facts: {e}")
new_retrieved_facts = []
@@ -178,24 +173,30 @@ class Memory(MemoryBase):
logging.info(resp)
try:
if resp["event"] == "ADD":
memory_id = self._create_memory(data=resp["text"], metadata=metadata)
returned_memories.append({
"memory" : resp["text"],
"event" : resp["event"],
})
_ = self._create_memory(data=resp["text"], metadata=metadata)
returned_memories.append(
{
"memory": resp["text"],
"event": resp["event"],
}
)
elif resp["event"] == "UPDATE":
self._update_memory(memory_id=resp["id"], data=resp["text"], metadata=metadata)
returned_memories.append({
"memory" : resp["text"],
"event" : resp["event"],
"previous_memory" : resp["old_memory"],
})
returned_memories.append(
{
"memory": resp["text"],
"event": resp["event"],
"previous_memory": resp["old_memory"],
}
)
elif resp["event"] == "DELETE":
self._delete_memory(memory_id=resp["id"])
returned_memories.append({
"memory" : resp["text"],
"event" : resp["event"],
})
returned_memories.append(
{
"memory": resp["text"],
"event": resp["event"],
}
)
elif resp["event"] == "NONE":
logging.info("NOOP for Memory.")
except Exception as e:
@@ -206,7 +207,6 @@ class Memory(MemoryBase):
capture_event("mem0.add", self)
return returned_memories
def _add_to_graph(self, messages, filters):
added_entities = []
@@ -220,7 +220,6 @@ class Memory(MemoryBase):
return added_entities
def get(self, memory_id):
"""
Retrieve a memory by ID.
@@ -236,11 +235,7 @@ class Memory(MemoryBase):
if not memory:
return None
filters = {
key: memory.payload[key]
for key in ["user_id", "agent_id", "run_id"]
if memory.payload.get(key)
}
filters = {key: memory.payload[key] for key in ["user_id", "agent_id", "run_id"] if memory.payload.get(key)}
# Prepare base memory item
memory_item = MemoryItem(
@@ -261,9 +256,7 @@ class Memory(MemoryBase):
"created_at",
"updated_at",
}
additional_metadata = {
k: v for k, v in memory.payload.items() if k not in excluded_keys
}
additional_metadata = {k: v for k, v in memory.payload.items() if k not in excluded_keys}
if additional_metadata:
memory_item["metadata"] = additional_metadata
@@ -271,7 +264,6 @@ class Memory(MemoryBase):
return result
def get_all(self, user_id=None, agent_id=None, run_id=None, limit=100):
"""
List all memories.
@@ -288,10 +280,12 @@ class Memory(MemoryBase):
filters["run_id"] = run_id
capture_event("mem0.get_all", self, {"filters": len(filters), "limit": limit})
with concurrent.futures.ThreadPoolExecutor() as executor:
future_memories = executor.submit(self._get_all_from_vector_store, filters, limit)
future_graph_entities = executor.submit(self.graph.get_all, filters) if self.version == "v1.1" and self.enable_graph else None
future_graph_entities = (
executor.submit(self.graph.get_all, filters) if self.version == "v1.1" and self.enable_graph else None
)
all_memories = future_memories.result()
graph_entities = future_graph_entities.result() if future_graph_entities else None
@@ -307,15 +301,22 @@ class Memory(MemoryBase):
"To use the latest format, set `api_version='v1.1'`. "
"The current format will be removed in mem0ai 1.1.0 and later versions.",
category=DeprecationWarning,
stacklevel=2
stacklevel=2,
)
return all_memories
def _get_all_from_vector_store(self, filters, limit):
memories = self.vector_store.list(filters=filters, limit=limit)
excluded_keys = {"user_id", "agent_id", "run_id", "hash", "data", "created_at", "updated_at"}
excluded_keys = {
"user_id",
"agent_id",
"run_id",
"hash",
"data",
"created_at",
"updated_at",
}
all_memories = [
{
**MemoryItem(
@@ -325,19 +326,9 @@ class Memory(MemoryBase):
created_at=mem.payload.get("created_at"),
updated_at=mem.payload.get("updated_at"),
).model_dump(exclude={"score"}),
**{
key: mem.payload[key]
for key in ["user_id", "agent_id", "run_id"]
if key in mem.payload
},
**{key: mem.payload[key] for key in ["user_id", "agent_id", "run_id"] if key in mem.payload},
**(
{
"metadata": {
k: v
for k, v in mem.payload.items()
if k not in excluded_keys
}
}
{"metadata": {k: v for k, v in mem.payload.items() if k not in excluded_keys}}
if any(k for k in mem.payload if k not in excluded_keys)
else {}
),
@@ -346,10 +337,7 @@ class Memory(MemoryBase):
]
return all_memories
def search(
self, query, user_id=None, agent_id=None, run_id=None, limit=100, filters=None
):
def search(self, query, user_id=None, agent_id=None, run_id=None, limit=100, filters=None):
"""
Search for memories.
@@ -373,15 +361,21 @@ class Memory(MemoryBase):
filters["run_id"] = run_id
if not any(key in filters for key in ("user_id", "agent_id", "run_id")):
raise ValueError(
"One of the filters: user_id, agent_id or run_id is required!"
)
raise ValueError("One of the filters: user_id, agent_id or run_id is required!")
capture_event("mem0.search", self, {"filters": len(filters), "limit": limit, "version": self.version})
capture_event(
"mem0.search",
self,
{"filters": len(filters), "limit": limit, "version": self.version},
)
with concurrent.futures.ThreadPoolExecutor() as executor:
future_memories = executor.submit(self._search_vector_store, query, filters, limit)
future_graph_entities = executor.submit(self.graph.search, query, filters) if self.version == "v1.1" and self.enable_graph else None
future_graph_entities = (
executor.submit(self.graph.search, query, filters)
if self.version == "v1.1" and self.enable_graph
else None
)
original_memories = future_memories.result()
graph_entities = future_graph_entities.result() if future_graph_entities else None
@@ -390,23 +384,20 @@ class Memory(MemoryBase):
if self.enable_graph:
return {"results": original_memories, "relations": graph_entities}
else:
return {"results" : original_memories}
return {"results": original_memories}
else:
warnings.warn(
"The current get_all API output format is deprecated. "
"To use the latest format, set `api_version='v1.1'`. "
"The current format will be removed in mem0ai 1.1.0 and later versions.",
category=DeprecationWarning,
stacklevel=2
stacklevel=2,
)
return original_memories
def _search_vector_store(self, query, filters, limit):
embeddings = self.embedding_model.embed(query)
memories = self.vector_store.search(
query=embeddings, limit=limit, filters=filters
)
memories = self.vector_store.search(query=embeddings, limit=limit, filters=filters)
excluded_keys = {
"user_id",
@@ -428,19 +419,9 @@ class Memory(MemoryBase):
updated_at=mem.payload.get("updated_at"),
score=mem.score,
).model_dump(),
**{
key: mem.payload[key]
for key in ["user_id", "agent_id", "run_id"]
if key in mem.payload
},
**{key: mem.payload[key] for key in ["user_id", "agent_id", "run_id"] if key in mem.payload},
**(
{
"metadata": {
k: v
for k, v in mem.payload.items()
if k not in excluded_keys
}
}
{"metadata": {k: v for k, v in mem.payload.items() if k not in excluded_keys}}
if any(k for k in mem.payload if k not in excluded_keys)
else {}
),
@@ -450,7 +431,6 @@ class Memory(MemoryBase):
return original_memories
def update(self, memory_id, data):
"""
Update a memory by ID.
@@ -466,7 +446,6 @@ class Memory(MemoryBase):
self._update_memory(memory_id, data)
return {"message": "Memory updated successfully!"}
def delete(self, memory_id):
"""
Delete a memory by ID.
@@ -478,7 +457,6 @@ class Memory(MemoryBase):
self._delete_memory(memory_id)
return {"message": "Memory deleted successfully!"}
def delete_all(self, user_id=None, agent_id=None, run_id=None):
"""
Delete all memories.
@@ -511,8 +489,7 @@ class Memory(MemoryBase):
if self.version == "v1.1" and self.enable_graph:
self.graph.delete_all(filters)
return {'message': 'Memories deleted successfully!'}
return {"message": "Memories deleted successfully!"}
def history(self, memory_id):
"""
@@ -527,7 +504,6 @@ class Memory(MemoryBase):
capture_event("mem0.history", self, {"memory_id": memory_id})
return self.db.get_history(memory_id)
def _create_memory(self, data, metadata=None):
logging.info(f"Creating memory with {data=}")
embeddings = self.embedding_model.embed(data)
@@ -542,12 +518,9 @@ class Memory(MemoryBase):
ids=[memory_id],
payloads=[metadata],
)
self.db.add_history(
memory_id, None, data, "ADD", created_at=metadata["created_at"]
)
self.db.add_history(memory_id, None, data, "ADD", created_at=metadata["created_at"])
return memory_id
def _update_memory(self, memory_id, data, metadata=None):
logger.info(f"Updating memory with {data=}")
existing_memory = self.vector_store.get(vector_id=memory_id)
@@ -557,9 +530,7 @@ class Memory(MemoryBase):
new_metadata["data"] = data
new_metadata["hash"] = existing_memory.payload.get("hash")
new_metadata["created_at"] = existing_memory.payload.get("created_at")
new_metadata["updated_at"] = datetime.now(
pytz.timezone("US/Pacific")
).isoformat()
new_metadata["updated_at"] = datetime.now(pytz.timezone("US/Pacific")).isoformat()
if "user_id" in existing_memory.payload:
new_metadata["user_id"] = existing_memory.payload["user_id"]
@@ -584,7 +555,6 @@ class Memory(MemoryBase):
updated_at=new_metadata["updated_at"],
)
def _delete_memory(self, memory_id):
logging.info(f"Deleting memory with {memory_id=}")
existing_memory = self.vector_store.get(vector_id=memory_id)
@@ -592,7 +562,6 @@ class Memory(MemoryBase):
self.vector_store.delete(vector_id=memory_id)
self.db.add_history(memory_id, prev_value, None, "DELETE", is_deleted=1)
def reset(self):
"""
Reset the memory store.
@@ -602,6 +571,5 @@ class Memory(MemoryBase):
self.db.reset()
capture_event("mem0.reset", self)
def chat(self, query):
raise NotImplementedError("Chat function not implemented yet.")

6
mem0/memory/storage.py
View File

@@ -12,9 +12,7 @@ class SQLiteManager:
with self.connection:
cursor = self.connection.cursor()
cursor.execute(
"SELECT name FROM sqlite_master WHERE type='table' AND name='history'"
)
cursor.execute("SELECT name FROM sqlite_master WHERE type='table' AND name='history'")
table_exists = cursor.fetchone() is not None
if table_exists:
@@ -62,7 +60,7 @@ class SQLiteManager:
INSERT INTO history (id, memory_id, old_memory, new_memory, new_value, event, created_at, updated_at, is_deleted)
SELECT id, memory_id, prev_value, new_value, new_value, event, timestamp, timestamp, is_deleted
FROM old_history
"""
""" # noqa: E501
)
cursor.execute("DROP TABLE old_history")

18
mem0/memory/telemetry.py
View File

@@ -1,7 +1,7 @@
import logging
import os
import platform
import sys
import os
from posthog import Posthog
@@ -15,8 +15,9 @@ if isinstance(MEM0_TELEMETRY, str):
if not isinstance(MEM0_TELEMETRY, bool):
raise ValueError("MEM0_TELEMETRY must be a boolean value.")
logging.getLogger('posthog').setLevel(logging.CRITICAL + 1)
logging.getLogger('urllib3').setLevel(logging.CRITICAL + 1)
logging.getLogger("posthog").setLevel(logging.CRITICAL + 1)
logging.getLogger("urllib3").setLevel(logging.CRITICAL + 1)
class AnonymousTelemetry:
def __init__(self, project_api_key, host):
@@ -24,9 +25,8 @@ class AnonymousTelemetry:
# Call setup config to ensure that the user_id is generated
setup_config()
self.user_id = get_user_id()
# Optional
if not MEM0_TELEMETRY:
self.posthog.disabled = True
if not MEM0_TELEMETRY:
self.posthog.disabled = True
def capture_event(self, event_name, properties=None):
if properties is None:
@@ -40,9 +40,7 @@ class AnonymousTelemetry:
"machine": platform.machine(),
**properties,
}
self.posthog.capture(
distinct_id=self.user_id, event=event_name, properties=properties
)
self.posthog.capture(distinct_id=self.user_id, event=event_name, properties=properties)
def identify_user(self, user_id, properties=None):
if properties is None:
@@ -65,6 +63,7 @@ def capture_event(event_name, memory_instance, additional_data=None):
"collection": memory_instance.collection_name,
"vector_size": memory_instance.embedding_model.config.embedding_dims,
"history_store": "sqlite",
"graph_store": f"{memory_instance.graph.__class__.__module__}.{memory_instance.graph.__class__.__name__}" if memory_instance.config.graph_store.config else None,
"vector_store": f"{memory_instance.vector_store.__class__.__module__}.{memory_instance.vector_store.__class__.__name__}",
"llm": f"{memory_instance.llm.__class__.__module__}.{memory_instance.llm.__class__.__name__}",
"embedding_model": f"{memory_instance.embedding_model.__class__.__module__}.{memory_instance.embedding_model.__class__.__name__}",
@@ -76,7 +75,6 @@ def capture_event(event_name, memory_instance, additional_data=None):
telemetry.capture_event(event_name, event_data)
def capture_client_event(event_name, instance, additional_data=None):
event_data = {
"function": f"{instance.__class__.__module__}.{instance.__class__.__name__}",

19
mem0/memory/utils.py
View File

@@ -4,13 +4,14 @@ from mem0.configs.prompts import FACT_RETRIEVAL_PROMPT
def get_fact_retrieval_messages(message):
return FACT_RETRIEVAL_PROMPT, f"Input: {message}"
def parse_messages(messages):
response = ""
for msg in messages:
if msg["role"] == "system":
response += f"system: {msg['content']}\n"
if msg["role"] == "user":
response += f"user: {msg['content']}\n"
if msg["role"] == "assistant":
response += f"assistant: {msg['content']}\n"
return response
response = ""
for msg in messages:
if msg["role"] == "system":
response += f"system: {msg['content']}\n"
if msg["role"] == "user":
response += f"user: {msg['content']}\n"
if msg["role"] == "assistant":
response += f"assistant: {msg['content']}\n"
return response