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Minor fixes in procedural memory (#2469)

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This commit is contained in:
Deshraj Yadav
2025-03-29 17:20:58 -07:00
committed by GitHub
parent 72bb631bb5
commit c1f5a655ba
4 changed files with 20 additions and 11 deletions
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14
mem0/memory/main.py
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@@ -89,6 +89,7 @@ class Memory(MemoryBase):
infer=True,
memory_type=None,
prompt=None,
llm=None,
):
"""
Create a new memory.
@@ -103,6 +104,7 @@ class Memory(MemoryBase):
infer (bool, optional): Whether to infer the memories. Defaults to True.
memory_type (str, optional): Type of memory to create. Defaults to None. By default, it creates the short term memories and long term (semantic and episodic) memories. Pass "procedural_memory" to create procedural memories.
prompt (str, optional): Prompt to use for the memory creation. Defaults to None.
llm (BaseChatModel, optional): LLM class to use for generating procedural memories. Defaults to None. Useful when user is using LangChain ChatModel.
Returns:
dict: A dictionary containing the result of the memory addition operation.
result: dict of affected events with each dict has the following key:
@@ -139,7 +141,7 @@ class Memory(MemoryBase):
messages = [{"role": "user", "content": messages}]
if agent_id is not None and memory_type == MemoryType.PROCEDURAL.value:
results = self._create_procedural_memory(messages, metadata, prompt)
results = self._create_procedural_memory(messages, metadata=metadata, llm=llm, prompt=prompt)
return results
if self.config.llm.config.get("enable_vision"):
@@ -623,9 +625,15 @@ class Memory(MemoryBase):
capture_event("mem0._create_memory", self, {"memory_id": memory_id})
return memory_id
def _create_procedural_memory(self, messages, metadata, llm=None, prompt=None):
def _create_procedural_memory(self, messages, metadata=None, llm=None, prompt=None):
"""
Create a procedural memory
Args:
messages (list): List of messages to create a procedural memory from.
metadata (dict): Metadata to create a procedural memory from.
llm (BaseChatModel, optional): LLM class to use for generating procedural memories. Defaults to None. Useful when user is using LangChain ChatModel.
prompt (str, optional): Prompt to use for the procedural memory creation. Defaults to None.
"""
try:
from langchain_core.messages.utils import convert_to_messages # type: ignore
@@ -644,7 +652,7 @@ class Memory(MemoryBase):
try:
if llm is not None:
parsed_messages = convert_to_messages(parsed_messages)
response = llm.invoke(messages=parsed_messages)
response = llm.invoke(input=parsed_messages)
procedural_memory = response.content
else:
procedural_memory = self.llm.generate_response(messages=parsed_messages)