DOC: <A long term memory agent 'DOC: ' prefix>

[simpliatanu]

URL

https://python.langchain.com/docs/versions/migrating_memory/long_term_memory_agent/

Checklist

• I added a very descriptive title to this issue.
• I included a link to the documentation page I am referring to (if applicable).

Issue with current documentation:

Something is wrong with this example, when I run exactly same as in the documentation I keep get 429 error. Although I have a commercial license of OpenAI and there is enough dollars left. comes load_memories, not sure what is wrong

error --
raise self._make_status_error_from_response(err.response) from None
openai.RateLimitError: Error code: 429 - {'error': {'message': 'You exceeded your current quota, please check your plan and billing details. For more information on this error, read the docs: https://platform.openai.com/docs/guides/error-codes/api-errors.', 'type': 'insufficient_quota', 'param': None, 'code': 'insufficient_quota'}}
During task with name 'load_memories' and id '0852441c-bcd1-ee97-f431-c3b9d0a980f2'

Idea or request for content:

kindly correct the doc

[simpliatanu]

can be closed, found the problem in the sample code given in docs
corrected code below, first time documents will be [], no check was there, which results in weird error

def search_recall_memories(query: str, config: RunnableConfig) -> List[str]:
"""Search for relevant memories."""
# Extract the user ID from the config
user_id = get_user_id(config)

print (f"User ID: {user_id}")
# Perform a similarity search with a predefined filter
documents = recall_vector_store.similarity_search(
    query,
    k=3,
    filter=lambda doc: doc.metadata.get("user_id") == user_id,
)


# Check if any documents were found
if not documents:
    return []
else:
# Extract and return the content of the documents
    return [doc.page_content for doc in documents]