dosubot[bot]
commented
1 year ago Answer generated by a 🤖
Answer
I understand that you're looking for a way to persist the Conversation Knowledge Graph Memory to disk or remote storage in the LangChain framework. This is indeed possible and can be achieved by converting the messages to Python dictionaries, saving them (for instance, as a JSON file), and then loading them when needed.
Here's how you can do it:
import json
from langchain.memory import ChatMessageHistory
from langchain.schema import messages_from_dict, messages_to_dict
# Initialize a chat history
history = ChatMessageHistory()
# Add some messages to the history
history.add_user_message("hi!")
history.add_ai_message("whats up?")
# Convert the messages to dictionaries
dicts = messages_to_dict(history.messages)
# Save the dictionaries to a JSON file
with open('history.json', 'w') as f:
json.dump(dicts, f)
# Later, load the dictionaries from the JSON file
with open('history.json', 'r') as f:
loaded_dicts = json.load(f)
# Convert the loaded dictionaries back to messages
loaded_messages = messages_from_dict(loaded_dicts)In this code, we first create a ChatMessageHistory object and add some messages to it. We then convert these messages to dictionaries using the messages_to_dict function and save them to a JSON file. When we need to retrieve the messages, we load the dictionaries from the JSON file and convert them back to messages using the messages_from_dict function.
Please note that this is one potential solution and there might be other ways to achieve the same result depending on your specific requirements and the constraints of your environment.
If you find this solution helpful and believe it could benefit others, feel free to contribute by making a pull request. Your contributions are always welcome!
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weiminw
mvillanue
microcoder-py
Issue you'd like to raise.
Is there way to Persist Conversation Knowledge Graph Memory to disk or remote storage
Suggestion:
No response