LLM Memory with LangChain (6.3)

LLMs do not have the sort of memory where you often see ChatGPT recall information from earlier in the conversation. This sort of memory must be added by the host program. In this video I will show how LangChain can add this sort of memory to a conversation.
Code for This Video:
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#python #langchain #llm

[@ManiSaintVictor]

Love the memento analogy! Makes it stick.

[@PicaPauDiablo1]

Thank you

[@דניאלכהן-ג6ג]

If I have the budget for both 4070 Super and 4060Ti, which is better?
When not dealing with state of the art models, what is better, is 50% more performance better than +4GB Vram?
When more than 12GB Vram is needed the the training will always be very long (1Hour+)?
I mean, when needing 16Vram is the training will always be Hours long?
Is there a scenario when you need 16Vram but the training is very fast (Minutes)? If for both GPUs I will need the cloud for large models, should I get the 4070 Super for not so large models?
Please advise.

[@kaikai7702]

how to add memory in langchain serve？

[@ashvinnihalani8821]

How does the Summary Memory determine what to store there. Is that include in the System prompt or is another model used as a Summarizer?

[@HeatonResearch]

Its another LLM, with a couple of prompts built into the memory class.