LangChain for LLM Application Development

https://learn.deeplearning.ai/langchain

https://www.langchain.com/

Models, Prompts, and Parsers

Langchain provides convenience wrappers over OpenAI models. It lets you wrap your prompts so that even the complex prompts can be reused. Parsers let you define the format of the output you want to extract from the OpenAI response.

Memory

LLMs are stateless.

Each transaction is independent.

the entire conversation is provided as context every single time.

Store the entire conversation in the conversation buffer memory. Every new message is added to the buffer.

It is possible to use the conversationbufferwindowmemory. This way only the last n messages are stored in the context memory.

there is also a conversationTokenBufferMemory - this can help control the spending directly as pricing is related to tokens

there is also a ConversationSummaryBufferMemory - summary of the conversation over time.

Chains