langchain/docs/use_cases/chatbots.md
2023-01-06 07:58:38 -08:00

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# Chatbots
Since language models are good at producing text, that makes them ideal for creating chatbots.
Aside from the base prompts/LLMs, an important concept to know for Chatbots is `memory`.
Most chat based applications rely on remembering what happened in previous interactions, which is `memory` is designed to help with.
The following resources exist:
- [ChatGPT Clone](../modules/memory/examples/chatgpt_clone.ipynb): A notebook walking through how to recreate a ChatGPT-like experience with LangChain.
- [Conversation Memory](../modules/memory/getting_started.ipynb): A notebook walking through how to use different types of conversational memory.
- [Conversation Agent](../modules/memory/examples/conversational_agent.ipynb): A notebook walking through how to create an agent optimized for conversation.
Additional related resources include:
- [Memory Key Concepts](../modules/memory/key_concepts.md): Explanation of key concepts related to memory.
- [Memory Examples](../modules/memory/how_to_guides.rst): A collection of how-to examples for working with memory.