mirror of
https://github.com/hwchase17/langchain
synced 2024-10-31 15:20:26 +00:00
19 lines
1.2 KiB
Plaintext
19 lines
1.2 KiB
Plaintext
|
# 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 `memory` is designed to help with.
|
||
|
|
|
||
|
|
The following resources exist:
|
||
|
|
- [ChatGPT Clone](/docs/modules/agents/how_to/chatgpt_clone.html): A notebook walking through how to recreate a ChatGPT-like experience with LangChain.
|
||
|
|
- [Conversation Memory](/docs/modules/memory.html): A notebook walking through how to use different types of conversational memory.
|
||
|
|
- [Conversation Agent](/docs/modules/agents/agent_types/conversational_agent.html): A notebook walking through how to create an agent optimized for conversation.
|
||
|
|
|
||
|
|
|
||
|
|
Additional related resources include:
|
||
|
|
- [Memory Key Concepts](/docs/modules/memory.html): Explanation of key concepts related to memory.
|
||
|
|
- [Memory Examples](/docs/modules/memory/how_to_guides.html): A collection of how-to examples for working with memory.
|
||
|
|
|
||
|
|
More end-to-end examples include:
|
||
|
|
- [Voice Assistant](./voice_assistant.html): A notebook walking through how to create a voice assistant using LangChain.
|