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add memprompt docs (#294)

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Harrison Chase 2022-12-09 12:40:24 -08:00 committed by GitHub
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7
docs/explanation/glossary.md
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@ -72,3 +72,10 @@ Encouraging the model to think a certain way by including the start of the model
Resources:
- [Example](https://twitter.com/goodside/status/1583262455207460865?s=20&t=8Hz7XBnK1OF8siQrxxCIGQ)
### MemPrompt
MemPrompt maintains a memory of errors and user feedback, and uses them to prevent repetition of mistakes.
Resources:
- [Paper](https://memprompt.com/)

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docs/getting_started/memory.ipynb
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@ -6,7 +6,7 @@
"metadata": {},
"source": [
"# Memory\n",
"So far, all the chains and agents we've gone through have been stateless. But often, you may want a chain or agent to have some concept of \"memory\" so that it may remember information about its previous interactions. The most clear and simple example of this is when designing a chatbot - you want it to remember previous messages so it can use context from that to have a better conversation. This would be a type of \"short-term memory\". On the more complex side, you could imagine a chain/agent remembering key pieces of information over time - this would be a form of \"long-term memory\".\n",
"So far, all the chains and agents we've gone through have been stateless. But often, you may want a chain or agent to have some concept of \"memory\" so that it may remember information about its previous interactions. The most clear and simple example of this is when designing a chatbot - you want it to remember previous messages so it can use context from that to have a better conversation. This would be a type of \"short-term memory\". On the more complex side, you could imagine a chain/agent remembering key pieces of information over time - this would be a form of \"long-term memory\". For more concrete ideas on the later, see this [awesome paper](https://memprompt.com/).\n",
"\n",
"LangChain provides several specially created chains just for this purpose. This notebook walk throughs using one of those chains (the `ConversationChain`) with two different types of memory."
]
@ -297,7 +297,7 @@
"source": [
"### More Resources on Memory\n",
"\n",
"This just scratches the surface of what you can do with memory. For more examples on things like how to implement custom memory classes, how to add memory to a custom LLM chain and how to use memory with and agent, please see the [How-To: Memory](../../examples/memory) section."
"This just scratches the surface of what you can do with memory. For more examples on things like how to implement custom memory classes, how to add memory to a custom LLM chain and how to use memory with and agent, please see the [How-To: Memory](../../examples/memory) section. For even more advanced ideas on memory (which will hopefully be included in LangChain soon!) see the [MemPrompt](https://memprompt.com/) paper."
]
},
{
@ -325,7 +325,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.6"
"version": "3.9.1"
}
},
"nbformat": 4,