Evidence receipt / uncertainty
Published · transcript-backedShawn Wang: uncertainty
6 Sept 2023 Latent Space The Point of LangChain — with Harrison Chase of LangChain
“Then you have a concept called Agents, which I don't know if exactly matches what other people call Agents.”
Source trail
Everything needed to verify it.
- Speaker
- Shawn Wang
- Attribution
- Verified speaker
- Claim type
- uncertainty
- Recorded
- 6 Sept 2023
- Publisher
- Latent Space
Transcript context
…I think right off the bat, having different options for language models. I mean, language models is the main one that right off the bat we knew we wanted to support a bunch of different options for. There's a lot to discuss there. People want optionality between different language models. They want to try it out. They want to maybe change to ones that are cheaper as new ones kind of emerge. They don't want to get stuck into one particular one if a better one comes out. There's some challenges there as well. Prompts don't really transfer. And so there's a lot of nuance there. But from the bat, having this optionality between the language model providers was a big important part because I think that was just something we felt really strongly about. We believe there's not just going to be one model that rules them all. There's going to be a bunch of different models that are good for a bunch of different use cases. I did not anticipate the number of vector stores that would emerge. I don't know how many we supported in the initial release. It probably wasn't as big of a focus as language models was. But I think it kind of quickly became so, especially when Postgres and Elastic and Redis started building their vector store implementations. We saw that some people might not want to use a dedicated vector store. Maybe they want to use traditional databases. I think to your point around what we're opinionated about, I think the thing that we believe most strongly is it's super early in the space and super fast moving. And so there's a lot of uncertainty about how things will shake out in terms of what role will vector databases play? How many will there be? And so I think a lot of it has always kind of been this optionality and ability to switch and not getting locked in. There's other pieces of LangChain which maybe don't get as much attention sometimes. And the way that you explained LangChain is somewhat different from the docs. I don't know how to square this. So for example, you have at the top level in your docs, you have, we mentioned ModelIO, we mentioned Retrieval, we mentioned Chains. Then you have a concept called Agents, which I don't know if exactly matches what other people call Agents. And we also talked about Memory. And then finally there's Callbacks. Are there any of the less understood concepts in LangChain that you want to give some air to? I mean, I think buried in ModelIO is some stuff around like few-shot example selectors that I think is really powerful. That's a workhorse.…
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