[Jimmc414]

Langchain allows an LLM to initiate query and prompt workflows and observing the results in a sequential or conditional logic chain or workflow and invoking agents, while GPT Index (now Llama Index) excels at connecting an LLM to external data sources and implementing creative indexing schemes for querying within given token context windows. Right now they both fill a need and complement each other nicely.

[bugglebeetle]

Do you have any good/interesting examples of these prompt workflows with langchain? I can see the utility in the abstract, but haven’t seen anything out in the world beyond clever toy projects.

[Jimmc414]

This is a good cookbook style collection of notebooks that illustrate the Langchain functionality https://github.com/gkamradt/langchain-tutorials

Pinecone has some comparable langchain 'recipe' notebooks in their pinecone-io\examples Github repo

[bugglebeetle]

Thank you! I’ll check these out!

[nell]

Be careful out there when using Pinecone. The pricing seems to be confusing. https://twitter.com/Exploringfornow/status/16426070792852193...

[bugglebeetle]

Yikes! Thanks for the heads up.

[TrevorJ]

Entirely notional as of now, but I plan on testing it for game development. The thought is, you could create an embedding of the lore, data, facts and state of your game world and then interrogate the LLM about this in various ways. I see this being very useful both during the authoring of the game, and at runtime.

[darkteflon]

That’s awesome, wonderful idea.

“State Machine games” is incredibly hard to Google!

[TrevorJ]

I'm realizing I probably should update my bio on here more than once every decade! Currently working full time in a related industry, so most of my AI experimentations are strictly on my own time these days. If anyone is interested in these same sorts of things I am on twitter @TrevorJ