We’re going to assembling a list of open source demos/projects that use LangChain and feature then on our GitHub. Which ones should we include?
LLMS
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LangChain Demo Showcasing Prompt Templates LLM Chains
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Very cool demo that is also a great showcase for using LangChain’s prompt templates, LLM wrapper, and chains
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LLMs as Solutions for Scientific Publication Overload
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“Scientific publication has extended far beyond our ability to keep up" (V Bush, 1945). Could LLM’s help?
https://
arxiv.org/pdf/2211.09085
.pdf
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Will Neural Networks Create Novel Symbolic Abstractions?
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When will our large neural network models invent one of these? What will it be?! I dream of this novel knowledge creation, because the generation of symbolic abstractions and descriptions of the world has been great for generalisation beyond the senses.
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LLM Interactions Beyond Prompts: Integration with Tools and Systems
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Yeah it’s really not limited to prompts talking to eachother, but rather any interactions between an LLM and other things (whether that be another prompt, or a python REPL, or anything)
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Latest LLM Reads Text on Wall Warning of Impact
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The latest LLM can read writing on a wall. It says "You're about to hit me."
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LangChain 0.0.21: Memory, Conversational Chain, and Improvements
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LangChain version 0.0.21 Added in Memory abstraction (
@sjwhitmore
) Conversational chain (
@sjwhitmore
) Method for adding examples to ExampleSelector class (
@sjwhitmore
) Bug fix for search class Support for all params in the OpenAI wrapper -
Generative AI framing undersells actual capabilities
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Similar issue with "Generative AI" – so hot right now, but this framing is, believe it or not, *underselling* capabilities we are already seeing, and perhaps causing people to work on the wrong things.
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LangChain Overview by Shubham Saboo Appreciated
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A good overview of LangChain by @Saboo_Shubham_ ! Thanks for the write up 🙂
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InstructGPT/RLHF tuning makes model assume all questions answerable
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My guess is this is InstructGPT/RLHF rather than anything in the pre-training corpus. Tuning implicitly makes it assume all questions are answerable — it sees all text as “ ” and Q/A is a subset of that.