LangChain: Build AI apps with LLMs through composability

• sketch

  20 2,194 4.4 Python

  AI code-writing assistant that understands data content

  

In terms of applications with it, I have made things like sketch: https://github.com/approximatelabs/sketch

Raw prompt-structure ideas i've worked with:

• langchain

  152 56,526 10.0 Python

  Discontinued ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain] (by hwchase17)

  

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• lambdaprompt

  8 368 5.6 Python

  λprompt - A functional programming interface for building AI systems

  

This is great! I love seeing how rapidly in the past 6 months these ideas are evolving. I've been internally calling these systems "prompt machines". I'm a strong believer that chaining together language model prompts is core to extracting real, and reproducible value from language models. I sometimes even wonder if systems like this are the path to AGI as well, and spent a full month 'stuck' on that hypothesis in October.

Specific to prompt-chaining: I've spent a lot of time ideating about where "prompts live" (are they best as API endpoint, as cli programs, as machines with internal state, treated as a single 'assembly instruction' -- where do "prompts" live naturally) and eventually decided on them being the most synonymous with functions (and api endpoints via the RPC concept)

mental model I've developed (sharing in case it resonates with anyone else)

a "chain" is `a = 'text'; b = p1(a); c = p2(b)` where p1 and p2 are LLM prompts.

What comes next (in my opinion) is other programming constructs: loops, conditionals, variables (memory), etc. (I think LangChain represents some of these concepts as their "areas" -> chain (function chaining), agents (loops), memory (variables))

To offer this code-style interface on top of LLMs, I made something similar to LangChain, but scoped what i made to only focus on the bare functional interface and the concept of a "prompt function", and leave the power of the "execution flow" up to the language interpreter itself (in this case python) so the user can make anything with it.

https://github.com/approximatelabs/lambdaprompt

I've had so much fun recently just playing with prompt chaining in general, it feels like the "new toy" in the AI space (orders of magnitude more fun than dall-e or chat-gpt for me). (I built sketch (posted the other day on HN) based on lambdaprompt)

My favorites have been things to test the inherent behaviors of language models using iterated prompts. I spent some time looking for "fractal" like behavior inside the functions, hoping that if I got the right starting point, an iterated function would avoid fixed points --> this has eluded me so far, so if anyone finds non-fixed points in LLMs, please let me know!

I'm a believer that the "next revolution" in machine-written code and behavior from LLMs will come when someone can tame LLM prompting to self-write prompt chains themselves (whether that is on lambdaprompt, langchain, or something else!)

All in all, I'm super hyped about LangChain, love the space they are in and the rapid attention they are getting~

• squidgy-prompts

  2 26 2.2 Python
  

3. https://github.com/squidgyai/squidgy-prompts/tree/main/tests - unit test in YAML

• gpt_index

  48 7,332 9.8 Python

  Discontinued LlamaIndex (GPT Index) is a project that provides a central interface to connect your LLM's with external data. [Moved to: https://github.com/jerryjliu/llama_index]

• Helix

  4 125 0.0 JavaScript

  Engineering Consciousness (by Miserlou)

I had a similar idea, but it uses a graph construction and Elixir. Definitely going to poach some ideas from LangChain though.

https://github.com/Miserlou/Helix

• LiteratureReviewBot

  1 44 10.0 Python

  Experiment to use GPT-3 to help write grant proposals.

Thanks for sharing your ideas! With respect to the research this topic for me concept, I stumbled upon this repo:

https://github.com/daveshap/LiteratureReviewBot

It does something similar, but uses the ArXiv dataset to search PDFs instead of the internet.

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