riter

11 ms·

1.
by riter 3y ago
OP here. i agree. perhaps you're confused on the intent. the only flag being planted is for folks using rasa looking for a reference implementation just like i was a week ago. not sure if you're being intentionally cynical but try
2.
by riter 3y ago
LOL. you're not alone my dude. i have a similar challenge w/ my engineers. my best lead is an artisan and its proud of what he authors, and like me sees their code as part of the product UX / funnel (1%). the others (99%) i h
3.
by riter 3y ago
thanks for the share, will check out
4.
by riter 3y ago
lol
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by riter 3y ago
well to be fair, when you're scaling it does matter. i would want my techlead or seniors to care and know when/where to make specific trade-offs bc cloud costs are not forgiving. i think that's where folks that make those com
6.
by riter 3y ago
in terms of search store and engine, would you agree that pgvector is sufficient for most text-specific cases?
7.
by riter 3y ago
very much agreed re: dust settling. it makes no sense deploying any of these libraries to prod. as-is. best to understand a configuration / workflow / tuning / etc. that fits your data best and write it from scratch in golang
8.
by riter 3y ago
<3 ty, i totally misinterpreted the comment for cynicism. u guys are kind ty!
9.
by riter 3y ago
ah! in that case glad you asked. my objective falls into neither bucket. i want rasa users to find it so i optimize for search (GH tags, clear description), ease of use (video, addt'l MD files) and perception (logos) but i'll be h
10.
by riter 3y ago
OP here. that's a somewhat cynical interpretation. what if i just care about aesthetics and want to raise the bar. my primary motivation was to get users of Rasa out of a directional hole bc that's where i was. of course i like st
11.
by riter 3y ago
there are a few decent YT videos on this topic (dated 2022 though) vast.ai is decent if you want to rent.
12.
by riter 3y ago
the next best platform I could find for my friend I was helping was google's dialog flow. again, it was managed, closed-source opinionated and not as flexible. and most importantly design considerations were for a pre-LLM world. i pers
13.
by riter 3y ago
it solves how to integrate LLMs (Langchain) an application API pipeline with Rasa... of which I could not find an out-of-the-box public example on github. and so here we are :) TL;DR: i solved a friend's headache (at the time)
14.
by riter 3y ago
yes. there are a few approaches which i intend to take and some helpful resources: You could implement a Dual LLM Pattern Model https://simonwillison.net/2023/Apr/25/dual-llm-pattern/ You could also leve
15.
by riter 3y ago
very interesting abstraction. very DBT-esque. i will dig into the docs, thanks for sharing!
16.
by riter 3y ago
Amen. Constructive feedback to Langchain dev(s): - Reduce bloat, make packages optional e.g. pip install langchain[all] - Reduce opinionated implementation of vector stores, I want my own schema - Don't unnaturally force the chain abst
17.
by riter 3y ago
lol @ knowsitallkaren. i smell a winner.
18.
by riter 3y ago
I was referring to Langchain who raised $10mm from Benchmark https://blog.langchain.dev/announcing-our-10m-seed-round-led... I'm fairly Jerry Liu (LlamaIndex founder) already has angels or will see enough traction to w
19.
by riter 3y ago
To be clear (apologies if I haven't made it so) this is not an LLM. This is an implementation of Rasa leveraging Langchain under the hood. A user technically does not need to dig into Langchain themselves, but they would want to if the
20.
by riter 3y ago
I agree. I mentioned in a thread below that these frameworks are useful for discovering appropriate index-retrieval strategy that works best for you product. On PGVector, I tried to use LangChains class ( https://python.langchain.
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by riter 3y ago
It itself is not a GPT. It is a a framework of a framework project built on top of Rasa ( https://github.com/RasaHQ/rasa ) and Langchain which by default uses gpt3.5-turbo (change it in the .env file) or any foundation m
22.
by riter 3y ago
lololol. i think this opportunity gets bigger post $10m seed round. they'll likely double down and expand footprint vs the inverse. check out llama-index. its purpose-built for document indexing and retrieval and less agents and "
23.
by riter 3y ago
Not off-topic at all. After struggling with LangChain's hyper-opinionated implementation of classes I agree. In fact, this is better off leveraging Llamaindex. This is a proof-of-concept and ultimately leveraging a library / frame
24.
by riter 3y ago
why is that exactly? is it offensive, if so I'm unaware and appreciate the feedback.
25.
by riter 3y ago
I appreciate the feedback. I didn't realize they were acting on it. Would Rasa-LLM sound as compelling?
26.
by riter 3y ago
Totally. Rasa ( https://github.com/RasaHQ/rasa ) is an open source chatbot platform. It allows you to setup "Input Channels" e.g. slack telegram, and has an intents and response pipeline. It leverages pre-LLM N
27.
by riter 3y ago
thanks for asking. this implementation leverages Rasa and stands up a FastAPI server where it receives the user response webhook first and gets processed by (or bypasses) Rasa. The LLM queries a set of documents indexed by Langchain. Dummy
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RasaGPT: First headless LLM chatbot built on top of Rasa, Langchain and FastAPI(github.com)
179 points by riter 3y ago|111 comments
29.
by riter 3y ago
Unfortunately there were not a whole lot of end-to-end examples of integrating Rasa with OpenAI nor functional boilerplates on github so I put a working prototype together in a few days and thus RasaGPT was bron. RasaGPT is a python-based b
30.
by riter 3y ago
acid not necessary. ammonia.

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