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roh26it
searching Neon…
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6 ms
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1.
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by
roh26it
4mo ago
What do you use for the onboarding guide?
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by
roh26it
5mo ago
Well written, but does this all change in a claude-ified world?
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Why do you need an MCP Gateway?
(portkey.ai)
1 points
by
roh26it
8mo ago
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0 comments
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Show HN: Fast Semantic Tool-filtering for MCP servers
(github.com)
1 points
by
roh26it
10mo ago
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0 comments
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Everything we know about Claude Code Limits
(portkey.ai)
4 points
by
roh26it
1y ago
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0 comments
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Portkey's Prompt Engineering Studio – The IDE for Prompt Engineers
2 points
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roh26it
2y ago
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0 comments
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Ask HN: Have you used v0, lovable or bolt for anything useful?
2 points
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roh26it
2y ago
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1 comments
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We analysed 4B requests on our AI Gateway
(portkey.ai)
5 points
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roh26it
2y ago
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0 comments
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by
roh26it
2y ago
Looks solid, going to try it out. I'm going to be __that guy__, but just ask - is the functionality set similar to llamaparse or is this llamaparse + llm?
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by
roh26it
2y ago
So, while time to first token is lower, throughput might also be lower in most cases?
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by
roh26it
2y ago
What are the trade-offs you've made to achieve this?
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Come down a rabbit hole with OpenAI o1 system card
(portkey.ai)
1 points
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roh26it
2y ago
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1 comments
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roh26it
2y ago
The most interesting findings (at least from my perspective) - OpenAI measured "honesty" that could become an interesting model eval others should adopt. - Using instruction heirarchy to _avoid_ prompt injections - When pushed to
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Ask HN: Is function patching in Python acceptable for a library to do?
3 points
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roh26it
2y ago
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2 comments
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by
roh26it
2y ago
I've been thinking about AI guardrails in production for almost 7 months now, and I'm convinced that using them to "control", "secure", or "block" LLM outputs is not the best use for them . Using them
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by
roh26it
2y ago
Also wondering if this would become expensive very fast if it ends up using S3 with a large number of PUT calls
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Show HN: Created a notebook to compare the top LMSYS vision models easily
(github.com)
2 points
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roh26it
2y ago
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0 comments
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by
roh26it
2y ago
thanks for the support!
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by
roh26it
2y ago
We use a bunch of caching mechanisms on the LLM requests themselves and extend the same to guardrails now. So there's 2 levels of cache - the LLM request itself might be cached (simple and semantic) and the guardrail response can be ca
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Show HN: An open-source AI Gateway with integrated guardrails
(github.com)
21 points
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roh26it
2y ago
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5 comments
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by
roh26it
2y ago
Being one of the most downloaded datasets on Huggingface, I was a little bit surprised by how dirty this dataset was. Plus it had very limited information and some incorrect classifications as well. For an internal experiment on building a
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I added context data to the TruthfulQA dataset
(huggingface.co)
1 points
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roh26it
2y ago
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1 comments
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roh26it
2y ago
Here's a mega guide on keeping costs low with LLMs - https://portkey.ai/blog/implementing-frugalgpt-smarter-llm-u... tl;dr: - Keep prompts short, combine prompts or make more detailed prompts but go to a smaller m
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roh26it
2y ago
At Portkey, this is a problem we deal with quite a bit. Also the reason that Datadog and the traditional observability vendors did not work for LLM use cases since they're not built to handle large volumes of data. We've done this
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Implementing FrugalGPT in Production
(portkey.ai)
2 points
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roh26it
2y ago
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0 comments
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Streaming LLM requests need this Nginx config
(serverfault.com)
1 points
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roh26it
2y ago
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0 comments
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by
roh26it
2y ago
Openrouter packages APIs and most companies prefer having individual relationships with AI vendors. Choosing an AI gateway might be another way to go
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by
roh26it
3y ago
Individual subreddits have usually been my go-to place to discuss and understand the nuances of academic papers. Love LocalLLama for discussions on generative AI papers.
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Adding a streaming run function to the Assistants API
(github.com)
1 points
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roh26it
3y ago
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0 comments
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Caching stream responses across LLMs is hard
(twitter.com)
2 points
by
roh26it
3y ago
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0 comments
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