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I agree this is an interesting direction, I think this is on the roadmap for DSPy [https://github.com/stanfordnlp/dspy], but right now they mainly focus on optimizing the in-context examples.
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InfluxDB
InfluxDB – Built for High-Performance Time Series Workloads. InfluxDB 3 OSS is now GA. Transform, enrich, and act on time series data directly in the database. Automate critical tasks and eliminate the need to move data externally. Download now.
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Thanks for sharing! These are useful toos, but they are a bit different, more based on similarity search in prompt space (a bit like semantic router: https://github.com/aurelio-labs/semantic-router). Our router uses a neural network for the routing decisions, and it can be trained on your own prompts [https://youtu.be/9JYqNbIEac0]. We're also working on adding support for on-prem deployment :)
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RAG
Discontinued [GET https://api.github.com/repos/Anteemony/RAG: 404 - Not Found // See: https://docs.github.com/rest/repos/repos#get-a-repository] (by Anteemony)
https://unify.ai/docs/demos/demos/LangChain/RAG_playground/R... under "Usage" step 2.
> "Input your Unify APhttps://github.com/Anteemony/RAG"
Your product looks good in my view, although I have only spend about 10min thus far. The docs look pretty easy to follow along.
I'll probably give this a try soon!
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gateway
A blazing fast AI Gateway with integrated guardrails. Route to 200+ LLMs, 50+ AI Guardrails with 1 fast & friendly API.
Great to know this!
I have come across Portkey's Open-source AI Gateway which kind of does the same.
https://github.com/portkey-ai/gateway
It looks like with more LLM adoption, resiliency and cost related aspects take off sooner than expected unlike other technological trends in the past.
I'm also thinking that there is a chance if something like this could help build a better RAG pipeline or evals for the GenAI App. Because end of the day you want to reduce hallucinations but still get good generative responses.
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