nextjs-openai-doc-search
Crate
nextjs-openai-doc-search | Crate | |
---|---|---|
8 | 6 | |
1,487 | 3,957 | |
1.4% | 0.5% | |
5.9 | 9.9 | |
about 2 months ago | 6 days ago | |
TypeScript | Java | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
nextjs-openai-doc-search
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Creating an advanced search engine with PostgreSQL
https://supabase.com/blog/openai-embeddings-postgres-vector
https://supabase.com/blog/chatgpt-supabase-docs
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Best Authentication Library in 2023 ?
There is already AI built into the docs - just hit cmd+k and ask a question. we were one of the first to do this: https://supabase.com/blog/chatgpt-supabase-docs
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We made a AI powered assistant using OpenAI, ruby and redis
We were inspired by what supabase did with the creation of their own ai powered assistant here: https://supabase.com/blog/chatgpt-supabase-docs but we wanted to make one that used a more standard backend in redis and ruby.
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Show HN: Gromit, the OS, AI powered assistant for your website/app
https://release.com/blog/training-chatgpt-with-custom-librar...
We were inspired by what supabase did with the creation of their own ai powered assistant here: https://supabase.com/blog/chatgpt-supabase-docs but we wanted to make one that used a more standard backend in redis and ruby.
Gromit is super new; please give it a shot and make pull requests, leave comments, we would love to chat with you about it!
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Knowledge retrieval architectures for LLMs (2023)
This is the same approach that Supabase Clippy took: https://supabase.com/blog/chatgpt-supabase-docs
They called it "context injection" but the OpenAI community appears to call it "retrieval-augmented generation".
(Tangent) I will go to the grave continuing to call it Supabase Clippy even though presumably this prediction from the Supabase blog post became true:
> Today, we're doing our part to support the momentum by releasing “Supabase Clippy” for our docs (and we don't expect this name to last long before the lawyers catch on).
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Finetuning Large Language Models
> the trick where you search for relevant content and paste that into a prompt
Supabase Clippy was the first docs site to ship this experience to production as far as I can tell: https://supabase.com/blog/chatgpt-supabase-docs
I believe they called it "context injection" and I have been following suit in my own writing on the topic.
I am prototyping experiences like Supabase Clippy and am also very interested in fine-tuning for docs Q&A. But my main question is: what exactly would the fine-tuning inputs and outputs look like for docs Q&A?
From my blog:
> AI is all about prediction. Given this temperature, this wind, this day of the year, what is the chance of rain? Temperature, wind, and date are your inputs. Chance of rain is your desired output. Now, try to apply this same type of thinking towards documentation. What are your inputs? What’s your output? The page title and code block could be your inputs. Whether or not the code builds could be your output. Or maybe the code block should be the output? This is why I keep saying that applying fine-tuning to docs is tricky. What are the inputs and outputs?
https://technicalwriting.tools/posts/ten-principles-response...
(I am an AI n00b and have not looked deeply into how fine-tuning works but it's high on my list to experiment with OpenAI's fine-tuning API. Please LMK if I am getting any fundamentals wrong.)
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Supabase kit for building ChatGPT apps
Make sure to check out https://supabase.com/blog/chatgpt-supabase-docs!
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A ChatGPT Starterkit with Next.js & Tailwind CSS
Can try this: https://github.com/supabase-community/nextjs-openai-doc-search
Crate
- FLaNK AI - 01 April 2024
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Creating an advanced search engine with PostgreSQL
I'm wondering if CrateDB [https://github.com/crate/crate] could fit your use case.
It's a relational SQL database which aims for compatibility with PostgreSQL. Internally it uses Lucene as a storage and such can offer fulltext functionality which is exposed via MATCH.
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Distributed query execution in CrateDB: What you need to know
A logical execution plan does not take into account the information about data distribution. CrateDB is a distributed database and data is sharded: a table can be split into many parts - so-called shards. Shards can be independently replicated and moved from one node to another. The number of shards a table can have is specified at the time the table is created.
- Parser generators vs. handwritten parsers: surveying major languages in 2021
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Querying time series data with SQL: examples
PD: If you liked this post... We'd really appreciate a ⭐️ in Github!
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What is CrateDB? 🤔 FAQ
But there's nothing better than trying things by yourself... So Download CrateDB, experiment, and tell us what you think! 😁
What are some alternatives?
superprompt - Prompt Development Environment for GPT
Presto - The official home of the Presto distributed SQL query engine for big data
namegpt - Generate unique and creative project names in seconds with AI!
OrientDB - OrientDB is the most versatile DBMS supporting Graph, Document, Reactive, Full-Text and Geospatial models in one Multi-Model product. OrientDB can run distributed (Multi-Master), supports SQL, ACID Transactions, Full-Text indexing and Reactive Queries.
medusa-product-ai-widget - A Medusa Admin widget to improve product descriptions with AI. Built with Medusa UI, OpenAI and Vercel AI SDK.
MapDB - MapDB provides concurrent Maps, Sets and Queues backed by disk storage or off-heap-memory. It is a fast and easy to use embedded Java database engine.
partner-gallery-example - Supabase Partner Gallery Example
jOOQ - jOOQ is the best way to write SQL in Java
nodejs-api-starter - 💥 Yarn v2 based monorepo template (seed project) pre-configured with GraphQL API, PostgreSQL, React, Relay, and Material UI. [Moved to: https://github.com/kriasoft/relay-starter-kit]
Flyway - Flyway by Redgate • Database Migrations Made Easy.
knowledge - A knowledge daemon to collect ideas and auto organize them, with SQLite
sql2o - sql2o is a small library, which makes it easy to convert the result of your sql-statements into objects. No resultset hacking required. Kind of like an orm, but without the sql-generation capabilities. Supports named parameters.