nextjs-openai-doc-search
Typesense
nextjs-openai-doc-search | Typesense | |
---|---|---|
8 | 129 | |
1,487 | 17,965 | |
1.4% | 2.7% | |
5.9 | 9.8 | |
about 2 months ago | 6 days ago | |
TypeScript | C++ | |
Apache License 2.0 | GNU General Public License v3.0 only |
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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
Typesense
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Website Search Hurts My Feelings
There are actually plenty of non-ES products that are way easier to integrate and tune (and get better results with less effort).
- Typesense (https://github.com/typesense/typesense)
- Algolia
- Google Programmable Search Engine (https://programmablesearchengine.google.com/about/)
- Remote Machine Learning and Searching on a Raspberry Pi 5
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Open Source alternatives to tools you Pay for
Typesense - Open Source Alternative to Algolia
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DNS record "hn.algolia.com" is gone
If you like your penny take a look at Typesense https://typesense.org/ - nothing to complain here. Especially nothing complain about pricing.
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Vector databases: analyzing the trade-offs
I work on Typesense [1] (historically considered an open source alternative to Algolia).
We then launched vector search in Jan 2023, and just last week we launched the ability to generate embeddings from within Typesense.
You'd just need to send JSON data, and Typesense can generate embeddings for your data using OpenAI, PaLM API, or built-in models like S-BERT, E-5, etc (running on a GPU if you prefer) [2]
You can then do a hybrid (keyword + semantic) search by just sending the search keywords to Typesense, and Typesense will automatically generate embeddings for you internally and return a ranked list of keyword results weaved with semantic results (using Rank Fusion).
You can also combine filtering, faceting, typo tolerance, etc - the things Typesense already had.
[1] https://github.com/typesense/typesense
[2] https://typesense.org/docs/0.25.0/api/vector-search.html
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Creating an advanced search engine with PostgreSQL
For something small with a minimal footprint, I'd recommend Typesense. https://github.com/typesense/typesense
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Obsidian Publish full text search
I haven’t used Publish, but I’d assume you could use something like https://typesense.org/ to index and search the vault.
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DynamoDB search options
A cheaper option would be to use https://typesense.org. You can use DynamoDb streams to automatically load records. It has worked well for me.
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[Guide] A Tour Through the Python Framework Galaxy: Discovering the Stars
Try tigris | typesense for faster search
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Is it worth using Postgres' builtin full-text search or should I go straight to Elastic?
I’m also checking out Typesense as a possibility for replacing Elastic: https://typesense.org/
What are some alternatives?
superprompt - Prompt Development Environment for GPT
MeiliSearch - A lightning-fast search API that fits effortlessly into your apps, websites, and workflow
namegpt - Generate unique and creative project names in seconds with AI!
Elasticsearch - Free and Open, Distributed, RESTful Search Engine
medusa-product-ai-widget - A Medusa Admin widget to improve product descriptions with AI. Built with Medusa UI, OpenAI and Vercel AI SDK.
Apache Solr - Apache Lucene and Solr open-source search software
partner-gallery-example - Supabase Partner Gallery Example
meilisearch-laravel-scout - MeiliSearch integration for Laravel Scout
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]
loki - Like Prometheus, but for logs.
knowledge - A knowledge daemon to collect ideas and auto organize them, with SQLite
sonic - 🦔 Fast, lightweight & schema-less search backend. An alternative to Elasticsearch that runs on a few MBs of RAM.