Github · GitHub Repository Radar
DiscovAI DiscovAI-search
🔍 DiscovAI-Search: An AI-powered search engine for AI tools and custom data. Built with Next.js, OpenAI, Supabase, and more. Features vector-based search, Redis caching, and LLM-powered responses.
Stars
285
Forks
32
Watchers: 285
Language
License: Apache License 2.0
Repository Radar Score
28 / 100
Growth
- 7d
- +0
- 30d
- +0
- %
- 0.0%
Not enough metric snapshots yet to chart growth for this repository.
Score breakdown
- popularity 43
- growth 0
- activity 15
- freshness 100
- community 22
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Get a quote →An AI-powered search engine for AI tools, or your own data.
discovai-demo.mp4
Please feel free to contact me on Twitter or create an issue if you have any questions.
DiscovAI.io (use it for free without signin or credit card)
- 🛠 Features
- 🧱 Tech-Stack
- 🚀 Quickstart
- 🌐 Deploy
-
Vector-based Search: Converts user queries into vectors for precise similarity matching in our AI product database.
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Redis-powered Caching: Utilizes Redis to cache search results and outputs, significantly improving response times for repeated queries.
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Comprehensive AI Database: Maintains an up-to-date collection of AI products across various categories and industries.
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LLM-powered Responses: Leverages large language models to provide detailed, context-aware answers based on search results.
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User-friendly Interface: Offers an intuitive design for effortless navigation and efficient AI product discovery.
- App framework: Next.js
- Text streaming: Vercel AI SDK
- LLM Model: gpt-4o-mini
- Database: Supabase
- Vector: Pgvector
- Embedding Model: Jina AI
- Redis Cache: Upstash
- Component library: shadcn/ui
- Headless component primitives: Radix UI
- Styling: Tailwind CSS
run the following command to clone the repo:
git clone https://github.com/DiscovAI/DiscovAI-search
cd discovai-search
pnpm i
create a supabase project, then run the src/db/init.sql in SQL Editor to setup database
Follow the guide below to set up Upstash Redis. Create a database and obtain UPSTASH_REDIS_REST_URL and UPSTASH_REDIS_REST_TOKEN. Refer to the Upstash guide for instructions on how to proceed.
cp .env.local.example .env.local
Your .env.local file should look like this:
# Required
# for match documents
NEXT_PUBLIC_SUPABASE_URL=
NEXT_PUBLIC_SUPABASE_ANON_KEY=
# for embedding query, retrieved here: https://jina.ai/embeddings/
JINA_API_KEY=
# for llm output, retrieved here: https://platform.openai.com/api-keys
OPENAI_API_KEY=
OPENAI_API_URL=
# for llm cache and serach cache
UPSTASH_REDIS_REST_URL=
UPSTASH_REDIS_REST_TOKEN=
pnpm dev
You can now visit http://localhost:3000.
You can deploy on any saas platform like vercel, zeabur, cloudflare pages.
Top contributors
Languages
Share of the codebase by language, based on repository metadata from the host.
- TypeScript 96.4%
- PLpgSQL 1.3%
- CSS 1.3%
- JavaScript 1.1%
Repository Radar analysis
Deterministic insights derived from public metadata and our observations — not personal testing or reviews.
Why this repository is interesting
- Listed in our discovery index with public GitHub metadata for analysis.
Who should use it
- Developers working primarily with TypeScript
- Teams exploring AI tooling, agents, or ML infrastructure
- Frontend engineers comparing UI frameworks and tools
Potential use cases
- Reference or evaluate TypeScript open-source approaches in this domain
- Prototype AI/agent workflows or study reference architectures
Strengths
- README present in our index
- Declared license: Apache License 2.0
Limitations / considerations
- Insights are derived from public metadata and our observations — not a substitute for code review
What to watch
- Radar Score is modest — dig into activity and docs before committing
Source: GitHub (public metadata) + Repository Radar analysis. We do not claim ownership of third-party repositories.
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