lukovicaleksa/semantic-search-mongodb-fastapi
This project demonstrates how you can enhance standard CRUD operations in your application using Semantic Search mechanism.
This project helps application developers enhance standard data operations by adding semantic search capabilities. It takes plain text data, converts it into numerical embeddings, and stores them in MongoDB. Developers can then search this data based on meaning, rather than just keywords, making applications more intuitive and powerful.
No commits in the last 6 months.
Use this if you are a developer building an application and want to implement intelligent search functionality that understands context and meaning, not just exact keyword matches.
Not ideal if you need a plug-and-play solution without writing code, or if your primary database is not MongoDB.
Stars
13
Forks
3
Language
Python
License
—
Category
Last pushed
Oct 23, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/embeddings/lukovicaleksa/semantic-search-mongodb-fastapi"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
DiceTechJobs/VectorsInSearch
Dice.com repo to accompany the dice.com 'Vectors in Search' talk by Simon Hughes, from the...
unmonoqueteclea/voilib
🎧 Podcast Search Engine. Try it now for free or run your own instance.
IuriiD/pinecone-faiss-pgvector
Comparing vector DBs Pinecone, FAISS & pgvector in combination with OpenAI Embeddings for semantic search
DrRuin/Personalized-Real-Estate-Agent
In an industry where personalization is key to customer satisfaction, your company wants to...
nmdra/Semantic-Search
A semantic search system built with PostgreSQL and pgvector, powered by Gemini for generating...