decisionfacts/semantic-ai
An open source framework for Retrieval-Augmented System (RAG) uses semantic search helps to retrieve the expected results and generate human readable conversational response with the help of LLM (Large Language Model).
This tool helps you quickly get answers to questions from your own business documents and data, even if it's stored in various places like SharePoint, S3, or databases. You input your documents or structured data and a natural language question, and it generates a human-readable, conversational response. It's designed for anyone who needs to extract specific information or insights from a large volume of internal data without manually sifting through it.
Available on PyPI.
Use this if you need to create a system that can answer questions about your organization's unstructured documents or structured database content using conversational AI.
Not ideal if you are looking for a simple, off-the-shelf chatbot solution that doesn't require connecting to your specific data sources or for general knowledge Q&A.
Stars
22
Forks
1
Language
Python
License
Apache-2.0
Category
Last pushed
Nov 21, 2025
Commits (30d)
0
Dependencies
20
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/vector-db/decisionfacts/semantic-ai"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
meilisearch/meilisearch
A lightning-fast search engine API bringing AI-powered hybrid search to your sites and applications.
nuclia/nucliadb
NucliaDB, The AI Search database for RAG
vespa-engine/vespa
AI + Data, online. https://vespa.ai
ICIJ/datashare
A self‑hosted search engine for documents
PrithivirajDamodaran/FlashRank
Lite & Super-fast re-ranking for your search & retrieval pipelines. Supports SoTA Listwise and...