Siddhant-K-code/distill
Reliable LLM outputs start with clean context. Deterministic deduplication, compression, and caching for RAG pipelines.
When working with AI agents or large language models, this tool ensures your inputs are clear and concise. It takes raw, potentially redundant information from various sources like documents, memory, or tools, and provides a cleaned-up, unique, and compressed context. This results in more reliable, consistent, and cost-effective outputs from your AI.
136 stars.
Use this if your AI agent or LLM is producing inconsistent or confusing answers due to too much repetitive information in its input context.
Not ideal if you need a solution for improving the core reasoning capabilities of the LLM itself, rather than refining its input.
Stars
136
Forks
14
Language
Go
License
AGPL-3.0
Last pushed
Feb 24, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/rag/Siddhant-K-code/distill"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related tools
wangxb96/RAG-QA-Generator
RAG-QA-Generator...
aws-samples/rag-with-amazon-opensearch-serverless-and-sagemaker
Question Answering Generative AI application with Large Language Models (LLMs) and Amazon...
PerciValXIII/CAFB-food-wise-ai
AI-powered content automation tool for the Capital Area Food Bank (CAFB), using RAG and LLMs to...
aws-samples/rag-with-amazon-opensearch-and-sagemaker
Question Answering Generative AI application with Large Language Models (LLMs) and Amazon...
manthan410/multimodal-RAG-ResearchQA-bot
using mulimodal RAG to query texts, images and tables from pdf for QA