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swaminarayan

How does this perform on longer videos, especially on lower-end machines? Is the transcription and video processing entirely local in the browser?
How it select model? using AI?
I am getting used to with this lightrag-snkv, Now I dont need to check hacker news site again, it automatically ingest top ranked posts and I can query and check answers using natural query language.
if you are opening video in mobile github app then it won’t open.Check in browser.
Right now Show HN and Ask HN tags based blogs and its comments are ingested in database.

Show HN: Query months of HN discussions and comments as a knowledge graph

https://github.com/hash-anu/lightrag-snkv

I built lightrag-snkv, Basically it uses lightRAG https://github.com/HKUDS/LightRAG ,this requires various storage databases like key value store, graph database, vector database, I built single embedded file based database which covers all these requirements: https://github.com/hash-anu/snkv. And developed ingestor which ingest data from Algolia's HN search API. Here auto ingestion timings can...

( Read More... | 5 comments | 2 points | on HN )
this is not mythology. this is ithihasas meaning thus it happened

Ask HN: Best LLM model for a RAG-based Android app across all smartphones?

I am developing RAG based android app using llama.cpp. For offline processing I am using Qwen 1.5 2.5B model using Q4 quantization, I am offloading computation to GPU if present, However for low end android phones my android app is either crashing due to OOM or If not crashing and no GPU available in that case it takes lots of time to generate text. I also tried with SmolLM 135M model for low...

( Read More... | 1 comment | on HN )
i like this idea, especially for the parent who dont want their kids to watch reels/shorts of the instagram and youtube apps.
What architectural decisions enabled pg_textsearch to outperform Tantivy/ParadeDB by 4.7×, especially given Tantivy’s reputation for speed?
Interesting approach — especially around modifying SQLite’s internals.

In SNKV, I’m taking almost the opposite direction: keeping B-tree / storage-layer ideas and removing the SQL layer entirely, to expose a minimal key-value interface.

Curious how you think about the tradeoff between simplifying the query layer vs the storage layer.

https://github.com/hash-anu/snkv

Really interesting design — especially using SQLite-compatible storage with a PostgreSQL interface.

I'm working on SNKV, which explores a different approach: skipping the SQL layer entirely and focusing on a simple key-value interface of the sqlite.

It trades SQL flexibility for simplicity and lower overhead in embedded use cases supports and also multi processing for postgresql.

Curious how you think about that tradeoff. https://github.com/hash-anu/snkv/tree/master

Very cool approach. I’m working on a related KV storage project (snkv - https://github.com/hash-anu/snkv)

How do you handle manifest consistency and updates—append-only or rewrite-heavy?

What were the biggest architectural changes in the rewrite, and what tradeoffs did you make compared to the old Video.js design?
Does your method work better than standard ANN when filters are very strict—and how does it affect speed vs accuracy?
How do you build a procedurally generated survival game in a terminal without a graphics engine?
How did you make a very small AI model (14M) sound more natural and expressive than even bigger models?
Re: on Wednesday March 18, 2026 @10:57PM (#47434348)
if you want to use key value store using sqlite then you can try : https://github.com/hash-anu/snkv

in which i am directly accessing b-tree layer and not consuming query layer.

for kv workloads it is much faster compare to sql.

and yeah you will get same benefits of sqlite storage engine.

Re: on Wednesday March 18, 2026 @10:53PM (#47434309)
What would you do if your entire Git history was instantly queryable with SQL?
What do we gain and lose by treating AI agents like software projects in Git?
Why do minimal apps sometimes work better than feature-rich ones?
makes sense
Why do AI agents get worse with more context, and how should we manage context windows?
Could a K-style array language be a practical way to design audio waveforms and DSP patches?
If a working compiler can be written in ~1000 lines, why are production compilers like GCC or LLVM millions of lines?
Re:Show HN: OneCLI – Vault for AI Agents in Rust on Saturday March 14, 2026 @12:39AM (#47373412)
How do you defend against prompt-injection attacks that cause the agent to call legitimate endpoints but exfiltrate sensitive data through the response?

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