[HN Gopher] Show HN: Trieve CLI - Terminal-based LLM agent loop ...
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Show HN: Trieve CLI - Terminal-based LLM agent loop with search
tool for PDFs
Hi HN, I built a CLI for uploading documents and querying them
with an LLM agent that uses search tools rather than stuffing
everything into the context window. I recorded a demo using the
CrossFit 2025 rulebook that shows how this approach compares to
traditional RAG and direct context injection[1]. The core insight
is that LLMs running in loops with tool access are unreasonably
effective at this kind of knowledge retrieval task[2]. Instead of
hoping the right chunks make it into your context, the agent can
iteratively search, refine queries, and reason about what it finds.
The CLI handles the full workflow: ```bash trieve upload
./document.pdf trieve ask "What are the key findings?" ``` You
can customize the RAG behavior, check upload status, and the
responses stream back with expandable source references. I really
enjoy having this workflow available in the terminal and I'm
curious if others find this paradigm as compelling as I do.
Considering adding more commands and customization options if
there's interest. The tool is free for up to 1k document chunks.
Source code is on GitHub[3] and available via npm[4]. Would love
any feedback on the approach or CLI design! [1]:
https://www.youtube.com/watch?v=SAV-esDsRUk [2]:
https://news.ycombinator.com/item?id=43998472 [3]:
https://github.com/devflowinc/trieve/blob/main/clients/cli/i...
[4]: https://www.npmjs.com/package/trieve-cli
Author : skeptrune
Score : 22 points
Date : 2025-06-18 13:52 UTC (9 hours ago)
(HTM) web link (github.com)
(TXT) w3m dump (github.com)
| jlarocco wrote:
| I don't really understand the point of it. It seems like a very
| shallow replacement for skimming (or god forbid reading) the
| paper, without the benefit of absorbing any of the material
| yourself.
|
| I have the same critique for a lot of AI tools. We're replacing
| the meaningful parts of content creation and consumption with a
| computer so we can pass it off as having created or understood it
| ourselves. It just seems pointless.
| skeptrune wrote:
| Sometimes you just want a quick answer to a question though. I
| agree that tools like this aren't something I'd use to consume
| some content I'm actually interested in or produce something I
| think of as high quality.
|
| However, I also want to flag that the cool part about the agent
| loop is that it _feels_ less like skimming since you can watch
| the LLM search, evaluate results, search again, evaluate
| results, and repeat until it 's happy that it has enough
| information to actually answer.
| behnamoh wrote:
| Your comment got me thinking about what it really means to
| understand something. Is it just about remembering the facts or
| the ideas? Or is it more about being aware of them? I've
| watched a ton of YouTube videos and read a bunch of articles
| about physics, but I can't remember how to derive those
| equations a few weeks later. So, I don't feel like I really
| understand them. But if I have an idea about how to do it, how
| much of it is just memory, and how much is actually
| understanding the concept? That's been a question I've been
| thinking about for a long time. With all the AI stuff, we've
| figured out how to deal with the memory part, so we don't have
| to rely on our own memories as much. But that still leaves the
| question: what does understanding really mean?
| dingnuts wrote:
| I've thought about this a lot in the context of "why do I
| need to learn facts when I can just look them up?"
|
| Understanding a concept means you are able to use it in
| higher order reasoning. Think about the rote practice
| necessary to build intuition in mathematics until you're able
| to use the concept being learned for the next concept which
| in turn relies on it.
|
| Once that intuition is built, that's understanding.
| BeetleB wrote:
| > It seems like a very shallow replacement for skimming
|
| Actually, I think we have it all backwards. We're taught to
| skim because such tools didn't exist. Once (if!) they are
| reliable enough, skimming should become a dead art, like
| shorthand is.
|
| One should know how to read well (in detail), when one needs
| to. Everything else can be delegated. Indeed, this is why
| people in high positions don't skim - they can afford
| secretaries and underlings to do the skimming for them.
| westurner wrote:
| neuml/paperai "indexes databases previously built with paperetl"
| and does RAG with txtai; https://github.com/neuml/paperai :
|
| > _paperai is a combination of a txtai embeddings index and a
| SQLite database with the articles. Each article is parsed into
| sentences and stored in SQLite along with the article metadata.
| Embeddings are built over the full corpus._
|
| paperai has a YAML report definition schema that's probably
| useful for meta-analyses.
|
| Paperetl can store articles with SQLite, Elasticsearch, JSON,
| YAML. It doesn't look like markdown from a tagged git repo is
| supported yet. Supported inputs include PDF, XML (arXiv, PubMed,
| TEI), CSV.
|
| PaperQA2 has a CLI: https://github.com/Future-House/paper-
| qa#what-is-paperqa2 :
|
| > _PaperQA2 is engineered to be the best agentic RAG model for
| working with scientific papers._
|
| > [ Semantic Scholar, CrossRef, ]
|
| paperqa-zotero: https://github.com/lejacobroy/paperqa-zotero
|
| The Oracle of Zotero is a fork of paper-qa with FAISS and
| langchain: https://github.com/Frost-group/The-Oracle-of-Zotero
| westurner wrote:
| simonw/llm is a CLI for LLMs: https://github.com/simonw/llm
|
| `llm --help`: https://llm.datasette.io/en/stable/help.html#llm-
| help
|
| simonw/llm plugin directory:
| https://llm.datasette.io/en/stable/plugins/directory.html#pl...
|
| From https://simonwillison.net/2024/Jun/17/cli-language-models/
| :
|
| > _Every prompt and response run through the LLM tool is
| permanently logged to a SQLite database,_
| it_shadow wrote:
| Are AI agents the new Todo list app? Everyone and their
| grandmother is creating one!
|
| How is this one better than syncing our Google drive with chatgpt
| for example and 'asking questions' ?
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(page generated 2025-06-18 23:00 UTC)