First try app packaging : librechat - issue with postgresql extention (pgvector)

[Valexico]

@canadaduane
Yes no problem

[girish]

Thanks, cc @vladimir.d . We will take a look .

[firmansi]

It seems the package is not shipped with RAG API ?

[nebulon]

The package does have pgvector extension, that should work, however I am not sure I understand how the app needs to be configured for RAG API and the local vectordb. Does anyone have upstream docs for that? I can only find https://www.librechat.ai/docs/configuration/rag_api

[luckow]

more or less the same question here -> https://forum.cloudron.io/topic/14037/libcrechat-postgresql-pgvector

[firmansi]

@nebulon the documentation for RAG API can be found in https://github.com/danny-avila/rag_api

As seen that the pgvector can't be used if the RAG API not installed and running. This RAG API is somehow critical part, if it's not running then the librechat can't have capability that openwebui has for files upload, processing files to embedding model and so on

[nebulon]

I see, so this is actually another project which needs to be bundled together with librechat or as a separate app.

This one is using pgvector, not librechat itself!

(will also move the thread here to the librechat category)

[LoudLemur]

@Valexico hey there! Trying this is awesome and thank you so much for putting your ai skills towards packaging.

I came here to offer congratulations on having LibreChat packaged, but to hear you have stated an ai cloudron packaging initiative is just fantastic. I am very glad you are here and thanks for your efforts.

[Valexico]

This post is deleted!

[Valexico]

Hi @LoudLemur
Thanks

For those who want to dig "AI assisted packaging", here is how I proceeded

• I use Zed Editor which has a nice prompt library tool allowing prompt nesting (prompts in prompts. Sins Zed last "agentic" update, you need to use what they call "text thread" to have this feature/behaviour
• I have a main big prompt with all main specificities of packaging (Cloudron documentation mainly)
• I have smaller prompts about addon to be loaded only when needed
• And then I made specific prompts loading target app source files, and the same for example of packaged apps to guide the AI

I did this in 2024. This could be largely improved in 2025 with more agentic behaviour to let the AI fetch the context it needs

[jdaviescoates]

See also the prompt put together by @canadaduane here https://git.knownelement.com/KNEL/KNELProductionContainers/src/commit/9f74e0fc3977d368f1ca4846843607c75cd05b1c/Techops/CloudronPackagePrompt.md

[robi]

With an MCP server if you install context7.com it has the ability to ingest all the relevant docs for the agent task. https://github.com/upstash/context7

There are other nice combos of MCPs, perhaps for another thread. Start and share.

[LoudLemur]

@robi @girish there is an option to add cloudron's docs here, if they are on github

https://context7.com/add-library?tab=github

[Valexico]

I think building a RAG-like knowledge base is not the best approach for this use case.
It would be much mode efficient an agent with

• General knowledge about cloudron packaging
• Toolset (sub agent) to retrieve relevant files from repositories (dockerfile, docker-compose...)
• Toolset to retrieve additional context for each addon needed
• Toolset to retrieve relevant example (existing cloudron packaged apps)

The process is complex but quite straightforward and I see no need for a RAG knowledge base

[firmansi]

But without RAG API, somehow we can nor "chat" with files, that's from understanding about how important to have RAG API packaged with core Librechat. Pleaset let us know if we can upload files to Librechat without RAG API, maybe I miss something

[Valexico]

We should split in 2 different thread
Yes Librechat needs RAG API to have all its feature

No a cloudron packaging agent does not need a RAG knowledge bases to be efficient (I think)

Those are 2 totally different subjects

[firmansi]

@Valexico Sure, to make it more efficient,but somehow RAG knowledgebase deem necessary for business usage as RAG can enhance model to understand the business context of the company using tool like librechat, without RAG knowledgebase, the model will only have vast general knowledge

[Valexico]

I agree with you @firmansi
the problem is there are 2 topics discussed in this thread :

• Topic #1: Packaging of librechat
• Topic #2: How to build an AI agent to automate the process of packaging Cloudron app

I think that lead to our misunderstanding

[marcusquinn]

@LoudLemur said in First try app packaging : librechat - issue with postgresql extention (pgvector):

@robi @girish there is an option to add cloudron's docs here, if they are on github

https://context7.com/add-library?tab=github

Great suggestion! Might need it's own post to make sure it doesn't get lost in this thread.

[LoudLemur]

@marcusquinn Thanks! I have checked and context7 can also ingest from websites, which I shall try instead. That website is very busy ingesting and it keeps saying, "Try again in a few minutes..." Eventually it said "failed to find project name" from cloudron's:
https://docs.cloudron.io/

so it is still not working and now it is rate limiting me. perhaps somebody else could try?