pathwaycom / pathwaycom/llm-app
Getting Started instructions are fragmented across templates, making initial setup unclear
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Description
Steps to reproduce
- Open the main repository README
- Follow the “Getting started” section
- Notice that setup instructions redirect users to individual app folders without:
- A minimal runnable example
- A common baseline configuration
- Clear guidance on template selection
Relevant log output
The main README should include:
- A minimal “First Run” example (e.g., one command or one simple pipeline)
- Clear guidance on which template is best for beginners
- A short checklist of prerequisites (Python version, Docker optional, API keys)
What did you expect to happen?
While exploring the Pathway AI Pipelines repository, I found that the onboarding experience for first-time users can be confusing due to getting-started instructions being spread across multiple template-specific README files.
The main repository README explains what the pipelines do very well, but it does not provide a single minimal, end-to-end setup example to help users quickly validate their environment before choosing a specific application template.
This can make it difficult for new users to understand:
- Which template to start with
- What the minimal system requirements are
- How to quickly run a first pipeline locally without deep exploration
Version
.
Docker Versions (if used)
No response
OS
Linux
On which CPU architecture did you run Pathway?
x86-64
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the main repository README, then compare the template-specific README files it currently links to. Done means the main README contains a minimal first-run example, beginner template guidance, and a short checklist covering Python, optional Docker, and API keys.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- docker, python
- Domain
- developer-experience, documentation
- Issue type
- Documentation
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Activity status
- Stale
- Clarity
- Clearly specified
- Newbie friendliness
- 58/100