Recent submissions

Comment · 1 year ago
Comment · 1 year ago
This is great feedback. I just improved the README and DockerHub overview to be more clear:

"Stop getting out-of-date Python package manager commands from your AI. Cross-reference latest official pip, poetry, uv, and conda docs with auto-updates."

Comment · 1 year ago
Thank you so much for pointing that out, I just updated the docker instructions in the README and on DockerHub:

```shell # Pin to commit hash for production security # Get current hash from: https://hub.docker.com/r/keminghe/py-dep-man-companion/tags docker pull keminghe/py-dep-man-companion@sha256:2c896dc617e8cd3b1a1956580322b0f0c80d5b6dfd09743d90859d2ef2b71ec6 # 2025-07-22 release example

# Or use latest for development docker pull keminghe/py-dep-man-companion:latest ```

Comment · 1 year ago
I see, yes, with this implementation, the networking component becomes necessary. I made different design decisions for `py-dep-man-companion` such that the tool is fully offline and can be used with local llms.
Comment · 1 year ago
Genuinely curious: what are aspects of the demo you find less helpful? I want to improve it.
Comment · 1 year ago
Appreciate you opening my eyes to this. Dash is indeed comprehensive, and a much bigger initiative. I wonder how it's handling the documentation staleness issue? New docs are published every minute.
Comment · 1 year ago
Thank you. Yes, 50% of the core value prop is the self-updating automation and the traditional fuzzy + full text search capabilities that disrupt the embedding-centric RAG paradigm. Plus, Tantivy (Rust-based) is fast.
Comment · 1 year ago
Appreciate the feedback. I will make it my todo to try out your suggestion of comparing Claude Code with and without MCP to measure the quantitative difference.
Comment · 1 year ago
I will admit that the tool itself is still a bit janky (had to make a lot of workarounds with Streamlit). Will def continue to work with my professor for polish and additional features.

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