Trampoline-AI/predict-rlm
Production focused Self-harnessed LM runtime (RLM) that allows the LM to call its sub-lm with DSPy signatures. Define your inputs, outputs, and tools — the model handles its own control flow. Get fully interpretable trajectories and performance that scales directly with model improvements. Without context rot.
- Stars
- 437
- Forks
- 47
- Language
- Python
- License
- MIT
- Last commit
- updated Oct 2026
Straight from GitHub
Nobody has written up this repo. Everything on this page comes straight from the GitHub API, so there is no founder write-up, no pros and cons, and no difficulty rating — rather than a generated guess at them.
Maintenance
Pushed within three months of the last stats read (as of Nov 6, 2026).
Licence
MIT
Tech stack
Primary language: Python. GitHub reports only the dominant language, so this is not the whole stack.
Install
No install command has been verified for this repo. Follow the README rather than a guess.
Quality score
Computed by the discovery import when this entry was added.
- Recent activity×0.30
- 1.00
How recently the default branch was pushed to.
- Adoption×0.20
- 0.56
Stars on a log scale, so adoption counts without dominating.
- Description and topics×0.15
- 1.00
Whether the repo describes itself: description, topics, homepage.
- README present×0.15
- 1.00
Whether the repository has a README at all.
- Licence clarity×0.10
- 1.00
Whether GitHub can resolve the licence to a recognised SPDX id.
- Issue health×0.10
- 0.80
Open issues relative to adoption, as a rough maintenance signal.
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Stats updated Nov 6, 2026. Stars, forks, issue counts, and dates are a snapshot read from the GitHub REST API, not a live figure. This site makes no requests to GitHub when you load a page.