llnl / llnl/dmx-learn

Agentic DMX Master Plan

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agentic-dmx
Dominant language
Jupyter Notebook
Stars
10
Forks
1
Avg merge
1m
Merged PRs (30d)
34

Description

Goal

Build the repo-local agentic DMX skill system in small, reviewable merge requests.

Ordered Sub-Issues

  • #72 Scaffold repo-local dmx-expert-orchestrator skill
  • #73 Define intake workflow for the orchestrator skill
  • #74 Add default lightweight EDA guidance for user-supplied data paths
  • #75 Write structure-first hierarchy and data-shape routing reference
  • #76 Encode the “joint model first” routing policy
  • #77 Add keys and parameter-sharing reference
  • #78 Add posterior reweighting and conditional reuse reference
  • #79 Add initialization, sufficient-stats, and pseudo-count reference
  • #80 Distill dmx_basics_conditional_vs_composite_mixture.ipynb
  • #81 Distill dmx_example_process_sequences.ipynb
  • #82 Distill dmx_example_reduced_search_space.ipynb
  • #83 Distill dmx_variable_sequence_length_search_depth.ipynb
  • #84 Distill dmx_basics_mixture_models.ipynb
  • #85 Distill dmx_advanced_plsi.ipynb
  • #86 Distill dmx_advanced_geotweet.ipynb
  • #87 Refactor dmx-local-modeling to rely on the new references
  • #88 Add compute and scaling reference, including torch_stats guidance
  • #89 Create a small benchmark prompt suite for agentic DMX tasks
  • #90 Define an evaluation rubric for “DMX expert” behavior
  • #91 Audit src/dmx/stats docstrings for keys
  • #92 Improve highest-priority src/dmx/stats docstrings for keys
  • #93 Audit src/dmx/stats docstrings for sufficient stats and pseudo-counts
  • #94 Improve src/dmx/stats docstrings for initialization semantics
  • #95 Add repo-curated canonical examples reference
  • #96 Run benchmark review for orchestrator routing behavior
  • #97 Run benchmark review for post-fit and downstream-task behavior

Notes

  • One MR per child issue.
  • Land work in the listed order unless a dependency changes.
  • Open follow-up issues instead of broadening an existing child issue.

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by reviewing the ordered child issues and their completion status, especially the remaining benchmark reviews #96 and #97. Use the completed orchestrator, modeling, reference, and evaluation work as context. The plan is complete when the benchmark reviews for routing behavior and post-fit/downstream-task behavior are finished or have produced clearly scoped follow-up issues.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
ai, machine-learning
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Quiet
Clarity
Needs clarification
Newbie friendliness
25/100

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