Bump pyjamaz tiny fuzz memory to 8192m

[tomusdrw]

Summary

• Sets docker_memory: '8192m' on the pyjamaz tiny demo workflow (was falling back to the 2048m default in demo-source.yml), matching what other tiny targets use.

Test plan

• Workflow YAML parses (next scheduled / manual run of Demo (tiny): pyjamaz).
• Container memory limit visible as 8192m in the run logs.

🤖 Generated with Claude Code

Summary by CodeRabbit

• Chores
  • Updated CI/CD workflow configuration to allocate additional memory resources for demo execution, improving container performance and stability.

[coderabbitai]

📝 Walkthrough

Walkthrough

This PR adds a docker_memory: '8192m' input parameter to the demo job in the pyjamaz-demo-tiny workflow, configuring the memory limit for the containerized execution passed to the reusable demo-source workflow.

Changes

Demo Workflow Memory Configuration

Layer / File(s)	Summary
Demo workflow memory limit .github/workflows/pyjamaz-demo-tiny.yml	The demo job now passes docker_memory: '8192m' to the reusable demo-source.yml workflow invocation to allocate 8GB of memory to the Docker container.

Estimated code review effort

🎯 1 (Trivial) | ⏱️ ~2 minutes

Possibly related PRs

• FluffyLabs/jam-testing#5: Both PRs modify reusable workflow inputs to set docker_memory value in workflow YAMLs for container memory limit configuration.
• FluffyLabs/jam-testing#14: Both PRs add docker_memory parameter to GitHub Actions workflows for Docker-based jobs to allocate container memory.
• FluffyLabs/jam-testing#46: Both PRs modify the demo job inputs in .github/workflows/*-demo-tiny.yml reusable workflow invocation for container execution configuration.

Poem

🐰 A memory boost hops into view,
Eight gigs now flow through the demo's queue,
No more constraints on the Docker throne,
The workflow dances—at last, full-grown!

🚥 Pre-merge checks | ✅ 5

✅ Passed checks (5 passed)

Check name	Status	Explanation
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Title check	✅ Passed	The title clearly and specifically describes the main change: bumping the pyjamaz tiny fuzz memory configuration to 8192m, which matches the file-level changes and PR objectives.
Docstring Coverage	✅ Passed	No functions found in the changed files to evaluate docstring coverage. Skipping docstring coverage check.
Linked Issues check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check	✅ Passed	Check skipped because no linked issues were found for this pull request.

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✨ Finishing Touches

🧪 Generate unit tests (beta)

• Create PR with unit tests
• Commit unit tests in branch td-pyjamaz-fuzz-mem-8192

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[tomusdrw]

Related #49 #54

[coderabbitai]

🧹 Nitpick comments (1)

.github/workflows/pyjamaz-demo-tiny.yml (1)

23-23: Clarify which other tiny targets should match this memory value.

The docker_memory parameter is correctly defined in .github/workflows/demo-source.yml as an optional string input that maps to TARGET_MEMORY. However, the current tiny demo workflows do not all use the same memory allocation:

• pyjamaz-demo-tiny.yml and javajam-demo-tiny.yml use 8192m
• pbnjam-demo-tiny.yml, jamforge-demo-tiny.yml, and jam4s-demo-tiny.yml use 4096m
• jotl-demo-tiny.yml uses 2048m

If the intent is to align pyjamaz with a specific subset of tiny targets, clarify which ones and ensure the choice is consistent with the overall strategy.

🤖 Prompt for AI Agents

Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.

In @.github/workflows/pyjamaz-demo-tiny.yml at line 23, The docker_memory value
for pyjamaz-demo-tiny (docker_memory: '8192m') is inconsistent with several
other tiny workflows; decide whether pyjamaz should align with the 8192m group
(javajam) or the lower-memory group (pbnjam, jamforge, jam4s at 4096m or jotl at
2048m) and update the docker_memory entries accordingly across the tiny workflow
files (pyjamaz-demo-tiny.yml, javajam-demo-tiny.yml, pbnjam-demo-tiny.yml,
jamforge-demo-tiny.yml, jam4s-demo-tiny.yml, jotl-demo-tiny.yml) so all chosen
targets match the agreed memory value and reflect that decision in the workflow
input mapping TARGET_MEMORY/docker_memory.

🤖 Prompt for all review comments with AI agents

Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.

Nitpick comments:
In @.github/workflows/pyjamaz-demo-tiny.yml:
- Line 23: The docker_memory value for pyjamaz-demo-tiny (docker_memory:
'8192m') is inconsistent with several other tiny workflows; decide whether
pyjamaz should align with the 8192m group (javajam) or the lower-memory group
(pbnjam, jamforge, jam4s at 4096m or jotl at 2048m) and update the docker_memory
entries accordingly across the tiny workflow files (pyjamaz-demo-tiny.yml,
javajam-demo-tiny.yml, pbnjam-demo-tiny.yml, jamforge-demo-tiny.yml,
jam4s-demo-tiny.yml, jotl-demo-tiny.yml) so all chosen targets match the agreed
memory value and reflect that decision in the workflow input mapping
TARGET_MEMORY/docker_memory.

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ℹ️ Review info

⚙️ Run configuration

Configuration used: Path: .coderabbit.yaml

Review profile: CHILL

Plan: Pro

Run ID: b35993cc-e84d-4a48-9c56-e051c50b6eff

📥 Commits

Reviewing files that changed from the base of the PR and between 033a192 and 4745f7e.

📒 Files selected for processing (1)

• .github/workflows/pyjamaz-demo-tiny.yml