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Llmff

v0.1.5 Feature

This release adds 2 notable features for engineering teams evaluating rollout.

Published 10d LLM Frameworks
✓ No known CVEs patched
Read the diff → Tool health → What is this tool? →

✓ No known CVEs patched in this version

Summary

AI summary

Adds agent harness contract with run-scoped artifact directory and result schema

Full changelog

llmff v0.1.5

Agent harness contract release. This release turns the agent-workflow direction
from guidance into a concrete subprocess contract: agents can now hand bounded
pipeline work to llmff run --run-dir, then supervise stable artifacts,
process status, and machine-readable results.

Supported Install

cargo install --git https://github.com/syndicalt/llmff --tag v0.1.5 llmff

Included Since v0.1.4

  • llmff run --run-dir <dir> creates a run-scoped artifact directory with
    inspect.json, trace.jsonl, events.jsonl, checkpoint.json, and
    result.json.
  • result.json records schema version, final status, exit code, manifest hash,
    artifact names, failure kind, safe failure message, and retry
    recommendation.
  • run-result-v1.schema.json freezes the result artifact shape for downstream
    supervisors and conformance tooling.
  • Agent harness conformance now validates successful runs and stage-execution
    failures through scripts/check-agent-harness-conformance.sh.
  • docs/agent-harness-contract.md documents process semantics, stdout
    ownership, exit-code authority, artifact separation, failure kinds, retry
    posture, safe metadata handling, and adapter expectations.
  • OpenAI Agents SDK and LangGraph examples show how to wrap llmff as a bounded
    subprocess tool or graph node without turning llmff into an agent framework.
  • The adapters materialize run-scoped manifests and inputs from a
    {{LLMFF_INPUT_PATH}} placeholder, so concurrent agent calls do not share or
    overwrite input files.
  • The Python subprocess supervisor, batch supervisor, Node.js streaming supervisor,
    agent runner adoption guide, OpenTelemetry bridge, and ecosystem
    readiness gates remain part of the release contract.
  • Release preflight continues to validate the documented ecosystem readiness
    surface before tagging; release preflight is still the local release gate.

Packaged Artifacts

Release-tag CI is expected to publish:

  • Linux x86_64 .tar.gz archive, .deb package, and Arch PKGBUILD plus
    llmff-0.1.5-arch.SRCINFO metadata.
  • macOS Apple Silicon and Intel .tar.gz archives and unsigned .pkg
    installers.
  • Windows x86_64 unsigned .zip archive and unsigned MSI installer.
  • Adjacent SHA-256 checksums and llmff-0.1.5-release-trust.json.

Manual workflow dispatch keeps generated files as Actions artifacts instead of
GitHub Release assets.

Known Limitations

  • This is a pipeline runner, not a native inference kernel, model converter,
    serving platform, or full agent framework.
  • Windows and macOS native artifacts are unsigned in this release.
  • Package-manager distribution through Homebrew, winget, Scoop, apt
    repositories, or an official AUR package remains parked until maintainers
    decide those channels are support-ready.
  • Authenticode signing, Apple Developer ID signing, and notarization remain
    deferred paid distribution tracks.
  • Live provider smoke jobs remain opt-in and require maintainers to configure
    secrets and runner expectations explicitly.
  • --run-dir currently owns trace, events, and checkpoint paths and is not yet
    combined with batch mode.

Verification

Release verification should pass before tagging:

scripts/release-preflight.sh v0.1.5
scripts/smoke-install.sh --git https://github.com/syndicalt/llmff --tag v0.1.5

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