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Man1Lab v1.2.2

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@maniac1um maniac1um released this 08 Jul 07:13
v1.2.2
50d5d16

Man1Lab v1.2.2 — LLM Platform & First-run Experience

Release date: 2026-07-08
Repository: https://github.com/maniac1um/Man1Lab
Status: Release Candidate

Overview

v1.2.2 completes the LLM Platform layer and delivers a polished first-run experience for external users installing Man1Lab via pip. New users can configure and switch LLM providers entirely through the CLI without editing configuration files.

v1.2.1 delivered complete Execution Planning. v1.2.2 delivers production-ready model management and release hardening for PyPI publication.

Milestone: Platform Capability
Previous: v1.2.1 (Execution Planning Stabilization)
Next: Repository Understanding (v1.3)

Highlights

  • LLM Provider foundation — LLMManager, ModelRegistry, ProviderRegistry
  • Multi-provider support — OpenAI, DeepSeek, Anthropic
  • Model Management CLI — full profile lifecycle via man1lab model
  • First-run wizard — interactive model setup during man1lab init
  • Portable profiles — man1lab model export / import (no secrets)
  • Doctor LLM validation — connection health and configuration checks
  • 614 unit tests passing
  • MIT License — LICENSE at repository root; declared in pyproject.toml and CITATION.cff
  • Release hardening — documentation sync, packaging validation, review directory normalization

Architecture Changes

No workflow or agent behavior changes. New platform layer:

CLI → Platform Facade → LLMManager → ModelRegistry → ProviderRegistry → LLMProvider

Business agents remain unaware of provider selection. Resolution happens inside LLMManager.

Execution Planning

Unchanged from v1.2.1 — six embedded providers with shared Decision Foundation (ADR-0018).

Workflow → Services → Providers → Decision Foundation → Builder → ExecutionStrategy

LLM Platform

Phase Deliverable Status
7.1 LLM Provider foundation ✅
7.2 Model Registry + persistence ✅
7.3 Anthropic provider ✅
7.4 Model Management CLI ✅
7.5 First-run Experience ✅
Component Location
LLMManager providers/llm/manager.py
ModelRegistry providers/llm/registry.py
ProviderRegistry providers/llm/provider_registry.py
Profile persistence conf/llm/user_profiles.yaml
Providers OpenAI, DeepSeek, Anthropic

CLI

Lifecycle

Command Description
man1lab init Workspace setup + optional first-model wizard
man1lab init --skip-model-config Legacy init behavior
man1lab doctor Environment + LLM validation
man1lab clean Remove regeneratable artifacts

Model Management

Command Description
man1lab model list List configured profiles
man1lab model current Show active profile
man1lab model use <profile> Switch active profile
man1lab model add Interactive profile creation
man1lab model remove <profile> Remove profile
man1lab model rename <old> <new> Rename profile
man1lab model test [profile] Provider health check
man1lab model validate Registry validation
man1lab model export <file> Export portable config (no secrets)
man1lab model import <file> Import profiles (--replace, --skip-existing)

Workflow (unchanged)

reproduce, analyze, discover, plan, execute, config, version

Model Management

Profiles are stored in conf/llm/user_profiles.yaml. API keys remain environment references only — never written to YAML.

Portable export format:

active: claude
profiles:
  claude:
    provider: anthropic
    model: claude-sonnet-4
    api_key_reference: ANTHROPIC_API_KEY
    enabled: true

First-run Experience

Recommended installation flow:

pip install man1lab
man1lab init          # configure first model interactively
man1lab doctor        # verify environment + LLM
man1lab reproduce paper.pdf

After successful init with wizard:

Workspace initialized.
Active model: default
Provider: Openai
Run `man1lab doctor` to verify your environment.

SDK

Unchanged public API:

from man1lab import Man1Lab, PLATFORM_VERSION, __version__

Model management is CLI-only in v1.2.2. SDK method exports planned for v1.3 polish.

Package Distribution

  • Version: 1.2.2
  • pip install man1lab
  • Console script: man1lab
  • Module entry: python -m man1lab
  • Bundled: conf/, prompts/, .env.example
  • Excluded: outputs/, logs/, mlruns/, workspace/tasks/

Bug Fixes

  • Fixed DoctorCheck import path in CLI tests
  • Synchronized version strings across application/version.py, pyproject.toml, and CLI --version
  • Corrected stale test counts and version references in documentation

Breaking Changes

None. All v1.2.1 CLI commands, SDK methods, and workflow behavior remain compatible.

Migration Notes

From v1.2.1

No migration required. Existing .env and Hydra configuration continue to work.

Optional: run man1lab init in an existing workspace to add named profiles via the wizard, or use man1lab model add.

From v1.2.0 or earlier

Follow v1.2.1 migration notes — no additional steps for v1.2.2.

Known Limitations

Inherited from v1.2.1 — see CURRENT_STATUS.md:

  • Discovery verification is shallow
  • MCP / REST interfaces not implemented
  • SDK does not expose model management methods
  • execution_planning.enabled=false transitional path remains

Future Roadmap (v1.3)

Direction Description
Repository Understanding Semantic mapping of repo structure to analysis modules
RepositoryKnowledge artifact New canonical object (design TBD)
SDK model management Export list_models(), use_model(), etc. on Man1Lab
MCP / REST interfaces Reserved in architecture

See ROADMAP.md.

Upgrade from v1.2.1

pip install --upgrade man1lab
man1lab --version   # 1.2.2
man1lab doctor

No configuration migration required.

Contributors

Man1Lab v1.2.2 Release Candidate — Platform Capability milestone.

Phase audits: reviews/7.1_llm_provider_foundation/ through reviews/7.5_first_run_experience/, reviews/1.2.2_release_candidate/.

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