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Status and roadmap

Early alpha

Everything listed here is a work in progress. "Shipped" means the code exists on PyPI and you can install it, not that it's stable or production-ready. APIs will change. This page will be updated as things solidify.

What's shipped

Core libraries (Phase 1)

Package Version PyPI Status
qwen-think v0.1.2 pip install qwen-think Shipped
qwen3.6-mtp v0.1.1 pip install qwen3.6-mtp Shipped
qwen3-repo v0.1.0 pip install qwen3-repo Shipped
forge-infer v0.3.0 pip install forge-infer Shipped (includes ForgeEngine)
qwen-compat -- GitHub Test matrix + upstream PRs

Product layers (Phase 2)

Package Version PyPI Status
forge-observe v0.1.1 pip install forge-observe Shipped
forge-infer-cloud v0.1.2 pip install forge-infer-cloud Shipped
forge-dashboard v0.1.1 pip install forge-dashboard Shipped
forge-studio v0.1.0 GitHub Shipped (FastAPI + React)
Open WebUI plugins -- GitHub Shipped (4 plugins)

Upstream contributions

PR Repo Status
#15899 ollama/ollama Open -- qwen35moe architecture support
#15901 ollama/ollama Open -- format constraint for all thinking parsers
#15902 ollama/ollama Open -- NVFP4 BF16 exemption for linear_attn

What's planned

Multi-model support. The session and routing layers are designed around Qwen3.6 today. Mistral Small 4 (configurable reasoning effort), GLM-5.1, and DeepSeek V4 (dual thinking/non-thinking mode) have the same patterns. Adding support means writing backend normalizers for each model's flag format -- the router and budget manager are already model-agnostic in structure.

Domain-specific agents (Phase 3). Medical coding, legal research, deep research -- same Forge infra stack with domain-tuned routing policies. Not fine-tuning models; tuning the control plane. These only make sense to build once the core tools have real users asking for them.

Hosted deployment. forge-cloud and forge-dashboard are both designed for self-hosting today. Managed hosting is planned if there's demand.

How development is prioritized

New features and modules ship when there's demonstrated demand -- GitHub issues, community requests, or usage patterns that justify the work. If you're using any of these packages and have a use case that's not covered, open an issue on the relevant repo.