Apodex – FrontierAgent

Apodex released FrontierAgent, an open-source agent runtime, terminal product, and evaluation suite for long-horizon research and file-based work, available through an OpenAI-compatible Apodex-1.1 endpoint with no model hosting required. The `frontier-agent` TUI ships two native workflows, ReAct and Agent Team, and the same workflow engine powers the benchmark runner used to evaluate Apodex models. The framework, tools, workflows, and evaluation layer remain separate so each can be reused independently.

FrontierAgent is an open-source agent runtime, terminal product, and evaluation suite for long-horizon research and file-based work. The frontier-agent TUI ships two native workflows: - ReAct — one stateful agent researches, reads files, writes deliverables, runs commands, and iterates in a task-scoped sandbox. - Agent Team — a coordinator maintains a task board, delegates independent work to parallel sub-agents, collects their reports, and synthesizes the result. The same workflow engine powers the benchmark runner used to evaluate Apodex models. The framework, tools, workflows, and evaluation layer remain separate, so each can be reused independently. Important No model hosting required. Get an API key, connect to the OpenAI-compatible Apodex-1.1 endpoint, and start running FrontierAgent in minutes. → Start building for free at platform.apodex.ai https://platform.apodex.ai/ ⏳ This is a limited-time offer—come try it and let us know what you build New here? Use the documentation index https://github.com/ApodexAI/FrontierAgent/blob/main/docs/README.md to find the right installation, SGLang, workflow, evaluation, or developer guide. - Native Agent Team workflow. The coordinator decomposes the request, dispatches bounded parallel assignments, receives structured reports, and can use an optional fast reporter for final evidence review. - Task Board. Agent Team's add task and update task events appear live in the TUI sidebar with pending, active, completed, blocked, and cancelled state. - Sandboxed file work. Shell and file tools share one task-scoped filesystem: /inputs is read-only, /workspace is working state, and /outputs contains persistent deliverables. Authorization and sandbox failures are fail-closed. - Asynchronous intervention. Type while an agent is running to queue a new instruction. It is injected at the next safe turn boundary without discarding the active run. In Agent Team mode it steers the coordinator; already-running sub-agents are allowed to finish. - Transparent deliverables. On macOS/Docker, /outputs maps to .apodex/runs/<session-id /outputs on the host. The same run directory also contains its checkpoint, trace, engine log, and trajectories. - Approval, trace, and recovery. Mutating operations show a diff and require approval unless --yes is enabled. Sessions are checkpointed, every action is traced locally, /revert restores session changes, and --resume continues a saved run. - Evaluation included. The subprocess runner supports research and file-grounded benchmarks, deterministic artifact collection, concurrency, progress inspection, and rerunning individual failures. Conceptual Agent Team workflow, from task delegation and asynchronous report collection to verification and final synthesis. php flowchart LR U "User / benchmark task" -- TUI "TUI or subprocess runner" TUI -- R "Stateful ReAct" TUI -- C "Agent Team coordinator" C -- B "Task board" B -- S1 "Sub-agent 1" B -- S2 "Sub-agent 2" B -- SN "Sub-agent N" R -- FS "Task sandbox" S1 -- FS S2 -- FS SN -- FS FS -- I "/inputs read-only " FS -- W "/workspace working files " FS -- O "/outputs deliverables " S1 -- C S2 -- C SN -- C C -- A "Final answer / report" R -- A The repository boundaries are intentional: frontier agent/ generic loop, scheduling, registries, AgentBus, observers plugins/tools/ web, shell, file, sandbox, and team tool implementations workflows/ ReAct and Agent Team pipelines, profiles, prompts, observers apodex/ terminal CLI/TUI, approvals, sessions, traces, and Docker path benchmarks/ public harness plus bundled FrontierSearchBench/FrontierChallenge More detail: framework architecture https://github.com/ApodexAI/FrontierAgent/blob/main/docs/framework.md , Agent Team https://github.com/ApodexAI/FrontierAgent/blob/main/workflows/agent team/README.md , and Stateful ReAct https://github.com/ApodexAI/FrontierAgent/blob/main/workflows/stateful react agent/README.md . See run artifacts and timestamps https://github.com/ApodexAI/FrontierAgent/blob/main/docs/run-artifacts.md for the on-disk layout. Requirements: Git, Python 3.12, uv https://docs.astral.sh/uv/ , and an OpenAI-compatible model endpoint. Docker is optional. git clone https://github.com/ApodexAI/FrontierAgent.git cd FrontierAgent uv sync --python 3.12 --extra dev cp .env.example .env Add your endpoint to .env : OPENAI API KEY=your-key OPENAI BASE URL=https://your-openai-compatible-endpoint/v1 OPENAI MODEL=your-model-name Optional web research tools SERPER API KEY= JINA API KEY= Start the TUI: Stateful single-agent workflow uv run frontier-agent --mode react --cwd /path/to/project Coordinator plus parallel sub-agents uv run frontier-agent --mode agent team --cwd /path/to/project uv sync above installs the lightweight terminal runtime. Scientific and document packages are intentionally optional in native mode; the agent installs only what a task actually needs into <project /.apodex/runtime/native . The apodex command is retained as a compatibility alias. Prefer a script that does all of the above? ./scripts/run-macos.sh and ./scripts/run-linux.sh set up a hosted-endpoint install, and ./scripts/run-linux-gpu.sh --install-system-deps --setup-only prepares a native, isolated SGLang environment on a Linux NVIDIA GPU. The step-by-step equivalent is the endpoint quickstart https://github.com/ApodexAI/FrontierAgent/blob/main/docs/install/tui-endpoint-quickstart.md 中文教程 https://github.com/ApodexAI/FrontierAgent/blob/main/docs/install/tui-endpoint-quickstart.zh-CN.md , which requires neither model self-hosting nor Docker. Local SGLang serving is pinned to reviewed NVIDIA driver / CUDA / SGLang tracks, and a mismatch surfaces late as opaque CUDA or Triton kernel errors during model load. Confirm your nvidia-smi driver against the GPU compatibility matrix https://github.com/ApodexAI/FrontierAgent/blob/main/docs/install/gpu-compatibility.md before choosing an image tag or native pin. The GPU helper selects a reviewed userspace track from the host driver, but never installs or replaces the driver itself. The operating system, FrontierAgent runtime, and model runtime are independent choices. “NVIDIA” describes the local model service, not how the agent itself runs. Unsure which applies to your machine or GPU provider? Start with the installation chooser https://github.com/ApodexAI/FrontierAgent/blob/main/docs/install/README.md . | Environment | FrontierAgent runtime | Model endpoint | Start here | |---|---|---|---| | macOS | native or Docker Desktop | hosted or another OpenAI-compatible endpoint | macOS https://github.com/ApodexAI/FrontierAgent/blob/main/docs/install/macos.md | | Linux host/VM | native default , bubblewrap, or Docker | hosted, native SGLang, or Docker SGLang | Linux https://github.com/ApodexAI/FrontierAgent/blob/main/docs/install/linux.md | | managed Linux GPU container | native inside the provider container | custom GPU image or native SGLang | GPU platforms https://github.com/ApodexAI/FrontierAgent/blob/main/docs/install/gpu-platforms.md | | Windows | WSL2, treated as Linux | hosted or a WSL2-reachable endpoint | Linux/WSL2 https://github.com/ApodexAI/FrontierAgent/blob/main/docs/install/linux.md windows-and-wsl2 | Chinese-speaking macOS users can use the macOS 中文安装与一键启动指南 https://github.com/ApodexAI/FrontierAgent/blob/main/docs/install/macos.zh-CN.md . Pre-built linux/amd64 and linux/arm64 images are published to the GitHub Container Registry, so no local Python environment is needed: cp .env.example .env docker compose run --rm agent - Run FrontierAgent in Docker https://github.com/ApodexAI/FrontierAgent/blob/main/docs/install/docker.md — Compose, image pinning, direct docker run , and EC2/ECS deployment. - Docker SGLang on a Linux NVIDIA host https://github.com/ApodexAI/FrontierAgent/blob/main/docs/install/linux-nvidia.md — two containers on one network; SGLang owns the GPU. - Native SGLang without nested Docker https://github.com/ApodexAI/FrontierAgent/blob/main/docs/install/linux-nvidia-native.md — for managed GPU environments that forbid a nested daemon. - SGLang configuration reference https://github.com/ApodexAI/FrontierAgent/blob/main/config/sglang/README.md — every .env.sglang variable, token-budget invariants, and tuning order. Production 35B templates for RTX 4090, RTX 5090, and two-GPU hosts live under config/sglang/ . Run without a task for an interactive session, or pass one and stay in the session for follow-ups: uv run frontier-agent --mode agent team --cwd /repo \ "Research the alternatives, verify the evidence, and write a report" One-shot, line mode, or resume a saved session uv run frontier-agent --mode react --cwd /repo -p "explain src/main.py" uv run frontier-agent --mode agent team --no-tui "compare these implementations" uv run frontier-agent --resume Attach read-only documents before the TUI starts repeatable uv run frontier-agent --mode react --cwd /repo \ --input ~/Downloads/claim.pdf --input ~/Desktop/photo.jpg The sidebar carries the plan/task board, live tool activity, deliverables, and a session-scoped diff. While a workflow is busy, typing a follow-up queues it for the next safe turn boundary rather than interrupting the run. For the four sidebar tabs, previews, approvals, attachments, clipboard support, keys, and Agent Team live steering, see the TUI user guide https://github.com/ApodexAI/FrontierAgent/blob/main/docs/tui-user-guide.md 中文使用教程 https://github.com/ApodexAI/FrontierAgent/blob/main/docs/tui-user-guide.zh-CN.md . The full slash-command, option, and theming reference is apodex/README.md https://github.com/ApodexAI/FrontierAgent/blob/main/apodex/README.md . | Mode | Best for | Execution model | |---|---|---| | react | focused research, repository analysis, document/file work | one stateful agent using the tui workflow profile | | agent team | broad questions that benefit from decomposition and parallel investigation | coordinator, persistent task board, bounded parallel sub-agents, report collection, synthesis | Agent Team parallelism is additional to benchmark concurrency. When evaluating, start with --concurrency 1 ; total simultaneous model calls can approach runner concurrency multiplied by the team spawn limit. Set SWARM NO WEB=1 to disable Agent Team web tools or REACT NO WEB=1 for closed-book ReAct tasks. | Path | Policy | Purpose | |---|---|---| | /inputs | read-only | supplied documents and benchmark inputs | | /workspace | read-write | source checkout, extracted data, scratch work | | /outputs | controlled read-write | final persistent deliverables | File and shell tools share this one task sandbox and path policy. Interactive sessions add an approval gate on writes, deletion, package installation, and risky shell commands; some operations stay denied even with --yes ; and file mutations are journaled so /revert can undo them. Details: sandboxing and path policy https://github.com/ApodexAI/FrontierAgent/blob/main/docs/framework.md sandboxing , approval and trace behavior https://github.com/ApodexAI/FrontierAgent/blob/main/apodex/README.md safety , and the security policy https://github.com/ApodexAI/FrontierAgent/blob/main/SECURITY.md . uv sync --frozen --extra sandbox --extra document-readers --extra eval --extra dev uv run pytest -q uv run ruff check . See CONTRIBUTING.md https://github.com/ApodexAI/FrontierAgent/blob/main/CONTRIBUTING.md for the full development environment, pre-flight checks, session debugging, and submission process. Building the container image is covered in Run FrontierAgent in Docker https://github.com/ApodexAI/FrontierAgent/blob/main/docs/install/docker.md build-from-the-current-checkout . The evaluation harness runs each benchmark question in an isolated subprocess, supports resumable multi-run experiments, and dispatches benchmark-specific deterministic or model-based judges. A minimal smoke run, once the datasets are downloaded per the evaluation guide https://github.com/ApodexAI/FrontierAgent/blob/main/docs/eval.md datasets , is: uv sync --extra eval --extra sandbox --extra document-readers uv run python -m benchmarks.public.runner.run subprocess \ --benchmark browsecomp --pipeline stateful-react-agent --profile default \ --limit 1 --concurrency 1 --out ./results/smoke The evaluation guide https://github.com/ApodexAI/FrontierAgent/blob/main/docs/eval.md is the canonical operator reference for credentials, judge preflight, datasets, file benchmarks, execution, and result inspection. The benchmark registry https://github.com/ApodexAI/FrontierAgent/blob/main/benchmarks/README.md lists dataset keys, default pipelines, scoring implementations, and extension points. FrontierSearchBench has its own external scorer and an isolation requirement, so it is documented separately in FrontierSearchBench evaluation https://github.com/ApodexAI/FrontierAgent/blob/main/docs/eval-frontier-search.md . BrowseComp, BrowseComp-ZH, xbench-DeepResearch, Humanity's Last Exam text-only , SuperChem, FrontierScience-Research, FrontierScience-Olympiad, DeepSearchQA, WideSearch, FrontierSearchBench, OfficeQA, GDPval, APEX, and OneMillion-Bench. GDPval uses deterministic deliverable validation in this open-source harness; the agentic pairwise grader is intentionally excluded. The benchmark registry https://github.com/ApodexAI/FrontierAgent/blob/main/benchmarks/README.md supported-benchmarks is authoritative for each dataset key, its default pipeline, and its scoring implementation. The chart above compares the two FrontierAgent workflows with the Apodex-1.0 baseline and selected external systems. The Apodex results are summarized here: | Configuration | APEX-Agents | GDPval | FrontierFinance | FrontierScience-Research | BioMysteryBench | HLE | |---|---|---|---|---|---|---| | Apodex-1.1 Agent Team | 38.5 | 78.8 | 54.3 | 63.3 | 35.3 | 56.1 | | Apodex-1.1 ReAct | 34.4 | 69.5 | 48.7 | 55.0 | 23.5 | 53.2 | | Apodex-1.0 | 16.5 | 59.3 | 40.3 | 28.3 | 17.6 | 49.0 | Earlier Apodex-1.0 checkpoints remain available in the Hugging Face collection https://huggingface.co/collections/apodex/apodex-1 , with model cards and serving guidance. Cite the current release: @article{apodex11, title = {Apodex-1.1: Scaling Agentic Intelligence for Complex Work}, author = {Apodex Team}, year = {2026}, eprint = {2608.23283}, archivePrefix = {arXiv}, primaryClass = {cs.AI}, url = {https://arxiv.org/abs/2608.23283} } @misc{frontierchallenge, title = {FrontierChallenge: Evaluating Scientific Workflow Completion}, author = {Su, Liangcai and Feng, Zhaopeng and Chen, Zhuo and Zhang, Zhen and Lin, Xiang and Li, Ruilin and Zhang, Handuo and Wang, Ning and Wen, Kailong and Guo, Yueqi and Xing, Feng and Guo, Yiling and Qian, Chenxiong and Du, Simon Shaolei and Bing, Lidong and Wang, Xinyu}, year = {2026} } For work that refers specifically to the previous generation: @techreport{apodex10, title = {Apodex-1.0: A Verification-Centric Agent Team for Discoverative Intelligence}, author = {Apodex Team}, year = {2026} } Apache 2.0 — see LICENSE https://github.com/ApodexAI/FrontierAgent/blob/main/LICENSE .