Claude models are served on /messages, which the OpenAI SDK can't speak, so
those runs go through LiteLLM's Anthropic route instead. Prompt caching moves
with them, since LiteLLM consumes the injection points the raw SDK rejects.
Zen and Go now show up by name instead of both reading 'OpenCode
subscription', and Zen keeps its cost tracked: it bills prepaid credits per
request, so those runs were never actually free.
* add extra-files plumbing so orchestrators can drop single files into the sandbox workspace
* reject extra-file paths that collide with a local source tree
* add --workspace-file so CLI users can place files in the sandbox workspace
* reject repeated and control-character workspace paths
* revalidate persisted workspace files when resuming a run
* drop the workspace-file size limit
* make the working-directory prompt answer the mouse
Its Confirm and Cancel were drawn as buttons and did nothing when clicked: the
modal mouse handler had a case for every dialog except this one, so a click fell
through and the scan sat waiting on an answer the user believed they had given.
Only the keyboard could answer it.
The prompt is docked in a corner rather than centered, so it also needs its own
bounds; the centered ones every other dialog uses would have put the buttons in
the wrong place. Those bounds now come from the same placement cornerOverlay
draws with.
Two returns that hand back the model alongside a call that mutates it are now
sequenced explicitly. They work, but only because the compiler happens to
evaluate the call first, and one of them is what puts the prompt back in the
composer when the mount is declined.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* skip the mount instead of abandoning the scan
Declining the working-directory prompt threw the whole launch away and dropped
back to the start screen, which is a lot to lose for answering one question
about one directory. The two answers are now about the directory alone: mount it,
or run without it. The prompt is the whole of the input either way.
The buttons say which is which - Mount and Skip rather than Confirm and Cancel -
and the prompt says what skipping costs.
A run with neither target nor directory is a real run, so two things follow it.
It can be resumed: its instruction is what drives it, and that is in the run
record. And it tells the agent plainly that it has neither, because an agent
given no scope goes looking for the one it assumes it was meant to have.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
* perf(cli): fast startup — lazy heavy imports + onedir standalone build
* perf(cli): drop legacy single-file compat from install/self-update
* perf(cli): simplify — drop constants module and extra lazy-import refactors
* refactor(update): strix --update just re-runs the install script
* perf(cli): drop packaging/install/update changes; deepen lazy imports instead
Reverts the onedir build, install.sh, and self-update changes so release
mechanics stay untouched. Startup cost is addressed purely by deferring
heavy imports (agents/openai, config.models, report state/writer, docker)
until a scan actually runs; DEFAULT_MAX_TURNS moves to strix.config.settings
so argparse no longer pulls the agents SDK.
---------
Co-authored-by: Ahmed Allam <ahmed39652003@gmail.com>
feat(inputs): implement logic for required tool choice based on model
test(inputs): add tests for force_required_tool_choice behavior
test(runner): update tests to include force_required_tool_choice in settings
* fix: resolve pre-commit check failures
- Change RuntimeError to TypeError for type validation in report/writer.py
- Update pyupgrade to v3.21.2 for Python 3.14 compatibility
* chore: add pytest test infrastructure
Mirror the layout introduced on feature/438-token_budget: pytest +
pytest-asyncio dev deps, asyncio_mode auto, a tests.* mypy override, and
pytest in the mypy pre-commit hook deps so the tests/ package type-checks.
* feat: add --mount and large-target pre-flight for local repos (#492)
Large local targets were copied into the sandbox file-by-file via the SDK
LocalDir entry, which stalls on big repos and could leave /workspace empty.
- --mount <path> bind-mounts a host directory read-only at /workspace/<subdir>
instead of copying it, bypassing the per-file stream.
- A size pre-flight (STRIX_MAX_LOCAL_COPY_MB, default 1024) fails fast with a
clear message suggesting --mount when a non-mounted local target is too big.
* fix: reject empty --mount paths
An empty or whitespace-only --mount value resolves to the current working
directory and would silently bind-mount it into the sandbox. Reject it.
* fix: dedupe local targets so a dir is never both copied and mounted
If the same directory is passed via --target and --mount (or as duplicate
values), it previously produced two targets — copied AND bind-mounted, and
the copied one could trip the size pre-flight. Dedupe by resolved path,
preferring the bind mount.
* fix: treat non-positive STRIX_MAX_LOCAL_COPY_MB as disabled
Previously a value of 0 (or negative) made every local target count as
oversized, aborting all local scans. Now <= 0 disables the pre-flight.
* fix: log unreadable subtrees during size pre-flight
os.walk silently swallowed directory-listing errors, so a permission-denied
subtree could make a large repo under-count and slip past the pre-flight.
Surface such omissions via an onerror warning.
* docs: document --mount and STRIX_MAX_LOCAL_COPY_MB
Add CLI reference + example for --mount, document the size pre-flight env var,
note the read-only-is-not-a-hard-boundary caveat and that remote repos are not
size-checked, and clarify the backends docstring on when bind mounts apply.
* Update strix/interface/main.py
* Update strix/runtime/docker_client.py
---------
OpenAI's Responses API rejects reasoning.effort on non-reasoning
models like gpt-4o with `unsupported_parameter`, so any scan with
the default STRIX_REASONING_EFFORT=high against gpt-4o crashed at
the first model call. drop_params=True absorbs the rejected param
on LiteLLM-routed models but the SDK's native OpenAI path has no
equivalent.
Lift model_supports_reasoning to a public helper that strips
litellm/, any-llm/, openai/ prefixes and falls back to last-segment
lookup so prefixed forms like anthropic/claude-opus-4-7 resolve
through the bare model_cost entry. make_model_settings regains
model_name and skips Reasoning() when the registry doesn't confirm
support. uses_chat_completions_tool_schema reuses the same helper
(was duplicating the lookup under a misleading name).
Drop every hand-rolled provider table and per-model gating that had
accumulated in the model-handling layer:
* normalize_model_name no longer auto-prefixes bare claude-* / gemini-*
names. Users supply the full <provider>/<model> form. The function
became literally model_name.strip(), so callers now inline that and
the function is removed.
* tool_choice="required" is gone everywhere. Thinking-mode endpoints
(Anthropic, DeepSeek /beta) reject it; modern reasoning models don't
need it; non-interactive runs already have
_append_noninteractive_tool_required_message as the convergence
backstop. model_supports_reasoning, model_known_to_registry, and
_model_cost_entry were only used to gate this and follow it out.
* Reasoning(effort=...) is now attached whenever
STRIX_REASONING_EFFORT is non-none. litellm.drop_params=True absorbs
it for non-reasoning models.
* Warm-up's bare-name OpenAI 401 hint is removed (false-positive prone,
relied on substring matching).
* reset_tool_choice on SandboxAgent is no-op now (no tool_choice gets
set) and is removed.
* report/dedupe.py was still routing through stock MultiProvider, so
non-OpenAI configs failed the dedupe LLM pass; switch it to
StrixProvider.
Verified end-to-end against modern provider strings (openai/gpt-5.4,
anthropic/claude-opus-4-7, deepseek/deepseek-reasoner,
gemini/gemini-2.5-pro, groq/, xai/, mistral/, together_ai/, perplexity/,
openrouter/, litellm/ legacy form, and whitespace-padded input): 18/18
cases route correctly, env vars mirror via litellm.validate_environment,
and ModelSettings carries no tool_choice. mypy strict passes.
When the user opts into reasoning_effort but the configured model
isn't in litellm.model_cost at all (private SKUs, fresh releases the
registry hasn't picked up — e.g. deepseek/deepseek-v4-pro), we can't
confirm thinking support and were sending tool_choice="required",
which thinking-mode endpoints reject ("Thinking mode does not support
this tool_choice").
Add model_known_to_registry() and split the decision: when the user
wants reasoning AND the model is either confirmed-reasoning OR
unknown-to-registry, drop tool_choice. The Reasoning(effort=...) param
still only attaches for confirmed-reasoning models, so we don't send
reasoning hints to known non-reasoning models.
Known non-reasoning models (gpt-4o, registry-confirmed) keep
tool_choice="required" unchanged.
Five rounds of sweep across the tree. Net ~544 lines removed.
Removed:
- Section-divider banners and one-line section labels (# Display
utilities, # ----- list_requests -----, # CVSS breakdown, etc.).
- Module-level prose docstrings on internal modules. Kept one-line
summaries; trimmed multi-paragraph narration about SDK/Strix
responsibility splits, cache strategies, three-source precedence.
- Internal-helper docstrings that just restate the function name —
caido_api helpers (caido_url, get_client, view_request, etc.),
settings-class one-liners (LLMSettings, RuntimeSettings, ...),
UI helper docstrings.
- Args/Returns blocks on non-LLM-facing internal helpers
(build_strix_agent, render_system_prompt, create_or_reuse,
bootstrap_caido) — kept only the genuinely non-obvious params.
- Internal-history phrasing — "Mirrors main-branch shape",
"pre-SDK harness", "previous lookup matched no attribute".
- Narrative comments inside function bodies that explained what the
next line does, design rationale obvious from the surrounding code,
or "we used to..." asides.
- Trailing periods on every error-string literal across the tool tree.
- Duplicated roundtripTime quirk comment (kept the LLM-facing copy in
tools/proxy/tools.py).
Kept (every one names an upstream bug, vendored-code provenance, or
non-obvious data quirk):
- core/runner.py: SDK replay-with-empty-initial-input + on_agent_end
lifecycle gap.
- runtime/docker_client.py: VERBATIM COPY block of the upstream
_create_container body, pinned to SDK v0.14.6.
- runtime/session_manager.py: NO_PROXY for agent-browser CDP loopback.
- tools/proxy/caido_api.py: generated-pydantic Request.raw quirk,
replay double-history pitfall.
- tools/proxy/tools.py: Caido roundtripTime=0 quirk for proxy
captures.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Jonathan Singer