* feat(cli): add --output-format stream-json for headless clients
Emit EvoScientist's native event stream as line-delimited JSON on stdout
in single-shot (-p) mode, with all human output redirected to stderr so
stdout stays pure JSONL. Intended as the integration surface for
programmatic clients (e.g. an agent runtime) that drive EvoSci headlessly.
- stream/json_sink.py: write_events_as_json + stream_json sink, plus
redirect_console_to_stderr helper for stdout purity
- cli/interactive.py: cmd_run gains output_format; stream-json branch runs
the sink instead of the Rich renderer
- cli/commands.py: --output-format option + validation (stream-json
requires -p; value must be text|stream-json)
- docs/stream-json.md: event-schema contract + example transcript
- tests: json sink serialization, CLI dispatch, console redirect, validation
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* fix(cli): honor explicit --no-auto-mode over config in stream-json
Address CodeRabbit review (discussion_r3514041123): the auto-mode override
block only wrote to cli_overrides when the resolved value was True, so an
explicit --no-auto-mode silently fell back to a config that enables
auto-mode -- breaking "explicit flags always win" and leaving stream-json
running unattended despite the warning. Write auto_mode=False when the flag
is explicitly False. Add regression tests that capture the overrides.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
* feat: add scheduler functionality with cron-style task management
- Implemented a new scheduler subagent to automate recurring tasks using cron expressions.
- Enhanced the subagent factory to include the skill manager and auxiliary chat model for the scheduler.
- Created a YAML configuration for the scheduler with a detailed system prompt and toolset.
- Updated README files to include documentation on scheduled tasks and usage examples.
- Added tests for the scheduler, including command execution, scheduling tools, and middleware integration.
- Introduced new dependencies for timezone handling and ensured compatibility in the project configuration.
* fix(async-notifier): ensure fallback hint is used for unknown notification kinds
* feat: enhance scheduling functionality and improve system message handling
- Ensure 'task' is excluded from the default PTC allowlist to prevent ValueError in langchain-quickjs >=0.3.
- Verify that essential async dispatch tools remain in the allowlist.
- Confirm that the live quickjs filter accepts the default allowlist even with a 'task' tool present.
- Test the creation of the code_interpreter middleware to ensure it builds correctly.
* feat(middleware): reposition code interpreter middleware in the stack
* feat(models): add qwen3.7-plus model entry and update context window comment
* feat(models): add qwen3.7-max and qwen3.7-plus model entries for DashScope
* feat(auxiliary): implement auxiliary model support for background tasks and tool selection
- Added auxiliary model configuration to EvoScientistConfig.
- Introduced _ensure_auxiliary_chat_model function to manage auxiliary model instances.
- Updated onboarding steps to include auxiliary model selection.
- Modified middleware to route tool selection to the auxiliary model when applicable.
- Enhanced tests to cover auxiliary model functionality and configuration.
* feat(steps): update UI backend selection options and descriptions
* Refactor code structure for improved readability and maintainability
* feat(patches): implement OpenRouter response reasoning item stripping to prevent multi-turn errors
* feat: update version to v0.1.4 in badges, README, and pyproject.toml; adjust skill counts in steps.py
* feat(config): add auxiliary model and provider environment variables to test setup
* feat(deploy): implement standalone LangGraph server and CLI command for deployment
* feat(deploy): enhance port validation and environment variable management for deployment
* Refactor langgraph dev deployment and introduce workspace sidecar protocol
- Updated the deployment mode handling in `server.py` to use a single environment variable `EVOSCIENTIST_DEPLOY_MODE` with values `full` and `stripped`.
- Enhanced the `manager.py` to implement a workspace fingerprint sidecar, allowing cross-process reuse of langgraph dev instances while ensuring workspace consistency.
- Introduced functions to write and read the workspace sidecar, with error handling for missing or corrupt data.
- Added tests for the workspace sidecar functionality, including validation of the JSON schema and ensuring proper error handling for workspace mismatches.
- Updated existing tests to reflect changes in deployment mode handling and added new tests for signal handling during shutdown.
- Ensured that cleanup routines remove the workspace sidecar alongside the PID file during shutdown.
* fix(langgraph): improve workspace sidecar checks for process ownership and stale handles
* feat(docker): official image with all runtime deps pre-installed
Multi-stage build using uv for the EvoScientist core + all messaging-channel
extras, plus Node.js 24 LTS (for npx-based MCP servers) and uv (for runtime
Python MCP installs) in the runtime layer. Runs as non-root user evosci,
with workspace, app data, and config (XDG_CONFIG_HOME) all consolidated
under a single /home/evosci/.evoscientist volume so a single mount
persists everything across container restarts.
Includes a docker-compose.yml starter, a build/push GitHub Actions
workflow targeting ghcr.io with multi-arch (amd64/arm64) and PR-only
build verification, a .dockerignore, and a new Docker section in the
README documenting mounts, derivation recipes for the unbundled stt /
oauth / TinyTeX extras, and proxy/cert handling expectations.
* fix(docker): pin trixie base + drop redundant python image
Switch builder and runtime from `python:3.11-slim-bookworm` to a single
`ghcr.io/astral-sh/uv:python3.11-trixie-slim` base — trixie drops several
CRITICAL vulnerabilities that bookworm carries today, and reusing the uv
image for runtime eliminates the separate `COPY --from=…/uv` line.
* chore(docker): pin GitHub Actions to commit SHAs in workflow
Replace mutable major-version tags with full commit SHAs (with the
corresponding semver tag in a trailing comment) so a compromised /
retagged action release can't silently change what runs in the publish
pipeline.
* chore(deps): enable Dependabot version updates for Dockerfile pins
Adds a weekly `docker` ecosystem that watches the Dockerfile's `FROM` /
`COPY --from=` references — including the ARG-bound `BASE_IMAGE` and
`NODE_IMAGE` digests — and opens one grouped PR per cadence bumping
both the @sha256 digest and the trailing version comment. This keeps
the otherwise-frozen pins flowing with Debian point releases and
upstream patches.
* fix(docker): use nodejs alias stage so NODE_IMAGE ARG actually resolves
`COPY --from=${NODE_IMAGE}` left the dollar-curly literal at parse time
under buildkit 29.x — it expands ARGs in `FROM` but reads `--from=` as a
static stage/image name. Introduce a tiny `FROM ${NODE_IMAGE} AS nodejs`
alias and `COPY --from=nodejs …` against it, which preserves the
ARG-driven Dependabot updates without tripping the parser.
* fix(docker): harden venv ownership and PATH ordering
- Drop `--chown` on the `/opt/venv` COPY so the venv stays root-owned.
The runtime user only needs read+execute (default Unix perms allow
that); making it user-owned let the agent rewrite its own
dependencies, which defeats the sandboxing premise. All persistent
agent state already lives under /home/evosci/.evoscientist/.
- Reorder PATH so /opt/venv/bin precedes the user-writable
UV_TOOL_BIN_DIR. Otherwise a stray binary dropped into the latter
(e.g. via `uv tool install`) could shadow the canonical
`evosci` / `python` / `pip` shipped with the image.
* docs: update README
* docs(docker): warn about non-root UID and `curl | sh` for derived images
- The image runs as `evosci` (UID 1000), so a host-side `./workspace`
bind mount fails if the host user has a different UID — same gotcha
that bites onboarding's `mcp.yaml` write. Add an !IMPORTANT block
with the two practical fixes (`chown -R 1000:1000` once, or
`--user "$(id -u):$(id -g)"` on each run).
- The TinyTeX derivation snippet pipes an unpinned remote installer
into `sh`. Add a one-line pointer to fetching a pinned release
tarball from `rstudio/tinytex-releases` for users who'd rather not
trust the upstream script blindly. The official installer is kept
as the default since that's what TinyTeX itself recommends.
* chore(docker): cancel in-flight workflow runs + flag iMessage as host-only
- Add `concurrency: cancel-in-progress: true` to the docker workflow
so successive pushes on the same ref supersede the prior run rather
than queueing in parallel — multi-arch buildx is the slowest job in
CI, no point burning minutes on superseded builds.
- Spell out that the docker image installs the `all-chanels` extra and
call out iMessage as a deliberate host-only exclusion: it requires
the `imsg` CLI bridging to macOS's Messages.app, which no Linux
container config can satisfy.
* chore(release): update version to v0.0.8 and dependencies in project files
* feat(models): add new model entries for Claude Opus 4-7 and update version handling
* Refactor code structure for improved readability and maintainability
* chore(assets): update wechat_group image file
* Refactor code structure for improved readability and maintainability
* feat(backends): enhance MergedReadOnlyBackend with improved ls, grep, and glob methods
* fix(docs): update WeChat QR code image link in README files
* feat(skills): enhance skill management to support global and workspace tiers
* style: apply ruff format to skills_cmd and commands/implementation/skills
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix(skills): improve uninstall_skill to prevent removal of built-in skills
* fix(docs): update skill installation documentation for clarity on global and user directories
* fix(skills): enhance uninstall_skill to validate skill directory before removal
* fix(skills): improve error handling in install_skill and uninstall_skill for directory creation and validation
---------
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix: update OpenRouter API key validation to use /auth/key endpoint and httpx
* Refactor code structure for improved readability and maintainability
* feat: enhance welcome banner to include file commands indication
* feat: update LaTeX setup prompt to use selection UI for better user experience
* feat: update version to v0.0.5 in badges and project configuration
* feat(tui): enhance conversation history rendering and implement two-level thread hierarchy in picker
* feat(tui): improve conversation history display and enhance thread selection UI
* feat(file_mentions): implement @file mention parsing and completion for CLI and TUI
* feat(uv-tool): add compatibility checks and installation helpers for uv tool environments
* feat(dependencies): update package versions in uv.lock for compatibility and improvements
* feat(badges): update PyPI version to v0.0.4 in SVG assets and README files
* feat(tests): format code in TestUvToolCompat for improved readability
* feat: implement background update check and startup notifications
* feat: enhance user experience with timestamp notifications and UI polish
* feat: implement multi-line chat input with Enter-to-submit and modifier+Enter newline
* update
* update
* v0.0.3
* feat: improve code readability with consistent formatting in TUI and test files
* feat: update PyPI badge version to v0.0.3 in README files
* feat: add docstrings for test classes in test_update_check.py
* feat: update MiniMax integration to use Anthropic-compatible endpoint and enhance routing logic
* refactor: streamline OAuth install hint and update ccproxy health check timeout
Add MiniMax (api.minimax.io/v1) as a first-class third-party provider,
enabling direct API access without routing through NVIDIA/SiliconFlow/
OpenRouter intermediaries. Includes M2.5 and M2.5-highspeed models
with 204K context window.
Changes:
- Register "minimax" in _THIRD_PARTY_PROVIDERS with MINIMAX_API_KEY
- Add MiniMax-M2.5 and MiniMax-M2.5-highspeed model entries
- Add minimax_api_key to config, env mappings, and env export
- Add MiniMax to onboarding wizard with API key validation
- Update .env.example, README.md, README.zh-CN.md
- Add 9 unit tests and 3 integration tests (all passing)
Co-authored-by: PR Bot <pr-bot@minimaxi.com>
Co-authored-by: Xi Zhang <106144707+X-iZhang@users.noreply.github.com>
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