Ulysses — a hardened fork of Odysseus AI. Self-hosted AI model management for the Helm home server.
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* fix(chat): strip executed email tool fences from the live stream (#3993) The backend strips every fenced tool block from persisted text (the regex in src/tool_parsing.py is built from the full TOOL_TAGS set, which includes the email tools), so a reloaded session renders cleanly. The live frontend path uses a separate hardcoded EXEC_FENCE_RE in static/js/chatRenderer.js that only listed web_search/read_file/write_file/create_document/edit_document/ update_document — so executed email tool fences (list_emails, etc.) lingered as raw code blocks in the live assistant bubble until the user reloaded. Add the nine email tool tags to EXEC_FENCE_RE so the live render settles into the same clean layout as the history reload. bash/python stay excluded on purpose: those are languages a user may legitimately have asked the model to show as code, not tool invocations. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * refactor(chat): single-source live exec-fence tool list from TOOL_TAGS (#3993) Per review: EXEC_FENCE_RE was a second, hand-maintained copy of the executable-tool list, so any tool not in it — and every future tool added to TOOL_TAGS — would leave its executed fence lingering in the live bubble until reload (the original #3993 bug, recurring one tool at a time). EXEC_FENCE_RE is now built from an explicit EXEC_TOOL_TAGS list that mirrors TOOL_TAGS (src/agent_tools/__init__.py) minus bash/python, which stay excluded as legitimate code-example languages. A new regression test (test_exec_fence_re_covers_all_executable_tools) extracts both lists from source and fails if they drift, so the whole class is caught in CI instead of by a user — the "minimum acceptable middle ground" from the review, made exact (set equality, not just coverage). Verified: pytest tests/test_live_strip_email_tool_fences.py (5 passed); node --check static/js/chatRenderer.js; and a node run of the built regex confirms email/generate_image/manage_memory/ls fences strip while bash/python/sh are preserved. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * refactor(chat): build live exec-fence list from /api/tools at runtime (#3993) Make TOOL_TAGS the single source for live exec-fence stripping. chatRenderer.js no longer hard-codes a tool list; it fetches the backend's authoritative set once from GET /api/tools (sorted(TOOL_TAGS)) and builds EXEC_FENCE_RE from it at load, minus bash/python. No second list to drift, and a future tool added to TOOL_TAGS is covered automatically — without touching the streaming path. Until the fetch resolves EXEC_FENCE_RE is null and exec fences aren't stripped (a sub-second window before the first stream); the backend already strips persisted history, so a reload always renders clean. Drop test_exec_fence_re_covers_all_executable_tools (no hand-maintained list to guard) and add source-level guards: the frontend keeps no hard-coded list and fetches /api/tools, and the endpoint serves the full sorted(TOOL_TAGS). Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01CVCKth4g8pWh7pwFDVm4iL * fix(chat): warn on /api/tools fetch failure instead of swallowing it (#3993) A fresh-context review flagged that loadExecFenceRegex's catch silently discarded errors: if the one-shot fetch fails, EXEC_FENCE_RE stays null for the whole session and live exec fences go unstripped until reload, with zero signal. console.warn it, and correct the comment to describe the failure mode honestly (was understated as just a sub-second startup window). Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01CVCKth4g8pWh7pwFDVm4iL --------- Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
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| .env.example | ||
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| ACKNOWLEDGMENTS.md | ||
| app.py | ||
| build-macos-app.sh | ||
| build-windows-portable.ps1 | ||
| CONTRIBUTING.md | ||
| docker-compose.gpu-amd.yml | ||
| docker-compose.gpu-nvidia.yml | ||
| docker-compose.yml | ||
| Dockerfile | ||
| install-service.sh | ||
| launch-windows.ps1 | ||
| launcher.py | ||
| LICENSE | ||
| odysseus-ui.service | ||
| Odysseus.spec | ||
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| README.md | ||
| requirements-optional.txt | ||
| requirements.txt | ||
| ROADMAP.md | ||
| SECURITY.md | ||
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| THREAT_MODEL.md | ||
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A self-hosted AI workspace for chat, agents, research, documents, email, notes, calendar, and local model workflows.
Quick Start · Setup Guide · Contributing · Roadmap
Quick Start
devis the default branch and gets the newest changes first. Usemainif you want the more curated branch.
git clone https://github.com/pewdiepie-archdaemon/odysseus.git
cd odysseus
cp .env.example .env
docker compose up -d --build
Open http://localhost:7000 when the containers are healthy. The first admin password is printed in docker compose logs odysseus.
Native installs, GPU notes, Windows/macOS instructions, HTTPS, and configuration live in the setup guide.
Features
- Chat + Agents — local/API models, tools, MCP, files, shell, skills, and memory.
- Cookbook — hardware-aware model recommendations, downloads, and serving.
- Deep Research — multi-step web research with source reading and report generation.
- Compare — blind side-by-side model testing and synthesis.
- Documents — writing-first editor with AI edits, suggestions, Markdown, HTML, CSV, and syntax highlighting.
- Email — IMAP/SMTP inbox with triage, tags, summaries, reminders, and reply drafts.
- Notes, Tasks + Calendar — reminders, todos, scheduled agent tasks, and CalDAV sync.
- Extras — gallery/image editor, themes, uploads, web search, presets, sessions, and 2FA.
Demo
A full hover-to-play tour lives on the landing page: docs/index.html.
Contributing
Help is welcome. The best entry points are fresh-install testing, provider setup bugs, mobile/editor polish, docs, and small focused refactors. See CONTRIBUTING.md and ROADMAP.md.
Security
Odysseus is a self-hosted workspace with powerful local tools. Keep auth enabled, keep private data out of Git, and do not expose raw model/service ports publicly. Deployment details are in the setup guide.
Star History
License
AGPL-3.0-or-later -- see LICENSE and ACKNOWLEDGMENTS.md.