Commit Graph
195 Commits
Author SHA1 Message Date
Jon Saad-FalconandGitHub 57151327b3 feat: LLM-guided spec search building blocks (split-aware sampling, external corpora, agent-trace adapter) (#332) 2026-05-08 20:18:40 -07:00
Jon Saad-FalconandGitHub b8245136db fix(security): block IPv4-mapped IPv6 addresses in SSRF check (#327) 2026-05-07 14:55:52 -07:00
Jack HamiltonandGitHub 9e7366fc05 Close KnowledgeStore connections in connectors_router endpoints (#209)
* fix: close KnowledgeStore connections in connectors_router endpoints

KnowledgeStore opens a persistent SQLite connection in __init__ but was
never closed at the three instantiation sites in connectors_router.py,
leaking one file descriptor (plus its WAL handle) per call. The worst
offender is _connector_summary(), which is invoked per-connector on
every GET /connectors poll from the frontend — after ~100 polls the
backend hits the default macOS per-process FD limit (256) and asyncio's
accept() starts failing with OSError: [Errno 24] Too many open files.

Add __enter__/__exit__ to KnowledgeStore (close() already existed) and
wrap all three instantiation sites in `with` blocks so the connection
is released deterministically when the scope exits.

- connectors/store.py: add context manager protocol
- server/connectors_router.py: use `with KnowledgeStore() as store:`
  in _connector_summary, _ingest, and _run_sync

* test: cover KnowledgeStore context manager + connectors_router close leak

- test_store.py: add two tests for the new __enter__/__exit__ protocol
  verifying the connection closes on normal exit and on exceptions.
- test_connectors_router.py: add a regression test that monkeypatches
  KnowledgeStore.close to count invocations and asserts every store
  opened by GET /v1/connectors is paired with a close.

Also fix a pre-existing bug in the test_connectors_router fixture: the
router is created with prefix="/v1/connectors" internally (line 92 of
connectors_router.py), and the fixture was wrapping it again with
prefix="/v1", producing "/v1/v1/connectors". All 6 existing router
tests were failing with 404 before this fix. 5 of them now pass; the
remaining failure (test_trigger_sync) is an unrelated KeyError on a
missing response field and is out of scope for this PR.

* test: drop connectors_router regression test — skipped in CI anyway

The regression test added in the previous commit relies on FastAPI
being importable, but CI's dev-extra install does not include fastapi
(it lives in the `server` optional group). All tests in
test_connectors_router.py silently skip on CI with "fastapi not
installed", so the regression test would never actually execute there.

Revert test_connectors_router.py to the upstream main version. The
fixture bug I fixed (double prefix) and the connection-leak regression
test both deserve a separate PR scoped to test infrastructure — that
PR should either add fastapi to dev deps, split server tests into
their own CI job, or both.

The KnowledgeStore context manager tests in test_store.py are kept
because they have no fastapi dependency and will run in CI.
2026-05-06 23:44:43 -07:00
4935053ac7 feat(mining): register ScalingIntelligence Pearl models (#324)
Co-authored-by: krypticmouse <herumbshandilya123@gmail.com>
2026-05-06 22:20:18 -07:00
8fb9d5ece3 feat(mining): add Pearl model conversion workflow (#323)
* feat(mining): add Pearl model conversion workflow

* test(mining): tolerate missing Docker device request type

* docs(mining): record Gemma and Qwen conversion evidence

* docs(mining): record Qwen local validation evidence

---------

Co-authored-by: krypticmouse <herumbshandilya123@gmail.com>
2026-05-06 16:20:27 -07:00
Avanika NarayanandGitHub daaa5577f0 feat(mining): inspect Pearl model artifacts before launch
Add jarvis mine inspect-model to fail fast on missing Pearl/Hugging Face artifact metadata before GPU startup.
2026-05-05 21:21:33 -07:00
a689be0c69 fix(evals): clean up AI stack runtime harness (#320)
Co-authored-by: krypticmouse <herumbshandilya123@gmail.com>
2026-05-05 19:28:50 -07:00
Jon Saad-FalconandGitHub f41cf420be feat(mining): Pearl mining integration
Consolidates NVIDIA vLLM, Apple Silicon, CPU Pearl mining support, CLI/docs, and live H100 validation.
2026-05-05 19:11:15 -07:00
Avanika NarayanandGitHub e79bc1e196 Add cold-start CLI installer (#313) 2026-05-05 14:42:48 -07:00
Avanika NarayanandGitHub a3ba63d148 AI_stack_support: subprocess-based external framework harness (#311) 2026-05-05 13:37:33 -07:00
Avanika NarayanandGitHub d7624510bb Eval framework: silent-failure detection, surgical reruns, continuous-score reporting (#303) 2026-05-03 21:07:44 -07:00
Robby ManihaniandGitHub 259f97b81c fix(server): allow Tauri 2 webview origins on every platform (#292)
The desktop app's chat-completions stream relies on a raw browser
fetch from the Tauri webview to the FastAPI backend, so it is
subject to CORS. The default allowlist only contained
`tauri://localhost`, which is the production webview origin on
macOS, Linux, and iOS. On Windows and Android, Tauri 2 serves the
app from `http://tauri.localhost` (or `https://tauri.localhost`
when `windows.useHttpsScheme` is enabled), so the preflight for
`POST /v1/chat/completions` was rejected and the streaming fetch
threw `TypeError: Failed to fetch` before any byte was read.

Symptom users reported: in the Logs tab the request appears to
succeed up to "Request sent", followed immediately by
"Stream error: Failed to fetch" and "Response: 22 chars" -- which
is exactly the length of the synthesized fallback string
`Error: Failed to fetch` written by InputArea.tsx when streamChat
throws.

Add `http://tauri.localhost` and `https://tauri.localhost` to both
default origin lists (`ServerConfig.cors_origins` and the
`create_app` fallback), and add a regression test that drives a
real preflight against `/v1/chat/completions` for each of the
three Tauri origin schemes.

Browser model loading kept working because it is routed through
the Rust `tauriInvoke('fetch_models')` command, which is a
server-to-server HTTP call not subject to browser CORS -- only
streaming chat goes through the webview's fetch.
2026-04-29 12:55:25 -07:00
Jon Saad-FalconandGitHub f5695845b7 feat(distillation): M1→M2→M3 spec-level distillation pipeline + hill-climb optimizer (#273) 2026-04-20 19:18:10 -07:00
Robby ManihaniandGitHub 8258295f51 Feature/twitter bot (#272) 2026-04-20 15:33:51 -07:00
Robby ManihaniandGitHub ef03d98fc0 Feature/twitter bot (#259) 2026-04-17 15:22:17 -07:00
Andrew ParkandGitHub 30d4d45a7d refactor(system): decompose JarvisSystem god-object into system/ package (#257) 2026-04-17 11:02:56 -07:00
Andrew ParkandGitHub 88a7ebcaa3 test: add live marker, CI coverage gate, rust bridge boundary tests (#256) 2026-04-17 11:02:21 -07:00
Andrew ParkandGitHub 28e913f706 fix(agents): bind built-in tools, live tool-call UI, Markdown streaming (#255) 2026-04-17 11:01:50 -07:00
Andrew ParkandGitHub 54d79ef235 feat: add Apple Contacts connector (macOS AddressBook) (#248)
* feat: add Apple Contacts connector (macOS AddressBook)

Reads directly from ~/Library/Application Support/AddressBook/AddressBook-v22.abcddb
in read-only mode. Extracts names, phone numbers, emails, postal addresses, URLs,
social profiles, and notes for each contact. Requires Full Disk Access like
iMessage and Apple Notes connectors.

- New connector: src/openjarvis/connectors/apple_contacts.py
- Registered in connectors/__init__.py
- Added frontend catalog entry (PIM category) and icon mapping
- MCP tools: contacts_search, contacts_get_contact

* test: add comprehensive tests for Apple Contacts connector

15 tests covering: is_connected (exists/missing), sync yields all real
contacts (skips system rows), extracts all field types (phone, email,
address, URL, social, notes), cleans Apple label markup, org-only
contacts, minimal contacts, since filter, sync_status tracking,
structured metadata, disconnect, mcp_tools, registry, empty DB,
missing DB. Uses fake SQLite database — no real Contacts DB needed.

* fix: scan iCloud/Exchange source databases for all contacts

The main AddressBook database only contains locally-created contacts.
Synced contacts (iCloud, Exchange, etc.) live under
Sources/<UUID>/AddressBook-v22.abcddb. Now scans all source databases
and deduplicates by ZUNIQUEID across sources.

Adds tests for multi-source scanning and cross-source deduplication.
2026-04-14 09:49:08 -07:00
Andrew ParkandGitHub ed2acf1895 fix(skills): implement skill remove and search CLI commands (#240) 2026-04-13 15:03:39 -07:00
Avanika NarayanandGitHub a3789212ec refactor: remove dead shims, stale files, and test duplication (#243) 2026-04-13 15:03:03 -07:00
Jon Saad-FalconandClaude Opus 4.6 db4b031c45 fix: rename DeepResearchBench references in docs, configs, and tests
Update all human-readable strings (docstrings, comments, descriptions,
log messages, TOML config descriptions) to correctly say
"DeepResearchBench" instead of "LiveResearchBench" for the
deep_research_bench benchmark. Class names and file paths are
unchanged for backward compatibility.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-13 18:59:24 +00:00
Jon Saad-FalconandClaude Opus 4.6 70cbda8a73 chore: derive __version__ from metadata, bump GHA action versions
- openjarvis.__version__ now comes from importlib.metadata.version("openjarvis")
  instead of a hardcoded string, so it stays in sync with pyproject.toml on every
  release. Tests assert against openjarvis.__version__ rather than a literal.
- Bump actions/checkout@v4 → @v6 and astral-sh/setup-uv@v4 → @v8 across every
  workflow ahead of the 2026-06-02 Node.js 20 deprecation on GitHub Actions runners.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-11 13:19:19 -07:00
Tanvir BhathalandGitHub 0e122cd776 DGX Spark Fix (#231) 2026-04-10 11:40:03 -07:00
Jon Saad-FalconandGitHub 3c34ad47ab feat: add skills system with import, learning loop, and benchmark harness (#230) 2026-04-09 14:43:04 -07:00
Robby ManihaniandGitHub cff83a93a0 fix: recommend Qwen3.5 MoE models instead of Qwen3 dense (#189)
Qwen3.5 MoE models provide better quality per GB of memory since only
a fraction of parameters are active per token. Updates the tier table:

  ≤8 GB  → qwen3.5:2b
  8-16GB → qwen3.5:4b
 16-32GB → qwen3.5:9b
  32GB+  → qwen3.5:27b
2026-04-04 11:14:41 -07:00
Robby ManihaniandGitHub 35b8991cc2 feat: hardware-aware model recommendation in jarvis init (#188)
Closes #132 — jarvis init now recommends a Qwen3 dense model based on
available memory using an explicit tier table:

  ≤8 GB  → qwen3:1.7b  (~1.1 GB)
  8-16GB → qwen3:4b    (~2.5 GB)
 16-32GB → qwen3:8b    (~5.2 GB)
  32GB+  → qwen3:14b   (~9.3 GB)

Adds qwen3:0.6b, 1.7b, 4b, 14b, 30b to the model catalog. Falls back
to scanning all compatible models if the tiered pick doesn't support
the selected engine. Shows the user why the model was chosen and how
to download later if declined.
2026-04-03 22:19:27 -07:00
Robby ManihaniandGitHub cef64450bd fix: inject default system prompt to ground locally-hosted models (#184)
Closes #164 — Qwen and other models with baked-in corporate identities
would claim to be cloud services when running locally. Adds a
configurable default_system_prompt to AgentConfig that is injected as a
fallback when no other system prompt is provided. The default tells the
model it is running locally through OpenJarvis. Users can override or
clear it via config.toml.
2026-04-03 21:59:33 -07:00
Jon Saad-FalconandClaude Opus 4.6 c5c420c1c7 fix: use UTC timestamps in digest tests for CI compatibility
Tests were storing digests with local time but get_today() filters
by UTC date, causing failures when local date != UTC date.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-03 18:57:51 -07:00
Jon Saad-FalconandGitHub a009646071 feat: Morning Digest with Voice Mode + unified OAuth + Apple connectors (#174) 2026-04-03 11:05:41 -07:00
Robby ManihaniandGitHub 4a8cc41034 Merge pull request #156 from eddierichter-amd/lemonade-backend
Adding Lemonade Backend
2026-04-02 01:53:10 -07:00
dfddd8c785 feat(evals): ToolCall-15, LiveCodeBench, LiveResearchBench + telemetry (#169)
* fix(evals): add tool_choice=auto + fix traces thread safety

Two fixes for eval accuracy and stability:

1. TauBench agent: add tool_choice="auto" to match tau2's native
   LLMAgent behavior. Without this, Qwen and GPT-5.4 score 10-14pp
   below leaderboard because the models don't receive explicit
   tool-calling guidance.

2. SystemBuilder: apply self._traces flag to config.traces.enabled.
   Previously builder.traces(False) was a no-op — traces stayed
   enabled, creating SQLite connections in the main thread that
   crashed when accessed from ThreadPoolExecutor worker threads
   in GAIA evals ("SQLite objects created in a thread can only be
   used in that same thread").

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* feat: enrich inference events with model response content and add Trace.messages

Add content, tool_calls, and finish_reason fields to INFERENCE_END events
published by InstrumentedEngine. For non-instrumented engines, BaseAgent._generate()
now publishes INFERENCE_START/END events with the same rich data. Add _message_to_dict
helper and messages field to Trace dataclass for full conversation capture.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* feat: enhance TraceCollector with rich content, tool details, and messages

Capture model response content, tool_calls, and finish_reason in GENERATE
steps; store tool arguments and result text in TOOL_CALL steps; extract
conversation messages from AgentResult.metadata into Trace.messages; and
implement the last_trace property.  Also adds a messages column to the
TraceStore schema so messages survive the SQLite round-trip.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* feat: agents store conversation messages in AgentResult.metadata

Both NativeReActAgent and MonitorOperativeAgent now serialize their
internal messages list via _message_to_dict and include it in the
returned AgentResult.metadata under the "messages" key. This enables
TraceCollector to capture full conversation traces.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* feat: wire TraceCollector into system._run_agent and JarvisAgentBackend

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* feat: persist rich trace data in eval trace JSONL files

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* feat: add TerminalBench config for Qwen 3.5-122B

* fix: add SQLite migration for traces.messages column on existing databases

* fix: check trace_store instead of shared config for trace enablement

* feat(evals): add ToolCall-15, LiveCodeBench, LiveResearchBench + telemetry

Three new benchmark integrations and full telemetry wiring for the
NeurIPS 2026 IPW/IPJ experiments.

## New Benchmarks

### ToolCall-15
15-scenario tool calling accuracy benchmark across 5 categories.
All scenarios defined inline with deterministic scoring (0/1/2 per
scenario). Fast to run (~5min/model) — ideal for optimization loops.

### LiveCodeBench
Competitive programming from LeetCode/AtCoder/CodeForces via
HuggingFace dataset. Sandboxed code execution with per-test
timeouts. Single-turn generation via jarvis-direct backend.

### LiveResearchBench
100 expert-curated deep research tasks. LLM-as-judge scoring
across 4 dimensions (comprehensiveness, insight, instruction
following, readability). Uses web_search tool for live research.

## Telemetry Wiring

- FLOPs estimation: 2 * active_params * total_tokens (MoE-aware)
- Energy/power capture flows from InstrumentedEngine through
  backends to EvalResult and RunSummary
- New telemetry_summary section in output JSON with IPW/IPJ
- JarvisDirectBackend now propagates gpu_metrics flag
- TauBench forwards telemetry flags to SystemBuilder

## Experiment Plan

Added docs/experiments/neurips-2026-plan.md tracking the full
experiment matrix: 9 models x 7 benchmarks across NVIDIA, AMD,
and Apple hardware stacks.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

---------

Co-authored-by: Jon Saad-Falcon <jonsaadfalcon@gmail.com>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-01 21:06:20 -07:00
robbym-dev 87bbcb862c fix: update test_amd to expect lemonade for consumer AMD GPUs
The recommend_engine logic now routes consumer AMD GPUs to lemonade
instead of vllm. This test was missed in the original PR.
2026-04-02 00:12:09 +00:00
Robby ManihaniandGitHub 795874bf09 Merge pull request #160 from Prathap-P/fix/session_history
fix(channels): push session history into agent context on channel mes…
2026-04-01 16:57:38 -07:00
Robby ManihaniandGitHub 0bd84cb10a Merge pull request #154 from Prathap-P/fix/agent_config_tools
Fix/agent config tools
2026-04-01 14:23:22 -07:00
43b3a59033 feat(evals): TauBench V2 native integration + GAIA eval configs (#162)
* feat(evals): add TauBench V2 native integration + GAIA eval configs

Integrate TauBench V2 (τ²-bench) multi-turn customer service benchmark
natively through OpenJarvis's inference engine. The agent's LLM calls go
through OpenJarvis while tau2-bench handles the orchestration, user
simulation, domain tools, database, and evaluation.

## TauBench Integration

Architecture: JarvisHalfDuplexAgent bridges OpenJarvis's engine into
tau2's Orchestrator as a drop-in agent replacement. This enables
testing how well OpenJarvis's Intelligence + Engine handles multi-turn
customer service tasks with real tool calling and database mutations.

Key features:
- Native OpenJarvis engine for agent LLM calls
- tau2's UserSimulator for realistic customer interactions
- Domain tools (airline, retail, telecom) with mock databases
- Full evaluation: DB state checks, action matching, NL assertions
- Test-split filtering for leaderboard-comparable results
- Pass^k multi-trial support (default 3 trials per task)
- Qwen thinking-mode disabled for clean tool call parsing
- Gemini thought_signature handling for multi-turn conversations

Files:
- datasets/taubench.py: Dataset provider with test-split filtering
- execution/taubench_env.py: JarvisHalfDuplexAgent + simulation runner
- scorers/taubench.py: Scorer reading tau2 evaluation rewards
- CLI registration and KNOWN_BENCHMARKS update

## Results (test split, pass^3, 60 tasks)

| Model              | TauBench | Leaderboard |
|--------------------|----------|-------------|
| Claude Opus 4.6    | 86.67%   | 84.8%       |
| Nemotron-3-Super   | 86.67%   | —           |
| Qwen3.5-397B       | 81.67%   | 95.6%       |
| GPT-5.4            | 81.67%   | 91.5%       |
| Qwen3.5-122B       | 80.00%   | 93.6%       |
| Qwen3.5-35B        | 77.27%   | 89.2%       |
| Gemini 3.1 Pro     | 58.33%   | ~87%        |

## GAIA Eval Configs

Added configs for GPT-5.4, Gemini 3.1 Pro, Nemotron, Qwen 122B,
Qwen 35B, and existing GAIA rerun configs for multiple models.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* fix: lint errors in taubench integration

Remove unused imports and sort import blocks.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* fix: E501 line too long in slack_connector.py

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* chore: remove unrelated GAIA configs from PR

Keep only TauBench configs that were created and tested in this PR.
GAIA configs are pre-existing or belong in a separate PR.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

---------

Co-authored-by: Jon Saad-Falcon <jonsaadfalcon@gmail.com>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-31 14:59:20 -07:00
Prathap 35fa18fd1c add test case 2026-03-31 19:25:29 +05:30
Eddie Richter 13ea4c53db Documentation update and lint 2026-03-30 21:48:39 -06:00
Eddie Richter d9983077f0 Fixing incorrect v0 api name to v1 2026-03-30 21:28:24 -06:00
Eddie Richter 8f6ee7ae10 Fixing lemonade server when used in proxy 2026-03-30 20:50:55 -06:00
Eddie Richter f3d122e9c1 Addinig initial lemonade support 2026-03-30 20:50:53 -06:00
Prathap e3d77548c5 fix lint issues 2026-03-29 16:31:29 +05:30
Prathap ecc6d6f0bc add unit tests 2026-03-29 13:31:28 +05:30
Jon Saad-FalconandGitHub 09d1cc3681 Merge pull request #152 from open-jarvis/feat/security-hardening
feat: security hardening — layered boundary enforcement
2026-03-28 22:15:22 -07:00
Jon Saad-FalconandClaude Opus 4.6 0cbd0e1dac fix: update existing tests for new secure defaults
test_config.py: SecurityConfig.mode default changed from "warn" to "redact"
test_config_phase3.py: ServerConfig.host default changed from "0.0.0.0" to "127.0.0.1"

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-28 22:02:02 -07:00
Jon Saad-FalconandClaude Opus 4.6 f122f5a699 fix: tests work without Rust extension and server extras
- BoundaryGuard degrades gracefully when Rust scanners unavailable
- BoundaryGuard tests use lightweight mock scanners (no Rust needed)
- Server-dependent tests use pytest.importorskip for starlette/fastapi
- Fix import ordering in test files

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-28 21:46:53 -07:00
Jon Saad-FalconandClaude Opus 4.6 57ecd5c77f feat: security profiles — personal, shared, server presets with user overrides
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-28 21:30:27 -07:00
Jon Saad-FalconandClaude Sonnet 4.6 6aca5eb559 feat: add Content-Security-Policy header to API responses
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-28 21:27:38 -07:00
Jon Saad-FalconandClaude Sonnet 4.6 60317ffcba feat: get_tool_credential — scoped credential access without env pollution
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-28 21:26:42 -07:00
Jon Saad-FalconandClaude Sonnet 4.6 687ad30f9e feat: SanitizingFormatter — auto-redact credentials in all log output
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-28 21:24:57 -07:00