Dashboard / Repos / Jarvis Ai Assistant

Jarvis Ai Assistant

C 61 completed
Bot
web_app / python · medium
749
Files
195,063
LOC
7
Frameworks
13
Languages
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Pipeline State

completed
Run ID
#306071
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Cataloged
Decision
proceed
Novelty
84.40
Framework unique
—
Isolation
—
Last stage change
2026-05-10 03:34:46
Deduplication group #55009
Member of a group with 1 similar repo(s) — this repo is canonical view group →
Top concepts (12)
RepositoryProject DescriptionLayered ArchitectureSingletonObserver/Event Emitterapibusiness_logicdata_accessinfrastructuretestingWeb FrontendFactory
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🧪 Code Distillation

Browse all specs →
Function bodies →
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Real LLM specs →
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97.0% coverage
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LLM insights →
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Sample distilled functions (click for full spec)
RelationshipClassifier.classify_contact
Classifies a contact's relationship type using a provided chat identifier and an optional display name. It first checks a time-to-live cache using the chat ID to potentially return a stored result immediately. If the result is not cached or has expired, it retrieves all messages for the chat and the
RelationshipClassifier.classify_messages
Classifies the relationship type from a list of message objects, optionally using provided chat and display identifiers. It first checks if enough messages are present, then extracts features and computes initial scores, subsequently adjusting these scores using a bonus derived from the display name
RelationshipClassifier._score_display_name
Calculates a dictionary of bonus scores for relationship categories based on the provided contact display name. It accepts a single string representing the display name as input and returns a dictionary mapping category names to a float score. The function checks if any predefined relationship keywo

AI Prompt

Create a local-first AI assistant, similar to Jarvis, designed for macOS users that integrates with iMessage. The system needs a core pipeline handling intent routing, retrieval-augmented generation, and reliability gates. It should use local message retrieval and feature a desktop application communicating via socket-based IPC. Please structure the architecture to include components for SQLite vector indexing and a metrics/health monitoring system. The backend should be built using FastAPI, and the frontend/desktop client should leverage SvelteKit.
python fastapi sveltekit tauri macos ai-assistant local-first messaging web-app ipc
Generated by gemma4:latest

Catalog Information

Jarvis is a local-first AI assistant designed for macOS users, integrating seamlessly with iMessage.

Description

Jarvis is an artificial intelligence-powered personal assistant that runs locally on your macOS device. It integrates with iMessage to provide a convenient and intuitive way to interact with the AI. Jarvis can perform various tasks, such as answering questions, setting reminders, and providing information on a wide range of topics.

الوصف

يوريس هو مساعد ذكاء اصطناعي يعمل محليا على جهاز ماكنتوش الخاص بك، ويدمج مع تطبيق iMessage لتقديم طريقة سهلة ومريحة للتفاعل مع الذكاء الاصطناعي. يمكن يوريس تنفيذ العديد من المهام مثل الإجابة عن الأسئلة والترتيب للذكرى وتقديم المعلومات حول مجموعة واسعة من المواضيع.

Novelty

7/10

Tags

ai-assistant local-first macos imessage-integration task-management information-provision question-answering

Technologies

fastapi huggingface matplotlib numpy openai pandas pydantic pytorch rich scikit-learn scipy typer uvicorn

Claude Models

claude-opus-4.6

Quality Score

C
61.3/100
Structure
68
Code Quality
62
Documentation
79
Testing
75
Practices
44
Security
25
Dependencies
90

Strengths

  • CI/CD pipeline configured (github_actions)
  • Good test coverage (35% test-to-source ratio)
  • Code linting configured (ruff (possible))
  • Consistent naming conventions (snake_case)

Weaknesses

  • No LICENSE file \u2014 legal ambiguity for contributors
  • 4 files with critical complexity need refactoring
  • Potential hardcoded secrets in 1 files
  • 15687 duplicate lines detected \u2014 consider DRY refactoring
  • 72 'god files' with >500 LOC need decomposition

Recommendations

  • Add a LICENSE file (MIT recommended for open source)
  • Move hardcoded secrets to environment variables or a secrets manager
  • Address 54 TODO/FIXME items \u2014 consider tracking them as issues

Security & Health

57.1h
Tech Debt (A)
High
DORA Rating
A
OWASP (100%)
Repobility — same analyzer, your code, free for public repos · /scan/
FAIL
Quality Gate
A
Risk (13)
MIT
License
5.0%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

python
69.7%
typescript
9.1%
svelte
7.9%
json
7.8%
yaml
2.3%
markdown
2.1%
rust
0.6%
shell
0.4%
toml
0.1%
css
0.0%
text
0.0%
html
0.0%

Frameworks

FastAPI Svelte SvelteKit Tauri pytest Vitest Vite

Symbols

variable3,606
method1,815
function1,466
constant1,113
class782
interface230
property120
type_alias33
protocol21
struct11
enum2
extension2

API Endpoints (126)

Repobility · code-quality intelligence · https://repobility.com
MethodPathHandlerFramework
All rows above produced by Repobility · https://repobility.com
GETlist_templatesFastAPI
GETget_priority_inboxFastAPI
POSTcreate_taskFastAPI
POSTcreate_experimentFastAPI
GETlist_experimentsFastAPI
POSTget_suggestionsFastAPI
POSTcreate_templateFastAPI
GETlist_tasksFastAPI
GETlist_attachmentsFastAPI
GETget_settingsFastAPI
GETlist_calendarsFastAPI
PUTupdate_settingsFastAPI
GETget_prometheus_metricsFastAPI
GETlist_conversationsFastAPI
GET/rootFastAPI
POST/backupexport_full_backupFastAPI
DELETE/cacheclear_analytics_cacheFastAPI
GET/{chat_id}get_conversation_statsFastAPI
DELETE/{chat_id}/cacheinvalidate_stats_cacheFastAPI
GET/{chat_id}/messagesget_messagesFastAPI
POST/{chat_id}/sendsend_messageFastAPI
POST/{chat_id}/send-attachmentsend_attachmentFastAPI
GET/{chat_id}/threadsget_threaded_viewFastAPI
POST/{chat_id}/threads/analyzeanalyze_threadsFastAPI
GET/{chat_id}/threads/{thread_id}get_thread_messagesFastAPI
POST/clear-handledclear_handledFastAPI
GET/clustersget_clustersFastAPI
DELETE/completed/clearclear_completed_tasksFastAPI
GET/contact/{contact_id}get_contact_profileFastAPI
GET/contacts/{chat_id}/statsget_contact_statsFastAPI
POST/contacts/importantmark_contact_importantFastAPI
GET/contacts/leaderboardget_contacts_leaderboardFastAPI
GETContent-Dispositionheaders.getExpress
POST/conversation/{chat_id}export_conversationFastAPI
GET/debug/statusget_system_statusFastAPI
GET/debug/tracesget_tracesFastAPI
DELETE/debug/tracesclear_tracesFastAPI
GET/debug/traces/summaryget_trace_summaryFastAPI
POST/detectdetect_events_in_textFastAPI
POST/detect/messagesdetect_events_in_messagesFastAPI
GET/ego/{contact_id}get_ego_graphFastAPI
POST/evaluateevaluate_responseFastAPI
POST/eventscreate_eventFastAPI
GET/eventsget_eventsFastAPI
POST/events/from-detectedcreate_event_from_detectedFastAPI
GET/events/searchsearch_eventsFastAPI
GET/evolutionget_graph_evolutionFastAPI
GET/exportexport_analyticsFastAPI
POST/exportexport_templatesFastAPI
POST/exportbatch_exportFastAPI

Showing 50 of 126

Concepts (22)

Open methodology · Repobility · https://repobility.com/research/
CategoryNameDescriptionConfidence
Generated by Repobility's multi-pass static-analysis pipeline (https://repobility.com)
design_patternRepositoryFound repository-named files80%
auto_descriptionProject DescriptionLocal-first AI assistant for iMessage workflows on macOS.80%
arch_patternLayered ArchitectureFound API/routes, service, and data layers70%
design_patternSingletonFound get_instance/instance patterns70%
design_patternObserver/Event EmitterFound event emission/subscription patterns70%
arch_layerapiDetected api layer70%
arch_layerbusiness_logicDetected business_logic layer70%
arch_layerdata_accessDetected data_access layer70%
arch_layerinfrastructureDetected infrastructure layer70%
arch_layertestingDetected testing layer70%
auto_categoryWeb Frontendweb-frontend70%
design_patternFactoryFound factory/create_ naming patterns60%
business_logicSearchDetected from 32 related files50%
business_logicTestingDetected from 181 related files50%
business_logicUser ManagementDetected from 10 related files50%
business_logicAnalyticsDetected from 27 related files50%
business_logicAuthenticationDetected from 3 related files50%
business_logicCachingDetected from 12 related files50%
business_logicConfigurationDetected from 25 related files50%
business_logicDatabaseDetected from 49 related files50%
business_logicLoggingDetected from 11 related files50%
business_logicFile ManagementDetected from 11 related files50%
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1 quality score recorded.

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BinComp Dependency Hardening

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23 of this repo's dependencies have been scanned for binary hardening. Grade reflects RELRO / stack canary / FORTIFY / PIE coverage.
Ntransformers5.5.3 · 0 gadgets · risk 10146.5Ftorch2.11.0 · 1,257 gadgets · risk 5116.6Nstarlette1.0.0 · 0 gadgets · risk 1608.0Dorjson3.11.8 · 215 gadgets · risk 336.6Nargcomplete3.6.3 · 0 gadgets · risk 0.0Nasyncio4.0.0 · 0 gadgets · risk 0.0Nfastapi0.135.3 · 0 gadgets · risk 0.0Njoblib1.5.3 · 0 gadgets · risk 0.0Nnetworkx3.6.1 · 0 gadgets · risk 0.0Fnumpy2.4.4 · 6,596 gadgets · risk 0.0Bonnxruntime1.24.4 · 1 gadgets · risk 0.0Nopenai2.31.0 · 0 gadgets · risk 0.0Fpandas3.0.2 · 6,381 gadgets · risk 0.0Fpsutil7.2.2 · 19 gadgets · risk 0.0Npydantic2.12.5 · 0 gadgets · risk 0.0Nrich14.3.4 · 0 gadgets · risk 0.0Dsafetensors0.7.0 · 421 gadgets · risk 0.0Fscipy1.17.1 · 21,805 gadgets · risk 0.0Dtokenizers0.22.2 · 1,441 gadgets · risk 0.0Ntqdm4.67.3 · 0 gadgets · risk 0.0Nuvicorn0.44.0 · 0 gadgets · risk 0.0Dwatchfiles1.1.1 · 370 gadgets · risk 0.0Fwebsockets16.0 · 4 gadgets · risk 0.0