Mnemebrain Lite

B+ 87 completed
Api
unknown / python · tiny
38
Files
3,693
LOC
2
Frameworks
4
Languages

Pipeline State

completed
Run ID
#361841
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Skipped
Decision
skip_scaffold_dup
Novelty
42.84
Framework unique
Isolation
Last stage change
2026-04-16 18:15:42
Deduplication group #48867
Member of a group with 1 similar repo(s) — canonical #68026 view group →
Top concepts (2)
Project DescriptionWeb Backend
Repobility · severity-and-effort ranking · https://repobility.com

AI Prompt

Build me a Python application, perhaps using FastAPI, that implements a structured belief memory system for AI agents. The system needs to manage beliefs, where each belief must track evidence, confidence, provenance, and revision logic. I need endpoints to allow users to `believe` a claim with supporting evidence, `explain` the justification chain, `retract` evidence, and `revise` beliefs with new data. The core logic should handle concepts like TruthState (TRUE, FALSE, BOTH, NEITHER) and incorporate time decay based on belief types like FACT, PREFERENCE, etc. Please structure this using FastAPI and include necessary testing setup using pytest.
python fastapi ai-agents memory belief-system rest-api pytest structured-data
Generated by gemma4:latest

Catalog Information

MnemeBrain-lite provides AI agents with a structured memory of beliefs, each stored with evidence, confidence, provenance, and revision logic.

Description

MnemeBrain-lite is a lightweight API that gives AI agents a structured memory of beliefs. It stores each belief together with evidence, a confidence score, provenance information, and revision rules. The system exposes a FastAPI interface that allows agents to add, query, and update beliefs in real time. Developers can integrate it with language models to provide context‑aware reasoning and audit trails. By tracking provenance and confidence, the tool helps prevent hallucinations and supports dynamic belief revision. It is ideal for researchers and developers building conversational or decision‑making agents.

الوصف

يُقدّم MnemeBrain-lite واجهة برمجية خفيفة تُعطي وكلاء الذكاء الاصطناعي ذاكرة منظمّة للآراء. تُخزّن كل فكرة مع الأدلة التي تدعمها، درجة الثقة، ومعلومات المنشأ، بالإضافة إلى قواعد تعديل الآراء. تُعرّف الخدمة نقاط نهاية REST عبر FastAPI، ما يتيح إضافة واسترجاع وتحديث الآراء في الوقت الفعلي. يتيح المطوّرين دمجها مع نماذج اللغة لتوفير استجابات أكثر سياقاً وتدقيقاً. بفضل تتبع الأدلة والثقة، يُساعد النظام على تقليل التباسات المعلومات وتسهيل مراجعة الآراء. كما يوفّر سجلّاً شفافاً للمنشأ يُسهل تدقيق المعلومات. يُستهدف الباحثين والمطورين الذين يبنون وكلاء محادثة أو اتخاذ قرار.

Novelty

7/10

Tags

memory-management belief-tracking evidence-logging confidence-scoring provenance-tracking revision-logic ai-agent-support knowledge-base

Technologies

fastapi huggingface numpy pydantic pytorch uvicorn

Claude Models

claude-opus-4.6

Quality Score

B+
87.2/100
Structure
94
Code Quality
100
Documentation
70
Testing
85
Practices
68
Security
100
Dependencies
60

Strengths

  • CI/CD pipeline configured (github_actions)
  • Good test coverage (86% test-to-source ratio)
  • Code linting configured (ruff (possible))
  • Consistent naming conventions (snake_case)
  • Low average code complexity \u2014 well-structured code
  • Good security practices \u2014 no major issues detected
  • Properly licensed project

Weaknesses

  • 104 duplicate lines detected \u2014 consider DRY refactoring

Security & Health

4.1h
Tech Debt (C)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (3)
All rows above produced by Repobility · https://repobility.com
MIT
License
4.4%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

python
71.7%
markdown
19.5%
yaml
6.3%
toml
2.4%

Frameworks

FastAPI pytest

Concepts (2)

Scored by Repobility's multi-pass pipeline · https://repobility.com
CategoryNameDescriptionConfidence
Provenance: Repobility (https://repobility.com) — every score reproducible from /scan/
auto_descriptionProject DescriptionBiological belief memory for LLM agents.80%
auto_categoryWeb Backendweb-backend70%

Quality Timeline

1 quality score recorded.

View File Metrics

Embed Badge

Add to your README:

![Quality](https://repos.aljefra.com/badge/85997.svg)
Quality BadgeSecurity Badge
Export Quality CSVDownload SBOMExport Findings CSV