Notion2Ragapi

D 57 completed
Api
api / python · tiny
34
Files
4,227
LOC
3
Frameworks
6
Languages

Pipeline State

completed
Run ID
#345475
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Cataloged
Decision
proceed
Novelty
67.18
Framework unique
Isolation
Last stage change
2026-05-10 03:35:31
Deduplication group #60751
Member of a group with 2 similar repo(s) — canonical #88451 view group →
Top concepts (2)
Project DescriptionWeb Backend
Methodology: Repobility · https://repobility.com/research/state-of-ai-code-2026/

AI Prompt

Create a backend API using Python, FastAPI, and SQLAlchemy for a real-time knowledge hub. This system needs to ingest messages and files from various sources like Slack, Telegram, and Google Drive. Key features must include normalizing incoming data, enriching content using RAG techniques (chunking, embeddings, summaries, entities), and supporting hybrid search over Postgres. The API should deliver this unified content stream to clients, potentially using a mechanism like Electric Shapes for real-time updates. Please structure the code to handle ingestion endpoints, the enrichment pipeline, and metadata storage.
python fastapi sqlalchemy api rag knowledge-base real-time postgres llm
Generated by gemma4:latest

Catalog Information

A real‑time knowledge hub that ingests messages and files from multiple messengers and cloud storage, enriches them with RAG and metadata, and delivers the content to clients via a unified API for developers building knowledge‑centric applications.

Description

This system provides a real‑time knowledge hub that collects messages and files from popular messengers and cloud storage services. It normalizes the data into a PostgreSQL store, enriches it with chunking, embeddings, summaries, entities, and tags, and indexes it for hybrid search. Clients receive updates through a real‑time sync layer and can query the data using full‑text, vector, or metadata filters. The platform is designed for backend developers who need to build knowledge‑centric applications, chatbots, or enterprise search solutions. It solves the problem of fragmented information by unifying disparate sources and providing a single, policy‑controlled API for ingestion, enrichment, and retrieval.

الوصف

يُقدِّم هذا النظام مركز معرفة فوري يجمع الرسائل والملفات من وسائط المراسلة الشهيرة وخدمات التخزين السحابي. يتم تطبيع البيانات في قاعدة PostgreSQL، ثم يُثريّها عبر تجزئة، إنشاء تمثيلات متجهية، تلخيص، استخراج الكيانات، والوسوم، ويُفهرسها للبحث المختلط. يتلقى العملاء التحديثات عبر طبقة مزامنة فورية، ويمكنهم الاستعلام عن المحتوى باستخدام بحث نصي كامل، بحث متجه، أو عوامل تصفية للبيانات الوصفية. صُمم هذا المنصة للمطورين الخلفيين الذين يرغبون في بناء تطبيقات تعتمد على المعرفة، مثل الروبوتات الحوارية أو حلول البحث المؤسسي. يحل المشكلة التي تنشأ من تشتت المعلومات عبر مصادر متعددة، موفراً واجهة موحدة ومتحكم فيها بالسياسات للادخال، التخصيص، والاسترجاع.

Novelty

8/10

Tags

knowledge-ingestion real‑time-sync rag-enrichment multimessenger-integration hybrid-search metadata-extraction policy‑based-routing oauth-broker

Technologies

alembic chromadb fastapi langchain openai pinecone pydantic sqlalchemy uvicorn

Claude Models

claude (unknown version) claude-opus-4.6

Quality Score

D
57.0/100
Structure
44
Code Quality
63
Documentation
65
Testing
0
Practices
85
Security
100
Dependencies
60

Strengths

  • Consistent naming conventions (snake_case)
  • Good security practices \u2014 no major issues detected
  • Containerized deployment (Docker)

Weaknesses

  • No LICENSE file \u2014 legal ambiguity for contributors
  • No tests found \u2014 high risk of regressions
  • No CI/CD configuration \u2014 manual testing and deployment
  • 131 duplicate lines detected \u2014 consider DRY refactoring

Recommendations

  • Add a test suite \u2014 start with critical path integration tests
  • Set up CI/CD (GitHub Actions recommended) to automate testing and deployment
  • Add a linter configuration to enforce code style consistency
  • Add a LICENSE file (MIT recommended for open source)

Security & Health

6.3h
Tech Debt (C)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (4)
All rows above produced by Repobility · https://repobility.com
Unknown
License
0.2%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

python
61.8%
markdown
29.2%
yaml
7.7%
text
0.8%
json
0.3%
toml
0.2%

Frameworks

FastAPI pytest SQLAlchemy

Concepts (2)

Same analyzer free for public repos: https://repobility.com
CategoryNameDescriptionConfidence
All rows scored by the Repobility analyzer (https://repobility.com)
auto_descriptionProject Description아래 2개 파일부터 바로 깔고 시작하자.80%
auto_categoryWeb Backendweb-backend70%

Quality Timeline

1 quality score recorded.

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