GB
aws-samples/generative-bi-using-rag
A solution guidance for Generative BI using Amazon Bedrock, Amazon OpenSearch with RAG
173 51 +0/wk
GitHub
llm nlq nlq-to-sql rag text-to-sql text2sql
Trend
0
Star & Fork Trend (19 data points)
Stars
Forks
Multi-Source Signals
Growth Velocity
aws-samples/generative-bi-using-rag has +0 stars this period . Velocity data will be available after more historical data is collected.
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| Metric | generative-bi-using-rag | cortex-tms | loomkin | jido_ai |
|---|---|---|---|---|
| Stars | 173 | 173 | 173 | 173 |
| Forks | 51 | 7 | 26 | 49 |
| Weekly Growth | +0 | +0 | +0 | +0 |
| Language | Python | MDX | Elixir | Elixir |
| Sources | 1 | 1 | 1 | 1 |
| License | MIT-0 | MIT | MIT | Apache-2.0 |
Capability Radar vs cortex-tms
generative-bi-using-rag
cortex-tms
Maintenance Activity 0
Last code push 384 days ago.
Community Engagement 100
Fork-to-star ratio: 29.5%. Active community forking and contributing.
Issue Burden 70
Issue data not yet available.
Growth Momentum 30
No measurable growth in the current period (first-day cold start expected).
License Clarity 60
Licensed under MIT-0. Review license terms for your use case.
Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.