Jupyter Notebook · MIT
panaversity/learn-agentic-ai
Learn Agentic AI using Dapr Agentic Cloud Ascent (DACA) Design Pattern and Agent-Native Cloud Technologies: OpenAI Agents SDK, Memory, MCP, A2A, Knowledge Graphs, Dapr, Rancher Desktop, and Kubernetes.
★ 4.4k
Stars
1k forks · 59 open issues
—
Growth · stale
We stopped seeing this repository in its topic's top results, so its star count is frozen at the date it was last read. Subtracting from a frozen number would read as zero growth, which would be false, so no rate is shown.
10.6
Momentum / 100
see the breakdown below
2y ago
Created
last push 12mo ago
Star history
How this score was built
| Component | Weight | Earned | Why |
|---|---|---|---|
| Velocity | 55 | 0.0 | — — no measurable rate |
| Acceleration | 15 | 0.0 | needs 7-day and 30-day rates side by side |
| Freshness | 15 | 0.0 | last push 12mo ago; decays to zero at 180 days |
| Scale | 15 | 10.6 | 4.4k stars, log-scaled against 150k — stops a 3-star repo topping the board |
| Momentum | 100 | 10.6 | capped at 35 because growth is unmeasured |
Detail
| Topics | a2aagentic-aidaprdapr-pub-subdapr-service-invocationdapr-sidecardapr-workflowdockerkafkakuberneteslangmemmcpopenaiopenai-agents-sdkopenai-apipostgresql-databaserabbitmqrancher-desktopredisserverless-containers |
| Matched on | AI Agents (agentic-ai) |
| Short window | no snapshot 5–10 days old yet |
| Long window | +2 stars over 26 days = 0.1/day |
| Lifetime average | 5.01 stars/day over 876 days |
| First seen here | 2026-10-11 |
| Last read | 16d ago |