GitHub user aglinxinyuan added a comment to the discussion: Task ideas for the
dkNet-AI · Apache Texera Agent Hackathon
Here are some example ideas:
1. AI agent
- NL-to-workflow auto-suggest — extend agent-service to suggest the next
operator given the current canvas state (not just whole-workflow generation).
Inline ghost-node previews on the canvas.
- "Explain this workflow" — agent reads a workflow + recent execution
stats and produces a plain-English summary, including bottleneck and data-shape
narration. Great demo material.
- Voice-driven workflow editing — Web Speech API → agent-service →
workflow mutation. "Add a filter on age > 30 after the CSV scan."
- Self-healing workflows — when a run fails, the agent reads the error +
operator config and proposes a fix as a diff on the workflow JSON.
2. Workflow engine (Amber)
- Operator marketplace / share-a-UDF — one-click publish of a Python UDF
(with its requirements) to a shared registry; one-click import into someone
else's workflow. Hits the pytexera SDK and file-service.
- GPU-aware scheduler hint — let an operator declare requires: gpu and
have computing-unit-managing-service route it to a GPU pod. Even a stub that
just labels pods is demo-worthy.
3. Frontend
- Workflow diff & PR-style review — visualize the diff between two
workflow versions (357K versions in the badge — clearly important) as a
side-by-side DAG with added/removed/changed nodes highlighted. Comment threads
on nodes.
- "Replay another user's session" — record canvas edits + executions and
play them back as a tutorial. Pairs well with the real-time collab infra
already in place.
- Mobile / tablet read-only viewer — render workflows + live execution
status on a phone for monitoring long-running jobs.
4. Data / AI for Science
- One-click LLM eval workflow template — drag a dataset, a prompt
template, and a model operator; get a leaderboard. Showcases Texera as an
experiment harness.
- RAG-as-a-workflow — chunker → embedder → vector store → retriever → LLM,
all as composable operators. A killer-demo template that ships with the
platform.
5. Dev/infra
- In-browser Python sandbox for UDFs — use Pyodide to validate operator
code (lint + smoke run) before shipping it to a worker. Faster feedback than
the round-trip through Amber.
- texera dev CLI — single command that brings up the minimum stack (Amber
+ one service + frontend) using Docker compose, replacing the multi-step
single-node setup in bin/single-node.
GitHub link:
https://github.com/apache/texera/discussions/5059#discussioncomment-16911198
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