RagaAI-Catalyst vs re_gent
RagaAI-Catalyst is much bigger: 16.2k stars against 801. Over the days we have tracked them RagaAI-Catalyst moved +0.2% and re_gent +2.4%, so re_gent is growing faster right now.
They split the axes: RagaAI-Catalyst leads on customization and model freedom, re_gent on context depth and setup ease.
Stars and commit dates come from our own daily tracking. The six axes are read off each project's documentation by our review pipeline, so they describe what a project says about itself, not what we measured in its code.
Where they stand today
Combines agent/LLM tracing, evaluation, guardrails and red‑teaming with a self‑hosted dashboard and execution-timeline analytics for multi-agent debugging.
- Stars
- 16.2k
- Tracked growth
- +0.2%
- Maturity
- ●●●●●
- Last commit
- 250d ago
- Language
- Python
- License
- Apache-2.0
- Cost to run
- Requires RagaAI account; external LLM usage billed to your provider.
Provides content-addressed, per-step audit trails and per-line 'blame' tied to the exact prompt and conversation that produced a change—something traditional VCS and most tools do not track.
- Stars
- 801
- Tracked growth
- +2.4%
- Maturity
- ●●●●●
- Last commit
- 109d ago
- Language
- Go
- License
- Apache-2.0
- Cost to run
- Free local CLI; external model/API usage may incur costs
Six axes, head to head
Each axis runs 0 to 5. The label under a score is what that project's own docs claim, not a category average.
| Axis | RagaAI-Catalyst | re_gent |
|---|---|---|
Context depth How much of your codebase it sees before it answers: the open diff, the diff plus related files, or the whole repository. | ●●●●● Diff/file only | ●●●●● Workspace snapshot |
Noise control How it keeps output volume down — severity thresholds, deduplication, incremental runs over new commits only. | ●●●●● Configurable thresholds | ●●●●● Ignore & dedupe |
Customization How far it bends to your team: custom rules, prompts, style guides, per-path config. | ●●●●● Custom rules & prompts | ●●●●● Config file & hooks |
Privacy Whether your code stays on your own infrastructure: fully local, self-hostable, or cloud API only. | ●●●●● Self-hostable | ●●●●● Self-hostable |
Model freedom Whether you can point it at any provider, or it is wired to one. | ●●●●● Bring-your-key | ●●●●● Known providers |
Setup ease What it takes to get a first useful run out of it. | ●●●●● API key + config | ●●●●● One-command init |
Which one to pick
Pick RagaAI-Catalyst if…
Comprehensive observability — pick this when you need end-to-end tracing, evaluation and guardrails for agentic systems with an optional self-hosted dashboard and red‑teaming tools.
- Customization: Custom rules & prompts (5/5 against 3/5)
- Model freedom: Bring-your-key (5/5 against 3/5)
Pick re_gent if…
Agent-auditability — pick re_gent when you need a zero-config, local audit trail that shows which prompt wrote each line and lets you inspect full step and conversation context.
- Context depth: Workspace snapshot (5/5 against 1/5)
- Setup ease: One-command init (5/5 against 3/5)
What people want from each one
raga-ai-hub/RagaAI-Catalyst
regent-vcs/re_gent
Questions people ask
Is RagaAI-Catalyst better than re_gent?
They split the axes: RagaAI-Catalyst leads on customization and model freedom, re_gent on context depth and setup ease. RagaAI-Catalyst is worth picking when comprehensive observability — pick this when you need end-to-end tracing, evaluation and guardrails for agentic systems with an optional self-hosted dashboard and red‑teaming tools.
Which of RagaAI-Catalyst and re_gent keeps my code private?
RagaAI-Catalyst: Self-hostable (4/5). re_gent: Self-hostable (4/5).
What does each one cost to run?
RagaAI-Catalyst: Requires RagaAI account; external LLM usage billed to your provider.. re_gent: Free local CLI; external model/API usage may incur costs.
Full profiles: raga-ai-hub/RagaAI-Catalyst and regent-vcs/re_gent. Everything else in Observability & tracing.