[Project] Using Ollama to investigate captured HTTP/WebSocket traffic locally. Feedback on this context and redaction flow?
Hi r/ollama,
I’m Stephen, the indie developer behind Rockxy, an open-source native macOS HTTP debugging proxy.
I’ve integrated Ollama into Rockxy’s AI Assistant so developers can investigate captured HTTP, HTTPS, GraphQL, and WebSocket traffic using a model running on their own machine.
The AI Assistant demonstrates the current flow:
Select one or more captured requests.
Ask a debugging question, such as why a request failed or what changed between two flows.
Rockxy builds a bounded context from only the selected traffic.
Common sensitive values, including authorization headers, cookies, and tokens, are redacted.
Review Data shows the exact context before it is submitted.
After approval, the selected Ollama model processes that context through the configured local Ollama runtime.
The answer streams back with evidence connected to the source requests and suggested follow-up steps.
The Assistant is intentionally read-only. It may prepare a replay, comparison, filter, or another investigation step, but it does not execute those actions automatically.
The main design question is how much network evidence a local model actually needs.
Sending an entire capture session creates noise, wastes context, and may expose unrelated data. Sending only a summary is safer and faster, but could remove the exact header, timing, payload, or WebSocket event that explains the problem.
I would particularly value the community’s opinion on these questions:
- Should the model receive structured request summaries, raw HTTP sections, or a combination of both?
- Is Review Data useful control, or would you prefer a persistent per-project policy after the first approval?
- Which Ollama models and context sizes work well for JSON, REST, GraphQL, and WebSocket debugging on Apple Silicon?
- For multi-request investigations, should Rockxy pre-filter and rank evidence before inference?
- Should suggested actions remain user-confirmed, or would you want an optional agent mode with stricter permissions?
I’m especially interested in results from smaller local models. The goal is not to require the largest model just to explain a failed API request.
Rockxy is native Swift, local-first, and open source under AGPL-3.0:
https://github.com/RockxyApp/Rockxy
Rockxy website:
Please be direct about anything that feels unsafe, slow, confusing, or unnecessary. Architecture suggestions, model recommendations, test cases, issues, and contributions are all welcome.
For r/ollama members who test this with a real debugging session and provide detailed feedback, please DM me your Mac configuration, Ollama model, findings, and the email you plan to use at checkout. I’ll personally send you a private Rockxy Pro tester discount code as a thank-you. The offer is for genuine testing and is not tied to upvotes or stars.