OpenTrace is a local-first debugging assistant for developers. A user pastes
an error, stack trace, or service log and receives a structured report with a
summary, severity, evidence, likely cause, safe next actions, and questions
that would improve the diagnosis.
Live demo: https://opentrace-ai-debugger.onrender.com
Source code: https://github.com/samainakhatun115-cpu/opentrace-ai-debugger
Logs are often technically detailed but operationally unclear. The final error
message may hide the first useful signal, and a generic chatbot can present a
guess as a fact. OpenTrace makes the distinction visible: evidence is shown
separately from hypotheses, and every response includes safe next steps rather
than destructive commands.
When Ollama is available, OpenTrace sends the pasted log to a local
Ollama-compatible open-source model and requests a strict JSON report. The
server does not store logs or request history. The model name and endpoint are
configurable through environment variables.
If Ollama is unavailable, OpenTrace uses a deliberately limited heuristic
fallback and labels the result Demo Mode. It never presents the fallback
as model output.
flowchart LR
A[Browser] --> B[Node HTTP server]
B --> C{Ollama available?}
C -->|yes| D[Open-source local model]
C -->|no| E[Clearly labelled demo heuristic]
D --> F[Structured JSON report]
E --> F
F --> A
The most important product decision was not to make the assistant execute
commands. A debugging helper should help a developer decide what to inspect
next, while the developer remains responsible for validating production changes.
Making evidence and limitations visible is more useful than producing a
confident-looking answer.
cd OpenTrace
node server.js
Open http://localhost:3000. For model-backed analysis, install Ollama and run:
ollama pull llama3.2:3b
Built as a new project for the Hacktoberfest Open-Source AI Challenge: Week 4.
AI assistance was used during development and drafting.