README.md

metadata

title: Trace Field Notes
colorFrom: green
colorTo: gray
sdk: gradio
sdk_version: 6.16.0
app_file: app.py
pinned: false
license: mit

Trace Field Notes

Trace Field Notes turns coding-agent session logs into qualitative field reports.

Upload a Codex, Claude Code, or Pi Agent JSONL trace. The app ignores raw tool telemetry by default and analyzes only the agent's visible narrative messages: what it planned, where it got stuck, how it detoured, how it recovered, and how it claimed completion.

Built for the Build Small Hackathon. The frontend is a custom React field-notebook UI (a trail map of the session) served by gradio.Server; it calls the Python analyze_trace endpoint through @gradio/client. Both models run on the Space GPU through ZeroGPU: a quick Qwen/Qwen3.5-9B pass by default, and the larger nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 for deeper analysis. A verified deterministic codebook analyzer is the always-available recovery path and needs no model or GPU.

Architecture

• app.py — a gradio.Server (FastAPI) app. It serves frontend/index.html, mounts frontend/static/, exposes @server.api("analyze_trace") (queued, with gradio_client compatibility), and an /agents.md instructions endpoint.
• frontend/ — the designer's React app (in-browser Babel, no build step): field_report.css (the design system), data.js (codebook + tone labels), components.jsx (atoms + trail map + report sections), app.jsx (shell + upload, wired to the backend).
• view_model.py — adapts an AnalysisResult into the JSON shape the frontend renders (synthesizes the whole-session verdict, captured, duration_total).
• analyzer.py / parser.py / redaction.py / schemas.py — the deterministic pipeline. model_runtime.py — the optional small-model assist on ZeroGPU.

Run Locally

python3.11 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
python app.py

Test

python3.11 -m unittest discover -s tests

Analysis Engines

• Qwen3.5 9B — quick analysis: default model pass on the Space GPU.
• NVIDIA Nemotron 3 Nano 30B-A3B — deeper analysis: the larger model on the Space GPU for a richer memo.
• Rule-based — instant, no model: local codebook analyzer, no model or GPU.

If a model fails to load or returns invalid JSON, the report records the reason in model notes and returns the deterministic analysis instead of failing the whole Space.

The model-backed analysis runs under @spaces.GPU(size="xlarge") so the weights load on Hugging Face ZeroGPU hardware; Qwen/Qwen3.5-9B and nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 are loaded with transformers and cached across requests. The rule-based engine runs on CPU and never requests a GPU slot, so it returns instantly.

Agent Session Locations

# Codex
ls ~/.codex/sessions

# Claude Code
ls ~/.claude/projects

# Pi Agent
ls ~/.pi/agent/sessions

Privacy

Agent traces can contain prompts, tool inputs, command outputs, local file paths, screenshots, secrets, private source code, and personal data. Review and redact before uploading or sharing publicly. The app defaults to basic regex redaction and exports only a redacted narrative text file.