feat(backend): add /api/diagnostics endpoint for environment and dependency health#623
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SxBxcoder wants to merge 2 commits intoAOSSIE-Org:mainfrom
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feat(backend): add /api/diagnostics endpoint for environment and dependency health#623SxBxcoder wants to merge 2 commits intoAOSSIE-Org:mainfrom
SxBxcoder wants to merge 2 commits intoAOSSIE-Org:mainfrom
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No actionable comments were generated in the recent review. 🎉 ℹ️ Recent review info⚙️ Run configurationConfiguration used: defaults Review profile: CHILL Plan: Pro Run ID: 📒 Files selected for processing (1)
📝 WalkthroughWalkthroughAdded a new Flask GET endpoint Changes
Sequence Diagram(s)sequenceDiagram
participant Client as Client
participant Server as Flask Server
participant OS as OS/System
participant Torch as PyTorch (optional)
Client->>Server: GET /api/diagnostics
Server->>OS: gather platform, release, arch, python_version, cpu_count
alt PyTorch import succeeds
Server->>Torch: import torch
Torch-->>Server: torch.__version__, cuda.is_available()
else PyTorch import fails
Torch-->>Server: ModuleNotFoundError / Exception
end
Server-->>Client: JSON diagnostics (200) or 403 if disabled
Estimated code review effort🎯 3 (Moderate) | ⏱️ ~20 minutes Poem
🚥 Pre-merge checks | ✅ 2 | ❌ 1❌ Failed checks (1 warning)
✅ Passed checks (2 passed)
✏️ Tip: You can configure your own custom pre-merge checks in the settings. ✨ Finishing Touches🧪 Generate unit tests (beta)
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Actionable comments posted: 2
🤖 Prompt for all review comments with AI agents
Verify each finding against the current code and only fix it if needed.
Inline comments:
In `@backend/server.py`:
- Around line 495-528: The diagnostics endpoint system_diagnostics currently
returns detailed host/runtime metadata; gate it behind a configuration flag and
tighten production behavior: add a config check (e.g.,
app.config.get("DIAGNOSTICS_ENABLED", False) or ENV != "production") at the top
of system_diagnostics and return a minimal 403/404 or a small
{"status":"unavailable"} response when disabled, and in production ensure only
non-identifying info (or just status) is returned; update any references to
platform/sys/os/torch usage to only run when diagnostics are enabled to avoid
leaking environment details.
- Around line 518-525: The current try/except only catches ImportError for the
torch import block and can still crash on OSError/RuntimeError or attribute
access failures; update the diagnostics logic around the torch import and
attribute reads (the block that sets
diagnostics["ml_environment"]["pytorch_available"],
diagnostics["ml_environment"]["torch_version"],
diagnostics["ml_environment"]["cuda_available"]) to catch broad exceptions
(catch Exception) and on any failure set diagnostics["status"] = "degraded
(pytorch error)" and record the exception message into diagnostics (e.g.,
diagnostics["ml_environment"]["pytorch_error"]) so broken installs return a
degraded status instead of raising; also guard attribute access
(torch.__version__, torch.cuda.is_available) inside the same exception scope to
avoid unhandled errors.
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Author
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Addressed CodeRabbit's security and resilience feedback in the latest commit.
Pipeline is green and this is ready for maintainer review whenever you have a chance @yatikakain @Aditya062003 |
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Addressed Issues:
Fixes N/A (Proactive backend infrastructure addition to assist maintainers in triaging local setup and dependency failures).
Screenshots/Recordings:
N/A (Backend JSON Endpoint).
Expected Output from
GET /api/diagnostics:{ "status": "healthy", "system": { "os": "Windows", "release": "10", "architecture": "AMD64", "python_version": "3.10.11", "cpu_count": 8 }, "ml_environment": { "pytorch_available": true, "cuda_available": false, "torch_version": "2.1.2+cpu" } }Additional Notes:
This PR introduces a lightweight /api/diagnostics endpoint to backend/server.py.
Currently, when new contributors (especially those on Windows or machines with 8GB RAM) experience backend crashes during onboarding, maintainers have to guess if the issue is a Python version mismatch, a missing PyTorch wheel, or a CPU/VRAM bottleneck.
This endpoint requires zero new dependencies and provides an instant snapshot of the host's environment. Moving forward, when a user reports a crash in the Discord, maintainers can simply ask them to ping /api/diagnostics and share the output, drastically reducing triage time and friction for GSoC applicants.
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