{"slug": "build-an-ai-error-explainer-in-python", "title": "Build an AI Error Explainer in Python", "summary": "Telnyx released a Python example that turns stack traces into structured debugging JSON using its AI Inference API. The Flask app accepts a stack trace and optional context, then returns a predictable object with root cause, severity, suggested fix, and other fields. This enables developers to route, store, or display error explanations programmatically.", "body_md": "Stack traces are useful, but they are not always easy to act on quickly.\n\nWhen something breaks, you usually want more than the exception name. You want to know the likely root cause, how serious it is, where to look, and what fix to try first.\n\nThis Python example turns a stack trace into structured debugging JSON using Telnyx AI Inference.\n\nThe Flask app exposes:\n\n```\nPOST /explain\nGET /analyses\nGET /analyses/<id>\nGET /health\n```\n\n`POST /explain`\n\naccepts a stack trace, plus optional language and runtime context:\n\n```\n{\n  \"language\": \"python\",\n  \"context\": \"Flask production server with gunicorn\",\n  \"stack_trace\": \"Traceback (most recent call last):\\n  File \\\"app.py\\\", line 42...\"\n}\n```\n\nThe app sends the trace to Telnyx AI Inference and asks for structured JSON:\n\n```\n{\n  \"root_cause\": \"The outbound HTTP call is failing because the downstream service is unreachable.\",\n  \"severity\": \"high\",\n  \"confidence\": 0.91,\n  \"likely_culprit\": \"app.py:42\",\n  \"suggested_fix\": \"Add timeout handling and retry logic around the request.\",\n  \"fix_snippet\": \"resp = requests.post(url, timeout=15)\",\n  \"related_errors\": [\"requests.exceptions.Timeout\"],\n  \"prevention\": \"Set explicit timeouts for outbound HTTP calls.\"\n}\n```\n\nPlain text explanations are nice for humans. Structured output is useful for apps.\n\nWith this response shape, you could:\n\nThe example stores recent analyses in memory and lets you retrieve them by ID.\n\nClone the examples repo:\n\n```\ngit clone https://github.com/team-telnyx/telnyx-code-examples.git\ncd telnyx-code-examples\ngit switch feat/error-explainer-python\ncd error-explainer-python\n```\n\nCreate your `.env`\n\nfile:\n\n```\ncp .env.example .env\n```\n\nAdd your Telnyx API key:\n\n```\nTELNYX_API_KEY=your_telnyx_api_key\nAI_MODEL=moonshotai/Kimi-K2.6\nHOST=127.0.0.1\n```\n\nInstall and start:\n\n```\npip install -r requirements.txt\npython app.py\n```\n\nTry the health endpoint:\n\n```\ncurl http://localhost:5000/health\n```\n\nExplain an error:\n\n```\ncurl -X POST http://localhost:5000/explain \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\n    \"language\": \"python\",\n    \"context\": \"Flask production server\",\n    \"stack_trace\": \"KeyError: user_id\"\n  }' | python3 -m json.tool\n```\n\nThis is a small example, but it maps pretty cleanly to real developer workflows:\n\nThe useful part is not only that a model can explain an error. It is that the app gets back a predictable object it can route, store, display, or review.\n\nTelnyx AI skills and toolkits: [https://github.com/team-telnyx/ai](https://github.com/team-telnyx/ai)\n\nTelnyx AI Inference docs: [https://developers.telnyx.com/docs/inference](https://developers.telnyx.com/docs/inference)\n\nChat Completions API: [https://developers.telnyx.com/api/inference/chat-completions](https://developers.telnyx.com/api/inference/chat-completions)\n\nTelnyx Portal: [https://portal.telnyx.com/](https://portal.telnyx.com/)", "url": "https://wpnews.pro/news/build-an-ai-error-explainer-in-python", "canonical_source": "https://dev.to/sonam_50a41a4ced7e6b4f3fa/build-an-ai-error-explainer-in-python-5gjn", "published_at": "2026-07-14 20:51:36+00:00", "updated_at": "2026-07-14 21:28:04.088447+00:00", "lang": "en", "topics": ["artificial-intelligence", "developer-tools", "ai-tools", "natural-language-processing"], "entities": ["Telnyx", "Telnyx AI Inference", "Flask", "Python", "moonshotai/Kimi-K2.6"], "alternates": {"html": "https://wpnews.pro/news/build-an-ai-error-explainer-in-python", "markdown": "https://wpnews.pro/news/build-an-ai-error-explainer-in-python.md", "text": "https://wpnews.pro/news/build-an-ai-error-explainer-in-python.txt", "jsonld": "https://wpnews.pro/news/build-an-ai-error-explainer-in-python.jsonld"}}