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🩹 Self-Healing Code — try_ai Fixes Runtime Errors with AI

Pipe's new try_ai syntax catches runtime errors and uses an LLM to repair and re-execute the broken expression, with a catch block as a final fallback. In an example, the type error "42" * 3 was automatically fixed to (to_num "42") * 3, returning 126, while healthy code like 6 * 7 runs without any API call. The feature is part of the Pipe in 30 Lines series and requires a DeepSeek API key to run.

read3 min views1 publishedAug 14, 2026
🩹 Self-Healing Code — try_ai Fixes Runtime Errors with AI
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Fixes Runtime Errors with AI

A type error that repairs itself: try_ai catches the crash, asks the LLM to fix the expression, and re-runs it.

Part of the Pipe in 30 Lines series: RAG without a vector DB · Parallel LLM calls · Your first MCP server

"42" * 3

is a type error — a string multiplied by a number. Most runtimes crash. Pipe's try_ai

catches the error, sends the broken expression to the LLM, and re-runs the repaired code. The catch

block only fires if even the AI can't fix it.

ai_provider "deepseek"

result: try_ai
    "42" * 3          -- E002 type error → AI repairs it
catch e
    0                 -- only reached if the fix fails

print result          -- 126

fast: try_ai
    6 * 7             -- healthy code: zero API calls
catch e
    -1

print fast            -- 42

What happens here:

runs the block. On success it returns the value directly —try_ai

no API call, no latency. The safety net is free.- On a runtime error it asks the LLM to repair the broken expression: "42" * 3

becomes(to_num "42") * 3

and re-runs. - The block is the final fallback — your pipeline never dies silently.catch

This is where a language boundary pays off: try_ai

isn't a library that wraps your calls, it's syntax that can rewrite and re-execute a fragment of your own program. That's self-healing infrastructure — not an SDK callback.

[try_ai] E002 | attempt 1 | ""42" * 3" → "(to_num "42") * 3" | ✓ FIXED
126
42

Run it: export DEEPSEEK_API_KEY=... && pipe -vm -q examples/blog_try_ai.pipe

. The deeper mechanics (including the sandboxed re-run profile) are covered in the MCP Cell deep dive.

repariert Laufzeitfehler mit KI

Ein Typfehler, der sich selbst repariert: try_ai fängt den Crash, lässt das LLM den Ausdruck fixen und führt ihn erneut aus.

Teil der Serie Pipe in 30 Lines: RAG ohne Vektor-DB · Parallele LLM-Calls · Dein erster MCP-Server

"42" * 3

ist ein Typfehler — ein String mal eine Zahl. Die meisten Runtimes crashen. Pipes try_ai

fängt den Fehler, schickt den kaputten Ausdruck an das LLM und führt den reparierten Code erneut aus. Der catch

-Block feuert nur, wenn selbst die KI es nicht hinbekommt.

ai_provider "deepseek"

result: try_ai
    "42" * 3          -- E002 Typfehler → KI repariert ihn
catch e
    0                 -- wird nur erreicht, wenn der Fix scheitert

print result          -- 126

fast: try_ai
    6 * 7             -- gesunder Code: null API-Calls
catch e
    -1

print fast            -- 42

Was hier passiert:

führt den Block aus. Bei Erfolg liefert es den Wert direkt —try_ai

kein API-Call, keine Latenz. Das Sicherheitsnetz ist kostenlos.- Bei einem Laufzeitfehler bittet es das LLM, den Ausdruck zu reparieren: aus "42" * 3

wird(to_num "42") * 3

, dann wird erneut ausgeführt. - Der -Block ist die letzte Absicherung — deine Pipeline stirbt nie still.catch

Hier zahlt sich die Sprachgrenze aus: try_ai

ist keine Bibliothek, die deine Calls umwickelt, sondern Syntax, die ein Fragment deines eigenen Programms umschreiben und neu ausführen kann. Selbstheilende Infrastruktur — kein SDK-Callback.

[try_ai] E002 | attempt 1 | ""42" * 3" → "(to_num "42") * 3" | ✓ FIXED
126
42

Starten: export DEEPSEEK_API_KEY=... && pipe -vm -q examples/blog_try_ai.pipe

. Die tieferen Mechanismen (inkl. des sandboxed Re-Run-Profils) findest du im MCP-Cell-Deep-Dive.

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