JC Beasley
0bd719ab91
- Create patterns/ directory with README, manifest, and 10 initial patterns covering Ollama JSON fallback, API escaping, deprecation, PTY auth, queue-poll, LLM-as-parser, credential rotation, reverse proxy binding, human approval gates, and transient retry. - Wire pattern loading into architecture/pipeline.js based on task tags. - Update architecture/orchestrator.js to load patterns and surface them in the system prompt. - Update MEMORY.md, ARCHITECTURE.md, and CONTEXT.md to document the registry and record the decision.
33 lines
1.8 KiB
Markdown
33 lines
1.8 KiB
Markdown
# Pattern: JSON Escaping for Downstream APIs
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## Symptom
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An n8n workflow passes LLM-generated text into a downstream API call, and the request fails with a JSON parse error, malformed payload, or unexpected truncation. The generated text contains quotes, newlines, backslashes, emojis, or control characters that break JSON encoding.
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## Affected Projects
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- LinkedIn content automation (LinkedIn REST API posts)
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- AI video generation pipeline (ComfyUI / JSON2Video payloads)
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- Any n8n workflow that injects LLM output into an HTTP Request node body
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## Root Cause
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LLMs produce human-readable text; downstream APIs consume machine-readable JSON. Naive string concatenation or weak JSON serialization allows unescaped characters to corrupt the payload. The failure often appears at the receiving API, making root-cause diagnosis slower.
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## Standard Fix
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1. Treat LLM output as untrusted string data.
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2. Always serialize it through a proper JSON encoder (`JSON.stringify` in JS, `json.dumps` in Python) before embedding in a payload.
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3. If building a payload string manually, escape quotes, backslashes, newlines, and control characters; better, avoid manual string building entirely.
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4. Add a validation step that parses the final payload with `JSON.parse` before sending.
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5. For n8n, prefer expression mapping through structured fields rather than raw body strings.
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## When to Apply
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- Any new integration where LLM-generated content becomes part of an API request body.
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- Any HTTP Request node in n8n that builds a JSON body from expressions containing LLM output.
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## Verification
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- Test with adversarial LLM output containing quotes, newlines, unicode, and backslashes.
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- Confirm the receiving API parses the payload correctly.
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- Log payload shape (without secrets) for debugging.
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## Related Patterns
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- `ollama-structured-output-fallback`
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- `llm-as-parser-fallback`
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