Flowise AI Workflow Testing: Validate Self-Hosted Agents

Flowise’s 2026 sunset leaves self-hosted chatflows operational under the Apache 2.0 license but without upstream maintenance, bundled self-hosted evaluations, or reliable distribution updates, making independent testing, version pinning, and migration planning increasingly important. The proposed approach is to test chatflows externally through the POST prediction API, validating response structure, latency, required and forbidden terms, retrieval grounding through sourceDocuments, tool usage, and multi-turn memory via reused session IDs rather than relying on brittle exact text matches. Because agent failures can appear as plausible but ungrounded, incomplete, context-blind, or poorly toned responses despite successful HTTP calls, the text recommends combining deterministic assertions with model-based behavioral evaluation for qualities such as hallucination, completeness, tone, and user outcomes. It advises running tests both after flow, prompt, or knowledge-base changes and on scheduled intervals to detect model-provider drift, while storing flow exports and pinning container versions. For eventual migration or internal maintenance, teams should capture a version-controlled baseline of real production questions, full responses, retrieval metadata, latency, and configuration settings, then replay that dataset against successor platforms to measure behavioral differences.

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