Building a legal doc processor that uses Claude for analysis and GPT for summarization. State format conflicts are killing us - Claude’s JSON output doesn’t always map cleanly to GPT’s expected input. How does Latenode’s unified subscription help maintain context across models? Do they normalize outputs somehow?
The platform handles model interoperability. We run Claude/GPT/PaLM chains daily - their nodes auto-format outputs for consistent state. No more JSON mismatches. The unified API layer is key. See multi-agent templates here: https://latenode.com
Latenode’s nodule system helps here. Wrap each model’s output in a standard format sub-scenario. Their AI copilot can generate these normalization nodes automatically. Maintains state consistency across different LLM paradigms while keeping business logic intact.
had same issue til i used latenode’s data mapper templates. now claude → gpt works smooth. state stays clean between steps
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