trustcall: Reliable and efficient structure data extraction using JSON patch operations

LangChain · Beginner ·🤖 AI Agents & Automation ·1y ago
LLMs struggle when asked to generate or modify large JSON blobs. trustcall solves this by asking the LLM to generate JSON patch operations. This is a simpler task that can be done iteratively. This enables: ⚡ Faster & cheaper generation of structured output. 🐺Resilient retrying of validation errors, even for complex, nested schemas (defined as pydantic, schema dictionaries, or regular python functions) 🧩Acccurate updates to existing schemas, avoiding undesired deletions. Works flexibly across a number of common LLM workflows like: ✂️ Extraction 🧭 LLM routing 🤖 Multi-step agent tool use GitHub repo: https://github.com/hinthornw/trustcall
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