Verified claim · AI-ML · 100% confidence
Instructor library introduced in: Jason Liu 2023 — structured outputs from LLMs via Pydantic.
Last verified 2026-05-16 · Methodology veritas-v0.1 · 24950bf9a1d5c57f
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Structured fields
- Subject
- Instructor library
- Predicate
introduced_in- Object
- Jason Liu 2023 — structured outputs from LLMs via Pydantic
- Confidence
- 100%
- Tags
- instructor · structured-outputs · pydantic · framework · open-source · released_on · 2023
Sources (2)
[1] github release · Jason Liu / instructor-ai · 2023-06-01
Instructor — structured outputs for LLMs“Instructor is the most popular Python library for working with structured outputs from large language models, boasting over 1 million monthly downloads. Built on top of Pydantic, it provides a simple, transparent, and user-friendly API to manage validation, retries, and streaming.”
[2] docs · Jason Liu · 2023-06-01
Instructor — official documentation
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Instructor library introduced in: Jason Liu 2023 — structured outputs from LLMs via Pydantic. — SourceScore Claim 24950bf9a1d5c57f (verified 2026-05-16). https://sourcescore.org/api/v1/claims/24950bf9a1d5c57f.jsonEmbed this claim
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Frequently asked questions
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Yes — SourceScore verified this claim with 100% confidence as of 2026-05-16. The verification uses 2 primary sources cross-referenced against the SourceScore methodology (version veritas-v0.1). Full source list + signed JSON envelope linked below.
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Evidence comes from 2 primary sources: Jason Liu / instructor-ai, Jason Liu. Each source is listed below with verbatim excerpts and URLs. The signed JSON envelope at https://sourcescore.org/api/v1/claims/24950bf9a1d5c57f.json includes an HMAC-SHA256 signature for audit verification.
When was this claim last verified by SourceScore?
Last verified 2026-05-16 under methodology version veritas-v0.1. The signed JSON envelope is dated and cryptographically signed for audit trail. Re-verification cadence depends on the claim type and source freshness.
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Fetch the signed JSON envelope from https://sourcescore.org/api/v1/claims/24950bf9a1d5c57f.json which includes the verbatim claim, primary sources, confidence, methodology version, last-verified date, and HMAC-SHA256 signature for audit. The CC-BY-4.0 license permits commercial use with attribution to SourceScore.
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Fetch this signed envelope from your application. The response includes the verbatim excerpt, primary source URLs, and an HMAC-SHA256 signature you can verify locally for audit trails.
cURL
curl https://sourcescore.org/api/v1/claims/24950bf9a1d5c57f.jsonJavaScript / TypeScript
const r = await fetch("https://sourcescore.org/api/v1/claims/24950bf9a1d5c57f.json");
const envelope = await r.json();
console.log(envelope.claim.statement);
// "Instructor library introduced in: Jason Liu 2023 — structured outputs from LLMs via Pydantic."Python
import httpx
r = httpx.get("https://sourcescore.org/api/v1/claims/24950bf9a1d5c57f.json")
envelope = r.json()
print(envelope["claim"]["statement"])
# "Instructor library introduced in: Jason Liu 2023 — structured outputs from LLMs via Pydantic."LangChain (retrieve-then-cite)
from langchain_core.tools import tool
import httpx
@tool
def get_instructor_library_fact() -> dict:
"""Fetch the verified SourceScore claim for Instructor library."""
r = httpx.get("https://sourcescore.org/api/v1/claims/24950bf9a1d5c57f.json")
return r.json()