Open Source
Instructor
by Jason Liu (community)
Structured output for LLMs via Pydantic. The cleanest answer to 'just give me a typed object back'.
Our verdict
We have not reviewed Instructor yet
No one at Enterprise DNA has checked this listing against its sources. The description comes from public listings gathered automatically. Any fact below shows where it came from and when it was last checked.
From the listing
About Instructor
Instructor patches the major LLM clients to return Pydantic models (or Zod schemas, in TS) instead of raw strings. It handles validation, retries, and streaming of structured output across providers. The first thing most engineering teams reach for when they need an LLM call that has to round-trip data reliably.
Best for
Engineers tired of regexing JSON out of model output
Use cases
- Force a model to return a well-typed JSON object on every call
- Add validation and retries to structured extraction tasks
- Stream typed structured output to the UI
- Use across many providers with one consistent API
Notes
Why it matters
Structured output is the unsung hero of production LLM apps. Instructor made the typed-object pattern the default, not the exception.
How teams use it in production
Patch the client, write a Pydantic model, ask for the model back. The rest of the code looks like a normal service. Reliability follows from the schema, not from clever prompt engineering.
What to watch
Native structured output is shipping across most major providers. Instructor's value is the cross-provider consistency layer that stays useful when each provider does it slightly differently.
Pros
- Drop-in patch on existing OpenAI, Anthropic, Google clients
- Validation + retries handled cleanly
- Streaming structured output is rare and well-implemented
- Strong docs and large community
Cons
- Python implementation is more mature than TypeScript
- Adds a layer of abstraction on top of provider SDKs
- Newer streaming features still evolving
Key facts
What we have checked
- Latest version
- 1.17.0 (released 9 Sept 2026)
- Days since the last commit
- 0
- GitHub forks
- 1,357
- GitHub stars
- 14,099
- Days to a first reply on issues
- 24.4
- Open issues
- 0
- Releases in the last 90 days
- 2
Each value shows when we last confirmed it and where it came from. Values we have not confirmed are left out, never guessed.
Stars and usage
How Instructor is growing
13,943 to 14,099
Health and security
Is Instructor looked after, and what do its setup files show
Health score
76 out of 100
| Part | Points | What we saw |
|---|---|---|
| Recent activity | 30 of 30 | Last push 0 days ago |
| Releases | 11.3 of 15 | 2 releases in 90 days |
| Issue replies | 4.2 of 20 | First reply in 24.4 days (median) |
| Maintainer | 15 of 15 | Owned by an organisation |
| Official source | Not counted | MCP servers only |
Alternatives
Alternatives to Instructor
| Record | Type | How we know | Checked |
|---|---|---|---|
| GuidanceThis is an alternative to it | Open source | Named in the listing | Not dated |
| OutlinesThis is an alternative to it | Open source | Named in the listing | Not dated |
Compare
Compare Instructor side by side
Sources
Where this comes from
A source shows what was published when we checked it. It does not certify security, performance or a working installation. Read our method.
Changelog
What changed
Released 1.17.0
Released 1.16.0
Released 1.15.4
Released 1.15.3
Released 1.15.1
Released 1.15.0
Released 1.14.5
Released 1.14.4
Released 1.14.3
Released 1.14.2
Open-source & AI alternatives
Swap-in tools that solve the same job. Weigh the trade-offs before you commit.
Pairs with
Other entries in the index that connect to this one. Click through to see the chain.
Get the free Developer’s Field Guide
A 27-page field guide to the AI coding workflow with Claude. Claude Code, MCP servers, the prompt patterns that work, and what to delegate. Free.
Enter your work email. We send it straight over, plus a few short notes worth knowing. Unsubscribe any time.