--- name: outlines-3a087310b552 description: >- Generates guaranteed-valid structured text from LLMs with Outlines, the Python library that constrains token sampling to a JSON schema, regex, choice list or grammar. Use when a user asks for reliable JSON from a local or hosted model, classification into fixed labels, regex-shaped output, grammar-constrained generation, or structured output with vLLM, Transformers, Ollama or OpenAI-compatible servers. license: Apache-2.0 compatibility: "Python 3.10 to 3.13; install the extra for the backend you use (transformers, vllm, ollama, openai, llamacpp)" metadata: author: terminal-skills version: "1.1.0" category: data-ai tags: "llm, structured-generation, json, grammar, regex" repository: https://github.com/dottxt-ai/outlines --- # Outlines — Structured Text Generation ## Overview Outlines forces a model's output to match a declared type. For local backends it compiles the type (Pydantic model, regex, choice list, context-free grammar) into a constraint on token sampling, so the first generation is already valid and no retry loop is needed. For hosted backends (OpenAI, Anthropic, Gemini, Ollama, vLLM server) it passes the type to the provider's own structured-output feature through one common interface. Checked against Outlines 1.3 (October 2026). The 1.x API is `model(prompt, output_type)`. The 0.x calls (`outlines.generate.json(...)`, `outlines.models.transformers(...)`, `outlines.generate.regex(...)`) were removed; code using them fails on current versions. ## Instructions ### Installation and model loading ```bash pip install "outlines[transformers]" # local Hugging Face models (also pulls torch) pip install "outlines[ollama]" # or: openai, anthropic, gemini, llamacpp, vllm, mlxlm ``` ```python import outlines from transformers import AutoModelForCausalLM, AutoTokenizer name = "microsoft/Phi-3-mini-4k-instruct" model = outlines.from_transformers( AutoModelForCausalLM.from_pretrained(name), AutoTokenizer.from_pretrained(name), ) ``` Other loaders: `outlines.from_ollama(client, "llama3.2")`, `outlines.from_openai(client, model_name)`, `outlines.from_vllm(openai_client, model_name)` for a running vLLM server (OpenAI client pointed at `http://127.0.0.1:8000/v1`), `outlines.from_vllm_offline(llm)`, `outlines.from_llamacpp(llm)`, plus `from_anthropic`, `from_gemini`, `from_mistral`, `from_sglang`, `from_tgi`, `from_mlxlm`. ### Output types The second argument of the call is the constraint. Always pass `max_new_tokens` on the Transformers backend: the default of 20 truncates JSON. ```python from enum import Enum from typing import Literal from pydantic import BaseModel, Field from outlines.types import Regex, Choice, CFG class ReviewAnalysis(BaseModel): sentiment: Literal["positive", "negative", "neutral"] score: float = Field(ge=0, le=1) topics: list[str] raw = model("Analyze: 'Great product, slow shipping'", ReviewAnalysis, max_new_tokens=200) review = ReviewAnalysis.model_validate_json(raw) # the call returns a JSON string phone = model("Support phone number:", Regex(r"\(\d{3}\) \d{3}-\d{4}"), max_new_tokens=20) label = model("Is this spam? 'You won $1000000!!!'", Choice(["spam", "ham", "uncertain"])) count = model("How many minutes in an hour?", int, max_new_tokens=5) ``` Also accepted: `Literal[...]`, `Enum` classes, plain types (`int`, `float`, `bool`, `datetime.date`), `JsonSchema(schema_string)`, and `CFG(lark_grammar_string)` for a Lark grammar (not every backend supports CFG). ### Batches and reuse ```python answers = model.batch(["Capital of Lithuania?", "Capital of Latvia?"], max_new_tokens=20) generator = outlines.Generator(model, ReviewAnalysis) # compile the constraint once raw = generator("Analyze: 'Arrived broken'", max_new_tokens=200) ``` ## Examples ### Example 1: Classify support tickets into fixed labels Request: "Sort these tickets into billing, bug or feature, nothing else." ```python tickets = ["I was charged twice in September", "Export button does nothing on Safari"] labels = Choice(["billing", "bug", "feature"]) print(model.batch([f"Ticket: {t}\nCategory:" for t in tickets], labels, max_new_tokens=8)) ``` Result: `['billing', 'bug']`. The output can only be one of the three strings, so no post-processing is needed. ### Example 2: Extract a typed record with a local server Request: "Get name, city and plan from this signup email using our vLLM server." ```python import openai, outlines from pydantic import BaseModel class Signup(BaseModel): name: str city: str plan: str client = openai.OpenAI(base_url="http://127.0.0.1:8000/v1", api_key="local-vllm-key") model = outlines.from_vllm(client, "microsoft/Phi-3-mini-4k-instruct") raw = model("Priya Nair from Pune signed up for the Growth plan.", Signup) print(Signup.model_validate_json(raw)) ``` Result: `Signup(name='Priya Nair', city='Pune', plan='Growth')`, validated against the schema. ## Guidelines - Constrained output guarantees the shape, not the truth: a valid JSON object can still hold a wrong answer. Keep prompts specific and check values that matter. - Complex schemas and large grammars add compile time on the first call; reuse a `Generator` rather than recompiling. - Backend support differs (for example CFG and some regex features); the model documentation page for each backend lists what it accepts. - Python 3.14 is not supported yet by the current release. - If you already use PydanticAI or a provider's native structured outputs against a hosted model, you may not need Outlines; its strength is local and self-hosted models. - Never send private text to a hosted backend you have not approved; local backends keep data on the machine. --- Source attribution: terminal-skills Original project: https://github.com/TerminalSkills/skills/blob/8a9852d489f274538be9bf1c9121aeb403750b1c/skills/outlines/SKILL.md License: Apache-2.0 License information: https://www.apache.org/licenses/LICENSE-2.0 Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. Definitions. "License" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document. "Licensor" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License. "Legal Entity" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, "control" means (i) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (ii) ownership of fifty percent (50%) or more of the outstanding shares, or (iii) beneficial ownership of such entity. "You" (or "Your") shall mean an individual or Legal Entity exercising permissions granted by this License. "Source" form shall mean the preferred form for making modifications, including but not limited to software source code, documentation source, and configuration files. "Object" form shall mean any form resulting from mechanical transformation or translation of a Source form, including but not limited to compiled object code, generated documentation, and conversions to other media types. "Work" shall mean the work of authorship, whether in Source or Object form, made available under the License, as indicated by a copyright notice that is included in or attached to the work (an example is provided in the Appendix below). "Derivative Works" shall mean any work, whether in Source or Object form, that is based on (or derived from) the Work and for which the editorial revisions, annotations, elaborations, or other modifications represent, as a whole, an original work of authorship. For the purposes of this License, Derivative Works shall not include works that remain separable from, or merely link (or bind by name) to the interfaces of, the Work and Derivative Works thereof. "Contribution" shall mean any work of authorship, including the original version of the Work and any modifications or additions to that Work or Derivative Works thereof, that is intentionally submitted to the Licensor for inclusion in the Work by the copyright owner or by an individual or Legal Entity authorized to submit on behalf of the copyright owner. For the purposes of this definition, "submitted" means any form of electronic, verbal, or written communication sent to the Licensor or its representatives, including but not limited to communication on electronic mailing lists, source code control systems, and issue tracking systems that are managed by, or on behalf of, the Licensor for the purpose of discussing and improving the Work, but excluding communication that is conspicuously marked or otherwise designated in writing by the copyright owner as "Not a Contribution." "Contributor" shall mean Licensor and any individual or Legal Entity on behalf of whom a Contribution has been received by the Licensor and subsequently incorporated within the Work. 2. Grant of Copyright License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license to reproduce, prepare Derivative Works of, publicly display, publicly perform, sublicense, and distribute the Work and such Derivative Works in Source or Object form. 3. Grant of Patent License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable (except as stated in this section) patent license to make, have made, use, offer to sell, sell, import, and otherwise transfer the Work, where such license applies only to those patent claims licensable by such Contributor that are necessarily infringed by their Contribution(s) alone or by combination of their Contribution(s) with the Work to which such Contribution(s) was submitted. If You institute patent litigation against any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Work or a Contribution incorporated within the Work constitutes direct or contributory patent infringement, then any patent licenses granted to You under this License for that Work shall terminate as of the date such litigation is filed. 4. Redistribution. You may reproduce and distribute copies of the Work or Derivative Works thereof in any medium, with or without modifications, and in Source or Object form, provided that You meet the following conditions: (a) You must give any other recipients of the Work or Derivative Works a copy of this License; and (b) You must cause any modified files to carry prominent notices stating that You changed the files; and (c) You must retain, in the Source form of any Derivative Works that You distribute, all copyright, patent, trademark, and attribution notices from the Source form of the Work, excluding those notices that do not pertain to any part of the Derivative Works; and (d) If the Work includes a "NOTICE" text file as part of its distribution, then any Derivative Works that You distribute must include a readable copy of the attribution notices contained within such NOTICE file, excluding any notices that do not pertain to any part of the Derivative Works, in at least one of the following places: within a NOTICE text file distributed as part of the Derivative Works; within the Source form or documentation, if provided along with the Derivative Works; or, within a display generated by the Derivative Works, if and wherever such third-party notices normally appear. The contents of the NOTICE file are for informational purposes only and do not modify the License. You may add Your own attribution notices within Derivative Works that You distribute, alongside or as an addendum to the NOTICE text from the Work, provided that such additional attribution notices cannot be construed as modifying the License. You may add Your own copyright statement to Your modifications and may provide additional or different license terms and conditions for use, reproduction, or distribution of Your modifications, or for any such Derivative Works as a whole, provided Your use, reproduction, and distribution of the Work otherwise complies with the conditions stated in this License. 5. Submission of Contributions. Unless You explicitly state otherwise, any Contribution intentionally submitted for inclusion in the Work by You to the Licensor shall be under the terms and conditions of this License, without any additional terms or conditions. Notwithstanding the above, nothing herein shall supersede or modify the terms of any separate license agreement you may have executed with Licensor regarding such Contributions. 6. Trademarks. This License does not grant permission to use the trade names, trademarks, service marks, or product names of the Licensor, except as required for reasonable and customary use in describing the origin of the Work and reproducing the content of the NOTICE file. 7. Disclaimer of Warranty. Unless required by applicable law or agreed to in writing, Licensor provides the Work (and each Contributor provides its Contributions) on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied, including, without limitation, any warranties or conditions of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A PARTICULAR PURPOSE. You are solely responsible for determining the appropriateness of using or redistributing the Work and assume any risks associated with Your exercise of permissions under this License. 8. Limitation of Liability. In no event and under no legal theory, whether in tort (including negligence), contract, or otherwise, unless required by applicable law (such as deliberate and grossly negligent acts) or agreed to in writing, shall any Contributor be liable to You for damages, including any direct, indirect, special, incidental, or consequential damages of any character arising as a result of this License or out of the use or inability to use the Work (including but not limited to damages for loss of goodwill, work stoppage, computer failure or malfunction, or any and all other commercial damages or losses), even if such Contributor has been advised of the possibility of such damages. 9. Accepting Warranty or Additional Liability. While redistributing the Work or Derivative Works thereof, You may choose to offer, and charge a fee for, acceptance of support, warranty, indemnity, or other liability obligations and/or rights consistent with this License. However, in accepting such obligations, You may act only on Your own behalf and on Your sole responsibility, not on behalf of any other Contributor, and only if You agree to indemnify, defend, and hold each Contributor harmless for any liability incurred by, or claims asserted against, such Contributor by reason of your accepting any such warranty or additional liability. END OF TERMS AND CONDITIONS Copyright 2025 Terminal Skills Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. # Mega AI Hub resource metadata Creator / publisher: terminal-skills Original project: https://github.com/TerminalSkills/skills/blob/8a9852d489f274538be9bf1c9121aeb403750b1c/skills/outlines/SKILL.md Attribution basis: Source repository record Fields of work: Data & Analytics, Development & Engineering Roles: Data Scientist, ML / AI Engineer, Backend Developer Specialties: API, Backend Tools: Outlines Country applicability: Country not specified Classification basis: Source category, role and specialization labels Instruction SHA-256: da01a39717827a09fb0baece541047e8ca9599224b3e1ef55db43e712a25f46e