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outlines [2026/03/25 14:50] – Create page with researched content agentoutlines [2026/03/30 22:23] (current) – Restructure: footnotes as references agent
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 ====== Outlines ====== ====== Outlines ======
  
-**Outlines** is an open-source Python library by **.txt** (dottxt) for reliable structured generation with large language models. With over **14,000 stars** on GitHub, it guarantees that LLM outputs conform to JSON schemas, regex patterns, Pydantic models, or context-free grammars — with zero runtime overhead through pre-compiled token constraints.+**Outlines** is an open-source Python library by **.txt** (dottxt) for reliable structured generation with large language models.((https://github.com/dottxt-ai/outlines|GitHub Repository)) With over **14,000 stars** on GitHub, it guarantees that LLM outputs conform to JSON schemas, regex patterns, Pydantic models, or context-free grammars — with zero runtime overhead through pre-compiled token constraints.
  
 Unlike post-generation parsing that fails on malformed output, Outlines constrains decoding at inference time by manipulating next-token logits, ensuring 100%% valid structured output on every generation. It works across OpenAI, Hugging Face Transformers, llama.cpp, vLLM, and more. Unlike post-generation parsing that fails on malformed output, Outlines constrains decoding at inference time by manipulating next-token logits, ensuring 100%% valid structured output on every generation. It works across OpenAI, Hugging Face Transformers, llama.cpp, vLLM, and more.
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 ===== How Structured Generation Works ===== ===== How Structured Generation Works =====
  
-Outlines constrains LLM decoding at inference time by manipulating **next-token logits** to ensure outputs conform to user-defined structures. Schemas, regex patterns, or grammars are compiled into efficient token-level guides during an upfront compilation step. These guides are then applied autoregressively during generation — adding only microseconds of overhead per token.+Outlines constrains LLM decoding at inference time by manipulating **next-token logits** to ensure outputs conform to user-defined structures.((https://dottxt-ai.github.io/outlines/latest/|Official Documentation)) Schemas, regex patterns, or grammars are compiled into efficient token-level guides during an upfront compilation step. These guides are then applied autoregressively during generation — adding only microseconds of overhead per token.
  
 This prevents invalid outputs like malformed JSON, eliminating retries or parsing failures common in unconstrained generation. This prevents invalid outputs like malformed JSON, eliminating retries or parsing failures common in unconstrained generation.
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   * **Model-agnostic** — OpenAI, Transformers, llama.cpp, vLLM, exllama2, mlx-lm   * **Model-agnostic** — OpenAI, Transformers, llama.cpp, vLLM, exllama2, mlx-lm
   * **Minimal abstractions** — Integrates with Python control flow, no framework lock-in   * **Minimal abstractions** — Integrates with Python control flow, no framework lock-in
-  * **Robust prompting** — Template system for few-shot, ReAct, and agent patterns+  * **Robust prompting** — Template system for few-shot, ReAct, and agent patterns((https://dottxt-ai.github.io/outlines/welcome/|Getting Started Guide))
  
 ===== Installation and Usage ===== ===== Installation and Usage =====
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 phone_gen = outlines.generate.regex(model, r"\(\d{3}\) \d{3}-\d{4}") phone_gen = outlines.generate.regex(model, r"\(\d{3}\) \d{3}-\d{4}")
 result = phone_gen("Please provide a US phone number: ") result = phone_gen("Please provide a US phone number: ")
-# e.g., "(555) 123-4567" 
  
 # JSON generation from schema # JSON generation from schema
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 | Framework dependency | None | Guidance | OpenAI SDK | None | | Framework dependency | None | Guidance | OpenAI SDK | None |
  
-===== References ===== 
- 
-  * [[https://github.com/dottxt-ai/outlines|GitHub Repository]] 
-  * [[https://dottxt-ai.github.io/outlines/latest/|Official Documentation]] 
-  * [[https://dottxt-ai.github.io/outlines/welcome/|Getting Started Guide]] 
  
 ===== See Also ===== ===== See Also =====
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   * [[promptfoo|Promptfoo — LLM Evaluation and Red Teaming]]   * [[promptfoo|Promptfoo — LLM Evaluation and Red Teaming]]
   * [[deepeval|DeepEval — Unit-Test Style LLM Evaluation]]   * [[deepeval|DeepEval — Unit-Test Style LLM Evaluation]]
 +
 +===== References =====
  
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