GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
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Decision brief
Facilitates LLM programming with constraints for efficiency, Python-based.
Good fit when
- When needing precise control over language model output through programmable constraints
- In projects that require optimization of interaction efficiency in LLM programming
Avoid when
- For general-purpose coding without leveraging specific LLM functionalities
- If the project does not benefit from constraint-guided interactions with language models
Observed Jul 14, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Dormant (450d since push)
- As of Aug 16, 2026
- Provenance
- Not a fork · Organization account
- As of Aug 16, 2026
- Security (OSV)
- No lockfile
- As of Jul 11, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install lmqlSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
lmql is a framework that facilitates the creation of programs using large language models guided by specific constraints to optimize efficiency and specificity in responses.
Capability facts
- Languages
- python
Source: github.language · Aug 16, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Aug 16, 2026)
To install the latest version of LMQL run the following command with Python ==3.10 installed.Source link
Tags
README
Getting Started To install the latest version of LMQL run the following command with Python ==3.10 installed. Local GPU Support: If you want to run models on a local GPU, make sure to install LMQL in an environment with a GPU enabled installation of PyTorch = 1.11 (cf. https://py...
For agents
This page has a .md twin and JSON over the API.