---
title: "llm-guard vs langkit"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/protectai-llm-guard-vs-whylabs-langkit"
tools: ["protectai-llm-guard", "whylabs-langkit"]
---

# llm-guard vs langkit

*GraphCanon updated Aug 5, 2026*

## Verdict

Pick llm-guard if lLM Guard is a toolkit tailored for securing interactions with large language models, focusing on safeguarding against prompt injection and adversarial attacks; pick langkit if langKit is an open-source toolkit designed for monitoring large language models by extracting signals from prompts and responses to ensure their quality, relevance, and sentiment analysis.

[llm-guard](https://protectai.github.io/llm-guard/) reports 3.2k GitHub stars, 435 forks, and 40 open issues, last pushed Jul 8, 2026. [langkit](https://whylabs.ai) has 994 stars, 73 forks, and 37 open issues, last pushed Nov 22, 2024. Figures are from public GitHub metadata via [llm-guard's repository](https://github.com/protectai/llm-guard) and [langkit's repository](https://github.com/whylabs/langkit).

| | [llm-guard](/tools/protectai-llm-guard.md) | [langkit](/tools/whylabs-langkit.md) |
| --- | --- | --- |
| Tagline | The Security Toolkit for LLM Interactions | An open-source toolkit for monitoring Large Language Models ensuring safety and security |
| Stars | 3,202 | 994 |
| Forks | 435 | 73 |
| Open issues | 40 | 37 |
| Language | Python | Jupyter Notebook |
| Adopt for | LLM Guard is a toolkit tailored for securing interactions with large language models, focusing on safeguarding against prompt injection and adversarial attacks. | LangKit is an open-source toolkit designed for monitoring large language models by extracting signals from prompts and responses to ensure their quality, relevance, and sentiment analysis. |
| Persona | - | - |
| Runtime | - | - |
| License | MIT | Apache-2.0 |
| Categories | Developer Tools, Evaluation & Observability | Evaluation & Observability |

## Trust and health

_Sourced signals - not a safety guarantee. No winner column._

| | [llm-guard](/tools/protectai-llm-guard.md) | [langkit](/tools/whylabs-langkit.md) |
| --- | --- | --- |
| Maintenance | Archived (8%) | Dormant (18%) |
| Days since push | 27d | 617d |
| Archived on GitHub | Yes | No |
| Open issues (now) | 40 | 37 |
| Full report | [trust report](/tools/protectai-llm-guard/trust.md) | [trust report](/tools/whylabs-langkit/trust.md) |

## Shared compatibility

- **Python**: [llm-guard](/tools/protectai-llm-guard.md) - Python runtime; [langkit](/tools/whylabs-langkit.md) - Python runtime

## Decision facts: llm-guard

- **Requirements:** Min 2 GB RAM; Ensure you have Python version 3.9 or higher.; Some advanced features require additional libraries which are automatically installed as needed.
- **Adopt for:** LLM Guard is a toolkit tailored for securing interactions with large language models, focusing on safeguarding against prompt injection and adversarial attacks.

## Decision facts: langkit

- **Requirements:** Installation instructions suggest using pip to install LangKit.; The 'langkit[all]' package installation implies a full version that includes all optional dependencies.
- **Adopt for:** LangKit is an open-source toolkit designed for monitoring large language models by extracting signals from prompts and responses to ensure their quality, relevance, and sentiment analysis.
- **License detail:** Apache-2.0

## Choose when

### Choose llm-guard if…

- llm-guard is primarily Python; langkit is Jupyter Notebook.
- License: llm-guard is MIT, langkit is Apache-2.0.
- Requirements: Min 2 GB RAM; Ensure you have Python version 3.9 or higher.; Some advanced features require additional libraries which are automatically installed as needed..
- Tags unique to llm-guard: adversarial-machine-learning, chatgpt, llm security, security-tools.
- Also covers Developer Tools.
- - You need to secure your application from sophisticated prompt injection techniques.

### Choose langkit if…

- langkit is primarily Jupyter Notebook; llm-guard is Python.
- License: langkit is Apache-2.0, llm-guard is MIT.
- Requirements: Installation instructions suggest using pip to install LangKit.; The 'langkit[all]' package installation implies a full version that includes all optional dependencies..
- Tags unique to langkit: machine-learning, nlg, nlp, observability.
- When you need a comprehensive observability tool specifically crafted with features targeting text quality, relevance metrics, and sentiment analysis of LLM outputs.

## When NOT to use llm-guard

- - If you are working in a low-security environment or with small-scale projects where advanced security mechanisms are not necessary.
- - In cases where integrating external libraries and ensuring Python version compatibility may introduce complexities that outweigh the benefits.

## When NOT to use langkit

- When the focus is exclusively on training models rather than observing their behavior and performance post-training, as LangKit specializes in monitoring and not enhancing training processes.
- In scenarios where minimal dependencies are necessary. LangKit's comprehensive feature set comes packaged with a broader dependency list that may be excessive for simpler needs.

## Common questions

### What is the difference between llm-guard and langkit?

llm-guard: The Security Toolkit for LLM Interactions. langkit: An open-source toolkit for monitoring Large Language Models ensuring safety and security. See the comparison table for live GitHub stats and shared categories.

### When should I choose llm-guard over langkit?

Choose llm-guard over langkit when llm-guard is primarily Python; langkit is Jupyter Notebook; License: llm-guard is MIT, langkit is Apache-2.0; Requirements: Min 2 GB RAM; Ensure you have Python version 3.9 or higher.; Some advanced features require additional libraries which are automatically installed as needed.; Tags unique to llm-guard: adversarial-machine-learning, chatgpt, llm security, security-tools; Also covers Developer Tools; - You need to secure your application from sophisticated prompt injection techniques.

### When should I choose langkit over llm-guard?

Choose langkit over llm-guard when langkit is primarily Jupyter Notebook; llm-guard is Python; License: langkit is Apache-2.0, llm-guard is MIT; Requirements: Installation instructions suggest using pip to install LangKit.; The 'langkit[all]' package installation implies a full version that includes all optional dependencies.; Tags unique to langkit: machine-learning, nlg, nlp, observability; When you need a comprehensive observability tool specifically crafted with features targeting text quality, relevance metrics, and sentiment analysis of LLM outputs.

### When should I avoid llm-guard?

- If you are working in a low-security environment or with small-scale projects where advanced security mechanisms are not necessary. - In cases where integrating external libraries and ensuring Python version compatibility may introduce complexities that outweigh the benefits.

### When should I avoid langkit?

When the focus is exclusively on training models rather than observing their behavior and performance post-training, as LangKit specializes in monitoring and not enhancing training processes. In scenarios where minimal dependencies are necessary. LangKit's comprehensive feature set comes packaged with a broader dependency list that may be excessive for simpler needs.

### Is llm-guard or langkit more popular on GitHub?

llm-guard has more GitHub stars (3,202 vs 994). Stars measure visibility, not whether either tool fits your constraints.

### Are llm-guard and langkit open source?

Yes - both are open-source projects on GitHub (llm-guard: MIT, langkit: Apache-2.0).

### Where can I find alternatives to llm-guard or langkit?

GraphCanon lists graph-backed alternatives at [llm-guard alternatives](/tools/protectai-llm-guard/alternatives) and [langkit alternatives](/tools/whylabs-langkit/alternatives) ([llm-guard markdown twin](/tools/protectai-llm-guard/alternatives.md), [langkit markdown twin](/tools/whylabs-langkit/alternatives.md)), ranked by typed relationship edges rather than popularity votes.

### Is there a machine-readable version of this comparison?

Yes. The markdown twin at [this comparison](/compare/protectai-llm-guard-vs-whylabs-langkit.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, llm-guard or langkit?

llm-guard: Archived. langkit: Dormant. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.

### Where are the full trust reports for llm-guard and langkit?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [llm-guard trust report](/tools/protectai-llm-guard/trust); [langkit trust report](/tools/whylabs-langkit/trust).

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/graph?tool=protectai-llm-guard`](/api/graphcanon/graph?tool=protectai-llm-guard)
- LLM index: [/llms.txt](/llms.txt)
- Full corpus: [/llms-full.txt](/llms-full.txt)

_GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_