How to Check LLM License Compatibility
Navigate the complexities of LLM licensing with essential guidelines for compliance, avoiding conflicts, and leveraging automated tools.
Want to avoid legal trouble when using open-source LLMs? Here's how:
- Understand License Types: Open-source licenses fall into three categories: Permissive (e.g., MIT, Apache 2.0), Strong Copyleft (e.g., GPL, AGPL), and Weak Copyleft (e.g., MPL). Each has different rules for use, modification, and distribution.
- Review License Terms: Always check for commercial use permissions, modification rights, and redistribution rules. Watch out for restrictions like acceptable use policies or source-available licenses (e.g., Meta’s Llama 2 Community License).
- Identify Dependencies: Map all components, including model code, architecture, weights, and datasets. Use tools like LiDetector or SCANOSS to scan for license conflicts.
- Avoid License Conflicts: Ensure all licenses in your stack are compatible. For example, GPL licenses may require you to open-source your entire project.
- Document Everything: Maintain a Software Bill of Materials (SBOM) to track components, licenses, and compliance efforts.
- Use Tools: Automate compliance checks with tools like Microsoft’s SBOM Tool or Anchore’s Syft. Integrate these into your CI/CD pipeline for continuous monitoring.
Quick Comparison of License Types
| License Type | Commercial Use | Modification Rights | Distribution Flexibility | Compliance Complexity | Risk Level |
|---|---|---|---|---|---|
| Permissive | Yes | Full | High | Low | Low |
| Strong Copyleft | Conditional | Must share modifications | Low | High | High |
| Weak Copyleft | Yes | Limited sharing required | Moderate | Medium | Medium |
Bottom Line: Start reviewing licenses early, document your findings, and use automated tools to avoid compliance risks. Missteps can lead to fines, legal disputes, and project delays.
Open-Source LLM License Types
When integrating large language models (LLMs) into commercial software, understanding open-source license types is essential. Each license type comes with specific obligations that can influence how you use, modify, or distribute the software. Let’s break down the three main categories of open-source licenses so you can better navigate compliance requirements.
Permissive Licenses
Permissive licenses are the most flexible, placing few restrictions on how the code can be used. They allow modification, distribution, and incorporation into proprietary projects, provided basic attribution requirements are met.
The MIT License is straightforward: you can reuse the code, even in proprietary software, as long as the original copyright notice is included.
Apache 2.0 offers similar freedoms but includes additional provisions around patent rights. Users must provide the original copyright notice, a copy of the license, and details of any significant changes made to the code. Unlike the MIT License, Apache 2.0 explicitly allows end users to claim patents on modifications.
Examples of permissive licensing in action include Falcon (TII UAE) and Mistral 7B, which are released under Apache 2.0, allowing commercial use and adaptation of their model weights. Similarly, EleutherAI's GPT-NeoX code is distributed under Apache 2.0. Notably, in 2019, 27% of all open-source projects on GitHub used the MIT License.
Next, let’s look at how copyleft licenses differ by imposing stricter conditions on derivative works.
Copyleft Licenses
Copyleft licenses are designed to ensure that any derivative works remain open source, preserving the openness of the original code.
Strong copyleft licenses, such as the GNU General Public License (GPL), go a step further. They require that any redistributed program incorporating GPL-licensed code be released under the same license. This includes linked libraries or other integrated components. For instance, if a proprietary application uses a GPL-licensed library, the entire application may need to be open-sourced. Similarly, SaaS products using AGPL-licensed components might have to disclose their modified source code, even if the software is hosted rather than distributed. These requirements can create challenges for commercial projects aiming to keep their code private. The Free Software Foundation introduced copyleft licenses to ensure that software remains open for use, modification, and redistribution.
Weak Copyleft Licenses
Weak copyleft licenses strike a balance, allowing proprietary software to integrate open-source components as long as only the modified parts are disclosed. The key difference is that the copyleft obligations apply only to the derivative components, not to the entire software.
The Mozilla Public License 2.0 (MPL) is a prime example. Under this license, any changes to the licensed component must be open-sourced, but the rest of the code in a composite project can remain proprietary. This flexibility makes it easier for companies to integrate weak copyleft components into their software without exposing their entire codebase, provided they comply with the license terms.
| License Type | Commercial Use | Source Code Requirements | Patent Protection | Examples |
|---|---|---|---|---|
| Permissive | Unrestricted | Attribution only | Varies (Apache 2.0: Yes, MIT: Ambiguous) | MIT, Apache 2.0, BSD |
| Strong Copyleft | Restricted | Entire derivative work | Limited | GPL, AGPL |
| Weak Copyleft | Conditional | Modified components only | Varies | MPL |
Choosing the right license type is critical for shaping your compliance strategy and business model. Many companies mitigate risks by isolating copyleft components or opting for alternative licenses. Clear documentation and thorough legal reviews are essential to ensure compliance.
How to Check LLM License Compatibility
Once you're familiar with the different license types, the next step is ensuring they align with your business goals. A structured approach to checking LLM license compatibility is crucial to sidestep potential compliance issues later on.
Find Licenses and Dependencies
Start by mapping out all components that could influence compliance. LLMs are made up of several interconnected parts, such as model code, architecture, weights, and training datasets - each of which may have its own license.
Focus first on your direct dependencies, which include any libraries or components your code directly integrates with, as these present the highest compliance risks. Next, look into transitive dependencies - those that your dependencies rely on - as they can also introduce licensing obligations. To speed up this process, consider using automated tools that scan for open-source components, identify their licenses, and flag potential risks. This risk-based approach helps prioritize the most critical areas first.
Review License Terms and Conditions
Once you've identified the components, dive into the specifics of their licenses. Pay close attention to terms that could impact commercial usage, especially clauses related to redistribution, modifications, and commercial applications. It's critical to recognize that not all licenses labeled as "open" are truly unrestricted.
Be particularly mindful of source-available licenses, which may look similar to open-source licenses but often come with conditions for commercial use or specific applications. For example, Meta's Llama 2 Community License and Open RAIL licenses allow free use but under clearly defined terms.
"Under a strict definition, an 'Open Source LLM' would be one released under an OSI-approved license that doesn't limit use or access - a high bar that many so-called open models do not meet."
Also, check for any acceptable use policies included in the licenses. These policies can restrict certain industries or activities. Remember, just because a model offers its weights openly doesn't mean it's truly open-source. Always verify if the license is OSI-approved to ensure it meets open-source standards.
Check for License Conflicts
Identifying and addressing license conflicts early is crucial for avoiding disruptions in commercial use. Conflicts often occur when components with incompatible licenses are combined, and this issue becomes even trickier in mixed-license scenarios. For instance, strong copyleft licenses like the GPL may require you to open-source portions of your proprietary code, while AGPL licenses could mandate disclosing modified source code even for hosted applications.
When reviewing terms, confirm that the software explicitly allows commercial use. If you're unsure about any part of a license, consult your legal team or reach out to the license holder for clarification.
For LLM systems with components covered by different licenses, document potential conflicts and plan how to address them. Solutions could include isolating certain components, negotiating alternative licensing terms, or using different technical approaches.
Document Your Findings
Keeping detailed records is vital for compliance audits and ongoing license management. Document every part of your license review process, including the components analyzed, their versions, and the licenses identified. Record any conflicts and how they were resolved.
Create a Software Bill of Materials (SBOM) to log all components and their respective licenses. Additionally, keep track of any communications with license holders, legal consultations, or decisions to exclude certain components due to licensing issues. This documentation not only shows due diligence but also protects your organization if licensing questions arise in the future.
Tools and Best Practices for License Compliance
Navigating license compliance for large language models (LLMs) becomes much easier with the right tools. Considering that modern applications often consist of up to 90% open-source code, automated solutions are essential for staying on top of compliance requirements.
License Scanning Tools
Specialized tools can automatically identify and analyze licenses associated with LLMs. For example, SCANOSS compares AI-generated code against a comprehensive database of known code, helping developers pinpoint matches and understand the associated licenses in detail.
Another useful tool is Microsoft's SBOM Tool, an open-source utility that generates SPDX 2.2–compatible Software Bill of Materials (SBOMs) across platforms like Linux, Mac, and Windows. Similarly, Anchore's Syft is a command-line tool and Go library that creates SBOMs from container images and filesystems. It supports both SPDX and CycloneDX formats and works across multiple programming languages.
These tools address a critical need, especially since many organizations still lack formal compliance procedures. Incorporating them into your workflow can help catch potential issues early and avoid complications down the line.
Add Compliance to DevOps
Embedding license compliance directly into your DevOps pipeline is a proactive way to prevent issues before they escalate. This "compliance as code" strategy ensures that both regulatory and organizational requirements are met seamlessly throughout the development lifecycle.
Start by integrating license scanning tools into your CI/CD pipelines. This way, every new dependency is reviewed as the code is built and deployed. Use automated policies within these tools to flag problematic licenses and adopt standardized playbooks to simplify compliance workflows. Establishing an Open Source Review Board (OSRB) can also centralize oversight, enforce open-source policies, and provide guidance for complex licensing scenarios.
Automation in compliance not only reduces risks but also helps avoid costly fines by identifying potential issues early in the process. These measures lay the groundwork for a solid SBOM strategy.
Create a Software Bill of Materials (SBOM)
An SBOM is essentially an inventory of all components used in building and running your LLM applications. This includes modules, libraries, dependencies, machine learning models, and datasets. For AI projects, SBOMs must also account for dynamic elements like model weights, training data, and external APIs.
To keep your SBOM accurate, automate its generation and updates during the build process. Use consistent formats like SPDX or CycloneDX, ensuring they include details such as component versions, sources, and any known vulnerabilities. Regular updates are crucial to reflect the current state of your software composition.
Work with Latitude for LLM Compliance
Latitude offers a collaborative platform that bridges the gap between technical and business teams, ensuring smoother compliance with LLM licensing requirements. By involving all stakeholders early in the development process, Latitude simplifies navigating complex licensing landscapes.
The platform includes features like model watermarking, which tracks when, where, and how model outputs are used. This is crucial for detecting misuse or unauthorized sharing of model-generated data. Latitude also supports detailed logging of LLM interactions, capturing prompt histories and outputs. Automated audit processes can then scan these logs for potential security incidents.
With the North American LLM market projected to hit $105.5 billion by 2030, having strong compliance processes in place is becoming increasingly important for commercial success. Latitude’s collaborative tools help ensure compliance is integrated into every stage of development, avoiding the pitfalls of treating it as an afterthought.
Check Compatibility with Commercial Systems
Once you've identified potential license conflicts, the next step is to evaluate whether the LLM's license fits your commercial goals. This process connects the technical aspects of license review with broader business priorities.
Match License Requirements to Business Needs
It’s essential to align the license terms with your business model, including how you plan to distribute your product, meet customer expectations, and comply with regulations. Start by defining your deployment method - whether it's SaaS, desktop, or mobile.
Commercial use permissions are a critical consideration. Most open-source licenses allow commercial use, but the specific conditions can vary widely.
Pay close attention to modification and distribution rights. If your business involves tailoring the LLM for specific industries or clients, make sure the license allows for modifications and redistribution of derivative works. For example, permissive licenses generally provide more leeway, while copyleft licenses often require you to share any changes under the same terms.
Another key factor is ensuring that the outputs generated by the LLM don't infringe on third-party intellectual property rights. Additionally, U.S.-specific legal and regulatory factors may influence how well a license aligns with your business needs.
U.S.-Specific Legal and Business Factors
Beyond aligning with business needs, U.S. laws and regulations add another layer of complexity. The nuances of U.S. contract law and industry-specific rules can heavily impact how licenses are interpreted and enforced.
Regulatory compliance is a major consideration, especially for industries like healthcare, finance, or government. For instance, organizations must ensure that their LLM deployments meet regulations such as HIPAA, SOC 2, or federal contracting requirements. To simplify compliance, look for vendors that have undergone external audits to verify adherence to these standards.
Risk management is equally important. U.S. companies face potential risks such as patent litigation and copyright infringement claims. To mitigate these, assess the risks of vendor lock-in and consider combining proprietary and open-source AI solutions. Additionally, establish clear policies and technical safeguards to prevent sensitive data leaks when using LLMs.
When calculating the total cost of ownership (TCO), factor in U.S.-specific expenses like computing power, storage, fine-tuning, and security measures. Proprietary models might reduce some infrastructure costs but can become expensive as API usage scales. On the other hand, open-source models often involve higher upfront costs but may prove more economical over time.
Use Comparison Tables for Decisions
Using structured comparison tables can help you weigh the pros and cons of different license types and how they affect your operations. These tables make it easier to visualize trade-offs.
| License Type | Commercial Use | Modification Rights | Distribution Flexibility | Compliance Complexity | Risk Level |
|---|---|---|---|---|---|
| Permissive (Apache 2.0) | Unrestricted | Full rights | Maximum flexibility | Low | Low |
| Weak Copyleft (LGPL) | Permitted | Limited sharing requirements | Moderate flexibility | Medium | Medium |
| Strong Copyleft (GPL) | Permitted with conditions | Must share modifications | Restricted | High | High |
| Custom (Llama 2) | Conditional on user base | Permitted with restrictions | Limited by terms | Medium | Medium |
This kind of comparison highlights both immediate and long-term implications of each license. For instance, permissive licenses offer greater freedom but less control, while restrictive licenses prioritize the creator's rights, potentially limiting how the model can be used.
When evaluating license options, also consider your organization's technical expertise and resources. Open-source models are becoming increasingly popular for their customization potential and cost efficiency. However, they often require more in-house skills to manage and maintain compared to proprietary options.
Ultimately, license compatibility isn't just about legal compliance - it's about ensuring your approach aligns with your business goals while minimizing risks. Conduct a thorough license review to understand data ownership, modification rights, deployment restrictions, and embedding permissions before finalizing your strategy.
Conclusion: Maintain License Compliance
Maintaining license compliance isn't just a one-time task - it’s an ongoing responsibility. As technology and licensing terms shift, keeping up with LLM license compatibility requires constant attention. The risks of falling short are significant and can have serious consequences for organizations.
Consider this: in 2021, two organizations in Kansas were fined nearly $75,000 for using unlicensed software. While this example relates to traditional software, the same principles apply to LLM licensing. Non-compliance can lead to financial penalties, legal troubles, and damage to your organization's reputation.
To stay on top of compliance, establish a systematic approach to license management. This includes thoroughly reviewing software license agreements and reassessing them each time a renewal comes up. Create clear procedures for selecting, purchasing, and managing LLM software, and ensure all relevant team members are familiar with these processes. Keep all license information centralized - this "single source of truth" should include purchase records, renewal dates, and user assignments. Regular compliance checks, such as quarterly reviews, can help you catch and resolve issues before they escalate.
For LLM deployments, take a proactive approach to renewals. Set up a renewal calendar with checkpoints at 90, 60, and 30 days before expiration. This gives you the flexibility to decide whether to renew, renegotiate, or replace licenses based on your organization’s changing needs.
If you're using Latitude for LLM development, extend these compliance practices across all tools and dependencies. Latitude’s collaborative features make it easier to track and enforce license terms throughout the entire development process. Since AI engineering often involves multiple contributors, it's crucial to ensure compliance across every stage - from initial prompt creation to final deployment.
Another tip: before purchasing new licenses, check if existing ones can be reassigned or replaced with more cost-effective options that still meet your needs. This approach not only keeps you compliant but also helps manage costs as your LLM usage grows.
As LLM licensing continues to evolve, staying vigilant is key. Organizations that prioritize compliance will be better positioned to maintain both legal integrity and operational success in their AI initiatives.
FAQs
How can I verify that open-source LLM licenses align with my project's licensing needs?
When evaluating whether open-source LLM licenses fit your project's licensing requirements, it’s essential to dive into the specifics of each license. Focus on key aspects like commercial use, modifications, and redistribution. Licenses such as MIT or Apache tend to offer more flexibility, while copyleft licenses like GPL might require your entire project to adhere to similar licensing conditions.
For more complex situations - like projects that incorporate multiple open-source components - consider consulting legal professionals. They can help you navigate potential challenges and create a license compliance checklist to keep everything in order. These precautions can help ensure compatibility and minimize the chance of licensing conflicts.
What legal risks should I consider when using LLMs with strong copyleft licenses in commercial software?
Using LLMs with strong copyleft licenses in commercial software can lead to significant legal challenges. These licenses often require that any derivative works or modifications be shared under the same license terms. For businesses, this might mean revealing proprietary code or internal changes, potentially exposing sensitive intellectual property.
Failing to comply with copyleft terms can result in serious repercussions, including license termination, legal conflicts, or financial penalties. To avoid these risks, it’s essential to thoroughly review the license terms and seek advice from legal professionals before incorporating copyleft-licensed LLMs into commercial projects.
How can tools like Microsoft's SBOM Tool and Anchore's Syft simplify LLM license compliance?
Automated tools like Microsoft's SBOM Tool and Anchore's Syft simplify the process of managing LLM license compliance. These tools create a Software Bill of Materials (SBOM), which acts as a detailed inventory of all software components and their associated licensing terms.
By automating the identification of potential conflicts or compliance issues, these tools help ensure your software stays within licensing guidelines. This not only minimizes legal risks but also saves time during audits or reviews.