--- title: "langevals vs llm-app" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/langwatch-langevals-vs-pathwaycom-llm-app" tools: ["langwatch-langevals", "pathwaycom-llm-app"] --- # langevals vs llm-app *GraphCanon updated Jul 15, 2026* ## Verdict Pick langevals when tags unique to langevals: evaluation, guardrails, openai; pick llm-app when requirements: Requires Docker; The tool is Docker-friendly and designed to ensure synchronization with cloud-based storage solutions among others.. [langevals](https://langwatch.ai/) reports 72 GitHub stars, 9 forks, and 18 open issues, last pushed Feb 15, 2026. [llm-app](https://pathway.com/developers/templates/) has 59k stars, 1.4k forks, and 10 open issues, last pushed Jul 5, 2026. Figures are from public GitHub metadata via [langevals's repository](https://github.com/langwatch/langevals) and [llm-app's repository](https://github.com/pathwaycom/llm-app). | | [langevals](/tools/langwatch-langevals.md) | [llm-app](/tools/pathwaycom-llm-app.md) | | --- | --- | --- | | Tagline | LangEvals aggregates various language model evaluators into a single platform, providing a standard interface for a multitude of scores and LLM guardrails, for you to protect and benchmark your LLM mo | Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. | | Stars | 72 | 59,068 | | Forks | 9 | 1,432 | | Open issues | 18 | 10 | | Language | - | Jupyter Notebook | | Adopt for | - | llm-app offers pre-configured cloud deployment templates designed specifically for creating AI-driven applications such as chatbots and machine learning projects leveraging Hugging Face models. It supports direct integrz | | Persona | - | - | | Runtime | - | - | | License | - | MIT | | Categories | Data & Retrieval, Evaluation & Observability, LLM Frameworks | Data & Retrieval, LLM Frameworks, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [langevals](/tools/langwatch-langevals.md) | [llm-app](/tools/pathwaycom-llm-app.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Very active (96%) | | Days since push | 149d | 5d | | Open issues (now) | 18 | 10 | | Full report | [trust report](/tools/langwatch-langevals/trust.md) | [trust report](/tools/pathwaycom-llm-app/trust.md) | ## Decision facts: llm-app - **Requirements:** Requires Docker; The tool is Docker-friendly and designed to ensure synchronization with cloud-based storage solutions among others. - **Adopt for:** llm-app offers pre-configured cloud deployment templates designed specifically for creating AI-driven applications such as chatbots and machine learning projects leveraging Hugging Face models. It supports direct integrz ## Choose when ### Choose langevals if… - Tags unique to langevals: evaluation, guardrails, openai. - Also covers Evaluation & Observability. ### Choose llm-app if… - Requirements: Requires Docker; The tool is Docker-friendly and designed to ensure synchronization with cloud-based storage solutions among others.. - Tags unique to llm-app: chatbot, hugging-face, retrieval-augmented-generation, vector-database. - Also covers Vector Databases. - - You need a ready-to-run solution that directly integrates with various data sources like Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and live APIs. ## When NOT to use langevals - Last GitHub push was 149 days ago (slowing maintenance, Feb 15, 2026). Validate activity before betting a new project on langevals. - Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. - Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## When NOT to use llm-app - - You require custom deployment configurations that extend beyond the pre-set cloud templates available through llm-app. - - There’s a need for tightly integrated support with data sources or APIs not explicitly mentioned, such as specialized CRM systems (Salesforce), which may lack direct template support in llm-app. ## Common questions ### What is the difference between langevals and llm-app? langevals: LangEvals aggregates various language model evaluators into a single platform, providing a standard interface for a multitude of scores and LLM guardrails, for you to protect and benchmark your LLM mo. llm-app: Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data.. See the comparison table for live GitHub stats and shared categories. ### When should I choose langevals over llm-app? Choose langevals over llm-app when Tags unique to langevals: evaluation, guardrails, openai; Also covers Evaluation & Observability. ### When should I choose llm-app over langevals? Choose llm-app over langevals when Requirements: Requires Docker; The tool is Docker-friendly and designed to ensure synchronization with cloud-based storage solutions among others.; Tags unique to llm-app: chatbot, hugging-face, retrieval-augmented-generation, vector-database; Also covers Vector Databases; - You need a ready-to-run solution that directly integrates with various data sources like Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and live APIs. ### When should I avoid langevals? Last GitHub push was 149 days ago (slowing maintenance, Feb 15, 2026). Validate activity before betting a new project on langevals. Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### When should I avoid llm-app? - You require custom deployment configurations that extend beyond the pre-set cloud templates available through llm-app. - There’s a need for tightly integrated support with data sources or APIs not explicitly mentioned, such as specialized CRM systems (Salesforce), which may lack direct template support in llm-app. ### Is langevals or llm-app more popular on GitHub? llm-app has more GitHub stars (59,068 vs 72). Stars measure visibility, not whether either tool fits your constraints. ### Are langevals and llm-app open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to langevals or llm-app? GraphCanon lists graph-backed alternatives at [langevals alternatives](/tools/langwatch-langevals/alternatives) and [llm-app alternatives](/tools/pathwaycom-llm-app/alternatives) ([langevals markdown twin](/tools/langwatch-langevals/alternatives.md), [llm-app markdown twin](/tools/pathwaycom-llm-app/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/langwatch-langevals-vs-pathwaycom-llm-app.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, langevals or llm-app? langevals: Slowing. llm-app: Very active. 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 langevals and llm-app? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [langevals trust report](/tools/langwatch-langevals/trust); [llm-app trust report](/tools/pathwaycom-llm-app/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=langwatch-langevals`](/api/graphcanon/graph?tool=langwatch-langevals) - 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/_