LLMStack vs LMQL
Side-by-side comparison · Updated September 2026
| Description | LLMStack is a source-available builder for AI agents, workflows and chatbots that combine model calls with your own data. Its visual builder can chain multiple models and connect data sources, making it more suitable for assembling an application or process than for simply opening a personal chat app. The project documents deployment on your own infrastructure and points to Promptly as its hosted offering. Supported data inputs include documents, websites and connected sources such as Google Drive and Notion. The builder provides preprocessing and vectorization for retrieval workflows. Apps can be shared publicly or with selected people, and viewer and collaborator permissions control access to shared work. The repository also documents HTTP API access and Slack or Discord triggers. Plan for infrastructure, model-provider usage, credentials and permissions as separate decisions. Installing a self-hosted builder does not make externally hosted models free or keep every data request local. Start with a limited workflow and representative documents, review the generated output, and confirm the permissions required by each connected source before expanding access. Compare AnythingLLM when a document-chat workspace is the main need; LLMStack is oriented toward composing the application and its workflow. | LMQL is a programming language tailored for large language models (LLMs). It offers robust and modular LLM prompting through the use of types, templates, constraints, and an optimizing runtime. It simplifies the creation of complex prompts by allowing procedural programming techniques in a query-like syntax. Created by the SRI Lab at ETH Zurich, LMQL supports features such as nested queries, scripted prompting, and custom constraints. It also provides a Playground IDE for ease of use. |
| Category | AI Assistant | Other |
| Rating | No reviews | No reviews |
| Pricing | Unknown | Pricing unavailable |
| Starting Price | N/A | N/A |
| Plans |
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| Tags | Open sourceAI agentsWorkflowsApplicationsData | programming languagelarge language modelstypestemplatesconstraints |
| Features | ||
| Visual AI workflow and model-chain builder | ||
| Data imports from documents, websites and connected services | ||
| Document preprocessing and vectorization | ||
| Viewer and collaborator permissions | ||
| Self-hosted deployment instructions | ||
| Hosted offering through Promptly | ||
| HTTP API access for apps and chatbots | ||
| Slack and Discord workflow triggers | ||
| Nested Queries | ||
| Scripted Prompting | ||
| Custom Constraints | ||
| Optimizing Runtime | ||
| Playground IDE | ||
| Local Model Support | ||
| Tool Augmentation | ||
| High-level Constraint Management | ||
| Sequential Query Execution | ||
| Integration with Popular Libraries | ||
| View LLMStack | View LMQL | |
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