DSPy vs txtai
DSPy
dspy.aitxtai
neuml.github.ioSide by side
| Figure | DSPy | txtai |
|---|---|---|
| Price from | — | Free |
| Free plan | — | Yes |
| Free trial | — | — |
| Open source | — | — |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 0 | 1 |
| Spec score · LLM Application Development Frameworks | 7.6 (#10) | 8.3 (#6) |
| Deployment | The documentation describes deploying DSPy programs with FastAPI or MLflow. | txtai API instances and workflows can run locally, on a server, on a cluster, or serverless; documented serverless options include AWS Lambda, Google Cloud Functions, Azure Cloud Functions, and Kubernetes with Knative. |
| Integrations | DSPy uses LiteLLM to normalize inference providers and says it can connect to nearly any model and provider supported by LiteLLM. | The documentation describes agent support for Hugging Face and llama.cpp models, and OpenAI, Claude, and AWS Bedrock through LiteLLM. |
| License | The project is listed as MIT licensed. | txtai is open-source under the Apache 2.0 license. |
| Support | The site links to a DSPy Discord community and GitHub repository. | NeuML offers implementation guidance, development support, and AI consulting, with meetings or email as contact options. |
Plans
In their own words
txtai
txtai is an open-source framework for semantic search, language-model orchestration, and language-model workflows. Its embeddings database brings together sparse and dense vector indexes, graph networks, and relational databases. It supports vector search with SQL, object storage, topic modeling, graph analysis, and multimodal indexing, and can create embeddings from text, documents, audio, images, and video. Pipelines cover prompts, question answering, labeling, transcription, translation, and summarization; workflows combine pipelines with business logic, while agents can coordinate embeddings, pipelines, workflows, and other agents. Web and Model Context Protocol APIs are available, alongside JavaScript, Java, Rust, and Go bindings. txtai can run locally or be deployed on a server, cluster, or serverless environment. Install with pip or use Docker; Python 3.11 or later is supported. The software is free under the Apache 2.0 license. The API is open over HTTP by default, with HTTPS and token authorization options documented.