Langflow vs txtai
Langflow
langflow.orgtxtai
neuml.github.ioSide by side
| Figure | Langflow | txtai |
|---|---|---|
| Price from | — | Free |
| Free plan | — | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | — |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 0 | 1 |
| Spec score · LLM Application Development Frameworks | 7.6 (#11) | 8.3 (#6) |
| Spec score · Retrieval-Augmented Generation Tools | 7.5 (#20) | 8.3 (#9) |
| Integrations | The homepage lists integrations including Anthropic, Azure, OpenAI, Hugging Face, Ollama, Qdrant, Pinecone, Slack, and Google Drive. | The documentation describes agent support for Hugging Face and llama.cpp models, and OpenAI, Claude, and AWS Bedrock through LiteLLM. |
| Purpose | Langflow is an open-source, Python-based framework for building customizable AI applications, including agent and MCP applications. | txtai is an all-in-one AI framework for semantic search, LLM orchestration, and language model workflows. |
| Security | Langflow can execute developer-provided Python with access to the host backend, filesystem, and network, and it does not enforce user isolation within a single process. | The API is open over HTTP by default; the documentation describes HTTPS options, API-token authorization, and a safeopen option enabled by default for API and application runs. |
| Support | The official site links to community help on Discord, professional services, and Premier Support. | 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.