pengjunjie/langflow
1
0
Fork 1
mirror of https://github.com/langflow-ai/langflow.git synced 2026-07-23 19:24:11 +08:00
Code Issues Packages Projects Releases Wiki Activity

docs: llms.txt and llms-full.txt (#11786)

Browse Source 
* llms-txt

* add-llms-full-and-check-urls

* change-electron-to-tauri
This commit is contained in:
Mendon Kissling
2026-02-18 16:52:35 -05:00
committed by GitHub
parent f7743eb027
commit 63c19c314b
2 changed files with 109 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

74
docs/static/llms-full.txt vendored Normal file
View File

@ -0,0 +1,74 @@
# Langflow Documentation (full)
> Comprehensive guide for AI language models: Langflow documentation at docs.langflow.org. Covers the visual flow builder, API and webhook triggers, MCP, deployment, components, and API reference. Use this file for deeper context than llms.txt.
**Platform overview**
Official documentation for Langflow, a low-code platform for building and deploying AI-powered agents and workflows. Type: Technical Documentation – AI Development Platform. URL: https://docs.langflow.org. Category: Developer Documentation, AI/ML, Workflow Automation, RAG, MCP. Target: developers and teams adopting Langflow (OSS or Desktop) for AI applications.
**Technical specifications (Langflow product)**
Application type: Python web application (OSS); Tauri-based desktop (Langflow Desktop). Supported platforms: Windows, macOS, Linux. Minimum requirements: Windows 10 (64-bit), macOS 10.15 Catalina, Ubuntu 18.04 LTS or equivalent; 4GB RAM minimum (8GB recommended), 2GB storage, internet for model integrations; Python 3.10–3.13 for OSS. Architecture: modular component system. License: MIT. Runtime: Python 3.10–3.13 (OSS); Node.js and Python (Desktop). Package format: pip/uv (OSS), Docker image, native Desktop installers (.exe, .dmg, .deb/.rpm). Default URL: http://127.0.0.1:7860. Repository: https://github.com/langflow-ai/langflow.
**Core features (by doc section)**
Get Started: about, installation, quickstart, tutorials (RAG, files, agents, MCP). Flows: visual editor, build flows, API and webhook triggers, playground, import/export. Agents: agents and tools, MCP client/server/Astra. Develop: API keys, custom dependencies, config and globals, env vars, storage and memory, observability (LangSmith, LangFuse, etc.), data types, voice mode, CLI. Deploy: overview, public server, Nginx/SSL, Docker, Kubernetes, GCP/Hugging Face/Railway/Render, security. Components: concepts, core components, bundles (integrations), custom components. API Reference: get started, TypeScript client, flow/OpenAI/files/projects/logs/monitor/build/users endpoints, API spec. Contribute: community, how to contribute, components, bundles, tests, templates. Support: troubleshooting, get help, Luna/IBM, release notes.
**Page structure**
Get Started: about, install, quickstart, tutorials. Flows: visual editor, triggers, playground, import/export. Agents: agents, MCP. Develop: config, storage, observability, CLI. Deploy: overview, Docker, Kubernetes, cloud, security. Components: concepts, core, bundles, custom. API Reference: getting started, endpoints, spec. Contribute: community, contributing. Support: troubleshooting, help, release notes.
**Installation**
OSS: uv pip install langflow -U; uv run langflow run. Docker: docker run -p 7860:7860 langflowai/langflow:latest. From source: make run_cli. First use: UI at 127.0.0.1:7860, configure API keys, build or import flows, trigger via API or webhooks.
**Use cases**
RAG applications, multi-agent workflows, MCP servers and clients, API-backed AI services, document processing, custom components and bundles, deployment (Docker, Kubernetes, cloud). Target users: developers, data scientists, devops, contributors.
**Support**
Documentation sections: get started, flows, agents, develop, deploy, components, API, contribute, support. Community: Discord, GitHub discussions, YouTube, release notes. Technical: GitHub issues, troubleshooting docs, IBM Elite Support (Luna).
**Privacy & security**
Deployment security and API keys/auth documented at docs.langflow.org. Repository: SECURITY.md and GitHub security advisories. Data handling and env vars in Develop section.
**Performance**
Default port 7860; observability docs (LangSmith, LangFuse, etc.); deployment best practices for scaling.
**Documentation for AI agents**
Documentation URL: https://docs.langflow.org. llms.txt: https://docs.langflow.org/llms.txt. llms-full.txt: https://docs.langflow.org/llms-full.txt. Release notes: https://docs.langflow.org/release-notes.
**Roadmap**
Follow Langflow releases and GitHub for product direction; release notes at docs.
## Docs
- [About Langflow](https://docs.langflow.org/about-langflow): Platform overview and introduction
- [Install Langflow](https://docs.langflow.org/get-started-installation): Installation options (OSS, Docker, from source)
- [Quickstart](https://docs.langflow.org/get-started-quickstart): Get up and running quickly
- [Use the visual editor](https://docs.langflow.org/concepts-overview): Visual flow builder overview
- [Build flows](https://docs.langflow.org/concepts-flows): Concepts for building flows
- [Trigger flows with the API](https://docs.langflow.org/concepts-publish): Run flows via the Langflow API
- [Trigger flows with webhooks](https://docs.langflow.org/webhook): Webhook triggers
- [Test flows](https://docs.langflow.org/concepts-playground): Playground and testing
- [Import and export flows](https://docs.langflow.org/concepts-flows-import): Import/export
- [Agents](https://docs.langflow.org/agents): Agents and tools
- [MCP client](https://docs.langflow.org/mcp-client): Model Context Protocol client and server
- [API keys and authentication](https://docs.langflow.org/api-keys-and-authentication): Configure API keys and auth
- [Deployment overview](https://docs.langflow.org/deployment-overview): How to deploy Langflow
- [Docker deployment](https://docs.langflow.org/deployment-docker): Langflow Docker images
- [Security](https://docs.langflow.org/security): Deployment and security guidance
- [Components overview](https://docs.langflow.org/concepts-components): Component reference introduction
- [API reference – get started](https://docs.langflow.org/api-reference-api-examples): Get started with the Langflow API
- [Troubleshooting](https://docs.langflow.org/troubleshoot): Troubleshooting guide
- [Release notes](https://docs.langflow.org/release-notes): Version history and release notes
## Community
- [GitHub repository](https://github.com/langflow-ai/langflow): Source code and issues
- [Langflow website](https://langflow.org): Main product site
- [Langflow Desktop](https://langflow.org/desktop): Desktop app download
- [Discord](https://discord.com/invite/EqksyE2EX9): Community chat
- [Twitter/X](https://x.com/langflow_ai): Updates and news
- [YouTube](https://www.youtube.com/@Langflow): Tutorials and demos
- [GitHub Discussions](https://github.com/langflow-ai/langflow/discussions): Community discussions
## Optional
- [Contributing community](https://docs.langflow.org/contributing-community): Community guidelines
- [How to contribute](https://docs.langflow.org/contributing-how-to-contribute): Contribution guide
- [Get help and request enhancements](https://docs.langflow.org/contributing-github-issues): GitHub issues and help

35
docs/static/llms.txt vendored Normal file
View File

@ -0,0 +1,35 @@
# Langflow Documentation
> Official documentation for Langflow, a low-code platform for building and deploying AI-powered agents and workflows with a visual builder, API, and MCP server. Technical documentation for developers, data scientists, and teams building RAG and multi-agent applications.
Langflow is open source (MIT). Run locally with `uv run langflow run` (Python 3.10–3.13, default http://127.0.0.1:7860). Also available as Langflow Desktop (Windows, macOS). Key areas: get started (installation, quickstart, tutorials), flows (build, run via API or webhooks, test, import/export), agents and MCP, develop (config, storage, observability), deploy (Docker, Kubernetes, cloud), components reference, and API reference.
## Docs
- [About Langflow](https://docs.langflow.org/about-langflow): Platform overview and introduction
- [Install Langflow](https://docs.langflow.org/get-started-installation): Installation options (OSS, Docker, from source)
- [Quickstart](https://docs.langflow.org/get-started-quickstart): Get up and running quickly
- [Use the visual editor](https://docs.langflow.org/concepts-overview): Visual flow builder overview
- [Trigger flows with the API](https://docs.langflow.org/concepts-publish): Run flows via the Langflow API
- [Agents](https://docs.langflow.org/agents): Agents and tools
- [MCP client and server](https://docs.langflow.org/mcp-client): Model Context Protocol integration
- [Deployment overview](https://docs.langflow.org/deployment-overview): How to deploy Langflow
- [Security](https://docs.langflow.org/security): Deployment and security guidance
- [Release notes](https://docs.langflow.org/release-notes): Version history and release notes
## Community
- [GitHub repository](https://github.com/langflow-ai/langflow): Source code and issues
- [Langflow website](https://langflow.org): Main product site
- [Langflow Desktop](https://langflow.org/desktop): Desktop app download
- [Discord](https://discord.com/invite/EqksyE2EX9): Community chat
- [Twitter/X](https://x.com/langflow_ai): Updates and news
- [YouTube](https://www.youtube.com/@Langflow): Tutorials and demos
## Optional
- [Build flows](https://docs.langflow.org/concepts-flows): Concepts for building flows
- [Test flows](https://docs.langflow.org/concepts-playground): Playground and testing
- [Components overview](https://docs.langflow.org/concepts-components): Component reference introduction
- [API reference](https://docs.langflow.org/api-reference-api-examples): Get started with the Langflow API
- [Troubleshooting](https://docs.langflow.org/troubleshoot): Troubleshooting guide