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> **Give local AI agents one model endpoint that can run your own observable multi-model workflow behind the scenes.** Claude Code, Codex, OpenCode, Cline, Continue, and SDKs call one normal model name. 1flowbase can run a workflow behind that name: mount a vision model for screenshots, call several models as a Fusion-style review panel, verify or format the result, and show the full trace of model calls, tool callbacks, tokens, latency, and failures. ```text Agent client -> one virtual model endpoint -> your workflow -> trace / tokens / cost -> final answer ``` | If you need to... | 1flowbase helps you... | |---|---| | make a text coding model understand screenshots | mount GLM-5V-Turbo, Gemini, GPT vision, OCR, or another visual model as a tool | | run a Fusion-style model panel | fan out to several branch models, synthesize the result, and publish it as one endpoint | | debug why an agent answer was slow, expensive, or wrong | inspect workflow nodes, model calls, tool callbacks, token usage, latency, and errors | | reuse a better model chain from existing clients | publish the workflow as OpenAI-compatible or Claude-compatible model APIs |  --- ## What You Can Build ### Add vision to text-first coding models Keep GLM-5.2, DeepSeek, or another strong text coding model as the main planner, then let 1flowbase route screenshots, UI images, charts, and PDF pages to a mounted vision model. ```text Claude Code -> 1flowbase virtual model endpoint -> GLM-5.2 / DeepSeek / other main coding model -> mounted vision tool -> GLM-5V-Turbo / Gemini / GPT vision / OCR model -> structured visual result -> final coding answer ``` Guide: [Make GLM-5.2 See Images in Claude Code with 1flowbase](https://github.com/taichuy/1flowbase/wiki/Make-GLM-5.2-See-Images-in-Claude-Code-with-1flowbase) ### Publish a Fusion-style multi-model reviewer 1flowbase includes a `fusion` template. Your client calls one model name; 1flowbase asks several branch models, runs a synthesis model, returns the final answer, and keeps every branch visible. ```text User request -> Main LLM -> fusion tool -> Branch LLM A -> Branch LLM B -> Branch LLM C -> Synthesis LLM -> final answer ``` Guide: [Fusion-Style Workflows: Publish a Multi-Model Panel as an Observable Virtual Model](https://github.com/taichuy/1flowbase/wiki/Fusion-Style-Workflow) ### Publish workflow-backed model APIs Build the workflow once, then expose it through common model APIs: | Protocol | API path | Typical usage | |---|---:|---| | OpenAI Responses API | `/v1/responses` | newer OpenAI-style clients and application code | | OpenAI Chat Completions API | `/v1/chat/completions` | SDKs, coding tools, chat clients, application frameworks | | Claude-compatible Messages API | `/v1/messages` | Claude-compatible clients that support custom endpoints | --- ## Installation or Upgrade Linux/macOS: ```bash curl -fsSL https://raw.githubusercontent.com/taichuy/1flowbase/main/scripts/shell/docker-deploy.sh | sh ``` Windows PowerShell: ```powershell irm https://raw.githubusercontent.com/taichuy/1flowbase/main/scripts/powershell/docker-deploy.ps1 | iex ``` Windows CMD: ```cmd powershell -NoProfile -ExecutionPolicy Bypass -Command "irm https://raw.githubusercontent.com/taichuy/1flowbase/main/scripts/powershell/docker-deploy.ps1 | iex" ``` --- ## Run From Source Use this path when you want to develop 1flowbase itself. Requirements: Node.js `>= 24.0.0`, pnpm, latest stable Rust, and Docker for local middleware. ```bash git clone https://github.com/taichuy/1flowbase.git cd 1flowbase docker compose -f docker/docker-compose.middleware.yaml up -d cd web pnpm install pnpm dev ``` Frontend: ```text http://127.0.0.1:3100 ``` Start backend services: ```bash cd api # Copy api/apps/api-server/.env.example to .env before the first run. cargo run -p api-server --bin api-server cargo run -p plugin-runner --bin plugin-runner ``` Default backend endpoints: ```text API Server: http://127.0.0.1:7800 Plugin Runner: http://127.0.0.1:7801 ``` Script-assisted startup: ```bash node scripts/node/dev-up.js node scripts/node/dev-up.js status node scripts/node/dev-up.js stop node scripts/node/dev-up.js restart ``` See [scripts/README.md](scripts/README.md) for more options. --- ## Where 1flowbase Fits 1flowbase is not just a model proxy and not just a generic workflow canvas. | Tool category | What it usually does | How 1flowbase is different | |---|---|---| | LLM gateway / model router | routes one request to one provider or model | composes multiple model and tool nodes into one workflow-backed virtual model | | AI workflow builder | builds an AI app or workflow | exposes the workflow as OpenAI / Claude-compatible model APIs | | Agent framework | helps developers code agent graphs | provides a visual runtime, protocol publishing, and execution logs | | Observability / cost tracker | shows token or spend totals | connects cost to workflow nodes, model calls, tool callbacks, and trace logs | ```text Model routers choose a model. 1flowbase builds a new virtual model from a workflow. ``` --- ## Feature Preview ### Publish as OpenAI-compatible API  ### Publish as Claude-compatible Messages API  ### Customize exposed model information  ### Use in local AI agent clients Call a published workflow from compatible clients that support custom model endpoints.  ### Inspect execution logs Trace model requests, node inputs and outputs, tool callbacks, response content, latency, and errors.  ### View tool callback traces  ### Track token consumption  --- ## Common Use Cases ### Make a text coding model understand screenshots ```text Screenshot / UI mockup / chart -> vision tool -> structured visual context -> strong coding model -> patch, plan, or explanation ``` Useful for UI reconstruction, frontend debugging, visual regression analysis, chart reading, PDF page understanding, and design-to-code workflows. ### Build a Fusion-style reviewer ```text Architecture proposal -> cheap broad reviewer -> strong reasoning reviewer -> provider-diverse reviewer -> synthesis model -> final recommendation ``` Useful for architecture review, research synthesis, code review, document review, and high-stakes agent decisions. ### Control cost with model cascading ```text Simple classification -> small model Formatting -> small model Complex reasoning -> strong model Final verification -> verifier node ``` ### Guarantee output structure Use verifiers, JSON Schema validation, and formatter nodes before returning the final result. This is useful for JSON outputs, API responses, tool call parameters, code patches, document generation, and automated task results. ### Build a programmable upstream model for agents ```text Code generation -> test / lint check -> reviewer node -> fix node -> final patch ``` The client calls one model name while 1flowbase runs your workflow behind it. --- ## Current Status ### Implemented - [x] visual workflow editor - [x] multi-node workflow orchestration - [x] virtual model endpoint publishing - [x] OpenAI Responses protocol support - [x] OpenAI Chat Completions protocol support - [x] Claude-compatible Messages protocol support - [x] streaming response support - [x] mounted LLM tools for multimodal and branch-model workflows - [x] `fusion` workflow template - [x] execution logs - [x] tool callback traces inside 1flowbase workflows - [x] application-level token consumption statistics - [x] prompt and model configuration version history ### Enhancing - [ ] deeper local agent conversation collection - [ ] session search and playback - [ ] Token Bill of Materials by prompt, history, tool definitions, command outputs, media inputs, and nodes - [ ] abnormal cost detection and optimization suggestions - [ ] session export and Recall Pack generation - [ ] more Claude Code / Codex / OpenCode / Cline / Continue templates - [ ] MCP-aware plugin nodes and tool-call source attribution ### Planned - [ ] low-code application building platform for AI organizations - [ ] team workspace and multi-tenant management - [ ] permissions, approval, audit, and cost governance - [ ] support for more local AI agent clients - [ ] template market and workflow recipe ecosystem > Note: 1flowbase is not currently positioned as an MCP server or MCP gateway. MCP-aware capabilities are on the roadmap. The current product focuses on publishing compatible model endpoints and tracing 1flowbase workflow execution. --- ## Transparency and Security 1flowbase is designed for transparent, self-hosted AI workflow execution. Recommended principles: - self-hosted first - transparent model chains - auditable node calls - traceable token usage - configurable log retention - sensitive data masking - explicit model and workflow configuration 1flowbase does not advocate stealthy model replacement. Published endpoints should be configured intentionally, observed clearly, and governed by the project owner. --- ## Guides - [Make GLM-5.2 See Images in Claude Code with 1flowbase](https://github.com/taichuy/1flowbase/wiki/Make-GLM-5.2-See-Images-in-Claude-Code-with-1flowbase) - [Fusion-Style Workflows: Publish a Multi-Model Panel as an Observable Virtual Model](https://github.com/taichuy/1flowbase/wiki/Fusion-Style-Workflow) - [1flowbase Wiki](https://github.com/taichuy/1flowbase/wiki) --- ## Repo Layout ```text web/ Frontend root, powered by pnpm + Turbo api/ Rust backend workspace api/apps/ Backend service entry points api/crates/ Shared backend crates api/plugins/ Plugin workspace, HostExtension manifests, and templates docker/ Local middleware orchestration and self-hosted stack scripts/ Development, testing, verification, and debugging scripts ``` --- ## Contributing Contributions are welcome. Before submitting a pull request, run: ```bash node scripts/node/verify.js repo ``` Project guidelines: - [AGENTS.md](AGENTS.md) - [web/AGENTS.md](web/AGENTS.md) - [api/AGENTS.md](api/AGENTS.md) --- ## Friend Links - [Linux.do](https://linux.do/) - Learn AI, on L Station. - [Aionui](https://github.com/iOfficeAI/AionUi) - Remotely control AI to work via mobile phone. - [OfficeCLI](https://github.com/iOfficeAI/OfficeCLI) - Office suite designed for AI agents. - [deepseek-pp](https://github.com/zhu1090093659/deepseek-pp) - DeepSeek web chat browser extension. - [MuseAI](https://github.com/yejiming/MuseAI) - Local AI companion, text adventure, and story immersion app. - [FrontAgent](https://github.com/FrontAgent/FrontAgent) - AI Agent system designed specifically for front-end engineering. - [RedBox](https://github.com/Jamailar/RedBox) - Localized AI creative workbench for Xiaohongshu creators. --- ## OpenAI Build Week ### Built with Codex and GPT-5.6 Codex was used to: - redesign MCP configuration workflows - implement and review Rust backend changes - improve React components - debug integration issues GPT-5.6 was used for: - designing agent workflows - validating MCP capability patterns - improving architecture decisions ## License This project is licensed under [Apache-2.0](LICENSE). --- ## Contributors