1f1flowbase
Open source · Self-hosted · Observable

Conversation is the moat.The native foundation for AI apps.

Compose models, tools, and workflows into reusable AI capabilities, then publish them through one observable, OpenAI- and Claude-compatible runtime.

Works with the tools you already use

Claude CodeCodexOpenCodeClineContinue
OpenAI Responses
Chat Completions
Claude Messages
Tool callbacks
A concrete composition

Turn text models into one multimodal virtual model.

Keep each model focused on what it does best. 1flowbase connects perception, reasoning, and synthesis behind one endpoint while preserving the full execution trace.

  1. 01

    Input

    Text · image · files

    Accept a multimodal request through one compatible endpoint.

  2. 02

    Reasoning

    DeepSeek V4

    Plan the task, reason over evidence, and decide which capability to call.

  3. 03

    Synthesis

    GLM 5.2

    Review intermediate results and assemble the final response.

  4. 04

    Perception

    Vision + OCR tools

    Convert visual and document context into evidence text models can use.

PUBLISHED ASOne observable multimodal model endpoint
Compose, publish, observe

Build a better virtual model from the models you already trust.

1flowbase sits between agent clients and model providers. The client still calls one familiar model name while your workflow decides what happens behind it.

01

Compose text models into multimodal capability

Use DeepSeek V4 for reasoning, GLM 5.2 for synthesis, and visual tools for perception, then publish the whole workflow as one model.

DeepSeek V4 + GLM 5.2 + vision tools → multimodal model

02

Run a multi-model review panel

Fan out to several reviewers, preserve every branch, and synthesize one stronger answer behind a single model endpoint.

parallel reviewers → synthesis → final answer

03

Debug cost, latency, and failures

Inspect model calls, tool callbacks, tokens, duration, and errors as one connected execution trace instead of scattered logs.

request → trace → evidence → improvement

A small surface, a powerful runtime

Your agents see a normal model. You see the whole system.

Publish once and keep existing client integrations unchanged. 1flowbase handles orchestration, protocol compatibility, and observability behind the endpoint.

01

Agent client

Claude Code, Codex, OpenCode, SDKs

02

Virtual model API

OpenAI- and Claude-compatible endpoints

03

Workflow runtime

Models, branches, tools, and synthesis

04

Execution evidence

Traces, tokens, latency, cost, failures

Control without lock-in

Designed for local agents and real production debugging.

1flowbase / workflow-editor
1flowbase visual workflow editor showing a multi-model fusion workflow
01

Protocol compatible

Use the clients and SDKs you already have. Publish workflows through familiar OpenAI and Claude APIs.

02

Provider flexible

Mix OpenAI-compatible providers, Claude-compatible models, vision models, and private endpoints in one workflow.

03

Visual workflow editor

Make branching, tools, and synthesis explicit. Reuse a workflow instead of rebuilding orchestration in every client.

04

Trace every call

Connect the final answer to every model invocation, tool callback, token count, duration, and error.

05

Self-hosted by default

Keep model credentials and execution data under your control with a one-command Docker deployment.

06

Open extension surface

Build workflow nodes, model providers, tools, and frontstage experiences on an open-source base.

Evidence, not guesswork

See why an answer was slow, expensive, or wrong.

A final answer is only the last line of a workflow. 1flowbase keeps the path that produced it visible, so you can compare branches, inspect tool results, and improve the system with evidence.

  • Model and tool call timeline
  • Token, latency, and failure attribution
  • Inputs and outputs connected to workflow nodes
execution / trace-7b14● complete
1flowbase detailed execution logs with model and tool call traces
Run it on your own machine

From zero to a workflow endpoint with one command.

Deploy the full stack with Docker, open the visual editor, and publish your first virtual model.

Linux / macOSbash
curl -fsSL https://raw.githubusercontent.com/taichuy/1flowbase/main/scripts/shell/docker-deploy.sh | sh
Frequently asked

What developers usually want to know.

Is 1flowbase another LLM proxy?+

No. A proxy mainly selects or forwards to a model. 1flowbase composes models and tools into a workflow, publishes that workflow as a virtual model, and preserves the complete execution trace.

Do I need to change Claude Code or Codex?+

Usually no. If a client supports a custom OpenAI- or Claude-compatible endpoint, it can call a published 1flowbase workflow through the same model API shape it already understands.

Can I use local or private model providers?+

Yes. 1flowbase is designed for self-hosted deployments and provider-compatible endpoints, so credentials and traffic can remain in infrastructure you control.

How is this different from coding an agent graph?+

Agent frameworks help you write orchestration in code. 1flowbase gives that orchestration a visual editor, a reusable runtime, protocol publishing, and connected observability for local agent clients.

1f

Make every conversation compound into your AI application moat.

Start with the multimodal composition, adapt the workflow, and publish it as your own model endpoint.