AgentFlux README

The project's README from github.com/davemessew/AgentFlux. As one markdown file: README.md.

AgentFlux

AgentFlux

Your data. Your models. Your workflows.

Agentic AI platform for visual workflows and autonomous agents.
Import files, automate tasks and keep results local.

Release Docker License

Download the Docker release · Website · Documentation · Report an issue


AgentFlux overview with workflows, data sources and getting started

What you can do

AgentFlux connects documents, data sources and language models in a visual workflow. Build each step yourself or let an agent create a workflow from a task description. The application runs on your computer or server, with a browser interface.

In AgentFlux
Visual workflows 17 preconfigured steps, eight templates, branching, undo/redo and JSON import/export.
AI agents Describe tasks, select sources and a model, then start manually or set a schedule.
Video to workflow Identify actions in a recording, review them with timestamps and turn them into an editable workflow.
Knowledge and learnings Store documents locally, review observations from runs and reuse instructions as skills.
Your own models Connect Ollama, LM Studio, vLLM and OpenAI-compatible endpoints.
Files and connections Import PDF, DOCX, XLSX, CSV, JSON and text; connect folders, HTTP endpoints and approved programs.
Traceable runs Inspect steps and results, cancel running tasks and export results as JSON or CSV.

Create a workflow from a video

Open Agents → Analyse video, select a recording and a model connection with vision support. If details are missing or a step is unclear, the agent asks short questions. Reply in text and it continues the analysis using your answers. Once the workflow is fully mapped, you can review the steps with timestamps. Choose Open in editor to save and run the workflow.

The recording stays in your browser. Up to 24 evenly spaced JPEG frames are sent to the selected model server for analysis. Audio is not analysed, and brief actions between frames may be missed. Videos up to 250 MB and 30 minutes are supported if your browser can read the codec. Cloud models require explicit permission to receive unredacted images.

Generated workflows contain only executable steps for existing connections. The analysis does not control other desktop applications. If a suitable connection is missing, the agent asks about the target and an available alternative. Video analysis is included in the current source code; the prebuilt v0.2.0 Docker image does not include it yet. Use a build from source for this feature.

Get started with Docker in minutes

You need Docker with Compose. The release includes the application, built interface and Node.js. You do not need to install Node or pnpm locally.

Use the prebuilt image

Download these two files from release v0.2.0 into the same folder:

Open a terminal in that folder:

docker load -i agentflux-0.2.0-linux-amd64.tar.gz
docker compose up -d --wait

Open localhost:4310. Done.

The prebuilt image targets Linux/amd64. On Windows, use Docker Desktop in Linux container mode. You can build from source for other architectures; they were not tested for this release.

Download from the terminal 
mkdir agentflux
cd agentflux
curl -fLO https://github.com/davemessew/AgentFlux/releases/download/v0.2.0/agentflux-0.2.0-linux-amd64.tar.gz
curl -fLO https://github.com/davemessew/AgentFlux/releases/download/v0.2.0/compose.yaml
docker load -i agentflux-0.2.0-linux-amd64.tar.gz
docker compose up -d --wait

In Windows PowerShell, use curl.exe instead of curl if needed. Checksums and full instructions are also included in the release.

Prefer to build from source? 
git clone https://github.com/davemessew/AgentFlux.git
cd AgentFlux
docker compose up --build -d --wait

Installation without Docker is also documented.

A look inside

The screenshots show the current source version. The published v0.2.0 Docker release still uses the green colour scheme; the new design is included when you build from source.

Build workflows on the canvas

Connect sources and processing steps, configure each step and follow its execution.

Visual workflow editor with connected steps

Agents
Tasks, models and recurring jobs in one place.		 Knowledge base
Search documents and processed content locally.
Manage agents in AgentFlux Local knowledge base with sample documents

Your first workflow

  1. Open Templates and choose Clean and save data. This template uses synthetic sample data and does not need an AI model.
  2. Start the workflow and open its run results.
  3. Connect your model server under Models to summarise documents or use agents.
  4. Create a task under Agents and select the allowed sources and model.

The Docker image does not include a model. Use an existing local server or an external provider with your own credentials.

Model server on your computer Base URL from the container
Ollama http://host.docker.internal:11434
LM Studio / OpenAI-compatible http://host.docker.internal:1234/v1
vLLM http://host.docker.internal:8000/v1

Adjust the port and model ID for your server. The model server must accept connections from the container.

Operations and data

docker compose ps            # Status and healthcheck
docker compose logs -f       # View server output
docker compose stop          # Stop
docker compose up -d --wait  # Start again

Workflows, documents, credentials and run logs stay in the named agentflux-data volume. Replacing the container does not delete them. Back up the entire volume including .vault-key; docker compose down -v deletes the volume.

[!IMPORTANT] The supplied configuration binds port 4310 to localhost. AgentFlux has no login and is designed for a single user. Shared or public access requires an access-control layer and suitable network configuration.

Cloud model calls and external HTTP POST steps require approval in Settings and in the workflow. HTTP GET requests can send information in URLs and headers. Optional redaction uses rules and may miss sensitive information. See the installation guide and operations guide.

Documentation and development

Start here Contents
Docker release Prebuilt image, Compose file, source code and SHA-256 checksums
Install the release Download, verify, start and update
Installation and models Docker, native installation and model connections
Workflows and agents Editor, steps, templates, learnings and skills
Operations and configuration Environment variables, import folders, backups and programs 
src/          Web interface and visual editor
server/       API, agents, execution and SQLite storage
shared/       Workflow rules and templates
examples/     Sample local program export
scripts/      Docker release checks
docs/         Usage, operations and screenshots

For local development: Node.js 24+, pnpm 11.25.0, pnpm install --frozen-lockfile, then pnpm dev.

Run the Docker check after building:

docker build -t agentflux:0.2.0 .
node scripts/smoke-docker.mjs agentflux:0.2.0

The check uses its own container and volume. It covers the API, built interface, an example run and data persistence when replacing the container.

Licence

Apache License 2.0. Bundled dependencies and fonts retain their respective licences.


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