zeekay
81ce604aee
The fork's provider extras were pinned to a pre-1.0 langchain generation that can't coexist with lfx's langchain-core 1.x, so `uv sync` (and CI) couldn't resolve at all. Per the "route everything through hanzoai/ai" direction, the fix is to align/drop rather than resurrect the provider zoo: - langchain-openai >=1.1.12, langchain-anthropic >=1.0, pgvector >=0.4.2 (match lfx / cuga) - dropped langchain-cohere (no core-1.x release exists; cohere is reached via the hanzoai/ai gateway, not a direct langchain integration) - [tool.uv] environments pinned to linux (our deploy target; the macOS-only cuga/pgvector split is a separate dev-env concern) - renamed the stale SDK module dir langflow_sdk -> flow_sdk (the rebrand renamed the pyproject refs + the pytest11 entry point but missed the directory, so the `flow` test plugin failed to import) Verified: `uv sync` resolves + installs clean, and the IAM auth seam test now runs in the REAL full-app env — 7/7 pass (previously only verifiable via direct module load). This unblocks CI and all further flow work.
Hanzo Flow
Hanzo Flow is a powerful platform for building and deploying AI-powered agents and workflows. It provides developers with both a visual authoring experience and built-in API and MCP servers that turn every workflow into a tool that can be integrated into applications built on any framework or stack. Hanzo Flow comes with batteries included and supports all major LLMs, vector databases and a growing library of AI tools.
Highlight features
- Visual builder interface to quickly get started and iterate.
- Source code access lets you customize any component using Python.
- Interactive playground to immediately test and refine your flows with step-by-step control.
- Multi-agent orchestration with conversation management and retrieval.
- Deploy as an API or export as JSON for Python apps.
- Deploy as an MCP server and turn your flows into tools for MCP clients.
- Observability with LangSmith, LangFuse and other integrations.
- Enterprise-ready security and scalability.
Quickstart
Install locally (recommended)
Requires Python 3.10-3.13 and uv (recommended package manager).
Install
From a fresh directory, run:
uv pip install hanzoflow -U
Run
To start Hanzo Flow, run:
uv run hanzoflow run
Hanzo Flow starts at http://127.0.0.1:7860.
Other install options
Run from source
If you've cloned this repository and want to contribute, run this command from the repository root:
make run_cli
For more information, see DEVELOPMENT.md.
Docker
Start a Hanzo Flow container with default settings:
docker run -p 7860:7860 hanzoai/flow:latest
Hanzo Flow is available at http://localhost:7860/.
Deployment
Hanzo Flow is completely open source and you can deploy it to all major deployment clouds.
Contribute
We welcome contributions from developers of all levels. If you'd like to contribute, please check our contributing guidelines and help make Hanzo Flow more accessible.