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h5i-python
Python SDK for Programmable Multi-Agent Orchestration
Multi-agent coding is more than launching agents or letting them chat. h5i-python lets you program the full development process in Python: Claude Code, Codex, and other runtimes can implement independently, review one another, revise, run neutral tests, compete, and safely apply the winner. Each agent works in an isolated Git worktree, making every run reproducible and auditable. Open source, with 40 multi-agent LLM paper workflows included.
Claude Code, Codex, and other coding agents have different strengths. However, naive multi-agent orchestration such as simply launching several agents in parallel or allowing them to exchange messages does not define a reproducible development process. A real workflow must specify:
who implements;
who reviews whom;
when an agent must revise its work;
which candidates are independently tested;
how the winner is selected; and
when the selected change is applied to the original branch.
h5i-python is the Python SDK for the h5i orchestra engine. This SDK lets you define and execute multi-agent coding workflows across Claude Code, Codex, and other runtimes as ordinary Python programs.
Each agent works inside its own sandboxed Git worktree, so it cannot overwrite the original checkout or another agent's work. Agent turns produce Git-backed artifacts that can be reviewed, revised, neutrally verified, compared, selected, and applied as one auditable workflow.
Install
pip install h5i-orchestra
Quickstart
Create ensemble.py inside the Git repository the agents should modify. This workflow let Claude and Codex independently implement the same task, review and improve each other’s work, and then select the better result.
from h5i.orchestra import Conductor
async def main(task):
async with Conductor(repo=".", run="demo-task", launcher="resident") as c:
claude = await c.hire("claude-agent", runtime="claude")
codex = await c.hire("codex-agent", runtime="codex")
# Have both agents implement the task independently and in parallel
claude_work, codex_work = await asyncio.gather(claude.work(task), codex.work(task))
await c.freeze() # Seal the round, ensuring that neither agent influenced the other beforehand
# Have each agent review the other's work
await asyncio.gather(codex.review(claude_work), claude.review(codex_work))
# Verify each submission in a fresh, neutral sandbox
await c.verify(claude_work, ["pytest", "--quiet"])
await c.verify(codex_work, ["pytest", "--quiet"])
verdict = await c.judge() # Select the smallest diff among the submissions that pass all tests
print("winner:", verdict.selected_submission)
asyncio.run(main("implement quicksort in python with unit test"))
Run it as a normal Python program:
python ensemble.py
With the default launcher="resident", h5i automatically starts the agent sessions through tmux.
About h5i-python on Product Hunt
“Python SDK for Programmable Multi-Agent Orchestration”
h5i-python was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #124 on the daily leaderboard. Multi-agent coding is more than launching agents or letting them chat. h5i-python lets you program the full development process in Python: Claude Code, Codex, and other runtimes can implement independently, review one another, revise, run neutral tests, compete, and safely apply the winner. Each agent works in an isolated Git worktree, making every run reproducible and auditable. Open source, with 40 multi-agent LLM paper workflows included.
On the analytics side, h5i-python competes within Open Source, Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how h5i-python performed against the three products that launched closest to it on the same day.
Who hunted h5i-python?
h5i-python was hunted by Koukyosyumei. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of h5i-python including community comment highlights and product details, visit the product overview.
Koukyosyumei
Claude Code, Codex, and other coding agents have different strengths. However, naive multi-agent orchestration such as simply launching several agents in parallel or allowing them to exchange messages does not define a reproducible development process. A real workflow must specify:
who implements;
who reviews whom;
when an agent must revise its work;
which candidates are independently tested;
how the winner is selected; and
when the selected change is applied to the original branch.
h5i-python is the Python SDK for the h5i orchestra engine. This SDK lets you define and execute multi-agent coding workflows across Claude Code, Codex, and other runtimes as ordinary Python programs.
Each agent works inside its own sandboxed Git worktree, so it cannot overwrite the original checkout or another agent's work. Agent turns produce Git-backed artifacts that can be reviewed, revised, neutrally verified, compared, selected, and applied as one auditable workflow.
Install
Quickstart
Create ensemble.py inside the Git repository the agents should modify. This workflow let Claude and Codex independently implement the same task, review and improve each other’s work, and then select the better result.
Run it as a normal Python program:
With the default launcher="resident", h5i automatically starts the agent sessions through tmux.