banzhuan 0.2.0

Python SDK for BanZhuan.AI Builder, research, backtests, and strategy management.

banzhuan

Python SDK for BanZhuan.AI Builder, AI Chat, backtests, research, drafts, and strategy publishing on:

• https://hype.banzhuan.ai (Hyperliquid perps)
• https://edge.banzhuan.ai (EdgeX perps)
• https://poly.banzhuan.ai (Polymarket prediction markets)
• https://afp.banzhuan.ai (Autonity AFP)

This package is designed for automation and agent workflows. It uses the same production session token model as the website.

Installation

pip install banzhuan

Authentication

1. Open https://banzhuan.ai/credits
2. Connect your wallet and sign in
3. Copy your session token from the "Session Token (CLI)" card
4. Pass that token to the SDK or store it with the CLI

The package does not perform wallet signing. It assumes you already have a valid session token.

banzhuan auth set <your-session-token>

Or use an environment variable:

export BANZHUAN_SESSION_TOKEN=<your-session-token>

Quick Start

from banzhuan import BanzhuanClient, build_perps_risk_config

# exchange can be "hype", "edge", "poly", or "afp"
client = BanzhuanClient(exchange="hype", session_token="your-session-token")

reply = client.builder_chat(
    "Build a trend-following strategy for ETH-USD with a stop loss and cooldown",
    current_graph=None,
    conversation_history=[],
    async_mode=True,
    builder_run_config={
        "market": "ETH-USD",
        "lookbackDays": 14,
        "initialCapital": 10_000,
    },
)

job = client.wait_for_builder_job(reply["jobId"])
result = job["result"]
graph = client.apply_builder_result(None, result)

backtest = client.create_backtest(
    strategy_graph=graph,
    start_ms=client.days_ago_ms(14),
    end_ms=client.now_ms(),
    initial_capital=10_000,
    risk_config=build_perps_risk_config(10_000, "ETH-USD"),
)

final_backtest = client.wait_for_backtest(backtest["jobId"], include="result")
print(final_backtest["result"]["summary"])

What The SDK Covers

• Builder AI chat: POST /builder-chat
• Builder async job polling: GET /builder-chat/jobs/:jobId
• Chat session persistence: POST/GET/DELETE /builder-chat/sessions
• Strategy drafts: POST/GET/DELETE /strategies/drafts
• Strategy publishing and versioning: POST /strategies, POST /strategies/:id/versions
• Backtests: POST /backtests, GET /backtests/:id, GET /backtests
• Factor-ledger research:
  • POST /research/factors/generate-preview
  • POST /research/factors
  • POST /research/factors/evaluate
  • POST /research/factors/evaluate-all
  • GET /research/jobs/:jobId
  • GET /research/:id
• Market insights: GET /market-insights, POST /market-insights/generate

Builder Graphs

Builder AI chat returns command deltas, not a fully materialized graph. This package includes a Python port of the production graph mutation logic so you can:

• send a prompt
• receive Builder commands
• apply them locally
• save the graph
• backtest or publish the graph later

CLI

The CLI is intentionally small and focused on session-token workflows.

Save a session token

banzhuan auth set <your-session-token>

Run a Builder prompt against a graph file

banzhuan builder-chat \
  --exchange hype \
  --message "Create a funding mean-reversion strategy for HYPE-USD" \
  --graph-out graph.json

Backtest a graph file

banzhuan backtest \
  --exchange hype \
  --graph graph.json \
  --market HYPE-USD \
  --days 14 \
  --capital 10000 \
  --out backtest.json

Publish a Builder graph

banzhuan publish \
  --exchange hype \
  --graph graph.json \
  --name "ETH Trend" \
  --market ETH-USD \
  --visibility private

Notes

• A valid session token authenticates you as the wallet that created it.
• Credits and invite-key checks still apply on production endpoints.
• Research uses the current factor-ledger workflow. The legacy sweep-style /research/run path is not used.
• Builder AI Chat (builder_chat(), wait_for_builder_job(), apply_builder_result()) works across all four exchanges.
• Backtest and strategy publishing methods use perps-specific formats on HYPE/EDGE. For POLY and AFP, use the Python API with exchange-specific payloads or the web UI.
• Live session deployment can still be completed in the web app.

License

MIT