pi-python
zycode is an open-source coding agent for your terminal and your editor. It is built from this repository: the ACP agent pi-agent-cli-lc and the terminal UI zypi. Website: zycode.dev (中文).
Unofficial project: this repository is not affiliated with, endorsed by, or maintained by the official pi project or its maintainers.
Python port of pi-agent-core from the pi project, with LangChain replacing pi-ai for LLM calls.
The loop semantics, event protocol, and tool execution are faithful ports of pi; LangChain is only a StreamFn boundary adapter — never a replacement for the agent loop.
This repository is a monorepo containing:
Python packages (PyPI):
pi-agent-core-lc / pi_agent_core: lightweight core loop, messages, tools, adapters.pi-agent-harness-lc / pi_agent_harness: harness runtime, sessions, queues, hooks, compaction, skills/templates, and local execution env.pi-agent-cli-lc / pi_agent_cli: standard ACP coding agent (python -m pi_agent_cli, headless -p).pi-web-access-py / pi_web_access: web search and URL fetch extension.pi-goal-x-py / pi_goal_x: goal-planning extension.pi-dynamic-workflows-py / pi_dynamic_workflows: workflow orchestration extension.pi-mcp-py / pi_mcp: optional extension that connects the MCP servers an ACP client (an editor) passes (see packages/pi-mcp).
Rust TUI (beta — prebuilt binary in GitHub Releases):
zypi: full-screen terminal UI for interactive coding-agent sessions. Vendored fork of grok-build (Apache-2.0), with all x.ai/* vendor extensions removed. It offers three permission modes (Shift+Tab): Normal (ask, the start mode), Auto and Always-Approve. See TUI & Code-Agent Guide for details.
Status
| Component | Status | Distribution |
|---|
pi-agent-core-lc | Stable | PyPI |
pi-agent-harness-lc | Stable | PyPI |
pi-agent-cli-lc | Beta | PyPI |
pi-web-access-py | Beta | PyPI |
pi-goal-x-py | Beta | PyPI |
pi-dynamic-workflows-py | Beta | PyPI |
pi-mcp-py | Alpha | PyPI (from 0.6.0) |
zypi (Rust TUI) | Beta | GitHub Releases (Linux x86_64) |
zycode.zycode (VS Code extension) | Beta | VS Code Marketplace and Open VSX (five platforms; the project owner tested the install of 1.0.0 and the update from 0.1.0 to 1.0.0 on Windows on 2026-11-12; the rest of the Windows flow, macOS and Linux in a real VS Code are not verified) |
Features
Core runtime (Phase 1)
Agent — stateful agent with steering / follow-up queues, abort, subscribe() event barrieragent_loop — tool execution loop with pi-compatible event protocol (parallel/sequential tools, terminate semantics, should_stop_after_turn, prepare_next_turn)- LangChain
StreamFn adapter (langchain_stream) for OpenAI / Anthropic / DeepSeek-style / any init_chat_model provider
- Mock stream for tests — the whole suite runs without API keys
Production hardening (Phase 2 / 2.5)
- Cross-provider message replay (
transform_messages: tool-call id normalization, thinking downgrade, image stripping)
- Usage & cost tracking (accumulated across stream chunks, correct for all three real-world reporting shapes) +
CostCalculator
- Thinking/reasoning: provider param mapping (
reasoning_effort / Anthropic thinking budgets), streamed thinking_delta events, Anthropic signature replay, DeepSeek-style reasoning_content
- Stream-level retries before the first token (exponential backoff + jitter,
Retry-After aware)
- Runaway protection:
max_turns (raises MaxTurnsExceededError) and per-tool tool_timeout
- Guardrail hooks:
before_llm_call (with a ContextBudget token signal — the compaction hook point), after_llm_call (tripwire on raise), on_agent_end
- Observability:
on_payload / on_response hooks; every event carries run_id / turn_id
- Granular stream events:
text_start/end, thinking_start/end, toolcall_start/end (plus deltas)
- Structured output:
response_schema (pydantic model or JSON schema) → parsed AssistantMessage.structured_output
- Tool-result images: Anthropic native blocks, user-message fallback elsewhere, stripped when
supports_images=False
- OpenAI-compatible gateways via
Model.base_url (SiliconFlow, vLLM, DeepSeek, ...)
Tool ecosystem (Phase 3.5)
여기까지가 README 앞부분입니다. 나머지는 원문에서 읽을 수 있습니다. README 전문 보기 ↗
