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Zag Python Binding

Python binding for zag — a unified CLI for AI coding agents.

Prerequisites

  • Python 3.10+
  • The zag CLI binary installed and on your PATH (or set via ZAG_BIN env var)

Installation

pip install zag-agent

For development from source:

cd bindings/python
pip install -e .

Quick start

from zag import ZagBuilder

output = await ZagBuilder() \
    .provider("claude") \
    .model("sonnet") \
    .auto_approve() \
    .exec("write a hello world program")

print(output.result)

Streaming

from zag import ZagBuilder

async for event in await ZagBuilder().provider("claude").stream("analyze code"):
    print(event.type, event)

Builder methods

Method Description
.provider(name) Set provider: "claude", "codex", "gemini", "copilot", "ollama"
.model(name) Set model name or size alias ("small", "medium", "large")
.system_prompt(text) Set a system prompt
.root(path) Set the working directory
.auto_approve() Skip permission prompts
.add_dir(path) Add an additional directory (chainable)
.file(path) Attach a file to the prompt (chainable)
.env(key, value) Add an environment variable for the agent subprocess (chainable)
.json_mode() Request JSON output
.json_schema(schema) Validate output against a JSON schema (implies .json_mode())
.worktree(name=None) Run in an isolated git worktree
.sandbox(name=None) Run in a Docker sandbox
.session_id(uuid) Use a specific session ID
.output_format(fmt) Set output format ("text", "json", "json-pretty", "stream-json")
.input_format(fmt) Set input format ("text", "stream-json" — Claude only)
.replay_user_messages() Re-emit user messages on stdout (Claude only)
.include_partial_messages() Include partial message chunks (Claude only)
.max_turns(n) Set the maximum number of agentic turns
.timeout(duration) Set a timeout duration (e.g., "30s", "5m", "1h"). Kills the agent if exceeded.
.mcp_config(config) MCP server config: JSON string or file path (Claude only)
.show_usage() Show token usage statistics (JSON output mode)
.size(size) Set Ollama model parameter size (e.g., "2b", "9b", "35b")
.verbose() Enable verbose output
.quiet() Suppress non-essential output
.debug() Enable debug logging
.bin(path) Override the zag binary path

Provider support for streaming / MCP flags

Four builder methods that toggle streaming I/O details and per-invocation MCP configuration are only honored by the Claude provider. Passing them to any other provider is a no-op.

Method Claude Codex Gemini Copilot Ollama
.input_format() Yes No No No No
.replay_user_messages() Yes No No No No
.include_partial_messages() Yes No No No No
.mcp_config() Yes No No No No

.exec_streaming() is Claude-only and always sets -i stream-json, -o stream-json, and --replay-user-messages. By default it emits one assistant_message event per complete assistant turn — you get one event when the model finishes speaking, not a stream of token chunks. Call .include_partial_messages(True) to receive token-level partial assistant_message chunks instead. The default stays False so existing callers that render whole-turn bubbles are not broken.

At the end of every agent turn the session emits a turn_complete event carrying the provider's stop_reason (end_turn, tool_use, max_tokens, stop_sequence, or None), a zero-based monotonic turn_index, and the turn's usage. A per-turn result event fires immediately after. New code should key turn-boundary UI off turn_complete — it is the authoritative signal and carries richer metadata than result. result continues to fire per-turn for backward compatibility.

Terminal methods

Method Returns Description
.exec(prompt) AgentOutput Run non-interactively, return structured output
.stream(prompt) AsyncGenerator[Event] Stream NDJSON events
.exec_streaming(prompt) StreamingSession Bidirectional streaming (Claude only). Emits one assistant_message event per complete turn; pair with .include_partial_messages(True) for token-level chunks.
.run(prompt=None) None Start an interactive session (inherits stdio)
.resume(session_id) None Resume a previous session by ID
.continue_last() None Resume the most recent session
.exec_resume(session_id, prompt) AgentOutput Resume a session non-interactively with a follow-up prompt
.exec_continue(prompt) AgentOutput Resume the most recent session non-interactively
.stream_resume(session_id, prompt) AsyncGenerator[Event] Resume a session in streaming mode
.stream_continue(prompt) AsyncGenerator[Event] Resume the most recent session in streaming mode

Version checking

The SDK automatically checks the installed zag CLI version before running commands. If you use a builder method that requires a newer CLI version than what's installed, a clear error is raised:

env() requires zag CLI >= 0.6.0, but the installed version is 0.5.0.
Please update the zag binary.

The version is detected once (by running zag --version) and cached for the lifetime of the process.

Method Minimum CLI version
.env() 0.6.0
.mcp_config() 0.6.0

All other methods are available since the initial release (0.2.3).

Discovery

Standalone async functions for discovering available providers, models, and capabilities:

from zag import list_providers, get_capability, get_all_capabilities, resolve_model

providers = await list_providers()
cap = await get_capability("claude")
all_caps = await get_all_capabilities()
resolved = await resolve_model("claude", "small")  # ResolvedModel(input="small", resolved="haiku", is_alias=True)
Function Description
list_providers(bin=None) List available provider names
get_capability(provider, bin=None) Get capabilities for a provider
get_all_capabilities(bin=None) Get capabilities for all providers
resolve_model(provider, model, bin=None) Resolve a model alias

How it works

The SDK spawns the zag CLI as a subprocess (zag exec -o json or -o stream-json) and parses the JSON/NDJSON output into typed dataclasses. Zero external dependencies — only the Python standard library.

Testing

pip install pytest pytest-asyncio
pytest

See also

License

MIT

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