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132 lines
5.3 KiB
Python
132 lines
5.3 KiB
Python
"""Pi coding-task tool: hand a coding task to the Pi agent so it implements the change.
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Package layout (separation of concerns):
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- ``errors.py`` — :class:`PiCodingError` + stable ``error_kind`` constants.
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- ``validation.py`` — argument validators + :class:`ResolvedRequest` resolution.
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- ``runner.py`` — lifecycle/execution stages (enable gate, CLI readiness,
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run the polled Pi process, shape the result dict).
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- ``__init__.py`` — this file: the agent-facing :class:`BaseTool` contract whose
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``run`` orchestrates those stages. The class lives here (rather than a sister
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module) because the tool registry discovers instances by ``__class__.__module__``
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and does not recurse into sub-modules.
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This is the first **mutating** agent-callable tool, so it is deliberately gated,
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mirroring how ``execute_python_code`` is gated by availability:
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- ``side_effect_level = "mutating"``.
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- ``is_available`` returns True only when ``PI_CODING_ENABLED`` is set, so it is
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never offered to the agent unless the operator opts in.
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- ``surfaces = ("investigation",)`` — the surface the REPL assistant tool loop and
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the investigation pipeline actually consume (the ``chat`` surface has no live
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consumer). Reachability is gated by ``PI_CODING_ENABLED``, not by the surface.
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Expected failures return a structured ``{"success": False, "error_kind": ...}`` dict;
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any *unexpected* exception propagates to ``BaseTool.__call__``, which reports it to
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Sentry. It edits the working tree and returns a summary + git diff; it never commits,
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pushes, or opens a PR (see ``integrations/pi``).
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"""
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from __future__ import annotations
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from typing import Any
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from core.tool_framework.base import BaseTool
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from integrations.pi import is_pi_coding_enabled
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from tools.pi_coding_tool.errors import PiCodingError
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from tools.pi_coding_tool.runner import (
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SOURCE,
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ensure_cli_ready,
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ensure_enabled,
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error_output,
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execute,
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to_output,
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)
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from tools.pi_coding_tool.validation import resolve_request
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class PiCodingTool(BaseTool):
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"""Submit a coding task to the Pi agent; it edits the workspace and returns a diff."""
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name = "pi_coding_task"
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display_name = "Pi coding task"
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source = SOURCE
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side_effect_level = "mutating"
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surfaces = ("investigation",)
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description = (
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"Submit a coding task to the Pi agent (pi.dev). Pi edits files in the workspace to "
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"implement the change and returns a summary plus the git diff. It does not commit, "
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"push, or open a PR. Disabled unless PI_CODING_ENABLED=1 and the Pi CLI is installed "
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"and authenticated."
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)
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use_cases = [
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"Apply a small, well-scoped fix identified during an investigation",
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"Make a targeted code change in the current repository and return the diff for review",
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]
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anti_examples = [
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"Reading logs, metrics, or traces (use a read-only evidence tool instead)",
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"Large multi-file refactors that should be reviewed interactively",
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]
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input_schema = {
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"type": "object",
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"properties": {
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"task": {
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"type": "string",
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"description": "Natural-language description of the coding change Pi should make.",
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},
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"workspace": {
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"type": "string",
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"description": (
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"Absolute path to the repository to edit. "
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"Defaults to PI_CODING_WORKSPACE or the current directory."
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),
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"nullable": True,
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},
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"model": {
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"type": "string",
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"description": (
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"Optional Pi model override in provider/model form "
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"(e.g. anthropic/claude-haiku-4-5). Defaults to PI_CODING_MODEL."
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),
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"nullable": True,
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},
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},
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"required": ["task"],
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}
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outputs = {
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"success": "True when Pi completed and exited cleanly",
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"error_kind": "Stable failure category (disabled, invalid_input, cli_unavailable, "
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"timeout, execution_error) or None on success",
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"summary": "Pi's final message summarizing what it changed",
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"changed_files": "Files modified in the working tree (status porcelain)",
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"diff": "git diff of the changes vs HEAD (truncated if large)",
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"diff_truncated": "True when the diff was truncated",
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"error": "Human-readable error detail when the task failed",
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}
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def is_available(self, _sources: dict[str, dict]) -> bool:
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"""Only available when explicitly opted in (cheap flag check)."""
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return is_pi_coding_enabled()
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def run(
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self,
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task: str,
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workspace: str | None = None,
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model: str | None = None,
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) -> dict[str, Any]:
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try:
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ensure_enabled()
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request = resolve_request(task, workspace, model)
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ensure_cli_ready()
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except PiCodingError as exc:
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return error_output(exc.kind, exc.message)
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# Expected execution failures (timeout, provider limit, no-op) come back as a
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# populated PiCodingResult; any *unexpected* exception propagates to
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# BaseTool.__call__, which reports it to Sentry (the global tool wrapper).
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return to_output(execute(request))
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# Module-level instance so the tool registry auto-discovers it (see tools/registry.py).
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pi_coding_task = PiCodingTool()
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