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64 lines
2.2 KiB
Python
64 lines
2.2 KiB
Python
"""Shell adapter for one conversational answer turn.
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Binds the interactive shell's Rich output, grounding caches, reasoning client,
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and telemetry around core ``stream_answer``.
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"""
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from __future__ import annotations
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from collections.abc import Callable
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from rich.console import Console
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from core.agent_harness.accounting.run_record import DefaultRunRecordFactory
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from core.agent_harness.error_reporting import DefaultErrorReporter
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from core.agent_harness.ports import OutputSink
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from core.agent_harness.turns.default_reasoning_client import DefaultReasoningClientProvider
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from core.agent_harness.turns.orchestrator import (
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stream_answer as core_stream_answer,
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)
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from core.agent_harness.turns.turn_plan import TurnPlan
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from surfaces.interactive_shell.grounding.cli_reference import shell_prompt_context_provider
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from surfaces.interactive_shell.runtime.agent_harness_adapters import resolve_output_sink
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from surfaces.interactive_shell.session import Session
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from surfaces.interactive_shell.utils.telemetry import LlmRunInfo
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def answer_shell_question(
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message: str,
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session: Session,
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console: Console,
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*,
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confirm_fn: Callable[[str], str] | None = None,
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is_tty: bool | None = None,
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tool_observation: str | None = None,
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tool_observation_on_screen: bool = True,
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handoff_contents: tuple[str, ...] = (),
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turn_plan: TurnPlan | None = None,
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output: OutputSink | None = None,
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) -> LlmRunInfo | None:
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"""Answer one shell question through the grounded conversational assistant."""
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resolved_output = resolve_output_sink(console, output)
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return core_stream_answer(
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message,
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session,
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resolved_output,
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prompts=shell_prompt_context_provider(session),
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reasoning=DefaultReasoningClientProvider(
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output=resolved_output,
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error_reporter=DefaultErrorReporter(),
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session=session,
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),
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run_factory=DefaultRunRecordFactory(session),
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error_reporter=DefaultErrorReporter(),
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confirm_fn=confirm_fn,
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is_tty=is_tty,
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tool_observation=tool_observation,
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tool_observation_on_screen=tool_observation_on_screen,
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handoff_contents=handoff_contents,
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turn_plan=turn_plan,
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)
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__all__ = ["answer_shell_question"]
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