chore: import upstream snapshot with attribution
This commit is contained in:
wehub-resource-sync
@@ -0,0 +1,397 @@
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import json
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import os
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import subprocess
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from collections.abc import Awaitable, Callable
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from pathlib import Path
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from typing import Any, Literal, TypeAlias, cast
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from openai.types.responses import (
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ResponseComputerToolCall,
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ResponseFileSearchToolCall,
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ResponseFunctionToolCall,
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ResponseFunctionWebSearch,
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)
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from openai.types.responses.response_code_interpreter_tool_call import (
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ResponseCodeInterpreterToolCall,
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)
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from openai.types.responses.response_output_item import ImageGenerationCall, LocalShellCall, McpCall
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from pydantic import BaseModel, Field
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from rich import box
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from rich.console import Console, Group
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from rich.markdown import Markdown
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from rich.panel import Panel
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from rich.pretty import Pretty
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from rich.prompt import Prompt
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from rich.syntax import Syntax
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from rich.text import Text
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from typing_extensions import TypedDict
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from agents import ItemHelpers, TResponseInputItem
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from agents.items import (
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CompactionItem,
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HandoffCallItem,
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HandoffOutputItem,
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MCPApprovalRequestItem,
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MCPApprovalResponseItem,
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MCPListToolsItem,
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MessageOutputItem,
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ReasoningItem,
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ToolApprovalItem,
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ToolCallItem,
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ToolCallOutputItem,
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ToolSearchCallItem,
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ToolSearchOutputItem,
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)
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from agents.sandbox import Manifest
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from agents.sandbox.sandboxes.docker import DockerSandboxClient, DockerSandboxClientOptions
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from agents.sandbox.sandboxes.unix_local import UnixLocalSandboxClient
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from agents.sandbox.session import BaseSandboxClient, SandboxSession
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from agents.stream_events import (
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AgentUpdatedStreamEvent,
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RawResponsesStreamEvent,
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StreamEvent,
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)
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from examples.auto_mode import input_with_fallback, is_auto_mode
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DEFAULT_SANDBOX_IMAGE = "sandbox-tutorials:latest"
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console = Console()
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PanelBody = Group | Pretty | Text
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PrintableEvent: TypeAlias = StreamEvent | str
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SandboxClient: TypeAlias = BaseSandboxClient[Any]
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InteractiveTurnRunner: TypeAlias = Callable[
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[list[TResponseInputItem]], Awaitable[list[TResponseInputItem]]
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]
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class ApplyPatchOperationPayload(TypedDict):
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path: str
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type: Literal["create_file", "update_file", "delete_file"]
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diff: str
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class ApplyPatchCallPayload(TypedDict):
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type: Literal["apply_patch_call"]
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call_id: str
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operation: ApplyPatchOperationPayload
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class Question(BaseModel):
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query: str = Field(description="User-facing question to ask.")
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options: list[str] = Field(
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default_factory=list,
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description="Suggested answer options. The UI always adds a custom free-text choice.",
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)
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class QuestionAnswer(BaseModel):
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question: str = Field(description="The question that was asked.")
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answer: str = Field(description="The user's selected or free-text answer.")
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def load_env_defaults(env_path: Path) -> None:
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if not env_path.exists():
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return
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for raw_line in env_path.read_text(encoding="utf-8").splitlines():
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line = raw_line.strip()
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if not line or line.startswith("#") or "=" not in line:
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continue
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key, value = line.split("=", 1)
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normalized_key = key.strip()
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normalized_value = value.strip().strip('"').strip("'")
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if normalized_key:
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os.environ.setdefault(normalized_key, normalized_value)
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async def create_sandbox_client_and_session(
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*,
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manifest: Manifest,
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use_docker: bool,
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image: str = DEFAULT_SANDBOX_IMAGE,
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) -> tuple[SandboxClient, SandboxSession]:
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if use_docker:
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try:
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from docker import from_env as docker_from_env # type: ignore[import-untyped]
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except ImportError as exc:
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raise SystemExit(
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"Docker-backed runs require the Docker SDK. Install repo dependencies with `make sync`."
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) from exc
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client: SandboxClient = DockerSandboxClient(
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docker_from_env(environment=build_docker_environment())
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)
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sandbox = await client.create(
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manifest=manifest,
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options=DockerSandboxClientOptions(image=image),
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)
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return client, sandbox
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client = UnixLocalSandboxClient()
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sandbox = await client.create(manifest=manifest)
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return client, sandbox
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def build_docker_environment() -> dict[str, str]:
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environment = os.environ.copy()
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if environment.get("DOCKER_HOST") or environment.get("DOCKER_CONTEXT"):
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return environment
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# Respect whichever Docker context the CLI is currently using, including Docker Desktop
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# and Colima, without taking a direct dependency on a specific daemon provider.
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try:
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result = subprocess.run(
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["docker", "context", "inspect", "--format", "{{json .Endpoints.docker.Host}}"],
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capture_output=True,
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check=True,
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text=True,
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)
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docker_host = json.loads(result.stdout.strip() or "null")
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except (OSError, subprocess.SubprocessError, json.JSONDecodeError):
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return environment
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if isinstance(docker_host, str) and docker_host:
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environment["DOCKER_HOST"] = docker_host
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return environment
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def prompt_with_fallback(prompt: str, fallback: str) -> str:
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if is_auto_mode():
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return input_with_fallback(prompt, fallback).strip()
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try:
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return Prompt.ask(prompt).strip()
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except (EOFError, KeyboardInterrupt):
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return fallback
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def ask_user_questions(questions: list[Question]) -> list[QuestionAnswer]:
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answers: list[QuestionAnswer] = []
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for question_index, question in enumerate(questions, start=1):
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suggested_options = [option.strip() for option in question.options if option.strip()]
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custom_choice_index = len(suggested_options) + 1
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options_text = Text.from_markup(
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"\n".join(
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[
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*(
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f"[cyan]{index}.[/cyan] {option}"
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for index, option in enumerate(
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suggested_options,
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start=1,
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)
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),
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f"[cyan]{custom_choice_index}.[/cyan] Use your own text",
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]
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)
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)
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console.print(
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Panel(
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Group(
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Text(question.query),
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options_text,
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),
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title=f"Question {question_index}",
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border_style="magenta",
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box=box.ROUNDED,
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expand=False,
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)
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)
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while True:
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choice = prompt_with_fallback(
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f"[bold cyan]Select[/bold cyan] 1-{custom_choice_index}",
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"1" if suggested_options else str(custom_choice_index),
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)
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if choice.isdigit() and 1 <= int(choice) <= len(suggested_options):
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answer = suggested_options[int(choice) - 1]
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break
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if choice.isdigit() and int(choice) == custom_choice_index:
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answer = prompt_with_fallback(
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"[bold cyan]Your answer[/bold cyan]",
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suggested_options[0] if suggested_options else "Use a conservative assumption.",
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)
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if answer:
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break
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continue
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if choice and not choice.isdigit():
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answer = choice
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break
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console.print(
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f"[red]Please enter a number from 1 to {custom_choice_index}, or custom text.[/red]"
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)
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answers.append(QuestionAnswer(question=question.query, answer=answer))
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console.print(
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Panel(
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Pretty([answer.model_dump(mode="json") for answer in answers], expand_all=True),
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title="Question answers",
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border_style="magenta",
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box=box.ROUNDED,
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expand=False,
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)
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)
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return answers
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async def run_interactive_loop(
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*,
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conversation: list[TResponseInputItem],
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no_interactive: bool,
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run_turn: InteractiveTurnRunner,
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) -> list[TResponseInputItem]:
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if no_interactive or is_auto_mode():
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return conversation
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console.print("[dim]Enter follow-up prompts. Press Ctrl-D or Ctrl-C to finish.[/dim]")
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while True:
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try:
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next_message = Prompt.ask("[bold cyan]user[/bold cyan]").strip()
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except (EOFError, KeyboardInterrupt):
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break
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if not next_message:
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continue
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conversation.append({"role": "user", "content": next_message})
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conversation = await run_turn(conversation)
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return conversation
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def print_event(event: PrintableEvent) -> None:
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if isinstance(event, str):
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console.print()
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console.rule("[bold green]Final output[/bold green]", style="green")
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console.print(
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Panel(
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Markdown(event or "_No final output returned._"),
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border_style="green",
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box=box.ROUNDED,
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expand=False,
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)
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)
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return
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if isinstance(event, AgentUpdatedStreamEvent):
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console.print(
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Panel(
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Pretty(event.new_agent.name, expand_all=True),
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title="Agent updated",
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border_style="cyan",
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box=box.ROUNDED,
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expand=False,
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)
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)
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return
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if isinstance(event, RawResponsesStreamEvent):
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return
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body: PanelBody
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match event.item:
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case ReasoningItem() as item:
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body = Pretty(item, expand_all=True)
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title = f"Reasoning item: {event.name.replace('_', ' ')}"
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case ToolCallItem() as item:
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tool_name = "tool"
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body = Pretty(item.raw_item, expand_all=True)
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match item.raw_item:
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case ResponseFunctionToolCall() as raw_item:
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tool_name = raw_item.name
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payload = json.loads(raw_item.arguments) if raw_item.arguments else {}
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if tool_name == "exec_command":
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command = payload["cmd"]
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if "\\n" in command and "\n" not in command:
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command = command.replace("\\n", "\n")
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body = Group(
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Pretty(
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{key: value for key, value in payload.items() if key != "cmd"},
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expand_all=True,
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),
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Syntax(command, "bash", theme="ansi_dark", word_wrap=True),
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)
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else:
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body = Pretty(payload, expand_all=True)
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case ResponseComputerToolCall() as raw_item:
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tool_name = "computer"
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body = Pretty(raw_item, expand_all=True)
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case ResponseFileSearchToolCall() as raw_item:
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tool_name = "file_search"
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body = Pretty(raw_item, expand_all=True)
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case ResponseFunctionWebSearch() as raw_item:
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tool_name = "web_search"
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body = Pretty(raw_item, expand_all=True)
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case McpCall() as raw_item:
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tool_name = "mcp"
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body = Pretty(raw_item, expand_all=True)
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case ResponseCodeInterpreterToolCall() as raw_item:
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tool_name = "code_interpreter"
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body = Pretty(raw_item, expand_all=True)
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case ImageGenerationCall() as raw_item:
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tool_name = "image_generation"
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body = Pretty(raw_item, expand_all=True)
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case LocalShellCall() as raw_item:
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tool_name = "local_shell"
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body = Pretty(raw_item, expand_all=True)
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case dict() as raw_item:
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tool_name = "apply_patch"
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payload = cast(ApplyPatchCallPayload, raw_item)["operation"]
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body = Group(
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Pretty(
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{
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"path": payload["path"],
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"type": payload["type"],
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},
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expand_all=True,
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),
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Syntax(payload["diff"], "diff", theme="ansi_dark", word_wrap=True),
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)
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title = f"Tool call: {tool_name}"
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case ToolCallOutputItem() as item:
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body = Text(item.output) if isinstance(item.output, str) else Pretty(item.output)
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title = "Tool output"
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case MessageOutputItem() as item:
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output = ItemHelpers.text_message_output(item)
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body = Text(output) if isinstance(output, str) else Pretty(output, expand_all=True)
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title = "Message output"
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case ToolSearchCallItem() as item:
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body = Pretty(item.raw_item, expand_all=True)
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title = "Tool search call"
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case ToolSearchOutputItem() as item:
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body = Pretty(item.raw_item, expand_all=True)
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title = "Tool search output"
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case HandoffCallItem() as item:
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body = Pretty(item.raw_item, expand_all=True)
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title = "Handoff call"
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case HandoffOutputItem() as item:
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body = Pretty(item.raw_item, expand_all=True)
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title = "Handoff output"
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case MCPListToolsItem() as item:
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body = Pretty(item.raw_item, expand_all=True)
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title = "MCP list tools"
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case MCPApprovalRequestItem() as item:
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body = Pretty(item.raw_item, expand_all=True)
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title = "MCP approval request"
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case MCPApprovalResponseItem() as item:
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body = Pretty(item.raw_item, expand_all=True)
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title = "MCP approval response"
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case CompactionItem() as item:
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body = Pretty(item.raw_item, expand_all=True)
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title = "Compaction"
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case ToolApprovalItem() as item:
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body = Pretty(item.raw_item, expand_all=True)
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title = "Tool approval"
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console.print(
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Panel(
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body,
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title=title,
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border_style="cyan",
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box=box.ROUNDED,
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expand=False,
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)
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)
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