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westey
bad05a2bdc
* Add initial harness console for python * Add textual to project * Add planning and approval flows with list selector * Address PR comments * Fix list selection bug * Fix PR #6312 round 2 review comments - Escape untrusted agent text with rich.markup.escape() in observers (text_output, planning_output, reasoning_display) to prevent markup injection - Remove non-functional 'Always approve' choices from tool_approval.py (framework lacks CreateAlwaysApproveToolResponse support) - Remove textual from root pyproject.toml dev deps (sample-specific) - Add PEP 723 inline script metadata to harness_research.py - Narrow except Exception to except NoMatches in list_selection.py Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix build error * Fix build errors --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
88 lines
2.8 KiB
Python
88 lines
2.8 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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"""Main entry point for the harness console.
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Provides the top-level run_agent_async() function that creates and runs
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the Textual-based harness console application.
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"""
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from __future__ import annotations
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from typing import TYPE_CHECKING
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from .app import HarnessApp
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from .observers import build_default_observers
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if TYPE_CHECKING:
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from agent_framework import Agent, AgentSession
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from .commands import CommandHandler
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from .observers.base import ConsoleObserver
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async def run_agent_async(
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agent: Agent,
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*,
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session: AgentSession | None = None,
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observers: list[ConsoleObserver] | None = None,
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command_handlers: list[CommandHandler] | None = None,
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mode_colors: dict[str, str] | None = None,
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initial_mode: str | None = None,
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placeholder: str = "Type a message and press Enter...",
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title: str = "Harness Console",
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max_context_window_tokens: int | None = None,
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max_output_tokens: int | None = None,
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) -> None:
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"""Run the harness console with the given agent.
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This is the main entry point for the harness console. Creates a Textual
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application with the configured observers and runs it until the user exits.
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Args:
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agent: The agent to run conversations with.
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session: Optional agent session for conversation history.
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observers: List of console observers. If None, uses defaults.
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command_handlers: List of command handlers. If None, auto-detected from agent.
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mode_colors: Mapping of mode names to Rich color strings.
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initial_mode: Initial agent mode text.
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placeholder: Input placeholder text.
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title: Application title.
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max_context_window_tokens: Optional max context window size for usage display.
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max_output_tokens: Optional max output tokens for usage display.
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Example:
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.. code-block:: python
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from agent_framework import Agent
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from agent_framework.openai import OpenAIChatClient
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from console import run_agent_async
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agent = Agent(
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client=OpenAIChatClient(),
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instructions="You are helpful.",
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)
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await run_agent_async(agent)
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"""
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resolved_observers = observers or build_default_observers()
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resolved_mode_colors = mode_colors or {
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"plan": "cyan",
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"execute": "green",
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}
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resolved_session = session or agent.create_session()
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app = HarnessApp(
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agent=agent,
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observers=resolved_observers,
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session=resolved_session,
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mode_colors=resolved_mode_colors,
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initial_mode=initial_mode,
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placeholder=placeholder,
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title=title,
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max_context_window_tokens=max_context_window_tokens,
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max_output_tokens=max_output_tokens,
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command_handlers=command_handlers,
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)
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await app.run_async()
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