src/agent_server/chat/presenter.py - master - man4j/agent-server

src/agent_server/chat/presenter.py
71 строка2 KB
Vladimir
initial
18 апр 2026, 19:36
18 апр 2026, 19:36a95f341
import chainlit as cl

from agent_server.chat.types import ChatMessage, ToolExecutionRecord
from agent_server.local_tools import build_local_ui_elements
from agent_server.ui_meta import UsageTotals, apply_meta_block, build_meta_block


async def create_answer_message(author: str) -> cl.Message:
    answer_msg = cl.Message(content="", author=author, elements=[])
    await answer_msg.send()
    return answer_msg


async def apply_tool_results_to_answer(
    answer_msg: cl.Message,
    tool_results: list[ToolExecutionRecord],
) -> bool:
    updated = False
    current_elements = list(answer_msg.elements or [])
    extra_markdown_parts: list[str] = []

    for item in tool_results:
        result = item["result"]

        if result.get("ok") and result.get("ui_type") == "markdown_diff":
            markdown = result.get("markdown")
            if isinstance(markdown, str) and markdown.strip():
                extra_markdown_parts.append(markdown.rstrip())
                updated = True
            continue

        elements = build_local_ui_elements(result, len(current_elements))
        if not elements:
            continue

        current_elements.extend(elements)
        updated = True

    if extra_markdown_parts:
        base = answer_msg.content.rstrip()
        appendix = "\n\n".join(extra_markdown_parts)
        answer_msg.content = f"{base}\n\n{appendix}" if base else appendix

    if current_elements:
        answer_msg.elements = current_elements

    return updated


async def finalize_answer_message(
    answer_msg: cl.Message,
    *,
    usage_totals: UsageTotals,
    messages: list[ChatMessage],
    char_per_token: float,
    connected_servers: list[str],
    context_size: int,
    response_headroom_tokens: int,
    estimated_prompt_tokens_fn,
) -> None:
    meta_block = build_meta_block(
        usage_totals=usage_totals,
        messages=messages,
        char_per_token=char_per_token,
        estimated_prompt_tokens_fn=estimated_prompt_tokens_fn,
        connected_servers=connected_servers,
        context_size=context_size,
        response_headroom_tokens=response_headroom_tokens,
    )
    answer_msg.content = apply_meta_block(answer_msg.content, meta_block)
    await answer_msg.update()