"""Unit tests for LiteLLMRequester._convert_messages.

Focus: the content-part normalization that (a) converts image_base64 parts to
the OpenAI image_url shape and (b) drops non-image file parts (file_base64 /
file_url) which OpenAI-compatible chat models reject. The latter is essential
for Voice/File attachments — including ones replayed from conversation history —
since the agent consumes their bytes via the sandbox, not the model payload.
"""

import langbot_plugin.api.entities.builtin.provider.message as provider_message

from langbot.pkg.provider.modelmgr.requesters.litellmchat import LiteLLMRequester


def _make_requester() -> LiteLLMRequester:
    # _convert_messages does not touch instance config, so bypass __init__.
    return LiteLLMRequester.__new__(LiteLLMRequester)


def test_convert_messages_drops_file_base64_part():
    req = _make_requester()
    msg = provider_message.Message(
        role='user',
        content=[
            provider_message.ContentElement.from_text('analyze this audio'),
            provider_message.ContentElement.from_file_base64('data:audio/wav;base64,AAAA', 'voice.wav'),
        ],
    )
    out = req._convert_messages([msg])
    parts = out[0]['content']
    types = [p.get('type') for p in parts]
    assert 'file_base64' not in types
    assert types == ['text']
    assert parts[0]['text'] == 'analyze this audio'


def test_convert_messages_drops_file_url_part():
    req = _make_requester()
    msg = provider_message.Message(
        role='user',
        content=[
            provider_message.ContentElement.from_text('here is a doc'),
            provider_message.ContentElement.from_file_url('http://example.com/report.xlsx', 'report.xlsx'),
        ],
    )
    out = req._convert_messages([msg])
    types = [p.get('type') for p in out[0]['content']]
    assert types == ['text']


def test_convert_messages_keeps_image_and_converts_to_image_url():
    req = _make_requester()
    msg = provider_message.Message(
        role='user',
        content=[
            provider_message.ContentElement.from_text('look'),
            provider_message.ContentElement.from_image_base64('data:image/png;base64,AAAA'),
        ],
    )
    out = req._convert_messages([msg])
    parts = out[0]['content']
    types = [p.get('type') for p in parts]
    # image is preserved and reshaped to the OpenAI image_url form
    assert types == ['text', 'image_url']
    img_part = parts[1]
    assert img_part['image_url'] == {'url': 'data:image/png;base64,AAAA'}
    assert 'image_base64' not in img_part


def test_convert_messages_mixed_history_strips_only_files():
    req = _make_requester()
    # Simulate replayed history: an old voice turn + a current text turn.
    history_voice = provider_message.Message(
        role='user',
        content=[
            provider_message.ContentElement.from_text('old audio turn'),
            provider_message.ContentElement.from_file_base64('data:audio/wav;base64,BBBB', 'voice.wav'),
        ],
    )
    current = provider_message.Message(
        role='user',
        content=[provider_message.ContentElement.from_text('now do the csv')],
    )
    out = req._convert_messages([history_voice, current])
    assert [p.get('type') for p in out[0]['content']] == ['text']
    assert [p.get('type') for p in out[1]['content']] == ['text']


def test_convert_messages_plain_string_content_untouched():
    req = _make_requester()
    msg = provider_message.Message(role='user', content='just text')
    out = req._convert_messages([msg])
    assert out[0]['content'] == 'just text'