2e8c2c11d0
Vocabulary study with FSRS spaced repetition, AI tutoring (Ollama/Claude), essay marking, idioms browser, Anki export, and dashboard. 918 vocabulary entries across 39 categories. 41 tests passing. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
90 lines
3.1 KiB
Python
90 lines
3.1 KiB
Python
"""Tests for ai.py — dual AI backend."""
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import sys
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from pathlib import Path
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from unittest.mock import patch, MagicMock
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import pytest
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sys.path.insert(0, str(Path(__file__).parent.parent))
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import ai
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def test_ask_ollama_calls_ollama_chat():
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"""ask_ollama should call ollama.chat with correct messages."""
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mock_response = MagicMock()
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mock_response.message.content = "test response"
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with patch("ai.ollama.chat", return_value=mock_response) as mock_chat:
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result = ai.ask_ollama("Hello", system="Be helpful")
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assert result == "test response"
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call_args = mock_chat.call_args
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messages = call_args.kwargs.get("messages") or call_args[1].get("messages")
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assert len(messages) == 2
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assert messages[0]["role"] == "system"
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assert messages[1]["role"] == "user"
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assert messages[1]["content"] == "Hello"
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def test_ask_ollama_no_system():
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"""ask_ollama without system prompt should only send user message."""
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mock_response = MagicMock()
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mock_response.message.content = "response"
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with patch("ai.ollama.chat", return_value=mock_response) as mock_chat:
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ai.ask_ollama("Hi")
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call_args = mock_chat.call_args
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messages = call_args.kwargs.get("messages") or call_args[1].get("messages")
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assert len(messages) == 1
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assert messages[0]["role"] == "user"
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def test_ask_claude_calls_subprocess():
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"""ask_claude should call claude CLI via subprocess."""
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with patch("ai.subprocess.run") as mock_run:
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mock_run.return_value = MagicMock(stdout="Claude says hi\n")
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result = ai.ask_claude("Hello")
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assert result == "Claude says hi"
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mock_run.assert_called_once()
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args = mock_run.call_args[0][0]
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assert args[0] == "claude"
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assert "-p" in args
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def test_ask_fast_uses_ollama():
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"""ask with quality='fast' should use Ollama."""
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with patch("ai.ask_ollama", return_value="ollama response") as mock:
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result = ai.ask("test", quality="fast")
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assert result == "ollama response"
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mock.assert_called_once()
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def test_ask_smart_uses_claude():
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"""ask with quality='smart' should use Claude."""
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with patch("ai.ask_claude", return_value="claude response") as mock:
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result = ai.ask("test", quality="smart")
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assert result == "claude response"
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mock.assert_called_once()
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def test_chat_ollama():
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"""chat_ollama should pass multi-turn messages."""
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mock_response = MagicMock()
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mock_response.message.content = "continuation"
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with patch("ai.ollama.chat", return_value=mock_response) as mock_chat:
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messages = [
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{"role": "user", "content": "Hi"},
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{"role": "assistant", "content": "Hello!"},
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{"role": "user", "content": "How are you?"},
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]
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result = ai.chat_ollama(messages, system="Be helpful")
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assert result == "continuation"
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call_args = mock_chat.call_args
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all_msgs = call_args.kwargs.get("messages") or call_args[1].get("messages")
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# system + 3 conversation messages
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assert len(all_msgs) == 4
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