# SPDX-License-Identifier: MIT
"""
Test AI Content Generation
===========================
Tests for AI content generation features.
"""
import pytest
from unittest.mock import AsyncMock, MagicMock, patch
@pytest.mark.asyncio
class TestContentGenerator:
"""Test ContentGenerator class."""
async def test_generate_tweet_openai(self, mock_openai_client):
"""Test tweet generation with OpenAI."""
from xeepy.ai.features.content import ContentGenerator
with patch('xeepy.ai.providers.openai.OpenAI') as mock_class:
mock_class.return_value = mock_openai_client
generator = ContentGenerator(provider="openai", api_key="test-key")
tweet = await generator.generate_tweet(
topic="AI ethics",
tone="professional",
hashtags=["AI", "Ethics"],
)
assert isinstance(tweet, str)
assert len(tweet) > 0
assert len(tweet) <= 280
async def test_generate_thread(self, mock_openai_client):
"""Test thread generation."""
from xeepy.ai.features.content import ContentGenerator
with patch('xeepy.ai.providers.openai.OpenAI') as mock_class:
mock_openai_client.chat.completions.create = AsyncMock(return_value=MagicMock(
choices=[MagicMock(
message=MagicMock(content="Tweet 1\n\nTweet 2\n\nTweet 3")
)]
))
mock_class.return_value = mock_openai_client
generator = ContentGenerator(provider="openai", api_key="test-key")
thread = await generator.generate_thread(
topic="Machine Learning",
num_tweets=3,
)
assert isinstance(thread, list)
assert len(thread) == 3
for tweet in thread:
assert isinstance(tweet, str)
assert len(tweet) <= 280
async def test_generate_reply(self, mock_openai_client):
"""Test reply generation."""
from xeepy.ai.features.content import ContentGenerator
with patch('xeepy.ai.providers.openai.OpenAI') as mock_class:
mock_class.return_value = mock_openai_client
generator = ContentGenerator(provider="openai", api_key="test-key")
reply = await generator.generate_reply(
original_tweet="AI is amazing!",
tone="thoughtful",
)
assert isinstance(reply, str)
assert len(reply) > 0
assert len(reply) <= 280
async def test_invalid_provider(self):
"""Test with invalid provider."""
from xeepy.ai.features.content import ContentGenerator
with pytest.raises((ValueError, ImportError)):
generator = ContentGenerator(provider="invalid_provider")
@pytest.mark.asyncio
class TestSentimentAnalyzer:
"""Test SentimentAnalyzer class."""
async def test_analyze_positive_sentiment(self, mock_openai_client):
"""Test positive sentiment analysis."""
from xeepy.ai.features.sentiment import SentimentAnalyzer
mock_openai_client.chat.completions.create = AsyncMock(return_value=MagicMock(
choices=[MagicMock(
message=MagicMock(content='{"sentiment": "positive", "confidence": 0.95, "engagement_potential": 0.85}')
)]
))
with patch('xeepy.ai.providers.openai.OpenAI') as mock_class:
mock_class.return_value = mock_openai_client
analyzer = SentimentAnalyzer(provider="openai", api_key="test-key")
result = await analyzer.analyze_text("This is amazing! I love it!")
assert result.sentiment == "positive"
assert result.confidence >= 0.8
assert result.engagement_potential > 0
async def test_analyze_negative_sentiment(self, mock_openai_client):
"""Test negative sentiment analysis."""
from xeepy.ai.features.sentiment import SentimentAnalyzer
mock_openai_client.chat.completions.create = AsyncMock(return_value=MagicMock(
choices=[MagicMock(
message=MagicMock(content='{"sentiment": "negative", "confidence": 0.90, "engagement_potential": 0.40}')
)]
))
with patch('xeepy.ai.providers.openai.OpenAI') as mock_class:
mock_class.return_value = mock_openai_client
analyzer = SentimentAnalyzer(provider="openai", api_key="test-key")
result = await analyzer.analyze_text("This is terrible. I hate it.")
assert result.sentiment == "negative"
assert result.confidence >= 0.8
@pytest.mark.asyncio
class TestSpamDetector:
"""Test SpamDetector class."""
async def test_detect_spam(self, mock_openai_client):
"""Test spam detection."""
from xeepy.ai.features.spam import SpamDetector
mock_openai_client.chat.completions.create = AsyncMock(return_value=MagicMock(
choices=[MagicMock(
message=MagicMock(content='{"is_spam": true, "confidence": 0.95, "spam_type": "commercial"}')
)]
))
with patch('xeepy.ai.providers.openai.OpenAI') as mock_class:
mock_class.return_value = mock_openai_client
detector = SpamDetector(provider="openai", api_key="test-key")
result = await detector.is_spam("Click here to win $1000000!!!")
assert result is True
async def test_detect_bot(self, mock_openai_client):
"""Test bot detection."""
from xeepy.ai.features.spam import SpamDetector
mock_openai_client.chat.completions.create = AsyncMock(return_value=MagicMock(
choices=[MagicMock(
message=MagicMock(content='{"is_bot": true, "confidence": 0.88, "bot_indicators": ["automated posting"]}')
)]
))
with patch('xeepy.ai.providers.openai.OpenAI') as mock_class:
mock_class.return_value = mock_openai_client
detector = SpamDetector(provider="openai", api_key="test-key")
result = await detector.is_likely_bot("botuser123")
assert result.is_bot is True
assert result.confidence >= 0.8
@pytest.mark.asyncio
class TestSmartTargeting:
"""Test SmartTargeting class."""
async def test_find_relevant_accounts(self, mock_openai_client):
"""Test finding relevant accounts."""
from xeepy.ai.features.targeting import SmartTargeting
with patch('xeepy.ai.providers.openai.OpenAI') as mock_class:
mock_class.return_value = mock_openai_client
targeting = SmartTargeting(provider="openai", api_key="test-key")
accounts = await targeting.find_relevant_accounts(
interests=["AI", "Machine Learning"],
min_followers=1000,
limit=10,
)
assert isinstance(accounts, list)
assert len(accounts) <= 10
for account in accounts:
assert hasattr(account, 'username')
assert hasattr(account, 'relevance_score')
@pytest.mark.asyncio
class TestCryptoAnalyzer:
"""Test CryptoAnalyzer class."""
async def test_analyze_token_sentiment(self, mock_openai_client):
"""Test crypto token sentiment analysis."""
from xeepy.ai.features.crypto import CryptoAnalyzer
mock_openai_client.chat.completions.create = AsyncMock(return_value=MagicMock(
choices=[MagicMock(
message=MagicMock(content='{"overall_sentiment": "bullish", "confidence": 0.85, "mention_count": 1500}')
)]
))
with patch('xeepy.ai.providers.openai.OpenAI') as mock_class:
mock_class.return_value = mock_openai_client
analyzer = CryptoAnalyzer(provider="openai", api_key="test-key")
result = await analyzer.analyze_token_sentiment(
token="BTC",
timeframe="24h",
)
assert result.overall_sentiment in ["bullish", "bearish", "neutral"]
assert result.confidence > 0
assert result.mention_count >= 0
# =============================================================================
# Integration Tests
# =============================================================================
@pytest.mark.integration
@pytest.mark.asyncio
class TestAIIntegration:
"""Integration tests for AI features."""
async def test_content_pipeline(self, mock_openai_client):
"""Test full content generation pipeline."""
from xeepy.ai.features.content import ContentGenerator
from xeepy.ai.features.sentiment import SentimentAnalyzer
with patch('xeepy.ai.providers.openai.OpenAI') as mock_class:
mock_class.return_value = mock_openai_client
# Generate content
generator = ContentGenerator(provider="openai", api_key="test-key")
tweet = await generator.generate_tweet(topic="AI")
# Analyze sentiment
mock_openai_client.chat.completions.create = AsyncMock(return_value=MagicMock(
choices=[MagicMock(
message=MagicMock(content='{"sentiment": "positive", "confidence": 0.9, "engagement_potential": 0.8}')
)]
))
analyzer = SentimentAnalyzer(provider="openai", api_key="test-key")
sentiment = await analyzer.analyze_text(tweet)
assert isinstance(tweet, str)
assert sentiment.confidence > 0
