Base code
This commit is contained in:
Kunthawat Greethong
228
backend/test/test_grounding_integration.py
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228
backend/test/test_grounding_integration.py
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"""
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Test script for LinkedIn grounding integration.
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This script tests the integration of the new grounding services:
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- GoogleSearchService
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- GeminiGroundedProvider
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- CitationManager
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- ContentQualityAnalyzer
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- Enhanced LinkedInService
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"""
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import asyncio
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import os
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from datetime import datetime
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from loguru import logger
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# Set up environment variables for testing
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os.environ.setdefault('GOOGLE_SEARCH_API_KEY', 'test_key')
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os.environ.setdefault('GOOGLE_SEARCH_ENGINE_ID', 'test_engine_id')
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os.environ.setdefault('GEMINI_API_KEY', 'test_gemini_key')
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from services.linkedin_service import LinkedInService
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from models.linkedin_models import (
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LinkedInPostRequest, LinkedInArticleRequest, LinkedInCarouselRequest,
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LinkedInVideoScriptRequest, LinkedInCommentResponseRequest,
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GroundingLevel, SearchEngine, LinkedInTone, LinkedInPostType
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)
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async def test_grounding_integration():
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"""Test the complete grounding integration."""
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logger.info("Starting LinkedIn grounding integration test")
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try:
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# Initialize the enhanced LinkedIn service
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linkedin_service = LinkedInService()
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logger.info("LinkedIn service initialized successfully")
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# Test 1: Basic post generation with grounding disabled
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logger.info("\n=== Test 1: Basic Post Generation (No Grounding) ===")
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basic_request = LinkedInPostRequest(
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topic="AI in Marketing",
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industry="Marketing",
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post_type=LinkedInPostType.PROFESSIONAL,
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tone=LinkedInTone.PROFESSIONAL,
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research_enabled=False,
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grounding_level=GroundingLevel.NONE,
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include_citations=False
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)
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basic_response = await linkedin_service.generate_linkedin_post(basic_request)
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logger.info(f"Basic post generation: {'SUCCESS' if basic_response.success else 'FAILED'}")
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if basic_response.success:
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logger.info(f"Content length: {basic_response.data.character_count}")
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logger.info(f"Grounding enabled: {basic_response.data.grounding_enabled}")
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# Test 2: Enhanced post generation with grounding enabled
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logger.info("\n=== Test 2: Enhanced Post Generation (With Grounding) ===")
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enhanced_request = LinkedInPostRequest(
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topic="Digital Transformation in Healthcare",
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industry="Healthcare",
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post_type=LinkedInPostType.THOUGHT_LEADERSHIP,
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tone=LinkedInTone.AUTHORITATIVE,
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research_enabled=True,
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search_engine=SearchEngine.GOOGLE,
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grounding_level=GroundingLevel.ENHANCED,
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include_citations=True,
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max_length=2000
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)
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enhanced_response = await linkedin_service.generate_linkedin_post(enhanced_request)
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logger.info(f"Enhanced post generation: {'SUCCESS' if enhanced_response.success else 'FAILED'}")
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if enhanced_response.success:
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logger.info(f"Content length: {enhanced_response.data.character_count}")
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logger.info(f"Grounding enabled: {enhanced_response.data.grounding_enabled}")
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logger.info(f"Research sources: {len(enhanced_response.research_sources)}")
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logger.info(f"Citations: {len(enhanced_response.data.citations)}")
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if enhanced_response.data.quality_metrics:
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logger.info(f"Quality score: {enhanced_response.data.quality_metrics.overall_score:.2f}")
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if enhanced_response.grounding_status:
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logger.info(f"Grounding status: {enhanced_response.grounding_status['status']}")
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# Test 3: Article generation with grounding
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logger.info("\n=== Test 3: Article Generation (With Grounding) ===")
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article_request = LinkedInArticleRequest(
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topic="Future of Remote Work",
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industry="Technology",
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tone=LinkedInTone.EDUCATIONAL,
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research_enabled=True,
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search_engine=SearchEngine.GOOGLE,
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grounding_level=GroundingLevel.ENHANCED,
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include_citations=True,
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word_count=1500
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)
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article_response = await linkedin_service.generate_linkedin_article(article_request)
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logger.info(f"Article generation: {'SUCCESS' if article_response.success else 'FAILED'}")
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if article_response.success:
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logger.info(f"Word count: {article_response.data.word_count}")
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logger.info(f"Grounding enabled: {article_response.data.grounding_enabled}")
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logger.info(f"Research sources: {len(article_response.research_sources)}")
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logger.info(f"Citations: {len(article_response.data.citations)}")
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# Test 4: Carousel generation with grounding
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logger.info("\n=== Test 4: Carousel Generation (With Grounding) ===")
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carousel_request = LinkedInCarouselRequest(
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topic="Cybersecurity Best Practices",
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industry="Technology",
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tone=LinkedInTone.EDUCATIONAL,
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research_enabled=True,
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search_engine=SearchEngine.GOOGLE,
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grounding_level=GroundingLevel.ENHANCED,
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include_citations=True,
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number_of_slides=5
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)
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carousel_response = await linkedin_service.generate_linkedin_carousel(carousel_request)
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logger.info(f"Carousel generation: {'SUCCESS' if carousel_response.success else 'FAILED'}")
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if carousel_response.success:
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logger.info(f"Number of slides: {len(carousel_response.data.slides)}")
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logger.info(f"Grounding enabled: {carousel_response.data.grounding_enabled}")
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logger.info(f"Research sources: {len(carousel_response.research_sources)}")
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# Test 5: Video script generation with grounding
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logger.info("\n=== Test 5: Video Script Generation (With Grounding) ===")
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video_request = LinkedInVideoScriptRequest(
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topic="AI Ethics in Business",
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industry="Technology",
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tone=LinkedInTone.EDUCATIONAL,
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research_enabled=True,
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search_engine=SearchEngine.GOOGLE,
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grounding_level=GroundingLevel.ENHANCED,
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include_citations=True,
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video_duration=90
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)
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video_response = await linkedin_service.generate_linkedin_video_script(video_request)
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logger.info(f"Video script generation: {'SUCCESS' if video_response.success else 'FAILED'}")
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if video_response.success:
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logger.info(f"Grounding enabled: {video_response.data.grounding_enabled}")
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logger.info(f"Research sources: {len(video_response.research_sources)}")
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logger.info(f"Citations: {len(video_response.data.citations)}")
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# Test 6: Comment response generation
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logger.info("\n=== Test 6: Comment Response Generation ===")
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comment_request = LinkedInCommentResponseRequest(
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original_comment="Great insights on AI implementation!",
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post_context="Post about AI transformation in healthcare",
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industry="Healthcare",
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tone=LinkedInTone.FRIENDLY,
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response_length="medium",
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include_questions=True,
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research_enabled=False,
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grounding_level=GroundingLevel.BASIC
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)
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comment_response = await linkedin_service.generate_linkedin_comment_response(comment_request)
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logger.info(f"Comment response generation: {'SUCCESS' if comment_response.success else 'FAILED'}")
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if comment_response.success:
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logger.info(f"Response length: {len(comment_response.response) if comment_response.response else 0}")
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logger.info(f"Grounding enabled: {comment_response.grounding_status['status'] if comment_response.grounding_status else 'N/A'}")
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logger.info("\n=== Integration Test Summary ===")
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logger.info("All tests completed successfully!")
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except Exception as e:
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logger.error(f"Integration test failed: {str(e)}")
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raise
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async def test_individual_services():
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"""Test individual service components."""
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logger.info("\n=== Testing Individual Service Components ===")
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try:
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# Test Google Search Service
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from services.research import GoogleSearchService
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google_search = GoogleSearchService()
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logger.info("GoogleSearchService initialized successfully")
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# Test Citation Manager
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from services.citation import CitationManager
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citation_manager = CitationManager()
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logger.info("CitationManager initialized successfully")
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# Test Content Quality Analyzer
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from services.quality import ContentQualityAnalyzer
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quality_analyzer = ContentQualityAnalyzer()
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logger.info("ContentQualityAnalyzer initialized successfully")
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# Test Gemini Grounded Provider
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from services.llm_providers.gemini_grounded_provider import GeminiGroundedProvider
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gemini_grounded = GeminiGroundedProvider()
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logger.info("GeminiGroundedProvider initialized successfully")
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logger.info("All individual services initialized successfully!")
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except Exception as e:
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logger.error(f"Service component test failed: {str(e)}")
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raise
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async def main():
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"""Main test function."""
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logger.info("Starting LinkedIn Grounding Integration Tests")
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logger.info(f"Test timestamp: {datetime.now().isoformat()}")
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try:
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# Test individual services first
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await test_individual_services()
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# Test complete integration
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await test_grounding_integration()
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logger.info("\n🎉 All tests completed successfully!")
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except Exception as e:
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logger.error(f"Test suite failed: {str(e)}")
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logger.error("Please check the error details above and ensure all services are properly configured.")
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return 1
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return 0
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if __name__ == "__main__":
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# Run the tests
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exit_code = asyncio.run(main())
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exit(exit_code)
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