63a0df2536
Phase 1: Dead Code Cleanup - Remove GeminiGroundedProvider import and property from linkedin_service.py - Remove fallback_provider property (gemini_provider imports) - Fix routers/linkedin.py edit endpoint to use llm_text_gen - Delete dead LinkedInImageEditor class - Remove dead _transform_gemini_sources from content_generator.py Phase 2: Research Infrastructure Alignment - Add user_id to _conduct_research() for pre-flight validation - Add validate_exa_research_operations() before Exa/Tavily calls - Pass user_id to provider.simple_search() for usage tracking - Inject research content into LLM prompts via _build_research_context() - Fix Google engine path to fallback to Exa - Add Exa → Tavily fallback on research failure Phase 3: Cosmetic Cleanup - Rename _generate_prompts_with_gemini → _generate_prompts_with_llm - Rename _build_gemini_prompt → _build_image_prompt - Rename _parse_gemini_response → _parse_llm_response - Remove all Gemini references from LinkedIn code (0 remaining) - Update docstrings and log messages Additional: - Research caching using existing ResearchCache - Shared ExaContentResearchProvider in services/research/ - Persona service uses llm_text_gen instead of gemini_structured_json_response - LinkedInWriter.tsx ChatMessage → ChatMsg type mapping fix - RegisterLinkedInActionsEnhanced.tsx content_format_rules typing fix
21 lines
600 B
Python
21 lines
600 B
Python
"""
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LinkedIn Image Generation Package
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This package provides AI-powered image generation capabilities for LinkedIn content
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using the common llm_providers infrastructure. It includes image generation, storage,
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and management services optimized for professional business use.
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"""
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from .linkedin_image_generator import LinkedInImageGenerator
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from .linkedin_image_storage import LinkedInImageStorage
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__all__ = [
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'LinkedInImageGenerator',
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'LinkedInImageStorage'
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]
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# Version information
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__version__ = "1.0.0"
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__author__ = "Alwrity Team"
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__description__ = "LinkedIn AI Image Generation Services"
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