Major updates: LinkedIn auto-posting, timezone fixes, and Docker improvements

Features:
- Add LinkedIn OAuth integration and auto-posting functionality
- Add scheduler service for automated post publishing
- Add metadata field to generated_posts for LinkedIn URLs
- Add privacy policy page for LinkedIn API compliance
- Add company management features and employee accounts
- Add license key system for company registrations

Fixes:
- Fix timezone issues (use UTC consistently across app)
- Fix datetime serialization errors in database operations
- Fix scheduling timezone conversion (local time to UTC)
- Fix import errors (get_database -> db)

Infrastructure:
- Update Docker setup to use port 8001 (avoid conflicts)
- Add SSL support with nginx-proxy and Let's Encrypt
- Add LinkedIn setup documentation
- Add migration scripts for schema updates

Services:
- Add linkedin_service.py for LinkedIn API integration
- Add scheduler_service.py for background job processing
- Add storage_service.py for Supabase Storage
- Add email_service.py improvements
- Add encryption utilities for token storage

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>

src/config.py

@@ -6,7 +6,6 @@ from pathlib import Path
 
 class Settings(BaseSettings):
     """Application settings loaded from environment variables."""
-
     # API Keys
     openai_api_key: str
     perplexity_api_key: str
@@ -15,6 +14,7 @@ class Settings(BaseSettings):
     # Supabase
     supabase_url: str
     supabase_key: str
+    supabase_service_role_key: str = ""  # Required for admin operations like deleting users
 
     # Apify
     apify_actor_id: str = "apimaestro~linkedin-profile-posts"
@@ -46,6 +46,14 @@ class Settings(BaseSettings):
     user_frontend_enabled: bool = True  # Enable user frontend with LinkedIn OAuth
     supabase_redirect_url: str = ""  # OAuth Callback URL (e.g., https://linkedin.onyva.dev/auth/callback)
 
+    # LinkedIn API (Custom OAuth for auto-posting)
+    linkedin_client_id: str = ""
+    linkedin_client_secret: str = ""
+    linkedin_redirect_uri: str = ""  # e.g., https://yourdomain.com/settings/linkedin/callback
+
+    # Token Encryption
+    encryption_key: str = ""  # Generate with: python -c "from cryptography.fernet import Fernet; print(Fernet.generate_key().decode())"
+
     model_config = SettingsConfigDict(
         env_file=".env",
         env_file_encoding="utf-8",
@@ -55,3 +63,18 @@ class Settings(BaseSettings):
 
 # Global settings instance
 settings = Settings()
+
+# API pricing per 1M tokens (input, output)
+API_PRICING = {
+    "gpt-4o": {"input": 2.50, "output": 10.00},
+    "gpt-4o-mini": {"input": 0.15, "output": 0.60},
+    "sonar": {"input": 1.00, "output": 1.00},
+}
+
+
+def estimate_cost(model: str, prompt_tokens: int, completion_tokens: int) -> float:
+    """Estimate cost in USD for an API call."""
+    pricing = API_PRICING.get(model, {"input": 1.00, "output": 1.00})
+    input_cost = (prompt_tokens / 1_000_000) * pricing["input"]
+    output_cost = (completion_tokens / 1_000_000) * pricing["output"]
+    return input_cost + output_cost