Research component integration, Copilotkit implementation, SEO copilotkit implementation, Wix SEO metadata complete, Wix SEO metadata review
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ajaysi
@@ -44,15 +44,17 @@ def validate_research_operations(
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llm_provider_name = "gemini"
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# Estimate tokens for each operation in research workflow
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# Google Grounding call: ~2000 tokens (input + output)
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# Google Grounding call: ~1200 tokens (input: ~500 tokens, output: ~700 tokens for research results)
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# Keyword analyzer: ~1000 tokens (input: 3000 chars research, output: structured JSON)
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# Competitor analyzer: ~1000 tokens (input: 3000 chars research, output: structured JSON)
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# Content angle generator: ~1000 tokens (input: 3000 chars research, output: list of angles)
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# Note: These are conservative estimates. Actual usage may be lower, but we use these for pre-flight validation
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# to prevent wasteful API calls if the workflow would exceed limits.
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operations_to_validate = [
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{
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'provider': APIProvider.GEMINI, # Google Grounding uses Gemini
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'tokens_requested': 2000,
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'tokens_requested': 1200, # Reduced from 2000 to more realistic estimate
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'actual_provider_name': 'gemini',
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'operation_type': 'google_grounding'
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},
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@@ -126,6 +128,120 @@ def validate_research_operations(
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)
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def validate_exa_research_operations(
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pricing_service: PricingService,
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user_id: str,
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gpt_provider: str = "google"
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) -> None:
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"""
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Validate all operations for an Exa research workflow before making ANY API calls.
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This prevents wasteful external API calls (like Exa search) if subsequent
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LLM calls would fail due to token or call limits.
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Args:
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pricing_service: PricingService instance
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user_id: User ID for subscription checking
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gpt_provider: GPT provider from env var (defaults to "google")
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Returns:
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None
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If validation fails, raises HTTPException with 429 status
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"""
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try:
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# Determine actual provider for LLM calls based on GPT_PROVIDER env var
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gpt_provider_lower = gpt_provider.lower()
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if gpt_provider_lower == "huggingface":
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llm_provider_enum = APIProvider.MISTRAL # Maps to HuggingFace
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llm_provider_name = "huggingface"
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else:
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llm_provider_enum = APIProvider.GEMINI
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llm_provider_name = "gemini"
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# Estimate tokens for each operation in Exa research workflow
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# Exa Search call: 1 Exa API call (not token-based)
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# Keyword analyzer: ~1000 tokens (input: research results, output: structured JSON)
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# Competitor analyzer: ~1000 tokens (input: research results, output: structured JSON)
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# Content angle generator: ~1000 tokens (input: research results, output: list of angles)
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# Note: These are conservative estimates for pre-flight validation
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operations_to_validate = [
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{
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'provider': APIProvider.EXA, # Exa API call
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'tokens_requested': 0,
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'actual_provider_name': 'exa',
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'operation_type': 'exa_neural_search'
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},
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{
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'provider': llm_provider_enum,
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'tokens_requested': 1000,
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'actual_provider_name': llm_provider_name,
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'operation_type': 'keyword_analysis'
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},
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{
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'provider': llm_provider_enum,
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'tokens_requested': 1000,
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'actual_provider_name': llm_provider_name,
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'operation_type': 'competitor_analysis'
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},
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{
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'provider': llm_provider_enum,
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'tokens_requested': 1000,
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'actual_provider_name': llm_provider_name,
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'operation_type': 'content_angle_generation'
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}
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]
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logger.info(f"[Pre-flight Validator] 🚀 Starting Exa Research Workflow Validation")
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logger.info(f" ├─ User: {user_id}")
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logger.info(f" ├─ LLM Provider: {llm_provider_name} (GPT_PROVIDER={gpt_provider})")
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logger.info(f" └─ Operations to validate: {len(operations_to_validate)}")
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can_proceed, message, error_details = pricing_service.check_comprehensive_limits(
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user_id=user_id,
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operations=operations_to_validate
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)
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if not can_proceed:
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usage_info = error_details.get('usage_info', {}) if error_details else {}
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provider = usage_info.get('provider', llm_provider_name) if usage_info else llm_provider_name
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operation_type = usage_info.get('operation_type', 'unknown')
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logger.error(f"[Pre-flight Validator] ❌ EXA RESEARCH WORKFLOW BLOCKED")
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logger.error(f" ├─ User: {user_id}")
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logger.error(f" ├─ Blocked at: {operation_type}")
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logger.error(f" ├─ Provider: {provider}")
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logger.error(f" └─ Reason: {message}")
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# Raise HTTPException immediately - frontend gets immediate response, no API calls made
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raise HTTPException(
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status_code=429,
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detail={
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'error': message,
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'message': message,
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'provider': provider,
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'usage_info': usage_info if usage_info else error_details
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}
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)
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logger.info(f"[Pre-flight Validator] ✅ EXA RESEARCH WORKFLOW APPROVED")
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logger.info(f" ├─ User: {user_id}")
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logger.info(f" └─ All {len(operations_to_validate)} operations validated - proceeding with API calls")
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# Validation passed - no return needed (function raises HTTPException if validation fails)
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except HTTPException:
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raise
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except Exception as e:
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logger.error(f"[Pre-flight Validator] Error validating Exa research operations: {e}", exc_info=True)
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raise HTTPException(
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status_code=500,
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detail={
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'error': f"Failed to validate operations: {str(e)}",
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'message': f"Failed to validate operations: {str(e)}"
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}
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)
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def validate_image_generation_operations(
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pricing_service: PricingService,
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user_id: str
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