heading_title = Understanding AI Models for Your Business Intelligence

# Introduction
help_intro_title = What is RAG Business Intelligence (RAG BI)?
help_intro_text = RAG BI is your intelligent assistant that helps you analyze your business data using natural language. Instead of writing complex database queries, you can simply ask questions like:
help_intro_example_1 = How many products do we have?
help_intro_example_2 = What are our sales this month?
help_intro_example_3 = Show me the top 10 best-selling products
help_intro_description = The system understands your question, generates the appropriate database query, retrieves the data, and presents it to you in an easy-to-understand format.

# Model Capabilities
help_capabilities_title = Understanding Model Capabilities
help_capabilities_intro = Different AI models have different strengths. Here's what you need to know:

help_analytics_title = Analytics Queries
help_analytics_description = These are questions about your business data that require calculations and analysis. <strong>All models support this.</strong>
help_analytics_examples_title = Examples:
help_analytics_example_1 = Product counts and inventory
help_analytics_example_2 = Sales revenue and trends
help_analytics_example_3 = Customer statistics
help_analytics_example_4 = Order analysis

help_semantic_title = Semantic Search
help_semantic_description = These are questions about policies, procedures, or information stored in your documents. <strong>Only some models support this.</strong>
help_semantic_examples_title = Examples:
help_semantic_example_1 = Return policies
help_semantic_example_2 = Shipping information
help_semantic_example_3 = Product descriptions
help_semantic_example_4 = Company procedures

# Model Comparison
help_comparison_title = Available AI Models - Comparison Guide
help_comparison_intro = Choose the right model for your needs. All models have been tested and work reliably. Please note that models can evolve and impact results. Gpt-4 and Gpt4.1 are well-suited for this type of analysis.

help_table_model = Model
help_table_best_for = Best For
help_table_analytics = Analytics
help_table_semantic = Semantic Search
help_table_speed = Speed
help_table_cost = Cost
help_table_recommendation = Recommendation

# Models
help_model_gpt4o_name = GPT-4o
help_model_gpt4o_best = Complete solution, all features
help_model_gpt4o_speed = Good
help_model_gpt4o_cost = Medium
help_model_gpt4o_recommendation = ⭐ Primary Choice

help_model_gpt41mini_name = GPT-4.1-mini
help_model_gpt41mini_best = Best balance of speed and features
help_model_gpt41mini_speed = Fastest
help_model_gpt41mini_cost = Low
help_model_gpt41mini_recommendation = ⭐ Best Value

help_model_gpt4omini_name = GPT-4o-mini
help_model_gpt4omini_best = High-volume, cost-effective
help_model_gpt4omini_speed = Very Fast
help_model_gpt4omini_cost = Very Low
help_model_gpt4omini_recommendation = Cost-Effective

help_model_phi4_name = Microsoft Phi-4
help_model_phi4_best = Privacy, offline use, local deployment
help_model_phi4_speed = Fast
help_model_phi4_cost = Free
help_model_phi4_recommendation = ⭐ Local/Privacy

help_model_mistral_name = Mistral Large
help_model_mistral_best = Alternative provider, vendor diversity
help_model_mistral_speed = Good
help_model_mistral_cost = Medium
help_model_mistral_recommendation = Alternative

help_badge_yes = ✓ Yes
help_badge_no = ✗ No

# Use Cases
help_usecases_title = Which Model Should I Use?

help_usecase_business_title = For Most Businesses (Recommended)
help_usecase_business_model = GPT-4.1-mini
help_usecase_business_why = Why?
help_usecase_business_reason_1 = Fastest response times (5.3 seconds average)
help_usecase_business_reason_2 = Supports both analytics and semantic search
help_usecase_business_reason_3 = Most cost-effective for full features
help_usecase_business_reason_4 = 100% success rate in testing
help_usecase_business_reason_5 = Latest stable technology
help_usecase_business_perfect = Perfect for: Daily business intelligence, customer inquiries, sales analysis

help_usecase_volume_title = For High-Volume Operations
help_usecase_volume_model = GPT-4o-mini
help_usecase_volume_why = Why?
help_usecase_volume_reason_1 = Lowest cost per query
help_usecase_volume_reason_2 = Very fast response times (5.4 seconds)
help_usecase_volume_reason_3 = Supports all features
help_usecase_volume_reason_4 = Ideal for processing thousands of queries
help_usecase_volume_perfect = Perfect for: Large e-commerce sites, automated reporting, high-traffic applications

help_usecase_privacy_title = For Privacy & Data Security
help_usecase_privacy_model = Microsoft Phi-4
help_usecase_privacy_why = Why?
help_usecase_privacy_reason_1 = Runs locally on your server (no data sent to cloud)
help_usecase_privacy_reason_2 = Complete data privacy and control
help_usecase_privacy_reason_3 = No per-query costs
help_usecase_privacy_reason_4 = Fast response times (5.6 seconds)
help_usecase_privacy_reason_5 = 100% success rate for analytics
help_usecase_privacy_note = Note: Does not support semantic search (document/policy questions)
help_usecase_privacy_perfect = Perfect for: Healthcare, finance, government, or any business with strict data privacy requirements

help_usecase_maximum_title = For Maximum Capabilities
help_usecase_maximum_model = GPT-4o
help_usecase_maximum_why = Why?
help_usecase_maximum_reason_1 = Reference implementation - most tested
help_usecase_maximum_reason_2 = Handles complex queries excellently
help_usecase_maximum_reason_3 = Supports all features
help_usecase_maximum_reason_4 = 100% success rate
help_usecase_maximum_reason_5 = Best for complex business logic
help_usecase_maximum_perfect = Perfect for: Complex analytics, multi-step reasoning, critical business decisions

help_usecase_diversity_title = For Vendor Diversity
help_usecase_diversity_model = Mistral Large
help_usecase_diversity_why = Why?
help_usecase_diversity_reason_1 = Alternative to OpenAI (reduces vendor lock-in)
help_usecase_diversity_reason_2 = European-based provider
help_usecase_diversity_reason_3 = Supports all features
help_usecase_diversity_reason_4 = Good performance (6.0 seconds)
help_usecase_diversity_reason_5 = 100% success rate
help_usecase_diversity_perfect = Perfect for: Organizations wanting multiple AI providers, European data residency requirements

# Example Queries
help_examples_title = Example Queries You Can Ask

help_examples_analytics_title = Analytics Queries (All Models)
help_examples_analytics_1 = How many products do we have?
help_examples_analytics_2 = What's our revenue this month?
help_examples_analytics_3 = Show me the top 10 best-selling products
help_examples_analytics_4 = How many orders did we receive today?
help_examples_analytics_5 = What's the stock level for iPhone 17 Pro?
help_examples_analytics_6 = Give me the SKU for product X
help_examples_analytics_7 = How many new customers this month?
help_examples_analytics_8 = What's our average order value?

help_examples_semantic_title = Semantic Queries (GPT-4o, GPT-4.1-mini, GPT-4o-mini, Mistral)
help_examples_semantic_1 = What is our return policy?
help_examples_semantic_2 = How do I ship internationally?
help_examples_semantic_3 = What are the warranty terms?
help_examples_semantic_4 = Tell me about product X features
help_examples_semantic_5 = What payment methods do we accept?
help_examples_semantic_6 = How do I process a refund?
help_examples_semantic_note = <strong>Note:</strong> Microsoft Phi-4 does not support semantic queries

# Performance
help_performance_title = Performance & Reliability
help_performance_intro = All models have been rigorously tested and have achieved a good level of performance, but they may still contain errors—particularly depending on how you phrase your question. Below are the results of our tests.

help_performance_table_model = Model
help_performance_table_time = Average Response Time
help_performance_table_success = Success Rate
help_performance_table_queries = Queries Tested

help_performance_gpt41mini = 5.3 seconds
help_performance_gpt4omini = 5.4 seconds
help_performance_phi4 = 5.6 seconds
help_performance_mistral = 6.0 seconds
help_performance_gpt4o = 6.5 seconds
help_performance_success = 100%
help_performance_queries = 5/5

help_performance_note = Testing conducted December 2025 with 5 representative business intelligence queries per model.

# Quick Decision Guide
help_decision_title = Quick Decision Guide
help_decision_subtitle = Choose Your Model in 3 Questions:

help_decision_q1 = Do you need semantic search (policy/document questions)?
help_decision_q1_yes = Yes → Choose GPT-4.1-mini, GPT-4o-mini, GPT-4o, or Mistral Large
help_decision_q1_no = No → Microsoft Phi-4 is also an option

help_decision_q2 = Is data privacy critical (healthcare, finance)?
help_decision_q2_yes = Yes → Choose Microsoft Phi-4 (local deployment)
help_decision_q2_no = No → Continue to question 3

help_decision_q3 = What's your priority?
help_decision_q3_value = Best value → GPT-4.1-mini
help_decision_q3_cost = Lowest cost → GPT-4o-mini
help_decision_q3_capability = Maximum capability → GPT-4o
help_decision_q3_diversity = Vendor diversity → Mistral Large

# Technical Information
help_technical_title = Technical Information

help_embeddings_title = About Embeddings & Semantic Search
help_embeddings_text = When we say a model "supports embeddings," it means the model can work with semantic search features. The system uses a separate embedding model (text-embedding-3-large) to convert your documents into searchable vectors, then the chat model uses these to find relevant information.
help_embeddings_with = <strong>Models with embedding support:</strong> GPT-4o, GPT-4.1-mini, GPT-4o-mini, Mistral Large
help_embeddings_without = <strong>Models without embedding support:</strong> Microsoft Phi-4 (analytics only)

help_notes_title = Important Notes
help_notes_1 = All models require proper configuration in the ChatGPT settings
help_notes_2 = Microsoft Phi-4 requires LM Studio to be running locally
help_notes_3 = Response times may vary based on query complexity and server load
help_notes_4 = All models have been tested and validated for production use

# Footer
help_footer_validated = All models tested and validated December 2025
help_footer_support = For technical support or questions, please contact your system administrator.
