> ## Documentation Index > Fetch the complete documentation index at: https://docs.praison.ai/llms.txt > Use this file to discover all available pages before exploring further. # Router > Smart model selection based on task complexity The `--router` flag enables intelligent model selection, automatically choosing the best model based on task complexity. ## Quick Start ```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} praisonai "Simple question" --router ``` Router Demo Router Selects Optimal Model ## Usage ### Basic Router ```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} praisonai "What is 2+2?" --router ``` **Expected Output:** ``` 🎯 Task complexity: simple 🤖 Selected model: gpt-4o-mini ╭─ Agent Info ─────────────────────────────────────────────────────────────────╮ │ 👤 Agent: DirectAgent │ │ Role: Assistant │ │ 🤖 Model: gpt-4o-mini (auto-selected) │ ╰──────────────────────────────────────────────────────────────────────────────╯ ╭────────────────────────────────── Response ──────────────────────────────────╮ │ 2 + 2 equals 4. │ ╰──────────────────────────────────────────────────────────────────────────────╯ ``` ### Complex Task ```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} praisonai "Analyze the implications of quantum computing on cryptography and provide a detailed technical assessment" --router ``` **Expected Output:** ``` 🎯 Task complexity: complex 🤖 Selected model: gpt-4-turbo ╭─ Agent Info ─────────────────────────────────────────────────────────────────╮ │ 👤 Agent: DirectAgent │ │ Role: Assistant │ │ 🤖 Model: gpt-4-turbo (auto-selected) │ ╰──────────────────────────────────────────────────────────────────────────────╯ ╭────────────────────────────────── Response ──────────────────────────────────╮ │ # Quantum Computing Impact on Cryptography │ │ │ │ ## Executive Summary │ │ Quantum computing poses significant challenges to current cryptographic... │ │ │ │ ## Technical Analysis │ │ ### 1. Vulnerable Algorithms │ │ - RSA: Shor's algorithm can factor large numbers in polynomial time... │ │ [Detailed technical analysis continues...] │ ╰──────────────────────────────────────────────────────────────────────────────╯ ``` ### Specify Provider ```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} # Prefer Anthropic models praisonai "Complex analysis" --router --router-provider anthropic # Prefer OpenAI models praisonai "Simple task" --router --router-provider openai ``` **Expected Output:** ``` 🎯 Task complexity: complex 🏢 Provider preference: anthropic 🤖 Selected model: claude-3-opus-20240229 ╭────────────────────────────────── Response ──────────────────────────────────╮ │ [Response from Claude 3 Opus] │ ╰──────────────────────────────────────────────────────────────────────────────╯ ``` ### Combine with Other Features ```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} # Router with metrics (see cost savings) praisonai "Quick question" --router --metrics # Router with planning praisonai "Complex project" --router --planning # Router with guardrail praisonai "Generate code" --router --guardrail "Follow best practices" ``` ## How It Works ```mermaid theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} flowchart LR A[Prompt] --> B[Complexity Analysis] B --> C{Complexity Level} C -->|Simple| D[Fast/Cheap Model] C -->|Medium| E[Balanced Model] C -->|Complex| F[Powerful Model] D --> G[Execute] E --> G F --> G ``` 1. **Prompt Analysis**: The router analyzes your prompt 2. **Complexity Assessment**: Determines task complexity (simple/medium/complex) 3. **Model Selection**: Chooses appropriate model based on complexity 4. **Execution**: Runs the task with the selected model ## Complexity Levels | Level | Indicators | Model Selection | | ----------- | ------------------------------------------- | --------------------------- | | **Simple** | Short questions, basic math, simple lookups | gpt-4o-mini, claude-3-haiku | | **Medium** | Explanations, summaries, moderate analysis | gpt-4o, claude-3-sonnet | | **Complex** | Deep analysis, code generation, research | gpt-4-turbo, claude-3-opus | ## Model Selection Matrix ### OpenAI Models | Complexity | Model | Cost (per 1M tokens) | | ---------- | ----------- | -------------------- | | Simple | gpt-4o-mini | $0.15 / $0.60 | | Medium | gpt-4o | $2.50 / $10.00 | | Complex | gpt-4-turbo | $10.00 / $30.00 | ### Anthropic Models | Complexity | Model | Cost (per 1M tokens) | | ---------- | --------------- | -------------------- | | Simple | claude-3-haiku | $0.25 / $1.25 | | Medium | claude-3-sonnet | $3.00 / $15.00 | | Complex | claude-3-opus | $15.00 / $75.00 | ## Cost Savings Example Without router (always using gpt-4-turbo): ```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} praisonai "What is Python?" --metrics # Tokens: 150, Cost: $0.0045 ``` With router (auto-selects gpt-4o-mini): ```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} praisonai "What is Python?" --router --metrics # Tokens: 150, Cost: $0.0001 # Savings: 97% ``` **Expected Output:** ``` 🎯 Task complexity: simple 🤖 Selected model: gpt-4o-mini 💰 Estimated savings: 97% vs gpt-4-turbo ╭────────────────────────────────── Response ──────────────────────────────────╮ │ Python is a high-level, interpreted programming language known for its │ │ simple syntax and readability... │ ╰──────────────────────────────────────────────────────────────────────────────╯ 📊 Metrics: ┌─────────────────────┬──────────────┐ │ Metric │ Value │ ├─────────────────────┼──────────────┤ │ Model │ gpt-4o-mini │ │ Total Tokens │ 150 │ │ Estimated Cost │ $0.0001 │ │ vs gpt-4-turbo │ $0.0045 │ │ Savings │ 97% │ └─────────────────────┴──────────────┘ ``` ## Use Cases ### Cost Optimization ```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} # Let router choose the most cost-effective model praisonai "Answer user questions" --router --metrics ``` ### Quality Assurance ```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} # Ensure complex tasks get powerful models praisonai "Write a comprehensive security audit" --router ``` ### Batch Processing ```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} # Process many queries efficiently for query in "${queries[@]}"; do praisonai "$query" --router done ``` ## Complexity Indicators The router considers these factors: * Short prompts (\< 50 words) * Basic questions * Simple calculations * Factual lookups * Yes/no questions * Long prompts (> 200 words) * Technical analysis * Code generation * Multi-step reasoning * Creative writing * Research tasks ## Best Practices Use `--router --metrics` to see the cost savings from automatic model selection. The router adds a small overhead for complexity analysis. For known simple tasks, you may prefer to specify the model directly with `--llm`. Use `--metrics` to track savings Use `--router-provider` for specific needs Use `--llm` to override router selection Router is ideal for varied batch tasks ## Related * [Model Router Feature](/features/model-router) * [Metrics CLI](/docs/cli/metrics) * [Models](/models)