# LangGraph with Conditional Routing
# Demonstrates conditional flow based on message content

agents:
  classifier:
    type: llm
    config:
      provider: openai
      model: gpt-3.5-turbo
      temperature: 0.1
      system_prompt: |
        Classify the input as either:
        - "question" if it's asking something
        - "command" if it's requesting an action
        - "statement" if it's providing information
        Reply with only one word: question, command, or statement.

  qa_agent:
    type: llm
    config:
      provider: openai
      model: gpt-4
      temperature: 0.7
      system_prompt: "Answer questions accurately and thoroughly."

  command_processor:
    type: tool
    config:
      tools: ["echo", "math"]
      safe_mode: true

  acknowledger:
    type: llm
    config:
      provider: openai
      model: gpt-3.5-turbo
      temperature: 0.5
      system_prompt: "Acknowledge statements and provide relevant comments."

# NEW: Unified routes section
routes:
  conditional_flow:
    type: graph  # REQUIRED: Must specify type
    entry_point: start
    
    nodes:
      # Classify the input
      classify:
        type: agent
        agent: classifier
      
      # Route based on classification
      router:
        type: conditional
        condition:
          type: always  # The actual routing happens via edges
      
      # Process question
      handle_question:
        type: agent
        agent: qa_agent
      
      # Process command
      handle_command:
        type: agent
        agent: command_processor
      
      # Process statement
      handle_statement:
        type: agent
        agent: acknowledger
      
    edges:
      # Initial flow
      - source: start
        target: classify
      
      - source: classify
        target: router
      
      # Conditional routing based on classification
      - source: router
        target: handle_question
        condition:
          type: content_contains
          text: "question"
      
      - source: router
        target: handle_command
        condition:
          type: content_contains
          text: "command"
      
      - source: router
        target: handle_statement
        condition:
          type: content_contains
          text: "statement"
      
      # All paths lead to end
      - source: handle_question
        target: end
      
      - source: handle_command
        target: end
      
      - source: handle_statement
        target: end

  # Simple stream setup
  input_handler:
    type: stream  # REQUIRED: Must specify type
    stream_type: cold
    operators:
      - type: graph_execute
        params:
          graph: conditional_flow
    publications:
      - __output__

merges:
  - sources: [__input__]
    target: input_handler

context:
  global:
    app_name: "Conditional LangGraph Router"