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Retellai Create Conversation Flow

Create a new Conversation Flow that can be attached to an agent for response generation. Requires start_speaker, model_choice, and nodes. Returns conversation_flow_id and full configuration.

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Use Retellai Create Conversation Flow

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Inputs

  • mcpsarray
    MCP (Model Context Protocol) server configurations. Enables integration with external MCP-compatible services. Each MCP may include 'name', 'url', 'headers', 'query_params', and 'timeout_ms'.
  • nodesarray
    Required
    Array of conversation flow nodes. Each node must have an 'id' (string), 'type' (string), and type-specific configuration like 'instruction'. Example: [{'id': 'greeting_node', 'type': 'conversation', 'instruction': {'type': 'prompt', 'text': 'Greet the user'}}].
  • toolsarray
    Custom and built-in function definitions available in the conversation flow. Includes custom tools, end call tools, appointment booking tools, etc.
  • kb_configobject
    Knowledge base configuration for retrieval behavior. May include 'top_k' and 'filter_score' parameters.
  • componentsarray
    Reusable sub-flows embedded within the conversation flow. Each component has its own nodes and tools.
  • model_choiceobject
    Required
    Model configuration with model name and type. Example: {'model': 'gpt-4o', 'type': 'cascading'}. Required fields: 'model' (string) and 'type' (string).
  • global_promptstring
    System instructions applied across all nodes in the conversation flow. Used to define overall agent behavior and personality.
  • start_node_idstring
    ID of the node where execution begins. If not specified, the first node in the nodes array is used.
  • start_speakerstring
    Required
    Who initiates the conversation. Either 'user' or 'agent'.
  • is_transfer_llmboolean
    Whether this conversation flow is used for transfer LLM scenarios. Affects how the flow is processed during call transfers.
  • model_temperaturenumber
    Controls the randomness of the model's responses. Valid range: 0-1. Lower values make responses more deterministic. Default: 0.7.
  • knowledge_base_idsarray
    Array of knowledge base IDs for RAG (Retrieval-Augmented Generation). Enables the agent to retrieve information from specified knowledge bases.

Observable output

  • data
    Required
    Data from the action execution
  • errorstring
    Error if any occurred during the execution of the action
  • successfulboolean
    Required
    Whether or not the action execution was successful or not

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