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LLM OpenAI

Overview

The LLM OpenAI component provides integration with OpenAI and OpenAI-compatible APIs (Azure OpenAI, Ollama, etc.).

Configuration

Setup

{
  "component-llm-openai": {
    "api_key": "sk-xxx...",
    "api_base": "https://api.openai.com/v1",
    "default_model": "gpt-4"
  }
}

For Azure OpenAI

{
  "component-llm-openai": {
    "api_key": "your-azure-key",
    "api_base": "https://your-resource.openai.azure.com",
    "api_type": "azure",
    "api_version": "2024-02-15-preview",
    "deployment_name": "gpt-4"
  }
}

Usage in Flows

Basic Completion

- id: ask_llm
  type: llm
  config:
    model: "gpt-4"
    prompt: "What is the capital of France?"
  next: use_response

With System Prompt

- id: classify
  type: llm
  config:
    model: "gpt-4"
    system_prompt: |
      You are a customer service intent classifier.
      Classify the user's message into one of: greeting, question, complaint, other.
      Respond with JSON: {"intent": "...", "confidence": 0.0-1.0}
    prompt: "{{message}}"
    output_format: json
  next: route_intent

Chat Completion

- id: chat
  type: llm
  config:
    model: "gpt-4"
    messages:
      - role: system
        content: "You are a helpful assistant."
      - role: user
        content: "{{user_message}}"
    temperature: 0.7
    max_tokens: 500

With Function Calling

- id: extract_entities
  type: llm
  config:
    model: "gpt-4"
    prompt: "Extract order information from: {{message}}"
    functions:
      - name: extract_order
        description: "Extract order details"
        parameters:
          type: object
          properties:
            order_id:
              type: string
              description: "The order ID"
            product:
              type: string
              description: "Product name"
          required: ["order_id"]
    function_call: "auto"

Parameters

Parameter	Type	Default	Description
`model`	string	”gpt-4”	Model name
`prompt`	string	-	User prompt
`system_prompt`	string	-	System message
`messages`	array	-	Full message array
`temperature`	float	1.0	Creativity (0-2)
`max_tokens`	int	-	Max response tokens
`output_format`	string	”text"	"text” or “json”
`functions`	array	-	Function definitions
`function_call`	string	”auto”	Function call mode

Response Handling

- id: ask_llm
  type: llm
  config:
    model: "gpt-4"
    prompt: "{{question}}"
  output: llm_response
  next: use_response

- id: use_response
  type: reply
  config:
    message: "{{llm_response}}"

Error Handling

- id: safe_llm_call
  type: llm
  config:
    model: "gpt-4"
    prompt: "{{message}}"
    timeout: 30000
    retry_count: 3
  on_error: handle_error
  next: success

- id: handle_error
  type: reply
  config:
    message: "I'm having trouble processing that. Please try again."

Next Steps