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70 lines
2.1 KiB
YAML
70 lines
2.1 KiB
YAML
# yaml-language-server: $schema=https://promptfoo.dev/config-schema.json
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description: OpenAI Realtime API multi-turn conversation demonstration
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prompts:
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- file://realtime-conversation.js
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providers:
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- id: openai:realtime:gpt-realtime-1.5
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config:
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modalities: ['text']
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instructions: 'You are a helpful assistant. Keep your responses concise and informative.'
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# Increase WebSocket timeout to handle potential slow connections
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websocketTimeout: 60000 # 60 seconds
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# Set up the system message for all tests
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defaultTest:
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vars:
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system_message: You are a helpful, friendly AI assistant. Keep your responses conversational and engaging.
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# Test out conversations with multiple turns
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tests:
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# First conversation about travel
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- vars:
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question: What are some popular tourist destinations in Japan?
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metadata:
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conversationId: japan_travel
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assert:
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- type: llm-rubric
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value: Provides information about tourist destinations in Japan
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- vars:
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question: Which of those places is best to visit in autumn?
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metadata:
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conversationId: japan_travel
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assert:
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- type: llm-rubric
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value: Recommends autumn destinations in Japan based on previous conversation
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- vars:
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question: What traditional foods should I try there?
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metadata:
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conversationId: japan_travel
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assert:
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- type: llm-rubric
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value: Suggests traditional Japanese foods relevant to autumn destinations
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# Second conversation about technology (runs independently)
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- vars:
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question: Can you explain how real-time AI systems work?
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metadata:
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conversationId: tech_thread
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assert:
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- type: llm-rubric
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value: Explains real-time AI systems
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- vars:
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question: What are the advantages over traditional API calls?
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metadata:
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conversationId: tech_thread
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assert:
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- type: llm-rubric
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value: Compares real-time APIs to traditional API calls
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- vars:
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question: How is WebSocket technology used in these systems?
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metadata:
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conversationId: tech_thread
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assert:
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- type: llm-rubric
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value: Explains the role of WebSockets in real-time AI
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