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Copy file name to clipboardExpand all lines: use-cases/adding_reasoning_to_llama_3/cot_tools_config.yaml
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# Custom configuration for tool use Chain of Thought enhancement
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llm:
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# Provider selection: "vllm" or "api-endpoint"
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provider: "vllm"
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vllm:
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api_base: "http://localhost:8000/v1"
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model: "unsloth/Meta-Llama-3.3-70B-Instruct"
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max_retries: 3
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retry_delay: 1.0
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# API endpoint configuration
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api-endpoint:
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api_base: "https://api.llama.com/v1"# Optional base URL for API endpoint (null for default API)
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api_key: "llama_api_key"# API key for API endpoint or compatible service (can use env var instead)
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model: "Llama-4-Maverick-17B-128E-Instruct-FP8"# Default model to use
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max_retries: 3# Number of retries for API calls
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retry_delay: 1.0# Initial delay between retries (seconds)
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sleep_time: 0.5# Small delay in seconds between batches to avoid rate limits
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generation:
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temperature: 0.2# Lower temperature for more consistent reasoning
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top_p: 0.95
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# The most important part - our custom Chain of Thought prompt
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prompts:
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cot_enhancement: |
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You are a highly intelligent AI with an IQ of 170, and your job is to enhance existing conversation examples. Remember to return the entire conversation as is, BUT
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You are a highly intelligent AI with an IQ of 170, and your job is to enhance existing conversation examples. Remember to return the entire conversation as is,
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BUT, we will add Chain of Thought and planning to "Assistant" messages whenever they return a tool call.
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Remember, ONLY when an assistant message returns a tool call will we add thinking and reasoning traces before it to add logic. Otherwise, we don't touch the conversation history.
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Remember to return the entire message, but only enhance the assistant messages whenever a tool is called in the conversation by adding thoughts.
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