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f8c5c5c96e
Privacy and configuration improvements: - Remove Google Analytics tracking from frontend (privacy enhancement) - Remove Anthropic Claude 3 Opus from example LLM configurations - Renumber example config IDs sequentially (-1 through -4) Technical details: - Removed @next/third-parties/google import from layout.tsx - Removed GoogleAnalytics component from HTML root - Removed Claude example from global_llm_config.example.yaml - Production uses three-tier local-first architecture (Mistral NeMo + TildeOpen + Gemini fallback) These changes align with the local-first European AI architecture already deployed at https://ai.kapteinis.lv using Mistral NeMo 12B (France) and TildeOpen 30B (Latvia) with Gemini as emergency fallback only. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
68 lines
2 KiB
YAML
68 lines
2 KiB
YAML
# Global LLM Configuration
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#
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# SETUP INSTRUCTIONS:
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# 1. For production: Copy this file to global_llm_config.yaml and add your real API keys
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# 2. For testing: The system will use this example file automatically if global_llm_config.yaml doesn't exist
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#
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# NOTE: The example API keys below are placeholders and won't work.
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# Replace them with your actual API keys to enable global configurations.
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#
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# These configurations will be available to all users as a convenient option
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# Users can choose to use these global configs or add their own
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global_llm_configs:
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# Example: OpenAI GPT-4 Turbo
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- id: -1
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name: "Global GPT-4 Turbo"
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provider: "OPENAI"
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model_name: "gpt-4-turbo-preview"
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api_key: "sk-your-openai-api-key-here"
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api_base: ""
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language: "English"
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litellm_params:
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temperature: 0.7
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max_tokens: 4000
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# Example: Fast model - GPT-3.5 Turbo
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- id: -2
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name: "Global GPT-3.5 Turbo"
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provider: "OPENAI"
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model_name: "gpt-3.5-turbo"
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api_key: "sk-your-openai-api-key-here"
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api_base: ""
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language: "English"
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litellm_params:
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temperature: 0.5
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max_tokens: 2000
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# Example: Chinese LLM - DeepSeek
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- id: -3
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name: "Global DeepSeek Chat"
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provider: "DEEPSEEK"
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model_name: "deepseek-chat"
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api_key: "your-deepseek-api-key-here"
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api_base: "https://api.deepseek.com/v1"
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language: "Chinese"
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litellm_params:
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temperature: 0.7
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max_tokens: 4000
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# Example: Groq - Fast inference
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- id: -4
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name: "Global Groq Llama 3"
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provider: "GROQ"
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model_name: "llama3-70b-8192"
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api_key: "your-groq-api-key-here"
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api_base: ""
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language: "English"
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litellm_params:
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temperature: 0.7
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max_tokens: 8000
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# Notes:
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# - Use negative IDs to distinguish global configs from user configs
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# - IDs should be unique and sequential (e.g., -1, -2, -3, etc.)
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# - The 'api_key' field will not be exposed to users via API
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# - Users can select these configs for their long_context, fast, or strategic LLM roles
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# - All standard LiteLLM providers are supported
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