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This application requires the following model to be deployed on your inference endpoint:
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-**Qwen/Qwen3-4B-Instruct-2507** - Small language model optimized for Intel Xeon processors with 8K context window
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All nine AI agents (Code Explorer, API Reference, Call Graph, Error Analysis, Environment Config, Dependency Analyzer, Planner, Mermaid Generator, and QA Validator) use this model for efficient documentation generation.
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**Note:** This model must be available through your GenAI Gateway or APISIX Gateway deployment before running the application.
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### Required API Configuration
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**For Inference Service (Documentation Generation):**
-**INFERENCE_API_ENDPOINT**: URL to your inference service (example: `https://api.example.com`)
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-**INFERENCE_API_TOKEN**: Authentication token/API key for your chosen service
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**Note:** All nine AI agents (Code Explorer, API Reference, Call Graph, Error Analysis, Env Config, Dependency Analyzer, Planner, Mermaid Generator, QA Validator) plus PR Agent use Qwen/Qwen3-4B-Instruct-2507 optimized for Intel Xeon processors
**Note:** All nine AI agents (Code Explorer, API Reference, Call Graph, Error Analysis, Env Config, Dependency Analyzer, Planner, Mermaid Generator, QA Validator) plus PR Agent use Qwen/Qwen3-4B-Instruct-2507 optimized for Intel Xeon processors
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**Important Configuration Notes:**
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-**INFERENCE_API_ENDPOINT**: Your actual inference service URL (replace `https://api.example.com`)
@@ -562,15 +586,7 @@ For detailed troubleshooting guidance and solutions to common issues, refer to:
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## Additional Info
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### Model Compatibility
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| Model Name | Deployment Platform | Notes |
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|------------|---------------------|-------|
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| Qwen/Qwen3-4B-Instruct-2507 | Xeon | Optimized SLM with 8K context window for efficient documentation generation across all nine micro-agents. |
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### Performance Metrics
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## Performance Metrics
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The system tracks comprehensive performance metrics for each agent execution, providing visibility into token usage, processing speed, and resource consumption. Metrics are calculated and displayed in real-time during workflow execution:
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