# The Kodesage engine

The Kodesage platform is architecturally designed for on-premises deployment, encapsulating its core functionality within Docker containerized environments for enhanced modularity and isolation. The system's logical structure is centered around a virtual machine hosting the Kodesage services, with external integration points to source code repositories, ticketing systems, and documentation.

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Key elements of the solution include an ingestion service to process and analyze the source code, creating a searchable vector database and a comprehensive knowledge graph.&#x20;

This system architecture enables essential services such as semantic code search ("Ask Kodesage"), automated document generation, and issue ticketing integration, powered by a dedicated Large Language Model (LLM). The LLM instances are hosted separately, emphasizing the system's distributed nature, which enhances both the scalability and reliability of the service.

This design facilitates seamless integration, while the on-prem LLM is used to maintain high throughput and low latency. The clear separation of services ensures a maintainable and scalable system.


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.kodesage.ai/welcome-to-kodesage/the-kodesage-engine.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.