# Input & Extraction

- [Doc Extractor](https://docs.glik.ai/system-architecture/blocks-and-nodes/input-and-extraction/doc-extractor.md)
- [Knowledge Retrieval](https://docs.glik.ai/system-architecture/blocks-and-nodes/input-and-extraction/knowledge-retrieval.md)
- [LLM Block](https://docs.glik.ai/system-architecture/blocks-and-nodes/input-and-extraction/llm-block.md)
- [LLM Reasoning](https://docs.glik.ai/system-architecture/blocks-and-nodes/input-and-extraction/llm-block/llm-reasoning.md): Enables adaptive decision-making, reduces manual review, and adds explainability to enterprise workflows.
- [Fallback to LLM Reasoning](https://docs.glik.ai/system-architecture/blocks-and-nodes/input-and-extraction/llm-block/fallback-to-llm-reasoning.md): Fallback to LLM Reasoning provides resilience and human-like adaptability in GLIK workflows. It ensures continuity, captures contextual judgment, and keeps workflows flexible when predefined logic is
- [Tool Node](https://docs.glik.ai/system-architecture/blocks-and-nodes/input-and-extraction/tool-node.md)
- [Agent](https://docs.glik.ai/system-architecture/blocks-and-nodes/input-and-extraction/agent.md)
- [Answer](https://docs.glik.ai/system-architecture/blocks-and-nodes/input-and-extraction/answer.md)


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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.glik.ai/system-architecture/blocks-and-nodes/input-and-extraction.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.