# What is GLChat DeepResearch?

GLChat DeepResearch is an **experience-layer pipeline** that defines **product behavior** for deep research in GLChat.

As an experience-layer pipeline, it is responsible for:

* Interpreting user intent and research requirements
* Applying product-level settings (profiles, configurations)
* Preparing results for presentation in the chat UI
* Handling user experience concerns (progress, citations, formatting)

**What it does NOT do**: Backend execution, infrastructure management, or reasoning design (these are delegated to lower layers).

## Responsibilities

**1. Pre-processing**

* Gathers and prepares context (attachments, conversation history, memory)
* Interprets user intent and research requirements
* Determines if deep research is needed or if normal generation suffices

**2. Profile Selection and Resolution**

Applies the user's selected profile and resolves to the appropriate backend implementation:

| Profile           | Backend               | Characteristics                    |
| ----------------- | --------------------- | ---------------------------------- |
| **Essentials**    | OpenAI Deep Research  | Fast, cost-effective, concise      |
| **Comprehensive** | Parallel AI           | Thorough, expensive, comprehensive |
| **Internal**      | OpenAI + Google Drive | Internal data access               |

**3. Research Execution**

Invokes the appropriate DeepResearcher component (SDK layer) with prepared inputs.

**4. Post-processing**

* Structures research results for chat presentation
* Formats citations and references
* Applies product-level policies before delivery

## Pipeline Flow

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## Related Components

GLChat DeepResearch depends on two other layers in the deep research architecture. This section provides a brief overview; see their respective documentation for details.

### GL SDK DeepResearcher

**GL SDK DeepResearcher** is a library-level SDK abstraction that provides a unified, backend-agnostic interface for executing deep research.

**What it does**:

* Exposes consistent research`()` interface across all providers
* Handles streaming, events, and result structuring
* Hides backend differences from pipelines

**Implementations used by GLChat DeepResearch**:

* `OpenAIDeepResearcher` — For Essentials and Internal profiles
* `ParallelDeepResearcher` — For Comprehensive profile

**📚 For more details**: [GL SDK DeepResearcher Documentation](https://gdplabs.gitbook.io/sdk/tutorials/generation/deep-researcher)
