> ## Documentation Index
> Fetch the complete documentation index at: https://simili.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Architecture

> Deep dive into Simili Bot's modular architecture

# Architecture Overview

Simili Bot uses a modular, pipeline-based architecture designed for flexibility and extensibility. It is built to handle organization-scale issue management while maintaining a small, efficient footprint.

## System Design

Simili Bot acts as a bridge between GitHub events and AI-powered analysis engines. It processes events sequentially through a customizable pipeline of 14 discrete steps.

### High-Level Components

1. **Event Source**: GitHub Actions (Webhook) or the Simili CLI provides the issue/PR context.
2. **Pipeline Engine**: Orchestrates the execution of 14 steps, passing a shared `Context` object forward.
3. **Search Layer**: Flexible backends (GitHub Native Hybrid, Qdrant, or BM25).
4. **Intelligence Layer**: Integration with Google Gemini, OpenAI, and Anthropic Claude.

### The 14-Step Pipeline

The pipeline is composed of distinct modules that handle specific logic:

**1. Initialization**

**Gatekeeper & Command Handler**: Validates the repo and parses `@simili-bot` commands.

**2. Search Preparation**

**VectorDB Prep**: Ensures collections exist if using Qdrant.

**3. Similarity Discovery**

**Similarity Search / GitHub Similarity**: Finds related issues using the chosen backend.

**4. Analysis**

**LLM Router & Duplicate Detector**: Performs deep logic checks on routing and relationship.

**5. Triage**

**Quality Checker & Triage**: Scores the issue and suggests labels.

**6. Action Building**

**Response Builder**: Constructs the final summary comment.

**7. Execution**

**Action Executor**: Posts to GitHub and triggers labels/transfers.

**8. Post-Processing**

**Indexer & Scheduler**: Updates the vector DB and schedules pending background tasks.

***

## Core Technologies

Simili Bot is designed for the modern AI stack.

### Pipeline Engine

A step-based execution model written in Go 1.24. Each step implements a common interface, making the system highly extensible.

### Search Architecture

The bot supports **Hybrid Routing** and **Hybrid Search**:

* **Routing**: Combines static rules with semantic VDB-based logic.
* **Search**: Combines dense vector embeddings (Gemini/OpenAI) with sparse keyword matching (BM25/GitHub Native).

### Integration Layer

High-performance clients for:

* **Google Gemini**: Preferred for high-dimensional embeddings (3072 dims).
* **Qdrant**: Low-latency vector storage and retrieval.
* **GitHub**: REST (v3) and GraphQL APIs for comprehensive management.

***

## Technical Specifications

| Aspect | Technology Stack |
| :- | :- |
| **Language** | Go 1.24 |
| **AI Engine** | Google Gemini (default) or OpenAI |
| **Vector DB** | Qdrant (Optional) |
| **Search API** | GitHub Search API v3 + Hybrid |
| **Agent Logic** | Claude Code Integration |

***

## Next Steps

> [card] [Pipeline Reference](https://simili.mintlify.site/reference/pipeline/steps.md)

> [card] [Search Backends](https://simili.mintlify.site/configuration/search-backends.md)


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