Dota 2 AI Coach
An intelligent AI assistant for Dota 2 that analyzes game situations in real-time and provides tactical advice through an overlay. The system uses RAG (Retrieval-Augmented Generation) for more relevant and well-grounded responses.
Features
- 🎮 Dota 2 Integration via GSI (Game State Integration)
- 🤖 AI Provider Support: Google Gemini and OpenRouter
- 🔍 RAG System: Searches relevant information from knowledge base before generating responses
- 💬 Automatic Advice every N seconds
- ❓ Interactive Questions directly in-game
- ⌨️ Hotkey Management
- 📚 Built-in Knowledge Base with information about heroes, abilities, items
Requirements
- Go 1.24.0+
- Windows (uses WinAPI)
- Dota 2
- API key from Gemini or OpenRouter
Installation
# Clone the repository
git clone https://github.com/BrightGir/game-ai-helper.git
cd GameHelper
# Download dependencies
go mod tidyConfiguration
1. API Key
Create a .env file in the project root directory:
API_KEY=your_api_key_here
MODELS_DIR=storage (or folder where the BERT model will be located)Where to get an API key:
- Gemini: https://makersuite.google.com/app/apikey
- OpenRouter: https://openrouter.ai/keys (paid models, some free options available)
💡 Tip: For best results, use advanced models. Free models work well for basic advice.
2. Dota 2 GSI Configuration
Before using the application, you need to configure Dota 2 to send game data to GameHelper:
- Locate your Dota 2 GSI config folder:
C:\Program Files (x86)\Steam\steamapps\common\dota 2 beta\game\dota\cfg\gamestate_integration\
💡 Tip: If the
gamestate_integrationfolder doesn't exist, create it manually.
-
Create a new file in this folder named:
gamestate_integration_aicoach.cfg -
Copy and paste the following content into the file:
"Dota 2 Integration Configuration" { "uri" "http://localhost:6000" "timeout" "5.0" "buffer" "0.1" "throttle" "0.1" "heartbeat" "30.0" "data" { "provider" "1" "map" "1" "player" "1" "hero" "1" "abilities" "1" "items" "1" } } -
Save the file and restart Dota 2 if it's already running.
3. Application Settings
Edit config.json:
{
"local_gsi_port": 6000,
"provider": "openrouter",
"model": "openai/gpt-4o-mini",
"request_interval_seconds": 60,
"silence_duration_seconds": 60,
"hotkey_turn_overlay": 120,
"hotkey_focus_overlay": 121,
"minSimilarity": 0.7
}Parameters:
local_gsi_port— port for GSI server (default 6000)provider—"gemini"or"openrouter"model— AI model:- Gemini:
gemini-2.5-flash,gemini-2.5-pro - OpenRouter:
google/gemma-3-27b-it:free,meta-llama/llama-3.2-3b-instruct:free,openai/gpt-4o-mini
- Gemini:
request_interval_seconds— automatic advice interval (seconds)silence_duration_seconds— pause after question before auto-advice (seconds)hotkey_turn_overlay— toggle overlay key (120=F9)hotkey_focus_overlay— focus key (121=F10)minSimilarity— minimum similarity threshold for RAG search (default 0.7)
⚠️ Important: Advice quality depends on the model. Advanced models provide significantly better results.
Usage 🎮
First Launch
Development mode:
go run ./cmd/game-helperOr build and run:
# Build
go build -o GameHelper.exe ./cmd/game-helper
# Run
./GameHelper.exeWhat happens on first run:
- BERT models for embedding are downloaded (may take a few minutes)
- Knowledge base is indexed in Chroma DB.
- You will see overlay
- Subsequent runs will be faster (uses cache)
Keep the console window open — closing it will stop the application.
Starting Dota 2
- Launch Dota 2 in Windowed Mode (Settings → Video → Display Mode → Borderless Window)
⚠️ IMPORTANT: Dota 2 must be running in Windowed Mode (not Fullscreen) for the overlay to work correctly.
Using the Overlay
The overlay consists of three main areas:
- AI Advice Panel — Shows automatic tactical advice and AI responses
- Question Input Field — Type your questions here
- Context Input Field — Add additional game context/notes
Hotkeys Reference
| Key | Action | Description |
|---|---|---|
F9 |
Toggle Overlay | Show or hide the entire overlay |
F10 |
Focus Overlay | Enable/disable text input mode (allows typing) |
Enter |
Submit | Send your question or save context |
How to Ask Questions
- Press
F10to focus the overlay (you'll see the input fields become active) - Click on the Question Input Field
- Type your question, for example:
- "What items should I buy next?"
- "How do I counter this hero?"
- "What's the best strategy for this situation?"
- Press
Enterto send the question - The AI will process your question and display the answer in the AI Advice Panel
Adding Game Context
You can provide additional context to help the AI give better advice:
- Press
F10to focus the overlay - Click on the Context Input Field (bottom section)
- Type relevant information, for example:
- "Enemy team has strong magic damage"
- "I'm playing as support"
- This context will be included in all future AI requests
Automatic Advice
The application automatically provides tactical advice every N seconds (configured in config.json as request_interval_seconds, default: 60 seconds).
- Advice appears automatically in the AI Advice Panel
- The system analyzes your current game state (hero, items, abilities, gold, etc.)
- Advice pauses for N seconds after you ask a manual question (configured as
silence_duration_seconds)
Architecture
┌─────────────────────────────────────────────────────┐
│ Dota 2 Game Client │
│ (Sends Game State) │
└────────────────┬────────────────────────────────────┘
│ HTTP POST (JSON)
▼
┌────────────────────────────┐
│ GSI Handler │
│ (transport/http_gsi.go) │
│ localhost:6000 │
└────────┬───────────────────┘
│
▼
┌────────────────────────────┐
│ Parser │
│ (dota/parser.go) │
│ JSON → GameState │
└────────┬───────────────────┘
│
▼
┌────────────────────────────┐
│ Store (Thread-safe) │
│ (state/store.go) │
│ RWMutex + GameState │
└────────┬───────────────────┘
│
│ Reads state
▼
┌──────────────────────┐ ┌───────────────────┐
│ Prompt Handler │ │ Overlay (UI) │
│ (prompt.go) │◄─────────────│ (ui/*.go) │
│ │ userPromptChan │
│ • Timer (auto) │ │ • RayLib window │
│ • User questions │ │ • Hotkeys │
└──────────┬───────────┘ │ • Text input │
│ │ • GetContextText()│
│ Calls Build() │ (user notes) │
▼ └─────────┬─────────┘
┌──────────────────────────────────────┐ │
│ Builder (prompt/builder.go) │◄───────┘
│ │ ContextProvider
│ 1. store.Get() → GameState │ (user notes)
│ 2. ctxProvider.GetContextText() │
│ 3. Formats: hero, items, │
│ abilities, user notes │
│ 4. pipeline.Execute() │
└──────────┬───────────────────────────┘
│ gameContext + question
▼
┌──────────────────────────────────────────────────────┐
│ Pipeline (prompt/pipeline.go) [RAG SYSTEM] │
│ │
│ ┌─────────────────────────────────────────────┐ │
│ │ 1. generateSearchQueries() │ │
│ │ AI request → JSON with search queries │────►├──► AI Client
│ └─────────────────────────────────────────────┘ │ (Gemini/OpenRouter)
│ │ │
│ ▼ │
│ ┌─────────────────────────────────────────────┐ │
│ │ 2. retrieveKnowledge() │ │
│ │ Search in vector DB │────►├──► Retriever
│ └─────────────────────────────────────────────┘ │ (BERT + Chroma)
│ │ │
│ ▼ │
│ ┌─────────────────────────────────────────────┐ │
│ │ 3. buildFinalPrompt() │ │
│ │ knowledge + gameState + question │ │
│ └─────────────────────────────────────────────┘ │
└──────────────────────────┬───────────────────────────┘
│ finalPrompt (string)
▼
┌─────────────────────────┐
│ promptChan │
└────────────┬────────────┘
│
▼
┌──────────────────────────────────────────────────────┐
│ AI Worker (ai_worker.go) │
│ │
│ fetchAdviceWithRetry(): │
│ • aiProvider.Ask(systemPrompt, finalPrompt) ──────►├──► AI Client
│ • Retry logic (3 attempts) │ (Gemini/OpenRouter)
│ • Error handling │
└──────────────────────────┬───────────────────────────┘
│ advice (AI response)
▼
┌─────────────────────────┐
│ adviceChan │
└────────────┬────────────┘
│
▼
┌──────────────────────────────────────────────────────┐
│ Advice Consumer (ai_worker.go) │
│ │
│ overlay.SetAiAdvice(advice) │
└──────────────────────────┬───────────────────────────┘
│
▼
┌─────────────────────────┐
│ Overlay displays │
│ advice to user │
└─────────────────────────┘Project Structure
GameHelper/
├── cmd/
│ ├── game-helper/ # Main application
│ │ ├── main.go # Entry point, initialization
│ │ ├── app.go # App structure, coordinates all components
│ │ ├── ai_worker.go # AI request handler with retry logic
│ │ └── prompt.go # Prompt queue and timer management
│ └── rag/ # RAG system tools
│ ├── base-knowledge-loader/ # Loads JSON knowledge bases and create chunks with LLM
│ ├── knowledge-vectorizer/ # Converts text to vectors and saves to assets/rag/knowledge.json
│ └── prompt-debug/ # Debug tool for running prompt scenarios
├── internal/
│ ├── ai/ # AI provider integration
│ │ ├── gemini/ # Google Gemini API client
│ │ │ ├── client.go # Sends requests to Gemini API
│ │ │ └── types.go # Request/response structures
│ │ ├── openrouter/ # OpenRouter API client
│ │ │ ├── client.go # Sends requests to OpenRouter API
│ │ │ └── types.go # Request/response structures
│ │ ├── factory/ # Factory for creating AI clients
│ │ │ └── factory.go # Selects client based on config
│ │ ├── types.go # Common Client interface
│ │ └── errors/ # API error handling
│ │ └── errors.go # ShouldRetry, APIError structures
│ ├── dota/ # Game State Integration (GSI)
│ │ ├── parser.go # Parses JSON from Dota 2
│ │ └── types.go # GameState, Hero, Items, Abilities types
│ ├── prompt/ # AI prompt generation using RAG
│ │ ├── builder.go # Composes context from state + knowledge
│ │ ├── pipeline.go # RAG pipeline: queries → search → prompt
│ │ └── templates.go # Text templates for prompts
│ ├── retriever/ # Knowledge search (RAG component)
│ │ ├── retriever.go # Vector search + similarity filtering
│ │ ├── bert.go # BERT model initialization
│ │ └── types.go # Searcher interface, result types
│ ├── state/ # Thread-safe game state storage
│ │ └── store.go # RWMutex for concurrent access
│ ├── config/ # Configuration management
│ │ └── config.go # Config structure + LoadConfig
│ ├── transport/ # HTTP handler for GSI data
│ │ └── http_gsi.go # Receives POST from Dota 2
│ └── ui/ # Graphical overlay (RayLib)
│ ├── types.go # Overlay structure, UI state
│ ├── engine.go # Main rendering loop
│ ├── draw.go # Text rendering
│ ├── calculator.go # Layout calculations
│ ├── click.go # Windows API for transparency
│ ├── input.go # Input handling
│ └── keyboard.go # Hotkey handling
├── assets/ # Embedded data and templates
│ ├── data/ # Knowledge base in JSON
│ ├── prompts/ # Text templates for prompts
│ │ ├── base-coach-system-prompt.txt
│ │ ├── bd-queries-generator.txt
│ │ ├── final-prompt.txt
│ │ └── *.txt
│ ├── rag/
│ │ └── knowledge.json # Combined knowledge base
│ └── embed.go # go:embed directives
├── storage/ # Batches cache and models
│ └── cache/ # LLM response cache
│ ├── aghs_desc/
│ ├── heroes/
│ └── items/
├── config.json # Application configuration
├── .env # API key (create this)
├── gamestate_integration_aicoach.cfg # Dota 2 GSI config (example)
├── go.mod
├── go.sum
├── README.md
└── LICENSEAdvanced
RAG Tools
These tools are for developers who want to rebuild or modify the knowledge base.
Loading Knowledge
go run ./cmd/rag/base-knowledge-loaderLoads base knowledge (heroes, items, abilities) from JSON files (dotaconstants, Stratz API) and creates text chunks using LLM.
Vectorization
go run ./cmd/rag/knowledge-vectorizerConverts text knowledge to BERT vectors and stores them in assets/rag/knowledge.json
Prompt Debugging
go run ./cmd/rag/prompt-debugGeneration of final prompts based on data in internal/prompt/testdata
License
This project is distributed under the MIT License.