Configure Providers
AQBot connects to any number of AI providers simultaneously. Each provider has its own API keys, model list, and parameter defaults.
Supported Providers
AQBot includes first-class support for the following providers. Any service that exposes an OpenAI-compatible API also works out of the box.
| Provider | Example Models |
|---|---|
| OpenAI | GPT-4o, GPT-4, o3, o4-mini |
| Anthropic | Claude 4 Sonnet, Claude 4 Opus, Claude 3.5 Sonnet |
| Gemini 2.5 Pro, Gemini 2.5 Flash, Gemini 2.0 | |
| DeepSeek | DeepSeek V3, DeepSeek R1 |
| Alibaba Cloud | Qwen series |
| Zhipu AI | GLM series |
| xAI | Grok series |
| Any OpenAI-compatible API | Ollama, vLLM, LiteLLM, third-party relays, etc. |
Adding a Provider
- Go to Settings → Providers.
- Click the + button at the bottom left.
- Fill in the provider details:
| Field | Description |
|---|---|
| Name | A display name for the sidebar (e.g. OpenAI) |
| Type | Provider type — determines the default base URL and API behavior |
| Icon | Optional icon for visual identification |
| API Key | The secret key from your provider's dashboard |
| Base URL | API endpoint (pre-filled for built-in types, changeable for relays) |
| API Path | Request path — defaults to /v1/chat/completions |
TIP
For third-party relay services, keep the type set to OpenAI (or the matching upstream type) and change the Base URL to the relay's endpoint.
Multi-Key Rotation
AQBot supports multiple API keys per provider for load distribution and rate-limit avoidance.
Adding Keys
In the provider detail panel, click Add Key to add additional API keys. Each key shows its prefix, creation date, and last-used timestamp.
How Rotation Works
AQBot rotates through enabled keys automatically using a round-robin index. When a request completes, the rotation index advances to the next key. If a key is disabled or fails validation, it is skipped.
Validating Keys
Click the validate button next to a key to verify it against the provider's API. The validation result and any error message are recorded for reference.
Model Management
Fetching Models
Click Fetch Models in the provider detail panel to pull the full list of available models from the provider's API. The discovered models are added to your local list automatically.
Adding Models Manually
If a model is not returned by the API (e.g. a fine-tuned model or a new release), you can add it by typing the model ID directly.
Per-Model Parameters
Each model can have its own default parameter overrides. Open the model's settings to configure:
| Parameter | Description |
|---|---|
| Temperature | Controls randomness (0 = deterministic, higher = more creative) |
| Max Tokens | Maximum number of tokens in the response |
| Top P | Nucleus sampling threshold |
| Frequency Penalty | Reduces repetition of token sequences |
| Presence Penalty | Encourages the model to introduce new topics |
Model Capabilities
AQBot tracks capabilities per model — such as Vision, Function Calling, and Reasoning — and displays them as tags. These capabilities affect which features are available during a conversation.
Custom & Local Endpoints
AQBot works with any endpoint that implements the OpenAI chat completions API.
Ollama (Local Models)
- Install and start Ollama.
- In AQBot, create a new provider with type OpenAI.
- Set the Base URL to
http://localhost:11434. - Click Fetch Models to discover the models you have pulled locally.
vLLM / TGI
Point the Base URL to the address of your inference server (e.g. http://localhost:8000) and fetch or add models as usual.
API Relay Services
For relay or aggregator services (e.g. OpenRouter, one-api), set the type to OpenAI, enter the relay's base URL, and provide the relay's API key.
Default Model Settings
Default Assistant Model
Go to Settings → Default Model to choose the provider and model that new conversations use by default. You can always override the model on a per-conversation basis from the model selector.
Topic Naming Model
AQBot can automatically generate a title for each conversation. In the default model settings, you can assign a separate, lightweight model for topic naming to save cost and latency. Configure a custom prompt and context window size for title generation.
Next Steps
- MCP Servers — connect external tools to extend AI capabilities
- API Gateway — expose your providers as a local API server